• Title/Summary/Keyword: network-selection

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Face Detection Using A Selectively Attentional Hough Transform and Neural Network (선택적 주의집중 Hough 변환과 신경망을 이용한 얼굴 검출)

  • Choi, Il;Seo, Jung-Ik;Chien, Sung-Il
    • Journal of the Institute of Electronics Engineers of Korea SP
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    • v.41 no.4
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    • pp.93-101
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    • 2004
  • A face boundary can be approximated by an ellipse with five-dimensional parameters. This property allows an ellipse detection algorithm to be adapted to detecting faces. However, the construction of a huge five-dimensional parameter space for a Hough transform is quite unpractical. Accordingly, we Propose a selectively attentional Hough transform method for detecting faces from a symmetric contour in an image. The idea is based on the use of a constant aspect ratio for a face, gradient information, and scan-line-based orientation decomposition, thereby allowing a 5-dimensional problem to be decomposed into a two-dimensional one to compute a center with a specific orientation and an one-dimensional one to estimate a short axis. In addition, a two-point selection constraint using geometric and gradient information is also employed to increase the speed and cope with a cluttered background. After detecting candidate face regions using the proposed Hough transform, a multi-layer perceptron verifier is adopted to reject false positives. The proposed method was found to be relatively fast and promising.

Comparison of The Importance of Evaluation Items for Landscape Performance and Sustainability Using Analytic Network Process (ANP) (ANP기법을 이용한 조경성능 및 친환경 평가항목 중요도 비교)

  • Ryu, Myeung-Ji;Lee, Hyung-Sook
    • Journal of the Korean Institute of Landscape Architecture
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    • v.47 no.6
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    • pp.45-52
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    • 2019
  • As international criteria and standards are required in the fields of design and construction, landscape performance must also be considered not only for the value of the landscape but also for providing quality assurance and sustainability. Given the lack of research on landscape performance, the present research was purposed to analyze the importance of potential assessment categories and items using an analytical network process. A list of assessment items, which is composed of 20 items and 6 categories, was derived through a literature review and a preliminary survey of 11 landscape professionals. An ANP model was established and a survey was conducted among 30 landscape practitioners to determine the weight of priorities considering the criteria. The results of ANP showed that the categories of site selection, preservation and health, and convenience had high priorities while materials had the lowest importance score. For the assessment items, a monitoring plan was the highest importance, followed by cultural/ historic preservation, management cost reduction, and natural ground areas. Despite the difficulties in quantifying landscape achievements, most respondents agreed that there needs to be an evaluation system for landscape performance in order to assure the quality and sustainability of landscape development. More research and discussion are needed to develop an assessment system for landscape performance that is applicable to Korean context.

Semantic Network Analysis of Presidential Debates in 2007 Election in Korea (제17대 대통령 후보 합동 토론 언어네트워크 분석 - 북한 관련 이슈를 중심으로)

  • Park, Sung-Hee
    • Korean journal of communication and information
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    • v.45
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    • pp.220-254
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    • 2009
  • Presidential TV debates serve as an important instrument for the general viewers to evaluate the candidates’ character, to examine their policy, and finally to make an important political decisions to cast ballots. Every words candidates utter in the course of entire election campaign exert influence of a certain significance by delivering their ideas and by creating clashes with their respective opponents. This study focuses on the conceptual venue, coined as ‘stasis’ by ancient rhetoricians, in which the clashes take place, and examines the words selection made by each candidates, the manners in which they form stasis, call for evidence, educate the public, and finally create a legitimate form of political argumentation. The study applied computer based content analysis using KrKwic and UCINET software to analyze semantic networks among the candidates. The results showed three major candidates, namely Lee Myung Bak, Jung Dong Young, and Lee Hoi Chang, displayed separate patterns in their use of language, by selecting the words that are often neglected by their opponents. Apparently, the absence of stasis and the lack of speaking mutual language significantly undermined the effects of debates. Central questions regarding issues of North Korea failed to meet basic requirements, and the respondents failed to engage in effective argumentation process.

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A Novel Compressed Sensing Technique for Traffic Matrix Estimation of Software Defined Cloud Networks

  • Qazi, Sameer;Atif, Syed Muhammad;Kadri, Muhammad Bilal
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.12 no.10
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    • pp.4678-4702
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    • 2018
  • Traffic Matrix estimation has always caught attention from researchers for better network management and future planning. With the advent of high traffic loads due to Cloud Computing platforms and Software Defined Networking based tunable routing and traffic management algorithms on the Internet, it is more necessary as ever to be able to predict current and future traffic volumes on the network. For large networks such origin-destination traffic prediction problem takes the form of a large under- constrained and under-determined system of equations with a dynamic measurement matrix. Previously, the researchers had relied on the assumption that the measurement (routing) matrix is stationary due to which the schemes are not suitable for modern software defined networks. In this work, we present our Compressed Sensing with Dynamic Model Estimation (CS-DME) architecture suitable for modern software defined networks. Our main contributions are: (1) we formulate an approach in which measurement matrix in the compressed sensing scheme can be accurately and dynamically estimated through a reformulation of the problem based on traffic demands. (2) We show that the problem formulation using a dynamic measurement matrix based on instantaneous traffic demands may be used instead of a stationary binary routing matrix which is more suitable to modern Software Defined Networks that are constantly evolving in terms of routing by inspection of its Eigen Spectrum using two real world datasets. (3) We also show that linking this compressed measurement matrix dynamically with the measured parameters can lead to acceptable estimation of Origin Destination (OD) Traffic flows with marginally poor results with other state-of-art schemes relying on fixed measurement matrices. (4) Furthermore, using this compressed reformulated problem, a new strategy for selection of vantage points for most efficient traffic matrix estimation is also presented through a secondary compression technique based on subset of link measurements. Experimental evaluation of proposed technique using real world datasets Abilene and GEANT shows that the technique is practical to be used in modern software defined networks. Further, the performance of the scheme is compared with recent state of the art techniques proposed in research literature.

User Oriented clustering of news articles using Tweets Heterogeneous Information Network (트위트 이형 정보 망을 이용한 뉴스 기사의 사용자 지향적 클러스터링)

  • Shoaib, Muhammad;Song, Wang-Cheol
    • Journal of Internet Computing and Services
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    • v.14 no.6
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    • pp.85-94
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    • 2013
  • With the emergence of world wide web, in particular web 2.0 the rapidly growing amount of news articles has created a problem for users in selection of news articles according to their requirements. To overcome this problem different clustering mechanism has been proposed to broadly categorize news articles. However these techniques are totally machine oriented techniques and lack users' participation in the process of decision making for membership of clustering. In order to overcome the issue of zero-participation in the process of clustering news articles in this paper we have proposed a framework for clustering news articles by combining users' judgments that they post on twitter with the news articles to cluster the objects. We have employed twitter hash-tags for this purpose. Furthermore we have computed the credibility of users' based on frequency of retweets for their tweets in order to enhance the accuracy of the clustering membership function. In order to test performance of proposed methodology, we performed experiments on tweets messages tweeted during general election 2013 in Pakistan. Our results proved over claim that using users' output better outcome can be achieved then ordinary clustering algorithms.

An analysis of the signaling effect of FOMC statements (미 연준 통화정책방향 의결문의 시그널링 효과 분석)

  • Woo, Shinwook;Chang, Youngjae
    • The Korean Journal of Applied Statistics
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    • v.33 no.3
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    • pp.321-334
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    • 2020
  • The US Federal Reserve (Fed) has decided to cut interest rates. When we look at the expression of the FOMC statements at the time of policy change period we can understand that Fed has been communicating with markets through a change of word selection. However, there is a criticism that the method of analyzing the expression of the decision sentence through the context can be subjective and limited in qualitative analysis. In this paper, we evaluate the signaling effect of FOMC statements based on previous research. We analyze decision making characteristics from the viewpoint of text mining and try to predict future policy trend changes by capturing changes in expressions between statements. For this purpose, a decision tree and neural network models are used. As a result of the analysis, it can be judged that the discrepancy indicators between statements could be used to predict the policy change in the future and that the US Federal Reserve has systematically implemented policy signaling through the policy statements.

Temperature Prediction Method for Superheater and Reheater Tubes of Fossil Power Plant Boiler During Operation (화력발전 보일러 과열기 및 재열기 운전 중 튜브 온도예측기법)

  • Kim, Bum-Shin;Song, Gee-Wook;Yoo, Seong-Yeon
    • Transactions of the Korean Society of Mechanical Engineers A
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    • v.36 no.5
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    • pp.563-569
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    • 2012
  • The superheater and reheater tubes of a heavy-load fossil power plant boiler can be damaged by overheating, and therefore, the degree of overheating is assessed by measuring the oxide scale thickness inside the tube during outages. The tube temperature prediction from the oxide scale thickness measurement is necessarily accompanied by destructive tube sampling, and the result of tube temperature prediction cannot be expected to be accurate unless the selection of the overheated point is precise and the initial-operation tube temperature has been obtained. In contrast, if the tube temperature is to be predicted analytically, considerable effort (to carry out the analysis of combustion, radiation, convection heat transfer, and turbulence fluid dynamics of the gas outside the tube) is required. In addition, in the case of analytical tube temperature prediction, load changes, variations in the fuel composition, and operation mode changes are hardly considered, thus impeding the continuous monitoring of the tube temperature. This paper proposes a method for the short-term prediction of tube temperature; the method involves the use of boiler operation information and flow-network-analysis-based tube heat flux. This method can help in high-temperaturedamage monitoring when it is integrated with a practical tube-damage-assessment method such as the Larson-Miller Parameter.

Development of Prediction Model for Prevalence of Metabolic Syndrome Using Data Mining: Korea National Health and Nutrition Examination Study (국민건강영양조사를 활용한 대사증후군 유병 예측모형 개발을 위한 융복합 연구: 데이터마이닝을 활용하여)

  • Kim, Han-Kyoul;Choi, Keun-Ho;Lim, Sung-Won;Rhee, Hyun-Sill
    • Journal of Digital Convergence
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    • v.14 no.2
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    • pp.325-332
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    • 2016
  • The purpose of this study is to investigate the attributes influencing the prevalence of metabolic syndrome and develop the prediction model for metabolic syndrome over 40-aged people from Korea Health and Nutrition Examination Study 2012. The researcher chose the attributes for prediction model through literature review. Also, we used the decision tree, logistic regression, artificial neural network of data mining algorithm through Weka 3.6. As results, social economic status factors of input attributes were ranked higher than health-related factors. Additionally, prediction model using decision tree algorithm showed finally the highest accuracy. This study suggests that, first of all, prevention and management of metabolic syndrome will be approached by aspect of social economic status and health-related factors. Also, decision tree algorithms known from other research are useful in the field of public health due to their usefulness of interpretation.

A Study on the Selecting Factors of Manufacturing and Logistic Hub in Far Eastern Area (극동지역 제조 및 물류거점 선정요인 중요도 분석에 관한 연구)

  • Kim, Hak-so;Han, Ji-young
    • Journal of Korea Port Economic Association
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    • v.32 no.4
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    • pp.29-39
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    • 2016
  • As geopolitical, archaeological and strategic interests on cooperation with countries in the Far Eastern Area is gradually increased, countries are competing to attract or install a logistics or manufacturing hub in their countries. In this study, we investigated the relative importance of factors on the main three and nine detailed criteria from the domestic and overseas experts on Far Eastern Area. Using AHP(Analytic Hierarchy Process) analysis, priority importance of factors was derived. As a result, we find that the most important factor was economic factor. In detail, industrial complex creation was the highest factor and the institutional guarantees for the investment on policy and transportation network was second highest factor. Based on analysis result, specific competitiveness level in the 10 region of Far East was follows. Hunchun, Vladivostok, Yanji, Tumen, Rajin, Hassan, Ussuriysk, Cheongjin, Mihaylov Skiing, Nije Jeuchinski were showed in order. Hunchun showed the highest competitive level in location, topography, compliance to the around cities, transportation network, industrial complex, excellence in logistics facilities, long-term investment plans, institutional guarantees for investment, customs efficiency and political stability. However, in other factors such as population and number of households, public facilities, potential demand and resource utilization, Vladivostok showed the highest level.

Load Balancing of Unidirectional Dual-link CC-NUMA System Using Dynamic Routing Method (단방향 이중연결 CC-NUMA 시스템의 동적 부하 대응 경로 설정 기법)

  • Suh Hyo-Joon
    • The KIPS Transactions:PartA
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    • v.12A no.6 s.96
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    • pp.557-562
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    • 2005
  • Throughput and latency of interconnection network are important factors of the performance of multiprocessor systems. The dual-link CC-NUMA architecture using point-to-point unidirectional link is one of the popular structures in high-end commercial systems. In terms of optimal path between nodes, several paths exist with the optimal hop count by its native multi-path structure. Furthermore, transaction latency between nodes is affected by congestion of links on the transaction path. Hence the transaction latency may get worse if the transactions make a hot spot on some links. In this paper, I propose a dynamic transaction routing algorithm that maintains the balanced link utilization with the optimal path length, and I compare the performance with the fixed path method on the dual-link CC-NUMA systems. By the proposed method, the link competition is alleviated by the real-time path selection, and consequently, dynamic transaction algorithm shows a better performance. The program-driven simulation results show $1{\~}10\%$ improved fluctuation of link utilization, $1{\~}3\%$ enhanced acquirement of link, and $1{\~}6\%$ improved system performance.