• Title/Summary/Keyword: Line Selection Probability

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A Deterministic Transit Assignment Model for Intercity Rail Network (지역간 철도의 결정적 통행배정모형 구축 연구)

  • Kim, Kyoung-Tae;Rhee, Sung-Mo;Kwon, Yong-Seok
    • Journal of the Korean Society for Railway
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    • v.11 no.6
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    • pp.550-561
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    • 2008
  • The purpose of this paper is to propose a new transit assignment model for intercity rail networks. The characteristics of intercity rail are different from that of public transit in urban area. Line selection probability on route section is introduced to include the characteristics of intercity rail into transit assignment model. Network expansion is more simplified by a assumption line selection probability is externally given. The generalized cost is used to decide the volume of each transit line in most of existing transit assignment models. But, many variables have influence on the volume of each line such as time schedule of transit lines, inter-station distance, passengers' income, seasonal variation of demand and regional characteristics. The influence of these variables can be considered to decide the volume of each line by introducing line selection probability on route section. The tests on a small scale network show that the model proposed in this paper is superior to existing models for predicting intercity rail demand. Proposed model is suitable to consider the complicated fare structure of intercity rail and to draw inter-station demand directly as a result of assignment procedure.

Confusion Model Selection Criterion for On-Line Handwritten Numeral Recognition (온라인 필기 숫자 인식을 위한 혼동 모델 선택 기준)

  • Park, Mi-Na;Ha, Jin-Young
    • Journal of KIISE:Software and Applications
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    • v.34 no.11
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    • pp.1001-1010
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    • 2007
  • HMM tends to output high probability for not only the proper class data but confusable class data, since the modeling power increases as the number of parameters increases. Thus it may not be helpful for discrimination to simply increase the number of parameters of HMM. We proposed two methods in this paper. One is a CMC(Confusion Likelihood Model Selection Criterion) using confusion class data probability, the other is a new recognition method, RCM(Recognition Using Confusion Models). In the proposed recognition method, confusion models are constructed using confusable class data, then confusion models are used to depress misrecognition by confusion likelihood is subtracted from the corresponding standard model probability. We found that CMC showed better results using fewer number of parameters compared with ML, ALC2, and BIC. RCM recorded 93.08% recognition rate, which is 1.5% higher result by reducing 17.4% of errors than using standard model only.

Path Generation Method of UAV Autopilots Using Max-Min Algorithm

  • Kwak, Jeonghoon;Sung, Yunsick
    • Journal of Information Processing Systems
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    • v.14 no.6
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    • pp.1457-1463
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    • 2018
  • In recent times, Natural User Interface/Natural User Experience (NUI/NUX) technology has found widespread application across a diverse range of fields and is also utilized for controlling unmanned aerial vehicles (UAVs). Even if the user controls the UAV by utilizing the NUI/NUX technology, it is difficult for the user to easily control the UAV. The user needs an autopilot to easily control the UAV. The user needs a flight path to use the autopilot. The user sets the flight path based on the waypoints. UAVs normally fly straight from one waypoint to another. However, if flight between two waypoints is in a straight line, UAVs may collide with obstacles. In order to solve collision problems, flight records can be utilized to adjust the generated path taking the locations of the obstacles into consideration. This paper proposes a natural path generation method between waypoints based on flight records collected through UAVs flown by users. Bayesian probability is utilized to select paths most similar to the flight records to connect two waypoints. These paths are generated by selection of the center path corresponding to the highest Bayesian probability. While the K-means algorithm-based straight-line method generated paths that led to UAV collisions, the proposed method generates paths that allow UAVs to avoid obstacles.

The Performance Comparison for the Contention Resolution Policies of the Input-buffered Crosspoint Packet Switch

  • Paik, Jung-Hoon;Lim, Chae-Tak
    • Journal of Electrical Engineering and information Science
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    • v.3 no.1
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    • pp.28-35
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    • 1998
  • In this paper, an NxN input-buffered crosspoint packet switch which selects a Head of the Line, HOL, packet in contention randomly is analyzed with a new approach. The approach is based on both a Markov chain representation of the input buffer and the probability that a HOL packet is successfully served. The probability as a function of N is derived, and it makes it possible to express the average packet delay and the average number of packets in the buffer as a function of N. The contention resolution policy based on the occupancy of the input buffer is also presented and analyzed with this same approach and the relationship between two selection policies is analyzed in terms of the occupancy of the input buffer.

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A Stochastic Transit Assignment Model for Intercity Rail Network (지역간 철도의 확률적 통행배정모형 구측 연구)

  • Kwon, Yong-Seok;Kim, Kyoung-Tae;Lim, Chong-Hoon
    • Journal of the Korean Society for Railway
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    • v.12 no.4
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    • pp.488-498
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    • 2009
  • The characteristics of intercity rail network are different from those of public transit network in urban area. In this paper, we proposed a new transit assignment model which is generalized form of deterministic assignment model by introducing line selection probability on route section. This model consider various characteristics of intercity rail and simplify network expansion for appling search algorithms developed in road assignment model. We showed the model availability by comparing with existing models using virtual networks. The tests on a small scale network show that this model is superior to existing models for predicting intercity rail demand.

Research on Antennas Placement of Line-of-sight Datalink for Transport Drone (수송드론 가시선 데이터링크 안테나 배치 방안 연구)

  • Sung-Ho Lim;Kilyoung Seong;Jae-Kyung Kim
    • Journal of Aerospace System Engineering
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    • v.17 no.5
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    • pp.63-75
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    • 2023
  • The antenna radiation pattern was simulated by arranging the mounted antennae of the transport drone in 5 locations where radio interference was expected to be low, and they could be mounted. Depending on the mounting location, the probability that the link margin was less than 0 dB was (5.41 - 26.92) %. When two antennae were mounted and one was selected, the probability was (0.11 - 3.3) %. Among the arrangements, placing one antenna in the upper part of the front and one in the lower part of the rear showed the lowest link fail probability. In this case, it was analyzed that if the attitude roll and pitch of the aircraft were limited, link fail would not occur at an operating distance of 12 km or less. An antenna selection formula for this case was derived, and a method of reducing frequent alternation of antennae was applied to maintain a stable link.

Beam Selection Algorithm Utilizing Fingerprint DB Based on User Types in UAV Support Systems

  • Jihyung Kim;Yuna Sim;Sangmi Moon;Intae Hwang
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.17 no.9
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    • pp.2590-2608
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    • 2023
  • The high-altitude and mobility characteristics of unmanned aerial vehicles (UAVs) have made them a key element of new radio systems, particularly because they can exceed the limits of terrestrial networks. However, at high altitudes, UAVs can be significantly affected by intercell interference at a high line-of-sight probability. To mitigate this drawback, we propose an algorithm that selects the optimal beam to reduce interference and maximize transmission efficiency. The proposed algorithm comprises two steps: constructing a user-location-based fingerprint database according to the user types presented herein and cooperative beam selection. Simulations were conducted using cellular cooperative downlink systems for analyzing the performance of the proposed method, and the signal-to-interference-plus-noise cumulative distribution function and spectral efficiency cumulative distribution function were used as performance analysis indicators. Simulation results showed that the proposed algorithm could reduce the effect of interference and increase the performance of the desired signal. Moreover, the algorithm could efficiently reduce overheads and system cost by reducing the amount of resources required for information exchange.

Prediction of Galloping Accidents in Power Transmission Line Using Logistic Regression Analysis

  • Lee, Junghoon;Jung, Ho-Yeon;Koo, J.R.;Yoon, Yoonjin;Jung, Hyung-Jo
    • Journal of Electrical Engineering and Technology
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    • v.12 no.2
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    • pp.969-980
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    • 2017
  • Galloping is one of the most serious vibration problems in transmission lines. Power lines can be extensively damaged owing to aerodynamic instabilities caused by ice accretion. In this study, the accident probability induced by galloping phenomenon was analyzed using logistic regression analysis. As former studies have generally concluded, main factors considered were local weather factors and physical factors of power delivery systems. Since the number of transmission towers outnumbers the number of weather observatories, interpolation of weather factors, Kriging to be more specific, has been conducted in prior to forming galloping accident estimation model. Physical factors have been provided by Korea Electric Power Corporation, however because of the large number of explanatory variables, variable selection has been conducted, leaving total 11 variables. Before forming estimation model, with 84 provided galloping cases, 840 non-galloped cases were chosen out of 13 billion cases. Prediction model for accidents by galloping has been formed with logistic regression model and validated with 4-fold validation method, corresponding AUC value of ROC curve has been used to assess the discrimination level of estimation models. As the result, logistic regression analysis effectively discriminated the power lines that experienced galloping accidents from those that did not.

The Study on the Accident Injury Severity Using Ordered Probit Model (순서형 프로빗 모형을 이용한 사고심각도 분석)

  • Ha, Oh-Keun;Oh, Ju-Taek;Won, Jai-Mu;Sung, Nak-Moon
    • Journal of Korean Society of Transportation
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    • v.23 no.4 s.82
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    • pp.47-55
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    • 2005
  • In recent years, the rapid growth of vehicles have increased traffic crashes. Since they can cause the economic losses and have put the life qualify in danger, there should be numerous efforts to reduce traffic crashes. To reduce traffic crashes, this research seeks to improve the safety of intersections by analysing causations of injury severity with Ordered Probability Model. This research applied the Ordered Probit Model, which assumes that ${\epsilon}_i$(random error) is normally distributed, for model calibration and used $p^2$ (likelihood ratio) and $x^2$ (Chi-square) for model selection. The results show that minor road traffic, heavy vehicle rates, major and minor right-turn rates, presence of lightings, speed limits, instructive line for left-turn traffic are significant factors affecting crash severities at signalized intersections.

Recommendation and current status in exposure assessment using monitoring data in ship building industry - focused on the similar exposure group(SEG) (조선업의 작업환경측정결과를 이용한 노출평가의 문제점과 해결방향 - 유사노출군을 중심으로 -)

  • Roh, Youngman;Yim, Hyeon Woo;Kim, Suk Il;Park, Hyo Man;Jung, Jae Yeol;Park, Sook Kyung;Kim, Hyun-Wook;Chung, Chee Kyung;Lee, Won Chul;Kim, Jung Man;Kim, Soo Keun;Koh, Sang Baek;Karl, Sieber;Kim, Euna;Choi, Jung Keun
    • Journal of Korean Society of Occupational and Environmental Hygiene
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    • v.11 no.2
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    • pp.126-134
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    • 2001
  • Statistical approaches for analysis of data from the limited number of samples in ship building industry(SBI) collected by an industrial hygienist for checking compliance to an occupational standard were considered. Sampling for compliance usually has been guided by judgment selection, rather than true randomness, resulting in the creation of compliance samples which approximate a censored sample from the upper tail of the exposure distribution. Similar exposure groups(SEGs) including welding and painting process were established to assess representative values in each groups after reviewing the whole production line in SBI. For the convenient statistical approaches, the code has assigned to each SEGs. The descriptive statistics and probability plotting were used to yield the representative values in each SEGs. In the first step, SEGs of 558 were established from 5 ship building companies. The 38 SEGs showed the uncertainty are divided into each 5 companies and assessed the representative values again. The 44 SEGs in each companies was not showed the normal and lognormal distribution was analyzed each data. And also, recommendation was suggested to resolve the uncertainty in each groups.

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