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2023 SPE Nigeria Annual International Conference and Exhibition, NAIC 2023

作者： Chinonyelum, Ejimuda Kingsley, Okoli Lilian, Uzodiagu Juliet, Olusola Department of Mechanical Engineering Texas A & M University United States Controls Lab Texas A & M University United States Department of Computer Science and Knowledge Discovery Saint Petersburg Electrotechnical University LETI Saint Petersburg Russia Artificial Intelligence Lab University of Nigeria Nsukka Nigeria Department of Electrical and Electronics Engineering Bells University of Technology Ogun State Ota Nigeria Department of Electrical and Electronics Engineering Afe Babalola University Ekiti State Ado-Ekiti Nigeria

ISBN: (纸本)9781959025177

The advancement of technology has brought about ease of life with the help of technology automation which can be applied virtually in all aspects of living. With the emergence of internet of things, prototyping real state systems has become less expensive and easy to embark on thus creating platforms for development in the oil & gas sector. This research aims to analyze, design, and develop an effortless system powered via solar energy for the control of a sprinkler system and liquid flow void of human intervention. The system was programmed using an Arduino board and other hardware at an adjustable set time with Arduino software. The research is geared at reducing human efforts in irrigation systems, to save cost and time in sprinkling liquid on any system. The use of some weather parameters like humidity, temperature, and moisture sensors;Arduino kits and GSM module constitutes the smart irrigation system setup. The system is automated to feed the necessary quantity of liquid to any given surface based on design parameters with the moisture sensor programmed within 0 to 1023 (0-100%) range. The system adapted a method of pump-start at 40% moisture reading. Various analysis of the research findings has been presented in the work with applicability in remote areas and oil fields void of human intervention. Copyright © 2023 Society of Petroleum Engineers.

关键词： Automation

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Are Your Apps Accessible? A GCN-based Accessibility Checker for Low Vision Users

arXiv

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arXiv 2025年

作者： Zhang, Mengxi Liu, Huaxiao Song, Shenning Chen, Chunyang Huang, Pei Zhao, Jian College of Computer Science and Technology Jilin University Jilin Changchun130012 China Key Laboratory of Symbolic Computation and Knowledge Engineering Ministry of Education Jilin University Jilin Changchun130012 China Department of Computer Science Technical University of Munich Heilbronn85354 Germany Department of Computer Science Stanford University CA94305 United States College of Computer Science Changchun University Jilin Changchun130012 China

Context: Accessibility issues (e.g., small size and narrow interval) in mobile applications (apps) lead to obstacles for billions of low vision users in interacting with Graphical User Interfaces (GUIs). Although GUI accessibility scanning tools exist, most of them perform rule-based check relying on complex GUI hierarchies. This might make them detect invisible redundant information, cannot handle small deviations, omit similar components, and is hard to extend. Objective: In this paper, we propose a novel approach, named ALVIN (Accessibility Checker for Low Vision), which represents the GUI as a graph and adopts the Graph Convolutional Neural Networks (GCN) to label inaccessible components. Method: ALVIN removes invisible views to prevent detecting redundancy and uses annotations from low vision users to handle small deviations. Also, the GCN model could consider the relations between GUI components, connecting similar components and reducing the possibility of omission. ALVIN only requires users to annotate the relevant dataset when detecting new kinds of issues. Results: Our experiments on 48 apps demonstrate the effectiveness of ALVIN, with precision of 83.5%, recall of 78.9%, and F1-score of 81.2%, outperforming baseline methods. In RQ2, the usefulness is verified through 20 issues submitted to open-source apps. The RQ3 also illustrates the GCN model is better than other models. Conclusion: To summarize, our proposed approach can effectively detect accessibility issues in GUIs for low vision users, thereby guiding developers in fixing them efficiently. Copyright © 2025, The Authors. All rights reserved.

关键词： Convolutional neural networks

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Face Recognition Based On Fusion Feature Extraction Algorithms

Face Recognition Based On Fusion Feature Extraction Algorith...

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Emerging Smart Computing and Informatics (ESCI), Conference on

作者： Ibrahim Mahmood Rashid Albakri Muhammad Imran Ahmad Mohd Nazrin Md Isa Mustafa Zuhaer Nayef Al-Dabagh Faculty of Electronic Engineering Technology Universiti Malaysia Perlis Perlis Malaysia Collage of Agriculture Telafer University Telafer Iraq Department of Computer Science Knowledge University Erbil Iraq

Biometric-based methods have emerged as a highly promising avenue for individual recognition, with face recognition standing out as a key application in image analysis. Facial recognition systems are affected by various image condition factors, including expressions, occlusion, poses, and illuminations. It is crucial to consider reasonable variations in illumination between gallery and probe images when developing face recognition algorithms. In the context of face verification, illumination variation significantly influences the likelihood of misclassification. Existing research lacks a focus on imaging conditions, especially regarding illumination, in face recognition systems. This research aims to identify and design a scheme to address illumination variation in facial recognition. The proposed scheme will undergo analysis and evaluation to assess its accuracy and effectiveness. The image processing in this research is divided into two phases. The first is the preprocessing phase, encompassing auto contrast balancing and noise reduction. The second phase is face processing, which involves illumination normalization, face detection, feature extraction, and face recognition. Two datasets are utilized: the first being the ORL dataset, which includes images with illumination variations, and the second being the Yale database, where images contain various noises.

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Research on Conceptual Model of the Remote Sensing Big Data Workflow 5

Research on Conceptual Model of the Remote Sensing Big Data ...

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5th International Conference on E-Business, Information Management and computer science, EBIMCS 2022

作者： Du, Ying Zhang, Shuo Kaabar, Mohammed K.A. Yue, Xiao-Guang School of Computer and Information Engineering Henan University Kaifeng475004 China Institute of Mathematical Sciences Faculty of Science University Malaya Kuala Lumpur50603 Malaysia Department of Computer Science and Engineering European University Cyprus Nicosia1516 Cyprus Department of Information and Knowledge Management School of Consumer Intelligence and Information Systems University of Johannesburg Apk Campus Johannesburg2006 South Africa

ISBN: (纸本)9781450397834

Remote sensing big data workflows are formed by combining workflow and the remote sensing data processing system, and have the capabilities of remote sensing data processing, analysis, and visualization. There are many issues such as numerous sensors, sophisticated processing algorithms, and lacking of a unified process management about the operation control of the remote sensing data processing system. Therefore, the concept and characteristics of remote sensing big data workflows is reanalysed and the metamodel of remote sensing big data workflows from different aspects is constructed in order to establish a conceptual framework of them, and thus establish concept framework of Remote Sensing Big Data Workflow. © 2022 ACM.

关键词： Remote sensing

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Paris: Polarization-aware Recommender Interactive System 2

Paris: Polarization-aware Recommender Interactive System

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2nd Workshop on Online Misinformation- and Harm-Aware Recommender Systems, OHARS 2021

作者： Badami, Mahsa Nasraoui, Olfa Knowledge Discovery and Web Mining Lab Computer Engineering and Computer Science Department University of Louisville 132 Eastern Parkway LouisvilleKY40292 United States

One phenomenon that has been recently observed online is the emergence of polarization among users on social networks, where the population gets divided in groups with opposite opinions. As recommender system algorithms become more selective in filtering what users see and discover, one important question arises: Could recommender system algorithms become more selective in filtering what users see and discover? In this paper, we study this question and propose a new counter-polarization approach for existing Matrix Factorization based recommender systems, that can be tuned by a user-controlled counter-polarization parameter which serves like a voluntary user anti-polarization or discovery dial. © 2021 Copyright for this paper by its authors. Use permitted under Creative Commons License Attribution 4.0 International (CC BY 4.0).

关键词： Recommender systems

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Unsupervised Statistical Text Simplification

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IEEE Transactions on knowledge and Data engineering 2021年第4期33卷 1802-1806页

作者： Qiang, Jipeng Wu, Xindong Department of Computer Science Yangzhou University Yangzhou Jiangsu225127 China Key Laboratory of Knowledge Engineering with Big Data Hefei University of Technology Ministry of Education Hefei Anhui10084 China

Most recent approaches for Text Simplification (TS) have drawn on insights from machine translation to learn simplification rewrites from the monolingual parallel corpus of complex and simple sentences, yet their effectiveness strongly relies on large amounts of parallel sentences. However, there has been a serious problem haunting TS for decades, that is, the availability of parallel TS corpora is scarce or not fit for the learning task. In this paper, we will focus on one especially useful and challenging problem of unsupervised TS without a single parallel sentence. To the best of our knowledge, we present the first unsupervised text simplification system based on phrase-based machine translation system, which leverages a careful initialization of phrase tables and language models. On the widely used WikiLarge and WikiSmall benchmarks, our system respectively obtains 39.08 and 25.12 SARI points, even outperforms some supervised baselines. © 1989-2012 IEEE.

关键词： Machine translation

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Computational Intelligence in Business Management: Strategies for Innovation and Optimization 6

Computational Intelligence in Business Management: Strategie...

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6th International Congress on Human-computer Interaction, Optimization and Robotic Applications, HORA 2024

作者： Ahmed, Saadaldeen Rashid Hussein, Ali Jabbar ALhashmi, Lubna Qassim Al-Attar, Bourair Dheeb, Shaymaa Majeed, Duaa A. Hussain, Abadal-Salam T. Tawfeq, Jamal Fadhil Computer Science Department Bayan University Kurdistan Erbil Iraq Artificial Intelligence Engineering Department College of Engineering Al-Ayen University Thi-Qar Iraq Al Hikma University College Baghdad Iraq Department of information and knowledge technologies College of Arts Basrah University Basrah Iraq College of Medicin University of Al-Ameed Karbala PO Box 198 Iraq Department of Cyber Security and Cloud Computing Al-Ma’moon University College Al-Washash Baghdad Iraq Aeronautical Engineering Department Baghdad University Baghdad Iraq College of Technical Engineering National University of Science and Technology Dhi Qar Iraq Department of Medical Instrumentation Techniques Engineering Technical Engineering College Al-Kitab University Altun Kupri Kirkuk Iraq Department of Medical Instrumentation Technical Engineering Medical Technical College Al-Farahidi University Baghdad Iraq

ISBN: (纸本)9798350394634

In today's competitive corporate landscape, the successful integration of computational intelligence approaches provides a key edge for decision-making processes. Despite developments, there is a gap in understanding the subtle application of such methodologies in corporate management, particularly within retail environments. To address this gap, our study combines decision trees and artificial neural networks to evaluate retail transaction data, concentrating on customer behavior and purchase trends. Leveraging a comprehensive dataset spanning client demographics, transaction details, and product information, our study provides substantial insights. Results suggest an 87% accuracy rate reached by artificial neural networks in forecasting client preferences. This study contributes to bridging the research gap by giving actionable insights into the practical application of computational intelligence in boosting company strategies and decision-making processes within the retail industry. © 2024 IEEE.

关键词： Decision trees

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Altered Cloud Service Composition Techniques for Enhanced Integration

Altered Cloud Service Composition Techniques for Enhanced In...

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Emerging Trends in Industry 4.0 (ETI 4.0)

作者： Nancy Arya Priyanka Gupta B Rajalakshmi Ginni Nijhawan Praveen Hareth A. Alrikabi Department of Computer Science and Engineering Shree Guru Gobind Singh Tricentenary University Gurugram Institute of Aeronautical Engineering Dundigal Hyderabad Department of Computer Science New Horizon College of Engineering Bangalore Lovely Professional University Phagwara Lloyd Institute of Engineering & Technology Knowledge Park II Greater Noida Uttar Pradesh Collage of Dentist National University of Science and Technology Dhi Qar Iraq

ISBN: (数字)9798350373783

ISBN: (纸本)9798350373790

Create dynamic, dependable, and cost-effective cloud service combinations using the Dynamic Cloud Service Composition (DCSC) approach. Service Ranking (SR), Adaptive Composition (AC), and Cost Optimization algorithm are used in this strategy. Their combined efforts classify services by QoS, generate flexible compositions, and minimize prices. The most important factors for ranking service quality can be found using weighted numbers. It is possible to achieve dynamic flexibility by keeping an eye on service traits and using Adaptive Composition to start reconfigurations. Cutting costs without lowering the standard of service is what cost optimization is all about. Economically beneficial compositions result. Performance Score (PS), Adaptation Rate (AR), Cost Efficiency (CE), Resilience Index (RI), Resource Utilization (RU), and (ACost) are evaluated.

关键词： Technological innovation Costs Quality of service Writing Resource management Reliability Optimization

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Improving Multi-Factor Authentication Security with Deep Learning-Based User Behaviour Analysis

Improving Multi-Factor Authentication Security with Deep Lea...

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Integrated Circuits and Communication Systems (ICICACS), IEEE International Conference on

作者： Fahad Sulaiman Mohammed Alnafea Alok Singh Sengar Noor Kaylan Hamid Kuttimarks Muthu Selladurai Sharmeen Izzat Hassan R Saravanakumar Department of Accounting College of Business and Economics in Qassim University Buraida Saudi Arabia Department of Computer Science & Engineering Haridwar University Roorkee India Department of Computer Education Al Kitab University Kirkuk Iraq Shivajirao S. Jondhle College of Engineering and Technology Asangaon India Department of Computer Engineering College of Engineering Knowledge University Erbil Iraq Department of ECE Saveetha School of Engineering Saveetha Institute of Medical and Technical Sciences Saveetha University Chennai India

ISBN: (数字)9798331508456

ISBN: (纸本)9798331508463

With growing frequency and sophistication of cyber threats, there is an urgent need for more adaptive, secure multi-factor authentication systems. Traditional approaches often tend to make static factor-based authentication systems that just ignore the dynamic nature of user behavior and are constantly at risk from evolved attacks against authentication mechanisms. This paper presents a novel hybrid deep learning approach - that of long short-term memory networks and convolutional neural networks combined in an attempt to address these disadvantages and enhance the security of an MFA system. The approach uses LSTM to analyze sequential data on user behavior, hence recognizing long-term dependencies like login pattern and session durations. On the other hand, CNN layers will classify the attribute by learning the spatial hierarchy thus identifying small variations that can mark emerging threats to security. This method, in contrast to others, analyzes statically or all at once, providing a dynamic check into the temporal as well as spatial aspects of user interactions; thus, there is more force in its frame for anomaly detection. Experimental tests further verify the excellent performance of the system, with results indicating an accuracy of 98.2%, precision of 99.9%, recall of 99.5%, and an F1 score of 99%. The new strategy exploits MFA frameworks more effectively in minimizing their vulnerabilities against authentication attacks, while developing a dynamic and robust solution that caters to the shift in the ever-changing landscape within cybersecurity, thus advancing the possibility of practice securely.

关键词： Deep learning Hands Multi-factor authentication Accuracy Neural networks Reflection Pattern recognition Convolutional neural networks Integrated circuit modeling Long short term memory

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Opportunities for rationalization the electricity consumption of a port complex 8

Opportunities for rationalization the electricity consumptio...

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8th International Conference on Energy Efficiency and Agricultural engineering, EE and AE 2022

作者： Simeonova, Neli Georgiev, Ginko Kirov, Rumen Ivanov, Venelin Department of Electronic Electrical Engineering and Machine Knowledge University Prof. D-r. Asen Zlatarov Burgas Bulgaria Burgas Free University Department of Computer Science and Engineering Burgas Bulgaria Technical University - Varna Department of Electric Power Supply and Equipment Varna Bulgaria Burgas Bulgaria

ISBN: (纸本)9781665407090

The research on the different characteristics of the power supply system (PSS) of a port complex is done in order to identify measures to improve the operating modes. In general, the features and requirements for the power supply and electrical equipment of the site are presented and the main energy parameters of the main consumers are marked. A theoretical formulation of the study has been synthesized, giving the opportunity to make an analysis of the characteristic coefficients of energy consumption and the additional power losses from the unevenness of the load schedule. A total of seven power substations and 11 outputs were examined and the measurements were performed with professional network analyzers. The results are presented in tabular form and provide an opportunity to make a thorough analysis of the state of the PSS of the site. Based on them, technological solutions can be offered to rationalize the electricity supply and achieve savings in electricity. © 2022 IEEE.

关键词： Power transformers

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