• KSII Transactions on Internet and Information Systems (TIIS)
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• v.17 no.6
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• pp.1728-1742
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• 2023

In this paper, we extended a hierarchical clustering technique, which is the most researched in the sensor network field, and studied a dynamic differential clustering technique to minimize energy consumption and ensure equal lifespan of all sensor nodes while considering the mobility of sinks. In a sensor network environment with mobile sinks, clusters close to the sinks tend to consume more forwarding energy. Therefore, clustering that considers forwarding energy consumption is desired. Since all clusters form a hierarchical tree, the number of levels of the tree must be considered based on the size of the cluster so that the cluster size is not growing abnormally, and the energy consumption is not concentrated within specific clusters. To verify that the proposed DDC protocol satisfies these requirements, a simulation using Matlab was performed. The FND (First Node Dead), LND (Last Node Dead), and residual energy characteristics of the proposed DDC protocol were compared with the popular clustering protocols such as LEACH and EEUC. As a result, it was shown that FND appears the latest and the point at which the dead node count increases is delayed in the DDC protocol. The proposed DDC protocol presents 66.3% improvement in FND and 13.8% improvement in LND compared to LEACH protocol. Furthermore, FND improved 79.9%, but LND declined 33.2% when compared to the EEUC. This verifies that the proposed DDC protocol can last for longer time with more number of surviving nodes.

• Transactions of the Korean Society of Mechanical Engineers B
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• v.35 no.1
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• pp.1-8
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• 2011

An analytical study on the flow resistance of tree-shaped channel-flow architectures was carried out based on the principle of the constructal law; the evolutionary increase in the access to currents that flow through the channels with improvements in the flow configurations were studied in a square domain using two diameters. Two types of tree-shaped configurations were optimized. The minimized global flow resistance decreased steadily as the system size $N^2$ increased. From the two channel configurations, the one that resulted in better pressure drop was selected. Further, it was shown that the system performance can be enhanced by adopting the second tree-shaped configurations when the system size is greater than $18^2$.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.29 no.3B
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• pp.339-348
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• 2004

Packet classification is an important factor to support various services such as QoS guarantee and VPN for users in Internet. Packet classification is a searching process for best matching rule on rule tables by employing multi-field such as source address, protocol, and port number as well as destination address in If header. In this paper, we propose hardware based packet classification algorithm by employing tree bitmap of multi-bit trio. We divided prefixes of searching fields and rule into multi-bit stride, and perform a rule searching with multi-bit of fixed size. The proposed scheme can reduce the access times taking for rule search by employing indexing key in a fixed size of upper bits of rule prefixes. We also employ a marker prefixes in order to remove backtracking during searching a rule. In this paper, we generate two dimensional random rule set of source address and destination address using routing tables provided by IPMA Project, and compare its memory usages and performance.

• Journal of Broadcast Engineering
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• v.19 no.3
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• pp.405-414
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• 2014

High Efficiency Video Coding(HEVC) obtains high compression ratio by applying recursive quad-tree structured coding unit(CU). However, this recursive quad-tree structure brings very high computational complexity to HEVC encoder. In this paper, we present fast CU decision algorithm in recursive quad-tree structure. The proposed algorithm estimates initial CU size before CTU encoding and checks the proposed condition using Coded Block Flag(CBF) and Rate-distortion cost to achieve the fast encoding time saving. And, intra mode estimation is also possible to be skipped using the CBF values acquired during the inter PU mode estimations. Experiment results shows that the proposed algorithm saved about 49.91% and 37.97% of encoding time according to the weighting condition.

• Applied Biological Chemistry
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• v.41 no.2
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• pp.141-146
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• 1998

In order to determine the optimmum harvest time of Citrus unshiu Marc. var. miyagawa and C. unshiu Marc. var. okitsu produced in Cheju, citrus fruits sampled at packing houses or harvested directly on citrus tree in south and north area of Cheju were analyzed. The fruits were grown in size till middle of October, and soluble solids were increased continuously after that. The fruits size were different by positional directions on the tree, the quality of citrus fruits in central southern positions on the tree was good for fresh fruit consumptions. Compared with only the quality of citrus fruits as a factor of soluble solids, total sugar, pH, and color index, the optimum harvest time were supposed to be reasonable at late of November for C. unshiu Marc. var. okitsu, and at early of December for C. unshiu Marc. var. miyagawa. The results obtained from citrus fruits sampled at packing houses were supposed to be not suitable for determing the optimum harvest time, because of storage after harvest at ordinary harvesting time.

• Journal of KIISE:Databases
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• v.31 no.2
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• pp.91-98
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• 2004

DHP mining association rules algorithm maintains previously independent direct hash table to reduce the sire of hash tree containing the frequency number of each candidate large itemset. It performs pruning by using the direct hash table when the hash tree is constructed. The mort large the size of direct hash table increases, the higher the effort of pruning becomes. Especially, the effect of pruning in phase 2 which generate 2-large itemsets is so high that it dominates the overall performance of DHP algorithm. So, following the speedy trends of producing VLM(Very Large Memory) systems, extreme increment of direct hash table size is being tried and one of those trials is perfect hash table in phase 2. In case of using perfect hash table in phase 2, we found that some rearrangement of DHP algorithm got about 20% performance improvement compared to simply ｜H$_2$｜ reconfigured DHP algorithm. In this paper, we examine the feasibility of perfect hash table in phase 2 and propose PHP algorithm, a rearranged DHP algorithm, which uses the characteristics of perfect hash table sufficiently, then make an analysis on the results in experimental environment.

• Journal of Forest and Environmental Science
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• v.25 no.3
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• pp.167-175
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• 2009

An exploratory study was conducted in Juri Forest Range-2, a proposed biodiversity conservation area of Bangladesh to explore the present growing stock of tree, regeneration condition and status of non-timber forest products (NTFPs). This conservation area contains both natural and artificial plantation was selected by using multistage random sampling method. For determination of plot size and sampling methods, the quadrate size ($10m{\times}10m$) for tree stock measurement, ($2m{\times}2m$) for regeneration survey, ($20m{\times}20m$) for NTFPs survey was determined. Regarding tree stock survey, 14 species under eight families were found where Tectona grandis shows average number of stem/ha was 624 and basal area/ha was (10.36 $m^2/ha$) followed by Acacia auriculiformis (0.2 $m^2/ha$ and 637 stem/ha), Gmelina arborea (0.2 $m^2/ha$ and 600 stem/ha). In regeneration survey, 14 species were found belonging to 9 families where Alstonia scholaris shows highest (3,750) seedling per hectare. Regarding NTFPs, bamboo and cane are the most common resources. In last ten years, the total timber output was 1,28,596.14 cubic feet and total amount of revenue was 4,64,434 US$. The vacant area is 1,335.5 acre which contains 14% of total area. If this vacant area is planted with suitable species and take proper steps for appropriate management of this species it will be a good biologically diversified area.

• Animal cells and systems
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• v.3 no.1
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• pp.29-39
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• 1999

Current data on reproductive characters of endemic and native species are essential to provide a strategy for the conservation of these species. Red pine (Pinus densiflora Sieb. & Zucc.) is one of the dominant, native tree species in Korea, but its reproductive ecology is not well-known. In 1997, the pattern of variation in cone and seed yields contributing to the conservation of declining populations of red pines was examined. Plant height and dbh were measured, and several new cones were collected from each tagged tree after counting the number of cones on each tree. For a subset of cones sampled, the number of fertile scales, the number of seeds at three development stages (early/late aborted, and filled seed), seed wing size, wing color, and individual filled seed mass were measured. The three sites which differed significantly in mean plant size also differed in mean cone and seed production per plant. However further analyses showed that most variation in characters examined occurred among plants within sites, but not among sites. An average of 90% of the potential seeds on the cones aborted at an early developmental stage, demonstrating that early abortion is a major factor affecting the number of filled seeds per cone. Individual seed mass was the only character which exhibited significant variations among sites as well as among trees within sites. Individual seed mass was overall negatively correlated with both the percentage of late abortion and the number of old cones per plant, suggesting that both the past and current years' reproductive activities have caused variations in seed mass. The potential dispersal distance of red pine seeds is quite large. However, wing loading was correlated with seed mass and number in a complex pattern across the sites. Distribution of seeds with varied colored wings differed among sites and among trees within sites. These results suggest that red pines at different sites might possess different strategies to cope with selection pressures acting during the final phase of reproduction, from seed dispersal to establishment. Then the ‘fitted’ red pine trees at each site should be identified and managed to conserve or restore populations.

• Journal of Intelligence and Information Systems
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• v.13 no.2
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• pp.15-26
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• 2007

In this study, a SOHO (Small Office Home Office) bankruptcy prediction model is proposed using Modified Bagging Predictors which is modification of traditional Bagging Predictors. There have been several studies on bankruptcy prediction for large and middle size companies. However, little studies have been done for SOHOs. In commercial banks, loan approval processes for SOHOs are usually less structured than those for large and middle size companies, and largely depend on partial information such as credit scores. In this study, we use a real SOHO loan approval data set of a Korean bank. First, decision tree induction techniques and artificial neural networks are applied to the data set, and the results are not satisfactory. Bagging Predictors which has been not previously applied for bankruptcy prediction and Modified Bagging Predictors which is proposed in this paper are applied to the data set. The experimental results show that Modified Bagging Predictors provides better performance than decision tree inductions techniques, artificial neural networks, and Bagging Predictors.

• The Journal of Advanced Prosthodontics
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• v.10 no.6
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• pp.395-400
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• 2018

PURPOSE. This study tried to find the most significant factors predicting implant prognosis using machine learning methods. MATERIALS AND METHODS. The data used in this study was based on a systematic search of chart files at Seoul National University Bundang Hospital for one year. In this period, oral and maxillofacial surgeons inserted 667 implants in 198 patients after consultation with a prosthodontist. The traditional statistical methods were inappropriate in this study, which analyzed the data of a small sample size to find a factor affecting the prognosis. The machine learning methods were used in this study, since these methods have analyzing power for a small sample size and are able to find a new factor that has been unknown to have an effect on the result. A decision tree model and a support vector machine were used for the analysis. RESULTS. The results identified mesio-distal position of the inserted implant as the most significant factor determining its prognosis. Both of the machine learning methods, the decision tree model and support vector machine, yielded the similar results. CONCLUSION. Dental clinicians should be careful in locating implants in the patient's mouths, especially mesio-distally, to minimize the negative complications against implant survival.