• Journal of the Korean Institute of Electrical and Electronic Material Engineers
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• v.20 no.1
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• pp.57-64
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• 2007

One of the cause of insulation failure in power cable is well known by electrical treeing discharge. This is occurred for imposed continuous stress at cable. And this event is related to safety, reliability and maintenance. In this paper, throughout analysis of partial discharge(PD) distribution when occurring the electrical tree, is studied for the purpose of knowing of electrical treeing discharge characteristics according to defects. Own characteristic of tree will be differently processed in each defect and this reason is the first purpose of this paper. To acquire PD data, three defective tree models were made. And their own data is shown by the phase-resolved partial discharge method (PRPD). As a result of PRPD, tree discharge sources have their own characteristics. And if other defects (void, metal particle) exist internal power cable then their characteristics are shown very different. This result Is related to the time of breakdown and this is importance of cable diagnosis. And classification method of PD sources was studied in this paper. It needs select the most useful method to apply PD data classification one of the proposed method. To meet the requirement, we select methods of different type. That is, neural network(NN-BP), adaptive neuro-fuzzy inference system and PCA-LDA were applied to result. As a result of, ANFIS shows the highest rate which value is 98 %. Generally, PCA-LDA and ANFIS are better than BP. Finally, we performed classification of tree progress using ANFIS and that result is 92 %.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.42 no.4
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• pp.183-193
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• 2019

Process mining is an analytical technique aimed at obtaining useful information about a process by extracting a process model from events log. However, most existing process models are deterministic because they do not include stochastic elements such as the occurrence probabilities or execution times of activities. Therefore, available information is limited, resulting in the limitations on analyzing and understanding the process. Furthermore, it is also important to develop an efficient methodology to discover the process model. Although genetic process mining algorithm is one of the methods that can handle data with noises, it has a limitation of large computation time when it is applied to data with large capacity. To resolve these issues, in this paper, we define a stochastic process tree and propose a tabu search-genetic process mining (TS-GPM) algorithm for a stochastic process tree. Specifically, we define a two-dimensional array as a chromosome to represent a stochastic process tree, fitness function, a procedure for generating stochastic process tree and a model trace as a string of activities generated from the process tree. Furthermore, by storing and comparing model traces with low fitness values in the tabu list, we can prevent duplicated searches for process trees with low fitness value being performed. In order to verify the performance of the proposed algorithm, we performed a numerical experiment by using two kinds of event log data used in the previous research. The results showed that the suggested TS-GPM algorithm outperformed the GPM algorithm in terms of fitness and computation time.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.19 no.6
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• pp.139-144
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• 2019

For recent decades, Non-volatile Memory (NVM) technologies have been drawing a high attention both in industry and academia due to its high density and short latency comparable to that of DRAM. However, NVM devices has write endurance problem and thus the current data structures that have been built around DRAM-specific features including unlimited program cycles is inadequate for NVM, reducing the device lifetime significantly. In this paper, we revisit a red-black tree extensively adopted for data indexing across a wide range of applications, and make it to better fit for NVM. Specifically, we observe that the conventional red-black tree wears out the specific location of memory because of its rebalancing operation to ensure fast access time over a whole dataset. However, this rebalancing operation frequently updates the long-lived nodes, which leads to the skewed wear out across the NVM cells. To resolve this problem, we present a new swapping wear-leveling red-black tree that periodically moves data in the worn-out node into the young node. The performance study with real-world traces demonstrates the proposed red-black tree reduces the standard deviation of the write count across nodes by up to 12.5%.

• Journal of the Korea Society of Computer and Information
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• v.13 no.4
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• pp.141-150
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• 2008

In this mobile computing environment, data broadcasting is widely used to resolve the problem of limited power and bandwidth of mobile equipments. Most previous broadcast indexing methods concentrate on flat data. However. with the growing popularity of XML, an increasing amount of information is being stored and exchanged in the XML format. We propose a novel indexing method. called TOP tree(Tree Ordering based Path summary tree), for indexing XML document on mobile broadcast environments. TOP tree is a path summary tree which provides a concise structure summary at group level using global IDs and element information at local level using local IDs. Based on the TOP tree representation, we suggest a broadcast stream generation and query Processing method that efficiently handles not only simple Path queries but also multiple path queries. We have compared our indexing method with other indexing methods. Evaluation results show that our approaches can effectively improve the access time and tune-in time in a wireless broadcasting environment.

• Asian-Australasian Journal of Animal Sciences
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• v.19 no.8
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• pp.1134-1138
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• 2006

Forest tree leaves (12 different species) of semi hilly arid region of Punjab State were collected at 30-day interval throughout the year to assess the seasonal variations in tannin profile. Tannins were extracted and fractionated from fat free samples and data were analyzed statistically by $12{\times}12$ factorial design. The leaves of Anogeissus latifolia had the highest (p<0.05) concentration of total phenols (17.4%), net (15.9%) and hydrolysable (16.9%) tannins, followed by leaves of Acacia nilotica. Majority of the tree leaves selected had moderate levels (2-5%) of net tannins. Leaves of Carrisa had the highest (p<0.05) concentration of condensed tannins (CT), whereas the leaves of Anogeissus had the lowest (p<0.05) concentration of condensed tannins. The protein precipitable phenols (PPP) corresponded well with the net tannin content present in different tree leaves. Seasonal variation data revealed that in summer, net tannins and PPP decline in leaves of Bauhinia and Zizyphus whereas the net tannin content of Anogeissus and that of Carrisa increased during summer. The CT and PPP content in the leaves of Pheonix, Leucaena, Zizyphus and Ougenia increased in winter till spring season. Tree leaves generally had higher concentration of HT during summer months. It was concluded that leaves of leaves of A. nilotica, A. latifolia and L. leucocephala could serve as an excellent alternate feed stuffs for ruminants. However, leaves of Phoenix, Carrisa, Bauhinia and Dodonea should be avoided.

• Journal of KIISE:Databases
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• v.31 no.2
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• pp.132-139
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• 2004

A range $Top-\kappa$ query returns top k records in order of a measure attribute within a specified region on multi-dimensional data, and it is a powerful tool for analysis in spatial databases and data warehouse environments. In this paper, we propose an algorithm for answering the query via selective traverse of a Hierarchical Max R-Tree(HMR-tree). It is possible to execute the query by accessing only a small part of the leaf nodes in the query region, and the query performance is nearly constant regardless of the size of the query region. The algorithm manages the priority queue efficiently to reduce cost of handling the queue and the proposed HMR-tree can guarantee the same fan-out as the original R-tree.

• International Journal of Advanced Culture Technology
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• v.4 no.2
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• pp.38-42
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• 2016

In the growing data saturated world, the question of "whether data can be used" has shifted to "can it be utilized effectively?" More data is being generated and utilized than ever before. As the collection of data increases, data mining techniques also must become more and more accurate. Thus, to ensure this data is effectively utilized, the analysis of the data must be efficient. Interpretation of results from the analysis of the data set presented, have their own on the basis it is possible to obtain the desired data. In the data mining method a decision tree, clustering, there is such a relationship has not yet been fully developed algorithm actually still impact of various factors. In this experiment, the classification method of data mining techniques is used with easy decision tree. Also, it is used special technology of one R and J48 classification technique in the decision tree. After selecting a rule that a small error in the "one rule" in one R classification, to create one of the rules of the prediction data, it is simple and accurate classification algorithm. To create a rule for the prediction, we make up a frequency table of each prediction of the goal. This is then displayed by creating rules with one R, state-of-the-art, classification algorithm while creating a simple rule to be interpreted by the researcher. While the following can be correctly classified the pattern specified in the classification J48, using the concept of a simple decision tree information theory for configuring information theory. To compare the one R algorithm, it can be analyzed error rate and accuracy. One R and J48 are generally frequently used two classifications${\ldots}$

• The KIPS Transactions:PartD
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• v.8D no.4
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• pp.305-312
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• 2001

Recently, high-dimensional index structures have been required for similarity search in such database applications s multimedia database and data warehousing. In this paper, we propose a new cell-based signature tree, called CS-tree, which supports efficient storage and retrieval on high-dimensional feature vectors. The proposed CS-tree partitions a high-dimensional feature space into a group of cells and represents a feature vector as its corresponding cell signature. By using cell signatures rather than real feature vectors, it is possible to reduce the height of our CS-tree, leading to efficient retrieval performance. In addition, we present a similarity search algorithm for efficiently pruning the search space based on cells. Finally, we compare the performance of our CS-tree with that of the X-tree being considered as an efficient high-dimensional index structure, in terms of insertion time, retrieval time for a k-nearest neighbor query, and storage overhead. It is shown from experimental results that our CS-tree is better on retrieval performance than the X-tree.

• Journal of Environmental Science International
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• v.31 no.9
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• pp.735-741
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• 2022

Global warming affects forests and their ecology. Diversity in the forest is a buffer that reduces the damage due to global warming. Mixed forests are ecologically more valuable as versatile habitats and are effective in preventing landslides. In Korea, most forests were created by simple afforestation with trees of evergreen species. Typically, evergreen trees are shallow-rooted, and deciduous trees are deep-rooted. Mixed forest tree roots grip the soil effectively, which reduces the occurrence of landslides. Therefore, improving the distribution of tree types is essential to reduce damage due to global warming. For this improvement, the investigation of tree types of the forest is needed. However, determining the tree type distribution of forests that are spread over wide areas is labor-intensive and time-consuming. This study suggests effective methods for determining the distribution of tree types in a forest that is spread across a relatively wide area. Using normalized difference vegetation index and RGB images from unmanned aerial vehicles, each evergreen and deciduous tree, and grassland area can be distinguished. The distinguished image determines the distribution of tree type. This method is effective compared to directly determining the tree type distribution in the forest by the use of manpower. The data from these methods could be applied to plan a mixed forest or to prepare for future damage due to global warming.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.29 no.5B
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• pp.409-417
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• 2009

In this study it was assessed the accuracy of the Chukwooki rainfall data in Seoul by comparing with tree-ring width index data, sunspot numbers, southern oscillation index (SOI) and global temperature anomaly. And it was investigated the correlations of climatic change and change characteristics in past north-east asia by comparisons of tree-ring width index data in near Korea. The results of this study shows that Chukwooki rainfall data has the strong reliance since the trends and depths of change are very well matched with other comparative data. And with the results by compared with tree-ring width index data in six sites of near Korea, climates of north-east asia are changed with strong correlations as being temporal and spatial and longterm periodic possibility of reproducing are exist on those changes. However characteristics of climate change post 1960 A.D. are investigated as represented differently to past although statistical moving characteristics or changing criterion are within the limitations of reproducing phase in the past since they represent the different trends and irregularity and their frequencies are increase. The results of this study are widely used on long-term forecasting for climate change in north-east asia.