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Recent Advances in Science and engineering technology (ICRASET), International Conference on

作者： Gowrishankar J Ritesh Kumar Dharmesh Kumar Srivastava Department of Computer Science Engineering Faculty of Engineering and Technology JAIN (Deemed-to-be University) Bangalore Karnataka India Maharishi School of Engineering & Technology Maharishi University of Information Technology Uttar Pradesh India Department of Electronics and Communication Engineering Presidency University Bangalore Karnataka India

The integration of modern machine intelligence presents a transformative paradigm in the study of organisms' behaviors through visual data analysis. Leveraging deep learning algorithms like Convolutional Neural Networks (CNNs) and Recurrent Neural Networks (RNNs), this approach automates the extraction of intricate patterns from images and videos, enabling comprehensive insights into diverse organisms. Object detection algorithms further facilitate precise tracking. By surpassing traditional methods, it enhances accuracy and scalability. Ethical considerations guide responsible research. This fusion of technology and ecology fosters a deeper understanding of natural ecosystems, paving the way for sustainable coexistence with the environment and the preservation of biodiversity.

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Understanding the Journey to 6G Development

Understanding the Journey to 6G Development

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International Conference on Power Energy, Environment and Intelligent Control (PEEIC)

作者： Trapty Agrawal Ajit Kumar Gowrishankar J Maharishi School of Engineering & Technology Maharishi University of Information Technology Uttar Pradesh India Department of Electronics and Communication Engineering Presidency University Bangalore Karnataka India Department of Computer Science Engineering Faculty of Engineering and Technology JAIN (Deemed-to-be University) Bangalore Karnataka India

The fifth-generation (5G) mobile communication technology is now being widely deployed in a number of nations, along with a significant rise in the number of 5G customers. However, it is becoming more and more clear that it is time for both academics and business to shift their emphasis towards the next generation as the mobile telecommunications market continues to change. At this point, it is crucial to provide a thorough review of the state of the art and look forward to the future of communications. This article tries to achieve this goal by providing a thorough analysis designed to outline the sixth generation (6G) system's characteristics. The motivations, use cases, use scenarios, needs, key performance indicators (KPIs), architecture, and enabling technologies that will characterize 6G are all covered in this investigation.

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Cloud Deployment Unveiled: A Security Model Focused on Industry

Cloud Deployment Unveiled: A Security Model Focused on Indus...

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Advances in Computation, Communication and Information technology (ICAICCIT), International Conference on

作者： Rakesh Kumar Yadav Natya S Mahesh T R Maharishi School of Engineering & Technology Maharishi University of Information Technology Uttar Pradesh India Department of Electronics and Communication Engineering Presidency University Bangalore Karnataka India Department of Computer Science Engineering Faculty of Engineering and Technology JAIN (Deemed-to-be University) Bangalore Karnataka India

The Cloud Compute Adoption Architecture (CCAF), a unique architecture designed to improve safety of the business cloud installations, is introduced in this research article. Using router, authentication and authorization, and encryption methods embedded in Industrial File Sync/Share systems, CCAF aims to provide a multi-layered privacy strategy. Our paper describes the creation of this security A system, examines relevant literature, and explains the reasoning behind CCAF. Through testing and thorough analysis of the key technologies, the study assesses the effectiveness of the CCAF security layered approach. The intricate security system in place at CCAF proved to be an outstanding tool during penetration testing, detecting and eliminating 99.95% of worms including trojans, and even deactivating over 85% of them after 100 hours of continuous attack. Of particular note was the operating system's lightning-fast reaction time of less than 0.012 seconds per trojan and virus, which allowed for the early detection and mitigation of threats. Moreover, each try at SQL injection was successfully thwarted by the CCAF's extensive security defenses, guaranteeing strong security of data. The article highlights the usefulness of CCAF by exploring how its multi-layered security is seamlessly integrated into current regulations, services, and corporate processes. The research highlights how important CCAF's complex security is for Big Data applications running in the cloud, especially when it comes to scalability, speed, and veracity. The study's conclusions highlight CCAF's legitimacy and significant contributions to the field, demonstrating its applicability and effectiveness in protecting the cloud.

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Visualizing Wellness: The Impact of Deep Learning on Healthcare Image Analysis

Visualizing Wellness: The Impact of Deep Learning on Healthc...

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Advances in Computation, Communication and Information technology (ICAICCIT), International Conference on

作者： Deepak Kumar Sinha Preeti Naval Samreen Fiza Department of Computer Science Engineering Faculty of Engineering and Technology JAIN (Deemed-to-be University) Bangalore Karnataka India Maharishi School of Engineering & Technology Maharishi University of Information Technology Uttar Pradesh India Department of Electronics and Communication Engineering Presidency University Bangalore Karnataka India

Deep convolution networks have quickly established itself as the main method for deciphering medical pictures due to their widespread use. This extensive study examined almost 300 recent papers, mostly from the preceding year, that summarized the basic artificial intelligence ideas related to medical picture analysis. Applications of deep learning were explored in detail in a number of disciplines, including object recognition, picture grouping, classification, and registering. This book presents a succinct summary of studies conducted in the fields of neurological disorders, retinal cells, asthma, malignant scans, breasts, cardiovascular and cardiac pelvic, and nerve imaging. Study conducted concludes our assessment with a review of the state-of-the-art at this time, a thorough investigation of outstanding problems, and suggestions for further research. All areas, including computerized pathology, musculoskeletal, pulmonary, the heart, breasts, muscles and tendons, retinal, and neurology imaging, are summarized in a summary of current studies. This thorough review ends with an assessment of the field's current state, a critical analysis of ongoing issues, and specific suggestions for further research and development.

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Cyber Security Posterior Distribution

Cyber Security Posterior Distribution

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International Conference on Communication Systems and Network Technologies (CSNT)

作者： Leo John Baptist Andrews Sampath Kumar Venkatachary D Sarathkumar Annamalai Alagappan M. Fathima Raymon Antony Raj R Rajeshkanna Department of Information Technology Faculty of Engineering and Technology Botho University Gaborone Botswana Department of Electrical and Electronics Engineering Kongu Engineering College Erode district Tamilnadu India Grant Thornton Gaborone Botswana Department of Network and Infrastructure Management Faculty of Engineering and Technology Botho University Gaborone Botswana Department of EEE Thamirabarani Engineering College Tirunelveli Tamil Nadu India Department of Computer Science and Business Systems Sri Krishna College of engineering and Technology Coimbatore Tamilnadu India

ISBN: (数字)9798350305463

ISBN: (纸本)9798350305470

Currently, the vast majority of international interactions and activities related to trade, government, culture, social interaction, and economics take place online. These interactions involve people, non-governmental organizations, governments, and government agencies at all levels. Recently, a sizeable number of commercial firms and government organizations all over the world have been presented with the challenge offered by cyberattacks as well as the danger represented by wireless communication technologies. A very little amount of time has passed since this had place. We were able to develop a model for the risk of cyber security by making use of Bayesian Networks. This model has the capability of locating the point of cyber security that is weak and merging two different cyber analysis models. Among these is the activityquality model, which shows how individuals and/or groups adhere to the legal requirements for cyber security. Evidence describing the critical component of cyber security for a research reactor's RPS may be produced via the cyber security risk model. An further model that shows the probability of a cyberattack against RPS architecture is the cyber security risk model.

关键词： Wireless communication Analytical models Government Sociology Cyberspace Safety Security

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Toward Optimal Cost-Energy Management Green Framework for Sustainable Future Wireless Networks

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computers, Materials & Continua 2021年第7期68卷 1321-1339页

作者： Mohammed H.Alsharif Abu Jahid Mahmoud A.Albreem Peerapong Uthansakul Jamel Nebhen Khalid Yahya Department of Electrical Engineering College of Electronics and Information EngineeringSejong UniversitySeoul05006Korea Department of Electrical and Computer Engineering University of OttawaOttawaK1N 6N5ONCanada Department of Electronics and Communications Engineering A’Sharqiyah UniversityIbra400Oman School of Telecommunication Engineering Suranaree University of TechnologyNakhon RatchasimaThailand College of Computer Engineering and Sciences Prince Sattam bin Abdulaziz UniversityAlkharj11942Saudi Arabia Department of Mechatronics Faculty of Engineering and ArchitectureIstanbul Gelisim UniversityIstanbul34310Turkey

The design of green cellular networking according to the trafc arrivals has the capability to reduce the overall energy consumption to a cluster in a cost-effective *** cell zooming approach has appealed much attention that adaptively ofoads the BS load demands adjusting the transmit power based on the trafc intensity and green energy ***,the researchers are focused on implementing renewable energy resources,which are considered the most attractive practices in designing energy-efcient wireless networks over the long term in a cost-efcient way in the existing *** utilization of available solar can be adapted to acquire cost-effective and reliable power supply to the BSs,especially that sunlight is free,available everywhere,and a good alternative energy option for the remote ***,planning a photovoltaic scheme necessitates viability assessment to avoid poor power supply,particularly for ***,cellular operators need to consider both technical and economic factors before the implementation of solar-powered *** paper proposed the usercentric cell zooming policy of solar-powered cellular base stations taking into account the optimal technical criteria obtained by the HOMER software *** results have shown that the proposed system can provide operational expenditure(OPEX)savings of up to 47%.In addition,the efcient allocation of resource blocks(RBs)under the cell zooming technique attain remarkable energy-saving performance yielding up to 27%.

关键词： Wireless networks beyond 5G green communications sustainability OPEX communication systems

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Secure and Tailored Health Solutions for People with Specific Requirements Leveraging Advanced AI Techniques

Secure and Tailored Health Solutions for People with Specifi...

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International Conference on ICT in Business Industry & Government (ICTBIG)

作者： Vaishali Singh Veena C S Raja Praveen K N Maharishi School of Engineering & Technology Maharishi University of Information Technology Uttar Pradesh India Department of Electronics and Communication Engineering Presidency University Bangalore Karnataka India Department of Computer Science Engineering Faculty of Engineering and Technology JAIN (Deemed-to-be University) Bangalore Karnataka India

Our proposed method aims to revolutionize healthcare by leveraging advanced AI techniques to tailor health solutions for individuals with specific health requirements. This innovative approach integrates three powerful AI algorithms: Deep Neural Network (DNN), Long Short-Term Memory (LSTM), and Generative Adversarial Network (GAN). These algorithms work collaboratively to develop secure, precise, and individualized healthcare services. The DNN mimics the brain's structure to extract intricate patterns, the LSTM handles sequential data and long-term dependencies, and the GAN generates data resembling real distributions. Security and privacy are ensured through data encryption and secure communication. The tailored health solution is a result of integrating these techniques, providing enhanced healthcare services.

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Service-Centric Architectures in Cloud Security: An In-Depth Analysis

Service-Centric Architectures in Cloud Security: An In-Depth...

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Advances in Computation, Communication and Information technology (ICAICCIT), International Conference on

作者： Natya S Vivek V Dhananjay Kumar Yadav Department of Electronics and Communication Engineering Presidency University Bangalore Karnataka India Department of Computer Science Engineering Faculty of Engineering and Technology JAIN (Deemed-to-be University) Bangalore Karnataka India Maharishi School of Engineering and Technology Maharishi University of Information Technology Uttar Pradesh India

Due to its affordable and high-quality services, cloud computing has lately attracted a lot of interest. Due to the on- demand, pay-per-use characteristics that cloud services provide, which encourage companies to outsource parts of their operations with better service delivery and more value, they have become an essential component of both businesses et people's everyday lives during the last ten years. In the next years, a continued migration towards cloud-based services is predicted by the current market trend, which started in 2019. Despite the many benefits that the cloud computing paradigm offers to both enterprises and consumers, security issues are expected to be the biggest cloud computing challenges in 2020. Security problems are a result of a number of variables, including the streaming nature of these solutions and the technology that support cloud computing, which includes hybridization and multitenancy. This research examines security concerns in service-driven cloud computing in order to shed light on the situation of the industry at the moment. This paper's main contribution is an analysis of cloud security over the last ten years and the presentation of a thorough taxonomy of security concerns throughout the three-layer architecture, which includes Infrastructure-as-a-Service (IaaS), Platform-as- (PaaS), and Software-as-a-Service (SaaS).

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Reassessing Deep Learning in Time Series: Predicting Time with Foresight

Reassessing Deep Learning in Time Series: Predicting Time wi...

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Advances in Computation, Communication and Information technology (ICAICCIT), International Conference on

作者： Vinutha C B Vivek V Megha Pandeya Department of Electronics and Communication Engineering Presidency University Bangalore Karnataka India Department of Computer Science Engineering Faculty of Engineering and Technology JAIN (Deemed-to-be University) Bangalore Karnataka India Maharishi School of Engineering & Technology Maharishi University of Information Technology Uttar Pradesh India

Machine learning relies heavily on time series forecasting, which has a wide range of uses, including although not limited to forecasting air quality, traffic patterns, and power use. Recent developments in deep training and matrix factorization models, however, have shown competitive performance and are emerging as alternatives. However, a fundamental disadvantage of these contemporary models over more established ones is their complexity. The Gradient Boosted Regression Tree, a well-known machine learning baseline, and popular deep learning models are compared in this work. We convert the time series forecast challenge into a window-based prediction issue, which is akin to (DNN) models. In addition, we design the GBRT model's input and output structure. In order to construct a single input instance to simulate a multi-output GBRT model, we concatenate the desired values with additional characteristics for each training window before flattening them. Using nine datasets, we undertake a thorough investigation and evaluate eight cutting-edge deep learning models recently presented at prestigious conferences. The findings show that a simple GBRT model performs much better than the state-of-the-art DNN models evaluated in this research thanks to the window-based input transformation.

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MATLAB Toolbox for fractional-variable-order closed loop systems with a digital controller

MATLAB Toolbox for fractional-variable-order closed loop sys...

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International Conference on Control, Automation, Robotics and Vision (ICARCV)

作者： Piotr Oziablo Dorota Mozyrska Mariusz Matusiak Faculty of Computer Science Bialystok University of Technology Wiejska 45A Poland Faculty of Electrical Electronics Computer Science and Control Engineering Lodz University of Technology Lodz Poland

ISBN: (纸本)9781665476881

In the paper, there is presented a MATLAB Toolbox that allows simulation and parameter tuning of closed-loop systems with fractional-variable-order digital PID (FVOPID) controllers. The proposed toolbox provides MATLAB Simulink blocks of FVOPID based on two different implementations of Grünwald-Letnikov fractional-variable-order operator. An additional part of the toolbox is an application with a GUI interface which primary purpose is to simulate and find the optimal tuning parameters of FVOPID for a given closed-loop system. The tuning process, in this case, can be performed employing different optimization methods set to minimize an objective function according to the selected integral criterion. The paper describes the internal architecture (design) of the toolbox and its functionalities.

关键词： Software packages Optimization methods Programming Linear programming Calculus Closed loop systems Tuning

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