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检索条件"任意字段=7th International Conference on the Art, Science, and Engineering of Programming, Programming 2023"

共 1136 条记录，以下是1011-1020 订阅

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Welcome to the Seventh international Workshop on Crowd-Based Requirements engineering (CrowdRE'23)

Welcome to the Seventh International Workshop on Crowd-Based...

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IEEE international Requirements engineering conference Workshops (REW)

作者： Oliver Karras Irit Hadar Muneera Bano James Tizard TIB – Leibniz Information Centre for Science and Technology Hannover Germany University of Haifa Carmel Mount Israel Data61 - CSIRO Melbourne Australia University of Auckland Auckland New Zealand

Welcome to the 7th international Workshop on Crowd-Based Requirements engineering (CrowdRE'23), where scientists and representatives of industry meet to exchange ideas, experiences, and other contributions regarding the state of the art of Crowd-Based Requirements engineering (CrowdRE). the discipline of CrowdRE seeks to address the challenges of traditional requirements engineering (RE) in scaling up to settings with thousands to millions of users of (software) products or (software-driven) services, who form a large and heterogeneous group that can be denoted as a ‘crowd’ [1], [2]. the user feedback generated by the crowd, such as texts or usage data, can be a valuable source of requirements, problems, wishes, and needs. Responding quickly, effectively, and iteratively to this feedback can greatly increase a product's success. CrowdRE comprises any approach that provides RE with suitable means for this crowd paradigm, especially by involving the crowd and by collecting, harmonizing, analyzing, and Interpreting their user feedback.

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Automatic Speed Measurement and License Plate Reader for Motor Vehicles using CNN

Automatic Speed Measurement and License Plate Reader for Mot...

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international conference of Electronics, Communication and Aerospace Technology (ICECA)

作者： D. Poornima N. Gopinath L Harish Manju Santosh Kumar C. Tamilselvi Department of Computer and Science Engineering Sathyabama Institute of Science and Technology Tamil Nadu India Department of Computer Science Engineering B. S. Abdur Rahman Crescent Institute of Science and Technology Tamil Nadu India Department of Information Science and Engineering CMR Institute of Technology Karnataka India Department of Electrical Engineering Government Engineering College Bihar India Department of Electrical and Electronics Engineering Gaya Colleg of Engineering Bihar India Department of Information Technology Dr. MGR Educational and Research Institute Tamil Nadu India

Assessing traffic surveillance data is a prevalent utilization of deep learning methodologies. Video processing techniques were employed to develop the system aimed at determining the velocity of vehicles. the analysis of video speed is conducted without the requirement of camera calibration. Frame subtraction and masking techniques are employed to effectively segregate moving vehicles. the suggested system comprises four primary components. Object detection techniques are employed in the initial phase to identify and locate moving vehicles within a given footage. Real-time vehicle recognition leverages the utilization of R-CNN and deep learning techniques. In the subsequent section, algorithms are employed to observe the movement of objects within individual video frames. Optical flow methods are employed in the third segment to ascertain the velocities of the respective vehicles. In the preceding part, the proposed work have utilized image processing techniques in conjunction with deep learning methodologies to accurately decipher the license plates of the automobiles under our surveillance. the experimental evaluation involving the utilization of traffic film demonstrated a system performance of 97% in precisely quantifying speed while achieving a license plate identification accuracy of 95%. the incorporation of state-of-the-art traffic management systems has facilitated the implementation of real-time speed monitoring and license plate reading capabilities. this facilitates the deterrence of automobile theft and the implementation of traffic regulations. Additionally, the methodology has the capability to identify traffic patterns and pinpoint regions of congestion, thus assisting in the effective management of traffic.

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Query rewriting under ontology contraction 6th

Query rewriting under ontology contraction

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6th international conference on Web Reasoning and Rule Systems, RR 2012

作者： Tsalapati, Eleni Stoilos, Giorgos Stamou, Giorgos Koletsos, George School of Electrical and Computer Engineering National Technical University of Athens Zographou Campus Athens15780 Greece

ISBN: (纸本)9783642332029

Conjunctive query (CQ) answering is a key reasoning service for ontology-based data access. One of the most prominent approaches to conjunctive query answering is query rewriting where a wide variety of systems has been proposed the last years. All of them accept as input a fixed CQ q and ontology O and produce a rewriting for q,O. However, in many real world applications ontologies are very often dynamic—that is, new axioms can be added or existing ones removed frequently. In this paper we study the problem of computing a rewriting for a CQ over an ontology that has been contracted (i.e., some of its axioms have been removed) given a rewriting for the input CQ and ontology. Our goal is to compute a rewriting directly from the input rewriting and avoid computing one from scratch. We study the problem theoretically and provide sufficient conditions under which this process is possible. Moreover, we present a practical algorithm which we implemented and evaluated against other state-of-the-art systems obtaining encouraging results. Finally, axiom removal can also be relevant to ontology design. For each test ontology we study how much the removal of an axiom affects the size of the rewriting and the performance of systems. If the removal of a single axiom causes a significant decrease either in the size or in the computation time then this part of the ontology can be re-modelled. © Springer-Verlag Berlin Heidelberg 2012.

关键词： Ontology

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A Precision-Compensated Linear Power Flow Model Based on Mapping Voltage Magnitudes from Logarithmic Space to Squared Space

A Precision-Compensated Linear Power Flow Model Based on Map...

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IEEE international conference on Power and Energy Applications (ICPEA)

作者： Haipeng Lai Zhigang Li Jiahui Zhang Xiang Bai Huajian Li Hongyuan Liang J. H. Zheng School of Electric Power Engineering South China University of Technology Guangzhou China School of Science and Engineering The Chinese University of Hong Kong Shenzhen Shenzhen China Shanxi Energy Internet Research Institute Taiyuan China

ISBN: (数字)9798350356113

ISBN: (纸本)9798350356120

Linear power flow is widely applied in various areas of power systems. the DC power flow model is a classical linear power flow model, but its main limitation is the inability to account for voltage magnitude. Other classical models that consider voltage magnitude are typically linearized in the original voltage magnitude space, leading to a computational accuracy bottleneck. To address this issue, this study first proposes an improved linear power flow model. the model remaps the voltage magnitude from logarithmic space to square space, preserving the nonlinear characteristics of the original current equation and compensating for the voltage phase angle. this approach overcomes the accuracy bottleneck of classical models. then, through matrix partitioning and transformation, the model achieves complete decoupling of the voltage magnitude and phase angle, avoiding nonconvex quadratic programming problems in optimization and enhancing computational efficiency. Finally, the accuracy and speed of the proposed model are validated through simulations across multiple test systems.

关键词： Visualization Accuracy Computational modeling Voltage Mathematical models Numerical models Power systems Quadratic programming Optimization Load flow

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FASTER SEAM CARVING FOR VIDEO RETARGETING

FASTER SEAM CARVING FOR VIDEO RETARGETING

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IEEE international conference on Image Processing

作者： Chenyang Li Ruimin Hu Chao Liang Chunxia Xiao Weijian Ruan National Engineering Research Center for Multimedia Software Wuhan University China Collaborative Innovation Center of Geospatial Technology China School of Computer Science Wuhan University China

Video retargeting is to resize a video to a desired resolution or aspect ratio while preserving its salient content without visual distortion. the key to video retargeting is to reconcile spatio-temporal coherence of video frames, and most existing works use seam carving to achieve that by employing the dynamic programming to find optimal seams. However, these methods are too time-consuming due to high computational complexity of the dynamic programming. To this end, we propose a novel method which uses discontinuous and sub-optimal seams for seam carving. Concretely, we obtain the discontinuous seams by allowing seams to move freely in homogeneous regions of the frame, which helps preserve the spatio-temporal coherence effectively. then, the genetic algorithm is employed to find suboptimal seams, so as to reduce computational complexity. Finally, each frame can be retargeted to a new aspect ratio or size by repeatedly carving out seams. Compared to the-state-of-the-art methods, the proposed algorithm achieves comparable results at an average expense of only one third of their running time.

关键词： Coherence Genetic algorithms Computational complexity Spatial coherence Sociology Statistics Visualization

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Step-Based Carbon Trading Model for the thermal-Electric Optimization of Integrated Energy Systems Considering the Correlation Between Wind and PV

Step-Based Carbon Trading Model for the Thermal-Electric Opt...

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IEEE conference on Energy Internet and Energy System Integration (EI2)

作者： Fu Shen Yutao Zhang Fang Zeng Guangbing Yang Chong Wang Suwei Zhai Faculty of Electric Power Engineering Kunming University of Science and Technology Kunming China College of Energy and Electrical Engineering Hohai University Nanjing China China Electric Power Research Institute Yunnan Power Grid Company Ltd. Kunming China

the uncertainty and correlation of wind and PV power have significant impacts on the operational mode and energy utilization efficiency of integrated energy systems (IESs). It is necessary to optimize the operational flexibility of IESs equipment to lower the carbon emission (CE) levels of the IESs. this paper proposed a step-based carbon trading model for the thermal-electric optimization of IESs considering the correlation between wind and PV. Firstly, Latin Hypercube Sampling (LHS) method is used to sample random variables and generate scenarios that satisfy specific wind power and PV correlations to study the influence of wind and photovoltaic correlation on optimization scheduling. then, a step-based carbon trading model is introduced to optimize the carbon emission control strategy considering the participation of IESs in the carbon trading market. thirdly, an adjustable thermal-electric ratio for combined heat and power (CHP) and hydrogen fuel cell (HFC) operational strategies are formed to enhance the low-carbon and economic performance of IESs. And an economic objective function is formulated by minimizing the purchasing cost, CE cost, wind curtailment cost, and PV curtailment cost, which is transformed into a mixed-integer linear programming problem, worked using the CPLEX commercial solver. Finally, the multiple operating scenarios simulation results validate the effectiveness and accuracy of the proposed optimization strategies.

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Uncertainty and computer assisted problem solving environment (PSE) in scientific computing

Uncertainty and computer assisted problem solving environmen...

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international conference on Computer sciences and Convergence Information Technology (ICCIT)

作者： Shigeo Kawata Takashi Ishihara Daisuke Barada Wu Zhang Jiang Xie Hitohide Usami Takayuki Teramoto Masami Matsumoto Yasuhiko Manabe Yoshikazu Hayase Tae Whan Kim School of Computer Engineering and Science Shanghai University Shanghai China Department of Advanced Interdisciplinary Sciences Utsunomiya University Utsunomiya Japan Tamagawa university Machida Japan Tsuyama National College of Technology Tsuyama Japan Yonago National College of Technology Yonago Japan Numazu National College of Technology Numazu Japan Toyama National College of Technology Toyama Japan Hanyang University Seoul South Korea

ISBN: (纸本)9781467308946

Uncertainty in scientific computing is discussed in this paper. Uncertainty comes from various sources, for example, from physical model uncertainty, mathematical model errors, unknown input data, numerical model errors, insufficient numerical precision, round-off error, floating point precision, programming errors, data processing errors or uncertainty, visualization errors, etc., as well as human errors concerned. the uncertainty in scientific computing has induced serious accidents or disasters, so far. the uncertainty in scientific computing must be managed to avoid serious accidents and disasters, and also to obtain reasonable or precise scientific results for discoveries and scientific progresses. the uncertainty management is a hard job in scientific computing. On the other hand, studies on problem solving environments (PSEs) have been explored to enhance programming power and to help users to solve problems using computers. PSE is defined as “a system that provides all the computational facilities necessary to solve a target class of problems. It uses the language of the target class and users need not have specialized knowledge of the underlying hardware or software”. the uncertainty management could be supported by the concept of PSE. In this paper first we discuss on the uncertainty properties and their origin in scientific computing. then discussed is how to support the uncertainty management by the PSE concept.

关键词： Scientific Computing PSE (problem Solving Environment) Uncertainty Validation Verification Scientific computing Uncertainty Verification model error

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Advancing Residential Energy Management: Integrating Renewable Resources and Vehicle-to-Grid Systems for Optimized Electrical Grid Performance

Advancing Residential Energy Management: Integrating Renewab...

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international conference on Contemporary Computing and Informatics (IC3I)

作者： Rakesh Chandrashekar D Shobha Rani Ginni Nijhawan A Balaram Prateek Chaturvedi B Sankara Babu Department of Mechanical Engineering New Horizon College of Engineering Bangalore Karnataka India Department of Electrical and Electronics Engineering Institute of Aeronautical Engineering Hyderabad Telangana India Lovely Professional University Phagwara Punjab India Department of Computer Science & Engineering MLR Institute of Technology Hyderabad Telangana India Amity School of Engineering and Technology Amity University Greater Noida Uttar Pradesh India Department of Computer Science and Engineering GRIET Bachupally Hyderabad India

ISBN: (数字)9798350350067

ISBN: (纸本)9798350350074

the term “smart grid” describes the future generation of electrical power networks, which are very complicated systems. It must take into account all aspects of the electrical system, increasing its intelligence and adaptability. In response to shifts in the electrical market, this idea is put out with the intention of controlling the rising demand while guaranteeing higher service quality and enhanced safety. this research presents an urban scenario that incorporates dispersed energy sources into a smart grid. the research incorporates renewable energy sources like solar panels and tiny windmills into the system, as well as battery storage and grid-connected vehicles that can power the electrical grid by drawing electricity from the storage device. So, to maximize the energy production and absorption systems as well as the recharging and discharging time for a home user’s electric car, a mixed integer linear programming is proposed. Additionally, a number of case studies are provided by changing important variables using the Taguchi technique of design of experiments in order to identify the best solution and demonstrate how each influences the system’s complexity.

关键词： Vehicle-to-grid Renewable energy sources Electricity Production Safety Mixed integer linear programming Solar panels Informatics Energy management Optimization

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A Priority based Energy Aware Routing Algorithm for SDN Enabled Data Center Network

A Priority based Energy Aware Routing Algorithm for SDN Enab...

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Sustainable Technologies for Industry 4.0 (STI), international conference on

作者： Md. Naimul Pathan Maisha Muntaha Abida Sultana Selina Sharmin Sajeeb Saha Dept of Computer Science and Engineering Green University of Bangladesh Dhaka Dept of Computer Science and Engineering Jagannath University Bangladesh

Recently the number of data centers has increased tremendously to transport and manage the massive volume of data generated from various sources. As the network devices in data centers continue to increase at an alarming rate hence the need for efficient routing to handle this vast amount of data has emerged as a major concern. this increase in data flow adds many devices that consume a major portion of energy. As a result, maintaining the importance of data flow, and energy conservation are the critical considerations for an efficient routing path. Recently, SDN (Software Defined Network) has been used to improve the performance of DCN (Data Center Network) by reducing the amount of physical infrastructure required. this work proposes a novel admission and routing scheme that considers arbitrarily assigned priorities for network flows and path energy for data packet transmissions. Using the SDN paradigm in DCN, we attempt to maximize the number of flows as well as minimize the energy consumption in the network. For this, a MILP (Mixed Integer Linear programming) problem is formulated by jointly considering flow priority and path energy. Later, we introduce a greedy method named Priority Based Energy Minimization Algorithm (PEMA) to maximize the flow and minimize the energy as much as possible. Finally, the performance of the routing strategy is observed by comparing it with stat-of-the-art works..

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Scalable Tree Goal Prediction Based on Decision Interactions

Scalable Tree Goal Prediction Based on Decision Interactions

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conference on Vehicle Control and Intelligence (CVCI)

作者： Linhui Li Jiazheng Su Jing Lian School of Automotive Engineering Dalian University of Technology Dalian China

the road conditions for vehicle movement in urban intersection scenarios are complex. Autonomous vehicles must be able to effectively infer the goals of other vehicles to make reasonable decisions to complete the driving task. Considering the difficulty and specificity of inferring vehicle behavior in different scenarios, it is a challenge to predict the goals of vehicles in an accurate, interpretable and scalable way. Accordingly, this paper proposes a decision interaction based extensible tree (DIET), a scalable goal prediction system. DIET extracts common semantic features from road and vehicle information in the scenario, and extends the feature space and eliminates errors arising from simple behavioral inference by analyzing the decision interactions between surrounding vehicles. Extensive comparative experiments have been conducted on the proposed DIET and several other typical related works under different scenarios. the model reported in this paper outperforms state-of-the-art methods by 10.9% in accuracy of new scene predictions. Clearly, DIET is able to more accurately predict the vehicle's goal in different scenarios, and the process is interpretable.

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