• The Journal of Korean Institute of Communications and Information Sciences
• /
• v.36 no.11B
• /
• pp.1285-1296
• /
• 2011

Packet classification is one of the basic and important functions of the Internet routers, and it became more important along with new emerging application programs requiring real-time transmission. Since packet classification should be accomplished in line-speed on each incoming input packet for multiple header fields, it becomes one of the challenges in designing Internet routers. Various packet classification algorithms have been proposed to provide the high-speed packet classification. Hierarchical approach achieves effective packet classification performance by significantly narrowing down the search space whenever a field lookup is completed. However, hierarchical approach involves back-tracking problem. In order to solve the problem, set-pruning trie and grid-of-trie algorithms are proposed. However, the algorithm either causes excessive node duplication or heavy pre-computation. In this paper, we propose a smart set-pruning trie which reduces the number of node duplication in the set-pruning trie by the simple merging of the lower-level tries. Simulation result shows that the proposed trie has the reduced number of copied nodes by 2-8% compared with the set-pruning trie.

• Journal of Computing Science and Engineering
• /
• v.5 no.2
• /
• pp.111-120
• /
• 2011

Data mining algorithms should exploit new hardware technologies to accelerate computations. Such goal is difficult to achieve in database management system (DBMS) due to its complex internal subsystems and because data mining numeric computations of large data sets are difficult to optimize. This paper explores taking advantage of existing multithreaded capabilities of multicore CPUs as well as caching in RAM memory to efficiently compute summaries of a large data set, a fundamental data mining problem. We introduce parallel algorithms working on multiple threads, which overcome the row aggregation processing bottleneck of accessing secondary storage, while maintaining linear time complexity with respect to data set size. Our proposal is based on a combination of table scans and parallel multithreaded processing among multiple cores in the CPU. We introduce several database-style and hardware-level optimizations: caching row blocks of the input table, managing available RAM memory, interleaving I/O and CPU processing, as well as tuning the number of working threads. We experimentally benchmark our algorithms with large data sets on a DBMS running on a computer with a multicore CPU. We show that our algorithms outperform existing DBMS mechanisms in computing aggregations of multidimensional data summaries, especially as dimensionality grows. Furthermore, we show that local memory allocation (RAM block size) does not have a significant impact when the thread management algorithm distributes the workload among a fixed number of threads. Our proposal is unique in the sense that we do not modify or require access to the DBMS source code, but instead, we extend the DBMS with analytic functionality by developing User-Defined Functions.

• The Transactions of The Korean Institute of Electrical Engineers
• /
• v.66 no.7
• /
• pp.1117-1122
• /
• 2017

Pedestrian detection is a very important and valuable part of artificial intelligence and computer vision. It can be used in various areas for example automatic drive, video analysis and others. Many works have been done for the pedestrian detection. The accuracy of pedestrian detection on multiple pedestrian image has reached high level. It is not easily get more progress now. This paper proposes a new structure based on the idea of HOG and convolutional filters to do the pedestrian detection in single pedestrian image. It can be a method to increase the accuracy depend on the high accuracy in single pedestrian detection. In this paper, we use Multiblock HOG and magnitude of the pixel as the feature and use convolutional filter to do the to extract the feature. And then use NEWFM to be the classifier for training and testing. We use single pedestrian image of the INRIA data set as the data set. The result shows that the Convolutional Multiblock HOG we proposed get better performance which is 0.015 miss rate at 10-4 false positive than the other detection methods for example HOGLBP which is 0.03 miss rate and ChnFtrs which is 0.075 miss rate.

• Journal of Korean Society for Atmospheric Environment
• /
• v.9 no.3
• /
• pp.207-215
• /
• 1993

In order to statistically predict $O_3$ levels in Seoul, the study used the TMS (telemeted air monitoring system) data from the Department of Environment, which have monitored at 20 sites in 1989 and 1990. Each data in each site was characterized by 6 major criteria pollutants ($SO_2, TSP, CO, NO_2, THC, and O_3$) and 2 meteorological parameters, such as wind speed and wind direction. To select proper variables and to determine each pollutant's behavior, univariate statistical analyses were extensively studied in the beginning, and then various applied statistical techniques like cluster analysis, regression analysis, and expert system have been intensively examined. For the initial study of high level $O_3$ prediction, the raw data set in each site was separated into 2 group based on 60 ppb $O_3$ level. A hierarchical cluster analysis was applied to classify the group based on 60 ppb $O_3$ into small calsses. Each class in each site has its own pattern. Next, multiple regression for each class was repeatedly applied to determine an $O_3$ prediction submodel and to determine outliers in each class based on a certain level of standardized redisual. Thus, a prediction submodel for each homogeneous class could be obtained. The study was extended to model $O_3$ prediction for both on-time basis and 1-hr after basis. Finally, an expect system was used to build a unified classification rule based on examples of the homogenous classes for all of sites. Thus, a concept of high level $O_3$ prediction model was developed for one of $O_3$ alert systems.

• Journal of the Korean Home Economics Association
• /
• v.37 no.6
• /
• pp.59-76
• /
• 1999

This study was to investigate casual relation of psychological well-being and quality of life of married couples. For the data set 434 married couples living in Pusan, Korea were chosen. The data were analyzed using M, SD, t-test, Pearson's correlation, multiple regression, and path analysis. The findings of this study are as follows; First, marital satisfaction and the level of quality of life are higher for husbands than wives. Whereas psychological distress is higher for wives than husbands. Second, for husbands, husband's level of education, job satisfaction, husband's housework participation, and job stress have significant effect on marital satisfaction. For wives, wife's level of education, husband's housework participation, and husband's job stress have significant effect on marital satisfaction. Third, for husbands, job satisfaction and job stress have significant effect on psychological distress. For wives, husband's job stress have significant effect on psychological distress. Fourth, for husbands, job stress, marital satisfaction and psychological distress have significant direct effect on quality of life. Besides, husband's age, husband's level of education, job satisfaction, job stress, husband's housework participation, and marital satisfaction are indirectly associated with quality of life. For wives, marital satisfaction and psychological distress have significant direct effect on quality of life. Besides, wife's level of education, husband's job stress, husband's housework participation, and marital satisfaction are indirectly associated with quality of life.

• Journal of Families and Better Life
• /
• v.16 no.2
• /
• pp.151-164
• /
• 1998

This study was to investigate differences of quality of life between Korean and British married couples. For the data set 136 married couples living in London Plymouth United Kingdom and 208 married couples living in Pusan Korea were chosen. The data were analyzed using M, D, t-test multiple regression and path analysis,. The findings of this study are as follows; First the level of quality of life are higher for British married women than Korean married women. Second for Korean and british married women influence on quality of life are higher subjective variables than objective variables. Third for Korean married women wife's level of education religion marital satisfaction have significant direct effect on quality of life. Besides wife's age and husband's housework participation are indirectly associated with quality of life. For British married women marital satisfaction has significant direct effect on quality of life. Besides number of children income and religion are ind rectly associated with quality of life. Among the variables marital satisfaction is the strongest predictor variable.

• Smart Structures and Systems
• /
• v.17 no.5
• /
• pp.709-724
• /
• 2016

This study investigates the optimum design parameters of a superelastic friction base isolator (S-FBI) system through a multi-objective genetic algorithm to improve the performance of isolated buildings against near-fault earthquakes. The S-FBI system consists of a flat steel-PTFE sliding bearing and superelastic NiTi shape memory alloy (SMA) cables. Sliding bearing limits the transfer of shear across the isolation interface and provides damping from sliding friction. SMA cables provide restoring force capability to the isolation system together with additional damping characteristics. A three-story building is modeled with S-FBI isolation system. Multiple-objective numerical optimization that simultaneously minimizes isolation-level displacements and superstructure response is carried out with a genetic algorithm in order to optimize S-FBI system. Nonlinear time history analyses of the building with optimal S-FBI system are performed. A set of 20 near-fault ground motion records are used in numerical simulations. Results show that S-FBI system successfully control response of the buildings against near-fault earthquakes without sacrificing in isolation efficacy and producing large isolation-level deformations.

• Management & Information Systems Review
• /
• v.15
• /
• pp.147-164
• /
• 2004

The purpose of this paper is on employees as internal customers and the critical role this group plays in the delivery of quality results. The set up of research model for verification was as follows. The research model was drawn as internal service quality level $\Rightarrow$ internal customer satisfaction $\Rightarrow$ enterprise outcome. Then, two hypotheses were established to the research model. Through the factor analysis and multiple regression analysis, the results are as follows. First, internal service quality level turned out to be affected indirectly through internal customers' satisfaction rather than a direct factor to affect the enterprise outcome. Second, internal customers' satisfaction was proved to be the most important factor for the enterprise outcome as ti was the intimate factor precedent to the enterprise outcome. However, there could be a variation of response according to the personal circumstances of respondents since the respondents were from different enterprises and consisted various job positions and age group. Namely it included a limitation of rather unaccurate resulting values because the transverse methods were performed for convenience though it needed a longitudinal research to accomplish the general purpose of this study.

• The Journal of the Institute of Internet, Broadcasting and Communication
• /
• v.11 no.2
• /
• pp.63-72
• /
• 2011

Broadcast-based data dissemination has become a widely accepted approach of communication in the mobile computing environment. However, with a large set of data items, the expected delay of receiving a desired data increases due to the sequential nature of the broadcast channel. With the objective of minimizing this wait time, this paper explores the problem of data broadcast over multiple channels. In traditional approaches, data items are partitioned based on their access probabilities and allocated on multiple channels, assuming flat data scheduling per channel. If the data items allocated on the same channel are broadcast in different frequencies based on their access probabilities, the performance will be enhanced further. In this respect, this paper proposes a new broadcast scheduling scheme named two level dynamic programming(TLDP) which can reflect a variation of access probabilities among data items allocated on the same channel.

• Journal of Korea Multimedia Society
• /
• v.13 no.5
• /
• pp.702-709
• /
• 2010

The performance of mass segmentation is greatly influenced by an initial position of a mass. Some researchers performed mass segmentation with the initial position of a mass given by radiologists. The purpose of our research is to find the initial position for mass segmentation and to notify the segmented mass to radiologists without any additional information on mammograms. The proposed system consists of breast segmentation by region growing and opening operations, decision of an initial seed with characteristics of masses, and mass segmentation by a level set segmentation. A seed for mass segmentation is set based on mass scoring measure calculated by block-based variances and masked information in a sub-sampled mammogram. We used a DDSM database to evaluate the system. The accuracy of mass detection is 78% sensitivity at 4 FP/image, and it reached 92% if multiple views for masses were considered.