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37th AAAI Conference on Artificial Intelligence, AAAI 2023

作者： Schierreich, Šimon Department of Theoretical Computer Science Faculty of Information Technology Czech Technical University in Prague Prague Czech Republic

ISBN: (纸本)9781577358800

Modern social networks are dynamic in their nature;new connections are appearing and old connections are disappearing all the time. However, in our algorithmic and complexity studies, we usually model social networks as static graphs. In this paper, we propose a new paradigm for the study of the well-known TARGET SET SELECTION problem, which is a fundamental problem in viral marketing and the spread of opinion through social networks. In particular, we use temporal graphs to capture the dynamic nature of social networks. We show that the temporal interpretation is, unsurprisingly, NP-complete in general. Then, we study computational complexity of this problem for multiple restrictions of both the threshold function and the underlying graph structure and provide multiple hardness lower-bounds. Copyright © 2023, Association for the Advancement of Artificial Intelligence (***). All rights reserved.

关键词： Computational complexity

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Secure Decentralized File Sharing 4

Secure Decentralized File Sharing

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4th IEEE International Conference on Mobile Networks and Wireless Communications, ICMNWC 2024

作者： Usha, B.A. Aruna, S. Bms Institute of Technology and Management Department of Computer Science and Engineering Bengaluru India Bms Institute of Technology and Management Department of Information Science and Engineering Bengaluru India

ISBN: (数字)9798331528348

ISBN: (纸本)9798350352931

Current file sharing solutions have problems such as data loss, unauthorized access and have only one point of failure are insecure and unreliable. To overcome these challenges, this work proposes a Decentralized File Sharing system that optimizes the transfer of data securely and with high reliability. Others include decentralised storage by use of IPFS and Pinata, and safety of the file through AES encryption. Password de- cryption is ensured only by the recipient keeping the password, while MetaMask authentication is connected to the Ethereum network. To protect information integrity every file has a Content Identifier coded as CID. The benchmark assessments reveal that the execution time increases with lower variance for smaller file sizes and varies slightly with larger files. As for decentralized approaches they are protected from focused attacks, more reliable in terms of failures, and have much better scalability than the centralized ones providing a much better solution for file sharing. © 2024 IEEE.

关键词： Wireless communication Sharding Smart contracts Authentication Passwords Peer-to-peer computing Encryption Safety Reliability Standards

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An upgraded variant of backtracking search algorithm and its application to COVID-19 CT images segmentation

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Multimedia Tools and Applications 2025年 1-57页

作者： Debnath, Sanjib Nama, Sukanta Chakraborty, Sanjoy Saha, Apu Kumar Mirjalili, Seyedali Department of Computer Science & Engineering National Institute of Technology Agartala Tripura Agartala799046 India Department of Science & Humanities Gomati District Polytechnic Fulkumari Tripura Udaipur799013 India Department of Information Technology Bir Bikram Memorial College Tripura Agartala India Department of Mathematics National Institute of Technology Agartala Tripura Agartala799046 India Center for Artificial Intelligence Research and Optimization Torrens University Australia Brisbane Australia Faculty of Electrical Engineering and Computer Science VŠB-TU Ostrava Ostrava Czech Republic University Research and Innovation Center Obuda University Budapest Hungary Department of Computer Science & Engineering The ICFAI University Tripura Tripura 799210 India

To improve the performance of the original backtracking search algorithm (BSA), this work combines BSA with a centralized population initialization and an elitism-based local escape operator and proposes a new, improved variant of BSA called CiBSA. BSA's performance is improved by centralized population initialization regarding search capability, convergence speed, and capacity to jump out of the local optimum. The suggested algorithm's elitism-based local escape operator method prevents BSA searching slowness and enhances convergence rates and local search efficiency. The performance of the proposed algorithm has been tested on a set of 54 test suites. An extensive comparison with other recent meta-heuristics algorithms (MA) demonstrates that both methodologies substantially assist BSA in boosting the quality of its solutions and speeding up the convergence rate. The proposed CiBSA is then applied to a real-world problem: image segmentation using Kapur's entropy function. The proposed CiBSA is successfully applied to the segmentation of COVID-19 CT images using Kapur's entropy for grey-scale images. Considering the performance matrices Peak Signal-to-Noise Ratio (PSNR), Structural Similarity Index (SSIM), Feature Similarity Index (FSIM), and Intersection over Union (IoU), the suggested CiBSA outperformed conventional MA algorithms. In COVID-19 CT image segmentation trials, CiBSA has superior segmentation capability and adaptability at varied threshold levels than other approaches. As a result, CiBSA has a lot of potential for enhancing COVID-19 diagnosis accuracy. © The Author(s), under exclusive licence to Springer science+Business Media, LLC, part of Springer Nature 2024.

关键词： Signal to noise ratio

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Geometric behavior of the generalized Hadid-Luchko convolution operator in the open unit ball

Geometric behavior of the generalized Hadid-Luchko convoluti...

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2023 International Conference on Fractional Differentiation and Its Applications, ICFDA 2023

作者： Hadid, Samir B. Ibrahim, Rabha W. Obaiys, Suzan J. Nadia M. G, Al-Saidi Ajman University Department of Mathematics and Sciences College of Humanities and Sciences Ajman United Arab Emirates Ajman United Arab Emirates Lebanese American University Department of Computer Science and Mathematics Beirut Lebanon University of Malaya Faculty of Computer Science and Information Technology Department of Computer System & Technology Kuala Lumpur Malaysia University of Technology Department of Applied Sciences Iraq

ISBN: (纸本)9798350321685

In this effort, by consuming the k-symbol calculus, we generalize the Hdid-Luchko function (the Mittag-Leffler function of several variables). Some inequalities are established containing the normalized type of this function. In addition, we illustrate a list of conditions on the function to recognize some special geometric properties in a unit ball. Our theory is based on the differential subordination of several variables. © 2023 IEEE.

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Applications of Artificial Intelligence in the Economy, Including Applications in Stock Trading, Market Analysis, and Risk Management

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IEEE Access 2023年 11卷 80769-80793页

作者： Rahmani, Amir Masoud Rezazadeh, Bahareh Haghparast, Majid Chang, Wei-Che Ting, Shen Guan National Yunlin University of Science and Technology Future Technology Research Center Yunlin Douliou64002 Taiwan Islamic Azad University Science and Research Branch Department of Computer Engineering Tehran*** Iran University of Jyväskylä Faculty of Information Technology Jyväskylä40014 Finland

In an increasingly automated world, Artificial Intelligence (AI) promises to revolutionize how people work, consume, and develop their societies. science and technology advancement has led humans to seek solutions to problems;however, AI-based technology is not novel and has a wide range of economic applications. This paper examines AI applications in economics, including stock trading, market analysis, and risk assessment. A comprehensive taxonomy is proposed to investigate AI applications in various scopes of the proposed categories. Furthermore, we will discuss this area's most significant AI-based techniques and evaluation criteria. As a final step, we will identify challenges, open issues, and future work suggestions. © 2013 IEEE.

关键词： Decision making

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A Sustainable WSN system with Heuristic Schemes in IIoT

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computers, Materials & Continua 2022年第9期72卷 4215-4231页

作者： Wenjun Li Siyang Zhang Guangwei Wu Aldosary Saad Amr Tolba Gwang-jun Kim School of Computer and Communication Engineering Changsha University of Science and TechnologyChangsha410114China College of Computer and Information Engineering Central South University of Forestry and TechnologyChangsha410114China Computer Science Department Community CollegeKing Saud UniversityRiyadh11437Saudi Arabia Mathematics and Computer Science Department Faculty of ScienceMenoufia UniversityEgypt Department of Computer Engineering Chonnam National UniversityGwangju61186Korea

Recently, the development of Industrial Internet of Things hastaken the advantage of 5G network to be more powerful and more ***, the upgrading of 5G network will cause a variety of issues increase,one of them is the increased cost of coverage. In this paper, we proposea sustainable wireless sensor networks system, which avoids the problemsbrought by 5G network system to some extent. In this system, deployingrelays and selecting routing are for the sake of communication and *** main aim is to minimize the total energy-cost of communication underthe precondition, where each terminal with low-power should be charged byat least one relay. Furthermore, from the perspective of graph theory, weextract a combinatorial optimization problem from this system. After that,as to four different cases, there are corresponding different versions of theproblem. We give the proofs of computational complexity for these problems,and two heuristic algorithms for one of them are proposed. Finally, theextensive experiments compare and demonstrate the performances of thesetwo algorithms.

关键词： Industrial Internet of Things sustainable wireless sensor network system combinatorial optimization problem heuristic algorithms

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Real-Time Road Damage Detection and Infrastructure Evaluation Leveraging Unmanned Aerial Vehicles and Tiny Machine Learning

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IEEE Internet of Things Journal 2024年第12期11卷 21347-21358页

作者： Khan, Muhammad Waseem Obaidat, Mohammad S. Mahmood, Khalid Batool, Dania Badar, Hafiz Muhammad Sanaullah Aamir, Muhammad Gao, Wu Comsats University Islamabad Sahiwal Campus Department Of Computer Science Sahiwal57000 Pakistan Superior University Department Of Computer Science Lahore54000 Pakistan The University Of Jordan King Abdullah Ii School Of Information Technology Amman11942 Jordan University Of Science And Technology Beijing School Of Communication And Computing Engineering Beijing100083 China Amity University Amity School Of Engineering And Technology Uttar Pradesh Noida201301 India National Yunlin University Of Science And Technology Graduate School Of Intelligent Data Science Douliu64002 Taiwan University Of Palermo Department Of Engineering Palermo90133 Italy Emerson University Department Of Emerging Computing Technologies Multan60000 Pakistan Northwestern Polytechnical University Center For Bio-Inspired System-on-Chip School Of Computer Science Xi'an710060 China

Road damage detection (RDD) through computer vision and deep learning techniques can ensure the safety of vehicles and humans on the roads. Integrating unmanned aerial vehicles (UAVs) in RDD and infrastructure evaluation (IE) has also emerged as a key enabler, contributing significantly to data acquisition and real-time monitoring of road damages, such as potholes, cracks, and surface anomalies, facilitating proactive maintenance and improved road conditions. These UAVs are low-powered and resource-constrained devices that work autonomously to perform pattern detection and decision making leveraging tiny machine learning (Tiny ML) algorithms. These Tiny ML algorithms are designed to run on edge devices, IoT devices, UAVs, etc. In this study, the RDD2022 data set collected using UAVs and dashboard cameras of vehicles was utilized to train pure and mixed models that exhibit class instance imbalance in certain classes which is addressed by implementing data augmentation as a regularization technique. State-of-the-art two-stage detectors: Faster R-CNN ResNet101 and one-stage detectors: SSD MobileNet V1 FPN, YOLOv5, and Efficientdet D1 are employed. The results indicate that the two-stage detector achieved an impressive mean average precision (mAP) of 88.49% overall and 96.62% for focused classes. Notably, the state-of-the-art Efficientdet D1 approach achieved a competitive mAP of 86.47% overall and 95.12% for focused classes, with significantly lower computational cost. These findings highlight the potential of advanced object detection techniques, particularly Efficientdet D1, to enhance the accuracy and efficiency of RDD systems, thereby improving passenger safety and overall performance. © 2014 IEEE.

关键词： Object detection

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EDSA-Ensemble: an Event Detection Sentiment Analysis Ensemble Architecture

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IEEE Transactions on Affective Computing 2024年第2期16卷 1-18页

作者： PETRESCU, Alexandru TRUICA, Ciprian-Octavian APOSTOL, Elena-Simona PASCHKE, Adrian Computer Science and Engineering Department Faculty of Automatic Control and Computers National University of Science and Technology Politehnica Bucharest Bucharest Romania Fraunhofer Institute for Open Communication Systems Berlin Germany

As global digitization continues to grow, technology becomes more affordable and easier to use, and social media platforms thrive, becoming the new means of spreading information and news. Communities are built around sharing and discussing current events. Within these communities, users are enabled to share their opinions about each event. Using Sentiment Analysis to understand the polarity of each message belonging to an event, as well as the entire event, can help to better understand the general and individual feelings of significant trends and the dynamics on online social networks. In this context, we propose a new ensemble architecture, EDSAEnsemble (Event Detection Sentiment Analysis Ensemble), that uses Event Detection and Sentiment Analysis to improve the detection of the polarity for current events from Social Media. For Event Detection, we use techniques based on information Diffusion taking into account both the time span and the topics. To detect the polarity of each event, we preprocess the text and employ several Machine and Deep Learning models to create an ensemble model. The preprocessing step includes several word representation models: raw frequency, TFIDF, Word2Vec, and Transformers. The proposed EDSA-Ensemble architecture improves the event sentiment classification over the individual Machine and Deep Learning models. Authors

关键词： Sentiment analysis

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High-Performance Intelligent system for Real-Time Medical Image Using Deep Learning and Augmented Reality 4th

High-Performance Intelligent System for Real-Time Medical Im...

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4th International Conference on IoT Based Control Networks and Intelligent systems, ICICNIS 2023

作者： Senthil, G.A. Prabha, R. Rajesh Kanna, R. Umadevi Venkat, G. Deepa, R. Department of Information Technology Agni College of Technology Chennai India Department of Electronics and Communication Engineering Sri Sai Ram Institute of Technology Chennai India Department of Computer Science and Engineering Agni College of Technology Chennai India Department of Computer Science and Engineering Vels Institute of Science and Technology and Advanced Studies Chennai India

ISBN: (纸本)9789819965854

Evolving new diseases demand the need for technology to identify the disease in an effective way. Medical imaging in the field of disease identification helps to identify the disease by scanning the human parts, thereby preventing the increased rate of deaths. Deep learning algorithms make it easier to identify and analyze disease efficiently through medical imaging. The high performance of these models is needed for the disease to be predicted with accurate results. The prediction rate of the disease can be increased by the efficient use of deep learning modules and algorithms. This research involves the use of deep learning models in identifying brain hemorrhage and retinopathy diseases through deep learning algorithms. The deep learning algorithms AlexNet and convolutional neural network (CNN) with the accuracy of 90% and 96%, respectively, are employed for the detection of brain hemorrhage, and ResNet-50 and CNN with accuracy of 70% and 92%, respectively, are used for the identification of retinopathy. The output of the model is displayed using augmented reality (AR), which makes it interactive for the user to analyze the results. The AR display is achieved using the unity engine along with the Vuforia package and using the barracuda package for importing the deep learning model into unity. Thus, by increasing the accuracy rate of the system, this research demonstrates the high performance of the intelligent system. © 2024, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Augmented reality

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Examining the Role of Guardian Communications Software Design for Network Security 15

Examining the Role of Guardian Communications Software Desig...

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

作者： Giri, Rakesh Kumar Chaudhari, Madhuri Harshal Verma, Ashish Dhabliya, Dharmesh Kumar, L.Vinoth Jaison, B. Sunrise University DepartmenT of Computer Science & Engineering Alwar301028 India Dr.D.Y.Patil Science and Computer Science college Department of Computer Science pune Akurdi India Chitkara University Centre of Research Impact and Outcome Punjab Rajpura140417 India Vishwakarma Institute of Information Technology Department of Information Technology Maharashtra Pune India Technology University Department of Information Chennai India R.M.K.Engineering College Department of Computer Science and Engineering Kavarapettai601206 India

ISBN: (纸本)9798350370249

Network protection is a crucial region of generation and PC technology, and numerous equipment and techniques help ensure comfy conversation and records switch. Mum or Dad Communications software program (GCS) is a product suite that gives customers an answer for securing their networks. GCS offers an interactive person interface to facilitate configuration, analysis, and optimization of a community's safety architecture. The suite carries three core components, supplying an excellent and specialized feature. These additives are the mum or dad Firewall, the guardian Host Intrusion Prevention system (HIPS), and the father or mother community protection appliance (NSA). Each component works independently and in concert with each other to provide comprehensive network security. The Guardian Firewall is an application-level firewall that provides a secure edge to the network by controlling all incoming and outgoing traffic and packet communications. It dynamically updates its rules database to recognize and block malicious traffic while allowing access to known secure applications and services. The Guardian HIPS is an internal network monitoring system that can detect and respond to unauthorized intrusions while providing the administrator with real-time alerts and intelligence about the nature of any malicious activity. Finally, the Guardian Network Security Appliance is a hardware-based appliance that can be configured with firewalls and. © 2024 IEEE.

关键词： Communications Dynamically Guardian Security Unauthorized

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