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共 1802 条记录，以下是111-120 订阅

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Heterogeneous Green Vehicle Routing Problem with Different Customer Service Requirements 2

Heterogeneous Green Vehicle Routing Problem with Different C...

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2nd international conference on Machine Learning, Control, and Robotics, MLCR 2023

作者： Meng, Xianghu Lin, Zihan Tang, Jing Anhui University of Technology Department of Electrical and Information Engineering Maanshan China

ISBN: (纸本)9798350381245

The Green Vehicle Routing Problem (GVRP) is a challenging combinatorial optimization problem to optimize delivery routes while minimizing adverse environmental impacts. A Heterogeneous Green Vehicle Routing Problem with Different Customer Service Requirements (HGVRP-CSR) is presented in this paper, and it deals with three objectives to minimize vehicle traveling cost, and carbon emission cost and maximize customer satisfaction simultaneously. In this work, we propose a mixed integer linear programming model for HGVRP-CSR and present a Hybrid Variable Neighborhood Search (HVNS) combining two stages of heuristic operations. In HVNS, a Hungarian algorithm and a hierarchical clustering are conducted in the initialization stage to generate better initial solutions, and to enhance its search capabilities, four Neighborhood transformation operations are adopted, i.e., single-point insertion, two-point exchange, two-segment exchange, and 2-opt. The comprehensive experiments are performed on problems of different sizes to verify the effectiveness and efficiency of HVNS. The comparative results show that HVNS is more effective than the other two algorithms. © 2023 IEEE.

关键词： Customer satisfaction

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Research on IIVIFM Model for Batch Processing of Fiber Optic Logging Data 24

Research on IIVIFM Model for Batch Processing of Fiber Optic...

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2024 2nd international conference on Internet of Things and Cloud Computing Technology, IoTCCT 2024

作者： Qin, Minjun Liu, Dongming Pei, Yang Wang, Zhixing Li, Bing Cao, Juan Song, Wenguang Changqing Division of China Petroleum Logging Co. Ltd. Xi'an China School of Computer Science and Engineering Guangdong Ocean University Yangjiang China

ISBN: (纸本)9798400710148

Fiber optic can not only be used as a data transmission device, but also as a signal acquisition device. Research on fiber optic data acquisition for temperature and sound signals (DTS&DAS) has been widely carried out both domestically and internationally, but it has been hindered by numerous interference signals, massive data volume, and slow signal processing speed, which have become a bottleneck in the application of fiber optic DTS&DAS. The article proposes an integrated batch processing oriented big data retrieval and filtering model, IIVIFM, for the first time to address the difficult problem of fiber optic DTS&DAS big data processing in the development process of oil and gas fields. This model achieves batch processing of DTS&DAS data and can effectively filter the data. Finally, through software programming, this method was implemented, enabling it to be widely promoted and applied, providing a new approach for oil and gas data analysis. © 2024 Copyright held by the owner/author(s).

关键词： Gas industry

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Three Sources of Blockchain Technology Vulnerabilities-how to Deal with them? 2

Three Sources of Blockchain Technology Vulnerabilities-how t...

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2nd international conference on Computer science, engineering and Applications, ICCSEA 2022

作者： Kustov, Vladimir Aleksey, Grokhotov Nikolay, Beksaev Ekaterina, Selanteva Ravi, Renjith V. Saint Petersburg Railway Transport University of Emperor Alexander I Informatics and Information Security Department Saint Petersburg Russia M.E.A Engineering College Department of Electronics and Communication Engineering Kerala India

ISBN: (数字)9781665458344

ISBN: (纸本)9781665458344

The authors consider the problem of ensuring the security of smart contracts. The relevance of research is associated with a growing field of threats, an increase in economic risks, and the absence or insufficiency of the necessary tools to ensure the security of smart contracts. The authors begin the study by classifying the sources of vulnerabilities in smart contracts. The authors distinguish three groups: the disadvantages and limitations of the programming languages of smart contracts, the weaknesses of the blockchain technology itself, and the penalties associated with the misunderstanding or incorrect application of accepted programming methods. The authors provide a detailed classification of the vulnerabilities of smart contracts. Further, the authors show the need to use static code analyzers of smart contracts and their automation using static code analyzers of smart contracts. The final part discusses the results of an experiment to study the effectiveness of using static analyzers to improve the security of smart contracts. © 2022 IEEE.

关键词： Smart contract

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2nd international conference on Bridging the Gap Between AI and Reality, AISoLA 2024

2nd International Conference on Bridging the Gap Between AI ...

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2nd international conference on Bridging the Gap Between AI and Reality, AISoLA 2024

ISBN: (纸本)9783031754333

The proceedings contain 28 papers. The special focus in this conference is on Bridging the Gap Between AI and Reality. The topics include: Responsible and Trusted AI: An Interdisciplinary Perspective;team Design Patterns for Meaningful Human Control in Responsible Military artificial Intelligence;transparent Transparency Developing a Scheme for Understanding Transparency Requirements;AI Act for the Working Programmer;AI Assisted programming: (AISoLA 2024 Track Introduction);SEGym: Optimizing Large Language Model Assisted Software engineering Agents with Reinforcement Learning;Towards Specification-Driven LLM-Based Generation of Embedded Automotive Software;proof Repair Utilizing Large Language Models: A Case Study on the Copland Remote Attestation Proofbase;LLM-Based Scheme for Synthesis of Formal Verification Algorithms;verification and Learning for Assured Autonomy;a Comparison of Monitoring Techniques for Deep Neural Networks;efficient Shield Synthesis via State-Space Transformation;Runtime Verification and AI: Addressing Pragmatic Regulatory Challenges;A Game-Based Semantics for the Probabilistic Intermediate Verification Language HeyVL;Systematic Translation from Natural Language Robot Task Descriptions to STL;it’s Safe to Play While Driving: From a Spatial Traffic Logic Towards Traffic Games;monitoring Safety and Reliability of Underwater Robots: A Case Study;statistical Model Checking the 2024 Edition!;Reinforcement Learning for Discretized Euclidean MDPs;adaptive Stopping Algorithms Based on Concentration Inequalities;digging for Decision Trees: A Case Study in Strategy Sampling and Learning;statistical Analysis of the Impact of Bit-Flips in Security Critical Code;statistical Model Checking of Python Agent-Based Models: An Integration of MultiVeStA and Mesa;On SMC-Based Dependability Analysis in LoLiPoP-IoT Project;Towards Verifying Robotic Systems Using Statistical Model Checking in STORM.

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Students Performance Monitoring and Customized Recommendation Prediction in Learning Education using Deep Learning 2

Students Performance Monitoring and Customized Recommendatio...

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2nd IEEE international conference on Distributed Computing and Electrical Circuits and Electronics, ICDCECE 2023

作者： Sharma, Vivek Kumar Goel, Amit Kumar Noida Institute of Engineering and Technology Department of Cse Greater Noida India Galgotias University Department of Computer Science and Engineering Greater Noida India

ISBN: (纸本)9798350347456

This paper is focused on the development of a student academic result alert system using Short Service Message (SMS). The motivation behind the work was borne out of the numerous problems that students encounter before seeing their results. The issue of checking examination results through notice boards in anxiety has been a challenge from time immemorial. In some cases where results are posted on websites, students will have to pay for internet services to check their grades. Similarly, the privacy that should be upheld with respect to results publishing is not through public display. With these problems in mind, the authors developed a system to deliver students' results and grades through SMS using a dedicated Application programming Interface (API). The factfinding methods employed in the work were both primary and secondary methods. Primary method involved the use of questionnaire and observation of documents, while we deployed Object Oriented Analysis and Design Methodology (OOADM) as the design methodology. The software tools used are HTML (Hyper Text Markup Language), PHP (Hypertext PreProcessor) for the front-end and MYSQL for the database solution. The software developed is a highly interactive and has the capability of preventing unauthorized access or mutilation of students' results, thus maintaining data integrity. It also sends student's results directly to their phones and that of their sponsors. © 2023 IEEE.

关键词： Students

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Nonparametric Analytical Method for Probabilistic Optimal Power Flow in Renewable Energy Distribution Systems Based on Weighted-KNN 2

Nonparametric Analytical Method for Probabilistic Optimal Po...

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2nd international conference on Clean Energy Storage and Power engineering, CESPE 2023

作者： Zong, Xingchen Si, Jiandong Yang, Jian Li, Yunyi Zhang, Xiaoyan College of Electrical Engineering Zhejiang University Hangzhou China State Grid Zhejiang Electric Power Co. Ltd. Taizhou Power Supply Company Taizhou China State Grid Electric Power Research Institute Nanjing China

ISBN: (纸本)9798350395495

The high penetration rate of multiple renewable energy poses increasingly severe challenges to the economic and stable operation of distribution systems. The optimal power flow problem that considers uncertain factors is a stochastic nonlinear programming problem, which is difficult for traditional methods to solve accurately. To effectively analyze the impact of system parameter uncertainty on system optimization results and achieve effective solutions to probabilistic optimal power flow problems, this paper introduces the weighted-KNN similarity measurement method into the probability optimal power flow calculation of renewable energy distribution systems, uses data-driven methods to mine the uncertainty information of random variables from historical data, and constructs an analytical mapping relationship between renewable energy output and decision variables such as distribution network voltage amplitude and phase through KKT conditions. This method effectively enhances the calculation speed and precision of the optimal power flow problem. Then it combines the multivariate mixed GMM method, depicting the probability distribution of decision variables in nonparametric form to improve the accuracy of uncertainty description. © 2023 IEEE.

关键词： Electric power distribution

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Sentiment Analysis using Supervised Machine Learning 2

Sentiment Analysis using Supervised Machine Learning

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2nd international conference on Advance Computing and Innovative Technologies in engineering, ICACITE 2022

作者： Chauhan, Hritik Rathore, Kanishka Singh Rajan, V Gokul School of Computing Science and Engineering Galgotias University Greater Noida India

ISBN: (纸本)9781665437899

The dataset is the IMDB dataset which comprise of the reviews of 50k movies and it is available on the Kaggle, which has 2 columns in it. The two columns in the dataset contains the reviews and the sentiment which will help us to identify the reviews is a positive review, or a negative review about the movie. Machine Learning is a modern-day concept in which the machine can be trained in the same manner as an infant baby learns the things in an environment, with the use of machine learning certain patterns are used from the data to give the machine a learning, reasoning and predicting ability. The aim is to train and build a machine learning model that will be able to predict whether a movie review provided is a positive or negative review, this is also known as binary text Classification which will be done by using Scikit-learn library, which is a very common machine learning library used in python programming language. © 2022 IEEE.

关键词： Classification (of information)

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Hybrid Quantum-Classical Convolutional Squeeze Excitation Neural Network based HEVC Video Quality Enhancement 2

Hybrid Quantum-Classical Convolutional Squeeze Excitation Ne...

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2nd international conference on Self Sustainable artificial Intelligence Systems, ICSSAS 2024

作者： Arun Shalin, L.V. Kansal, Vipashi Nikitha, M. Nandini, V. Ronald, Bindu Soudagar, Manzoore Elahi M. Karunya Institute of Technology and Sciences Division of Data Science and Cybersecurity Tamil Nadu Coimbatore641 114 India Graphic Era Deemed to be University Department of Computer Science & Engineering Dehradun248 002 India Bannari Amman Institute of Technology Department of Information Technology Tamil Nadu Erode638401 India Brindavan College of Engineering Department of Chemistry Dwaraka Nagara Yelahanka Karnataka Bengaluru560063 India Vimannagar Maharashtra Pune411014 India Saveetha Institute of Medical and Technical Sciences Saveetha School of Engineering Department of Vlsi Microelectronics Tamil Nadu Chennai602105 India

ISBN: (纸本)9798350368413

Due to the popularity of video streaming on the internet, there is a high utilization of HEVC because of the high compression ratio it delivers in video quality. However, the compression process causes distorting elements that have a negative impact on the quality of the videos, which presents much complication in preserving the content integrity as it was decoded from the videos. To overcome these issues, this manuscript proposes a Hybrid Quantum-Classical Convolutional Squeeze Excitation Neural Network for HEVC Video Quality Enhancement through a two-phase approach: There are two areas namely, (i) Quantization Bit Stream and (ii) post-processing. In the first phase, for example, a Squeeze Excitation Multi-Head Attention-Based Encoder and Decoder radically effects a video frame compression by utilising possibilities of prediction, transformation, quantization, and entropy coding, though it distorts at the same time. The decoder then unpacks the frames thus created to the format that the enhancement module uses as input. The second phase makes use of a Hybrid Quantum-Classical Convolutional Neural Network (HQ2C2N). This approach involves a Feature Extraction Layer that employs quantum circuits to optimize the feature extraction step, a Feature Enhancement Layer that applies classical convolutional networks to eliminate artifacts that have been introduced to the video and a Post-Processing Layer that allows for tuning of end frames to the desired quality standards typical of plyback or further processing. The experiments of the proposed HQ2C2N method are conducted using MATLAB programming environment. The HQ2C2N significantly improves HEVC video quality by effectively reducing compression artifacts, resulting in a higher PSNR of 75 dB and a lower MSE of 0.1%, outperforming previous methods in visual fidelity and performance metrics. © 2024 IEEE.

关键词： MATLAB

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User Angle Estimation Based on Intelligent Reflecting Surface Assisted Communication 2

User Angle Estimation Based on Intelligent Reflecting Surfac...

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2nd IEEE international conference on Data science and Computer Application, ICDSCA 2022

作者： Li, Yang Chen, Xiangning Li, Xuemei Nanjing University School of Electronic Science and Engineering Nanjing China

ISBN: (数字)9781665472005

ISBN: (纸本)9781665472005

This paper analyzes and solves the problem of estimating the user's angle under the condition that there is no line-of-sight (LoS) communication link between the base station (BS) and the user, and multiple intelligent reflecting surfaces (IRS) are used to assist communication. According to the established communication model, the appropriate passive beam vector is obtained by simulation analysis. After that, the area where the user is located is determined by using the transmission delay parameter of the received signal, and then the estimated area is finely divided. Based on sparse optimization knowledge, a second-order cone (SOC) programming problem is established, which is solved using the optimization toolbox and a graph of the simulation results is obtained. The simulation results show that when the LoS communication link between the BS and the user is missing, the position angle of the user can be effectively estimated based on the IRS-assisted communication. At the same time, increasing the number of IRSs in the communication system can improve the estimation accuracy. © 2022 IEEE.

关键词： Analytical models Simulation Estimation programming Matrices Surface roughness Rough surfaces

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FDA-MIMO beampattern optimization with complex circle manifold 2

FDA-MIMO beampattern optimization with complex circle manifo...

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2nd IEEE international conference on Signal, Information and Data Processing, ICSIDP 2024

作者： Qi, Jiawei Lan, Lan Liao, Guisheng Cui, Lei Chen, Guozhong Xidian University National Key Laboratory of Radar Signal Processing Xi'an China Shanghai Institute of Satellite Engineering Shanghai China

ISBN: (纸本)9798331515669

This paper investigates the design of beampattern in an Frequency Diverse Array (FDA)-Multiple-Input MultipleOutput (MIMO) radar by jointly optimizing the transmit waveform and receive filter considering the environment of jammers at specific range-angle intervals. In this regard, the optimization problem is formulated by forcing the constant modulus constraint on the waveform. For solving the devised non-convex problem, an alternating optimization procedure is introduced, where the optimization problem is partitioned into two subproblems related to waveform and filter, respectively. Particularly, the former is solved by utilizing a projection, descent, and retraction (PDR) method leveraging the complex circle manifold, whereas the latter resorts to a quadratic programming model. Hence, a desired beampattern with deep nulls at specific range and angle intervals can be formed. Finally, numerical results illustrate the convergence performance of the developed algorithm and the effectiveness of the devised beampattern in suppressing jammers. © 2024 IEEE.

关键词： MIMO radar

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