• Journal of KIISE:Information Networking
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• v.35 no.1
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• pp.1-10
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• 2008

Once the sensor node in wireless sensor networks is installed, it usually operates without human intervention for a long time. The remote code update scheme is required because it is difficult to recall the sensor node in many situations. Therefore, studies on the reliable and efficient transport protocol for code propagation in wireless sensor networks have been increasingly done. However, by considering only the stability aspect of transmission, most of previous works ignore the consideration on the fast code propagation. This results the energy inefficiency by consuming unnecessary energy due to the slow code propagation. In this paper, in order to overcome limitation of the previous code propagation protocols, we propose a new code propagation protocol called "FCPP(Fast Code Propagation Protocol)". The FCPP aims at improving the reliability at well as performance. For this purpose, the FCPP accomplishes the fast code propagation by using the RTT-based transmission rate control and NACK suppression scheme, which provides a better the network utilization and avoids a unnecessary transmission delay. Based on the ns-2 simulation result, we prove that the FCPP Improves significantly both reliability and performance.

• Journal of the Korea Computer Industry Society
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• v.3 no.7
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• pp.921-926
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• 2002

B+-Tree is the most popular indexing method in DBMS to manage large size data in more efficiency. However the existing B+-Tree has shortcomings in there is overhead on DISK/IO when the first time of constructing DB or of making Index, and it lessens the concurrency if there are frequent delete operations so that the index structure also should be changed frequently. To solve these problems almost DBMS is using batch construction method and lazy deletion method. But to apply B+-Tree, which is using batch construction method and lazy deletion method, into DBMS the technique for controlling and recovering concurrency is necessary, but its researching is still unsatisfactory so that there is a problem on applying it into actual systems. On this paper I suggest the technique for controlling and recovering concurrency how to implement the batch construction method and the lazy deletion method in actual DBMS. Through the suggested technique there is no cascade rollback by using Pending list, it enhances the concurrency by enabling insertion and deletion for base table on every reconstruction, and it shortens transaction response time for user by using system queue which makes the batch constructing operation is processed not in user's transaction level but in system transaction level.

• Journal of Internet Computing and Services
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• v.16 no.1
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• pp.67-74
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• 2015

In recent years, frequent itemset mining for considering the importance of each item has been intensively studied as one of important issues in the data mining field. According to strategies utilizing the item importance, itemset mining approaches for discovering itemsets based on the item importance are classified as follows: weighted frequent itemset mining, frequent itemset mining using transactional weights, and utility itemset mining. In this paper, we perform empirical analysis with respect to frequent itemset mining algorithms based on transactional weights. The mining algorithms compute transactional weights by utilizing the weight for each item in large databases. In addition, these algorithms discover weighted frequent itemsets on the basis of the item frequency and weight of each transaction. Consequently, we can see the importance of a certain transaction through the database analysis because the weight for the transaction has higher value if it contains many items with high values. We not only analyze the advantages and disadvantages but also compare the performance of the most famous algorithms in the frequent itemset mining field based on the transactional weights. As a representative of the frequent itemset mining using transactional weights, WIS introduces the concept and strategies of transactional weights. In addition, there are various other state-of-the-art algorithms, WIT-FWIs, WIT-FWIs-MODIFY, and WIT-FWIs-DIFF, for extracting itemsets with the weight information. To efficiently conduct processes for mining weighted frequent itemsets, three algorithms use the special Lattice-like data structure, called WIT-tree. The algorithms do not need to an additional database scanning operation after the construction of WIT-tree is finished since each node of WIT-tree has item information such as item and transaction IDs. In particular, the traditional algorithms conduct a number of database scanning operations to mine weighted itemsets, whereas the algorithms based on WIT-tree solve the overhead problem that can occur in the mining processes by reading databases only one time. Additionally, the algorithms use the technique for generating each new itemset of length N+1 on the basis of two different itemsets of length N. To discover new weighted itemsets, WIT-FWIs performs the itemset combination processes by using the information of transactions that contain all the itemsets. WIT-FWIs-MODIFY has a unique feature decreasing operations for calculating the frequency of the new itemset. WIT-FWIs-DIFF utilizes a technique using the difference of two itemsets. To compare and analyze the performance of the algorithms in various environments, we use real datasets of two types (i.e., dense and sparse) in terms of the runtime and maximum memory usage. Moreover, a scalability test is conducted to evaluate the stability for each algorithm when the size of a database is changed. As a result, WIT-FWIs and WIT-FWIs-MODIFY show the best performance in the dense dataset, and in sparse dataset, WIT-FWI-DIFF has mining efficiency better than the other algorithms. Compared to the algorithms using WIT-tree, WIS based on the Apriori technique has the worst efficiency because it requires a large number of computations more than the others on average.

• KIPS Transactions on Computer and Communication Systems
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• v.4 no.9
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• pp.283-288
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• 2015

Scientists gain benefits from on-demand scalable resource provisioning, and various computing environments by using cloud computing resources for their applications. However, many cloud computing service providers offer their cloud resources according to their own policies. The descriptions of resource specification are diverse among vendors. Subsequently, it becomes difficult to find suitable cloud resources according to the characteristics of an application. Due to limited understanding of resource availability, scientists tend to choose resources used in previous experiments or over-performed resources without considering the characteristics of their applications. The need for standardized notations on diverse cloud resources without the constraints of complicated specification given by providers leads to active studies on intercloud to support interoperability in hybrid cloud environments. However, projects related to intercloud studies are limited as they are short of expertise in application characteristics. We define an intercloud resource classification and propose semantic resource recommendation based on statistical analysis to provide semantic cloud resource services for an application in hybrid cloud computing environments. The scheme proves benefits on resource availability and cost-efficiency with choosing semantically similar cloud resources using cluster analysis while considering application characteristics.

• Journal of Korea Multimedia Society
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• v.15 no.6
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• pp.794-804
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• 2012

For the geometric computations on the protein molecules, the proximity queries, such as computing the minimum distance from an arbitrary point to the molecule or detecting the collision between a point and the molecule, are essential. For the proximity queries, the efficiency of the computation time can be different according to the data structure used for the molecule. In this paper, we present the data structures and algorithms for applying proximity queries to a molecule with GPU acceleration. We present two data structures, a voxel map and a sphere tree, where the molecule is represented as a set of spheres, and corresponding algorithms. Moreover, we show that the performance of presented data structures are improved from 3 to 633 times compared to the previous data structure for the molecules containing 1,000~15,000 atoms.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.16 no.8
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• pp.1765-1772
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• 2012

Success rate of transplantation of body organs improved due to development of medical equipment and diagnostic technology. In particular, a liver transplant due to liver dysfunction has increased. With the development of image processing and analysis to obtain the volume for liver transplantation have increased the accuracy and efficiency. In this thesis, we try to reconstruct the regions of the liver within three dimensional images using the mevislab tool, which is effective in quick comparison and analysis of various algorithms, and in expedient development of prototypes. Liver is divided by applying threshold values and region growing method to the original image, and by removing noise and unnecessary entities through morphology and region filling, and setting of areas of interest. It is deemed that high temporal efficiency, and presentation of diverse range of comparison and analysis module application methods through usage of MeVisLab would make contribution towards expanding of baseline of medical image processing researches.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.41 no.5
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• pp.87-97
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• 2004

In this paper, we propose an algorithm for interlaced-to-progressive conversion by the weighted summation of the information collected from spatial do-interlacing method, in which the weighted edge based line average is applied, and the temporal method in which the motion compensation is employed by using hi-directional BMA (block matching algorithm). We employed time-recursive and motion adaptive processing as motion detection is involved. Also, a median filter is used to deal with limitation of the linear summation in which only an intermediate of values being involved is determined. The main goal of the approach is to overcome the shortcomings of each of the do-interlacing techniques without significant increment of the computational complexity, and the proposed method is apt to implement in hardware for real-time processing.

• The Transactions of the Korea Information Processing Society
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• v.7 no.10
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• pp.3226-3235
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• 2000

The more complex and larger semiconductor integraed circuits become, the core important delay test becomes which guarantees that semiconductor integrated circuits operate in time. In this paper, we propose a new partial enhanced scan method that can generate test patterns for path delay faults offectively. We implemented a new partial enhanced scan method based on an automatic test pattern generator(ATPG) which uses implication and justification . First. we generate test patterns in the standard scan environment. And if test patterns are not generated regularly in the scan chain, we determine flip-flops which applied enhanced scan flip-flops using the information derived for running an automatic test pattern generator inthe circuti. Determming enhanced scan flip-flops are based on a fault coverage or a hardware overhead. through the expenment for JSCAS 89 benchmark sequential circuits, we compared the fault coverage in the standard scan enviroment and enhance scan environment, partial enhanced scan environment. And we proved the effectiveness of the new partial enhanced scan method by identifying a high fault coverage.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2014.05a
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• pp.319-322
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• 2014

Due to the active use of the internet currently, the transportation volume of logistics firms is dramatically increasing, but it is not easy to secure available vehicles and vehicle suppliers, so it is the most important for logistics companies to streamline transportations management and process. For such reason, there have been a number of studies to deal with VRP and VSP for efficient vehicle allocation planning of vehicle suppliers and vehicles. But it is hard to reflect traffic situations changing everyday and detailed geographic conditions, and it requires big scale of database and huge calculation time consumption as increase number of depots, which is very inefficient. For solving the vehicle allocation planning problems of 3PL firms with various constraints due to the transportation cost, this paper suggest new vehicle allocation information system and an algorithm based transportation cost/income. Also this paper presents actual results applied to a logistics company. As a result, the transportation profit of vehicle suppliers increased by 11 percent in average, when the developed transportation cost-based vehicle allocation system applied.

• Proceedings of the Korea Information Processing Society Conference
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• 2010.11a
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• pp.925-928
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• 2010

Wireless sensor networks are composed of a large number of sensor nodes with limited energy resources. One critical issue in wireless sensor networks is how to gather sensed information in an energy efficient way since the energy is limited. The clustering algorithm is a technique used to reduce energy consumption. It can improve the scalability and lifetime of wireless sensor network. In this paper, we introduce a clustering protocol with mode selection (CPMS) for wireless sensor networks. Our scheme improves the performance of BCDCP (Base Station Controlled Dynamic Clustering Protocol) and BIDRP (Base Station Initiated Dynamic Routing Protocol) routing protocol. In CPMS, the base station constructs clusters and makes the head node with highest residual energy send data to base station. Furthermore, we can save the energy of head nodes using modes selection method. The simulation results show that CPMS achieves longer lifetime and more data messages transmissions than current important clustering protocol in wireless sensor networks.