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检索条件"任意字段=6th International Conference on the Art, Science, and Engineering of Programming, Programming 2022"

共 1076 条记录，以下是421-430 订阅

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V2P Protection Based on Multi-Sensor Fusion in Foggy Scene 2022

V2P Protection Based on Multi-Sensor Fusion in Foggy Scene

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6th international conference on Compute and Data Analysis, ICCDA 2022

作者： Wei, Jianming Liu, Shumin Liu, Qiuming Lin, Huimin School of Software Engineering Jiangxi University of Science and Technology China

ISBN: (纸本)9781450395472

To protect the vulnerable groups in traffic environment, this paper proposes a V2P protection method with multi-sensor in foggy ***, lidar and camera are combined to achieve mapping 3D point cloud data to the 2D plane to form a sparse point cloud map;secondly, an image guided algorithm is proposed to pad sparse point cloud data;finally, by employing the improved sort algorithm, combined with YOLOv4 target detection algorithm, integrating vehicle IMU data and radar point cloud data to protect the *** show that the proposed V2P protection method is robust under different degrees of foggy scenarios, with pedestrian F1 performance measures maintained above 80%, 3% higher than the sparse point cloud method and 10% higher than the dark channel prior defogging method;the F1 performance index of non-motor vehicle drivers was maintained above 75%, 2% higher than the sparse point cloud method, and 12% higher than the dark channel prior defogging *** results of speed prediction of vulnerable groups show that the proposed method can effectively realize speed prediction and protection of vulnerable groups in foggy scenarios. © 2022 ACM.

关键词： Object detection

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Food Resources in Food System Technology: Bifunctional Food System Technology Based on Pickering Emulsions 6

Food Resources in Food System Technology: Bifunctional Food ...

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6th Smart Cities Symposium, SCS 2022

作者： Potoroko, Irina Kadi, Ammar Paymulina, Anastasia Bagale, Uday Abotaleb, Mostafa El-Kenawy, El-Sayed M. Department of Food and Biotechnology South Ural State University Chelyabinsk454080 Russia Siberian Federal Scientific Center of Agro-Bio Technologies of the Russian Academy of Sciences Novosibirsk region Krasnoobsk Russia Department of System Programming South Ural State University Chelyabinsk454080 Russia Department of Communications and Electronics Delta Higher Institute of Engineering and Technology Mansoura Egypt

ISBN: (纸本)9781839538544

the development of domestically generated food additives based on eco-technologies with specified functional-technological and bioactive qualities is now a significant focus of contemporary study. Pickering emulsions are more stable both physically and chemically, making them a highly promising method of introducing biologically active chemicals into the body. the purpose of this research was to determine if ultrasound could be used to create a bioactive colloidal Pickering emulsion system using flax cellulose or brown algal polysaccharides as a stabilizer. Pickering emulsions stabilized with fucoidan, sodium alginate, or flax cellulose, based on a lipid fraction of sunflower oil and cinnamon oil blend, or a lipid fraction of linseed oil, were applied to the subjects, who were then subjected to ultrasound treatment at 630W/l for 16 min (4 min on, 3 min off) at a controlled temperature of 50 °C. the results obtained demonstrate the effectiveness of using ultrasonic exposure to create bioactive Pickering emulsion colloidal systems. Fucoidan stabilizes pickering emulsion, with the highest AOA values (5.120±0.005 DPPH, %) and a rise in AOA values in linseed oil-based emulsion samples from 30% to 100% in comparison to emulsion samples based on a blend of lipid phases. the viscoelastic characteristics of Pickering emulsions with various oil fractions vary dramatically for the integrated structure-forming components. © 2022 IET conference Proceedings. All rights reserved.

关键词： Flax

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Review of User Comments for the OVO Fintech application using LDA

Review of User Comments for the OVO Fintech application usin...

引用

international conference on Information Technology (INCIT)

作者： Albertus Dwiyoga Widiantoro Bernardinus Harnadi Information Systems Department Computer Science Faculty Soegijapranata Catholic University Semarang Indonesia

the main purpose of this article is to model the topic of OVO Fintech user comments using LDA. this research is a word processing research conducted using text mining. the statistical population is the comments of OVO e-wallet Fintech users in 2021 who take data randomly. LDA (Latent Dirichlet Allocation) and Python programming language were applied to analyze data and implement text mining algorithms from topic modeling. Findings are the most important keywords in Fintech user comments. Also, there are 6 important topics identified in the comments of Fintech users by applying a topic modeling *** mining and Latent Dirichlet Allocation were applied to analyze the e-wallet. OVO is a hot topic for Fintech users. Finally, in addition to a retrospective approach to data collection and analysis, the results can be utilized with a prospective approach to strategic planning and policy making.

关键词： Text mining Analytical models Online banking Sociology Strategic planning Maintenance engineering Resource management

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the Teaching Mode and Evaluation of Computer Course in Higher Vocational Colleges in the Intelligent Era 4th

The Teaching Mode and Evaluation of Computer Course in Hi...

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4th EAI international conference on 6G for Future Wireless Networks, 6GN 2021

作者： Geng, Jiangtao Tang, Yong Chang, Chao South China Normal University Guangdong Guangzhou510631 China Guangzhou International Economic College Guangdong Guangzhou510540 China

ISBN: (纸本)9783031042447

the intelligent era brings new opportunities and challenges to the development of higher vocational education, requiring higher vocational colleges to train high-quality compound skilled talents. However, the current higher vocational students have a poor learning foundation and lack the motivation to learn, so it is necessary to reform the training of talents and the traditional classroom teaching mode of higher vocational colleges. Based on the specific teaching practice of the computer "Bilingual C programming" course on the intelligent cloud platform, this paper explores the unique characteristics of higher vocational teaching under the background of mobile Internet and big data technology, according to different learning conditions and different teaching environments. Combining multiple teaching modes organically, achieving complementary advantages through the use of online and offline mixed teaching, using flipped classroom and PAD (Presentation Assimilation Discussion) class teaching modes, and adopting process evaluation methods to achieve teaching goals of "teaching with improvement, learning with achievement, teaching and learning mutually beneficial". the results of empirical research show that the students who adopt the flipped classroom and the PAD class teaching mode show good learning results and stronger learning motivation. © 2022, ICST Institute for Computer sciences, Social Informatics and Telecommunications engineering.

关键词： Teaching

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A Relation-and-Regression-assisted Evolutionary Algorithm for Expensive Constrained Multi-objective Optimization

A Relation-and-Regression-assisted Evolutionary Algorithm fo...

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Data-driven Optimization of Complex Systems (DOCS), international conference on

作者： Siyu Chen Jinyuan Zhang Department of Computer Science and Engineering Southern University of Science and Technology Shenzhen China

ISBN: (数字)9798350377842

ISBN: (纸本)9798350377859

Expensive constrained multi-objective optimization problems involve computationally expensive objectives and constraints, which impose stiff challenges on traditional evolutionary algorithms to optimize within limited function evaluations. To address this, some surrogate-assisted constrained multi-objective evolutionary algorithms have been proposed, where surrogate models are constructed to replace expensive function evaluations. However, most existing surrogate models are either regression or classification models, which are liable to poor reliability in approximating complicated constraints. In this paper, a relation-and-regression-assisted constrained multi-objective evolutionary algorithm, named RCMOEA, is proposed. In RCMOEA, each regression model is constructed to approximate each objective function, and each relation model is built to learn the relation of constraint values between any two solutions. Based on the constructed surrogate models, a relation-and-regression-based constrained Pareto dominance, denoted as RCPD, is proposed to compare solution pairs. By adopting RCPD as the dominance criterion, the RCPD-based selection strategy is proposed for selecting offspring solutions. Also, the distance-based infill sampling strategy is proposed to preserve the diversity of solutions. Experimental results demonstrate the superiority of RCMOEA over the compared algorithms.

关键词： Computational modeling Evolutionary computation Predictive models Linear programming Prediction algorithms Approximation algorithms Manufacturing Reliability Complex systems Optimization

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the Empirical Analysis of Machine Learning-Based Techniques for Improving Cyber Security

The Empirical Analysis of Machine Learning-Based Techniques ...

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international conference on Contemporary Computing and Informatics (IC3I)

作者： Yerrolla Chanti M. Chalapathi Rao Ch. Srinivasa Reddy Mohd. Yaseen Wani Abdullah Samdani Mohit Tiwari School of CS & AI SR University Warangal Telangana India Department of CSE Malla Reddy University Hyderabad Telangana Department of IT Vignan's Institute of Information Technology(A) Duvvada Visakhapatnam School of Law Kashmir University Srinagar Jammu &Kashmir School of Law University of Petroleum & Energy Studies Dehradun Uttarakhand India Department of Computer Science and Engineering Bharati Vidyapeeth's College of Engineering Paschim Vihar Delhi

the absence of training statistics is still the major obstacle among the numerous that tend to cause cyberattack identification difficult to identify. Millions of consumers are still at risk due to an absence of knowledge about website activities and characteristics that could lead to an attack, even when businesses and companies utilize well-known network surveillance technologies. In reality, the majority of attacks happen not since attackers employ sophisticated programming and evasive strategies, yet rather since victims lack the fundamental skills needed to recognize and prevent the *** of these difficulties, machine learning (ML) is demonstrated to fundamentally alter our awareness of the context of cyberattacks. For this research, ML techniques were applied to data from phishing websites to improve cybersecurity by contrasting five techniques and offering knowledge that the broad accessible may employ to prevent common phishing traps. the research outcomes imply that the neural network (NN) technique is the most effective one. Since NNs are built on multi-layer perceptrons, the foundation of intelligence, phishing identification will eventually be automated and transformed into an artificial intelligence endeavor.

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Robust Object Profile Extraction Based on Multi-beam Sonar 6

Robust Object Profile Extraction Based on Multi-beam Sonar

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6th international conference on Transportation Information and Safety, ICTIS 2021

作者： De-Shan, Chen Heng-Rui, Liu Ting-Wen, Li Yang, Wang Zhong-Ping, Wu Jiang-Bin, Zhao Wuhan University of Technology National Engineering Research Center for Water Transport Safety Wuhan China Yangtze River Waterway Transportation Monitoring and Emergency Center Wuhan China The 710th Institute of China Shipbuilding Industry Corporation Wuhan China Wuhan University of Technology Wuhan China

ISBN: (纸本)9781665497138

Multi-beam sonar is one of the most important visual perception tools for underwater medium and longdistance object detection. the sonar image obtained by it is an important data source for three-dimensional reconstruction of underwater scenes. In order to solve the problems of background noise and clutter in underwater target detection based on multi-beam sonar, a robust object profile extraction method for multi-beam image sonar is proposed in this paper. Firstly, threshold processing and non-maximum suppression are carried out for the points on each column of the image according to the pixel gray value to obtain the candidate points of the object profile. Secondly, according to the imaging principle of multi-beam sonar, the likelihood probability model of candidate points and the jump penalty model between adjacent columns of image are established to remove the influence of noise on profile extraction. According to the characteristics of the established objective function, the dynamic programming method is used to solve the problem. the experimental results of measured and simulated data show that this algorithm is simple and easy to operate, and can accurately and effectively extract the single profile of multi-beam image sonar, which has a high application value. © 2021 IEEE.

关键词： Dynamic programming

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Smart Contracts and Blockchain : An Analytical Approach

Smart Contracts and Blockchain : An Analytical Approach

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international conference on Contemporary Computing and Informatics (IC3I)

作者： Anu Sayal Chetlur Vasundhara Veethika Gupta Ashulekha Gupta Himani Maheshawri Minakshi Memoria Department of Mathematics Taylor's University Malaysia Department of CSE (AI & ML) JAIN (deemed to be University) Bangalore Karnataka India School of Social Sciences Doon University Dehradun Uttarakhand India Department of Management Studies Graphic Era (Deemed to be University) Dehradun Uttarakhand India Department of Computing Graphic Era Hill University Dehradun Uttarakhand India Department of Computer Science and Engineering Uttaranchal Institute of Technology Uttaranchal University Dehradun Uttarakhand India

the conventional paper-based legal agreements have been replaced with smart contracts in the modern day. the way legal contracts are utilized to bind the parties to do business is changing as a result of this developing idea. SM-Smart contracts offer a solution to the issue of trust in the digital era. A smart contract is a computer program that is designed to automatically execute the terms of a contract between two or more parties. It operates on a blockchain network and contains the rules and conditions of the agreement. A software developer creates smart contracts by computer-programming the terms and conditions of the written legal agreement. In order for all parties to be aware of the conclusion right away, smart contracts are used to automate the execution of legal agreements. No third party is involved in the contract's execution. Numerous platforms and applications built using blockchain technology depend heavily on smart contracts.

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Can ChatGPT Fix My Code?

Can ChatGPT Fix My Code?

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18th international conference on Software Technologies, ICSOFT 2023

作者： Csuvik, Viktor Gyimóthy, Tibor Vidács, László University of Szeged Department of Software Engineering Hungary University of Szeged MTA-SZTE Research Group on Artificial Intelligence Hungary

ISBN: (纸本)9789897586651

ChatGPT, a large language model (LLM) developed by OpenAI, fine-tuned on a massive dataset of text and source code, has recently gained significant attention on the internet. the model, built using the Transformer architecture, is capable of generating human-like text in a variety of tasks. In this paper, we explore the use of ChatGPT for Automated Program Repair (APR);that is, we ask the model to generate repair suggestions for instances of buggy code. We evaluate the effectiveness of our approach by comparing the repair suggestions to those made by human developers. Our results show that ChatGPT is able to generate fixes that are on par with those made by humans. Choosing the right prompt is a key aspect: on average, it was able to propose corrections in 19% of cases, but choosing the wrong input format can drop the performance to as low as 6%. By sampling real-world bugs from seminal APR datasets, generating 1000 input examples for the model, and evaluating the output manually, our study demonstrates the potential of language models for Automated Program Repair and highlights the need for further research in this area. © 2023 by SCITEPRESS-science and Technology Publications, Lda.

关键词： Java programming language

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GRAFCET Virtual Machine Enables Digital Twin and Implements PLCopen Systems

GRAFCET Virtual Machine Enables Digital Twin and Implements ...

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IEEE international conference on Orange Technologies (ICOT)

作者： Po-Tong Wang Chieh-Jung Lu Chung-Liang Chang Department of Electrical Engineering Lunghwa University of Science and Technology Taoyuan Taiwan

ISBN: (纸本)9781665454209

Industrial Internet of things (IIoT) systems challenges implementing programming logic controller (PLC) real-time technology. Firstly, the design of IIoT is fragmented and distributed. Secondly, existing PLC tools are hard to meet and dramatically complicated in emergent industries. Most of all, the deployment of IIoT is state-of-the-art engineering in complexity. A scheme to integrate the GRAFCET virtual machine (GVM) with a digital twin proposed enables IIoT systems in rapidly changing environments. they are compiling digital logic programs that support GVM at remote locations, deploying distributed manufacturing systems through IIoT communication networks, and building operational models of digital virtual and physical systems through digital twin modeling. Its behavior in dynamic operating environments is predictable. the results show that GRAFCET is not only IEC 60848 standard but also IEC 61131–3 for the PLCopen programming tool. Furthermore, a gateway of GVM performs rapid deployment of edge-cloud PLC programming. Significantly a cyber-physical system (CPS) through the digital twin improves the practicality of the digital transformation of PLC's value.

关键词： XML programming Virtual machining Real-time systems Digital twins Social implications of technology IEC Standards

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