• Title/Summary/Keyword: data-based model

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The Effect of Private Guards' Job Embeddedness on Dual Commitment (민간경비원의 직무착근도가 이중몰입에 미치는 영향)

  • Lim, Woon-Sik
    • Korean Security Journal
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    • no.41
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    • pp.123-151
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    • 2014
  • The purpose of this study was focused on the relationship between private guards' job embeddedness and dual commitment. In this study, job embeddedness is selected as an independent variable and dual commitment is selected as a dependent variable one. job embeddedness was divided into three sub-factors such as "fit", "links", and "sacrifice", and dual commitment is again composed with organizational commitment, and career commitment. Moreover sex, age, academic background, service period, and income were selected as a control variable. To test the hypotheses, survey data from private guards in Kyungpook are collected and analyzed. Principal component method is used to see which items cluster together in each factor and to calculate factor scores. Multiple regression analysis identifies several factors which have significant effects on dual commitment. Key finding can be summarized as follow. Fist, the factor of "fit" have significant effects on organizational commitment, and career commitment. Second, the factor of "links" have significant effects on organizational commitment, and career commitment. Third the factor of "sacrifice" have significant effects on organizational commitment, and career commitment. Finally, when all the variables with significant effects are included in the final model, "links" disappear, while "fit" and "sacrifice" remain statistically significant. Based on these finding, this study suggests some policy issues to promote private guards' dual commitment.

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Hydrothermal Alteration and Its Cenetic Implication in the Casado Volcanic-hosted Epithermal Cold-Silver Deposit: Use in Exploration (가사도 화산성 천열수 금은광상의 열수변질대 분포 및 성인: 탐사에의 적용)

  • 김창성;최선규;최상훈;이인우
    • Journal of the Mineralogical Society of Korea
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    • v.15 no.3
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    • pp.205-220
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    • 2002
  • The gold-silver deposits in the Casado district were formed in the sheeted and stockwork quartz veins which fill the fault fractures in volcanic rocks. K-Ar dating of alteration sericite (about 70 Ma) indicates a Late Cretaceous age for ore mineralization. These veins are composed of quartz, adularia, carbonate, and minor of pyrite, sphalerite, chalcopyrite, galena, Ag-sulfosalts (argentite, pearceite, Ag-As-Sb-S system), and electrum. These veins are characterized by chalcedonic, comb, crustiform and feathery textures. Based on the hydrothermally altered mineral assemblages, regional alteration zoning associated with mineralization in the Gasado district is defined as four zones; advanced argillic (kaolin mineral-alunite-quartz), argillic (kaolin mineral-quartz), phyllic (quartz-sericite-pyrite) and propylitic (chlorite-carbonate-quartz-feldspar-pyroxene) zone. Phyllic and propylitic zones is distributed over the study area. However, advanced argillic zone is restricted to the shallow surface of the Lighthouse vein. Compositions of electrum ranges from 14.6 to 53.7 atomic % Au, and the depositional condition for mineralization are estimated in terms of both temperature and sulfur fugacity: T=245。$~285^{\circ}C$, logf $s_2$=$10^{-10}$ ~ $10^{-12}$ Fluid inclusion and stable isotope data show that the auriferous fluids were mixed with cool and dilute (158。~253$^{\circ}C$ and 0.9~3.4 equiv. wt. % NaCl) meteoric water ($\delta^{18}$ $O_{water}$=-10.1~8.0$\textperthousand$, $\delta$D=-68~64$\textperthousand$). These results harmonize with the hot-spring type of the low-sulfidation epithermal deposit model, and strongly suggest that Au-Ag mineralization in the Gasado district was formed in low-sulfidation alteration type environment at near paleo-surface.

Prediction of Chemical Organic Composition of Manure by Near Infrared Reflectance Spectroscopy

  • Amari, Masahiro;Fukumoto, Yasuyuki;Takada, Ryozo
    • Proceedings of the Korean Society of Near Infrared Spectroscopy Conference
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    • 2001.06a
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    • pp.1265-1265
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    • 2001
  • The organic materials included in excreta of livestock are important resources for organic manure and for improving soil quality, although there is still far from effective using. One reason for this is still unclearly standard of quality for evaluation of manure made from excreta of livestock. Therefore, the objective of this study is to develop rapid and accurate analytical method for analyzing organic compositions of manure made from excreta of livestock, and to establish quality evaluation method based on the compositions predicted by near infrared reflectance spectroscopy (NIRS). Sixteen samples of manure, each eight samples prepared from two treatments, were used in this study. The manure samples were prepared by mixing 560 kg feces of swine,60 kg sawdust with moisture content was adjusted to be 65%. The mixture was then keep under two kinds of shelter, black and clear sheets, as a treatment on the effect of sunlight. Samples were taken in every week (form week-0 to 7) during the process of manure making. Samples were analyzed to determine neutral detergent fiber (NDF), acid detergent fiber (ADF) and acid detergent lignin (ADL) by detergent methods, and organic cell wall (OCW) and fibrous content of low digestibility in OCW (Ob) by enzymatic methods. Biological oxygen demand (BOD) was analyzed by coulometric respirometer method. These compositions were carbohydrateds and lignin that were hardly digested. Spectra of samples were scanned by NIR instrument model 6500 (Pacific Scientific) and read over the range of wavelength between 400 and 2500nm. Calibration equations were developed using eight manure samples collected from black sheet shelter, while prediction was conducted to the other eight samples from clear sheet shelter. Accuracy of NTRS prediction was evaluated by correlation coefficients (r), standard error of prediction (SEP) and ration of standard deviation of reference data in prediction sample set to SEP (RPD). The r, SEP and RPD value of forage were 0.99, 0.69 and 7.6 for ADL, 0.96, 1.03 and 4.1 for NDF, 0.98, 0.60 and 4.9 for ADF, 0.92, 1.24 and 2.6 for Ob, and 0.91, 1.02 and 7.3 for BOD, respectively. The results indicated that NIRS could be used to measure the organic composition of forage used in manure samples.

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Effects of the Trade Insurance and Exchange Risk on Export: The Experience of Korea (무역보험과 환위험이 수출에 미치는 영향)

  • Kim, Chang-Beom
    • International Commerce and Information Review
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    • v.13 no.3
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    • pp.77-95
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    • 2011
  • This paper investigates the relationship between export and economic variables such as trade insurance, world economy activity, relative price, unemployment rate, exchange rate volatility, using monthly data. I employ Johansen cointegration methodology since the model must be stationary to avoid the spurious results. The results indicate that there is a long-run relationship between export and variables. Also, the empirical analysis of cointegrating vector using the CCR, DOLS, FMOLS reveals that the increases of trade insurance has positive relations and the increases of exchange rate volatility have negative relations with export. Especially, DOLS based on Monte Carlo simulations, of this estimator being superior in small samples compared to a number of alternative estimators, as well as being able not only to accommodate higher orders of integration but also to account for possible simultaneity within regressors of a potential system. This paper also applies impulse-response functions to get the additional information regarding the responses of the export to the shocks of the variables. The result indicates that export positively to trade insurance and then decay fast compare with exchange rate volatility. Consequently, trade insurance plays the role of trade policy for export promotion in Korea. Whereas, increase of exchange risk result in reduction of export. Therefore, the support of trade insurance should be expanded and the stabilization of the foreign exchange market must be done for the export promotion.

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Analysis of Posting Preferences and Prediction of Update Probability on Blogs (블로그에서 포스팅 성향 분석과 갱신 가능성 예측)

  • Lee, Bum-Suk;Hwang, Byung-Yeon
    • Journal of KIISE:Databases
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    • v.37 no.5
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    • pp.258-266
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    • 2010
  • In this paper, we introduce a novel method to predict next update of blogs. The number of RSS feeds registered on meta-blogs is on the order of several million. Checking for updates is very time consuming and imposes a heavy burden on network resources. Since blog search engine has limited resources, there is a fix number of blogs that it can visit on a day. Nevertheless we need to maximize chances of getting new data, and the proposed method which predicts update probability on blogs could bring better chances for it. Also this work is important to avoid distributed denial-of-service attack for the owners of blogs. Furthermore, for the internet as whole this work is important, too, because our approach could minimize traffic. In this study, we assumed that there is a specific pattern to when a blogger is actively posting, in terms of days of the week and, more specifically, hours of the day. We analyzed 15,119 blogs to determine a blogger's posting preference. This paper proposes a method to predict the update probability based on a blogger's posting history and preferred days of the week. We applied proposed method to 12,115 blogs to check the precision of our predictions. The evaluation shows that the model has a precision of 0.5 for over 93.06% of the blogs examined.

A Multi-Agent framework for Distributed Collaborative Filtering (분산 환경에서의 협력적 여과를 위한 멀티 에이전트 프레임워크)

  • Ji, Ae-Ttie;Yeon, Cheol;Lee, Seung-Hun;Jo, Geun-Sik;Kim, Heung-Nam
    • Journal of Intelligence and Information Systems
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    • v.13 no.3
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    • pp.119-140
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    • 2007
  • Recommender systems enable a user to decide which information is interesting and valuable in our world of information overload. As the recent studies of distributed computing environment have been progressing actively, recommender systems, most of which were centralized, have changed toward a peer-to-peer approach. Collaborative Filtering (CF), one of the most successful technologies in recommender systems, presents several limitations, namely sparsity, scalability, cold start, and the shilling problem, in spite of its popularity. The move from centralized systems to distributed approaches can partially improve the issues; distrust of recommendation and abuses of personal information. However, distributed systems can be vulnerable to attackers, who may inject biased profiles to force systems to adapt their objectives. In this paper, we consider both effective CF in P2P environment in order to improve overall performance of system and efficient solution of the problems related to abuses of personal data and attacks of malicious users. To deal with these issues, we propose a multi-agent framework for a distributed CF focusing on the trust relationships between individuals, i.e. web of trust. We employ an agent-based approach to improve the efficiency of distributed computing and propagate trust information among users with effect. The experimental evaluation shows that the proposed method brings significant improvement in terms of the distributed computing of similarity model building and the robustness of system against malicious attacks. Finally, we are planning to study trust propagation mechanisms by taking trust decay problem into consideration.

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A Modeling Study on the AVO and Complex Trace Analyses of the Fracture Bone Reflection (파쇄대 반사에너지의 AVO 및 복소트레이스 분석에 관한 모형연구)

  • Han Soo-Hyung;Kim Ji-Soo;Ha Hee-Sang;Min Dong-Joo
    • Geophysics and Geophysical Exploration
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    • v.2 no.1
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    • pp.33-42
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    • 1999
  • AVO and complex trace analyses mainly used to characterize natural gas reservoir were tested in this paper for a possible application to detection of major geological discontinuities such as fracture zones. The test data used in this study were calculated by utilizing a viscoelastic numerical program which was based on the generalized Maxwell body for a horizontal fracture model. In AVO analysis of a horizontal fracture zone, p-wave reflection appears to be variant depending upon the acoustic-impedence contrast and the offset distance. The fracture zone is also effectively clarified both in gradient stack and range-limited stack in which fracture zone reflection is attenuated with the increasing offset distance. In complex attribute plots (instantaneous amplitude, frequency, and phase), the top and bottom of the fracture Tone are characterized by a zone of strong amplitudes and an event of the same phase. Low frequency characteristics appear at the fracture zone and the underneath. Amplitude attenuation and waveform dispersion are dependent on Q-contrast between the fracture zone and the surrounding media. They were properly compensated by optimum inverse Q-filtering.

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Context Awareness Model using the Improved Google Activity Recognition (개선된 Google Activity Recognition을 이용한 상황인지 모델)

  • Baek, Seungeun;Park, Sangwon
    • KIPS Transactions on Software and Data Engineering
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    • v.4 no.1
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    • pp.57-64
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    • 2015
  • Activity recognition technology is gaining attention because it can provide useful information follow user's situation. In research of activity recognition before smartphone's dissemination, we had to infer user's activity by using independent sensor. But now, with development of IT industry, we can infer user's activity by using inner sensor of smartphone. So, more animated research of activity recognition is being implemented now. By applying activity recognition system, we can develop service like recommending application according to user's preference or providing information of route. Some previous activity recognition systems have a defect using up too much energy, because they use GPS sensor. On the other hand, activity recognition system which Google released recently (Google Activity Recognition) needs only a few power because it use 'Network Provider' instead of GPS. Thus it is suitable to smartphone application system. But through a result from testing performance of Google Activity Recognition, we found that is difficult to getting user's exact activity because of unnecessary activity element and some wrong recognition. So, in this paper, we describe problems of Google Activity Recognition and propose AGAR(Advanced Google Activity Recognition) applied method to improve accuracy level because we need more exact activity recognition for new service based on activity recognition. Also to appraise value of AGAR, we compare performance of other activity recognition systems and ours and explain an applied possibility of AGAR by developing exemplary program.

Image Analysis Using Digital Radiographic Lumbar Spine of Patients with Osteoporosis (골다공증 환자의 Digital 방사선 요추 Image를 이용한 영상분석)

  • Park, Hyong-Hu;Lee, Jin-Soo
    • The Journal of the Korea Contents Association
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    • v.14 no.11
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    • pp.362-369
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    • 2014
  • This study aimed to propose an accurate diagnostic method for osteoporosis by realizing a computer-aided diagnosis system with the application of the statistical analysis of texture features using digital images of lateral lumbar spine of patients with osteoporosis and providing reliable supplementary diagnostic information by model experimental research for early diagnosis of diseases. For these purposes, digital images of lateral lumbar spine of normal individuals and patients with osteoporosis were used in the experiments, and the values of statistical texture features on the set ROI were expressed in six parameters. Among the texture feature values of the six parameters of osteoporosis, the highest and lowest recognition rates of 95 and 80% were shown in average gray level and uniformity, respectively. Moreover, all the six parameters showed recognition rates of over 80% for osteoporosis: 82.5% in average contrast, 90% in smoothness, 87.5% in skewness, and 87.5% in entropy. Therefore, if a program developing into a computer-aided diagnosis system for medical images is coded based on the results of this study, it is considered possible to be applied to preliminary diagnostic data for automatic detection of lesions and disease diagnosis using medical images, to provide information for definite diagnosis of diseases, to diagnose by limited device, and to be used to shorten the time to analyze medical images.

Numerical Study of Combustion Characteristics and NO Emission in Swirl Premixed Burner (스월 예혼합 버너의 연소 특성 및 NO 배출에 관한 수치적 연구)

  • Baek, Gwang Min;Cho, Cheon Hyeon;Cho, Ju Hyeong;Kim, Han Seok;Sohn, Chae Hoon
    • Transactions of the Korean Society of Mechanical Engineers B
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    • v.37 no.10
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    • pp.911-918
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    • 2013
  • The combustion characteristics of an EV (Environmental Vortex) burner (double-cone burner) adopted in a gas turbines are numerically investigated. The mixing of fuel and air is analyzed for reduction of NO emission. To predict the correlation between NO emission and fuel-air mixedness, 1-step and 2-step chemistry models are adopted. The results calculated by 1-step chemistry showed that NO emissions increased by 2% in the case of degraded mixedness and by 169% in the case of improved mixedness, where the temperature in the flame zone was overestimated upstream of the cone. However, the corresponding results calculated by 2-step chemistry showed that NO emission increased by 3% and decreased by 5%, where the flame zone was not formed inside the cone. The latter results agree well with the experimental ones indicating an increase of 63% and decrease of 11% in the respective cases. Despite quantitative errors, NO emissions can be predicted reasonably by the application of the 2-step chemistry model adopted here and design modification of burner for NO reduction can be proposed based on the numerical data.