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A Tolerant and Energy Optimization Approach for Internet of Things to Enhance the QoS Using Adaptive Blended Marine Predators Algorithm

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computers, Materials & Continua 2025年第5期83卷 2449-2479页

作者： Vijaya Krishna Akula Tan Kuan Tak Pravin Ramdas Kshirsagar Shrikant Vijayrao Sonekar Gopichand Ginnela Department of Information Technology G.Narayanamma Institute of Technology and Science for WomenHyderabad500104India Engineering Cluster Singapore Institute of Technology10 Dover DriveSingapore138683Singapore Department of Electronics and Telecommunication Engineering J.D.College of Engineering&ManagementNagpur441501India Department of Computer Science and Engineering J.D.College of Engineering&ManagementNagpur441501India School of Computer Science and Engineering Vellore Institute of TechnologyVellore632014TamilnaduIndia

The rapid expansion of Internet of Things(IoT)networks has introduced challenges in network management,primarily in maintaining energy efficiency and robust connectivity across an increasing array of *** paper introduces the Adaptive Blended Marine Predators Algorithm(AB-MPA),a novel optimization technique designed to enhance Quality of Service(QoS)in IoT systems by dynamically optimizing network configurations for improved energy efficiency and *** results represent significant improvements in network performance metrics such as energy consumption,throughput,and operational stability,indicating that AB-MPA effectively addresses the pressing needs ofmodern IoT *** are initiated with 100 J of stored energy,and energy is consumed at 0.01 J per square meter in each node to emphasize energy-efficient *** algorithm also provides sufficient network lifetime extension to a resourceful 7000 cycles for up to 200 nodes with a maximum Packet Delivery Ratio(PDR)of 99% and a robust network throughput of up to 1800 kbps in more compact node *** study proposes a viable solution to a critical problem and opens avenues for further research into scalable network management for diverse applications.

关键词： Internet of things trust energy marine predators algorithm(MPA) differential evolution(DE) nodes throughput lifetime

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Modeling the Percentage of NEET in Indonesia with Spatial Cauchy Regression through the Bayesian Analysis Approach

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IAENG International Journal of Applied Mathematics 2024年第7期54卷 1288-1295页

作者： Rantini, Dwi Fakhruzzaman, Muhammad Noor Ningrum, Ratih Ardiati Othman, Fazidah Choir, Achmad Syahrul Ramadan, Arip Alya, Najma Attaqiya Putri, Elfira Rahma Pratama, Muhammad Alfian Engineering Department Data Science Technology Study Program Faculty of Advanced Technology and Multidiscipline Universitas Airlangga Indonesia Engineering Department Data Science Technology Study Program Faculty of Advanced Technology andMultidiscipline Universitas Airlangga Indonesia Department of Computer System and Technology Faculty of Computer Science and Information Technology University of Malaya Malaysia Statistical Computing StudyProgram Politeknik Statistika STIS Indonesia Information System Study Program School of Industrial and System Engineering Telkom University Indonesia

Indonesia has entered a period of demographic bonus. Human resources must be optimized. The number of children who do not in employment, education or training (NEET) in each province needs attention. Several factors that could contribute to the decline in the NEET percentage are literacy rates and the number of adolescents with computer skills. Increasing these two factors is believed to be able to reduce the percentage of NEET in every province in Indonesia. To find out the relationship between these two factors and how much influence they have on the percentage of NEET, this research is modeled by Cauchy regression and includes spatial effects. The results of the analysis show that the best model is when the spatial effect is modeled by Fernandez Steel Skew Normal conditionally autoregressive (FSSN CAR). This result is seen from the smallest value of the Watanabe Akaike Information Criterion (WAIC) in this model, which is 190.5. The parameter estimated shows that the higher the literacy rate and the number of adolescents with computer skills, the lower the percentage of NEET in each province in Indonesia. The results of this research can be useful for the Indonesian government to increase the number of educational facilities related to these two factors. © (2024), (International Association of Engineers). All rights reserved.

关键词： Bayesian CAR Cauchy Education NEET

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Recent advances in tip-enhanced Raman spectroscopy probe designs

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Nano Research 2023年第4期16卷 5555-5571页

作者： Da Xu Boqun Liang Yaodong Xu Ming Liu Department of Electrical and Computer Engineering University of California-RiversideRiversideCalifornia 92521USA Materials Science and Engineering program University of California-RiversideRiversideCalifornia 92521USA

Tip-enhanced Raman spectroscopy(TERS)imaging is a super-resolution imaging technique that features the merits of both surface-enhanced Raman spectroscopy(SERS)and scanning probe microscopy(SPM),such as the high chemical sensitivity from the former and the nanoscale spatial resolution from the *** advantages make TERS an essential nanospectroscopic characterization technique for chemical analysis,materials science,bio-sensing,*** probes,the most critical factor determining the TERS imaging quality,are expected to provide a highly confined electromagnetic hotspot with a minimized scattering background for the generation of Raman signals with high spatial *** two decades of development,numerous probe design concepts have been proposed and *** review provides a comprehensive overview of the state-of-the-art TERS probe designs,from the working mechanism to the practical *** start with reviewing the recent development of TERS configurations and the corresponding working mechanisms,including the SPM platforms,optical excitation/collection techniques,and probe preparation *** then review the emerging novel TERS probe designs,including the remote-excitation probes,the waveguide-based nanofocusing probes,the metal-coated nanofocusing probes,the nanowire-assisted selective-coupling probes,and the tapered metal-insulator-metal *** discussion focuses on a few critical aspects,including the surface-plasmon-polariton(SPP)hotspot excitation technique,conversion efficiency,working frequency,and *** the end,we review the latest TERS applications and give a perspective on the future of TERS.

关键词： tip-enhanced Raman spectroscopy plasmonics scanning probe microscopy nanoscale imaging nanophotonics nanofocusing

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IoT Based Home Automation System: Security Challenges and Solutions 5

IoT Based Home Automation System: Security Challenges and So...

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5th International Conference on Advancements in Computational sciences, ICACS 2024

作者： Solangi, Nighat Khan, Aiman Qureshi, Mehak Fatima Zaki, Nafeesa Qureshi, Umair Mujtaba Umair, Zuneera Mehran University of Engineering and Technology Department of Telecommunication Engineering Sindh Pakistan Chinese University of Hong Kong Department of Computer Science & Engineering Kowloon Hong Kong The Hong Kong Baptist University Department of Computer Science Hong Kong

ISBN: (纸本)9798350394764

Smart homes entail the integration of wireless communication and sensor technologies to enhance traditional homes by incorporating Internet of Things (IoT) enabled smart appliances. These appliances offer automation and convenience to homeowners. However, unauthorized usage of appliances remains a significant concern in smart homes. This paper explores various approaches and technological advancements in the field of smart homes. It also addresses the security challenges faced by home automation systems and proposes a practical solution to mitigate unnecessary system utilization. The solution involves the utilization of an Arduino micro-controller paired with an Ethernet shield unit, enabling monitoring of the house and its appliances. An authentication mechanism employing username and password authentication is implemented to verify the legitimacy of users, thereby preventing unauthorized access and the subsequent unauthorized usage of smart home appliances. © 2024 IEEE.

关键词： Internet of things

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Deep Transfer Learning Models for Mobile-Based Ocular Disorder Identification on Retinal Images

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computers, Materials & Continua 2024年第7期80卷 139-161页

作者： Roseline Oluwaseun Ogundokun Joseph Bamidele Awotunde Hakeem Babalola Akande Cheng-Chi Lee Agbotiname Lucky Imoize Department of Multimedia Engineering Kaunas University of TechnologyKaunas44249Lithuania Department of Computer Science Landmark UniversityOmu Aran251103Nigeria Department of Computer Science Faculty of Information and Communication SciencesUniversity of IlorinIlorin240003Nigeria Department of Telecommunication Science University of IlorinIlorin230003Nigeria Department of Library and Information Science Fu Jen Catholic UniversityNew Taipei City24205TaiwanChina Department of Computer Science and Information Engineering Fintech and Blockchain Research CenterAsia UniversityTaichung City41354TaiwanChina Department of Electrical and Electronics Engineering Faculty of EngineeringUniversity of LagosAkokaLagos100213Nigeria Department of Electrical Engineering and Information Technology Institute of Digital CommunicationRuhr UniversityBochum44801Germany

Mobile technology is developing *** phone technologies have been integrated into the healthcare industry to help medical ***,computer vision models focus on image detection and classification ***2 is a computer vision model that performs well on mobile devices,but it requires cloud services to process biometric image information and provide predictions to *** leads to increased *** biometrics image datasets on mobile devices will make the prediction faster,but mobiles are resource-restricted devices in terms of storage,power,and computational ***,a model that is small in size,efficient,and has good prediction quality for biometrics image classification problems is *** pre-trained CNN(PCNN)MobileNetV2 architecture combined with a Support Vector Machine(SVM)compacts the model representation and reduces the computational cost and memory *** proposed novel approach combines quantized pre-trained CNN(PCNN)MobileNetV2 architecture with a Support Vector Machine(SVM)to represent models efficiently with low computational cost and *** contributions include evaluating three CNN models for ocular disease identification in transfer learning and deep feature plus SVM approaches,showing the superiority of deep features from MobileNetV2 and SVM classification models,comparing traditional methods,exploring six ocular diseases and normal classification with 20,111 images postdata augmentation,and reducing the number of trainable *** model is trained on ocular disorder retinal fundus image datasets according to the severity of six age-related macular degeneration(AMD),one of the most common eye illnesses,Cataract,Diabetes,Glaucoma,Hypertension,andMyopia with one class *** the experiment outcomes,it is observed that the suggested MobileNetV2-SVM model size is *** testing accuracy for MobileNetV2-SVM,InceptionV3,and MobileNetV2 is 90.11%,86.88%,a

关键词： Retinal images ocular disorder deep transfer learning disease identification mobile device

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Brain Tumor Diagnosis Using a Hybrid Method of BoVW, LBP, and Neural Networks 3

Brain Tumor Diagnosis Using a Hybrid Method of BoVW, LBP, an...

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3rd IEEE International Conference on Robotics, Automation, Artificial-Intelligence and Internet-of-Things, RAAICON 2024

作者： Hasan, Nowshad Islam, Md Saiful Sharif, Md. Maskat Chowdhury, Arafat Anam Rahman, Miskatur Khan, Md Tohedur Rahaman Khan, Md Rokibul Fahad Bahar, Anamul Chittagong University of Engineering and Technology Department of Electronics and Telecommunication Engineering Chittagong Bangladesh North South University Department of Computer Science Enginnering Dhaka Bangladesh International Islamic University Chittagong Department of Computer Science Enginnering Chittagong Bangladesh International Islamic University Chittagong Department of Electronics and Telecommunication Engineering Chittagong Bangladesh University of London Department of Computer Science Enginnering London United Kingdom

ISBN: (纸本)9798331534400

Brain tumor is one of the most deadly diseases today. Early identification is the key in treatment and automated method of image classification can help in this process. But, there are significant obstacles in precisely identifying brain tumors and increasing the classification accuracy for different types of tumors. In order to address the problem, the work suggests a hybrid model for effectively detecting and classifying brain tumors. First, the obtained pictures are preprocessed with resizing, application of sharpening filter and final stage of contrast enhancement. Further preprocessing in carried out using the K-mean clustering algorithm Next, Feature extraction is done by using the BoVW together with LBP which deal with the overall and region-specific texture features respectively. Following that, the seven statistical features are extracted, and then they are utilized as input to the artificial neural network classifier in order to obtain the classification of the glioma, meningioma, and pituitary tumor. The training function 'Levenberg-Marquardt' is also used in this work. This method provides 99.0 % of accuracy on Dataset I and 99.2% accuracy on Dataset II. Moreover, in relation to other modern methods, the selected seven statistical features employed in this study are relatively limited in demonstrating this performance. © 2024 IEEE.

关键词： K-means clustering

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A Smart Device for Real-Time Assistance to the Visually Impaired People 10

A Smart Device for Real-Time Assistance to the Visually Impa...

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10th International Conference on Communication and Signal Processing, ICCSP 2024

作者： Kasabekar, Om Jeurkar, Shardul Kamble, Riya Srivel, R. Kamble, Milind Vishwakarma Institute of Technology Department of Electronics and Telecommunication Pune India Adhiparasakthi Engineering College Department of Computer Science Melmaruvathur India

ISBN: (纸本)9798350353068

This research proposes an advanced and cost-effective smart blind device equipped with Internet of Things (IoT) sensors to address significant navigational challenges for individuals with visual impairments in both indoor and outdoor environments. The system employs IoT technologies to detect obstacles, staircases, and wet terrain, enhancing the safety of walking experiences. To bolster users' security, the device features a panic button, triggering the transmission of alert messages about their location. A companion software application enables acquaintances to modify contact numbers for alert messages in the device configurations. Additionally, the study introduces an artificial navigation system with adjustable sensitivity, integrating a GPS module and ultrasonic proximity sensors. Through ultrasonic reflections, this device empowers visually impaired individuals to autonomously navigate diverse surroundings, including negotiating barriers and potholes. The device's versatility is evident in its adaptable attachment options, such as shoes, clothing, body parts, and walking sticks, contributing to its reliability and flexibility. © 2024 IEEE.

关键词： Global positioning system

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Structure of Global Financial Networks Before and During COVID-19 Based on Mutual Information 1st

Structure of Global Financial Networks Before and During COV...

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1st International Conference on Machine Intelligence and Emerging Technologies, MIET 2022

作者： Hassan, Sheikh Shadia Rakib, Mahmudul Islam Tuhin, Kamrul Hasan Nobi, Ashadun Department of Computer Science and Telecommunication Engineering Noakhali Science and Technology University Noakhali Sonapur3814 Bangladesh

ISBN: (纸本)9783031346217

We investigate and perform a comparative study of the structure and network properties of global financial indices before and during COVID-19 using mutual information. We analyze the daily closing prices of 25 global stock markets from January 1, 2018, to March 31, 2021. We found that the dependence relationship among regional countries is enhanced during the pandemic. The network is constructed based on mutual information at different thresholds. At threshold 0.25, before the pandemic, the network was fragmented into two big clusters of Asian and European-Americans. At the same threshold, during the pandemic, the network forms a big cluster excluding New Zealand, which indicates strong dependence among indices in the pandemic. We observe different network properties of the threshold networks. A sharp drop in global efficiency is visible at threshold 0.25 before COVID-19 and at threshold 0.35 during the pandemic due to the network split into different isolated clusters at these thresholds. We construct the minimum spanning tree using the Kruskal algorithm and find a shallower tree during the pandemic. We found that the French, Canadian, and South Korean indices played an important role in their clusters before COVID-19, whereas during COVID-19, the hub of the European cluster was altered by Germany. © 2023, ICST Institute for computer sciences, Social Informatics and telecommunications engineering.

关键词： COVID-19

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Internet of Things Based Health Monitoring System Using Smart Glove 3

Internet of Things Based Health Monitoring System Using Smar...

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3rd IEEE International Conference on Robotics, Automation, Artificial-Intelligence and Internet-of-Things, RAAICON 2024

作者： Ahmed, Mohammad Faisal Hasan, Nowshad Ullah, Mohammad Woli Maskat Sharif, Md. Rahaman Khan, Md Tohedur Fahad Khan, Md Rokibul Bahar, Anamul Chittagong University of Engineering and Technology Department of Electronics and Telecommunication Engineering Chittagong Bangladesh International Islamic University Chittagong Department of Electronics and Telecommunication Engineering Chittagong Bangladesh University of London Department of Computer Science Enginnering London United Kingdom

ISBN: (纸本)9798331534400

The current healthcare and emergency response systems face significant challenges in preventing fatalities and serious injuries among elderly individuals and those living alone due to falls, delayed emergency care, and insufficient continuous health monitoring. This research proposes the development and evaluation of a cost-effective smart hand glove designed to enhance the safety and health monitoring of these vulnerable populations. The smart hand glove is built using an Arduino Uno microcontroller, an ESP8266 Wi-Fi module, two MPU6050 sensors for fall detection and gesture recognition, and a MAX30100 sensor for heart rate and SpO2 monitoring. These components work together to detect falls, recognize specific hand gestures, and continuously monitor vital signs. Upon detecting a fall or receiving a gesture input, the system triggers automatic SMS and email alerts to designated contacts. Additionally, health monitoring data is transmitted to a secure, password-protected website accessible by healthcare providers. The smart hand glove demonstrated its potential in improving safety and health outcomes for elderly individuals and those living alone by enabling timely medical intervention and continuous health monitoring. This innovative solution addresses critical gaps in emergency response and healthcare for vulnerable populations, ensuring better safety and wellbeing. © 2024 IEEE.

关键词： Fall detection

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Development of Smart Cup for Monitoring Post Stroke Patients 2

Development of Smart Cup for Monitoring Post Stroke Patients

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2nd IEEE International Conference on Interdisciplinary Approaches in Technology and Management for Social Innovation, IATMSI 2024

作者： Chandankhede, Pankaj H. Fatinge, Pragati M. Vaidya, Kanchan S. G H Raisoni College of Engineering Department of Electronics and Telecommunication Engineering Nagpur India G H Raisoni Institute of Engineering and Technology Department of Computer Science and Engineering Nagpur India Dhole Patil College of Engineering Department of Electronics & Telecommunication Engineering Pune India

ISBN: (纸本)9798350360523

Stroke is a major global health concern, affecting millions and leading to cognitive and motor impairments. Traditional rehabilitation often involves subjective assessments by therapists and can be costly and time-consuming. This paper proposes a novel approach to address these challenges: a smart object ecosystem for home monitoring of stroke patients. The first element of this ecosystem is a smart cup designed to monitor patients' arm and hand motor activity. This cup incorporates sensors to analyze how patients handle the cup, providing crucial insights into their recovery progress. Additionally, it detects tremors, indicating potential neurological or motor disorders, and monitors daily activities like sitting, standing, walking, and drinking. These data are essential for comprehensive assessment of patient independence and progress. This paper begins by reviewing existing stroke monitoring platforms, highlighting the limitations of current approaches. It then discusses the design concept and implementation details of the smart cup, delving into data processing methods for orientation, tremor detection, and activity analysis. A preliminary study showcasing the cup's accuracy (>92% for activity recognition) demonstrates its potential as a valuable tool in rehabilitation. © 2024 IEEE.

关键词： Strain gages

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