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15th International Conference on Electronics, computers and Artificial Intelligence, ECAI 2023

作者： Codrean, Marius Novac, Mihaela Cornelia Codrean, Mihaela Gordan, Cornelia Emilia Novac, Ovidiu Constantin Bujdoso, Gyongyi Slovac, Francisc University of Oradea Department of Electrical Engineering Electrical Engineering and Information Technology Faculty Oradea Romania National Geothermal Research Center Technology Transfer Center NGRC-TTC University of Oradea Oradea Romania University of Oradea Department of Electronics and Telecommunications Electrical Engineering and Information Technology Faculty Oradea Romania University of Oradea Department of Computers and Information Technology Electrical Engineering and Information Technology Faculty Oradea Romania University of Debrecen Faculty of Informatics Department of Computer Science and Library and Information Science Debrecen Hungary

ISBN: (纸本)9798350321388

The aim of this work is to develop numerical procedures for analyzing edge hardening using induction heating by turbulent currents. The section through the steel bar, whose lower edge needs to be hardened, is presented. For the inductor adapted to the piece configuration, the 2D model is assumed. The surface treatment of the piece must be differentiated: in the tip area, the heating must be greater than in the rest of the surface. Only the tip area needs to be subjected to hardening, while the rest of the piece must remain elastic to ensure the desired mechanical strength. The main purpose of this work is to propose inductor models for achieving differentiated heating of the blade. © 2023 IEEE.

关键词： Induction heating

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Explain Ability, Fairness and Trust in Data Systems and Analysis

Explain Ability, Fairness and Trust in Data Systems and Anal...

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2023 computer Applications and Technological Solutions, CATS 2023

作者： Hasan, Muhammad Zulkifl Hussain, Muhammad Zunnurain Fatima, Haniya Ayub, Malaika Nosheen, Summaira Mubarak, Zaima Chuhan, Saad Hussain Mustafa, Muzzamil University of Central Punjab Faculty of Information Technology Department of Computer Science Lahore Pakistan Bahria University Lahore Campus Department of Computer Science Lahore Pakistan Information Technology University of Punjab Department of Economics Lahore Pakistan National College of Business Administration & Economics Department of Computer Science DHA Campus Lahore Pakistan

ISBN: (纸本)9798350383881

From credit scoring algorithms to face recognition systems, data-driven technologies are already impacting our lives and choices. To guarantee that new technologies function for the advantage of everyone, rather than perpetuating prejudices and discrimination, we have to address the ability, fairness, and trustworthiness of data systems and analysis. In literature, ability of data systems and analysis is defines as the capability of data systems to capture, store, retrieve, and manipulate data in large databases. Fairness of data systems means making sure that the usage of data and analytics does not result in biased or discriminating results for individuals or organizations. Trust is an essential factor in the effectiveness and acceptability of data systems and analysis. Without trust, people may be unwilling to utilize or disclose their data with such systems, hampering their ability to give useful insights and take advantages of data systems. To analyze, the ability, fairness, and trust in data systems and analysis, researchers have used secondary, qualitative data. Researchers have used scholarly publications, research papers, and reports taken from credible and peer-reviewed research journals. Using the data, researchers came to the result that data systems analysis have enhanced decision making process and helped us to improve our productivity in daily-life activities, through its capabilities of capturing, stories, retrieving and manipulating data. Yet, there are issues regarding the fairness of data systems. While progress achieved in tackling fairness issues, trust issues concerning data systems and analysis exist owing to data breaches suffered by huge databases globally. To conclude, in order to create trust in data systems and analysis, firms need to concentrate on security, data quality, transparency and accountability of data. This requires implementing strong access limits, leveraging high-quality data sources, being transparent and honest about data

关键词： Database systems

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AraTraditions10k bridging cultures with a comprehensive dataset for enhanced cross lingual image annotation retrieval and tagging

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Scientific Reports 2025年第1期15卷 1-29页

作者： Emran Al-Buraihy Dan Wang Tariq Hussain Razaz Waheeb Attar Ahmad Ali AlZubi Khalid Zaman Gan Zengkang Faculty of Information Technology Beijing University of Technology Beijing 100124 China School of Computer Science and Technology Zhejiang Gongshang University Hangzhou 310018 China Management Department College of Business Administration Princess Nourah Bint Abdulrahman University P.O. Box 84428 11671 Riyadh Saudi Arabia Department of Computer Science Community College King Saud University Riyadh Saudi Arabia Shenzhen Institutes of Advanced Technology Chinese Academy of Sciences Shenzhen 518055 China Institute of Intelligent Manufacturing Technology Shenzhen Polytechnic University Shenzhen 518055 China

The exponential growth of multimedia content in the digital age has necessitated the development of advanced cross-lingual systems capable of understanding and interpreting visual information across different languages. However, current efforts have predominantly been focused on monolingual tasks, leaving a substantial gap in cross-lingual multimedia analysis, particularly for non-English languages. To address this gap, AraTraditions10k, a comprehensive and culturally rich dataset, has been introduced to enhance cross-lingual image annotation, retrieval, and tagging, with a specific focus on Arabic and English languages. The dataset consists of 10,000 carefully curated images representing diverse aspects of Arabic culture, each annotated with five captions in Modern Standard Arabic (MSA) and professionally translated into English. To maximize the utility of the dataset, advanced machine learning models, including a Multi-Layer Perceptron (MLP) for tag recommendation and an enhanced Word2VisualVec (W2VV) model for sentence recommendation, have been developed. These models have been augmented with attention mechanisms and contrastive loss functions, resulting in measurable performance improvements. Notably, the tag recommendation system achieved an overall top-1 accuracy of 93%, while the sentence recommendation system for the English language attained BLEU-4, METEOR, ROUGE-L, CIDEr, and SPICE scores of 78.2, 68.3, 75.8, 136.7, and 52.0, respectively. By addressing the linguistic and cultural gaps in existing datasets, AraTraditions10k establishes a new benchmark for the quality and inclusivity of multilingual datasets, contributing to the broader field of cross-lingual multimedia analysis and facilitating the development of more accessible and culturally sensitive multimedia technologies.

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Emotion analysis using self-training on malaysian code-mixed twitter data 13

Emotion analysis using self-training on malaysian code-mixed...

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13th IADIS International Conference ICT, Society and Human Beings 2020, ICT 2020 and 6th IADIS International Conference Connected Smart Cities 2020, CSC 2020 and 17th IADIS International Conference Web Based Communities and Social Media 2020, WBC 2020, Part of the 14th Multi Conference on computer science and information Systems, MCCSIS 2020

作者： Tan, Kathleen Swee Neo Lim, Tong Ming Lim, Yee Mei Department of Computer Science and Embedded Systems Faculty of Computing and Information Technology Tunku Abdul Rahman University College Kuala Lumpur Malaysia

ISBN: (纸本)9789898704191

Microblogs such as Twitter has made available a vast resource of User Generated Content (UGC) on which emotion analysis may be performed. Organizations increasingly value the opinions obtained from emotion analysis. These insights help to drive decision-making activities and provide constructive inputs to engage their customers and services. In a multiracial country such as Malaysia, it is common to find that tweets are written in mixed languages of Malay, Malaysian slang and English. These tweets increase the complexity of the emotion analysis task, especially considering that there is a serious lack of labeled data available in order to make use of supervised learning techniques. This paper explores the use of self-training, a semi-supervised technique that only requires a small initial labeled dataset to conduct emotion analysis of Malaysian code-mixed Twitter data. The results are promising as the accuracy achieved is higher compared to the baseline models. © Proceedings of the 13th IADIS International Conference ICT, Society and Human Beings 2020, ICT 2020 and Proceedings of the 6th IADIS International Conference Connected Smart Cities 2020, CSC 2020 and Proceedings of the 17th IADIS International Conference Web Based Communities and Social Media 2020, WBC 2020 - Part of the 14th Multi Conference on computer science and information Systems, MCCSIS 2020. All rights reserved.

关键词： Sentiment analysis

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A Review of Graph Theoretic and Weightage Techniques in File Carving 2

A Review of Graph Theoretic and Weightage Techniques in File...

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2nd Joint International Conference on Emerging Computing technology and Sports, JICETS 2019

作者： Sari, Sari Ali Mohamad, Kamaruddin Malik Faculty of Computer Science and Information Technology Universiti Tun Hussein Onn Malaysia 86400 Parit Raja Batu Pahat Johor Malaysia

Digital Forensics is a platform that helps in assisting investigation carried out in computer crimes through the recovery of material that is found in digital devices. Material is recovered through a method known as file carving that helps to recover data from storage media. Moreover, it also retrieves the extract hidden, overwritten or deleted files. File carving enables the file recovery without knowledge about contextual information such as file system metadata. Due to recent expansion in the research of information technology, file carving has become an essential technique for general data recovery and digital forensics investigations. Therefore, considering the important role played by file carving the present study conducted a survey of the previous literature to find out various data carving techniques. Results, from the previous literature helped to provide several algorithms for image construction which are based on graph theoretic techniques. Furthermore, the present study classifies the file carving techniques for JPEG file into two categories namely basic carving technique and advanced carving technique. The paper concludes by providing limitations in the present study which could be helpful for future investigations associated with the fragmentation problem of data files. © 2020 IOP Publishing Ltd. All rights reserved.

关键词： Metadata

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Reality considerations when designing a TDMA-FDMA based link-layer for real-time WSN

Reality considerations when designing a TDMA-FDMA based link...

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5th International Workshop on Multiple Access Communications, MACOM 2012

作者： Riliskis, Laurynas Berdajs, Jan Osipov, Evgeny Brodnik, Andrej Department of Computer Science and Electrical Engineering Luleå University of Technology 971 87 Luleå Sweden University of Ljubljana Faculty of Computer and Information Science Tržaška 25 1000 Ljubljana Slovenia

ISBN: (纸本)9783642349751

In this article we elaborate on reality considerations when designing and implementing application tailored TDMA-FDMA medium access protocol with guaranteed end-to-end delay. We highlight importance of considering underlaying hardware and software components when designing communication protocols for resource constrained platforms. We also show that by combining medium access protocol, bootstrapping, and time synchronization mechanisms within the link-layer, we can limit on average clock drift in the network to 0.5 μs, as well as achieve 81% energy efficiency while keeping collision probability at its minimum of 1%. Finally, we conclude with challenges and lessons learned in real-world deployment of TDMA/FDMA based link-layer with guaranteed end-to-end delay in WSN. © 2012 Springer-Verlag.

关键词： Wireless sensor networks

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Robust Misbehavior Detection Scheme for Vehicular Network

Robust Misbehavior Detection Scheme for Vehicular Network

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2021 International Conference on Data science and Its Applications, ICoDSA 2021

作者： Alzahrani, Mohammed Idris, Mohd. Yazid Ghaleb, Fuad A. Budiarto, Rahmat Universiti Teknologi Malaysia School of Computing Faculty of Engineering Johor Malaysia College of Computer Science Information Technology Albaha University Dept. of Computer Engineering and Science Albaha Saudi Arabia

ISBN: (纸本)9781665443036

Vehicular Ad Hoc Network VANET is emerged to improve future Intelligence Transportation Systems (ITS) and improve road safety and traffic efficiency as well as provide passenger comfort. Vehicles in VANET share their mobility status to improve application performance and provide network agility. However, misbehaving vehicles that send false mobility information can disrupt the fundamental operation of potential V ANET applications. Many solutions have been proposed to detect misbehavior data. However, most of these solutions are vulnerable to consistency-based attackers. Attackers can create false but consistent information and share it with neighboring vehicles causing serious driving situations. This study aims to design and develop a robust misbehavior detection scheme for VANET. A directional antenna and the received signal characteristics have been incorporated in the Kalman Filter state to validate the consistency of the received cooperative awareness messages. The received signal strength indicator (RSSI) and the angle of arrival (AoA) were used as trusted features that a vehicle can use to validate the correctness of the cooperative awareness messages received from neighboring vehicles. The innovation errors of the Kalman filter are used to determine the false information. That is if the message contains diverge much from its signal properties the message is considered misbehavior. The results of this study show the effectiveness of the proposed scheme for narrowing down the attack space in the future cooperative ITS. © 2021 IEEE.

关键词： Kalman filters

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Drone Gesture Control using OpenCV and Tello 8

Drone Gesture Control using OpenCV and Tello

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8th Conference on information Communication technology and Society, ICTAS 2024

作者： Khoza, Nokuthula Owolawi, Pius Malele, Vusumuzi Soshanguve Campus Tshwane University of Technology Faculty of Information and Communication Technology Department of Computer Systems Engineering Pretoria South Africa North-West University Unit for Data Science and Computing School of Computer Science and Information Systems Vanderbijlpark Campus Vanderbijlpark South Africa

ISBN: (纸本)9798350314892

Tracking a person with an onboard camera is a very difficult and perhaps technically impossible if one camera is used. In this regard, real-life projects use a series of cameras to achieve the task. The advent of camera installed drone technology has made it possible for researchers and designers to resolve the tracking issues of a single or multiple stagnant devices. This paper presents a method that makes it possible for a drone to recognize hand gestures as control mechanism and follow the person who control it. Furthermore, the method assists in drone object detection using an integrated depth camera that provides video capturing. The OpenCV and Tello were used in this project. A stabilized depth video is for use with current person trackers like the OpenCV tracker. The estimated Tello pose deduced from vision to stabilize the depth image by warping it to a virtual-static camera. This method allows the Tello to obtain not only the tracked person's position and orientation but also their full body pose, which can then be used, for instance, to recognize hand gestures and alter the Tello's behavior. This work has a potential of contributing or enhancing cutting-edge applications such as hands-free photography and videography. © 2024 IEEE.

关键词： Drones

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Wireless machine-to-machine communication for intelligent transportation systems: Internet of vehicles and vehicle to grid 40

Wireless machine-to-machine communication for intelligent tr...

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40th International Convention on information and Communication technology, Electronics and Microelectronics, MIPRO 2017

作者： Moloisane, Ntefeng Ruth Malekian, Reza Capeska Bogatinoska, Dijana Department of Electrical Electronic and Computer Engineering University of Pretoria Pretoria South Africa Faculty of Computer Science and Engineering University of Information Science and Technology St. Paul the Apostle Ohrid Macedonia

ISBN: (纸本)9789532330922

Machine to machine communication in intelligent transportation is a technology that aims to interconnect various components such as sensors, vehicles, road infrastructures and wireless networks. The significance thereof is to solve problems such as road congestion, road accidents and high vehicle fuel consumption. This paper gives an overview of how Machine-to-machine (M2M) communication can be used in intelligent transportation systems (ITS) to improve road safety and efficiency, where Vehicular ad-hoc networks (VANETs) play a major role. These applications include traffic light control, fleet management and smart grid systems. Some of M2M architectures that have been devised are also discussed. © 2017 Croatian Society MIPRO.

关键词： Machine-to-machine communication

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Faba Bean Disease Detection Using Deep Learning Techniques

Faba Bean Disease Detection Using Deep Learning Techniques

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2023 International Conference on Cyber Management and Engineering, CyMaEn 2023

作者： Salau, Ayodeji Olalekan Abeje, Bekalu Tadele Faisal, Abeer Naser Asfaw, Tesfa Tegegne Afe Babalola University Department of Electrical/Electronics and Computer Engineering Ado-Ekiti Nigeria Haramaya University College of Computing and Informatics Department of Information Technology Ethiopia Institute of Technology Faculty of Computing Bahir Dar University Department of Computer Science Ethiopia University of Sumer College of Computer Science and Information Technology Al-Rifai Iraq

ISBN: (纸本)9781665493291

Faba bean (Vicia faba L.) is an important cash crop for animal and human consumption in many countries, especially Ethiopia due to its high protein content and high rate of production. It also improves soil fertility with the help of bacteria, which forms nodules on its roots. Ethiopia is the second largest faba bean producer;however, according to research, the yield is generally low. Among the constraints contributing to low productivity of the crop, disease is the most important. Even though there are countermeasures such as the use of chemical sprays, which is used to reduce the damage or eliminate the disease, an effective disease identification technique is still required. Chocolate spot, faba bean gal, and rust are the most common diseases of faba beans. To effectively detect the disease, in this paper, we propose an end-to-end CNN model for training before and after the dataset is preprocessed. The CNN end-to-end model is trained with raw images and achieves 92.1% training accuracy. Also, the model is trained with preprocessed data and it achieves a training accuracy of 98.14% for the end-to-end CNN classifier. The results show that the proposed approach is suitable for faba bean disease detection and can be employed to detect diseases of other crops. © 2023 IEEE.

关键词： Convolutional neural networks

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