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23rd DIDFYZ Conference on New Approaches in Physics Education for Generation Z

作者： Susac, A. Sajka, M. Rosiek, R. Šipuš, Ž Milin Department of Applied Physics Faculty of Electrical Engineering and Computing University of Zagreb Unska 3 Zagreb10 000 Croatia Department of Mathematics Faculty of Exact and Natural Sciences University of the National Education Commission in Krakow ul. Podchorazych 2 Krakow30-084 Poland Institute of Technical Sciences Faculty of Exact and Natural Sciences University of the National Education Commission in Krakow ul. Podchorazych 2 Krakow30-084 Poland Department of Mathematics Faculty of Science University of Zagreb Horvatovac 102a Zagreb10 000 Croatia

The study investigates university students' difficulties in interpreting graphs through the analysis of their responses to the modified PISA racing car problem. The impact of adding a distractor that is appealing to students and supplementary questions to enhance students' graph understanding is explored. Eye-tracking technology was used to capture participants' visual attention during the task. The findings highlight the challenges of treating graphs as pictures and the benefits of incorporating additional questions to improve students' comprehension. The study emphasizes the need for instructional strategies that address intuitive reasoning and promote reflective thinking in graph interpretation. © Published under licence by IOP Publishing Ltd.

关键词： Students

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Performance Analysis of Quaternion vs Euler-based Approaches in Reduced INS/GNSS Fusion Techniques

Performance Analysis of Quaternion vs Euler-based Approaches...

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2023 International Telecommunications Conference, ITC-Egypt 2023

作者： Tarek, Maher Zahran, Shady Radi, Ahmed Nafea, Sherif F Oda, Eyad S. Hafez, Alaa El-Din Sayed Technical Researches and Development Center Control and Navigation Departement Cairo Egypt Arab Academy for Science Technology and Maritime Transport College of Computing and Information Technology Cairo Egypt Technical Researches Center Cairo Egypt Suez Canal University Electrical Engineering Department Cairo Egypt Alexandria University Electrical Engineering Affiliate Instructor Cairo Egypt

ISBN: (纸本)9798350326062

Unmanned vehicle navigation using various combination of sensors in different fields, civilian or military, has always known to be a challenging and nontrivial task. Bayesian filter algorithms are usually being used for combining and optimally processing measurements provided by such sensors, considering the available knowledge such as the uncertainty in measurements. Since the performance of any navigation system mainly depends on the efficiency of the chosen filter algorithm associated with the utilized sensors' quality, the choice of suitable filtering approach (according to the demand application) can be considered as a critical and essential designing point. In this paper, the performance of two different attitudes representation filtering approaches (Quaternion and Euler angles-based) is investigated, when applied in Multiplicative Extended Kalman Filter (MEKF) design. The overall performance and accuracy of both approaches were analyzed and compared during various GNSS signal outages for a self-driving cars application in straight and curved trajectory paths. Multiple in-filed experiments were conducted using a special setup that includes a MEMS-based SPATIAL Advanced Navigation INS/GNSS system where the output of both approaches was compared to the ground truth of a utilized reference navigation system. The comparison includes 1) Position, Velocity and Attitude (PVA) estimation accuracy, 2) processing time and computational complexity. Results concluded that each approach has its own merits in demerits where the Quaternion-based approach outperforms the Euler one in terms of PVA navigation solution estimation accuracy. On the other hand, a faster calculation for the Euler-based approach associated with lower computational complexity was significantly noticeable. © 2023 IEEE.

关键词： Inertial navigation systems

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Cloud-Powered Virtual Doctor Robots for Enhancing Elderly Care and Chronic Disease Management with Recurrent Neural Networks 3

Cloud-Powered Virtual Doctor Robots for Enhancing Elderly Ca...

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3rd International Conference on Electrical, Electronics, Information and Communication Technologies, ICEEICT 2024

作者： Ramesh, S. Mohankumar, N. Kovarasan, Rajesh Kambattan Selvamanikandan, R. Yuvaraj, S. Sujatha, S. Srm Institute of Science and Technology School of Computing College of Engineering and Technology Department of Computing Technologies Chennai Tamil Nadu Kattankulathur India Maharashtra Nagpur India Vel Tech Rangarajan Dr.Sagunthala R&d Institute of Science and Technology Department of Computer Science and Engineering Tamil Nadu Chennai India Care College of Engineering Department of Electrical and Electronics Engineering Tamil Nadu Trichy India Faculty of Engineering and Technology Department of Electronics and Communication Engineering Tamil Nadu India Saveetha School of Engineering Saveetha Institute of Medical and Technical Sciences Saveetha University Department of Biomedical Engineering Tamil Nadu Chennai India

ISBN: (纸本)9798350369083

This research introduces cloud-powered virtual doctor robots to improve elderly care and chronic illness management. This system uses recurrent neural networks (RNNs) to give personalized medical care to elderly chronic disease patients. These virtual doctor robots may integrate with cloud computing infrastructure to access huge medical databases for real-time patient data analysis and individualized treatment and care suggestions. Healthcare technology has advanced by using RNNs to learn from patient data, adapt to changing health situations, and predict prospective health issues. RNNs can interpret sequential data, thus virtual doctor robots may identify trends in patient health parameters, forecast illness development, and suggest risk mitigation strategies. Cloud-powered virtual doctor robots provide a scalable solution to conventional healthcare systems rising issues. These robots can work effectively in resource-constrained areas by offloading computational chores to distant servers, providing continuous medical expertise and lowering healthcare staff reliance. This technique might improve aged care and reduce load on overworked healthcare systems. Using proactive monitoring, timely intervention, and personalized guidance, virtual doctor robots with RNNs can improve health outcomes, empower patients to manage chronic conditions, and create a more sustainable healthcare model. © 2024 IEEE.

关键词： Medical robotics

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Design and Implementation of Telemedicine System Using Light Fidelity and PIC16F877A Microcontroller 14

Design and Implementation of Telemedicine System Using Light...

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14th International Conference on Information science and Technology, ICIST 2024

作者： Ezilarasan, M.R. Leung, Man-Fai Dai, Xiangguang Vel Tech Rangarajan Dr. Sagunthala R and D Instituteof Science and Technology Department of Electronics and Communication Engineering Chennai India School of Computing and Information Science Anglia Ruskin University Faculty of Science and Engineering Cambridge United Kingdom Information Processing and Control of Chongqing Municipal Institutions of Higher Education Chongqing Three Gorges University Key Laboratory of Intelligent Chongqing Wanzhou404100 China

ISBN: (纸本)9798350353334

Medical Body Area Networks (MBANs) increasingly utilize wireless communication technologies to enhance the freedom and convenience for patients and caregivers. Currently, radio frequency (RF) is the prevalent medium in healthcare applications;however, the potential for electromagnetic interference with precision medical equipment remains a concern. This study introduces a novel design and implementation of a medical healthcare information system using the newly developed Wireless Visible Light Communication (VLC) technology, also known as Light Fidelity (Li-Fi). Visible Light Emitting Diodes (LEDs), expected to soon surpass traditional incandescent and fluorescent bulbs as the primary light source due to their energy efficiency, facilitate this technology. In this research, patient health is monitored using sensors, with results displayed on an LCD. An LED lightbulb transmits the data as light signals, which are captured by a photo-detector at the receiver's end. This setup not only displays the output on an LCD but also alerts caregivers through an auditory signal, beeping every 15 seconds for respiration and every 30 seconds for heart rate monitoring. Moreover, these lighting fixtures serve dual functions: illumination and wireless data transmission, using the rapid switching capability of LEDs. This prototype VLC-based system offers a promising alternative for data services and monitoring in hospital areas where RF use is restricted. © 2024 IEEE.

关键词： Liquid crystal displays

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Adaptive AI-Based Personalized Learning for Accelerated Vocabulary and Syntax Mastery in Young English Learners

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International Journal of Advanced Computer science and Applications 2025年第4期16卷 678-687页

作者： Aravind, Angalakuduru Durairaj, M. Chitkara, Preeti Baker El-Ebiary, Yousef A. Muniyandy, Elangovan Ushasree, Linginedi Ammar, Mohamed Ben Kodad Telangana 508206 India Dept.of English Panimalar Engineering College Poonamallee Chennai600123 India Head PR & International Relations Department of Applied Sciences KIET Group of Institutions Delhi-NCR Ghaziabad India Faculty of Informatics and Computing UniSZA University Malaysia Department of Biosciences-Saveetha School of Engineering Saveetha Institute of Medical and Technical Sciences Chennai602 105 India Applied Science Research Center Applied Science Private University Amman Jordan Department of Computer Science and Engineering Koneru Lakshmaiah Education Foundation Vaddeswaram Andhra Pradesh Guntur Dist. 522302 India Center for Scientific Research and Entrepreneurship Northern Border University Arar73213 Saudi Arabia

Language acquisition is an integral part of early schooling, but young English language learners struggle to learn vocabulary and syntax since they are not provided with specialized instruction. Conventional teaching may vary according to different learning speeds and it leads to unbalanced levels of proficiency among students and possibly leading to disengagement among slow learners. The present computer-assisted learning aids provide practice interactively but without real-time adaptation and personalized feedback, limiting their capacity to address learners’ unique problems. To overcome these constraints, this study suggests an Artificial Intelligence based personalized learning system that supports vocabulary and syntax learning via adaptive learning models, NLP-based chatbots and gamified interactive lessons. The system dynamically adapts content according to students’ most recent performance in real time to enable a personalized learning experience, which results in efficient Learning. The research has experimental study design, and two groups are considered, an AI-supported learning group and a traditional learning group. Pre-test and post-test design measures the effects of the system on vocabulary recall and syntax correctness. Other learner engagement rates like survey results and qualitative feedback inform learner experience and learning efficacy. Initial results indicate that learners working with the Artificial Intelligence powered learning system gained 25percent in recalling vocabulary and 30percent in syntax accuracy over the control group. Further, learner engagement rates are elevated because of real-time feedback and gamification components. These results emphasize the promise of AI-based personalized learning to boost language acquisition and lay the basis for further effective innovations in adaptive education technologies. © (2025), (science and Information Organization). All rights reserved.

关键词： Students

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The Terms Estimation of S Robotics using MTRS as well as FEM 4

The Terms Estimation of S Robotics using MTRS as well as FEM

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4th IEEE International Conference on Advance computing and Innovative Technologies in Engineering, ICACITE 2024

作者： Gopal, R. Mudhafar, Mustafa Hashem, Amjad Ramalingam, Venkadeshan Bordoloi, Dibyahash Khan, Muhammad Numan Ali Adnan, Myasar Mundher Abdulhussain, Zahraa N. University of Buraimi Information and Communication Engineering College of Engineering Oman University of Kerbala Faculty of Medical Applied Sciences Department of Medical Physics Karbala56001 Iraq Al-kunooze University College Computer Engineer Department Basra Iraq University of Technology and Applied Sciences Network Computing College of Computing and Information Sciences Shinas Oman Dept of Cse Graphic Era Hill University Uttarakhand Dehradun India Graphic Era Deemed to Be University Uttarakhand Dehradun India University of Technology and Applied Sciences Network Computing College of Computing and Information Sciences Shinas Oman The Islamic University College of Technical Engineering Department of Computers Techniques Engineering Najaf Iraq National University of Science and Technology College of Technical Engineering Dhi Qar64001 Iraq

ISBN: (纸本)9798350360165

This look at addresses the critical project of reaching dependable and precise proprioception in soft robots, it really is essential for his or her effective deployment in complicated environments. By integrating multi-tap resistive sensors in the robot's form, our technique lets in for the distinct sensing of nearby deformations at various factors throughout the robotics' frame, moving beyond traditional techniques that anticipate steady curvature. We beautify the decision of these deformations and couple the sensory facts with a strong finite detail technique (FEM) model. This included framework allows the correct estimation of the smooth robot's form and the significance of outside forces applied to it, attaining a mean relative inaccuracy of about 4%. Additionally, our technique proves its software program in tender manipulation structures, in which it achieves thirteen% relative mistakes in external force estimation inside diverse zero to five N. The approach gives a promising direction for enhancing robotic interactions in sensitive and dynamic responsibilities, providing massive enhancements in robotic proprioception without reliance on outdoor monitoring generation. © 2024 IEEE.

关键词： Microrobots

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Integrating Cloud computing and Naive Bayes for Precision Detection and Classification of Sheet and Rill Erosion in Agriculture 2

Integrating Cloud Computing and Naive Bayes for Precision De...

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2nd International Conference on Self Sustainable Artificial Intelligence Systems, ICSSAS 2024

作者： Deshpande, Ashish Govindrao Raman, Ramakrishnan Vekariya, Vipul Mishra, Nilamadhab Arumugam, Sundaram Srinivasan, C. Pune Maharashtra Pune India Symbiosis Institute of Business Management Pune Maharashtra Pune India Parul Institute of Engineering and Technology Parul University Faculty of Engineering and Technology Gujarat Vadodara India Vit Bhopal University School of Computing Science and Engineering Madhya Pradesh India Navajo Technical University Department of Electrical Engineering Crown pointNM United States Saveetha Institute of Medical and Technical Sciences Saveetha University Saveetha School of Engineering Department of Computer Science and Engineering Tamil Nadu Chennai India

ISBN: (纸本)9798350368413

Sustainable agriculture has significant challenges from sheet and rill erosion for effective techniques. A new way to accurately identify and classifier sheet and rill erosion in agricultural landscapes with the combination of cloud computing and Naïve Bayes. To differentiate between these erosion patterns work proposes a technique that uses ground truth data and high-resolution satellite images. The technique gets results by using the Naïve Bayes algorithm, which is famous for being simple and successful in classification problems. More efficient and accurate and advanced methods by conducting comprehensive experiments and validations. This technology takes use of the scalability and accessibility of cloud computing to conduct erosion risk assessments in real-time, providing agricultural stakeholders with valuable information to enhance soil conservation initiatives. It highlights the revolutionary power of new technology to improve agricultural land management methods and address environmental issues. Sustainable agricultural practices mitigate the adverse implications of soil erosion by offering exact detection and classification of erosion events, which lead to better informed decision-making. © 2024 IEEE.

关键词： Environmental Monitoring Erosion Risk Assessment Ground Truth Data Land Management Satellite Imagery Soil Conservation Sustainable Agriculture

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Preserving culinary heritage and promoting sustainability: an overview of botanical nutrition regarding herbs and spices used on the territory of today’s Cameroon

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SN Social sciences 2024年第7期4卷 1-48页

作者： Dongmo, Fabrice Fabien Dongho Zangueu, Calvin Bogning Asongni, William Djeukeu Tsopgni, Wilfried Dongmo Tekapi Tchoutezou, Guy Herman Zanguim Dongmo, Jasmine Nguimfack Tchuenbou-Magaia, Fideline Laure Etame, Rebecca Madeleine Ebelle Sameza, Modeste Lambert Gouado, Inocent Ngane, Rosalie Anne Ngono Department of Biochemistry Faculty of Science University of Douala P.O. Box 24157 Douala Cameroon Department of Animal Biology and Physiology Faculty of Sciences University of Douala P.O. Box 24157 Douala Cameroon Department of Home Economic Advanced Teacher’s Training College for Technical Education University of Douala P.O. Box 1872 Douala Cameroon Department of Chemistry Faculty of Sciences University of Douala P.O. Box 24157 Douala Cameroon Department of Forestery Faculty of Agronomy and Agricultural Sciences University of Dschang P.O. Box 222 Dschang Cameroon School of Engineering Computing and Mathematical Sciences Faculty of Science and Engineering University of Wolverhampton Wulfruna Street West Midlands Wolverhampton WV1 1LY United Kingdom

Herbs and spices are not merely condiments;they are the essence of our cultural heritage, infusing our cuisine with flavors that do more than tantalize the palate, they offer a spectrum of health benefits. This study meticulously reviews 59 botanicals, 44 spices and 15 herbs, cherished in Cameroon, presenting a treasure trove of ethnobotanical and ethnonutritional wisdom. Fruits emerge as the most favored part of plants used in spices. Herbs often hail from Asia and Europe, and spices from the lush tropics and subtropics of Africa. This review casts a spotlight on the critical role these plants play in culinary artistry and health promotion, thanks to their rich array of bioactive compounds. It navigates through the complexities of sustainable management and conservation, advocating for the longevity of these botanicals for the enrichment of future generations. The paper calls for rigorous scientific research to substantiate the health claims associated with these natural wonders and promotes sustainable harvesting and market expansion. It underscores the necessity of educating the public about the value of these plants. In conclusion, the paper urges continued research into the scientific validation of health benefits, the adoption of sustainable practices, the exploration of value-added products, market development strategies, and heightened public awareness. This research aims to lay a robust foundation for future endeavors, aspiring to holistically manage health and well-being through the sustainable harnessing of these invaluable natural resources. © The Author(s), under exclusive licence to Springer Nature Switzerland AG 2024.

关键词： Cameroon Culinary traditions Ethnobotany Herbs and spices Sustainable practices

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Hybrid Grey Wolf and Dipper Throated Optimization in Network Intrusion Detection Systems

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Computers, Materials & Continua 2023年第2期74卷 2695-2709页

作者： Reem Alkanhel Doaa Sami Khafaga El-Sayed M.El-kenawy Abdelaziz A.Abdelhamid Abdelhameed Ibrahim Rashid Amin Mostafa Abotaleb B.M.El-den Department of Information Technology College of Computer and Information SciencesPrincess Nourah bint Abdulrahman UniversityP.O.Box 84428Riyadh11671Saudi Arabia Department of Computer Sciences College of Computer and Information SciencesPrincess Nourah bint Abdulrahman UniversityP.O.Box 84428Riyadh11671Saudi Arabia Department of Communications and Electronics Delta Higher Institute of Engineering and TechnologyMansoura35111Egypt Department of Computer Science Faculty of Computer and Information SciencesAin Shams UniversityCairo11566Egypt Department of Computer Science College of Computing and Information TechnologyShaqra University11961Saudi Arabia Computer Engineering and Control Systems Department Faculty of EngineeringMansoura UniversityMansoura35516Egypt Department of Computer Science University of Engineering and TechnologyTaxilaPakistan Department of System Programming South Ural State UniversityChelyabinsk454080Russia

The Internet of Things(IoT)is a modern approach that enables connection with a wide variety of devices *** to the resource constraints and open nature of IoT nodes,the routing protocol for low power and lossy(RPL)networks may be vulnerable to several routing ***’s why a network intrusion detection system(NIDS)is needed to guard against routing assaults on RPL-based IoT *** imbalance between the false and valid attacks in the training set degrades the performance of machine learning employed to detect network ***,we propose in this paper a novel approach to balance the dataset classes based on metaheuristic optimization applied to locality-sensitive hashing and synthetic minority oversampling technique(LSH-SMOTE).The proposed optimization approach is based on a new hybrid between the grey wolf and dipper throated optimization *** prove the effectiveness of the proposed approach,a set of experiments were conducted to evaluate the performance of NIDS for three cases,namely,detection without dataset balancing,detection with SMOTE balancing,and detection with the proposed optimized LSHSOMTE *** results showed that the proposed approach outperforms the other approaches and could boost the detection *** addition,a statistical analysis is performed to study the significance and stability of the proposed *** conducted experiments include seven different types of attack cases in the RPL-NIDS17 *** on the 2696 CMC,2023,vol.74,no.2 proposed approach,the achieved accuracy is(98.1%),sensitivity is(97.8%),and specificity is(98.8%).

关键词： Metaheuristics grey wolf optimization dipper throated optimization dataset balancing locality sensitive hashing SMOTE

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Cloud-Powered Neural Networks for Sustainable Fishing Practices and Stock Management System 4

Cloud-Powered Neural Networks for Sustainable Fishing Practi...

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4th International Conference on Sustainable Expert Systems, ICSES 2024

作者： Suresh, M. Xavier Prathik, A. Arun, V. Venugopal, R. Ganeshbabu, T.R. Muthulekshmi, M. School of Advanced Sciences and Languages Vit Bhopal University Department of Physics Madhya Pradesh Bhopal India Vel Tech Rangarajan Dr.Sagunthala R&d Institute of Science and Technology Department of Computer Science and Engineering Tamil Nadu Chennai India School of Computing Srm Institute of Science and Technology Faculty of Engineering and Technology Department of Computing Technologies Kattankulathur Tamil Nadu Chennai India Department of Mathematics Tamil Nadu Salem India Department of Electronics and Communication Tamil Nadu Namakkal India Saveetha School of Engineering Saveetha Institute of Medical and Technical Sciences Saveetha University Department of Biomedical Engineering Tamil Nadu Chennai India

ISBN: (纸本)9798331540364

Sustainable fishing methods and efficient stock management are crucial considering growing environmental concerns;fishing practices and effective stock management are imperative. This research presents a novel approach that uses neural networks (NN) hosted in the cloud to transform sustainable fishing and stock management. This method trains NN to make predictions by combining several data sources, such as satellite images, weather patterns, and catch records. These models can reliably predict fish stocks' dynamics, giving stakeholders the information needed to make informed decisions. Crucial for real-time processing and storage of massive information is the scalability and flexibility offered by cloud infrastructure. This framework provides the appropriate usage of resources while simultaneously optimizing fishing tactics, which helps protect marine ecosystems. It demonstrates that method promotes sustainable fishing via thorough case studies and simulations. It provides a flexible and scalable solution to the problems confronting marine biodiversity and the fishing industry by combining advanced technology with ecological principles. To ensure a more egalitarian and sustainable future for fisheries management on a global scale, method is a giant leap forward in balancing commercial interests with environmental protection. Integrating data, ensuring sensors are accurate, managing huge datasets, managing regulatory compliance, and encouraging stakeholders to work together for sustainable practices are all challenges. © 2024 IEEE.

关键词： Fisheries

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