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8th International Conference on I-SMAC (IoT in Social, Mobile, Analytics and Cloud), I-SMAC 2024

作者： Yesankar, Prajyot Gourshettiwar, Palash Gote, Pradnyawant Jiet, Moses Makuei Gadkari, Ayush Faculty of Engineering and Technology Department of Computer Science & Design Maharashtra Wardha442001 India Faculty of Engineering and Technology Department of Computer Science & Medical Engineering Maharashtra Wardha442001 India Faculty of Engineering and Technology Department of Artificial Intelligence & Data Science Maharashtra Wardha442001 India

ISBN: (纸本)9798350376425

The design of wireless mobile devices of the next generation 5G promises to address the demands of complex IOT designs in terms of connectivity technologies. This The study illuminates the architecture, benefits, and needs that5G can satisfy. drawbacks of the 5G network. Numerous sites throughout the world have conducted extensive analyses of IOT devices with 5G capabilities and research on this kind of network. A new era of communication has begun with the introduction of 5G technology, which promises unheard of velocity, low latency, and enormous capacity. The significant effects of 5G on the operation and efficiency of connected Internet of Things (IoT) gadgets are examined in this research. IoT devices stand to gain from improved communication capabilities as 5G networks proliferate, opening the door for creative applications in a variety of industries. The first section of the article gives a summary of the main characteristics of 5G technology, highlighting how it has the potential to completely change how Internet of Things devices interact and communicate. Real-time data transfer is made possible by 5G networks far lower latency and higher capacity, which open up possibilities for faster and smooth interactions between IoT *** report also explores how 5G may affect how much electricity Internet of Things devices use. 5G has the ability to solve a long-standing issue in the IoT ecosystem by extending the life of the batteries of IoT devices with the adoption of cost-effective communication protocols and increased network efficiency. A solution that can efficiently handle enormous volumes of information being transferred at very high capacity is required as the Internet of Things gains popularity One of the main demands or goals that need to be reached in the near future, or the next generation of IOT devices, is more capacity, a faster data transfer speed and less delay. © 2024 IEEE.

关键词： 5G mobile communication systems

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From 5G to 6G: The Role of AI, Machine Learning, and Deep Learning in Wireless systems 4

From 5G to 6G: The Role of AI, Machine Learning, and Deep Le...

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4th International Conference on Sentiment Analysis and Deep Learning, ICSADL 2025

作者： Gote, Pradnyawant M. Kumar, Praveen Verma, Prateek Yesankar, Prajyot Pawar, Adesh Saratkar, Saniya Faculty of Engineering and Technology Department of Computer Science & Design Maharashtra Wardha442001 India Faculty of Engineering and Technology Department of Computer Science & Medical Engineering Maharashtra Wardha442001 India Faculty of Engineering and Technology Department of Artificial Intelligence & Machine Learning Maharashtra Wardha442001 India Faculty of Engineering and Technology Department of Artificial Intelligence & Data Science Maharashtra Wardha442001 India

ISBN: (纸本)9798331523923

The swift progression of wireless communication technologies-specifically from 5G to 6G is an approach that could be the most significant revolutionary leap towards changing connectivity and data transmission forever. Additionally, algorithms of machine learning (ML) and deep learning (DL) in 5G and 6G can offer promising advancements toward predictive maintenance, dynamic spectrum management, and enhanced security. The review of the potentially transformative nature of these technologies underlines the need for future directions of research efforts called for in circumventing challenges towards making full capability exploitation of 6G possible. © 2025 IEEE.

关键词： Adversarial machine learning

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Enhanced Neutrosophic Set and Machine Learning Approach for Kidney Disease Prediction

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Neutrosophic Sets and systems 2025年 80卷 465-477页

作者： Al-Doori, Humam M. Alkellezli, Tareef S. Abdelhafeez, Ahmed Eassaa, Mohamed Sawah, Mohamed S. El-Douh, Ahmed A. Cybersecurity Sciences Department College of Science Ashur University Baghdad Iraq Cybersecurity Engineering Department College of Engineering Ashur University Baghdad Iraq Computer Science Department Faculty of Information System and Computer Science October 6 University Giza12585 Egypt Applied Science Research Center Applied Science Private University Amman Jordan Department of Computer Science Faculty of Information Technology Ajloun National University P.O.43 Ajloun26810 Jordan Cybersecurity Technology Engineering Department College of Engineering Technology Ashur University Baghdad Iraq

Kidney disease (KD) is a gradually increasing global health concern. It is a chronic illness linked to higher rates of morbidity and mortality, a higher risk of cardiovascular disease and numerous other illnesses, and expensive medical expenses. The machine learning (ML) models are applied for KD prediction with higher accuracy and precision. The KD dataset has uncertainty and vague information, so, we used the neutrosophic set (NS) to deal with vague and uncertainty information in the KD dataset. The KD dataset is converted into the N-KD dataset with three membership functions: truth, indeterminacy, and falsity. Three ML models are used in this study such as logistic regression (LR), support vector machine (SVM), and k-nearest neighbor (KNN). These ML models are applied to the N-KD dataset. The results show the LR has higher accuracy and precision on the N-KD dataset than the original KD dataset. © 2025, University of New Mexico. All rights reserved.

关键词： Logistic regression

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DETAILED GRID MAPPING FOR THE COLD AND HOT WEATHER CONCRETING PERIODS BASED ON THE MESH CLIMATOLOGICAL NORMALS 2020

Journal of Structural and Construction Engineering

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Journal of Structural and Construction engineering 2024年第824期89卷 1082-1091页

作者： Takasugi, Fumiya Nishiwaki, Tomoya Taniguchi, Madoka Fukase, Takayuki Hama, Yukio Ito, Korekiyo Koyama, Tomoyuki Department of Architecture and Building Science Graduate School of Engineering Tohoku University Japan College of Design and Manufacturing Technology Graduate School Division of Engineering Muroran Institute of Technology Japan Department of Architecture Faculty of Engineering Hokkaido University of Science Japan Department of Human Information Engineering School of Humanities and Science Tokai University Japan Department of Architecture and Urban Design Graduate School of Human-Environment Studies Kyushu University Japan

The quality of concrete is significantly influenced by the temperature environment before and after casting, requiring temperature-based countermeasures. The guidelines indicate the countermeasure-needed periods for cold and hot weather concreting but are limited to selected reference locations, not always matching individual construction sites. This paper introduces detailed maps created using data from the Mesh Climatological Normals 2020 to depict the countermeasure-needed period of each concreting. The system, which integrated these maps with an internet-based mapping, application was developed to enable rational decisions of the countermeasures-needed periods at individual construction sites from the construction planning stage. © 2024 Architectural Institute of Japan. All rights reserved.

关键词： Mapping

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Molecular levers enable anomalously enhanced strength and toughness of cellulose nanocrystal at cryogenic temperature

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Nano Research 2023年第5期16卷 8036-8041页

作者： YuanZhen Hou Jun Xia ZeZhou He YinBo Zhu HengAn Wu CAS Key Laboratory of Mechanical Behavior and Design of Materials Department of Modern MechanicsCAS Center for Excellence in Complex System MechanicsUniversity of Science and Technology of ChinaHefei 230027China Faculty of Civil Engineering and Mechanics Jiangsu UniversityZhenjiang 212013China

The quest for widespread applications especially in extreme environments accentuates the necessity to design materials with robust mechanical and thermodynamic *** all existing materials yield temperature-variant mechanical properties,essentially determined by their different atomic bonding *** general,weak non-covalent interactions are considered to diminish the structural anti-destabilization of covalent crystals despite the toughening ***,starting from multiscale theoretical modeling,we herein reveal an anomalous stabilizing effect in cellulose nanocrystals(CNCs)by the cooperation between the non-covalent hydrogen bonds and covalent glucosidic skeleton,namely molecular levers(MLs).It is surprising to find that the hydrogen bonds in MLs behave like covalent bindings under cryogenic conditions,which provide anomalously enhanced strength and toughness for *** analyses demonstrate that the unique dynamical mechanical behaviors from ambient to deep cryogenic temperatures are synergetic results of the intrinsic temperature dependence veiled in MLs and the overall thermo-induced CNC destabilization/*** the consequence,the variation trend of mechanical strength exhibits a bilinear temperature dependence with~77 K as the turning *** underlying investigations not only establish the bottom–up interrelations from the hydrogen bonding thermodynamics to the crystal-scale mechanical properties,but also facilitate the potential application of cellulose-based materials at extremely low temperatures such as those in outer space.

关键词： cellulose nanocrystal molecular lever thermodynamic stability thermo-mechanical behavior cryogenic temperature

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Advancing Bankruptcy Forecasting With Hybrid Machine Learning Techniques: Insights From an Unbalanced Polish Dataset

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IEEE Access 2024年 12卷 9369-9381页

作者： Ainan, Ummey Hany Por, Lip Yee Chen, Yen-Lin Yang, Jing Ku, Chin Soon Universiti Malaya Faculty of Computer Science and Information Technology Department of Computer System and Technology Kuala Lumpur50603 Malaysia National Taipei University of Technology Department of Computer Science and Information Engineering Taipei106344 Taiwan Universiti Tunku Abdul Rahman Department of Computer Science Kampar31900 Malaysia

The challenge of bankruptcy prediction, critical for averting financial sector losses, is amplified by the prevalence of imbalanced datasets, which often skew prediction models. Addressing this, our study introduces the innovative hybrid model XGBoost+ANN, designed to leverage the strengths of both ensemble learning and artificial neural networks. This model integrates a comprehensive set of features with parameters optimized through genetic algorithms, eschewing traditional feature selection approaches. Our research focuses on an unbalanced dataset of Polish companies and reveals that the XGBoost+ANN model, in particular, exhibits outstanding performance. Optimized using genetic algorithms and without feature selection, this model achieved the highest AUC (0.958), sensitivity (0.752), and accuracy (0.983) scores, surpassing other models in our study. This remarkable outperformance, along with the robust results, marks a substantial advancement in the field of bankruptcy prediction. It underscores the efficacy of our approach in addressing the persistent challenge of data imbalance, offering a more reliable and accurate solution for financial risk assessment. © 2013 IEEE.

关键词： Feature extraction

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Development of an Effective Chatter Control system for an End Mill Spindle Tool system

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Journal of The Institution of Engineers (India): Series C 2024年第5期105卷 1065-1081页

作者： Raju, C. Trivikrama Hussain, S. Jakeer Yedukondalu, G. Galal, Ahmed M. Department of Mechanical Engineering Koneru Lakshmaiah Education Foundation Vaddeswaram Guntur India Department of Mechanical Engineering Mother Teresa Institute of Science and Technology Sathupally India Production Engineering and Mechanical Design Department Faculty of Engineering Mansoura University Mansoura Egypt

Excessive chatter during the machining process reduces productivity and increases manufacturing costs. This disruption slows material removal, thereby decreasing operational efficiency and output. To increase the efficiency in cutting operations, dynamic stability, active structural control methods are the best way to get effective results. In the present paper integrated spindle tool systems are modelled using finite element methods by using the Timoshenko beam theory with shear and rotational deformation effects. To achieve the maximized average stable depth of cut for an end milling process while simultaneously minimizing chatter vibration levels, both semi-active and active control strategies have been investigated. Machining experiments performed on Al6061-alloy specimens and provide an empirical confirmation of the stability boundaries. Vibration levels and optical microscope images are considered, to identify chatter marks under various machining conditions, which helps to assure cutting process stability. A proportional derivative controller method is applied at the interface of the spindle tool to control the cutting forces at different cutting conditions. Stability lobe diagrams are plotted with these derived conditions and observed at an incremental level in the axial depths of cutting. The methodology presented in this paper improves the stability in machining of alloy materials with the reduction in the tool tip vibrations. © The Institution of Engineers (India) 2024.

关键词： Milling (machining)

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A systematic Literature Review on the Security Attacks and Countermeasures Used in Graphical Passwords

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IEEE Access 2024年 12卷 53408-53423页

作者： Por, Lip Yee Ng, Ian Ouii Chen, Yen-Lin Yang, Jing Ku, Chin Soon Universiti Malaya Faculty of Computer Science and Information Technology Department of Computer System and Technology Kuala Lumpur50603 Malaysia National Taipei University of Technology Department of Computer Science and Information Engineering Taipei106344 Taiwan Universiti Tunku Abdul Rahman Department of Computer Science Kampar31900 Malaysia

This systematic literature review delves into the dynamic realm of graphical passwords, focusing on the myriad security attacks they face and the diverse countermeasures devised to mitigate these threats. The core objective of this paper is to identify existing security threats to graphical password schemes and the corresponding countermeasures developed to mitigate these attacks. The study process begins by identifying the usable databases and search engines to identify all the relevant resources. The inclusion and exclusion criteria were carefully selected to prioritize the study, focusing mostly on attacks and countermeasures related to graphical password schemes between 2009 and 2023. After thorough identification and selection progress, 59 studies met all the criteria. Among these studies, 47 mentioned shoulder surfing as a threat to graphical password schemes, while 20 discussed brute force attacks. Additionally, there were 21 papers on dictionary attacks, 13 on smudge attacks, spyware attacks, and social engineering, and 19 that discussed guessing attacks as threats to graphical password schemes. Furthermore, the papers identified several other attacks, including frequency of occurrence analysis attacks, video recording, eavesdropping, computer vision, sonar, and image gallery attacks, with the corresponding numbers of papers being 9, 17, 5, 2, 2, and 1, respectively. The results also highlight the countermeasures proposed in the study papers to mitigate the aforementioned attacks. Among the various countermeasures identified, most revolve around randomization, obfuscation, and password space complexity as the most commonly used techniques for enhancing the security of graphical password schemes. © 2013 IEEE.

关键词： Authentication

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A Type-1 Fuzzy Logic Framework for Early Risk Assessment of Gestational Diabetes Mellitus Using Clinical Risk Factors 2

A Type-1 Fuzzy Logic Framework for Early Risk Assessment of ...

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2nd International Conference on Machine Learning and Autonomous systems, ICMLAS 2025

作者： Suman, Saurabh Pacharaney, Utkarsha Gote, Pradnyawant M. Faculty of Engineering and - Technology Department of Computer Science & Design Maharashtra Wardha442001 India Faculty of Engineering and Technology Department of Artificial Intelligence & Machine Learning Maharashtra Wardha442001 India

ISBN: (纸本)9798331505745

Gestational Diabetes Mellitus (GDM) is a condition that can put at risk both mother and fetus but early and proper risk assessment need to be carried out for effective management. This paper discloses a Mamdani-kind Fuzzy Inference system to evaluate GDM risk dependent on clinical parameters like age, parity, glucose levels, body mass index (BMI), and insulin levels. The system can simulate all the numerous risk factors in a more gentle way by the utilization of the triangular membership function that converts accurate clinical data into a fuzzy format. A clear rule base, got from the knowledge maps in the clinical field, is put together from the input data to determining the GDM risk levels. This is neither then defuzzied via the centroid method to generate a determinable score. Results show that this system can be used along with the experts, thus yielding the same results as them, meanwhile, it is capable of providing an intelligible output. It lends further credence to the role of fuzzy logic in uncertainties in medical data and their potential by decision support systems in clinical context. While reasonably beneficial results from the system are reported, the static nature of the membership functions implies, for the future, adaptability in methodologies for relative accuracy. This study still emphasizes that fuzzy logic finds application in settings of clinical delineation, which are distinctly more complex for their intended usefulness for conditions such as GDM here. © 2025 IEEE.

关键词： Risk assessment

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Building a Smart Virtual Chatbot Assistant with HTML, CSS, and JavaScript 2

Building a Smart Virtual Chatbot Assistant with HTML, CSS, a...

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2nd International Conference on Machine Learning and Autonomous systems, ICMLAS 2025

作者： Khonde, Tanvi Patle, Sneha Talvekar, Shreya Hajbe, Jahnavi Faculty of Engineering and Technology Department of Computer Science and Design Maharashtra Wardha442201 India

ISBN: (纸本)9798331505745

A virtual chatbot assistant is an interactive application designed to simulate human-like communication and respond to user inquiries promptly. It focuses on building an interesting user interface and putting simple conversational logic into practice;this article presents the development of a chatbot using HTML, CSS, and JavaScript. Developers can make these fundamental web technologies useful in the creation of accessible and user-friendly chatbot systems for any kind of application. The literature indicates that chatbot technology is under development, which includes the merging of AI and natural language processing to enhance the capabilities of conversations. This handbook is an invaluable tool in making useful chatbots by linking the needs of the users with contemporary online technology. © 2025 IEEE.

关键词： Chatbots

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