• Title/Summary/Keyword: Probabilistic environment

Search Result 288, Processing Time 0.027 seconds

An Energy-Efficient Periodic Data Collection using Dynamic Cluster Management Method in Wireless Sensor Network (무선 센서 네트워크에서 동적 클러스터 유지 관리 방법을 이용한 에너지 효율적인 주기적 데이터 수집)

  • Yun, SangHun;Cho, Haengrae
    • IEMEK Journal of Embedded Systems and Applications
    • /
    • v.5 no.4
    • /
    • pp.206-216
    • /
    • 2010
  • Wireless sensor networks (WSNs) are used to collect various data in environment monitoring applications. A spatial clustering may reduce energy consumption of data collection by partitioning the WSN into a set of spatial clusters with similar sensing data. For each cluster, only a few sensor nodes (samplers) report their sensing data to a base station (BS). The BS may predict the missed data of non-samplers using the spatial correlations between sensor nodes. ASAP is a representative data collection algorithm using the spatial clustering. It periodically reconstructs the entire network into new clusters to accommodate to the change of spatial correlations, which results in high message overhead. In this paper, we propose a new data collection algorithm, name EPDC (Energy-efficient Periodic Data Collection). Unlike ASAP, EPDC identifies a specific cluster consisting of many dissimilar sensor nodes. Then it reconstructs only the cluster into subclusters each of which includes strongly correlated sensor nodes. EPDC also tries to reduce the message overhead by incorporating a judicious probabilistic model transfer method. We evaluate the performance of EPDC and ASAP using a simulation model. The experiment results show that the performance improvement of EPDC is up to 84% compared to ASAP.

Group Key Management Scheme for Survelliance and Reconnaissance Sensor Networks based on Probabilistic Key Sharing (확률론적 키 공유를 통한 감시정찰 센서네트워크에서의 그룹 키 관리 기법)

  • Bae, Si-Hyun;Lee, Soo-Jin
    • Convergence Security Journal
    • /
    • v.10 no.3
    • /
    • pp.29-41
    • /
    • 2010
  • Survelliance and Reconnaissance Sensor Network(SRSN) which can collect various tactical information within battlefield in real time plays an important role in NCW environment, of sensor to shooter architecture. However, due to the resource-limited characteristics of sensor nodes and the intrinsic attributes of sensor network such as wireless communication, the SRSN may be vulnerable to various attacks compared to traditional networks. Therefore, in this paper, we propose a new group key management scheme to guarantee confidentiality, integrity, availability, and authentication during the operation of the SRSN. Proposed scheme generates and distributes the group key based on the topological characteristic of the SRSN and the probabilistic key sharing. The communication cost for distributing the group key is O(logn).

Performance Analysis on the IMM-PDAF Method for Longitudinal and Lateral Maneuver Detection using Automotive Radar Measurements (차량용 레이더센서를 이용한 IMM-PDAF 기반 종-횡방향 운동상태 검출 및 추정기법에 대한 성능분석)

  • Yoo, Jeongjae;Kang, Yeonsik
    • Journal of Institute of Control, Robotics and Systems
    • /
    • v.21 no.3
    • /
    • pp.224-232
    • /
    • 2015
  • In order to develop an active safety system which avoids or mitigates collisions with preceding vehicles such as autonomous emergency braking (AEB), accurate state estimation of the nearby vehicles is very important. In this paper, an algorithm is proposed using 3 dynamic models to better estimate the state of a vehicle which has various dynamic patterns in both longitudinal and lateral direction. In particular, the proposed algorithm is based on the Interacting Multiple Model (IMM) method which employs three different dynamic models, in cruise mode, lateral maneuver mode and longitudinal maneuver mode. In addition, a Probabilistic Data Association Filter (PDAF) is utilized as a data association algorithm which can improve the reliability of the measurement under a clutter environment. In order to verify the performance of the proposed method, it is simulated in comparison with a Kalman filter method which employs a single dynamic model. Finally, the proposed method is validated using radar data obtained from the field test in the proving ground.

A Review of the Progress with Statistical Models of Passive Component Reliability

  • Lydell, Bengt O.Y.
    • Nuclear Engineering and Technology
    • /
    • v.49 no.2
    • /
    • pp.349-359
    • /
    • 2017
  • During the past 25 years, in the context of probabilistic safety assessment, efforts have been directed towards establishment of comprehensive pipe failure event databases as a foundation for exploratory research to better understand how to effectively organize a piping reliability analysis task. The focused pipe failure database development efforts have progressed well with the development of piping reliability analysis frameworks that utilize the full body of service experience data, fracture mechanics analysis insights, expert elicitation results that are rolled into an integrated and risk-informed approach to the estimation of piping reliability parameters with full recognition of the embedded uncertainties. The discussion in this paper builds on a major collection of operating experience data (more than 11,000 pipe failure records) and the associated lessons learned from data analysis and data applications spanning three decades. The piping reliability analysis lessons learned have been obtained from the derivation of pipe leak and rupture frequencies for corrosion resistant piping in a raw water environment, loss-of-coolant-accident frequencies given degradation mitigation, high-energy pipe break analysis, moderate-energy pipe break analysis, and numerous plant-specific applications of a statistical piping reliability model framework. Conclusions are presented regarding the feasibility of determining and incorporating aging effects into probabilistic safety assessment models.

Adaptive Automatic Thresholding in Infrared Image Target Tracking (적외선 영상 표적추적 성능 개선을 위한 적응적인 자동문턱치 산출 기법 연구)

  • Kim, Tae-Han;Song, Taek-Lyul
    • Journal of Institute of Control, Robotics and Systems
    • /
    • v.17 no.6
    • /
    • pp.579-586
    • /
    • 2011
  • It is very critical for image processing of IIR (Imaging Infrared) seekers to achieve improved guidance performance for missile systems to determine appropriate thresholds in various environments. In this paper, we propose automatic threshold determination methods for proper thresholds to extract definite target signals in an EOCM (Electro-Optical Countermeasures) environment with low SNR (Signal-to-Noise Ratios). In particular, thresholds are found to be too low to extract target signals if one uses the Otsu method so that we suggest a Shifted Otsu method to solve this problem. Also we improve extracting target signal by changing Shifted Otsu thresholds according to the TBR (Target to Background Ratio). The suggested method is tested for real IIR images and the results are compared with the Otsu method. The HPDAF (Highest Probabilistic Data Association Filter) which selects the target originated measurements by taking into account of both signal intensity and statistical distance information is applied in this study.

A study on data association based on multiple model for improving target tracking performance in maneuvering interval in bistatic sonar environments (양상태 소나를 운용하는 자함이 기동하는 구간에서 추적성능향상을 위한 다수모델기반의 자료결합기법 연구)

  • Park, Seung-Hyo;Song, Taek-Lyul;Lee, Seung-Ho
    • The Journal of the Acoustical Society of Korea
    • /
    • v.36 no.3
    • /
    • pp.202-210
    • /
    • 2017
  • For the target tracking in cluttered environment using a bistatic sonar whose transmitter and receiver are separately positioned, it is necessary to use data association algorithm via applying a proper measurement modelling to the bistatic sonar. The measurements obtained from the interval of ownship's maneuver have an increased error due to uncertainty of the position of transmitter and receiver. Using the measurements from this interval results in poor target tracking performance. In this paper, an improved tracking performance for the proposed data association based multiple model algorithm is validated by a monte carlo simulation.

Probabilistic Reliability Analysis of KEPCO System Using TRELSS

  • Tran Trung Tinh;Kwon Jung-Ji;Choi Jae-Seok;Choo Jin-Boo;Jeon Dong-Hun;Han Kyoeng-Nam;Billinton Roy
    • Journal of Electrical Engineering and Technology
    • /
    • v.2 no.1
    • /
    • pp.10-18
    • /
    • 2007
  • The importance of conducting necessary studies on grid reliability evaluation has become increasingly important in recent years due to the number of blackout events occurring throughout the world. Additionally, quantitative evaluation of transmission system reliability is very important in a competitive electricity environment. The reason behind this is that successful operation of an electric power company under a deregulated electricity market depends on transmission system reliability management. The results of many case studies for the Korea Electric Power Cooperation (KEPCO) system using the Transmission Reliability Evaluation for Large-Scale Systems (TRELSS) Version 6.2 are illustrated in this paper. The TRELSS was developed by EPRI and Southern Company Services Inc. This paper presents the reliability analysis of KEPCO system expansion planning by using the TRELSS program.

Topological Localization of Mobile Robots in Real Indoor Environment (실제 실내 환경에서 이동로봇의 위상학적 위치 추정)

  • Park, Young-Bin;Suh, Il-Hong;Choi, Byung-Uk
    • The Journal of Korea Robotics Society
    • /
    • v.4 no.1
    • /
    • pp.25-33
    • /
    • 2009
  • One of the main problems of topological localization in a real indoor environment is variations in the environment caused by dynamic objects and changes in illumination. Another problem arises from the sense of topological localization itself. Thus, a robot must be able to recognize observations at slightly different positions and angles within a certain topological location as identical in terms of topological localization. In this paper, a possible solution to these problems is addressed in the domain of global topological localization for mobile robots, in which environments are represented by their visual appearance. Our approach is formulated on the basis of a probabilistic model called the Bayes filter. Here, marginalization of dynamics in the environment, marginalization of viewpoint changes in a topological location, and fusion of multiple visual features are employed to measure observations reliably, and action-based view transition model and action-associated topological map are used to predict the next state. We performed experiments to demonstrate the validity of our proposed approach among several standard approaches in the field of topological localization. The results clearly demonstrated the value of our approach.

  • PDF

A Study on the Development of Performance Evaluation Method for the Stormwater Treatment Wetland (비점오염관리를 위한 강우유출수 처리습지의 성능평가방법 개발)

  • Kim, Young Ryun;Kim, Sang Dan;Lee, Suk Mo;Sung, Kijun;Song, Kyo Ook;Son, Min Ho
    • Journal of Korean Society on Water Environment
    • /
    • v.29 no.3
    • /
    • pp.354-364
    • /
    • 2013
  • The performance of the stormwater wetlands can be significantly influenced by antecedent stormwater in storage at the commencement of a stormevent. As inflows are intermittent and stochastic in nature, the evaluation of the treatment efficiency of a stormwater wetland should be considered by runoff capture and water treatment characteristics during interevent periods. In this study, analytical probabilistic model is applied to identity runoff capture rate and treatment efficiency of the stormwater wetland. To achieve this, continuous rainfall data recorded in Busan for 31 years has been analyzed to derive the runoff capture rate, and 1st order kinetic decay constants ($k_V$, 1/d) are calculated from regression analysis to identify pollutants removal during interevent periods. The results show that about 60.9% of annual average runoff is captured through the stormwater wetland. The annual average treatment efficiencies of SS, BOD, COD, TN and TP is about 11.4, 8.9, 9.8, 4.3 and 9.6%, respectively. The analytical model has been compared with the numerical model and it shows that analytical model is valid. Performance evaluation methods developed in this study has the advantages of considering characteristics of rainfall-runoff, facility type and pollutant removal.

A software tool for integrated risk assessment of spent fuel transportation and storage

  • Yun, Mirae;Christian, Robby;Kim, Bo Gyung;Almomani, Belal;Ham, Jaehyun;Lee, Sanghoon;Kang, Hyun Gook
    • Nuclear Engineering and Technology
    • /
    • v.49 no.4
    • /
    • pp.721-733
    • /
    • 2017
  • When temporary spent fuel storage pools at nuclear power plants reach their capacity limit, the spent fuel must be moved to an alternative storage facility. However, radioactive materials must be handled and stored carefully to avoid severe consequences to the environment. In this study, the risks of three potential accident scenarios (i.e., maritime transportation, an aircraft crashing into an interim storage facility, and on-site transportation) associated with the spent fuel transportation process were analyzed using a probabilistic approach. For each scenario, the probabilities and the consequences were calculated separately to assess the risks: the probabilities were calculated using existing data and statistical models, and the consequences were calculated using computation models. Risk assessment software was developed to conveniently integrate the three scenarios. The risks were analyzed using the developed software according to the shipment route, building characteristics, and spent fuel handling environment. As a result of the risk analysis with varying accident conditions, transportation and storage strategies with relatively low risk were developed for regulators and licensees. The focus of this study was the risk assessment methodology; however, the applied model and input data have some uncertainties. Further research to reduce these uncertainties will improve the accuracy of this model.