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5th International Conference on Electronics and Sustainable Communication Systems, ICESC 2024

作者： Yesankar, Prajyot R. Bandre, Prajwal Verma, Prateek Gudadhe, Amit G. Gourshettiwar, Palash Puri, Chetan Faculty of Engineering and Technology Department of Computer Science & Design Maharashtra Wardha442001 India

ISBN: (纸本)9798350379945

Agriculture is changing into a more sustainable and productive sector as a result of the fusion of modern technologies, especially the Internet of Things (Io'T), with traditional farming methods. This shift, dubbed 'Smart Agriculture,' rethinks how farmers conduct cultivation, managing resources, and sustainability by using the power of online access, data analytics, and automation. A network of linked systems and gadgets that gather, transfer, and evaluate real-time data forms the basis of smart agriculture. With previously unheard-of precision and efficiency, farmers may now remotely track and supervise a variety of aspects of their farming activities thanks to this connectivity. The transformative influence of IoT on productivity, sustainability, or precision farming highlights the need for it in agriculture. A crucial element of smart agriculture is precision farming, which entails exact management of resources like pesticides, fertilizers, and water as well as real-time data processing. This study examines the ways in which integrated geospatial technologies, weather forecasting, and IoT -driven automation and actuation support productive and sustainable farming methods. The emphasis on aquaculture monitoring also draws attention to the wide range of uses for IoT in agriculture that go beyond conventional crop growing. The crucial part that IoT plays in meeting the growing need for food production on a worldwide scale while using scarce resources. Precision farming, management of water, and crop monitoring are made possible by Internet of Things technologies including sensors, drones, or automated machinery. These apps support environmental sustainability in agriculture, improve resource efficiency, and enable data-driven decision-making. This research work goes into more detail on the fundamental components of smart agriculture, such as sensor technologies, infrastructure connectivity, automation, data transfer, acquisition, and integration with geospatial tec

关键词： Smart agriculture

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A low-cost buoyant force measurement device for monitoring sugar concentration in water solution

A low-cost buoyant force measurement device for monitoring s...

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2023 International Conference on Electrical, computer, Communications and Mechatronics engineering, ICECCME 2023

作者： Kaučić, Luka Kovačević, Ivana Aleksi, Ivan Keser, Tomislav Zidar, Josip Rimac-Drlje, Snježana Computer Science and Information Technology Osijek Faculty of Electrical Engineering Department of Computer Engineering and Automation Osijek Croatia Computer Science and Information Technology Osijek Faculty of Electrical Engineering Department of Communications Osijek Croatia

ISBN: (纸本)9798350322972

Monitoring sugar concentration during fermentation is crucial for producing high-quality alcoholic beverages. Traditional methods for measuring sugar concentration can be costly and time-consuming, especially for small-scale producers. In this study, we developed a low-cost buoyant force measurement device for monitoring sugar concentration in water solutions. The device consists of a buoyant object fully submerged in the solution and connected to a load-cell sensor. As the sugar concentration in the liquid increases, the buoyant force on the object increases, and the load-cell measures this force. Proposed device is calibrated using solutions of known sugar concentrations and its high accuracy and precision is presented. The device is tested in controlled environment to ensure accurate tracking changes in sugar concentration over time. Proposed device can be a valuable tool for small-scale producers looking to optimize their fermentation processes while minimizing costs. © 2023 IEEE.

关键词： Fermentation

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A Perspective Analysis of Optical Biosensors in Machine Learning Applications 18

A Perspective Analysis of Optical Biosensors in Machine Lear...

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18th INDIAcom;11th International Conference on Computing for Sustainable Global Development, INDIACom 2024

作者： Kumar, B. Naveen Panduranga Rao, M.V. Sharan, Preeta Varun, K.R. Kallam, Suresh Kumaresan, M. Faculty of Engineering and Technology Department of Computer Science and Engineering Bengaluru India The Oxford College of Engineering Department of Electronics and Communication Engineering Bengaluru India The Oxford College of Engineering Department of Mechanical Engineering Bengaluru India

ISBN: (纸本)9789380544519

Optical biosensors, a novel invention at the intersection of biotechnology and optics, are revolutionizing the field of biomedical diagnostics. Optical biosensors act by identifying variations in light's wavelength, phase, polarization, or intensity caused by interactions between a sensing element and the target analyte. Optical biosensors outperform other sensor types in sensing applications due to their quick, accurate, and extremely sensitive results. When evaluating optical sensors, total power, core power, efficient area, and indices are the most crucial variables to consider. Recent years have seen notable advancements in machine learning (ML), a branch of artificial intelligence (AI). This review investigates the complementary nature of optical biosensors and machine learning methods. Here, the potential utility of ML for optical biosensors is explored in detail. The advantages and drawbacks of the most popular machine learning methods are listed based on an analysis of the optical biosensing data. It highlights the possible effects of machine learning on improving the sensitivity, selectivity, and adaptability of optical biosensing devices, and it summarizes current advancements in the field. Finally, the study considers the challenges and limitations that associated with current optical biosensing techniques. © 2024 Bharati Vidyapeeth, New Delhi.

关键词： Machine learning optical biosensor photonic crystal surface plasmon resonance surface-enhanced Raman scattering

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Analysis and Assessment of Wind Energy Potential of Socotra Archipelago in Yemen

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computers, Materials & Continua 2022年第1期70卷 1177-1193页

作者： Murad A.Almekhlafi Fahd N.Al-Wesabi Imran Khan Nadhem Nemri Khalid Mahmood Hany Mahgoub Noha Negm Amin M.El-Kustaban Ammar Zahary Department of Electrical Engineering–Communication Engineering Sana’a UniversityYemen Department of Computer Science King Khalid UniversityMuhayel AseerKingdom of Saudi Arabia Faculty of Computer and IT Sana’a UniversitySana’aYemen Department of Electrical Engineering University of Engineering and TechnologyPeshawarP.O.B 814Pakistan Department of Information Systems King Khalid UniversityMayahel AseerKSA Computer Science Department King Khaled UniversityKSA&Faculty of Computers and InformationComputer Science DepartmentMenoufia UniversityEgypt Computer Science Department King Khaled UniversityKSA&Faculty of ScienceDepartment of Mathematics and Computer ScienceMenoufia UniversityEgypt Electronics Department Faculty of EngineeringUSTSana’aYemen Faculty of Computer and IT Sana’a UniversityYemen

The increasing use of fossil fuels has a significant impact on the environment and ecosystem,which increases the rate of *** the high potential of renewable energy sources inYemen and the absence of similar studies in the region,this study aims to examine the potential of wind energy in Socotra *** was done by analyzing and evaluating wind properties,determining available energy density,calculating wind energy extracted at different altitudes,and then computing the capacity factor for a number of wind turbines and determining the *** average wind speed in Socotra Island was obtained from the Civil Aviation and Meteorology Authority data,only for the five-year data currently *** results showed high wind speeds from June to September(9.85-14.88 m/s)while the wind speed decreased for the rest of the *** average wind speed in the five years was 7.95 m/*** average annual wind speed,wind energy density,and annual energy density were calculated at different altitudes(10,30,and 50 m).According to the International Wind Energy Rating criteria,the region of Socotra Island falls under Category 7 and is classified as‘Superb’for most of the *** study provides useful information for developing wind energy and an efficient wind approach.

关键词： Energy potential wind characteristics Weibull distribution wind power density Socotra island

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CO2 Laser Fabrication of a Passive continuous-flow T-shaped Polymethyl Methacrylate (PMMA) Micromixer

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Lasers in Manufacturing and Materials Processing 2023年第3期10卷 373-388页

作者： Okello, Job Lazarus El-Bab, Ahmed M. Fath Yoshino, Masahiko El-Hofy, Hassan A. Industrial and Manufacturing Engineering Department University of Science and Technology New Borg El-Arab City Egypt Mechatronics and Robotics Engineering Department University of Science and Technology New Borg El-Arab City Egypt Department of Mechanical Engineering Tokyo Institute of Technology Tokyo Japan On leave from Department of Production Engineering Faculty of Engineering Alexandria University Alexandria Egypt

Since the emergence of microfluidics, the demand for microfluidic devices is ever increasing. Polymethyl methacrylate (PMMA) is extensively used to manufacture microfluidic devices because it is cheap, disposable, and biocompatible. CO2 laser micromachining of PMMA is cheap, fast, and efficient. However, thermal defects affect the process. In this work, a passive continuous-flow T-shaped micromixer was fabricated using a low-power CO2 laser. Microchannels were fabricated on PMMA substrates coated with a 1-µm layer of 99.95% pure aluminium. The power and speed of the laser varied from 1.5 to 7.5 W and 5 to 17.5 mm/s respectively. The effects of the deposited energy on surface roughness, heat-affected zone, and volumetric removal rate were examined. The microchannels were characterized to get the suitable dimensions for the micromixer’s microchannel which was fabricated at 3.0 W and 17.5 mm/s. The micromixer was bonded using the microwave welding technique and tested for leakage using purple dye by varying the flow pressure at intervals of 100 kPa for 20 min. Up to 1.5 MPa, no leakage occurred. Beyond 1.5 MPa, any increase in pressure resulted in leakage from the inlet tubes. Coating PMMA substrates with 99.95% pure aluminium before fabrication reduces thermal defects and improves efficiency. © 2023, The Author(s), under exclusive licence to Springer science+Business Media, LLC, part of Springer Nature.

关键词： Carbon dioxide lasers

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Evaluating Pretrained Deep Learning Models for COVID-19 Detection in Medical Imaging 1

Evaluating Pretrained Deep Learning Models for COVID-19 Dete...

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1st Renewable Energy Technologies and Modern Communications Systems: Future and Challenges Conference, RETMCS 2024

作者： AL-Shehri, Bushra A. Sabbeh, Sahar F. Dessouky, Mohamed M. Department of Data Science College of Computer Science and Engineering University of Jeddah Jeddah23218 Saudi Arabia Faculty of Computers and Artificial Intelligence Information Systems Department Benha University Benha13518 Egypt Department of Computer Science and Artificial Intelligence College of Computer Science and Engineering University of Jeddah Jeddah23218 Saudi Arabia Department of Computer Science and Engineering Faculty of Electronic Engineering Menoufia University Menouf32952 Egypt

ISBN: (纸本)9798331519445

COVID-19 is a respiratory disease for which reverse transcription-polymerase chain reaction (RT-PCR) is the standard detection method. This study introduces a hybrid deep learning approach to support the diagnosis of respiratory abnormalities, using COVID-19 as a case study. Multiple datasets were utilized, including the COVID-19 Radiography Dataset (Kaggle), the SARS-CoV-2 CT-Scan Dataset, and proprietary data from the King Faisal Medical Complex. Seven pre-trained deep learning models—VGG16, VGG19, MobileNet, DenseNet201, ResNet50, InceptionResNetV2, and InceptionV3—were evaluated for their performance. InceptionResNetV2 and InceptionV3 achieved perfect accuracy (100%) on the COVID-19 Radiography Dataset and 99% accuracy on the SARS-CoV-2 CT-Scan Dataset. Additionally, augmentation techniques were explored to improve model robustness. This research contributes significantly to medical imaging, offering practical insights for advancing diagnostic and monitoring practices for COVID-19 and other respiratory conditions. ©2024 IEEE.

关键词： COVID-19

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An Overview of Telemedicine: Evolution, Application, Challenges and Future Direction 3

An Overview of Telemedicine: Evolution, Application, Challen...

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3rd International Conference on Electronics and Renewable Systems, ICEARS 2025

作者： Kawde, Dhanshri Gourshettiwar, Palash Datta Meghe Institute of Higher Education and Research Faculty of Engineering and Technology Department of Computer Science and Engineering Sawangi Maharashtra Wardha442001 India Datta Meghe Institute of Higher Education and Research Faculty of Engineering and Technology Department of Computer Science and Medical Engineering Sawangi Maharashtra Wardha442001 India

ISBN: (纸本)9798331509675

Telemedicine is of great importance as it increases the availability of health care for people living in remote or undeveloped areas. It reduces the cost of health care, allows for early diagnosis and treatment of chronic conditions, and saves time for both patients and healthcare providers. Telemedicine also ensures continuity of care in situations like pandemics while reducing reducing the need for face-to-face consultations can reduce the chance of catching contagious diseases.. This innovation will combine wearable devices and artificial intelligence with personalized care and mental health support. This way, healthcare services would be available and efficient for everyone around the world. However, technological challenges include those stemming from poor system architecture, poor connectivity limitation in diagnosis from a physical examination privacy issues among others and diverse legal regulations. Lack of access and integration into mainstream health systems are also among the causes of discontinuities in care. Overcoming such barriers is critical, and telemedicine needs to be easy to integrate into mainstream frameworks for better access, equity, and health outcome. © 2025 IEEE.

关键词： Telemedicine

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Prototype Proposal of an 18 kW Non-Isolated Bidirectional Converter for Battery Energy Storage System 22

Prototype Proposal of an 18 kW Non-Isolated Bidirectional Co...

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22nd International Symposium on Power Electronics, Ee 2023

作者： Brandis, Andrej Knol, Kristian Pelin, Denis Topic, Danijel Computer Science and Information Technology Osijek Faculty of Electricity Engineering Department of Electromechanical Engineering Osijek Croatia Computer Science and Information Technology Osijek Faculty of Electrical Engineering Department of Power Engineering Osijek Croatia

ISBN: (纸本)9798350343175

In this paper, a brief overview of converter topologies used in stationary battery energy storage systems is given. A simulation model of converter was developed in MATLAB Simulink. A simulation is conducted to provide a preliminary understanding of the converter's bidirectional nature. The results indicate that the state of charge (SOC) increases during battery charging and decreases during discharging. The topology of non-isolated two-stage bidirectional converter is presented for proposed real-world prototype, including the high-level electrical schematic and mechanical layout. An 18-kW prototype converter for stationary battery energy storage systems was developed and presented. The converter housing with all installed ancillary components for proper operation is also described. At the time of writing this paper, the actual converter is still in the development phase. © 2023 IEEE.

关键词： Charging (batteries)

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Exposing a False Source of News on Social Media by using Machine Learning 14

Exposing a False Source of News on Social Media by using Mac...

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14th International Conference on Computing Communication and Networking Technologies, ICCCNT 2023

作者： Deshmukh, Vaishnavi J. Ambhaikar, Asha Kalinga University Department of Computer Science & Engineering Chattisgarh Raipur India Kalinga University Faculty of Engineering Department of Computer Science and Engineering Chattisgarh Raipur India

ISBN: (纸本)9798350335095

Fake news, or information that seemed false with the intention of misleading the public, has been all too common in recent years. By fostering political polarization and scepticism towards the government, the dissemination of this kind of information harms societal cohesion. Human validation has become impossible due to the massive amount of news being shared on social media, leading to the development and organization of automated methods for spotting false information. To increase the appeal of their publications, fake news publishers employ a number of stylistic strategies, one of which is stirring up reader's emotions. Our proposed methodology for exposing false news by performing feature selection method of Ensemble Bagging Classifier (EBAC), and Ensemble Boosting Classifier (EBOC), Multi-Kernel SVM(MKSVM), to experiment and choose the best fit features to obtain the sensitivity, specificity, Kappa Score, and Matthews Correlation Coefficient (MCC). © 2023 IEEE.

关键词： Fake detection

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ML Based Intrusion Detection Scheme for various types of attacks in a WSN using C4.5 and CART classifiers

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Materials Today: Proceedings 2023年 80卷 3769-3776页

作者： Gite, Pratik Chouhan, Kuldeep Murali Krishna, K. Kumar Nayak, Chinmaya Soni, Mukesh Shrivastava, Amit Department of Computer Science and Engineering IPSA-IES Indore AB Road MP Indore India Department of Computer Science and Engineering I.T.S Engineering College Greater Noida India Department of Electronics and Communication Engineering Vignan's Institute of Information Technology Duvvada Andhra Pradesh Visakhapatnam India Faculty of Emerging Technology Sri Sri University Odisha751001 India Department of Computer Science & Engineering Jagran Lakecity University Bhopal India Department of Computer Science Engineering Swami Vivekanand College of Engineering Khandwa Road Near Tolnaka Vivekanand Knowledge City Indore India

A key component for preserving a WSN's integrity is designing an intrusion detection system (IDS). This article covers several sorts of security threats that may occur in a WSN. It proposes a detection of malicious nodes in a WSN. This system identifies four common assaults (i.e., black hole, wormhole, gray hole, and DDoS attacks) and is based on a Base Station machine learning (ML) algorithm (BS). The suggested ML algorithm continually analyzes data patterns from each node. Based on this technique, BS recognizes the network's harmful behavior and provides notifications to neighbor nodes to prevent attacker. First, the various assaults are examined and their characteristics are derived in terms of network parameters. Furthermore, the gathered pattern trains an ML algorithm. Then, the attacker node is effectively and properly classified within the BS. The NS2 simulator simulated the needed secure WSN. The experimental findings revealed excellent accuracy of the suggested method for attack detection. This precision can enhance network performance in terms of energy usage and packet delivery (PDR). © 2021

关键词： Base stations

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