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9th IEEE International Conference on Smart Structures and Systems, ICSSS 2023

作者： Devi, D. Sathianesan, Godfrey Winster College of Engineering and Technology Srm Institute of Science and Technology Department of Computing Technologies Kattankulathur Chennai India

ISBN: (纸本)9798350384208

One of the most popular new technologies, cloud computing allows users to store and process massive amounts of data together with a wide variety of other computing resources. Scheduling tasks effectively is difficult, and inefficient management can lead to a drop in productivity. The task needs to be scheduled so that it runs quickly while using few resources as possible. As a result, this research suggests a novel approach to cloud-based work scheduling that incorporates increased security. To maximise throughput while minimising make span, a modified butterfly optimisation algorithm is developed for scheduling tasks. Secondly, user centric block level attribute-based encryption and decryption method is proposed for the security of data stored in the cloud. The suggested method utilises the block chain to carry out data transactions. Simulation results are carried out. The results demonstrated that the proposed method achieved superior results when compared to existing methods. © 2023 IEEE.

关键词： Cloud computing

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Enhanced Prediction Of Rheumatoid Arthritis Flares Through Ensemble Learning Methods 2

Enhanced Prediction Of Rheumatoid Arthritis Flares Through E...

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2nd IEEE International Conference on Advances in Information Technology, ICAIT 2024

作者： Priyadharshini, K. Vinitha, S. Sivaprakash, S. Kayalvili, S. Thilakavathy, P. Vasavi, M. Department of Computing Technologies School of Computing SRM Institute of Science and Technology Kattankulathur Campus Chennai India Department of Artificial Intelligence and Machine Learning Jerusalem College of Engineering Chennai India School of Computer Science and Engineering Vellore Institute of Technology Vellore India Department of Artificial Intelligence Kongu Engineering College Erode India Vels Institute of Science Technology and Advanced Studies Chennai India ET Department CVR College of Engineering Hyderabad India

ISBN: (纸本)9798350383867

RA is an inflammatory, autoimmune disease with an unpredictable course, during which patients experience exacerbations (increases in symptoms) and its associated complications, such as deterioration of the joint and decreased quality of life. Tipping the exact point when remission is reached or RA flares is most essential for devising optimal treatment and enhancing patient's well-being. In this study, we put forward the usage of various types of ensemble learning algorithms aimed at improved the predictive power of RA flares. We use diverse data sources, including clinical data, medical imagery, genetic profiles and patient-reported data, and ensemble methods like Random Forest, Gradient Boosting, AdaBoost and Stacking processors to help us identify the patterns automatically. Thus ensembles of models are shown to be leading in performance, reaching superior accuracy, accuracy precision, recall rate, F1-score and area under the receiver operating characteristic curve (AUC-ROC). Feature importance analysis highlights the significant impact of clinical features which include the levels of CRP, ESR, age of the patient, duration of the disease on the likelihood of RA flares among the individual variants. The sensitivity analysis shows how well the ensemble model behaves under the generation of different model parameters and input data. The presented study emphasizes the immense facilitative ability of the ensemble methods of learning as predicting RA flares and this can also provide great information about the disease process and personalized medical decision-making. The areas for future research could be improved ensembles models, identification of novel feature selection approaches and validation of model performance in a variety of clinical settings. This will give the researchers an opportunity to implement the models in practice and make clinics more effective. © 2024 IEEE.

关键词： Sensitivity analysis

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A Review Paper on Big Data Analytics: Tools Problems and Future Reseach Difficulties

A Review Paper on Big Data Analytics: Tools Problems and Fut...

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2023 International Conference on Sustainable Emerging Innovations in engineering and Technology, ICSEIET 2023

作者： Varshney, Sejal Shreya, Shilpa Kumar, Ritu Raj Kumar, Vikas Chauhan, Alok Singh School of Computing Science & Engineering Galgotias University Greater Noida India School of Computer Science Institute of Management Ghaziabad India

ISBN: (纸本)9798350329186

Each and every day, a tremendous wealth of terabytes of data is produced as a result of modern computerized technologies and data infrastructures, like distributed computing and the Internet of Things. When investigating these massive data sets, a lot of work needs to be done on a number of different levels in order to extract information that may be utilized as independent guidance. In this context, the examination of enormous swaths of data is a significant part of the creative process. This investigation's main goal is to look into the potential effects of significant informational hurdles, open exploration issues, and the many tools connected to these issues. As a consequence of this, the article offers a foundation upon which to investigate considerable data at a variety of stages. In addition to this, it opens up a new avenue for academics to investigate in order to progress the arrangement, taking into consideration the difficulties that have been shown and the concerns that remain unsolved. © 2023 IEEE.

关键词： Data Analytics

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Survey on Security Based Approach to Prevent Attacks in SDN Using IoT Framework 2

Survey on Security Based Approach to Prevent Attacks in SDN ...

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2nd International Conference on Edge computing and Applications, ICECAA 2023

作者： Prabhu, V. Balamurugan, P. School of Computing College of Engineering and Technology Srm Institute of Science and Technology Department of Computer Science and Engineering Kattankulathur Tamilnadu Chengalpattu603 203 India School of Computing College of Engineering and Technology Srm Institute of Science and Technology Department of Networking and Communications Kattankulathur Tamilnadu Chengalpattu603 203 India

ISBN: (纸本)9798350347579

Network evolution trendincludes Internet of Things (IoT) and Software-Defined Networking (SDN). By separating the data plane from the control plane, the software defined networking architectural framework is used and it will makes the network admins works more easily. SDN mainly focuses on network management and controls at the higher levels to monitoring and sharing the connection between the devices with the help of network connectivity in real time using the Internet of Things concepts. Almost in all the fields, IoT devices used so have to improve the security of IoT devices. The SDN has the centralized control logic, if the number of network traffic increases then centralized controller may not be handle all the network traffic requests at the same time, because the SDN controller is a single point of failure, its failure can bring the entire network down. The Software Defined Network (SDN) is easily exposed to various attacks mostly to DDoS attacks. Majority of the existing research is concentrated only on sensing of HR-DDoS attacks occurring over the control layer and not focusing on LR-DDoS attack occurring over the data layer because the accuracy of attacks on the LR-DDoS attacks are very low. This study mainly focusing on how to design the multi controller SDN architecture to improve the scalability, how to increase the detection accuracy of low-rate DDoS attacks on the SDN data layer and how to detect the attacks using machine learning algorithms. © 2023 IEEE.

关键词： Internet of things

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Enhanced Windows Fuzzy Firewall for DOS Attack Prevention 1

Enhanced Windows Fuzzy Firewall for DOS Attack Prevention

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1st IEEE International Conference on Emerging Research in Computational science, ICERCS 2023

作者： Himanshu Sharma, Manubhav Sujatha, G. Srm Institute of Science and Technology Faculty of Engineering Department of Networking and Communications School of Computing Chennai India

ISBN: (纸本)9798350359756

Winguardian, an enhanced version of FR-Winfirewall, enhances the security characteristics of the Windows Firewall. The native firewall is necessary, although it is not very efficient against DoS attacks. The improved version of Winguardian addresses this weakness by incorporating cutting-edge security features to counter a variety of DoS attacks, including those based on TCP, UDP, and ICMPv4 and ICMPv6 protocols. It protects Windows systems better than a lot of other firewalls. In addition to handling IPv6 traffic, the Winguardian also monitors HTTP and FTP packets to further improve its security features. This makes it an all-inclusive security tool for Windows users, ensuring that different kinds of network traffic are analysed and shielded from potential *** put it briefly, the Winguardian strengthens Windows-based systems' defences against online threats by providing a strong and intelligent security solution. © 2023 IEEE.

关键词： Denial-of-service attack

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An Efficient Proxy Blind Signcryption Scheme for IoT

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Computers, Materials & Continua 2022年第3期70卷 4293-4306页

作者： Aamer Khan Insaf Ullah Fahad Algarni Muhammad Naeem M.Irfan Uddin Muhammad Asghar Khan Department of Information Technology Abbottabad University of Science and TechnologyAbbotabadPakistan Hamdard Institute of Engineering and Technology Islamabad44000Pakistan College of Computing and Information Technology University of BishaBishaSaudi Arabia Institute of Computing Kohat University of Science and TechnologyKohatPakistan

Recent years have witnessed growing scientific research interest in the Internet of Things(IoT)technologies,which supports the development of a variety of applications such as health care,Industry 4.0,agriculture,ecological data management,and other various *** utilizes the Internet as a prime medium of communication for both single documents as well as multi-digital ***,due to the wide-open nature of the Internet,it is important to ensure the anonymity,untraceably,confidentiality,and unforgeability of communication with efficient computational complexity and low *** designed a light weight and secure proxy blind signcryption for multi-digital messages based on a hyperelliptic curve(HEC).Our results outperform the available schemes in terms of computational cost and communication *** designed scheme also has the desired authentication,unforgeability of warrants and/or plaintext,confidentiality,integrity,and blindness,***,our scheme is more suitable for devices with low computation power such as mobiles and tablets.

关键词： Proxy signcryption multi-digital-documents proxy blind signcryption hyperelliptic curve IoT

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A Comparative Analysis of Transformers for Multilingual Neural Machine Translation 7

A Comparative Analysis of Transformers for Multilingual Neur...

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7th IEEE Conference on Information and Communication Technology, CICT 2023

作者： Prasanna Kumar, R. Sudharson, S. Reddy, Avuthu Avinash Siva Jyothi Natha Reddy, B. Anvitha, Vemireddy Amrita School of Computing Chennai India Vellore Institute of Technology Computer Science and Engineering Chennai India

ISBN: (纸本)9798350305173

Multilingual neural machine translation (NMT) has emerged as a promising solution to break down language barriers and promote cross-lingual communication. Transformer-based NMT models have gained significant attention due to their ability to learn contextual information and their effectiveness in handling long-range dependencies. The transformer model, with its self-attention and cross-attention mechanisms, fundamentally alters machine translation when compared to other neural machine translation models and traditional machine translation models. Token alignments between source and target sentences are successfully modelled by these mechanisms. This paper deals with the performance of a transformer-based multilingual NMT model that uses a shared encoder and decoder. We conducted experiments on the publicly available Multi30k dataset for translation jobs involving German, French, and Czech into English. In comparison of models, the Transformer model has performed better against the Convolutional SeqtoSeq and Attention-Based Seq2Seq models. We have evaluated our model on the metric Bilingual Evaluation Understudy (BLEU), where the transformer achieved 36.67, 48.47, and 33.66 for DE, FR, and CZ to EN translations. © 2023 IEEE.

关键词： Neural machine translation

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Graph Neural Networks for Optimizing Reliability in Vehicle-to-Infrastructure Communication in Autonomous Systems 9

Graph Neural Networks for Optimizing Reliability in Vehicle-...

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9th International Conference on Communication and Electronics Systems, ICCES 2024

作者： Neelamegam, G. Revathy, J. Kannukkiniyal, M. Devendran, M. Akshya, J. Choudhry, Mani Deepak Vsb College of Engineering and Technology Department of Computer Science and Engineering Coimbatore India Christ the King Engineering College Department of Artificial Intelligence and Data Science Coimbatore India Kongu Engineering College Department of Computer Science and Engineering Erode India Hindustan institute of technology Department of Computer Science and Engineering Coimbatore India Srm Institute of Science and Technology Department of Computational Intelligence Chennai India Srm Institute of Science and Technology Department of Computing Technologies Chennai India

ISBN: (纸本)9798350377972

High reliance on autonomous systems necessitates efficient and reliable data exchange through Vehicle-to-Infrastructure (V2I) communication to have appropriate and stable network performance in dynamic vehicular environments. With heuristic approaches, Dijkstra's algorithm, and Deep Q-Networks (DQN), several methods are proposed for optimizing latency reduction, packet delivery rate improvement, and power efficiency in the direction of V2I communications. However, these approaches suffer from important challenges: low adaptability of the network to real-time dynamics, suboptimal resource usage, and difficulties in scalability towards complex large-scale networks. In this scenario, we propose a framework that incorporates a GNN inside autonomous systems for V2I communication to optimize performance. The GNN will process real-time graph features, including signal strength, packet loss, and mobility speed, as it dynamically changes in adaptation to the evolution of network behaviour and other functions. This work shows the superiority of the proposed GNN model for the efficiency of experimentally conducted simulations compared to the current models;it achieved latency reduced by up to 28%, 5-10% PDR, and 20% energy efficiency across the various scenarios with urban, rural, highway, and suburban networks. The results validate robustness and scalability for practical implementations by the proposed approach in real-world autonomous systems. Further development is possible with this framework: for example, the use of multi-agent reinforcement learning techniques within cooperative decision-making and the enhancement through blockchain-based security mechanisms to ensure the integrity of the data. © 2024 IEEE.

关键词： Graph neural networks

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Ambiguity Resolution in Direction of Arrival Estimation with Linear Antenna Arrays Using Differential Geometry

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Computers, Materials & Continua 2022年第1期70卷 581-599页

作者： Alamgir Safi Muhammad Asghar Khan Fahad Algarni Muhammad Adnan Aziz M.Irfan Uddin Insaf Ullah Tanweer Ahmad Cheema Department of Electronic Engineering ISRA UniversityIslamabad44000Pakistan Hamdard Institute of Engineering&Technology Islamabad44000Pakistan College of Computing and Information Technology University of BishaBishaSaudi Arabia Institute of Computing Kohat University of Science and TechnologyKohatPakistan

Linear antenna arrays(LAs)can be used to accurately predict the direction of arrival(DOAs)of various targets of interest in a given ***,under certain conditions,LA suffers from the problem of ambiguities among the angles of targets,which may result inmisinterpretation of such *** order to cope up with such ambiguities,various techniques have been ***,none of them fully resolved such a problem because of rank deficiency and high computational *** aimed to resolve such a problem by proposing an algorithm using differential *** proposed algorithm uses a specially designed doublet antenna array,which is made up of two individual linear *** angle observation models,ambiguous observation model(AOM)and estimated observation model(EOM),are derived for each individual *** ambiguous set of angles is contained in the AOM,which is obtained from the corresponding array elements using differential *** EOM for each array,on the other hand,contains estimated angles of all sources impinging signals on each array,as calculated by a direction-finding algorithm such as the genetic *** algorithm then contrasts the EOM of each array with its AOM,selecting the output of that array whose EOM has the minimum correlation with its corresponding *** comparison to existing techniques,the proposed algorithm improves estimation accuracy and has greater precision in antenna aperture selection,resulting in improved resolution capabilities and the potential to be used more widely in practical *** simulation results using MATLAB authenticates the effectiveness of the proposed algorithm.

关键词： Antenna array direction of arrival ambiguity resolution doublet antenna array ambiguous observation model estimated observation model

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Design of Energy Efficient BLDC Motor Pump for Agriculture Applications

Design of Energy Efficient BLDC Motor Pump for Agriculture A...

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2023 International Conference on System, Computation, Automation and Networking, ICSCAN 2023

作者： Richard Pravin, A. Franklin, J. Pongiannan R, K. Srm Institute of Science and Technology Department of Electrical and Electronics Engineering Kattankulathur India Srm Institute of Science and Technology Department of Computing Technologies Kattankulathur India

ISBN: (纸本)9798350315127

In the realm of residential, commercial, and agricultural applications, conventional pumps have long relied on induction motors. Nevertheless, a notable shift in the sectors like pump systems and electric vehicles where brushless DC (BLDC) motors are increasingly favored over the induction motor. The Bureau of Indian Standards (BIS) standards primarily revolve around key parameters are discharge (Q), head (H), and power input (Pi), intricately linked to the motor operating speed. In the pursuit of improving overall performance, especially in terms of efficiency, the focus is on enhancing both motor and pump efficiencies. Single-phase induction motors encounter limitations in their efficiency and speed capabilities. In contrast, BLDC motors offer a more versatile and efficient solution, the ability to modulate speed and optimized efficiency make them a superior choice for water pumping in agriculture applications. A BLDC motor with a 1 hp rating, designed to function within a voltage range of 72V and rotate at a speed of 3000 revolutions per minute (rpm), has been proposed as an efficient and effective option for these specific pumping needs. The design and analysis of this BLDC motor are carried out using finite element analysis software MagN et. Through finite element analysis using MagNet software, optimized BLDC motor designs with varying magnet thickness are developed and evaluated, resulting in significant improvements in water discharge capacity, pump head, and overall efficiency when compared to single-phase induction motor-driven pumps. Specifically, there is a 15% increase in both water discharge capacity and pump head. Furthermore, the overall conversion efficiency experiences a significant enhancement, ranging from 7% within the nominal operating head range. © 2023 IEEE.

关键词： Brushless DC motors

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