• Journal of Korea Water Resources Association
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• v.54 no.9
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• pp.681-692
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• 2021

Vegetation processes have a significant impact on rainfall runoff processes through evapotranspiration control, but are rarely considered in the conceptual lumped hydrological model. This study evaluated the model performance of the Hapcheon Dam watershed by integrating the ecological module expressing the leaf area index data sensed remotely from the satellite into the hydrological partition module. The proposed eco-hydrological model has three main features to better represent the eco-hydrological process in humid regions. 1) The growth rate of vegetation is constrained by water shortage stress in the watershed. 2) The maximum growth of vegetation is limited by the energy of the watershed climate. 3) The interaction of vegetation and aquifers is reflected. The proposed model simultaneously simulates hydrologic components and vegetation dynamics of watershed scale. The following findings were found from the validation results using the model parameters estimated by the SCEM algorithm. 1) Estimating the parameters of the eco-hydrological model using the leaf area index and streamflow data can predict the streamflow with similar accuracy and robustness to the hydrological model without the ecological module. 2) Using the remotely sensed leaf area index without filtering as input data is not helpful in estimating streamflow. 3) The integrated eco-hydrological model can provide an excellent estimate of the seasonal variability of the leaf area index.

• Journal of KIISE:Information Networking
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• v.34 no.5
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• pp.360-369
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• 2007

Since wireless sensor networks consist of nodes with the constrained battery, it is important to construct the topology performing energy-efficient routing while maximizing the whole network lifetime. Previous works related to this do not take into consideration the specific communication pattern in wireless sensor networks. In this paper, we propose a novel routing algorithm, called Up-Down Tree(UDT), which first constructs the tree topology based on distance and then adjusts the transmission range determined by the two different phases, tree setup and data gathering, to adapt the specific communication pattern in wireless sensor networks. Therefore, the UDT can improve energy efficiency, maximize the network lifetime, and block network partition Simulation results show that the UDT has the improved energy efficiency by constructing the optimal topology.

• The KIPS Transactions:PartB
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• v.11B no.6
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• pp.701-708
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• 2004

Existing contents-based video retrieval systems search by using a single method such as annotation-based or feature-based retrieval. Hence, it not only shows low search efficiency, but also requires many efforts to provide system administrator or annotator with a perfect automatic processing. Tn this paper, we propose an agent-based, and automatic and unified semantics-based video retrieval system, which support various semantics-retrieval of the massive video data by integrating the feature-based retrieval and the annotation-based retrieval. The indexing agent embodies the semantics about annotation of extracted key frames by analyzing a fundamental query of a user and by selecting a key-frame image that is ed by a query. Also, a key frame selected by user takes a query image of the feature-based retrieval and the indexing agent searches and displays the most similar key-frame images after comparing query images with key frames in the database by using the color-multiple-partition histogram techniques. Furthermore, it is shown that the performance of the proposed system can be significantly improved.

• Environmental Analysis Health and Toxicology
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• v.16 no.4
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• pp.223-226
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• 2001

Acetanilide is a High Production Volume Chemical, which is produced about 2,300 tons/year in Korea as of 1998 survey. Most is used as an intermediate for synthesis of pharmaceuticals and dyes. The chemical is one of seven chemicals, which are under the frame of OECD SIDS program sponsored by National Institute of Environmental Research of Korea. Regarding the information on the environmental fate. bioconcentration is one of important factor to estimate the environmental tranfer. However, measurement of bioconcentration needs high expense and time. For this reason, OECD recommends to use BCFWIN model to estimate bioconcentration of organic chemicals, BCFWIN estimates the bioconcentration factor (BCF) of an organic compound using the log octanol-water partition coefficient (Kow) of the compound. Structures are entered into BCFWIN through SMITES (Simplified Molecular Input Line Entry System) notations. The BCFWIN method classifies a compound as either ionic or non-ionic. ionic compounds include carboxylic acids, sulfonic acids and salts of sulfonic acids, and charged nitrogen compounds (nitrogen with a + 5 valence such as quaternary ammonium compounds). All other compounds are classified as non-ionic. In this study, bioaccumulation of acetanilide was estimated using BCFWIN model based on SMIIES notation, chemical name data and partition coefficient as one of environmental fate/distribution of the chemical elements.

• Journal of KIISE:Software and Applications
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• v.34 no.1
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• pp.11-17
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• 2007

One of the popular methods used for pattern classification is the MBR (Memory-Based Reasoning) algorithm. Since it simply computes distances between a test pattern and training patterns or hyperplanes stored in memory, and then assigns the class of the nearest training pattern, it cannot explain how the classification result is obtained. In order to overcome this problem, we propose an incremental teaming algorithm based on RPA (Recursive Partition Averaging) to extract IF-THEN rules that describe regularities inherent in training patterns. But rules generated by RPA eventually show an overfitting phenomenon, because they depend too strongly on the details of given training patterns. Also RPA produces more number of rules than necessary, due to over-partitioning of the pattern space. Consequently, we present the IREA (Incremental Rule Extraction Algorithm) that overcomes overfitting problem by removing useless conditions from rules and reduces the number of rules at the same time. We verify the performance of proposed algorithm using benchmark data sets from UCI Machine Learning Repository.

• The KIPS Transactions:PartA
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• v.13A no.3 s.100
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• pp.223-230
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• 2006

A MMORPG(Massively Multiplayer Online Role-Playing Game) is an online role-playing game in which a large number of players can interact with each other in the same world at the same time. Most of them require significant hardware requirements(e.g., servers and bandwidth), and dedicated support staff. Despite the efforts of developers, users often cite overpopulation, lag, and poor support as problems of games. In this paper, a dynamic load balancing method for MMORPGS is proposed. It tries to adapt to dynamic change of population by using dynamic map-partition method with VML(Virtual Map Layer) which consists of fields, sector groups, sectors, and cells. From the experimental results, our approach achieves about $23^{\sim}67%$ lower loads for each field server. By the modification to Virtual Area Layer, we can easily manage problems that come from changes of map data, resources' status, and users' behavior pattern.

• Structural Engineering and Mechanics
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• v.67 no.2
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• pp.105-113
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• 2018

To improve the prediction accuracy of the strong-unloading rock slope performance and obtain the range of variation in the slope displacement, a new displacement time-series prediction model is proposed, called the fuzzy information granulation (FIG)-genetic algorithm (GA)-back propagation neural network (BPNN) model. Initially, a displacement time series is selected as the training samples of the prediction model on the basis of an analysis of the causes of the change in the slope behavior. Then, FIG is executed to partition the series and obtain the characteristic parameters of every partition. Furthermore, the later characteristic parameters are predicted by inputting the earlier characteristic parameters into the GA-BPNN model, where a GA is used to optimize the initial weights and thresholds of the BPNN; in the process, the numbers of input layer nodes, hidden layer nodes, and output layer nodes are determined by a trial method. Finally, the prediction model is evaluated by comparing the measured and predicted values. The model is applied to predict the displacement time series of a strong-unloading rock slope in a hydropower station. The engineering case shows that the FIG-GA-BPNN model can obtain more accurate predicted results and has high engineering application value.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.19 no.4
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• pp.65-69
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• 2019

This paper presents an optimized adoption of NVM for the storage system considering application characteristics. To do so, we first characterize the storage access patterns for different application types, and make two prominent observations that can be exploited in allocating NVM storage efficiently. The first observation is that a bulk of I/O does not happen on a single storage partition, but it is varied significantly for different application categories. Our second observation is that there exists a large proportion of single accessing in storage data. Based on these observations, we show that maximizing the storage performance with NVM is not obtained by fixing it as a specific storage partition but by allocating it adaptively for different applications. Specifically, for graph, database, and web applications, using NVM as a swap, a journal, and a file system partitions, respectively, performs well.

• Database Research
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• v.34 no.3
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• pp.14-27
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• 2018

Recently, to alleviate the memory bottleneck problme occurred in Symmetric Multiprocessing (SMP) architecture, Non-Uniform Memory Access (NUMA) architecture was proposed. In addition, since an aggregation operator is an important operator providing properties and summary of data, the efficiency of the aggregation operator is crucial to overall performance of a system. Thus, in this paper, we propose an efficient aggregation processing technique on NUMA architecture. Our proposed technique consists of partition phase and merge phase. In the partition phase, the target relation is partitioned into several partial relations according to grouping attribute. Thus, since each thread can process aggregation operator on partial relation independently, we prevent the remote memory access during the merge phase. Furthermore, at the merge phase, we improve the performance of the aggregation processing by letting each thread compute aggregation with a local hash table as well as avoiding lock contention to merge aggregation results generated by all threads into one.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.29 no.8C
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• pp.1133-1141
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• 2004

In order to process video data effectively, it is required that the content information of video data is loaded in database and semantic-based retrieval method can be available for various query of users. In this paper, we propose semantic-based video retrieval system which support semantic retrieval of various users by feature-based retrieval and annotation-based retrieval of massive video data. By user's fundamental query and selection of image for key frame that extracted from query, the agent gives the detail shape for annotation of extracted key frame. Also, key frame selected by user become query image and searches the most similar key frame through feature based retrieval method that propose. From experiment, the designed and implemented system showed high precision ratio in performance assessment more than 90 percents.