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Application of VGIS Digital Twin Platform for Enhanced Oilfield Disaster Management and Environmental Protection

Informatica (Slovenia) 2024年第14期48卷 27-42页

作者： Alabbasi, Awab Aljabery, Maalim A. Bölük, Pınar Sarısaray Faculty of Engineering and Natural Sciences Electrical and Computer Engineering Dept. Bahcesehir University Istanbul34353 Turkey Faculty of Computer Science and Information Technology Computer Science Dept. University of Basrah Basrah61004 Iraq Faculty of Engineering and Natural Sciences Software Engineering Dept. Bahçeşehir University Istanbul34353 Turkey

VGIS (Virtual Geographic information System) Platform is a unified oilfield operations management platform based on MaaS (Management as a Service) that integrates advanced technologies such as AIoT (Artificial Intelligence & Internet of Things), GIS (Geographic information System), Digital Twin, and AR (Augmented Reality)/ VR (Virtual Reality). The VGIS platform connects, collects, integrates, analyses, and acts on disparate data sources to provide the oilfield with a centralized view to help make informed decisions fast, bring operational visibility across all assets to improve safety and operational efficiency, reduce costs and improve margins, provide comprehensive analytics and decision support, increase business agility, and reduce management complexity. This is a case study of the application of the VGIS platform Majnoon oilfield, Basrah, Iraq. VGIS digital transformation, production process, and KPIs (Key performance indicators) are highly managed taking oilfield management to a higher level globally, in this study, the objective is to address and resolve the issue of high costs associated with using cloud services by utilising a local Data Center (a large group of networked computer servers typically used by organizations for the remote storage, processing, or distribution of large amounts of data). This approach involves directly uploading 3D maps to ensure faster service on the intranet, eliminating the need to pay for cloud *** aims providing a platform for researching and implementing monitoring and controlling processes in a more convenient and remote manner. The vGIS platform has emerged as a crucial instrument in the realm of disaster response and crisis management. This technology enables responders to rapidly evaluate, analyse, and respond to crucial information in real-time. This research examined the application of vGIS technology in disaster response and analyse the potential advantages and obstacles associated with its utilisation. © 2

关键词： information management

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Prediction and Management of Traffic Congestion in Urban Environments 15

Prediction and Management of Traffic Congestion in Urban Env...

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15th International Conference on Computing Communication and Networking Technologies, ICCCNT 2024

作者： Gwalani, Aryan Pai, Abhishek Padalia, Adish Bhavathankar, Prasenjit Devadkar, Kailas Sardar Patel Institute of Technology Dept. of Information Technology Mumbai India Sardar Patel Institute of Technology Dept. of Computer Engineering Mumbai India

ISBN: (纸本)9798350370249

Efficient urban traffic congestion management is paramount for ensuring smooth vehicular flow, minimizing travel time, and reducing environmental pollution. In this context, utilizing intelligent intersection technologies emerges as a promising approach to tackling traffic challenges effectively. This paper presents an in-dept. analysis of the 'Intelligent Intersection' framework, a novel system designed to optimize traffic flow at intersections through advanced sensing, data processing, and control mechanisms. The research integrates the Gated Recurrent Unit (GRU) model for urban traffic prediction, Simulation of Urban Mobility (SUMO) for realistic traffic simulations, and adaptive traffic light control algorithms. Additionally, the integration of Vehicle-to-Infrastructure (V2I) communication, particularly Dedicated Short Range Communication (DSRC), facilitates efficient coordination between vehicles and infrastructure elements. Through comprehensive experimentation and evaluation, the effectiveness of this approach in mitigating traffic congestion, reducing travel time, and promoting sustainable transportation practices is demonstrated. This research contributes to the advancement of intelligent transportation systems and lays the groundwork for future innovations in urban mobility management. © 2024 IEEE.

关键词： Travel time

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Skyline Algorithm based on QoS to improve Web Services: A Review 6

Skyline Algorithm based on QoS to improve Web Services: A Re...

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6th Parul International Conference on Engineering and technology, PICET 2024

作者： Barge, Yamini Patel, Tanvi Purohit, Lalit Dept. of Computer Science Engineering Parul University Vadodara India Dept. of Information Technology SGSITS Indore India

ISBN: (纸本)9798350369748

The popularity of Web Service-based systems is due to the advantage of flexibility, reusability and support for rapid system development. Web Service selection is a very important step for these web service-based systems. The skyline technique is widely used in the past for the selection of web services. In this work, an exhaustive study of Skyline-based web service selection techniques is presented. A review of the existing state-of-the-art is presented based on the approach followed for selection of web services, the advantages of using the proposed approach, the limitations of the approach and the problem addressed. © 2024 IEEE.

关键词： Web services

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Reviewlogy: An Interface for Analyzing Sentiments 3

Reviewlogy: An Interface for Analyzing Sentiments

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3rd IEEE World Conference on Applied Intelligence and Computing, AIC 2024

作者： Shyam, Radhey Khanna, Shilpi Srivastava, Kavya Srivastava, Ajay Kumar Chaudhary, Ishika Bbd University Dept. of Computer Science & Engineering Lucknow India Srmcem Dept. of Information Technology Lucknow India

ISBN: (纸本)9798350384598

This paper investigates the impact of early reviews on product sales by analyzing the traits of initial reviewers on major e-commerce platforms. It segments product life-cycles into three phases: early, majority, and laggards, focusing on early reviewers who post reviews during the initial stages. The paper introduces an innovative interface for sentiment analysis to identify and predict early reviewers. Quantitative analysis reveals that early reviewers often provide more insightful comments and give higher overall ratings. Their ratings and helpfulness scores significantly affect product popularity. The methodology, tested on extensive datasets from Amazon and Yelp, extracts crucial attributes of early reviewers, including purchasing patterns and social impact. The interface employs a hybrid machine learning approach combining Naive Bayes, margin-based embedding ranking models (MERM), and support vector machines (SVMs) to predict potential early reviewers accurately. This approach balances probabilistic reasoning with robust classification, ensuring comprehensive forecasting. Evaluation metrics such as precision and accuracy demonstrate the effectiveness of the models over baseline methods. Furthermore, the study enhances the understanding of how early reviews influence consumer behavior and product success in e-commerce. The interface aids in refining product marketing strategies by enabling precise targeting of early reviewers, accelerating product adoption, amplifying sales, and optimizing marketing tactics in the competitive e-commerce landscape. © 2024 IEEE.

关键词： Support vector machines

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Improving Fake News Detection with a Mixture of Experts: Leveraging Sentiment Analysis and Sarcasm Detection as Core Expert Models 6

Improving Fake News Detection with a Mixture of Experts: Lev...

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6th International Conference on Advancements in Computing, ICAC 2024

作者： Gunasekara, Tharindu Thihan, Disira Kodithuwakku, Sansika Dissanayake, Dinuka Fernando, Harinda Vidhanaarachchi, Samitha Sindhujan, Archchana Sri Lanka Institute of Information Technology Malabe Dept. of Software Engineering Sri Lanka Sri Lanka Institute of Information Technology Malabe Dept. of Computer Computer Systems Engineering Sri Lanka University of Surrey Dept. of Computer Science and Electronic Engineering United Kingdom

ISBN: (纸本)9798331517878

Fake news continues to proliferate, posing an increasing threat to public discourse. The paper proposes a framework of a Mixture of Experts, Sentiment Analysis, and Sarcasm Detection experts for improved fake news detection. This approach captures the emotional cues in the text through a Sentiment Analysis expert, which is based on bidirectional encoder representations from Transformers (BERT) models with sentiment vectors generated using SentiWordNet and Integrated Gradients. It combines a sarcasm detection expert based on BERT, recognizing sarcasm and its type to help classify fake news. By fusing these experts through a Mixture of Experts gateway, subtle linguistic cues often found in fake news are more effectively analyzed, leading to improved accuracy in detecting misinformation. Experimental results are presented as 96% for the Sarcasm expert with the BERT base model and 83% for the Sentiment Analysis expert with the distilled version of the BERT (DistilBERT) base model, proving the effectiveness of the proposed approach in beating traditional methods. © 2024 IEEE.

关键词： fake news detection gateway mixture of experts sarcasm detection sentiment analysis

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Pathways for Security of Embedded System: Issues and Challenges 2

Pathways for Security of Embedded System: Issues and Challen...

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2nd International Conference Computational and Characterization Techniques in Engineering and Sciences, IC3TES 2024

作者： Diwaker, Sanjai K. Chaurasia, Pawan Kumar Khaliq, Mazhar Khwaja Moinuddin Chishti Language Dept. of Computer Science and Information Technology Lucknow India Babasaheb Bhimrao Ambedkar Central University Dept. of Information Technology Lucknow India

ISBN: (纸本)9798350364699

In today's scenario, security threats are increasing day by day as technology. Security breaches not only affect financial loss but also affect the trustworthiness and integrity of the software design and embedded software development industry. These breaches directly affect the security attributes. The objective of security in an embedded system is to protect the device from vulnerable attributes. The aim of this paper, identify challenges in embedded systems applied in various applications, research gaps, and untouched areas to discover possible parameters for sustainable devices. © 2024 IEEE.

关键词： Access Control Authenticity Authorization Cyber security Device Manager Healthcare Internet of Medical Things

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An Advance Boosting Approach for Multiclass Dry Bean Classification

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Journal of Engineering Science and technology Review 2023年第2期16卷 107-115页

作者： Nayak, Janmenjoy Dash, Pandit Byomokesha Naik, Bighnaraj Dept. of Computer Science Maharaja Sriram Chandra Bhanja Deo University Odisha Baripada757003 India Dept. of Information Technology Aditya Institute of Technology and Management AP Tekkali532201 India Dept. of Computer Application Veer Surendra Sai University of Technology Burla768018 India

Dry beans, which are produced in large quantities, have the highest level of genetic diversity. The quality of seeds has a significant impact on crop yield. The importance of seed classification to both marketing and production can be shown by realizing that sustainable agricultural systems depend on these principles. This research is primarily aimed at providing a means to generate uniform seed varieties, as seed is not certified as a single variety. To achieve consistent seed classification, we have proposed Extreme Gradient Boosting ensembles using the Synthetic Minority Over-Sampling Methodology (SMOTE) to differentiate seven distinct registered types of dry beans with similar characteristics. There were a total of 13,611 grains from seven different varieties of dry beans sampled for the classification model. Classification algorithms based on machine learning like Decision Tree (DT), Support Vector Machine (SVM), Multilayer Perceptron (MLP), Adaptive Boosting classifier, Bagging Classifier, and Extreme Gradient Boosting ensembles using the Synthetic Minority Over-Sampling Methodology (SMOTE) were developed and compared. Overall correct classification rates for SVM, MLP, DT, Adaboost, Bagging, and Extreme Gradient Boost classifiers were 94.44%, 94.48%, 96.53%, 96.35%, 96.89%, and 97.32%, respectively. Extreme Gradient Boosting ensembles using the SMOTE classification model have the best accuracy. The results of this study satisfy the producers' and customers' demand for uniform bean varieties. © 2023 School of Science, IHU. All rights reserved.

关键词： Adaptive boosting

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A New architecture for Decentralized Cybersecurity Mesh (DCSM) Using Blockchain technology for Distributed Networks 1

A New Architecture for Decentralized Cybersecurity Mesh (DCS...

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1st International Conference on Emerging Technologies for Dependable Internet of Things, ICETI 2024

作者： Al-Hussaini, Khalid Al-Swidi, Asalah Abdulkareem Information Technology Dept. Thamar University Dhamar Yemen Computer Science Dept. Thamar University Dhamar Yemen

ISBN: (纸本)9798331533557

Cybersecurity Mesh architecture (CSMA) is a promising new approach to cybersecurity that has the potential to improve network and information security. As networks become more complex and widespread, detecting and responding to threats has become more difficult. It has also led to security creep that leads to complexity of management, fragmentation of visibility, and limits organizations ability to respond effectively to threats. These and similar challenges have made integration with CSMA a necessity for today's organizations. The cybersecurity mesh can be viewed as centralizing security management and distributing the application of this management, but in some completely distributed networks, such as the Internet of Things (IoT), Cloud Computing, Edge Computing, Big Data, etc., the cybersecurity mesh is not compatible with them because it applies the principle of central management. Therefore, the researchers propose, in this paper, to change the cybersecurity mesh architecture. The cybersecurity mesh will be completely distributed using blockchain technology, where the network security infrastructure will first be changed to the blockchain network. After that, blockchain technology will be integrated into each layer of the proposed cybersecurity mesh. Finally, the proposed architecture will be evaluated by ensuring complete distribution and the expected security provided by the cybersecurity mesh. © 2024 IEEE.

关键词： Blockchain technology Decentralized Cybersecurity Mesh architecture DCSMA Distributed Networks and Technologies Zero Trust Model ZTM

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Optimizing Location Allocation in Urban Management: A Brief Review 29

Optimizing Location Allocation in Urban Management: A Brief ...

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29th International computer Conference, computer Society of Iran, CSICC 2025

作者： Ayati, Aref Naji, Hamid Reza Hashemi, Mohammad Mahdi Saffar, Mohsen Dept. of Computer Engineering and Information Technology Graduate University of Advanced Technology Kerman Iran

ISBN: (纸本)9798331523114

Various issues in the fields of urban management, digital transformation, and smart cities have been presented recently. Currently, we like to attend to optimizing location allocation problems that can be a new part of digital transformation in urban management (such as locating and placing facilities, locating and arranging centers such as aid and rescue centers, or even postal hubs, telecommunications, electronic equipment, data centers, and routing in transportation optimization). These issues, which are seemingly simple but in practice complex, are important in urban environments, and the issue of accurate location allocation based on existing criteria directly impacts cost management, profit, efficiency, and citizen satisfaction. In recent years, researchers have used or presented various models and methods for location allocation problems, some of which will be mentioned in this article. This review examines heuristic and meta-heuristic approaches, including GA, PSO, and GIS-based models, highlighting their applications and limitations in urban management optimization. Finally, a brief conclusion will be made of the existing methods and some of their weaknesses, and suggestions will be made for continuing the path and improving scientific and practical research in this field. © 2025 IEEE.

关键词： Urban transportation

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Quantitative Analysis and Forecasting in Finance: Leveraging Wavelet Packet Transform for Enhanced Market Insights

Quantitative Analysis and Forecasting in Finance: Leveraging...

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2024 International Conference on Communication, Computing and Internet of Things, IC3IoT 2024

作者： Libina, M. Kavitha, C. Kabilan, A. Ifet College Of Engineering Dept. Of Information Technology Villupuram India Manakula Vinayagar Institute Of Technology Dept. Of Computer Science Puducherry India

ISBN: (纸本)9798350352689

Finance forecasting is always known for its ever-changing and complex nature in geopolitical markets, requiring advanced analytical tools to provide valuable deep insights for financial advisors, investors, and vital decision-makers. In this study, we delve into the realm of both quantitative analysis and forecasting in finance-related markets, utilizing sophisticated techniques to enhance our understanding of the markets. Our study focuses on the innovative utilization of the Optimized Wavelet Packet Transform (WPT), an advanced tool for processing signals, to uncover complex patterns within financial time series data through quantitative analysis using Plotly's interactive line charts. It bridges the gap between quantitative analysis and forecasting. It also reaches an accuracy rate of 99.5%, which is considered the best among the other prediction models. These insights help stakeholders and advisors navigate the ever-evolving landscape of financial markets and make decisions wisely. © 2024 IEEE.

关键词： Forecasting

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