• Title/Summary/Keyword: $\partial$-estimate

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The study of simplified technique compared with analytical solution method for calculating the energy consumption loads of four houses having various wall construction

  • Han, Kyu-Il
    • Journal of the Korean Society of Fisheries and Ocean Technology
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    • v.47 no.1
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    • pp.46-58
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    • 2011
  • A steady-state analysis and a simple dynamic model as simplified methods are developed, and results of energy consumption loads are compared with results obtained using computer to evaluate the analytical solution. Before obtaining simplified model a mathematical model is formulated for the effect of wall mass on the thermal performance of four different houses having various wall construction. This analytical study was motivated by the experimental work of Burch et al. An analytical solution of one-dimensional, linear, partial differential equation for wall temperature profiles and room air temperatures is obtained using the Laplace transform method. Typical Meteorological Year data are processed to yield hourly average monthly values. This study is conducted using weather data from four different locations in the United States: Albuquerque, New mexico; Miami, Florida; Santa Maria, California; and Washington D.C. for both winter and summer conditions. The steady state analysis that does not include the effect of thermal mass can provide an accurate estimate of energy consumption in most cases except for houses #2 and #4 in mild weather areas. This result shows that there is an effect of mass on the thermal performance of heavily constructed house in mild weather conditions. The simple dynamic model is applicable for high cycling rates and accurate values of inside wall temperature and ambient air temperature.

Free Vibration Analysis of a Rotating Cantilever Beam by Using Differential Transformation Method (미분변환법을 이용한 회전외팔보의 자유진동해석)

  • Sin, Young-Jae;Jy, Young-Chel;Yun, Jong-Hak;Yoo, Yeong-Chan
    • Transactions of the Korean Society of Mechanical Engineers A
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    • v.31 no.3 s.258
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    • pp.331-337
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    • 2007
  • Rotating cantilever beams can be found in several practical engineering applications such as turbine blades and helicopter rotor blades. For reliable and economic design, it is necessary to estimate the dynamic characteristics of those structures accurately and efficiently since significant variation of dynamic characteristics resulted from rotational motion of the structures. Recently, Differential Transformation Method(DTM) was proposed by Zhou. This method has been applied to fluid dynamics and vibration problems, and has shown accuracy, efficiency and convenience in solving differential equations. The purpose of this study, the free vibration analysis of a rotating cantilever beam, is to seek for the reliable property of DTM and confidence in the results obtained by this method by comparing the results with that of finite element method applied to linear partial differential equations. In particular, this study is worked by supposing optional T-function values because the equations governing chordwise motion are based on two differential equations coupled with each other. This study also shows mode shapes of rotating cantilever beams for various rotating speeds.

Coordination of Anti-Spoofing Mechanisms in Partial Deployments

  • An, Hyok;Lee, Heejo;Perrig, Adrian
    • Journal of Communications and Networks
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    • v.18 no.6
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    • pp.948-961
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    • 2016
  • Internet protocol (IP) spoofing is a serious problem on the Internet. It is an attractive technique for adversaries who wish to amplify their network attacks and retain anonymity. Many approaches have been proposed to prevent IP spoofing attacks; however, they do not address a significant deployment issue, i.e., filtering inefficiency caused by a lack of deployment incentives for adopters. To defeat attacks effectively, one mechanism must be widely deployed on the network; however, the majority of the anti-spoofing mechanisms are unsuitable to solve the deployment issue by themselves. Each mechanism can work separately; however, their defensive power is considerably weak when insufficiently deployed. If we coordinate partially deployed mechanisms such that they work together, they demonstrate considerably superior performance by creating a synergy effect that overcomes their limited deployment. Therefore, we propose a universal anti-spoofing (UAS) mechanism that incorporates existing mechanisms to thwart IP spoofing attacks. In the proposed mechanism, intermediate routers utilize any existing anti-spoofing mechanism that can ascertain if a packet is spoofed and records this decision in the packet header. The edge routers of a victim network can estimate the forgery of a packet based on this information sent by the upstream routers. The results of experiments conducted with real Internet topologies indicate that UAS reduces false alarms up to 84.5% compared to the case where each mechanism operates individually.

The Wave Diffraction in a Partial-Reflecting Harbor due to Submarine Pit (Pit에 의한 부분반사율을 갖는 항내에서의 파랑 회절에 관한 연구)

  • Kim, Sung-Duk;Lee, Hong-Sik
    • Journal of Korean Society of Coastal and Ocean Engineers
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    • v.19 no.5
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    • pp.502-510
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    • 2007
  • The present study is to estimate the effect of diffracted wave fields inside a harbor, around harbor entrance and outer breakwater, when a navigation channel is dredged in the vicinity of the a harbor entrance. The wave field of the problem is considered to be two-dimensional plane and the configuration of the submarine pit on the sea bed is designated by a single rectangular type. The numerical simulation is performed by using the solution of the Greet function based on the boundary integral equation. The results of this study is illustrated by applying the normal incidence and partially reflecting boundaries.

Broker-Dealer Competition in the Korean Financial Securities Markets

  • Gwon, Jae-Hyun
    • The Journal of Industrial Distribution & Business
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    • v.9 no.4
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    • pp.19-26
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    • 2018
  • Purpose - This study measures how competitive securities broker-dealers are in the Korean financial markets. It aims to test whether the markets are perfectly competitive or monopolistic since the global financial crisis of 2008. Research design, data, and methodology - We apply the method developed by Panzar and Rosse (1987), H-statistics, which offers an index for the competitiveness as well as statistical tests. The dataset in use is retrieved mainly from the quarterly statements of the financial services companies by the Financial Statistics Information System of the Financial Supervisory Service. General information on officers and employees is utilized in addition to balance sheets and income statements of securities companies. Results - H-statistics for 2009-2015 is about 0.7 that is a robust estimate regardless of model specifications such as full trans-log, partial trans-log, and Cobb-Douglas regression equations. H-statistics for each year is also computed in similar ways in that it varies between 0.3 and 0.9. Conclusions - Since the global financial crisis, H-statistics concludes that securities broker-dealer markets in Korea is neither perfectly competitive nor monopolistic. It evidences that the markets are rather monopolistically competitive. The trend in annual H-statistics leads to the same conclusion but the result is not such stable that overall H-statistics implies.

Human Sensibility Ergonomic Apparel Coordination Supporting Method using Genetic Algorithm (유전자 알고리즘을 이용한 감성공학적 의상 코디 지원 방법)

  • Chung, Kyung-Yong
    • The Journal of the Korea Contents Association
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    • v.8 no.5
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    • pp.38-43
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    • 2008
  • As the sensibility engineering has become a mainstream information tool, searching answers has become crucial as well. Because the collaborative filtering refers to partial users information who have the similar preference, it tends to ignore the rest. In this paper, we propose the human sensibility ergonomic apparel coordination supporting method using the genetic algorithm. This proposed method calculates evaluation values using fitness function based the genetic algorithm, and gathers through a-cut. To estimate the performance, the suggested method is compared with the existing methods in the questionnaire dataset. The results have shown that the proposed method significantly outperforms the accuracy than the previous methods.

The Impact of Online Shopping Experience on Consumers Shopping Values and Purchase Intention (쇼핑가치가 구매의도에 미치는 영향 분석 : 인터넷 구매 경험 차이의 관점에서)

  • Kim, Mi-Suk;Yoo, Chul-Woo;Choe, Young-Chan
    • Journal of Korean Society of Rural Planning
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    • v.14 no.1
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    • pp.9-21
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    • 2008
  • This study deals with shopping value and trust as the factors to influence consumer attitude and purchase intention in online shopping. Utilitarian and hedonic shopping values, trust, attitude and purchase intention are incorporated into the Value-Attitude-Behavior model to find out how differently shopping values and trust influence online shoppers attitude and purchase intention when they have different purchase experiences. Data are collected from survey of 187 subjects and divided into two groups according to their online purchase experiences : 97 shoppers with low online purchase experiences and 89 with high experiences. PLS(Partial Least Square) method is applied to estimate the research model and to test 7 hypotheses. The results show the difference of the way how shopping value and trust influence purchase intention. In the case of low experienced online shoppers, trust has the greatest influence purchase intention, followed by hedonic shopping value mediated by attitude. However utilitarian shopping values have a bigger impact on it for shoppers with high purchase experiences. In the latter, trust also has a significant impact on purchase intention at confidence level of 0.05. The results also provide useful implications for practitioners to build and manage their marketing strategies. Managers of online shopping mall should react to the different shopping value by shopper's experience.

PERFORMANCE OF COMS SNOW AND SEA ICE DETECTION ALGORITHM

  • Lee, Jung-Rim;Chung, Chu-Yong;Ahn, Myoung-Hwan;Ou, Mi-Lim
    • Proceedings of the KSRS Conference
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    • 2007.10a
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    • pp.278-281
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    • 2007
  • The purpose of this study is to develop snow and sea ice detection algorithm in Communication, Ocean and Meteorological Satellite (COMS) meteorological data processing system. Since COMS has only five channels, it is not affordable to use microwave or shortwave infrared data which are effective and generally used for snow detection. In order to estimate snow and sea ice coverage, combinations between available channel data(mostly visible and 3.7 ${\mu}m$) are applied to the algorithm based on threshold method. As a result, the COMS snow and sea ice detection algorithm shows reliable performance compared to MODIS products with channel limitation. Specifically, there is partial underestimation over the complicated vegetation area and overestimation over the area of high level clouds such as cirrus. Some corrections are performed by using water vapor and infrared channels to remove cloud contamination and by applying NDVI to detect more snow pixels for the underestimated area.

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Development of Algorithm for Prediction of Bead Height on GMA Welding (GMA 용접의 최적 비드 높이 예측 알고리즘 개발)

  • 김인수;박창언;김일수;손준식;안영호;김동규;오영생
    • Journal of Welding and Joining
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    • v.17 no.5
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    • pp.40-46
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    • 1999
  • The sensors employed in the robotic are welding system must detect the changes in weld characteristics and produce the output that is in some way related to the change being detected. Such adaptive systems, which synchronise the robot arm and eyes using a primitive brain will form the basis for the development of robotic GMA(Gas Metal Arc) welding which increasingly higher levels of artificial intelligence. The objective of this paper is to realize the mapping characteristics of bead height through learning. After learning, the neural estimation can estimate the bead height desired from the learning mapping characteristic. The design parameters of the neural network estimator(the number of hidden layers and the number of nodes in a layer) are chosen from an estimation error analysis. A series of bead of bead-on-plate GMA welding experiments was carried out in order to verify the performance of the neural network estimator. The experimental results show that the proposed neural network estimator can predict the bead height with reasonable accuracy and guarantee the uniform weld quality.

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Learning the Covariance Dynamics of a Large-Scale Environment for Informative Path Planning of Unmanned Aerial Vehicle Sensors

  • Park, Soo-Ho;Choi, Han-Lim;Roy, Nicholas;How, Jonathan P.
    • International Journal of Aeronautical and Space Sciences
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    • v.11 no.4
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    • pp.326-337
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    • 2010
  • This work addresses problems regarding trajectory planning for unmanned aerial vehicle sensors. Such sensors are used for taking measurements of large nonlinear systems. The sensor investigations presented here entails methods for improving estimations and predictions of large nonlinear systems. Thoroughly understanding the global system state typically requires probabilistic state estimation. Thus, in order to meet this requirement, the goal is to find trajectories such that the measurements along each trajectory minimize the expected error of the predicted state of the system. The considerable nonlinearity of the dynamics governing these systems necessitates the use of computationally costly Monte-Carlo estimation techniques, which are needed to update the state distribution over time. This computational burden renders planning to be infeasible since the search process must calculate the covariance of the posterior state estimate for each candidate path. To resolve this challenge, this work proposes to replace the computationally intensive numerical prediction process with an approximate covariance dynamics model learned using a nonlinear time-series regression. The use of autoregressive time-series featuring a regularized least squares algorithm facilitates the learning of accurate and efficient parametric models. The learned covariance dynamics are demonstrated to outperform other approximation strategies, such as linearization and partial ensemble propagation, when used for trajectory optimization, in terms of accuracy and speed, with examples of simplified weather forecasting.