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7th International Conference on Soft Computing and Signal Processing, ICSCSP 2024

作者： Kumar, Gotte Ranjith Babu, K. Suresh Research Scholar Department of Computer Science and Engineering Jawaharlal Nehru Technological University Kukatpally Telangana Hyderabad500085 India Assistant Professor School of CS&AI SR University Telangana Warangal506371 India Professor Department of Computer Science and Engineering Jawaharlal Nehru Technological University Kukatpally Telangana Hyderabad500085 India

ISBN: (纸本)9789819799251

Mobile devices, empowered by advanced wireless networks, have revolutionized information sharing and productivity across industries. However, this ubiquitous connectivity exposes user privacy and security to risks. The core vulnerability lies in the lack of authentication between mobile devices and DHCP (Dynamic Host Configuration Protocol) servers, which assign network configurations. This research explored existing authentication mechanisms in wireless networks to address these DHCP-related security concerns, highlighting the essence of secure data communication in mobile environments. The majority of the authentication mechanisms rely on centralized environments. Some rely on a cryptographic security key, which needs to be exchanged during authentication. Blockchain-based authentication is proposed. This technology is distributed, scalable, and robust. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Mobile security

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TRANSITION FROM TRADITIONAL COB CONSTRUCTION TO 3D PRINTING OF CLAY HOMES

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Journal of Green Building 2021年第4期16卷 3-28页

作者： Amnah Y.Alqenaee Ali M.Memari Maryam Hojati Master of Science student at the Department of Civil Engineering The Pennsylvania State UniversityUniversity ParkPAUSA Professor and Bernard and Henrietta Hankin Chair in Residential Building Construction and Director of the PHRC at the Department of Architectural Engineering and the Department of Civil and Environmental EngineeringPenn State UniversityUniversity ParkPAUSA Assistant Professor at the Department of Civil Construction and Environmental EngineeringUniversity of New MexicoAlbuquerqueNMUSA

3D printing of cementitious material can provide an affordable,sustainable,and optimized approach for the construction of homes,without compromising quality or *** most of the current research and development efforts in this field are focused on cement-based concrete printing,this paper focuses on the current state-of-the-art literature review of designing and developing a sustainable clay-based mixture design that mainly includes clay,sand,straw,lime,and *** goal of this paper is to bridge the gap between typical traditional earth construction,specifically cob construction,and emerging 3D printing of cementitious *** specific objective of this paper is to offer some possible changes in the typical cob mixture so that it can be used for 3D printing of clay-based mixtures with sufficient flowability,buildability,strength,and open time(i.e.,the time period between printing of one layer and printing of another layer deposited on a layer below).The paper describes typical clay-based mixtures and their traditional process and then specifies the challenges in going from traditional cob construction to advanced computer-controlled robotic 3D printing.

关键词： 3D Printing Cob Home Cement-Free Concrete Earthen Construction Concrete 3D Printing Adobe Home Clay-Based Mixture Additive Manufacturing and Construction

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Machine Learning Techniques with LowDimensional Feature Extraction for Improving the Generalizability of Cardiac Arrhythmia

IAENG International Journal of Computer Science

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IAENG International Journal of computer science 2021年第2期48卷 1-10页

作者： Nurmaini, Siti Tutuko, Bambang Rachmatullah, Muhammad Naufal Darmawahyuni, Annisa Firdaus, Firdaus A Professor of Computer Engineering Intelligent System Research Group Universitas Sriwijaya Palembang30139 Indonesia A lecturer of Computer Engineering Department Faculty of Computer Science Universitas Sriwijaya Palembang30139 Indonesia A research assistant of Intelligent System Research Group Universitas Sriwijaya Palembang30139 Indonesia

Automatic heartbeat classification is an important stage in identifying cardiac arrhythmia. Several machine learning (ML) techniques have been proposed to perform this, but they produce an accuracy result of below 99%. In this study, a deep neural network (DNN) structure is applied to improve ML performance. The feature selection method is based on the combination of discrete wavelet transform (DWT) and principal component analysis (PCA). To avoid computational complexity, the components of PCA are derived by low-dimensional DWT coefficients. The results show that the proposed ML model achieves good performance, producing 99.76% accuracy, 91.80% sensitivity, 99.78% specificity, 93.02% precision, and 92.31% F1-score. To benchmark the proposed model, the support vector machine (SVM) and random forest (RF) techniques are used as the baseline models. The DNNs are 2.3% more sensitive than SVM, while the RF fails to classify the ECG heartbeat. Four datasets are used to analyze the robustness and generalization performance of the proposed model: MIT-BIH, SVDB, MITDB, and IncartDB. All testing results produce satisfying performance. The proposed ML model offers a potential solution to improve the generalizability of a DNN-based model in different cardiac datasets for classifying tasks. © 2021. All Rights Reserved.

关键词： Principal component analysis

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Challenges and Innovations in Multimedia and Real-Time Networking: A Review of Modeling Approaches

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Procedia computer science 2025年 252卷 53-62页

作者： Milind Shah Kajal Parmar Priyanka Padhiyar Naina Parmar Monali Parikh Dhruvansh Patni Assistant Professor Department of Computer Engineering Sardar Vallabhbhai Patel Institute of Technology (S.V.I.T) Vasad Gujarat India Department of Computer Engineering Devang Patel Institute of Advance Technology & Research (DEPSTAR) Faculty of Technology & Engineering (FTE) Charotar University of Science & Technology (CHARUSAT) Changa 388421 India Assistant Professor Department of Information Technology Krishna School of Emerging Technology & Applied Research - Drs. Kiran & Pallavi Patel Global University (KPGU) Vadodara Gujarat India

Over the past decade, the rise of broadband and mobile Internet access has led to the widespread adoption of real-time networking and multimedia applications. These platforms have become essential for connecting individuals and supporting businesses, particularly with the growing trend of remote work. The demand for video streaming services has surged significantly and is expected to continue rising. However, this increased traffic has strained network performance, leading to congestion and diminishing the quality of service, especially during peak evening hours and the COVID-19 pandemic. Besides upgrading network infrastructure, it is crucial to develop intelligent streaming systems that adapt to network conditions and user expectations to enhance customer satisfaction. This review paper explores into the basics and introduction of Multimedia and Real-Time Networking. It also explores the advancements in Adaptive and Intelligent Networking for real-time multimedia communication. The paper formulates research questions based on the discussed topics, such as the distinctions between real-time networking and traditional networking, the ways multimedia applications adjust to fluctuating network conditions, and the challenges and limitations associated with these technologies.

关键词： Real Time Networking Multimedia Challenges Innovations Intelligent Networking

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Relevance of ISO/SAE 21434 in Vehicular Architecture Development

Relevance of ISO/SAE 21434 in Vehicular Architecture Develop...

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IEEE International Conference on Systems, Man and Cybernetics

作者： V Kethareswaran Sanjay Moulik Doctoral Researcher in the Department of Computer Science and Engineering Indian Institute of Information Technology Guwahati Assam India Assistant Professor in the Department of Computer Science and Engineering Indian Institute of Information Technology Guwahati Assam India

Research in terms of security in vehicular architecture has been a focal point of deliberation in the automotive sector. The Automotive industry development has continuously evolved the scenario of adding more integration to networked vehicles or semi-autonomous vehicles. The end product of such manufacturing practices is a vehicle becoming a networked computer on wheels. In spite of providing numerous advantages, these developments in the automotive industry are also bringing more challenges in terms of security. Hence, the industry has been forced to emphasise the principle of Security by Design. Efforts in this direction have resulted in the formulation of the ISO/SAE 21434 standard. In this work, we focus on summarising the ISO/SAE 21434 standard and analysing its relevance for automotive architecture development. Related works in the standard's approach of Security by Design are summarised. Additionally, we propose an application work of the standard in the context of automotive Architecture development as future work.

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Standardization of Pediatric Cardiovascular Anomaly Anatomy Reconstructions

Standardization of Pediatric Cardiovascular Anomaly Anatomy ...

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Medical Technologies National Conference (TIPTEKNO)

作者： Mohamad Humam Alzaeim Kevser Banu Köse Şenol Pişkin Wael Shamsi Basha Fatma Zeynep Gungoren Ömer Faruk Şahin Js Femilda Josephin Master’s Student in Biomedical Engineering & Bioinformatics Istanbul Medipol University Istanbul Turkey Assistant Professor in Biomedical Engineering department Istanbul Medipol University Istanbul Turkey Assistant Professor in Mechanical Engineering department İstinye University Istanbul Turkey Department of Radiology The Anadolu Medical Center Istanbul Turkey Bachelor of Science in Molecula Biotechnology İstinye University Istanbul Turkey Assistant Professor in Computer Engineering Department İstinye University Istanbul Turkey

ISBN: (数字)9798331529819

ISBN: (纸本)9798331529826

In the realm of congenital cardiovascular diseases, the understanding, modeling, and visualization of such diseases as they develop during the neonatal growth period continues to be a challenge despite the current technological advancements. Moreover, such diseases as vascular abnormalities pose further risks due to their implications for a proper standardized method for three-dimensional visualization for planning and growth monitoring. This study uses imaging and computational techniques to create multiple models that relate the diseases as they progress from the initial phase toward the late growth stage for newborns’ cardiovascular systems. Three-dimensional modeling of patients would be created from patient-specific scans coupled with image processing algorithms. This study also aims to use the working principles of already existing tools for diagnosing aortic & brain aneurysms and pulmonary hypertension for cardiovascular development. To comprehensively understand such diseases and how their physical morphology may be standardized.

关键词： Visualization Solid modeling Pediatrics Computational modeling Morphology Standardization Brain modeling Planning Monitoring Medical diagnostic imaging

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Developing smart devices with automated Machine learning Approach: A review

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Materials Today: Proceedings 2022年 51卷 826-831页

作者： Sunil A. Patel Sanjay P. Patel Yagna Bhupendra Kumar Adhyaru Santosh Maheshwari Pankaj Kumar Mukesh Soni Assistant Professor Computer Science and Engineering Department Government Engineering College Patan Gujarat India Assistant Professor Computer Engineering Department Hansaba College of Engineering & Technology Gokul Global University Gujarat India Head Computer Engineering Department Hansaba College of Engineering & Technology Gokul Global University Gujarat India Department of Computer Science & Engineering Noida Institute of Engineering & Technology Greater Noida India Research Scholar Computer Science and Engineering Department University Bhopal 462044 India

In the current era, Artificial Intelligence is playing a major role in smart devices. Apart from incorporating intelligence in the devices, it has extended its range beyond that. Now new AI development tools such as automated machine learning (AutoML) approach are increasing rapidly because of its performance on smart devices. AutoML is used to design a machine learning model with self-adapting capability which can perform the task in less time with advanced skills. This approach does not need any explicit coding and the data science experts but this can build smart sensor codes that will get executed automatically on the microcontrollers embedded within the IoT devices. Due to these capabilities, the developers can build efficient smart devices with real-time responsiveness, security, and data privacy without the help of machine learning experts. In this paper, we will show how AutoML will be used to create smart de-vices. The objective of this paper is to develop the skills that will help to develop smart edge devices which include planning, design-ing, implementation, and the evaluation of the smart IoT applications.

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Intrusion detection in big data using hybrid feature fusion and optimization enabled deep learning based on spark architecture

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computers and Security 2022年 116卷

作者： M .P . , Ramkumar Reddy, P.V. Bhaskar Thirukrishna, J.T. Vidyadhari, Ch. Assistant Professor Department of Computer Science and Engineering Thiagarajar College of Engineering Madurai625015 India Professor School of Computer Science and Engineering REVA University Karnataka Bengalore India Associate Professor Department of Information Science and Engineering Dayananda Sagar Academy of Technology and Management Karnataka Bangalore560082 India Assistant Professor Department of Information Technology Gokaraju Rangaraju Institute of Engineering and Technology Bachupally Hyderabad India

With the rapid expansion of Internet services and increasing intrusion issues, conventional intrusion detection techniques cannot work well with several difficult intrusions. Though several intrusion detection methods have been introduced in the past years, developing an Intrusion Detection Systems (IDS) with prevailing intrusion detection strategy is still very much desirable. Hence, a robust and effective intrusion detection approach, named RV coefficient+Exponential Sea Lion Optimization-enabled Deep Residual Network (ExpSLO-enabled DRN) using spark is devised for the intrusion detection. Here, the unique features are selected using proposed RV coefficient-based hybrid feature fusion, which is designed by the incorporation of wrapper, class-wise information gain (CIG), and Canberra distance in slave node. With the distinctive features selected, the process of data augmentation is done using oversampling for making the data more appropriate to perform the further process in the slave node. Moreover, DRN classifier is utilized for detecting the intrusions in the master node where the DRN training is done using devised ExpSLO algorithm, which is the hybridization of Exponentially Weighted Moving average (EWMA) and Sea Lion Optimization (SLnO). Furthermore, the devised method obtained better performance by considering the evaluation metrics, such as precision, recall, and F-measure with the higher values of 0.8800, 0.8845, and 0.8822 based on without attacks using dataset-2. © 2022

关键词： Intrusion detection

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Effect of Natural Reinforcement Aperture Shape on Bearing Capacity of Reinforced Soil 4th

Effect of Natural Reinforcement Aperture Shape on Bearing Ca...

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4th International Conference on Transportation Geotechnics, ICTG 2021

作者： Ahirwar, Sunil K. Mandal, J.N. Assistant Professor Civil Engineering and Applied Mechanics Department Shri G. S. Institute of Technology and Science Indore452003 India Research Scholar Civil Engineering Department Indian Institute of Technology Bombay Mumbai400076 India Indian Institute of Technology Bombay Mumbai400076 India

ISBN: (纸本)9783030772338

It is of interest, for a developing country like India, to use natural and low-cost reinforcement material in rural roads. Bamboo is a locally and cheaply available alternative as a reinforcement material in place of commercial geosynthetic materials. The tridirectional bamboo grid is a new innovative reinforcement of the limited life geotextiles (LLGs) family. The present paper reports the experimental results of plate load tests conducted on sand overlying a soft clay. The model plate load tests were carried out to study the influence of the tridirectional and bidirectional bamboo grid with jute geotextile on the bearing capacity of soft marine clay. A mild steel tank with dimensions of 0.7 m × 0.7 m × 0.6 m and a square model footing size of 100 mm × 100 mm were used for all laboratory model tests. It was observed that by making a suitable modification in the aperture shape of reinforcement, the bearing capacity and settlement resistance of soft clay could be improved. The model test results show that the tridirectional bamboo grid offers superior performance compared to the bidirectional bamboo grid. © 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Bamboo

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Shielding NLP Systems: An In-depth Survey on Advanced AI Techniques for Adversarial Attack Detection in Cyber Security

Shielding NLP Systems: An In-depth Survey on Advanced AI Tec...

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Automation, Computing and Renewable Systems (ICACRS), International Conference on

作者： T. Sai Lalith Prasad K. B. Manikandan J. Vinoj Research Scholar Department of Computer Science and Engineering Vignan's Foundation for Science and Technology & Research (Deemed to be University) Guntur Andhra Pradesh India Assistant Professor Department of Artificial Intelligence and Data Science Vignan Institute of Technology and Science Telangana India Assistant Professor Department of CSE Vignan's Foundation for Science Technology and Research (Deemed to be University) Guntur Andhra Pradesh India

ISBN: (数字)9798331532420

ISBN: (纸本)9798331532437

This research investigates the challenges posed by adversarial perturbations to the robustness and reliability of Natural Language Processing (NLP) models. The study focuses on three key paradigms for enhancing the resilience of NLP systems: meta-learning, reinforcement learning, and self-supervised learning. A comprehensive evaluation of these strategies is conducted, analyzing their strengths and weaknesses in mitigating adversarial attacks. The study provides insights into the most promising approaches for enhancing the robustness of NLP models and offers directions for future research in this critical area. By advancing the resilience of NLP systems, this research contributes to the development of more robust and trustworthy AI applications across various domains, including healthcare, finance, and security.

关键词： Training Surveys Renewable energy sources Scalability Self-supervised learning Natural language processing Robustness Security Artificial intelligence Resilience

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