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检索条件"任意字段=Proceedings of the 9th Knowledge-Based Software Engineering Conference"

共 20293 条记录，以下是4811-4820 订阅

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VALIDATION OF A NUMERICAL MODEL FOR thE INVESTIGATION OF TENSION LEG PLATFORMS WIth MARINE ENERGY APPLICATION USING REEF3D 40

VALIDATION OF A NUMERICAL MODEL FOR THE INVESTIGATION OF TEN...

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40th ASME International conference on Ocean, Offshore and Arctic engineering (OMAE)

作者： Windt, Christian Goseberg, Nils Martin, Tobias Bihs, Hans Tech Univ Carolo Wilhelmina Braunschweig Leichtweiss Inst Hydraul Engn & Water Resources Braunschweig Germany Norwegian Univ Sci & Technol Dept Civil & Environm Engn Trondheim Norway

ISBN: (纸本)9780791885192

Exploiting the offshore wind resources using floating offshore wind systems at sites with deep water depths requires advanced knowledge of the system behaviour, including the hydro-, areo-, and mooring dynamics. To that end, high-fidelity numerical modelling tools, based on Computational Fluid Dynamics, can support the research and development of floating offshore wind systems by providing high-resolution data sets. this paper presents the first steps towards the numerical modelling of tension leg platforms for floating offshore wind applications using the open-source Computational Fluid Dynamics toolbox REEF3D. the numerical model of a taut-moored structure is validated against experimental reference data. Results from wave-only test cases highlight the simplicity and effectiveness of the wave generation method, implemented in REEF3D. For the considered wave-structure interaction cases, deviations between the experimental and numerical data can be observed for the surge and pitch displacements, while the heave displacement and the mooring forces are capture with sufficient accuracy. Overall, the numerical results indicate high potential of REEF3D to be used for the modelling of floating offshore wind systems

关键词： Computer simulation Ocean energy Tension-leg platforms Wind Ocean engineering Modeling Waves Mooring Computational fluid dynamics Displacement Resolution (Optics) Industrial research Dynamics (Mechanics) Surges Water

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Laser spot detection and characteristic analysis in plasma interaction simulation 14

Laser spot detection and characteristic analysis in plasma i...

引用

14th IADIS International conference Computer Graphics, Visualization, Computer Vision and Image Processing 2020, CGVCVIP 2020 and 5th IADIS International conference Big Data Analytics, Data Mining and Computational Intelligence 2020, BigDaCI 2020 and 9th IADIS International conference theory and Practice in Modern Computing 2020, TPMC 2020, Part of the 14th Multi conference on Computer Science and Information Systems, MCCSIS 2020

作者： Ai, Zhiwei Cao, Yi Wang, Huawei Xiao, Li Institute of Applied Physics and Computational Mathematics Beijing 100094 China CAEP Software Center for High Performance Numerical Simulation Beijing 100088 China

ISBN: (纸本)9789898704214

the analysis of beam divergence mechanism during laser plasma propagation is one of the hot topics research. Among them, laser spot detection and characteristic analysis is one of the important indicators to evaluate the energy distribution of the exit surface of the propagation system. the channel environmental factors during the plasma laser transmission are complex and changeable. this scene will cause distortion of the laser spot, making it difficult to achieve spot detection and precise analysis of characteristics. this paper presents a novel visual analysis method to study the beam divergence mechanism. First, the dynamic threshold segmentation method is used to analyze the numerical simulation data to generate a laser spot image. Second, the use of image edge detection technology to achieve spot contour drawing based on image pixels. the above two key technologies have been applied to the accurately positioning of the spot contour and the analysis of the spatial distribution characteristics of the spot. Experiments show that this technique is helpful to verify the correctness of the physical model of the laser plasma interaction simulation program, and is also effective. © proceedings of the 14th IADIS International conference Computer Graphics, Visualization, Computer Vision and Image Processing 2020, CGVCVIP 2020 and proceedings of the 5th IADIS International conference Big Data Analytics, Data Mining and Computational Intelligence 2020, BigDaCI 2020 and proceedings of the 9th IADIS International conference theory and Practice in Modern Computing 2020, TPMC 2020 - Part of the 14th Multi conference on Computer Science and Information Systems, MCCSIS 2020. All rights reserved.

关键词： Numerical methods

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A Comprehensive Study on Challenges in Deploying Deep Learning based software 2020

A Comprehensive Study on Challenges in Deploying Deep Learni...

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28th ACM Joint Meeting on European software engineering conference and Symposium on the Foundations of software engineering (ESEC/FSE)

作者： Chen, Zhenpeng Cao, Yanbin Liu, Yuanqiang Wang, Haoyu Xie, Tao Liu, Xuanzhe Peking Univ MoE Key Lab High Confidence Software Technol Beijing Peoples R China Beijing Univ Posts & Telecommun Beijing Peoples R China

ISBN: (纸本)9781450370431

Deep learning (DL) becomes increasingly pervasive, being used in a wide range of software applications. these software applications, named as DL based software (in short as DL software), integrate DL models trained using a large data corpus with DL programs written based on DL frameworks such as TensorFlow and Keras. A DL program encodes the network structure of a desirable DL model and the process by which the model is trained using the training data. To help developers of DL software meet the new challenges posed by DL, enormous research efforts in software engineering have been devoted. Existing studies focus on the development of DL software and extensively analyze faults in DL programs. However, the deployment of DL software has not been comprehensively studied. To fill this knowledge gap, this paper presents a comprehensive study on understanding challenges in deploying DL software. We mine and analyze 3,023 relevant posts from Stack Overflow, a popular Q&A website for developers, and show the increasing popularity and high difficulty of DL software deployment among developers. We build a taxonomy of specific challenges encountered by developers in the process of DL software deployment through manual inspection of 769 sampled posts and report a series of actionable implications for researchers, developers, and DL framework vendors.

关键词： deep learning software deployment Stack Overflow

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the Intelligent Technology of Integrated Expert Systems Construction: Specifics of the Ontological Approach Usage 4th

The Intelligent Technology of Integrated Expert Systems Cons...

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4th International Scientific conference on Intelligent Information Technologies for Industry (IITI)

作者： Rybina, Galina, V Fontalina, Elena S. Sorokin, Ilya A. Natl Res Nucl Univ MEPhI Moscow Russia

ISBN: (纸本)9783030500979

this paper studies the results of developing the basic components of the AT-TECHNOLOGY workplace intelligent software environment, predetermined for automation and rendering of intelligent processes for building integrated expert systems (IES), based on a problem-oriented methodology. the article itself presents a review of the scientific, methodological and technological experience in the implementation and use of IES training. Also, the creation of a single ontological space of knowledge and skills for the automated creation of competence-based models of experts in the field of methods and technologies of artificial intelligence in the field of training in the object of study "software engineering", obtained at the Department of Cybernetics NRNU MEPhI.

关键词： Intelligent software environment AT-TECHNOLOGY workbench Tutoring integrated expert systems Problem-oriented methodology Intellectual training

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A Real-Time Approach based on Deep Learning for Ego-Lane Detection 9

A Real-Time Approach Based on Deep Learning for Ego-Lane Det...

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9th International Japan-Africa conference on Electronics, Communications, and Computations, JAC-ECC 2021

作者： Yousri, Yousri Mostafa, Mohamed Yasser, Rawane Shawki, Mahmoud Khaled, Ahmed Mostafa, Ziad Soltan, Ahmed Darweesh, M. Saeed Giza12677 Egypt Nile University School of Engineering and Applied Sciences Giza12677 Egypt Nile University Giza12677 Egypt

ISBN: (纸本)9781665482929

Lane detection has been one of the most important tasks of autonomous driving vehicles. the main objective of lane detection is tracking the lane boundaries on a real-time basis. Recently, many researches have shown deep learning models that are capable of detecting road lanes robustly. Yet, providing testing results in the context of real-time is not commonly found. this paper aims to provide a comprehensive real-time evaluation for performing ego-lane detection based on deep learning. the lane detection is recognized here as a semantic segmentation task where a pre-trained ResUNet++ model is adopted from a prior study. the real-time evaluation approaches include testing driving video sequences, CARLA simulator environment, and finally, a hardware kit that runs the deep learning model on the NVIDIA Jetson Nano developer kit. the performance of the model was investigated in various complex environments and dynamic scenarios. Eventually, the experimental results were qualitatively and quantitatively evaluated, showing reliability and promptness of using deep learning models for the lane detection task in a real-time context. © 2021 IEEE.

关键词： Semantic Segmentation

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Numerical simulation of water hammer characteristics in the closing process of electric globe valve based on CFD

Numerical simulation of water hammer characteristics in the ...

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International conference on Fluid Power and Mechatronics (FPM)

作者： Zhenwang Jia Longlong Gao Zhixin Zhao Baoren Li School of Mechanical Science & Engineering Huazhong University of Science & Technology Wuhan China

ISBN: (数字)9798350304947

ISBN: (纸本)9798350304954

the electric globe valve is an important control element in the automatic water injection drainage system. the system requires the closing time of the electric globe valve to be less than 1s. However, the rapid closing of the globe valve may cause the water hammer phenomenon in the pipeline, which will lead to large mechanical vibration noise in the pipeline. Most of the traditional research only focuses on pipeline systems and carry out one-dimensional calculation based on the method of characteristic, while ignoring the influence of the two-dimensional characteristic of fluid flow and the internal flow structure of the valve on the water hammer phenomenon. In this paper, CFD technology and Fluent software are used to build the flow field simulation model of the electric globe valve, and the dynamic flow field simulation of the closing process of the electric globe valve is completed. the influence of inlet pressure, valve closing velocity, and valve closing motion law on the water hammer effect is obtained. the results show that the pressure pulsation amplitude caused by rapid valve closing can be effectively reduced by reducing the inlet pressure when the valve closing velocity is constant. When the inlet pressure and the valve closing velocity are constant, the maximum water hammer pressure can be effectively reduced by reducing the valve closing velocity. When the valve is closed for a certain time, the fast at first and then slow closing motion law can effectively reduce the maximum water hammer pressure. the research results can provide a reference for the design of the control law of the valve closing process in automatic injection drainage systems.

关键词： Water Vibrations Pipelines Dynamics Process control Valves Numerical simulation

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Research on Performance Optimization Scheme for Web Front-End and Its Practice 9th

Research on Performance Optimization Scheme for Web Front-En...

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9th International conference on Communications, Signal Processing, and Systems, CSPS 2020

作者： Yan, Fenglong Xu, Zhao Zhong, Yu Shan HaiBei, Zhang Ge, Chang Yun School of Computer and Software Neusoft University of Information Dalian China

ISBN: (纸本)9789811584107

this paper focuses on the performance optimization of web front-end, proposing an optimization scheme of the system from the front end. It takes an information management website as an example, proposes a set of systematic, practical and operable website performance optimization solution based on web services. the solution includes loading external CDN resources, optimising component packaging process, lazy loading in route, Qiniu cloud acceleration, file compression, etc. It can improve the usability and performance of web application system, so as to improve the satisfaction of users through the optimization. At the end of the project, the comparative analysis results of website access performance before and after optimization are listed. the result shows that the size of top 5 resources reduced form 20 Mb to 79.7 kb. the image size can be reduce 94.3%, and the loading time can be reduced greatly, which decrease from the initial 25.27 s to the final 0.3 s. © 2021, the Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Web services

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Image processing techniques for fast and accurate estimation of pose of a double pendulum 14

Image processing techniques for fast and accurate estimation...

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作者： Haris, Muhammad Memon, Junaid Ahmed Farhan, Muhammad School of Science and Engineering Habib University Karachi Sindh75290 Pakistan

ISBN: (纸本)9789898704214

Double pendulum exhibits a rich dynamic behavior and is often used to study nonlinear dynamics, instability, and chaos. In order to devise a method for its control, the angles and the angular velocities of its two arms need to be measured accurately with sufficiently fast sampling rate. Generally, encoders and other sensors are used which are costly, difficult to install for custom built pendulums, and require continuous calibration to measure the angles. therefore, in this paper we present a comparison of four image processing based methods to estimate the angles of double pendulum. the first two methods are widely used involving variants of Canny edge detection in conjunction with Hough transform. the third method extracts the skeleton of the thresholded pendulum and then applies Hough transform on the skeleton to compute the angles. the fourth method, never before used for double pendulum, segments the pendulum arms and uses basic matrix operations to extract the angles. the results focus on the speed-accuracy-memory tradeoff for all the methods and manifest that the fourth method is satisfactorily accurate with minimum computational complexity and memory usage. © proceedings of the 14th IADIS International conference Computer Graphics, Visualization, Computer Vision and Image Processing 2020, CGVCVIP 2020 and proceedings of the 5th IADIS International conference Big Data Analytics, Data Mining and Computational Intelligence 2020, BigDaCI 2020 and proceedings of the 9th IADIS International conference theory and Practice in Modern Computing 2020, TPMC 2020 - Part of the 14th Multi conference on Computer Science and Information Systems, MCCSIS 2020. All rights reserved.

关键词： Hough transforms

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Learning interpretable and statistically significant knowledge from unlabeled corpora of social text messages: A novel methodology of descriptive text mining 9

Learning interpretable and statistically significant knowled...

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9th International conference on Data Science, Technology and Applications, DATA 2020

作者： Frisoni, Giacomo Moro, Gianluca Carbonaro, Antonella Department of Computer Science and Engineering – DISI University of Bologna Via dellUniversità 50 CesenaI-47522 Italy

ISBN: (纸本)9789897584404

though the strong evolution of knowledge learning models has characterized the last few years, the explanation of a phenomenon from text documents, called descriptive text mining, is still a difficult and poorly addressed problem. the need to work with unlabeled data, explainable approaches, unsupervised and domain independent solutions further increases the complexity of this task. Currently, existing techniques only partially solve the problem and have several limitations. In this paper, we propose a novel methodology of descriptive text mining, capable of offering accurate explanations in unsupervised settings and of quantifying the results based on their statistical significance. Considering the strong growth of patient communities on social platforms such as Facebook, we demonstrate the effectiveness of the contribution by taking the short social posts related to Esophageal Achalasia as a typical case study. Specifically, the methodology produces useful explanations about the experiences of patients and caregivers. Starting directly from the unlabeled patients posts, we derive correct scientific correlations among symptoms, drugs, treatments, foods and so on. Copyright © 2020 by SCITEPRESS – Science and Technology Publications, Lda. All rights reserved.

关键词： Semantics

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Multi-Task Learning with Convolutional Neural Network Approach for Packet Collision Avoidance in 802.11 WLAN

Multi-Task Learning with Convolutional Neural Network Approa...

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National Foundation for Science and Technology Development conference on Information and Computer Science (NICS)

作者： Dody Ichwana Putra Harry Bintang Pratama Tomoki Nakashima Yuhei Nagao Masayuki Kurosaki Hiroshi Ochi Grad. School of Computer Science and System Engineering Kyushu Institute of Technology Iizuka Japan

Packet collision can degrade wireless network performance. the IEEE 802.11 Wireless Local Area Network (WLAN) uses the Clear Channel Assessment (CCA) mechanism to monitor channel availability to avoid interference of the presence signal. CCA successfully detects 802.11 signals if it obtains the packet preamble information or detects the threshold ambient power on the channel to determine the channel state. this paper proposes multi-task learning (MTL) with convolutional neural network (CNN) approach to detect WLAN packet formats and modulation types without preamble part information as a supplement to enhance CCA sensitivity. the main advantages of this method over single-task training are high classification accuracy and rapid learning with a lightweight neural network model. Shared knowledge of representation layers, such as model weights or gradients, improves the efficiency of training data and reduces redundancy. WLAN signals generated by the Matlab waveform simulator are used to verify the accuracy of the proposed method, which is then implemented on a real-time SDR-based hardware testbed. Although different time offsets affect the classifications, the proposed method proves superior in classifying the packet format and modulation of WLAN signals with an accuracy of 98.93% and 88.53% at SNR = 24 dB, respectively. the proposed method improves channel utilization and throughput of the WLAN network, as demonstrated by an NS-3 simulation.

关键词： Wireless LAN Sensitivity Computational modeling Modulation Multitasking Mathematical models Hardware

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