• ETRI Journal
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• v.42 no.3
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• pp.341-350
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• 2020

In a wireless sensor network (WSN), the data transmission technique based on the cooperative multiple-input multiple-output (CMIMO) scheme reduces the energy consumption of sensor nodes quite effectively by utilizing the space-time block coding scheme. However, in networks with high node density, the scheme is ineffective due to the high degree of correlated data. Therefore, to enhance the energy efficiency in high node density WSNs, we implemented the distributed source coding (DSC) with the virtual multiple-input multiple-output (MIMO) data transmission technique in the WSNs. The DSC-MIMO first compresses redundant source data using the DSC and then sends it to a virtual MIMO link. The results reveal that, in the DSC-MIMO scheme, energy consumption is lower than that in the CMIMO technique; it is also lower in the DSC single-input single-output (SISO) scheme, compared to that in the SISO technique at various code rates, compression rates, and training overhead factors. The results also indicate that the energy consumption per bit is directly proportional to the velocity and training overhead factor in all the energy saving schemes.

• Journal of the Korea Society of Computer and Information
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• v.22 no.12
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• pp.63-68
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• 2017

In this paper, we propose a bounding box prediction algorithm using multiple probability maps to improve object detection result of object detector. Although the performance of object detectors has been significantly improved, it is still not perfect due to technical problems and lack of learning data. Therefore, we use the result correction method to obtain more accurate object detection results. In the proposed algorithm, the preprocessed bounding box created as a result of object detection by the object detector is clustered in various form, and a conditional probability is given to each cluster to make multiple probability map. Finally, multiple probability map create new bounding box of object using morphological elements. Experiment results show that the newly predicted bounding box reduces the error in ground truth more than 45% on average compared to the previous bounding box.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.10 no.1
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• pp.272-287
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• 2016

Recently, various and effective contrast based salient object detection models to focus on a single target have been proposed. However, there is a lack of research on detection of multiple objects, and also it is a more challenging task than single target process. In the multiple target problem, we are confronted by new difficulties caused by distinct difference between properties of objects. The characteristic of existing models depending on the global maximum distribution of data point would become a drawback for detection of multiple objects. In this paper, by analyzing limitations of the existing methods, we have devised three main processes to detect multiple salient objects. In the first stage, regional features are extracted from over-segmented regions. In the second stage, the regional features are categorized into homogeneous cluster using the mean-shift algorithm with the kernel function having various sizes. In the final stage, we compute saliency scores of the categorized regions using only spatial features without the contrast features, and then all scores are integrated for the final salient regions. In the experimental results, the scheme achieved superior detection accuracy for the SED2 and MSRA-ASD benchmarks with both a higher precision and better recall than state-of-the-art approaches. Especially, given multiple objects having different properties, our model significantly outperforms all existing models.

• Journal of the Korean Association of Geographic Information Studies
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• v.14 no.4
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• pp.44-53
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• 2011

This study designed and implemented a web-based computing environment for geovisual analytics using HTML5 canvas. The computing environment supports visualization tools and user's interaction. The visualization tools are cluster map, animated map, temporal parallel coordinate plot, and temporal heat map chart. Users can explore the temporal changes of cluster using multiple view and brushing technique. The computing environment that works well across browsers is used in the computing environment with multiple devices.

• The Research Journal of the Costume Culture
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• v.19 no.3
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• pp.622-636
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• 2011

The purpose of this study was to assess the effects of self-image congruence on attitudes toward purchase intentions of children's clothing via the Behavioral Intention Model. The empirical study was conducted via on-line survey and data were collected from mothers with children aged 6 to 10 years. A total of 593 respondents answered the questionnaire and 574 usable data were statistically analyzed. SPSS 18.0 was used to conduct descriptive statistical analysis, factor analysis, reliability analysis, cluster analysis, Chi-square test, ANOVA, and multiple regressions. A K-means cluster analysis was conducted based on three dimensions brand images of children's wear. Respondents were divided into four groups: elegant image group, multiple image group, ordinary image group, and childlike image group. Characteristics of consumers and clothing evaluative criteria that mothers considered important differed significantly across groups. Moreover, based on these groups, each dimension of self-congruence had different effects on brand attitude. Brand attitude and subjective norms had different effects on purchase intentions. In conclusion, levels of self-congruence and factors influencing purchase intention varied according to brand images of children's wear.

• Journal of Family Resource Management and Policy Review
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• v.14 no.3
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• pp.1-14
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• 2010

The purpose of this study was (1) to investigate the changes in consumer competencies according to the types of shopping value, (2) to reveal the effects of shopping value on consumer competencies. The subjects of this study were 266 university students dwelling in Seoul. A questionnaire was used as the survey method. The data was analyzed by Cronbach's alpha, frequencies, percentile, mean, factor analysis, K-mean cluster analysis, t-test, ANOVA and Duncan's multiple range tests, multiple linear regressions. Computations were conducted by SPSS WIN 12.0. The study produced the following results. First, college students can be categorized into 3 shopping values by K-means Cluster analysis of 13 items: the hedonic shopper (shopping value), the utilitarian shopper (shopping value) and the balanced shopper (shopping value). Second, there were significant differences in grades, satisfaction with life and shopping value. That is, grade 3and utilitarian shopping value group had a higher level of consumer competency. Third, the variable that influenced consumer competency was the utilitarian shopping value, influencing consumer attitude and consumer skill. These results imply that consumers should be constantly educated and that there needs to be a campaign to promote utilitarian shopping value.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.38 no.6
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• pp.712-720
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• 2001

In this paper, we propose an efficient method to detect abrupt shot changes in a video sequence using an unsupervised clustering. Conventional clustering-based shot change detection algorithms use multiple features in order to overcome the shortcomings of a single feature. In such methods it is very important to determine the appropriate initial cluster centers well. In this paper we propose a modified k-means clustering algorithm which estimates the initial cluster center adaptively. Experimental results show that the proposed algorithm works well.

• Journal of KIISE:Computer Systems and Theory
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• v.26 no.9
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• pp.1145-1157
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• 1999

본 논문에서는 RFC 2022에서 제안한 MARS 모델을 기반으로 하여 단일 대규모 클러스터를 가지는 ATM 망에서 다중의 멀티캐스팅 서버(MCS)를 이용한 멀티캐스팅 방안을 제안하고 그 성능을 평가하였다. 클러스터 내의 한 ATM 호스트가 특정 IP 멀티캐스트 그룹에 가입할 경우 ATM 호스트의 위치와 이미 존재하는 멀티캐스팅 서버들 사이의 전송 지연을 고려하여 가능한 한 종단간 전송 지연을 최소화하는 멀티캐스팅 서버를 선택하는 방안을 기술하였다. 이 방안은 최단거리 경로 알고리즘(shortest path algorithm)에 기반하여 최적의 MCS를 선정하고 송수신자 사이의 최소 지연을 가지는 멀티캐스트 트리를 구성한다. 다양한 망 위상에서 MCS의 분포 패턴을 다르게 할 경우에도 이 방안은 멀티캐스트 트리의 평균 전달 지연을 줄이는 것을 시뮬레이션을 통하여 확인하였다.Abstract In this paper, we proposed a scheme to support multiple MCSs over a single and large cluster in ATM networks, evaluated its performance by simulation. When an ATM host requests joining into a specific multicast group, the MARS designate a proper MCS among the multiple MCSs for the group member to minimize the average path delay between the sender and the group members. This scheme constructs a multicast tree through 2-phase partial multicast tree construction based upon the shortest path algorithm.We reduced the average path delay in multicast tree using our scheme under various cluster topologies and MCS distribution scenarios.

• Journal of Korean Society for Atmospheric Environment
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• v.29 no.4
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• pp.447-458
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• 2013

The present operating system for the atmospheric monitoring network in the city of Seoul, Korea, has been established since the late 90s by the Korean Ministry of Environment (KMOE). In this research, it was evaluated by the multi-statistical approaches through combinations of time series analysis, correlation matrix, and multiple cluster analysis. Finally, road traffic including resuspended materials can be one of the main sources of particulate matter in the atmosphere. Based on its importance, it will be significant challenges in quantitative evaluation of its contribution to airborne concentrations. The future directions for their amendments such as a new management plan for the source of road dust (including car emissions) were devised and proposed based on the statistical judgements derived in this research.

• Journal of Ocean Engineering and Technology
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• v.20 no.4 s.71
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• pp.76-82
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• 2006

The large-eddy simulation(LES) technique, based an a message passing interface method(MPI), was applied to investigate the turbulent flaw phenomena around a ship. The Smagorinski model was used in the present LES simulation to simulate the turbulent flaw around a ship. The SPMD(sidsngle program multiple data) technique was used for parallelization of the program using MPI. All computations were performed an a 24-node PC cluster parallel machine, composed of 2.6 GHz CPU, which had been installed in the Advanced Ship Engineering Research Center(ASERC). Numerical simulations were performed for the Wigley hull, and the Series 60 hull(CB=0.6) using 1/4-, 1/2-, 1- and 2-million grid systems and the computational results had been compared to the experimental ones.