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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 1140 条记录，以下是961-970 订阅

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A heuristic solution for noisy image segmentation using Particle Swarm Optimization and Fuzzy clustering

A heuristic solution for noisy image segmentation using Part...

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international Joint conference on Computational Intelligence (IJCCI)

作者： Saeed Mirghasemi Ramesh Rayudu Mengjie Zhang School of Engineering and Computer Science Victoria University of Wellington Wellington New Zealand

ISBN: (纸本)9781509019687

Introducing methods that can work out the problem of noisy image segmentation is necessary for real-world vision problems. this paper proposes a new computational algorithm for segmentation of gray images contaminated with impulse noise. We have used Fuzzy C-Means (FCM) in fusion with Particle Swarm Optimization (PSO) to define a new similarity metric based on combining different intensity-based neighborhood features. PSO as a computational search algorithm, looks for an optimum similarity metric, and FCM as a clustering technique, helps to verify the similarity metric goodness. the proposed method has no parameters to tune, and works adaptively to eliminate impulsive noise. We have tested our algorithm on different synthetic and real images, and provided quantitative evaluation to measure effectiveness. the results show that, the method has promising performance in comparison with other existing methods in cases where images have been corrupted with a high density noise.

关键词： Noise measurement Image segmentation Clustering algorithms Linear programming Particle swarm optimization Heuristic algorithms Partitioning algorithms

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Multilinear objective function-based clustering

Multilinear objective function-based clustering

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international Joint conference on Computational Intelligence (IJCCI)

作者： Giovanni Rossi Departments of Computer Science and Engineering - DISI and Mathematics University of Bologna Bologna Italy

ISBN: (纸本)9781509019687

the input of most clustering algorithms is a symmetric matrix quantifying similarity within data pairs. Such a matrix is here turned into a quadratic set function measuring cluster score or similarity within data subsets larger than pairs. In general, any set function reasonably assigning a cluster score to data subsets gives rise to an objective function-based clustering problem. When considered in pseudo-Boolean form, cluster score enables to evaluate fuzzy clusters through multilinear extension MLE, while the global score of fuzzy clusterings simply is the sum over constituents fuzzy clusters of their MLE score. this is shown to be no greater than the global score of hard clusterings or partitions of the data set, thereby expanding a known result on extremizers of pseudo-Boolean functions. Yet, a multilinear objective function allows to search for optimality in the interior of the hypercube. the proposed method only requires a fuzzy clustering as initial candidate solution, for the appropriate number of clusters is implicitly extracted from the given data set.

关键词： Maximum likelihood estimation Silicon Clustering algorithms Phase change materials Symmetric matrices Search problems Linear programming

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A Deep Learning-Based Smart Helmet Detection and Notification with e-Challan Issuance for Traffic Fines

A Deep Learning-Based Smart Helmet Detection and Notificatio...

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India Council international Subsections conference (INDISCON), IEEE

作者： Rajdeep Ghosh Akash Kotal Raja Karmakar Krittika Das Department of Computer Science and Engineering Techno International New Town Kolkata India Department of Computer Science and Engineering Heritage Institute of Technology Kolkata India Department of Computer Science and Engineering Techno International New Town India

the Ministry of Road Transport and Highways estimates that 158,964 two-wheeler road accidents occurred in India in 2020, resulting in 56,873 fatalities, some of which were brought on by the lack of a helmet. this is still an issue on Indian roads and puts the lives of the country's young inhabitants in peril, despite numerous campaigns that have been undertaken by various state governments and the imposition of numerous punishments. the usage of computer vision is a suitable remedy for this issue. An automated system is suggested that employs a state-of-the-art single shot detector (SSD) for detection, image upscaling and Optical Character Recognition (OCR) to identify the vehicle's licence plate, as well as a database for e-challan records. Together with the payment link to clear the challan online, other Short Message Service (SMS) and mail Application programming Interface (API) is also utilised to notify about the challan's issuance. this paper explores a deep-learning-based idea that assures traffic safety and order on Indian roads and is a workable and useful solution to the highlighted issue.

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Position Control Application with Simatic S7-1500T and Sinamics S210

Position Control Application with Simatic S7-1500T and Sinam...

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international conference on Modern Power Systems (MPS)

作者： Mihai Rata Gabriela Rata Ciprian Bejenar Faculty of Electrical Engineering and Computer Science Stefan cel Mare University of Suceava Suceava Romania

Position control with PLC represents one of the high complexity software applications in the field of industrial automation. In this paper the authors present an automation design of two-axis control using Sinamics S210 and S7-1511T PLC which are useful for electrical engineering master's students. To provide an experience closer to real world applications and one that should allow the study of PLC programming, the PROFINET industrial communication protocol, design screens for Human Machine Interfaces (HMI) and positioning applications, the students can use the proposed solution in the faculty laboratories. they can start with the development of elementary complexity software applications, all the way to high complexity applications.

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Compact Transformer-based Language Models for the Moroccan Darija

Compact Transformer-based Language Models for the Moroccan D...

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international conference on Information science and Technology (ICIST)

作者： Mohamed Aghzal Mohamed Amine El Bouni Saad Driouech Asmaa Mourhir School of Science and Engineering Al Akhawayn University Ifrane Morocco

Over the past few years, pre-trained language models based on transformer architectures revolutionized the field of natural language processing, achieving state-of-the-art performance on various tasks. However, due to these models’ dependability on enormous corpora for training, very few such models were trained for underresourced languages and dialects, such as Moroccan Darija. In this work, we introduce DarRoBERTa and DarELECTRA which are two transformer-based language models for Darija. We evaluate the language models on the extrinsic tasks of text summarization and topic classification. As for the text summarization task, the results show that DarELECTRA achieves state-of-the art results with a score of 19.25 for Rouge 1, 5.79 for Rouge 2, and 18.01 for Rouge L. For the topic classification task, DarRoBERTa achieved an F1 score of 0.84 and accuracy of 0.86. While our Daija language models achieved results close the Arabic language models, they are much smaller and more efficient.

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Building blocks for secure multiparty federated wireless sensor networks

Building blocks for secure multiparty federated wireless sen...

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international Wireless Communications and Mobile Computing conference, IWCMC

作者： Christophe Huygens Nelson Matthys Jef Maerien Wouter Joosen Danny Hughes Computer Science Department K.U. Leuven Heverlee Belgium Computer Science and Software Engineering Department Xi'an Jiaotong-Liverpool University Suzhou China

Wireless Sensor Networks are increasingly being deployed in enterprise scenarios involving multiple actors. the capabilities of sensors must be shared across many applications and sensors must cooperate across federations spanning administrative domains. this paper describes our efforts towards constructing federated wireless sensor systems. It leverages and details key building blocks designed to achieve federation and sharing: a component model with distributed event-based communication, a policy-driven control infrastructure for resources and communications, a deployment architecture and a mechanism to establish and propagate trust into the wireless sensor network. the building blocks focus on the specific and necessary in-network extensions, such as extensions to sensor run-time, middleware and programming abstractions, rather than the backend challenges. the combination of the building blocks creates a security middleware that supports multiparty federated sensor networks. An estimate of the total cost of federation in terms of footprint is provided and first experiences of application of the middleware are reported upon.

关键词： Wireless sensor networks Middleware Security Runtime Logic gates Engines Peer to peer computing

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A Comprehensive and Secure Trustless Blockchain Framework for Autonomous Vehicles

A Comprehensive and Secure Trustless Blockchain Framework fo...

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international conference on Trends in Electronics and Informatics (ICEI)

作者： Sivaramakrishnan Rajendar Udhayakumar thangavel Sarvesh Devendran Vaishnavi Selvi Shanmuga Sundaram Muthumanickam Department of Computer Science and Engineering KPR Institute of Engineering and Technology Coimbatore Tamilnadu India

As Autonomous Vehicles (AVs) become increasingly prevalent, there is a growing need for secure and efficient data transfer between vehicles and other stakeholders in the transportation ecosystem. Blockchain technology has emerged as a promising solution to this challenge, offering a decentralized and tamper-resistant platform for storing and sharing data. this research study proposes a blockchain-based solution for addressing the challenges related to data security, ownership, trust, transparency, and auditability in AVs. It covers the use of blockchain for vehicle identity verification, secure data sharing, and real-time communication between AVs and other entities such as infrastructure and insurance providers. the proposed solution incorporates smart contracts, Merkle trees, and cloud storage to provide a trustless environment for data transfer and ensure that data is tamper-proof and auditable. the paper also provides a detailed implementation of the proposed solution. the findings of this research study provides a comprehensive overview of the state-of-the-art AVs and blockchain technology, highlighting the potential of this emerging field to transform the transportation industry.

关键词： Transportation industry Ecosystems Transportation Insurance Transforms Data transfer Trustless services

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Research on the Application of the Method of System engineering in Computer Software Design

Research on the Application of the Method of System Engineer...

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2017 7th ICEA international conference on Information science, Library science and Social sciences (ILS 2017)

作者： Hengni Ren College of Information and Engineering Shaanxi Institute of International Trade & Commerce

With the rapid development of computer technology, the computer has gradually become an indispensable part of people's lives. All kinds of programming language of computer have been mastered and used by more people, however, the function is more and more strong, the use is also very convenient, the process of the development of software has also become more complex, so the quality of the software is also very difficult to be guaranteed to a certain extent. And the method of system engineering is mainly aimed at the disadvantages and the solution to the problem in computer development software design. Because of its complexity, great attention must be paid to the application in computer software design. Because of the importance of this problem, at present, there are also many professional articles about the problem of the development of large software project. the purpose of this paper is to improve the quality and efficiency of computer software by studying the method of system engineering.

关键词： Computer software design Method of system engineering Application Research

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Decentralized Metadata Storage for Non-Fungible Token Collections Using Interplanetary File System

Decentralized Metadata Storage for Non-Fungible Token Collec...

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international conference on Electronics, Materials engineering and Nano-Technology (IEMENTech)

作者： Immanni Bhanu Prakash Adarsh Kr Tiwari U. Hariharan Department of Computer Science and Engineering Apex Institute of Technology Chandigarh University Mohali Punjab India

Non-fungible tokens (NFTs) have become known as a game-changing digital asset class, revolutionizing digital content ownership and trade. these one-of-a-kind tokens symbolize a variety of digital and physical goods, including art, music, antiques, and more. the metadata linked with each token is crucial to the value and legitimacy of NFTs, giving crucial details about the asset's authenticity, ownership history, and other pertinent factors. It is critical in this setting to ensure the security, longevity, and usability of this metadata. the novel method of storing NFT information on the Interplanetary File System (IPFS), a decentralized and distributed file storage technology, is explored in this research article. It then digs into IPFS's design and operations, describing how it works as a decentralized file storage system. the integration of IPFS with NFT collections is thoroughly examined, emphasizing the advantages it provides with regard to data integrity, accessibility, and security. this study highlights IPFS's potential as a game- changing solution for NFT metadata storage. Creating a web- based NFT minting and querying application using ***, Web3Modal, and Ethereum on the Mumbai test net user-friendly integration of decentralized NFT contracts, aiming to facilitate broader adoption of NFT applications. As a result, it adds to the continuing discussion about NFT technology and its integration with decentralized systems, paving the path for a more robust and permanent digital art and collectibles market.

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Prediction of Bushfire Area Using Machine Learning Techniques

Prediction of Bushfire Area Using Machine Learning Technique...

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international conference on Computing Communication Control and Automation (ICCUBEA)

作者： Debabrata Swain Manish Kumar Nikhil Jain Chirag Devnani Computer Science and Engineering Department Pandit Deendayal Energy University Gujarat India Electronics and Communication Engineering Department Pandit Deendayal Energy University Gujarat India

Wildfires are a widespread natural disaster that affect animal and human lives around the world, and can also cause property damage. It is important for fire-prone areas to have effective measures for curbing the damage caused by fires. Predicting the spread of fires is a useful tool for this. this paper explores the use of state-of-the-art machine learning models, tools, and techniques for predicting the estimated fire area using environmental factors like weather and vegetation index as input parameters. Wildfire data of Australia from 2005 to 2020 is used in this study. the importance of different features is studied and the performance of various models is compared for different feature sets calculated using feature selection and extraction techniques. the accuracy and effectiveness of these techniques are analyzed through comparison of the results in terms of different error measures. Out of all the implemented methods, the Random Forest model has shown the most promising result with an MAE of 78.6 km 2 .

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