• Title/Summary/Keyword: link-prediction

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Prediction-Based Routing Methods in Opportunistic Networks

  • Zhang, Sanfeng;Huang, Di;Li, Yin
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.9 no.10
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    • pp.3851-3866
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    • 2015
  • The dynamic nature of opportunistic networks results in long delays, low rates of success for deliveries, etc. As such user experience is limited, and the further development of opportunistic networks is constrained. This paper proposes a prediction-based routing method for opportunistic networks (PB-OppNet). Firstly, using an ARIMA model, PB-OppNet describes the historical contact information between a node pair as a time series to predict the average encounter time interval of the node pair. Secondly, using an optimal stopping rule, PB-OppNet obtains a threshold for encounter time intervals as forwarding utility. Based on this threshold, a node can easily make decisions of stopping observing, or delivering messages when potential forwarding nodes enter its communication range. It can also report different encounter time intervals to the destination node. With the threshold, PB-OppNet can achieve a better compromise of forwarding utility and waiting delay, so that delivery delay is minimized. The simulation experiment result presented here shows that PB-OppNet is better than existing methods in prediction accuracy for links, delivery delays, delivery success rates, etc.

Expressway Travel Time Prediction Using K-Nearest Neighborhood (KNN 알고리즘을 활용한 고속도로 통행시간 예측)

  • Shin, Kangwon;Shim, Sangwoo;Choi, Keechoo;Kim, Soohee
    • KSCE Journal of Civil and Environmental Engineering Research
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    • v.34 no.6
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    • pp.1873-1879
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    • 2014
  • There are various methodologies to forecast the travel time using real-time data but the K-nearest neighborhood (KNN) method in general is regarded as the most one in forecasting when there are enough historical data. The objective of this study is to evaluate applicability of KNN method. In this study, real-time and historical data of toll collection system (TCS) traffic flow and the dedicated short range communication (DSRC) link travel time, and the historical path travel time data are used as input data for KNN approach. The proposed method investigates the path travel time which is the nearest to TCS traffic flow and DSRC link travel time from real-time and historical data, then it calculates the predicted path travel time using weight average method. The results show that accuracy increased when weighted value of DSRC link travel time increases. Moreover the trend of forecasted and real travel times are similar. In addition, the error in forecasted travel time could be further reduced when more historical data could be available in the future database.

Prediction Model of Rain Attenuation for Ka-Band Satellite Link (Ka 대역 위성 신호의 강우 감쇠 예측 모델)

  • 우병훈;최용석;강병수;김내수;강희조
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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    • 2002.11a
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    • pp.640-643
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    • 2002
  • 본 연구에서는 위성통신을 이용한 방송 및 멀티미디어 서비스의 확대를 앞두고 20[GHz] 이상의 높은 주파수 대역의 강우에 의한 전파 손실 예측 모델을 제안하고 강우량에 따른 감쇠 정도를 기존의 모델과 비교 분석하였다. 특히 위성 방송대역으로 이용될 Ka 대역에서 강우 감쇠에 의한 전파 손실을 제시하고 Ka 대역 위성통신 링크 설계를 위한 기본 자료를 제공하고 강우 감쇠 극복 대책을 제시하고자 한다.

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A Theoretical Analysis of Probabilistic DDHV Estimation Models (확률적인 중방향 설계시간 교통량 산정 모형에 관한 이론적 해석)

  • Cho, Jun-Han;Kim, Seong-Ho;Rho, Jeong-Hyun
    • Journal of Korean Society of Transportation
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    • v.26 no.3
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    • pp.199-209
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    • 2008
  • This paper is described the concepts and limitations for the traditional directional design hour volume estimation. The main objective of this paper is to establish an estimation method of probabilistic directional design hour volume in order to improve the limitation for the traditional approach method. To express the traffic congestion of specific road segment, this paper proposed the link travel time as the probability that the road capacity can accommodate a certain traffic demand at desired service level. Also, the link travel time threshold was derived from chance-constrained stochastic model. Such successive probabilistic process could determine optimal ranked design hour volume and directional design hour volume. Therefore, the probabilistic directional design hour volume can consider the traffic congestion and economic aspect in road planning and design stage. It is hoped that this study will provide a better understanding of various issues involved in the short term prediction of directional design hourly volume on different types of roads.

Considerations of supporting seamless mobility to mobile user in Mobile IPTV environments (Mobile IPTV 환경에서 모바일 사용자에게 끊김없는 이동성 제공을 위한 고려사항)

  • Lee, Sung-Hyup;Kwon, Sun-Young;Jang, Won-Gyu;Park, Tae-Og
    • Proceedings of the Korean Society of Broadcast Engineers Conference
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    • 2010.07a
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    • pp.321-322
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    • 2010
  • Mobile IPTV lets mobile users transmit and receive multimedia traffic, such as TV signals, audio, text and graphics, through IP-based networks with the support of quality of service(QoS) and quality of experience(QoE), mobility and interactivity [1]. To provide service feasibility, QoS and seamless mobility to mobile users, we consider mobility prediction, link stability, service requirements to develop resource reservation scheme in mobile IPTV environments. Thus, we study for mobility prediction and QoS-guaranteed mobile IPTV service prior to develop the resource reservation scheme.

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Performance Improvement of Satellite Broadcasting System in Rain Attenuation (강우 감쇠가 존재하는 위성 방송 시스템의 성능 개선)

  • Kang, Heau-Jo
    • Journal of Advanced Navigation Technology
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    • v.10 no.4
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    • pp.356-363
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    • 2006
  • The demand for digital multimedia service using Ka band satellite communication are growing rapidly. So, in this paper, we have analyzed rain attenuation with typical model, and proposed prediction model of rain attenuation in high frequency(20 GHz). This paper illustrates Korea rain attenuation characteristics at the Ka band Koreasat beacon frequency based on the theoretical and empirical approaches and seek for efficient techniques by rain attenuation estimate and analyzed performance of adaptive modulation system. Propose prediction model of rain attenuation and parameter of satellite link can be available for the Ka band satellite communication.

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A Simple Path Prediction Scheme to Improve Handoff Efficiency in All-IP Wireless Networks

  • Zhu, Huamin;Kwak, Kyung-sup
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.29 no.7A
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    • pp.781-785
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    • 2004
  • Mobile IP maintains Internet connectivity while Mobile Hosts moving from one Internet attachment point to another. However, Mobile If is not appropriate for seamless mobility. Some micromobility protocols were proposed to complement Mobile IP by offering fast and seamless handoff control in limited geographical areas. In this paper, a new scheme, based on path prediction and resource reservation, is proposed to reduce the handoff latency by trying to eliminate the link setup time for fast handoff in all-IP wireless networks. Analytical results show that the proposed scheme offers shorter handoff delay and can improve the handoff efficiency.

Development of an analytic algorithm for reach prediction (동작한계 예측을 위한 해석적 알고리즘의 개발)

  • 정의승;정민근;기도형
    • Journal of the Ergonomics Society of Korea
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    • v.12 no.1
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    • pp.17-24
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    • 1993
  • Today, rapid development and timeliness of introducing a new product be- comes a more influencing factor of determing its competitive power due to a shortened product cycle, while rapid improvement of manufacturing technology makes product design and manufacturing fuse together. This implies that prod- uct usability evaluation and improvement starts right from its design phase, resulting in less development time and cost. To make this possible, proper as- sessment of human reach is one of essential functions for ergonomic product us- ability evaluation, specifically in the platform of computer-aided ergonomic evaluation models or any CAD system with a built-in man model. In this study, an analytic reach prediction algorithm ensuring the posture that human naturally takes, is presented by employing the methods developed for robot kinematics. Among robot kinematic methods for solving the multi-link system, the resolved motion method was found to be effective to solve human reach as a redundant manipulator model. Also, the joint range availability was used as a performance fonction to guarantee human naturalness. The result is expected to be directly applicable to product usability evaluations.

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Development of a Robust Nonlinear Prediction-Type Controller

  • Park, Ghee-Yong
    • 제어로봇시스템학회:학술대회논문집
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    • 1998.10a
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    • pp.445-450
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    • 1998
  • In this paper, a robust nonlinear prediction-type controller (RNPC) is developed for the continuous time nonlinear system whose control objective is composed of system output and its desired value. The basic control law of RNPC is derived such that the future response of the system is first predicted by appropriate functional expansions and the control law minimizing the difference between the predicted and desired responses is then calculated. RNPC which involves two controls, i.e., the auxiliary and robust controls into the basic control, shows the stable closed loop dynamics of nonlinear system of any relative degree and provides the robustness to the nonlinear system with parameter/modeling uncertainty. Simulation tests for the position control of a two-link rigid body manipulator confirm the performance improvement and the robustness of RNPC.

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Fuel Consumption Prediction and Life Cycle History Management System Using Historical Data of Agricultural Machinery

  • Jung Seung Lee;Soo Kyung Kim
    • Journal of Information Technology Applications and Management
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    • v.29 no.5
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    • pp.27-37
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    • 2022
  • This study intends to link agricultural machine history data with related organizations or collect them through IoT sensors, receive input from agricultural machine users and managers, and analyze them through AI algorithms. Through this, the goal is to track and manage the history data throughout all stages of production, purchase, operation, and disposal of agricultural machinery. First, LSTM (Long Short-Term Memory) is used to estimate oil consumption and recommend maintenance from historical data of agricultural machines such as tractors and combines, and C-LSTM (Convolution Long Short-Term Memory) is used to diagnose and determine failures. Memory) to build a deep learning algorithm. Second, in order to collect historical data of agricultural machinery, IoT sensors including GPS module, gyro sensor, acceleration sensor, and temperature and humidity sensor are attached to agricultural machinery to automatically collect data. Third, event-type data such as agricultural machine production, purchase, and disposal are automatically collected from related organizations to design an interface that can integrate the entire life cycle history data and collect data through this.