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2023 7th International Conference On Computing, Communication, Control And Automation, ICCUBEA 2023

作者： Sudharson, K. Panimalar, S.P. Ambhika, C. Vijaya, K. Kumar, S. Pradeep Kovarasan, Rajesh Kambattan Rajalakshmi Engineering College Department of Csbs Chennai India Saveetha Engineering College Dept. of Information Technology Chennai India Velammal Institute of Technology Dept. of Information Technology Chennai India Velalar College of Engineering and Technology Department of Cse Chennai India Saveetha School of Engineering Simats Department of Cse Chennai India Vel Tech Rangarajan Dr. Sagunthala R&d Institute of Sci. and Tech. Department of Cse Chennai India

ISBN: (纸本)9798350304268

The popular cryptosystem technology with a realistic way to a highly secure and a smaller encryption bit size is known as Hyper Elliptical Curve Cryptography (HECC). The key-agreement issue is a significant drawback in the crucial demand for an explanation. A secret key must be disseminated among the clients to protect group-based data transfer in a distributed architecture. A revolutionary dynamic group secret key control is present to establish effective key distribution and administration. This article suggests key-agreement architecture based on hyperelliptic curve cryptography. The concept of the strategy, in this case, is to split a large group into multiple segments, with each segment preserving its security code to regulate the segment and managing numerous segments using a HECC management algorithm based on the Key Agreement. The study introduces a novel approach to collective key generation with encryption. An architecture for mobile networks using the Key Agreement-based HECC for Encryption (KAHECCE) suggested algorithm were simulating in contrast to the traditional techniques currently used for MANETs. KAHECCS outperforms prior methods in terms of throughput efficiency while demonstrating sophisticated key exchange characteristics without sacrificing overhead or storage costs. © 2023 IEEE.

关键词： adhoc communication cryptography elliptic curve encryption key-agreement

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Multispectral Imaging and Geo-Environmental Detection-A Case Study

Multispectral Imaging and Geo-Environmental Detection-A Case...

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Geo-EnvironMeet 2025: Innovative Developments toward Sustainability

作者： Tohm, Calvin Sieverding, Heidi Lingwall, Bret South Dakota School of Mines and Technology Rapid CitySD United States Dept. of Civil and Environmental Engineering South Dakota School of Mines and Technology Rapid CitySD United States

ISBN: (数字)9780784485682

ISBN: (纸本)9780784486016

Detection of geo-environmental problems below pavements is a challenge. Although samples can be obtained by coring through the pavement, this can only be performed at a small number of select locations to provide access to the subgrade and subsurface soils. Remote sensing has potential, however, to reveal conditions below that pavement. For detection of the location of a heavy-metal-contaminated pipe leak below a pavement and extents of post-leak inundation, multispectral imaging from an unmanned aerial vehicle was performed. Multi-spectral imaging across multiple bands of the electromagnetic spectrum allows for sub-pavement conditions to be examined by flying the area and imaging multiple times per day over several days. A leak is known in the system as significant volumes of water were found to be missing after a mass balance on the inflow and outflow of the drain system. This heavy-metal-contaminated water required remediation, so the location and extents were critical to identify. Change detection across the multi-spectral point cloud collected from several flights allowed for the location of the leak in the drain system to be identified, and the extents of contaminated soils to be quantified. © ASCE.

关键词： Unmanned aerial vehicles (UAV)

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Two-Dimensional Direction-of-Arrival Estimation for More Sources Than Sensors 5

Two-Dimensional Direction-of-Arrival Estimation for More Sou...

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5th International Seminar on Research of Information technology and Intelligent systems, ISRITI 2022

作者： Wisudawan, Hasbi N. P. Ramadhani, Amalia Rizqy Dwicahyo, Nicholaus Valentino Ariananda, Dyonisius Dony Hidayat, Risanuri Dewanto, Wahyu Universitas Islam Indonesia Dept. of Electrical Engineering Yogyakarta Indonesia Universitas Gadjah Mada Dept. of Electrical Engineering and Information Technology Yogyakarta Indonesia

ISBN: (纸本)9781665455121

This paper concerns the problem of two-dimensional (2-D) angle (azimuth and elevation) estimation for uncorrelated far-field sources using the proposed sparse rectangular array of antennas, which is constructed by applying the spatial compression on the uniform rectangular array based on the 2-D sparse ruler concept. The correlation matrix of the sources is estimated and applied as an input for the power spectrum / pseudospec-Trum estimation algorithm, i.e., classical beamforming, minimum variance distortionless response (MVDR), and multiple signal classification (MUSIC). The simulation study shows that the estimation algorithms are able to spot the direction-of-Arrival (DoA) of the sources, which consists of the azimuth and elevation angles, and where the number of sensors is less than the number of sources. Apart from that, the 2-D DoA estimation process using the MUSIC-based method shows better performance from the perspective of the root mean square error, even in a very low sisnal-Te-noise ratio value at the receiver. © 2022 IEEE.

关键词： Multiple signal classification

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Impact of Implementing the Real Estate (Regulation and Development) Act in the Construction Industry

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Journal of Legal Affairs and Dispute Resolution in engineering and Construction 2025年第3期17卷

作者： Vaghela, Harshpalsinh Tripathi, Kamalendra Kumar Jha, Kumar Neeraj Dept. of Civil Engineering Institute of Technology Nirma Univ. Gujarat Ahmedabad382481 India Dept. of Civil Engineering Indian Institute of Technology Delhi New Delhi110016 India

The Indian real estate sector is pivotal in the nation's economic growth. The purpose of this study is to identify and evaluate the effects of implementing the Real Estate (Regulation and Development) Act in the Construction Industry in Gujarat, India. Utilizing a comprehensive literature review, 26 impact attributes were identified, and an extensive questionnaire was developed, collecting 96 responses from industry stakeholders. The data were analyzed using descriptive statistics, exploratory factor analysis, and fuzzy preference relations metrics. Findings reveal that consumer-centric standardization and transparency is the most critical factor, enhancing buyer confidence and market transparency, while price escalation and market uptrend is the least important. This research offers valuable insight for policymakers in improving the real estate sector's transparency to protect buyer's interests and boost real estate investment. The study underscores the necessity for targeted reforms to enhance industry standards and promote a more transparent and accountable real estate market in Gujarat. © 2025 American Society of Civil Engineers.

关键词： Real estate Impact attributes Factor analysis Questionnaire survey Fuzzy preference relations

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A Collection of Exploratory Data Analysis Techniques for Process Fault Detection in the Tennessee Eastman Dataset

A Collection of Exploratory Data Analysis Techniques for Pro...

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Information and Communication technology (ICICT), International Conference on

作者： Sadman Nasif Anika Tasnim Nahid Sanzida Dept. of Chemical Engineering Bangladesh University of Engineering and Technology Dhaka Bangladesh

ISBN: (数字)9798331508227

ISBN: (纸本)9798331508234

The Tennessee Eastman process (TEP) is a widely studied industrial benchmark for testing fault detection and diagnosis techniques, given its complexity and the need for reliable fault detection systems in chemical plants. This paper proposes a comprehensive application of exploratory data analysis (EDA) techniques to the TEP dataset to enhance process fault detection and improve understanding of the dataset's features. The proposed methodology involves plotting time series data to capture temporal dynamics and applying Shewhart control charts to monitor process variability. Additionally, deviation atlases are used to detect anomalies across all features, dendrograms are employed to identify hierarchical clusters, and correlation heatmaps visualize interdependencies between process variables. By applying these EDA techniques, patterns and relationships that were less apparent in the raw dataset became identifiable, contributing to a more thorough fault diagnosis. The findings highlight the value of EDA in uncovering hidden insights, which could aid in the development of more robust fault detection algorithms for real-world industrial applications.

关键词： Fault diagnosis Data analysis Fault detection Time series analysis Process control Data visualization Control charts Feature extraction Stability analysis Monitoring

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Lung Cancer Image Identify and Categorization using Artificial Neural Networks

Lung Cancer Image Identify and Categorization using Artifici...

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2024 International Conference on Computational Intelligence for Green and Sustainable Technologies, ICCIGST 2024

作者： Lingappa, Ediga Begum, D Jareena Pachouri, Priya Rashmi, Kuderu Varalakshmi, Thokala Tharuna Kumar, Anoop Mallareddy College of Engineering Maisammaguda Dept of Computer Science and Engineering TS Secunderabad500100 India CMR Institute of Technology Dept. of Artificial Intelligence and Data Science Bengaluru560037 India Malla Reddy University Dept of Cyber Security Hyderabad India

ISBN: (纸本)9798350381887

Lung cancer that is made up of small cells is called small cell lung cancer (SCLC). Smoking tobacco in any form-cigarettes, cigars, or pipes-is by far the most significant risk factor for developing lung cancer, though it is only one of many. Cancer of the lungs is known as lung cancer. When cells in the body multiply uncontrollably, cancer develops. If cancer cells enter the lymphatic system or the bloodstream, they can travel to other organs and spread the disease. Cheap and fast cancer diagnostics could save millions. Latestage cancer treatment is hard. Lung cancer is diagnosed non-invasively. Biopsy requires careful ANN architecture selection. This study proposes a diagnosis ANN model. ANN research is 'hot' in cardiology, cancer, and radiology. Medical research uses ANNs. Lung cancer diagnosis was tested. MR images assess lung health for the neural network. MATLAB created ANNs and processed images. Training data was extracted from MR images using Harlick texture features. MATLAB made ANNs. Elman Network exceeds ANNs with 90.30 %. Lung cancer can develop. MRIs detect lung cancer. MRIs show lung development. Many lung tumour detection research use machine learning and deep learning. MRI algorithms swiftly detect lung malignancies, improving patient therapy. Radiologists use these forecasts. The study evaluates a self-defined ANN for lung tumour identification. The radiologist needs time to find and remove the cancer from the MR. technology improves performance and segmentation. Machines always predict and detect. Neural networks outperformed SVM, Random forest, regression, and others. © 2024 IEEE.

关键词： Lung cancer

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Performance Analysis of Electric Drive Mechanism for Lifting the Shutter of a drainage dam using Programmable Logic Controller

Performance Analysis of Electric Drive Mechanism for Lifting...

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Signal Processing and Advance Research in Computing (SPARC), International Conference on

作者： Anurag Dwivedi Muskan Yadav Devanshu Singh Aman Kumar Javed Khan dept. of Electrical Engineering Bansal institute of engineering and technology Lucknow India

ISBN: (数字)9798350385205

ISBN: (纸本)9798350385212

In this paper the design and installation of a water level control system based on PLCs is the main work. Numerous water-saving systems are in place to deliver water from the dam (A wall that holds back water). Thus, it is crucial to open and close the dam gate in order to conserve water. The proposed system achieved a shutter opening/closing time of 10 seconds. Additionally, the PLC-based controller exhibited a response time of ${1 0}$ milliseconds to control signals, ensuring rapid and efficient shutter movement. The goal of the dam automation system with a PLC (programming logic controller) base is to control the water level in the dam reservoir area. Dam gates are controlled by both manual and programmable logic controller (PLC) systems. The PLC is used to regulate the releasing and shutting of dam gates in order to save water resources for irrigation and to operate the dam gate efficiently based on the water level. It also aids in warning nearby residents about impending flooding. A collection of level sensors, a PLC, relays, and a DC motor make up this system. A series of level sensors are used to measure the water level and provide an input signal to a PLC. PLC uses data from level sensors to manage the dam’s gate. To open and close the gate, a dc motor is driven by relays in both forward and backward directions. This autonomous system’s operation will be entirely dependent on the PLC’s ladder diagram programming technique.

关键词： Dams Programmable logic devices Logic gates Water conservation Signal processing DC motors Sensors Logic Time factors Relays

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Hybrid Layered Classification Model for Heart Disease Diagnosis 3

Hybrid Layered Classification Model for Heart Disease Diagno...

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3rd International Conference on Intelligent engineering and Management, ICIEM 2022

作者： Jain, Archika Somwanshi, Devendra Singh, Rajesh Singh, Ghanshyam Poornima College of Engineering Dept. of Computer Engineering Jaipur India Uttaranchal University Uttaranchal Institute of Technology Dept. of Electronics and Communication Dehradun India

ISBN: (数字)9781665467568

ISBN: (纸本)9781665467568

Over past few decades due to hectic schedule and careless behavior of human much of disease has arises in form of life killer. Among several Heart diseases is one of the most leading destroyer diseases around the globe. Only a precise and timely forecast of this disease can aid in its prevention. Although many ways have been presented to assist professionals, each algorithm has its own set of obstacles. To improve the prognosis accuracy with low false alarms a new ensemble algorithm has proposed in this paper. To show the effectiveness of proposed approach it has simulated with the traditional and modern algorithm. The results indicates that proposed approach has improve prediction accuracy significantly. © 2022 IEEE.

关键词： Diseases

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Effectiveness of Recurrent Neural Network with Biomimic Components 3

Effectiveness of Recurrent Neural Network with Biomimic Comp...

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

作者： Singh, Paras Nath Sakhare, Anupama Sarada, T. Cmr Institute of Technology Dept. of Computer Science and Engineering Bangalore560037 India Rtm Nagpur University Dept. of Electronics and Computer Science Nagpur440033 India

ISBN: (纸本)9798350343274

In order to improve the energy efficiency and computational capacity of our data processing systems, bioinspired, or neuromorphic, computing draws inspiration from how the brain computes. Emulation of natural systems, patterns, and components is known as biomimetics or biomimicry, and it is done to address challenging challenges in society. The term 'spintronics' refers to the application of a fundamental property of particles (the spin of an electron) known as the spin to information processing. Hopfield was the first to establish a direct connection between physical models and neural networks. To learn any of these models, the neural network must be able to adjust the coupling between each pair of spins. To implement multi-layer perceptron (neural network) structures, current technologies, however, have necessitated the extensive usage of complementary metal-oxide-semiconductor (CMOS) devices, which raises the perceptron's complexity of manufacture, space need, and power consumption. In this paper, it is suggested that the first trainable CMOS-free recurrent neural network with biomimetic components can be built using biomimetic neurons made of domain wall-magnetic tunnel junctions. This analysis shows how well this system performs computationally on benchmark tasks and how much more efficiently it performs computationally than alternative recurrent neural network systems. © 2023 IEEE.

关键词： Biomimetics

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Adventitia Segmentation on Superficial Femoral Artery Optical Coherence Tomography Images 24

Adventitia Segmentation on Superficial Femoral Artery Optica...

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24th IEEE International Conference on Bioinformatics and Bioengineering, BIBE 2024

作者： Anić, Miloš Nikopoulos, Sotirios Siaravas, Konstantinos Katsouras, Christos S. Potsika, Vassiliki Filipović, Nenad Fotiadis, Dimitrios I. University of Ioannina MedLab Ioannina Greece Medical School Dept. of Cardiology Ioannina Greece Medical School Michaelidion Cardiac Center Dept. of Cardiology Ioannina Greece University of Ioannina Unit of Medical Technology and Intelligent Information Systems Dept. of Materials Science and Engineering Ioannina Greece University of Kragujevac BioIRC Kragujevac Serbia University of Ioannina Biomedical Research Institute FORTH Unit of Medical Technology and Intelligent Information Systems Dept. of Materials Science and Engineering Ioannina Greece

ISBN: (纸本)9798331518622

Atherosclerotic disease on peripheral arteries, commonly known as peripheral artery disease represents accumulation of cholesterol in peripheral arteries. It causes the formation of different types of depositions called plaques which cause thickening of the arterial walls resulting in reduced blood flow to lower extremities, in case of femoral arteries, upper extremities, in case of brachial artery or brain in case of carotid artery. Current research shows that approximately 8.5 million Americans, aged over 40 years, are affected by peripheral artery disease while one fourth of them falls into a severe category. For these reasons, an early detection of the disease is important. In order to detect the disease, arteries need to be imaged properly. In the recent years, an increase of optical coherence imaging has occurred due to the ease of use and the ability to detect tissue morphology which is extremely important for the detection of the disease. From the tissue morphology, it is of most importance to observe the tissue between lumen and intimal layer of the artery, since the majority of the plaques form in that region, but it is also important to observe the region between intima and adventitia (the outer wall of the artery) since the plaque can penetrate the intimal layer as well. In this paper, a deterministic approach for the detection of the adventitia is described based on the previously detected intimal layer of the artery. The proposed method is evaluated on optical coherence tomography images from 8 specimens of porcine femoral arteries. The results show that the detection of adventitia is possible on this image modality with Dice coefficient 0.9805 and Hausdorff distance 0.1 mm. © 2024 IEEE.

关键词： Optical coherence tomography

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