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IEEE International Workshop on computer-Aided Modeling, Analysis, and Design of Communication Links and Networks, CAMAD

作者： Grace Khayat Constandinos X Mavromoustakis Jordi Mongay Batalla Andreas Pitsillides Department of Computer Science Mobile Systems Laboratory (MoSys Lab) University of Nicosia Nicosia Cyprus Warsaw University of Technology Warsaw Poland Department of Computer Science University of Cyprus Cyprus Department of Electrical & Electronic Engineering Science University of Johannesburg (Visiting Professor)

ISBN: (数字)9798350377644

ISBN: (纸本)9798350377651

Swarm of UAVs (S-UAVs) refers to an assembly of unmanned aerial vehicles (UAVs) working together to accomplish prearranged missions. In emergency scenarios, such as a fire, any UAV is susceptible to damage. Among the routing algorithms that S-UAVs utilize the most frequently is clustering, where UAVs are divided into clusters. Each cluster consists of a cluster head (CH) and cluster members (CM). The selection of the CH is a topic of continuous research because of its crucial significance in inter-cluster communication. We propose a clustered weighted method with dynamic weight modification and redundancy to ensure end-to-end communication despite non-functional CH. Interspace, speed, and performance indicators are combined into a weighted metric that is used to select the CH, redundant CHs, and CMs. The suggested technique optimizes UAV role selection by dynamically and autonomously adjusting the weights. Based on the results of the executed simulation, this is a promising strategy that minimizes data loss in an emergency situation and minimizes delay.

关键词： Measurement Conferences Computational modeling Redundancy Clustering algorithms Autonomous aerial vehicles Routing Routing protocols Delays Vehicle dynamics

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Prognosticating Liver Debility Using Classification Approaches of Machine Learning

Prognosticating Liver Debility Using Classification Approach...

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International Conference on Recent Trends in Machine Learning, IOT, Smart Cities and Applications, ICMISC 2020

作者： Akshara, Revelly Reddy, Sandhi Kranthi Assistant Professor Department of Computer Science and Engineering Vignan Institute of Technology and Science Yadadri Bhuvanagiri DistrictTelangana India

ISBN: (纸本)9789811572333

In the field of Machine Learning in Healthcare, one of the most compelling factors is the prognosis of illness by examining the characteristics which have the most impact on its recognition. One of the deadliest diseases is a liver disease that accounts for about two million deaths annually worldwide. Prognosticating it in an early stage is helpful to get diagnosed at the right time as this may lead to a complete recovery in some patients. We can effectively prognosticate liver disease using supervised learning techniques specifically classification methods of machine learning. In this paper, different classification methods are applied to the Indian Liver Patient Records Dataset downloaded from *** to prognosticate liver disease. © 2021, Springer Nature Singapore Pte Ltd.

关键词： Supervised learning

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Advancing Beyond Contextual Embeddings: Innovations in Word and Document Representations for Natural Language Processing 3rd

Advancing Beyond Contextual Embeddings: Innovations in Word ...

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3rd International Conference on Mechanical and Energy Technologies, ICMET 2023

作者： Nagender, Y. Ravichand, M. Kocherlakota, Nirupama Mary, S. Shyni Carmel Bharathi, S. Kavitha Kalaivaani, P.C.D. School of Computer Science and Artificial Intelligence SR University Telangana Warangal India Vijayawada India Department of Linguistics MIT World Peace University Maharashtra Pune India Assistant Professor in Business Analytics Loyola Institute of Business Administration Loyola College Campus Chennai600 034 India Department of Computer Technology Kongu Engineering College Perundurai India Department of CSE Kongu Engineering College Perundurai638060 India

ISBN: (纸本)9789819727155

Recent years have seen tremendous progress in Natural Language Processing (NLP), particularly in word and document illustration. Conventional methods that relied on contextual embeddings have given way to creative alternatives. In NLP, pre-trained language models have shown remarkable effectiveness, resulting in a fundamental shift away from supervised learning and towards pre-training accompanied by fine-tuning. Enhancing pre-trained models has attracted a lot of research attention in the NLP community. The taxonomy of pre-trained models is introduced, along with a thorough assessment of current advancements and representative work in the field of natural language processing. We initially provide a quick overview of pre-trained models, then go on to distinctive architectures and techniques. Next, we present and examine the implications and difficulties associated with pre-trained models and their subsequent uses. We wrap up quickly and discuss potential future research options in this area. These developments provide more accurate and effective ways to organise and extract data from large textual collections. In conclusion, this study addresses the intrinsic drawbacks of contextual embeddings and emphasises the critical role that word and document illustrations play in advancing NLP. These cutting-edge methods offer a viable avenue to improve natural language comprehension and utilisation as NLP continues to develop, with extensive applications in domains including information retrieval, machine translation, and sentiment analysis. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.

关键词： Embeddings

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Identification of Congenital Heart Defects in Ultrasound Images using U-Net Segmentation 1

Identification of Congenital Heart Defects in Ultrasound Ima...

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1st International Conference on Artificial Intelligence for Innovations in Healthcare Industries, ICAIIHI 2023

作者： Pandey, Saroj Kumar Diwan, Ritesh Rose, Anthony Singh, Kamred Udham Singh, Teekam Somasekar, J. Gla University Department of Computer Engineering & Apllications UP Mathura India Department of Ele. & Tele. Raipur Institute of Technology Raipur India Pune India School of Computing Graphic Era Hill University Dehradun India Graphic Era Deemed to Be University Department of Computer Science and Engineering Dehradun India Professor of Cse Department Bangalore India

ISBN: (纸本)9798350330915

In this study, the use of a U-Net segmentation model is measured for the accurate detection of congenital heart abnormalities in newborn ultrasound pictures. The technique includes U-Net model training, sophisticated picture preprocessing, as well as exhaustive dataset gathering. As a result of the model's considerable accuracy, sensitivity, and specificity, it has the potential to become a crucial diagnostic tool. A thorough analysis found both advantages, such as reliable performance, and disadvantages, which include the requirement for a larger and more varied dataset. Enlarging the dataset, addressing equipment variability, real-time clinical application, multidisciplinary cooperation, and ethical issues, including model improvement are among the key recommendations. In order to promote newborn healthcare, future work will require ongoing model development, real-time clinical integration, and ethical adherence. The work advances the development of accurate diagnostics in newborn care. © 2023 IEEE.

关键词： Congenital heart defects diagnostic accuracy medical image analysis neonatal ultrasound pediatric cardiology U-Net segmentation

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A Novel Approach of Topology Control in Underwater Sensor Networks 2

A Novel Approach of Topology Control in Underwater Sensor Ne...

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2nd IEEE Mysore Sub Section International Conference, MysuruCon 2022

作者： Sutagundar, A.V. Halakarnimath, B.S. Bhajantri, Lokesh B. Nalini, N. Basaveshwar Engineering College Electronics & Communication Engineering Karnataka Bagalkot India S. G. Balekundri Institute of Technology Computer Science & Engineering Karnataka Belagavi India Basaveshwar Engineering College Department of Information Science and Engineering Karnataka Bagalkot India Nitte Meenakshi Institute of Technology Professor & Dean Student's Welfare Department of Computer Science & Engineering Bengaluru India

ISBN: (数字)9781665497909

ISBN: (纸本)9781665497909

The wide spectrum of marine applications has drawn the research community to discuss the several issues of UASNs. Acoustic communication is the most relevant channel for communicating information among sensor nodes that utilize more energy to avoid network failure and render continuous connectivity. The Energy-efficient Topology Control (ETC) is proposed to discuss this issue for UASNs to overcome the coverage and connectivity by improving their lifetime. The proposed approach is divided into the topology construction and topology maintenance phase. In the construction phase, initially, each node recognizes the neighbor nodes and records the range and orientation in an internal database. After that, each node drops some nodes by applying specific conditions and forms the candidate neighbor nodes. Finally, the minimum number of sensor nodes is added to the Topology Member Set (TMS) based on the nodes' orientation, range, energy levels, and topology of the network are created. The topology's maintenance is initiated by the sink node periodically, or any sensor node can send a request message to the sink node at particular conditions. The proposed scheme's performance shows the necessity for minimal sensor nodes for seamless connection and improves coverage area. © 2022 IEEE.

关键词： Sensor nodes

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Next-Generation Diagnostic Tools: The Role of Hybrid CNN-Transformer Models in Liver Cancer Detection

Next-Generation Diagnostic Tools: The Role of Hybrid CNN-Tra...

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International Conference on Computing and Networking technology (ICCNT)

作者： Satvik Vats Choudhary Ravi Singh Shiva Mehta Computer Science and Engineering Graphic Era Hill University Adjunct professor Graphic Era Deemed to be University Dehradun India Computer Science And Engineering Department Invertis University Bareilly Chitkara University Institute of Engineering and Technology Chitkara University Punjab India

ISBN: (数字)9798350370249

ISBN: (纸本)9798350370270

The content of this paper describes a novel CNN-Transformer hybrid model that detects, classifies, and differentiates focal liver lesions into various categories using contrast-enhanced ultrasound (CEUS). A model, a harmonious convolutional neural network (CNN) integration and a decoder enable us to achieve a tremendous diagnostic performance (AUC of 0.8237 and an accuracy of 0.78). It outperforms the conventional baseline models. Merging local and global patio-temporal data aids the model designed for FLL categorizing. It allows the model to detect early at diagnosis and improves diagnostic confidence. The proposed methodology may do away with the previous health care practices that were heavy and complicated yet bring back the desired patient outcomes. Future studies should be oriented towards understanding the technology better, specifically its usability, and conducting clinical validation trials. Another element should be studied to determine its suitability for different medical imaging techniques. Efficient CNN-Transformer architecture is a significant milestone in developing an efficient liver cancer detection method that might become a robust clinical practice tool allowing emerging precision medicine.

关键词： Frequency locked loops Liver cancer Ultrasonic imaging Accuracy Computational modeling Liver Lesions Convolutional neural networks Usability Biomedical imaging

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A Hybrid Harmony Search Algorithm based on Firefly Algorithm and Boltzmann Machine

IAENG International Journal of Computer Science

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IAENG International Journal of computer science 2022年第1期49卷 241-251页

作者： Yang, J. Zhang, Xiaoxia Fu, S. Hu, Y.Y. Master Student of School of Computer Science and Software Engineering University of Science and Technology LiaoNing Anshan114051 China Professor of School of computer Science and Software Engineering University of Science and Technology LiaoNing Anshan11041 China

Harmony Search Algorithm (HS) is a new meta-heuristic algorithm based on music creation process. The algorithm has been widely used in many fields because of its simple and flexible structure and fewer controlled parameters. However, HS is easy to be affected by the initial harmony memory and falls into local optimization. In addition, there are also problems, such as low searching accuracy and slow convergence speed of the optimal solution. Therefore, this paper proposes a hybrid harmony search algorithm based on firefly algorithm and boltzmann machine (HSFA-BM). First, in order to avoid the possibility of harmony search algorithm falling into local optimum, boltzmann machine (BM) mechanism is used to update the harmony memory in this paper. Second, in order to enhance the ability of the algorithm to exploit optimal solutions, this paper uses the movement mode of fireflies to generate new solutions. The improved algorithm enhances the ability of global optimization and search precision, and speeds up the convergence speed. In this paper, six classical test functions are used to test the effectiveness of the algorithm, and a very obvious optimization result is obtained. © 2022. All Rights Reserved.

关键词： Flexible structures

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Redundant Weighted Clustered Scheme with Dynamic Weights Adjustment for Damaged S-UAV

Redundant Weighted Clustered Scheme with Dynamic Weights Adj...

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IEEE International Conference on Communications (ICC)

作者： Grace Khayat Constandinos X Mavromoustakis Andreas Pitsillides Jordi Mongay Batalla Evangelos K. Markakis Department of Computer Science Mobile Systems Laboratory (MoSys Lab) University of Nicosia Nicosia Cyprus Department of Computer Science University of Cyprus Cyprus Department of Electrical & Electronic Engineering Science University of Johannesburg (Visiting Professor) Warsaw University of Technology Warsaw Poland Department of Electrical and Computer Engineering Hellenic Mediteranean University Estavromenos Heraklion Greece

ISBN: (数字)9781728190549

ISBN: (纸本)9781728190556

Swarm of UAVs (S-UAVs) is the term used to describe an unplanned gathering of un-manned aerial vehicles (UAVs) that collaborate to complete predefined missions. Any UAV has a risk of being damaged in crisis situations like fire. Clustering is one of the most often used routing algorithms in S-UAVs. The clustering scheme divides the UAVs into clusters, with a cluster head (CH) and cluster members (CM) in each cluster. The CH plays a critical role within inter-cluster communication, and because of this, its selection is an ongoing area of study. A clustered weighted scheme with redundancy and dynamic weight adjustment is proposed in this paper. The selection of the principal CH, redundant CHs, and CMs is based on a weighted formula composed of distance, speed, and rewarding index. Whenever the primary CH is damaged, the redundant CH takes its place immediately. After the first clustering process, the proposed scheme dynamically and autonomously adjusts the weights to optimize the UAV role selection. According to the outcomes of the carried-out simulation, this is a promising scheme that reduces data loss in a crisis-case scenario and optimizes the time delay through the dynamic adjustments of the weights.

关键词： Delay effects Redundancy Clustering algorithms Routing Autonomous aerial vehicles Indexes Vehicle dynamics

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An Automated Security Approach of Image and Video Steganography 2nd

An Automated Security Approach of Image and Video Steganogra...

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2nd International Conference on Emerging Trends and Advances in Electrical Engineering and Renewable Energy, ETAEERE 2020

作者： Lavanya, P. Anusha, P. Kaveri, V. Vijeya Department of Computer Science and Engineering Sathyabama Institute of Science and Technology Chennai India Professor CSE Sri Krishna College of Engineering and Technology Coimbatore India

ISBN: (纸本)9789811575037

The steganography utilizes the craft of covered up;its principle point is to pass unnoticed information in information. There are numerous kinds of information utilized in steganography, for example, message, image, and video. Encryption is the job of securing data by shuffling it into a provision that cannot be used effectively and is called as the figure content. This mysterious figure or message content should be used by people using an anonymous key and able to decode the note into basic form. To match mystery information or single point data to the targeted alternative to various applications we use steganography. In cryptography, normally the matter in the mysterious note is mixed whereas in steganography the mysterious note is installed from diffuse standard. The proposed framework encodes a book or image within a cover image. Videos and images are exceptionally regular decisions to hide information. It is significant for the powerful and effective installation procedure to choose the video outlines which contains proper picture view that can be used to store mystery information. The audiovisual-built steganography is used due to memory prerequisites along with huge scope. LSB inclusion system, for concealing data we change LSB of video document with the data bits. This paper will concentrate on concealing data in an explicit video envelope and in an explicit advantage situation by replacing LSB. A verified copy is anticipated and created through joining less important bit and advanced encryption standard. Here we use AES for encryption plus LSB method for steganography. © 2021, Springer Nature Singapore Pte Ltd.

关键词： Steganography

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Blockchain effect on E-commerce: A framework for key research areas

Blockchain effect on E-commerce: A framework for key researc...

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2023 International Conference on Artificial Intelligence and Smart Communication, AISC 2023

作者： Nethravathi, K. Panduro-Ramirez, Jeidy Gehlot, Anita Barve, Amit Sanjay, C.P. Ponnusamy, R. Jain University Department of Bms Bangalore India Universidad Tecnológica Del Perú Peru Uttaranchal University Uttaranchal Institute of Technology India Parul University Department of Associate Professor & Hod India Department of It& Business Analytics India Chennai Institute of Technology Department of Computer Science & Engineering India

ISBN: (纸本)9798350322309

Several business applications and procedures are expected to be significantly disrupted by Blockchain-based technologies, which has significant consequences for ecommerce. In light of the potential blockchain based technology are popularly known as "trust building systems"that can be used in multiple business models and standard guidelines which evolved placed above a white period to achieve believe, serviceability, and enforcement in various domains such as cunsumers related business, business related connections have to be questioned and possibly adjusted. By enabling trustless trade interactions that work without specialized intermediaries or even central authority in the case of permission lessblock chains, Blockchain has the power to change how electronic commerce operates. Furthermore, giving universal access to immutable data across the whole supply chain may significantly alter the information and value exchange between businesses and consumers. The methodology presented in this paper are intended to motivate further study of the potential effects of Blockchain on e-commerce. technology, law, organizational and quality challenges, as well as consumer difficulties, are the four key categories. This paper demonstrates how Blockchain may affect many Electronic commercial components in these relevant fields. © 2023 IEEE.

关键词： Data mining

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