• Title/Summary/Keyword: Flow Detection

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A Configurable Software-based Approach for Detecting CFEs Caused by Transient Faults

  • Liu, Wei;Ci, LinLin;Liu, LiPing
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.15 no.5
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    • pp.1829-1846
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    • 2021
  • Transient faults occur in computation units of a processor, which can cause control flow errors (CFEs) and compromise system reliability. The software-based methods perform illegal control flow detection by inserting redundant instructions and monitoring signature. However, the existing methods not only have drawbacks in terms of performance overhead, but also lack of configurability. We propose a configurable approach CCFCA for detecting CFEs. The configurability of CCFCA is implemented by analyzing the criticality of each region and tuning the detecting granularity. For critical regions, program blocks are divided according to space-time overhead and reliability constraints, so that protection intensity can be configured flexibly. For other regions, signature detection algorithms are only used in the first basic block and last basic block. This helps to improve the fault-tolerant efficiency of the CCFCA. At the same time, CCFCA also has the function of solving confusion and instruction self-detection. Our experimental results show that CCFCA incurs only 10.61% performance overhead on average for several C benchmark program and the average undetected error rate is only 9.29%. CCFCA has high error coverage and low overhead compared with similar algorithms. This helps to meet different cost requirements and reliability requirements.

Regularization Parameter Determination for Optical Flow Estimation using L-curve (L-curve를 이용한 광학 흐름 추정을 위한 정규화 매개변수 결정)

  • Kim, Jong-Dae;Kim, Jong-Won
    • The KIPS Transactions:PartB
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    • v.14B no.4
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    • pp.241-248
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    • 2007
  • An L-curve corner detection method is proposed for the determination of the regularization parameter in optical flow estimation. The method locates the positive peak whose curvature difference from the just right-hand negative valley is the maximum in the curvature plot of the L-curve. while the existing curvature-method simply finds the maximum in the plot. Experimental results show that RMSE of the estimated optical flow is greater only by 0.02 pixels-per-frame than the least in the average sense. The proposed method is also compared with an existing curvature-method and the adaptive pruning method, resulting in the optical flow estimation closest to the least RMSE.

Optimal Design of Sheath Flow Nozzle Acceleration Section for Improving the Focusing Efficiency (집속효율 향상을 위한 외장유동노즐 가속 구간의 최적설계 연구)

  • Lee, Jin-Woo;Jin, Joung-Min;Kim, Youn-Jea
    • Journal of the Korea Institute of Military Science and Technology
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    • v.22 no.6
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    • pp.763-772
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    • 2019
  • There is a need to use sheath flow nozzle to detect bioaerosol such as virus and bacteria due to their characteristics. In order to enhance the detection performance depending on nozzle parameters, numerical analysis was carried out using a commercial code, ANSYS CFX. Eulerian-lagrangian approach method is used in this simulation. Multiphase flow characteristics between primary fluid and solid were considered. The detection performance was evaluated based on the results of flow field in nozzle chamber such as focusing efficiency and swirl strength. In addition, Latin hypercube sampling(LHS) of design of experiment(DOE) was used for generating a near-random sampling. Then, the acceleration section is optimized using response surface method(RSM). Results show that the optimized model achieved a 6.13 % in a focusing efficiency and 11.47 % increase in swirl strength over the reference model.

Artificial Intelligence-based Leak Prediction using Pipeline Data (관망자료를 이용한 인공지능 기반의 누수 예측)

  • Lee, Hohyun;Hong, Sungtaek
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.26 no.7
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    • pp.963-971
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    • 2022
  • Water pipeline network in local and metropolitan area is buried underground, by which it is hard to know the degree of pipe aging and leakage. In this study, assuming various sensor combinations installed in the water pipeline network, the optimal algorithm was derived by predicting the water flow rate and pressure through artificial intelligence algorithms such as linear regression and neuro fuzzy analysis to examine the possibility of detecting pipe leakage according to the data combination. In the case of leakage detection through water supply pressure prediction, Neuro fuzzy algorithm was superior to linear regression analysis. In case of leakage detection through water supply flow prediction, flow rate prediction using neuro fuzzy algorithm should be considered first. If flow meter for prediction don't exists, linear regression algorithm should be considered instead for pressure estimation.

Performance Characteristics of In-Situ Particle Monitors at Sub-Atmospheric Pressure (감압상태에서의 In-Situ Particle Monitor의 성능특성)

  • Bae, Gwi-Nam
    • Transactions of the Korean Society of Mechanical Engineers B
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    • v.22 no.11
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    • pp.1564-1570
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    • 1998
  • In-situ particle monitors(ISPMs) are widely used for monitoring contaminant particles in vacuum-based semiconductor manufacturing equipment. In the present research, the performance of a Particle Measuring Systems(PMS) Vaculaz-2 ISPM at subatmospheric pressures has been studied. We created uniform upstream conditions of particle concentration and measured the detection efficiency, the lower detection limit, and the size response of the ISPM using uniform sized methylene blue aerosol particles. The effect of particle size, particle velocity, particle concentration, and system pressure on the detection efficiency was examined. Results show that the detection efficiency of the ISPM decreases with decreasing chamber pressure, and with increasing mass flow rate. The lower detection limit of the ISPM, determined at 50 % of the measured maximum detection efficiency, was found to be about $0.15{\sim}0.2{\mu}m$, which is similar to the minimum detectable size of $0.17{\mu}$ given by the manufacturer.

Responses of Artificial Flow-Sensitive Hair for Raider Detection via Bio-Inspiration (침입자 탐지용 인공 유동감지모의 응답 모델링)

  • Park, Byung-Kyu;Lee, Joon-Sik
    • Transactions of the Korean Society of Mechanical Engineers B
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    • v.34 no.4
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    • pp.355-364
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    • 2010
  • Filiform hairs that respond to movements of the surrounding medium are the mechanoreceptors commonly found in arthropods and vertebrates. In these creatures, the filiform hairs function as a sensory system for raider detection. Parametric analyses of the motion response of filiform hairs are conducted by using a mathematical model of an artificial flow sensor to understand the possible operating ranges of a microfabricated device. It is found that the length and diameter of the sensory hair are the major parameters that determine the mechanical sensitivities and responses in a mean flow with an oscillating component. By changing the hair length, the angular displacement, velocity, and acceleration could be detected in a wide range of frequencies. Although the torques due to drag and virtual mass are very small, they are also very influential factors on the hair motion. The resonance frequency of the hair decreases as the length and diameter of the hair increase.

A Review of Gas How Method for Permeability Measurement and Preform Defect Detection in Resin Transfer Molding (RTM 공정에서 기체 유동을 이용한 프리폼의 투과성계수 측정 및 결함탐지 기법에 관한 고찰)

  • Kim Sun Kyoung
    • Composites Research
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    • v.18 no.1
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    • pp.10-15
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    • 2005
  • It is useful to detect defects of a preform for resin transfer molding before and after placement into the mold. To conduct this test, the gas flow method has been developed. This method not only measures permeability but also detects defects utilizing the pressure readings obtained from the gas flow test. This paper introduces the methodology and examine the applicability to actual processes.

Hazard analysis and monitoring for debris flow based on intelligent fuzzy detection

  • Chen, Tim;Kuo, D.;Chen, J.C.Y.
    • Structural Monitoring and Maintenance
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    • v.7 no.1
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    • pp.59-67
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    • 2020
  • This study aims to develop the fuzzy risk assessment model of the debris flow to verify the accuracy of risk assessment in order to help related organizations reduce losses caused by landslides. In this study, actual cases of landslides that occurred are utilized as the database. The established models help us assess the occurrence of debris flows using computed indicators, and to verify the model errors. In addition, comparisons are made between the models to determine the best one to use in practical applications. The results prove that the risk assessment model systems are quite suitable for debris flow risk assessment. The reproduction consequences of highlight point discovery are shown in highlight guide coordinating toward discover steady and coordinating component focuses and effectively identified utilizing these two systems, by examining the variety in the distinguished highlights and the element coordinating.

The Implementing a Color, Edge, Optical Flow based on Mixed Algorithm for Shot Boundary Improvement (샷 경계검출 개선을 위한 칼라, 엣지, 옵티컬플로우 기반의 혼합형 알고리즘 구현)

  • Park, Seo Rin;Lim, Yang Mi
    • Journal of Korea Multimedia Society
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    • v.21 no.8
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    • pp.829-836
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    • 2018
  • This study attempts to detect a shot boundary in films(or dramas) based on the length of a sequence. As films or dramas use scene change effects a lot, the issues regarding the effects are more diverse than those used in surveillance cameras, sports videos, medical care and security. Visual techniques used in films are focused on the human sense of aesthetic therefore, it is difficult to solve the errors in shot boundary detection with the method employed in surveillance cameras. In order to define the errors arisen from the scene change effects between the images and resolve those issues, the mixed algorithm based upon color histogram, edge histogram, and optical flow was implemented. The shot boundary data from this study will be used when analysing the configuration of meaningful shots in sequences in the future.

Modelling Data Flow in Smart Claim Processing Using Time Invariant Petri Net with Fixed Input Data

  • Amponsah, Anokye Acheampong;Adekoya, Adebayo Felix;Weyori, Benjamin Asubam
    • International Journal of Computer Science & Network Security
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    • v.22 no.2
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    • pp.413-423
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    • 2022
  • The NHIS provides free or highly subsidized healthcare to all people by providing financial fortification. However, the financial sustainability of the scheme is threatened by numerous factors. Therefore, this work sought to provide a solution to process claims intelligently. The provided Petri net model demonstrated successful data flow among the various participant. For efficiency, scalability, and performance two main subsystems were modelled and integrated - data input and claims processing subsystems. We provided smart claims processing algorithm that has a simple and efficient error detection method. The complexity of the main algorithm is good but that of the error detection is excellent when compared to literature. Performance indicates that the model output is reachable from input and the token delivery rate is promising.