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2023 International Conference on Power Energy, Environment and Intelligent Control, PEEIC 2023

作者： Divya Rani, M.S. Rajesh, A. Agarwal, Ankita Presidency University Department of Electronics and Communication Engineering Karnataka Bangalore India Faculty of Engineering and Technology Department of Computer Science Engineering Karnataka Bangalore India Maharishi School of Engineering & Technology Maharishi University of Information Technology Uttar Pradesh India

ISBN: (纸本)9798350357769

The use of online computing has grown quickly across a range of institutions and businesses. The storage of information in the clouds, which enables individuals and businesses to store their personal information largely in the cloud and not on local computers, is one of the main benefits of cloud computing. Safety of data maintained in the cloud is still a major worry, however. We provide a novel security architecture in this study that is intended to improve data confidentiality and safety. Data is separated into blocks of two bytes each, and each multi-byte bit sequence is subjected to a separate evolutionary process in the revised security framework. The end product of each genetic algorithm's operation is ciphertext, which is made up of two different sets of bits. The ciphertext for these encrypted messages is difficult to find since it is stored in many places across the cloud. Additionally, the newly developed safety architecture uses algorithms that evolve on fewer data blocks to improve data security. A capability list is also used to guarantee granular and secure access to information. © 2023 IEEE.

关键词： access control Cloud security cloud service providers (CSPs) data confidentiality data encryption data privacy data protection Genetic Algorithm (GA) Internet of Things (IoT) security architecture

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Dual Radial-Resonant Wide Beamwidth Circular Sector Microstrip Patch Antennas

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Chinese Journal of Electronics 2023年第4期32卷 710-719页

作者： MAO Xiaohui LU Wenjun JI Feiyan XING Xiuqiong ZHU Lei Jiangsu Key Laboratory of Wireless Communications Nanjing University of Posts and Telecommunications Key Laboratory of Wireless Sensor Network & Communication Shanghai Institute of Microsystem and Information Technology Chinese Academy of Sciences Department of Electrical and Computer Engineering Faculty of Science and Technology University of Macau

In this article, a design approach to a radial-resonant wide beamwidth circular sector patch antenna is advanced. As properly evolved from a U-shaped d ipole, a prototype magnetic dipole can be fit in the radial direction of a circular sector patch radiator, with its length set as the positive odd-integer multiples of onequarter wavelength. In this way, multiple TM0m（m = 1,2,...） modes resonant circular sector patch antenna with short-circuited circumference and widened E-plane beamwidth can be realized by proper excitation and perturbations. Prototype antennas are then designed and fabricated to validate the design approach. Experimental results reveal that the E-plane beamwidth of a dual-resonant antenna fabricated on air/Teflon substrate can be effectively broadened to 128°/120°, with an impedance bandwidth of 17.4%/7.1%, respectively. In both cases, the antenna heights are strictly limited to no more than 0.03-guided wavelength. It is evidently validated that the proposed approach can effectively enhance the operational bandwidth and beamwidth of a microstrip patch antenna while maintaining its inherent low profile merit.

关键词： Geometry Patch antennas Perturbation methods Prototypes Magnetic resonance Microstrip antennas Bandwidth

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Selective feature-based ovarian cancer prediction using MobileNet and explainable AI to manage women healthcare

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Multimedia Tools and Applications 2024年 1-22页

作者： Almujally, Nouf Abdullah Alzahrani, Abdulrahman Hakeem, Abeer M. Attiah, Afraa Umer, Muhammad Alsubai, Shtwai Polsinelli, Matteo Ashraf, Imran Department of Information Systems College of Computer and Information Sciences Princess Nourah bint Abdulrahman University P.O. Box 84428 Riyadh11671 Saudi Arabia Department of Computer Science and Engineering College of Computer Science and Engineering University of Hafr Al Batin Hafr Al Batin39524 Saudi Arabia Department of Information Technology Faculty of Computing and Information Technology King Abdulaziz University Jeddah21589 Saudi Arabia Department of Computer Science The Islamia University of Bahawalpur Bahawalpur Pakistan Department of Computer Science College of Computer Engineering and Sciences Prince Sattam bin Abdulaziz University P.O. Box 151 Al-Kharj11942 Saudi Arabia Department of Management & amp Innovation Systems University of Salerno Fisciano84084 Italy Department of Information and Communication Engineering Yeungnam University Gyeongsan38541 Korea Republic of

Ovarian cancer is a global health concern due to the unavailability of an effective screening strategy and is often diagnosed at a late stage with approximately 70% of the case which reduces the survival chances of patients. Initial diagnosis is challenging due to inconspicuous symptoms in its initial stages which complicate its timely diagnosis. Regular screenings, such as pelvic exams, ultrasounds, and blood tests targeting specific biomarkers can be helpful for early diagnosis. In addition, the use of machine learning models can help automate this process thereby assisting medical experts for accurate diagnosis. This study aims at timely and accurate detection of ovarian cancer using a transfer learning approach that uses the MobileNet model. Moreover, the Chi-square technique is used to extract the most impactful features for better accuracy. For experiments, the Soochow University ovarian cancer dataset is employed. Extensive experiments are performed using all features from the dataset, as well as, using Chi-square-based selective features. The best accuracy of 90.88% is achieved with the Xception model when all features are used. Experimental results show a substantial increase when selective features are used indicating a 98.49% accuracy using the MobileNet model with 20 most important features. In addition, precision, recall, and F1 scores of 99.13%, 99.27%, and 99.20% are obtained showing the model’s robustness and generalization. This study also employs Shapley additive explanations to explain the importance of various features toward the model’s output thereby providing transparency for the model’s decision-making process. © The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2024.

关键词： Diagnosis

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Powering Development Wirelessly: Improvements in Far-Field Instrument Power

Powering Development Wirelessly: Improvements in Far-Field I...

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2023 International Conference on Power Energy, Environment and Intelligent Control, PEEIC 2023

作者： Kumar Sinha, Deepak Singh, Swati Sivaperumal Faculty of Engineering and Technology Department of Computer Science Engineering Karnataka Bangalore India Maharishi School of Engineering & Technology Maharishi University of Information Technology Uttar Pradesh India Presidency University Department of Electronics and Communication Engineering Karnataka Bangalore India

ISBN: (纸本)9798350357769

In this study, far-field mobile electrical power options for inexpensively mobile sensors are thoroughly investigated. Emphasis is placed on situations in which sensor placements are uncertain and battery replacement is not practicable. Low-power nondirectional mobile battery backup becomes a possibility for sensors with occasional data transmission demands, estimated radiofrequency (RF) power consumption ranging from 20 to 200 W/cm2, and a necessity for small sensor dimensions. The sensor system uses an antenna to collect coming GHz electromagnetic waves, then transforms this energy into electricity for a storage device, which could be a thin-film battery, using a rectifier circuit. This method makes it possible for the full platform-which includes gauges, an inexpensively Bluetooth transmitter, including a low-power CPU for management-to function continuously. To maximize performance, particularly at reduced incident energy levels, RF power receipt and power control circuits must be designed in concert. Both hybrid and modular power management circuitry options are described and evaluated in this research. © 2023 IEEE.

关键词： Bluetooth wireless Energy harvesting and Efficiency Optimization Far-field power Low-power sensors Mobile sensors Power management Rectenna design System integration Wireless energy transfer

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An Exhaustive Meta-Analysis on Consumer Retention Forecasting Using Advanced Machine Learning Techniques 3

An Exhaustive Meta-Analysis on Consumer Retention Forecastin...

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3rd IEEE International Conference on ICT in Business Industry and Government, ICTBIG 2023

作者： Shreenidhi, H.S. Yadav, Dhyan Chandra Swetha, G. Faculty of Engineering and Technology Department of Computer Science Engineering Karnataka562112 India Maharishi School of Engineering & Technology Maharishi University of Information Technology Uttar Pradesh India Presidency University Department of Electronics and Communication Engineering Karnataka Bangalore India

ISBN: (纸本)9798350343274

In this meta-analysis, we present a robust approach for consumer retention forecasting by integrating advanced machine learning algorithms. The method comprises three core algorithms: Consumer Behaviour Neural Network (CBNN), Retention Decision Trees (RDT), and Long Short-Term Memory for Retention (LSTM-R). The objective is to model intricate relationships within consumer behaviours and accurately predict their retention probabilities. CBNN a key component, adeptly captures intricate patterns within consumer behaviour data. It involves multiple hidden layers with activation functions, enabling accurate prediction of retention probabilities based on input features. The flowchart for CBNN showcases the training process involving forward and backward passes, underlining its deep learning approach. RDT this method utilizes decision tree algorithms to predict consumer retention decisions. By recursively splitting the dataset based on information gain, RDT efficiently models consumer behaviour, as depicted in the flowchart. Information gain is maximized to create a robust predictive model. LSTM-R tailored for temporal data in consumer retention prediction, leverages specialized LSTM architecture. It effectively processes sequential consumer interactions, crucial for accurate prediction of consumer retention probabilities. The proposed method integrates these algorithms, leveraging historical consumer data, and conducts a comprehensive meta-analysis to evaluate their predictive performance. © 2023 IEEE.

关键词： Decision trees

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Managing Cloud Networks: A Classification of SDN-Enabled Clouds

Managing Cloud Networks: A Classification of SDN-Enabled Clo...

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2023 International Conference on Advances in Computation, communication and Information Technology, ICAICCIT 2023

作者： Singh, Vaishali Kehkeshan Jallal, S. Das, Sunanda Maharishi University of Information Technology Maharishi School of Engineering & Technology Uttar Pradesh India Presidency University Department of Electronics and Communication Engineering Karnataka Bangalore India Faculty of Engineering and Technology Department of Computer Science Engineering Karnataka Bangalore India

ISBN: (纸本)9798350344387

The idea of separating the management plane from the data-forwarding gear was first introduced by Software-Defined Networking (SDN), which has brought about a revolutionary new age in networking. This innovation makes networks programmable, flexible, and dynamically reconfigurable. These characteristics have great potential for the field of computer science in the cloud, where dynamic adjustments and reconfiguration are essential owing to on-demand consumption patterns. The many simulation and empirical assessment techniques that have been created expressly for SDN-enabled cloud settings are also highlighted by us. Finally, study conducted perform a critical review of the state of the research, highlighting gaps and suggesting possibilities for further study. © 2023 IEEE.

关键词： application framework cloud computing hardware resources programmable controller resource provisioning simulation and energy modeling Software-Defined Networking (SDN)

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Nodal Transmission in 5G Wireless Networking

Nodal Transmission in 5G Wireless Networking

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2023 International Conference on Power Energy, Environment and Intelligent Control, PEEIC 2023

作者： Agrawal, Trapty Kakati, Pallabi Das, Sunanda Maharishi School of Engineering & Technology Maharishi University of Information Technology Uttar Pradesh India Presidency University Department of Electronics and Communication Engineering Karnataka Bangalore India Faculty of Engineering and Technology Department of Computer Science Engineering Karnataka Bangalore India

ISBN: (纸本)9798350357769

The increase in data transmission network speed and reliability is inextricably linked to the fast growth of information technology. This calls for the ongoing improvement and upgrading of current standards. Next-generation communication networks are being developed and deployed with diligence by several organizations. This article provides a thorough examination of the software options available that are designed for analyzing and evaluating data network behaviors. It specifically emphasizes tools with substantial built-in functionality and flexibility that are ideally suited for mobile communication systems. It becomes clear that the NS3 network simulator is the best option. This article provides an overview as well as a unique NS3 solution that makes it possible to estimate the dependability of data transmission from a network node's first movement to its removal from a base station. © 2023 IEEE.

关键词： 5G Wireless Networking communication Networks Data Transmission Interference Analysis Network Security Nodal Transmission NS3 Network Simulator Signal Quality And Distribution Algorithms Simulation Modeling

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Beyond The Internet of Things: Imagining IoT's Structure and Potential Routes

Beyond The Internet of Things: Imagining IoT's Structure and...

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2023 International Conference on Advances in Computation, communication and Information Technology, ICAICCIT 2023

作者： Varalakshmi, K.R. Mahesh, T.R. Singh, Akhilendra Pratap Presidency University Department of Electronics and Communication Engineering Karnataka Bangalore India Faculty of Engineering and Technology Department of Computer Science Engineering Karnataka Bangalore India Maharishi University of Information Technology Maharishi School of Engineering & Technology Uttar Pradesh India

ISBN: (纸本)9798350344387

wireless sensor system technology has made it possible for ubiquitous sensing, which affects many aspects of contemporary life. Indicators of environmental health, from sensitive ecologies as well as biodiversity to urban settings, may now be measured, inferred, and understood. The Internet of Things is enabled by the extensive utilization of these devices in a network that facilitates communication and action. In this network, the actuators and sensors smoothly interact with our environment as data is exchanged across platforms to provide a unified operational view. Near field communication (NFC) is the upcoming technology that will enable the transformation of the worldwide web into a fully integrated Future Internet. This technology is being advanced through the adoption of variousenabling device methods, such as tags, audience members, encased sense and actuators nodes, and nodes for near field interaction. The demand for data-on-demand, using complex and straightforward queries, increases significantly as studies transition from web to web2 to web3. This study presents a cloud-centric vision for the worldwideimplementation of the Internet of Things. The future of IoT research is expected to be influenced by many significant technology enablers and their corresponding application domains, which are emphasized. A cloud architecture based on the interplay of public as well as private clouds and employing Aneka is shown. Study conducted elaborate on the need of unity, the global web, and distributed processing in our last section of our IoT vision for the community of technical researchers. © 2023 IEEE.

关键词： Cloud-centric Internet of Things Data storage and analytics Internet of Things (IoT) New protocols Participatory Sensing Quality of Service (QoS) Radio Frequency Identification (RFID) User-cantered cloud-based paradigm Visualization Wireless Sensor Networks

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The Cloud's Balancing Confidentiality and Collaboration

The Cloud's Balancing Confidentiality and Collaboration

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2023 International Conference on Power Energy, Environment and Intelligent Control, PEEIC 2023

作者： Vivek, V. Sahoo, Girija Shankar Kehkeshan Jallal, S. Faculty of Engineering and Technology Department of Computer Science Engineering Karnataka Bangalore India Maharishi School of Engineering & Technology Maharishi University of Information Technology Uttar Pradesh India Presidency University Department of Electronics and Communication Engineering Karnataka Bangalore India

ISBN: (纸本)9798350357769

Group data sharing in cloud settings has become more popular recently as a result of cloud computing's broad acceptance. The need for efficient and safe data exchange in such settings is currently urgent. Another particular problem in cloud-based exchange of data is finding a balance of anonymity and traceability. In order to preserve anonymity, this study focuses on providing safe and effective data exchange and storage for organizations via the cloud. In order to accommodate numerous users surreptitiously in public clouds, it suggests a unique traceable collective data sharing system that makes use of key collaboration and group signature techniques. This system ensures that member identities may be tracked when required while enabling group members to converse anonymously using group signatures. Additionally, to allow for safe data exchange and preservation among group members, a shared conference key is obtained via key agreement. Notably, the key generation process for the system uses a symmetrically balanced incomplete block architecture, greatly easing the load on participants while determining a shared conference key. The suggested approach for collective information sharing on the internet of things is shown to be secure and effective via theoretical investigation and empirical assessments. © 2023 IEEE.

关键词： (KA-ABE) access control anonymity Cloud computing data breaches data integrity fault tolerance group data sharing multiple-to-many data sharing traceability

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Secure and Tailored Health Solutions for People with Specific Requirements Leveraging Advanced AI Techniques 3

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

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3rd IEEE International Conference on ICT in Business Industry and Government, ICTBIG 2023

作者： Singh, Vaishali Veena, C.S. Raja Praveen, K.N. Maharishi School of Engineering & Technology Maharishi University of Information Technology Uttar Pradesh India Presidency University Department of Electronics and Communication Engineering Karnataka Bangalore India Faculty of Engineering and Technology Department of Computer Science Engineering Karnataka Bangalore India

ISBN: (纸本)9798350343274

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. © 2023 IEEE.

关键词： Long short-term memory

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