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

作者： Sahoo, Girija Shankar Dass, Sandhya Prakash, Febin Maharishi School of Engineering & Technology Maharishi University of Information Technology Uttar Pradesh India Presidency University Department of Electronics and Communication Engineering Karnataka Bangalore India Department of Computer Science and Information Technology Bangalore India

ISBN: (纸本)9798350315127

The precision comparison between the proposed method and traditional methods is a crucial evaluation of their performance in machine learning and information retrieval tasks. Precision, a fundamental metric, measures the accuracy of positive predictions. This study presents the 'Proposed Method,' an innovative approach, alongside 'Traditional Methods,' representing conventional approaches. The comparison, visualized in a precision-focused diagram, demonstrates how effectively each method identifies relevant instances. A higher precision value in the Proposed Method implies its proficiency in minimizing false positives, particularly vital in precision-critical applications like medical diagnosis and spam email classification. This analysis aids stakeholders and researchers in assessing the precision-related trade-offs between innovation and convention, guiding informed decisions for specific contexts. © 2023 IEEE.

关键词： information retrieval

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Enhancing Remote Oversight of Plants with a Compact IIoT System 3

Enhancing Remote Oversight of Plants with a Compact IIoT Sys...

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

作者： Singh, Shweta Ganorkar, Akshaya M Anujhna, B. Maharishi School of Engineering & Technology Maharishi University of Information Technology Uttar Pradesh India Presidency University Department of Electronics and Communication Engineering Karnataka Bangalore India Department of Computer Science and Information Technology Bangalore India

ISBN: (纸本)9798350343274

It is impossible to overestimate the importance of remotely monitoring industrial facilities in the context of the Industrial Internet of Things. The goal of this line of research is to improve remote monitoring by using real-time data analytics, predictive maintenance, and energy optimization with a tiny Industrial Internet of Things (IIoT) system. The three most important algorithms are an energy optimization method using a proportional-integral-derivative (PID) controller, a predictive maintenance strategy based on machine learning models, and a real-time data streaming and analysis tool. The proposed method is said to be able to use these algorithms in real time, which enables it to schedule preventive maintenance, identify anomalies, and use energy effectively. Effective, sustainable, and data-driven plant management support should be expected to result in minimal downtime, lower operating costs, and ecologically conscious operations. © 2023 IEEE.

关键词： Proportional control systems

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Two-Mode Biomedical Sensor Build-up:Characterization of Optical Amplifier

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computers, Materials & Continua 2022年第3期70卷 5487-5501页

作者： Usman Masud Fathe Jeribi Mohammed Alhameed Faraz Akram Ali Tahir Mohammad Yousaf Naudhani Faculty of Electrical and Electronics Engineering University of Engineering and TechnologyTaxila47050Pakistan Department of Electrical Communication Engineering University of KasselKassel34127Germany College of Computer Science&Information Technology Jazan UniversityJazan45142Saudi Arabia Faculty of Engineering and Applied Sciences Riphah International UniversityIslamabad44000Pakistan Faculty of Information&Communication Technology Balochistan University of Information TechnologyEngineering and Management SciencesQuetta

Intracavity absorption spectroscopy is a strikingly sensitive technique that has been integrated with a two-wavelength setup to develop a sensor for human *** factors are considered in such a scenario,out of which Relative Intensity Noise(RIN)has been exploited as an important parameter to characterize and calibrate the said *** the performance of an electrical based assessment arrangement which has been developed in the laboratory as an alternative to the expensive Agilent setup,the optical amplifier plays a pivotal role in its development and operation,along with other components and their ***,the investigation and technical analysis of the amplifier in the system has been explored in *** algorithm developed for the automatic measurements of the system has been effectively deployed in terms of the laser’s *** this in perspective,a frequency dependent calibration has been pursued in depth with this scheme which enhances the sensor’s efficiency in terms of its *** this way,our investigation helps us in a better understanding and implementation perspective of the proposed system,as the outcomes of our analysis adds to the precision and accuracy of the entire system.

关键词： Biomedical sensor cavity optomechanics spectroscopy relative intensity noise semiconductor laser diode

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IOT-Based Encrypted for Knowledge Safeguarding

IOT-Based Encrypted for Knowledge Safeguarding

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

作者： Krishna, Vijaya Manju Bargavi, S.K. Chaudhary, Chetan Presidency University Department of Electronics and Communication Engineering Karnataka Bangalore India Department of Computer Science and Information Technology Bangalore India Maharishi School of Engineering & Technology Maharishi University of Information Technology Uttar Pradesh India

ISBN: (纸本)9798350357769

A clandestine intelligence tactic emerged, involving the concealment of data within images reduced to a minuscule size, imperceptible to the human eye. In the modern era, characterized by the proliferation of Internet technology and global internet use, the focus shifts towards fortifying the security of IoT services. The objective is to enhance the reliability and efficacy of IoT systems in managing customer interactions. This work offers a secret-key steganographic technique that enables four 128x128 -pixel grayscale cover images to contain four 128x128 -pixel hidden pictures. The used technique analyses the frequency components of the cover image using the wavelet transform. Combining steganography with encryption techniques increases the system's security and makes it more resistant to potential attackers. The primary purpose of steganography is accomplished when the generated stego-image is conveyed, successfully avoiding suspicion in both objective and subjective assessments. The recommended system is created in MATLAB R2018b on a Pentium-4 computer. The reliability of IoT services. In the Internet of Things, where data encryption is in line with scientific development. © 2023 IEEE.

关键词： Covert communication Data security Encrypted Encryption techniques Image concealment and PSNR (Peak Signal to Noise Ratio) IoT-based Knowledge safeguarding Steganography Wavelet transform

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Generative Adversarial Networks for Cybersecurity Threat

Generative Adversarial Networks for Cybersecurity Threat

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2023 International Conference on Recent Advances in Science and engineering Technology, ICRASET 2023

作者： Ojha, Anatha Charan Agarwal, Ankita Swetha, G. Department of Computer Science and Information Technology Bangalore India Maharishi University of Information Technology Maharishi School of Engineering & Technology Uttar Pradesh India Presidency University Department of Electronics and Communication Engineering Karnataka Bangalore India

ISBN: (纸本)9798350306927

We provide a unique method to enhance cybersecurity threat prediction using generative adversarial networks (GANs). Through competitive training, the generator and discriminator parts of GANs are customized for application in the cybersecurity industry. Three key algorithms underlie this method. First, to create believable threats, GANs are employed in the GAN Architecture for Threat Generation. The discriminator distinguishes between actual and phony threat data, while the generator generates false threat data. These simulated assaults are a significant part of cybersecurity threat predictions. Second, Long Short-Term Memory (LSTM) neural networks are used in the Threat Scenario Prediction Algorithm's Time Series Forecasting Algorithm. To predict possible outcomes, long short-term memory (LSTM) models the temporal dependency of historical threat data. This approach offers perceptions into prospective threats, enabling the adoption of preventative actions. Finally, Markov chains are used by the Threat Evolution Algorithm to depict the dynamic evolution of cybersecurity threats. In order to shed light on how dangers vary over time, it forecasts the chance of a transition from one state of hazard to another. We get a deeper understanding of threat trajectories and how they influence an organization's cybersecurity by adopting a more dynamic approach. This comprehensive approach combines state-of-the-art techniques in threat scenario generation, forecasting, and evolution modeling, providing organizations with a robust toolset to proactively address cybersecurity challenges. © 2023 IEEE.

关键词： Long short-term memory

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An Effective Statistics Investigation for the Structured Healthcare using Reasonable Ensemble Machine Learning Systems 3

An Effective Statistics Investigation for the Structured Hea...

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

作者： Yadav, Dhananjay Kumar Sharma, Nipun Kudari, Jayashree M Maharishi School of Engineering & Technology Maharishi University of Information Technology Uttar Pradesh India Presidency University Department of Electronics and Communication Engineering Karnataka Bangalore India Department of Computer Science and Information Technology Bangalore India

ISBN: (纸本)9798350343274

Due to its rapid expansion, healthcare data has gained widespread attention in today's data-driven society. There are both structured and unstructured representations. In order to provide patients with individualised care, the healthcare industry now needs to analyse both structured and unstructured data. This study explains the basics of ensemble learning for categorization projects. Disease classification through organised healthcare analysis is the main topic here. Two stages are proposed in this section: The proposed competitive feature selection model was introduced in phase one. It takes datasets and determines which features are most useful. In the second stage, an aggressive ensemble classification model was proposed. It is made up of a number of distinct classifiers that compete with one another to determine which is best for each individual data set. These two steps enhance the categorization efficiency of structured healthcare data. The planned work was essential in pinpointing the best qualities to prioritise. The proposed competitive ensemble classification model outperforms the state-of-the-art approaches, as demonstrated by extensive experimental findings on a variety of datasets. © 2023 IEEE.

关键词： Classification (of information)

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Bridging Image Diagnostics with Advanced Computational Techniques for Hidden Feature Detection 3

Bridging Image Diagnostics with Advanced Computational Techn...

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

作者： Manikandan, M. Dutta, Abhishek Pandeya, Megha Presidency University Department of Electronics and Communication Engineering Karnataka Bangalore India Department of Computer Science and Information Technology Bangalore India Maharishi School of Engineering & Technology Maharishi University of Information Technology Uttar Pradesh India

ISBN: (纸本)9798350343274

This research presents a comprehensive methodology for efficient medical image segmentation in radiology by synergistically combining the strengths of MobileNet and U-Net architectures. The process begins with the collection and preprocessing of diverse medical image datasets, including CT scans, MRI images, and X-rays. Preprocessing involves resizing, normalization, and data augmentation to enhance model robustness. MobileNet, known for its computational efficiency, serves as the feature extraction backbone. It efficiently captures hierarchical features from input medical images while minimizing computational requirements. Simultaneously, a U-Net-style architecture is integrated to leverage its exceptional segmentation accuracy. Skip connections are introduced to connect corresponding layers in both MobileNet and U-Net, facilitating the transfer of low-level and high-level features. Feature maps from both components are fused at multiple levels, combining MobileNet's efficiency with U-Net's accuracy. map, representing the final segmentation output. The hybrid model is trained using annotated medical image data with loss functions like Dice loss or cross-entropy. Fine-tuning and hyperparameter optimization are performed to enhance performance. The proposed methodology is applied to real-world radiology scenarios, such as tumor segmentation, organ delineation, and lesion detection. It significantly outperforms traditional methods, demonstrating superior accuracy and computational efficiency. © 2023 IEEE.

关键词： Feature extraction

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Open Lora Design and Implementation For IoT

Open Lora Design and Implementation For IoT

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

作者： Yadav, Dhananjay Kumar Tony Aby Varkey, M. Adil, Mir Maharishi School of Engineering & Technology Maharishi University of Information Technology Uttar Pradesh India Presidency University Department of Electronics and Communication Engineering Karnataka Bangalore India Department of Computer Science and Information Technology Bangalore India

ISBN: (纸本)9798350357769

As an effective low-power wide-area (LPWA) connection that enables energy-efficient gadgets to build an affordable connection across huge regions, the Long Range (LoRa) networking is gaining appeal. This article provides users with a strong basis for numerous IoT applications by outlining a practical method for building and implementing a private LoRa network. Typical LoRa network-based scenarios are examined before we show the LoRa system's structure and describe the functions of every component. In addition, we provide a thorough examination of the equipment conception and development of the LoRa The Gateway, which serves as a link amongst LoRa terminals to the LoRa net administration. Notably, we provide an improved software design for the LoRa servers as well as make its free to download software source code accessible on GitHub as a noteworthy contribution. This design provides flexibility and adaptability by segmenting the LoRa networking server into five separate modules and implementing a message system based on information streaming for inter-module interaction. The performance of the LoRa network is thoroughly tested in the paper's conclusion in real-world settings. © 2023 IEEE.

关键词： Equipment conception IoT applications LoRa Gateway LoRa network LoRa Network Server LoRa Node LPWA connection Microservices and IoT possibilities Software design

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IoT'S Impact on Development in the Energy Sector

IoT'S Impact on Development in the Energy Sector

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

作者： Menaka, C. Singh, Swati Sindgi, Anupama Department of Computer Science and Information Technology 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

The major facilitators of green energy changes and worldwide warming mitigation are the incorporation of alternative energy sources and electricity usage optimisation. There are several uses for modern technology, such as the Internet of Issues, in the field of energy, including supply, delivery, and demand. IoT may be used to increase consumption of clean energy, improve energy efficiency, and lessen the harmful impacts associated with electricity use. This essay summarises the material that has been published on the use of IoT in the energy sector generally and smart electrical grids in specific. Additionally, we go through IoT technologies that enable it involving the internet of things and various platforms for data processing. We also discuss the privacy and security issues that arise when using IoT in the energy industry, as well as a few potential fixes such blockchain technology. A description of the importance of IoT in the system's optimization is given to supervisors, energy the economists, including politicians in the energy sector by this survey. © 2023 IEEE.

关键词： Alternative Energy Sources Blockchain Technology and System Optimization Clean Energy Consumption Data Processing Platforms Delivery Demand Development Electricity Usage Optimization Energy Sector Green Energy Impact IoT Privacy Security Issues Supply

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Curvelet Transform Based on Edge Preserving Filter for Retinal Blood Vessel Segmentation

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computers, Materials & Continua 2022年第5期71卷 2459-2476页

作者： Sonali Dash Sahil Verma Kavita N.Z.Jhanjhi Mehedi Masud Mohammed Baz Department of Electronics and Communication Engineering Raghu Institute of Technology(A)Visakhapatnam531162India Department of Computer Science and Engineering Chandigarh UniversityMohali140413India School of Computer Science and Engineering SCETaylor’s UniversitySubang Jaya Malaysia Department of Computer Science College of Computers and Information TechnologyTaif UniversityTaif21944Saudi Arabia Department of Computer Engineering College of Computer and Information TechnologyTaif UniversityTaif21994Saudi Arabia

Segmentation of vessel in retinal fundus images is a primary step for the clinical identification for specific eye *** diagnosis of vascular pathologies from angiographic images is thus a vital aspect and generally depends on segmentation of vascular *** various approaches for retinal vessel segmentation are extensively utilized,however,the responses are lower at vessel’s *** curvelet transform signifies edges better than wavelets,and hence convenient for multiscale edge *** bilateral filter is a nonlinear filter that is capable of providing effective smoothing while preserving strong *** bilateral filter is an advanced version of bilateral filter that regulates the contrast while preserving the ***,in this paper a fusion algorithm is recommended by fusing fast bilateral filter that can effectively preserve the edge details and curvelet transform that has better capability to detect the edge direction feature and better investigation and tracking of significant characteristics of the *** C mean thresholding is used for the extraction of *** recommended fusion approach is assessed on DRIVE *** results illustrate that the fusion algorithm preserved the advantages of the both and provides better *** results demonstrate that the recommended method outperforms the traditional approaches.

关键词： Blood vessel extraction curvelet transform fast bilateral filter C mean thresholding

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