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CLEO: science and Innovations, S and I 2022

作者： Arnold, Kellen P. Halimi, Sami I. Allen, Joshua A. Hu, Shuren Weiss, Sharon M. Interdisciplinary Materials Science Program Vanderbilt University NashvilleTN37235 United States Department of Electrical Engineering and Computer Science Vanderbilt University NashvilleTN37235 United States

We report a split ring photonic crystal that demonstrates an order of magnitude larger peak energy density compared to traditional photonic crystals. The split ring offers highly focused optical energy in an accessibl...

ISBN: (纸本)9781557528209

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A Performance Study of Selected Machine Learning Techniques for Predicting Heart Diseases 2nd

A Performance Study of Selected Machine Learning Techniques ...

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2nd International Conference on Security and Information Technologies with AI, Internet Computing and Big-data Applications, SITAIBA 2023

作者： Olorunfemi, Blessing Oluwatobi Ogunde, Adewale Opeoluwa Adeniyi, Abidemi Emmanuel Awotunde, Joseph Bamidele Imoize, Agbotiname Lucky Li, Chun-Ta Faculty of Natural Sciences Department of Computer Science Redeemer’s University Osun Nigeria Department of Computer Science Bowen University Iwo Nigeria Faculty of Information and Communication Sciences Department of Computer Science University of Ilorin Ilorin240003 Nigeria Faculty of Engineering Department of Electrical and Electronics Engineering University of Lagos Lagos Akoka100213 Nigeria Bachelor’s Program of Artificial Intelligence and Information Security Fu Jen Catholic University New Taipei City24206 Taiwan

ISBN: (纸本)9789819777853

Heart Disease remains a leading cause of mortality worldwide. It alarmingly rises at a quick rate, making early heart disease prediction crucial for effective prevention and timely intervention. Heart disease diagnosis is a difficult process that requires technical skills and accuracy to complete. With improvements in technology, computing has lent its voice to simplify the diagnosis of various health problems. Machine learning uses past or existing history to predict future results. Various machine learning techniques have been developed over the years and used in predicting heart diseases with various levels of performance. Identifying the best-suited machine learning technique to use for prediction purposes can be a challenging task. This research work analyses the performance of seven (7) machine learning techniques, comprising AdaBoost Algorithm, KNN, Logistic Regression, Naïve Bayes Classifier, Random Forest, SVM, and XGBoost. The heart disease dataset was downloaded from the UCI repository and analysed using Python programming language in the Jupyter Notebook environment. A comparative analysis of the seven (7) techniques was performed based on Accuracy, Precision, and Recall. From the results obtained, KNN, Random Forest, and XGBoost showed superior performance over the others with an accuracy of 100%, AdaBoost Algorithm followed with an accuracy of 92.2%, SVM followed with an accuracy of 91.71%, Naïve Bayes Classifier followed with an accuracy of 88.29% while Logistic Regression has the least accuracy of 86.34%. KNN, RF, and XGBoost outperformed AdaBoost, SVN, and LR. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Adversarial machine learning

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Design and Optimization of the Porous Metamaterial EM Absorbers in X-band

Design and Optimization of the Porous Metamaterial EM Absorb...

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2023 IEEE Symposium on Electromagnetic Compatibility and Signal/Power Integrity, EMC+SIPI 2023

作者： Anurakparadorn, Kanat Taub, Alan Michielssen, Eric University of Michigan Macromolecular Science and Engineering Program Department of Material Science and Engineering Ann ArborMI United States University of Michigan Department of Mechanical Engineering Ann ArborMI United States University of Michigan Department of Electrical Engineering and Computer Science Ann ArborMI United States

ISBN: (纸本)9798350309768

A strategy that combines experiment and simulation to design and optimize electromagnetic (EM) metamaterial absorbers containing a periodic porous structure is described. The approach provides the ability to produce absorbers that meet multiple user-specified objectives. Using the measured intrinsic properties of the baseline materials as an input to EM-field based computational modelling and optimization, absorption by the studied metamaterials measured by their reflection loss (RL) increases significantly. The resulting metamaterials have the potential for lower cost and lighter weight while providing greater protection than traditional metal gaskets and foams. © 2023 IEEE.

关键词： Metamaterials

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Application of 3D Printing and Design in Healthcare: A Focus on Undergraduate Research to Attract Students to Bioengineering and Related Disciplines 54

Application of 3D Printing and Design in Healthcare: A Focus...

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54th IEEE Frontiers in Education Conference, FIE 2024

作者： Zelada-Quiroz, Cindy M. Reyes-Santiago, Brian L. Ortiz-Rivera, Eduardo I. University of Puerto Rico at Mayagüez Bio-Engineering Graduate Program Mayagüez Puerto Rico University of Puerto Rico at Mayagüez Department of Computer Science and Engineering Mayagüez Puerto Rico University of Puerto Rico at Mayagüez Department of Electrical and Computer Engineering Mayagüez Puerto Rico

ISBN: (纸本)9798350351507

This research-to-practice paper describes developing and analyzing state-of-the-art smart boots created by combining CAD technology and advanced 3D printing techniques to attract students in bio-engineering and related fields. The primary objective of this innovative immobilization boot is to expedite fracture recovery phases through an ergonomic design to ensure optimal patient comfort during its use. Technological solutions are crucial in aiding the rehabilitation process for fractures caused by falls, heavy lifting, or rotational trauma. However, cost and comfort-related issues persist, underscoring the need for alternative approaches. This research addresses these challenges and delves into the broader implications of fracture treatment, catalyzing future projects and investigations in bioengineering. Additionally, this study serves as an educational tool that sparks the interest of high school and engineering students, promoting multidisciplinary collaboration in innovation. By involving students in specialized courses covering 3D design, human bone anatomy, biology, and materials science, this initiative empowers them to deepen their knowledge and develop new technologies to address bone injury problems. Material analyses include evaluating the type of material depending on the fracture site, such as PLA for printing and cotton and silicone gel for the midsection between the splint and the body. This research aims to advance our understanding of the type of fracture, the methods associated with their treatment, and tissue repair processes during bone callus formation. To summarize, this multidisciplinary approach drives advancements in bio-engineering and related fields, aiming to enhance patient outcomes and inspire students to pursue further research in bio-engineering and related fields. As part of this endeavor, a list of university-level courses based on the experience of the University of Puerto Rico at Mayaguez (UPRM), such as biology, bio-materials, 3D

关键词： Students

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CdS/Ti-Si-O Composite Photoanode for Photoelectrochemical Hydrogen Generation

CdS/Ti-Si-O Composite Photoanode for Photoelectrochemical Hy...

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10th Symposium on Dielectrics for Nanosystems: materials science, Processing, Reliability, and Manufacturing, held at the 245th ECS Meeting

作者： Feng, Weilong Ding, Dongyan Chen, Zhi SJTU-Zhongmu Joint Research Center for Materials and Technology of Intelligent and Connected Vehicles Institute of Electronic Materials and Technology School of Materials Science and Engineering Shanghai Jiao Tong University Shanghai200240 China Department of Electrical & Computer Engineering Center for Nanoscale Science & Engineering University of Kentucky LexingtonKY40506 United States

ISBN: (纸本)9781623326784

Advancements in clean energy drive socio-economic development and foster a sustainable future by restructuring energy systems and promoting low-carbon development. In this paper, we presented a comprehensive investigation on the design and performance characterization of CdS/Ti-Si-O composite photoanodes for photoelectrochemical (PEC) hydrogen generation. Silicon-doped TiO2 nanotube arrays were fabricated through anodization of Ti-5Si alloy, followed by the deposition of CdS using the SILAR (successive ionic layer adsorption and reaction) process, resulting in nanostructured Ti-Si-O photoanodes modified with CdS. The composite photoanodes were characterized in terms of their composition, microstructure, optical properties and photoelectrochemical hydrogen production performance. The composite photoanodes revealed a notable enhancement in PEC hydrogen generation properties with a photocurrent density of 7.86 mA/cm2,which was 19.15 times and 9.59 times to those of the undoped TiO2 photoanode and Ti-Si-O photoanode, respectively. The Si-doping mechanism of the photoanodes was elucidated through Density Functional Theory (DFT) calculations. The synergistic combination of Si-doping and CdS modification represents a novel and promising approach for the design of efficient nanostructured photoanodes. © The Electrochemical Society.

关键词： Cadmium sulfide

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An Environmentally Friendly Fishing Android-Based Mobile Device App for Penghu Islands (Pescadores), Taiwan

An Environmentally Friendly Fishing Android-Based Mobile Dev...

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Consumer Technology (ICCT-Pacific), International Conference on

作者： Hung-Tu Lin Ke-Qing Yan Ying-Zun Fang Xiang-Rui Huang Liang-Bi Chen Department of Computer Science and Information Engineering National Penghu University of Science and Technology Penghu Taiwan Department of Electrical Engineering Master Program in Electrical Engineering and Computer Science National Penghu University of Science and Technology Penghu Taiwan

ISBN: (数字)9798331504120

ISBN: (纸本)9798331504137

Penghu Islands (Pescadores), Taiwan's outlying islands surrounded by the sea, boast rich fishing resources that attract many anglers. However, successful fishing requires more than just gear: it involves understanding the varying fish species available in different locations, times, and climates, as well as adhering to relevant laws and regulations. To address these needs, this paper proposes an environmentally friendly fishing Android-based mobile device App specifically for the Penghu Islands. The proposed Android-based mobile device App aims to gather essential information, including local fishing regulations, aquatic safety tips, and important precautions. Its goal is to equip fishermen with the resources necessary to fish successfully and with peace of mind.

关键词： Sea measurements Length measurement Fish Regulation Mobile applications Tides Protection Smart phones Meteorology Lenses

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Colossal switchable photocurrents in topological Janus transition metal dichalcogenides

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npj Computational materials 2021年第1期7卷 284-292页

作者： Haowei Xu Hua Wang Jian Zhou Yunfan Guo Jing Kong Ju Li Department of Nuclear Science and Engineering Massachusetts Institute of TechnologyCambridgeMAUSA Department of Electrical Engineering and Computer Science Massachusetts Institute of TechnologyCambridgeMAUSA Department of Materials Science and Engineering Massachusetts Institute of TechnologyCambridgeMAUSA

Nonlinear optical properties,such as bulk photovoltaic effects,possess great potential in energy harvesting,photodetection,rectification,*** enable efficient light–current conversion,materials with strong photo-responsivity are highly *** this work,we predict that monolayer Janus transition metal dichalcogenides(JTMDs)in the 1T′phase possess colossal nonlinear photoconductivity owing to their topological band mixing,strong inversion symmetry breaking,and small electronic bandgap.1T′JTMDs have inverted bandgaps on the order of 10 meV and are exceptionally responsive to light in the terahertz(THz)*** first-principles calculations,we reveal that 1T′JTMDs possess shift current(SC)conductivity as large as 2300 nmμA V^(−2),equivalent to a photo-responsivity of 2800 mA/*** circular current(CC)conductivity of 1T′JTMDs is as large as∼104 nmμA V^(−2).These remarkable photo-responsivities indicate that the 1T′JTMDs can serve as efficient photodetectors in the THz *** also find that external stimuli such as the in-plane strain and out-of-plane electric field can induce topological phase transitions in 1T′JTMDs and that the SC can abruptly flip their *** abrupt change of the nonlinear photocurrent can be used to characterize the topological transition and has potential applications in 2D optomechanics and nonlinear optoelectronics.

关键词： topological transition nonlinear

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A Comprehensive Evaluaion of Solar Powered Electric Vehicle Charging Station Design Using Internet of Things 1

A Comprehensive Evaluaion of Solar Powered Electric Vehicle ...

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1st International Conference on Electronics, Communication and Signal Processing, ICECSP 2024

作者： Chitra, K. Gnanasekar, A. Ravi, C.N. Jaisudha, J. Ramya, R. Jithendar, P. CMR Institute of Technology Department of Electrical and Electronics Engineering Karnataka Bengaluru India R.M.D. Engineering College Department of Computer Science and Engineering Tamil Nadu Chennai India CMR Engineering College Department of Computer Science and Engineering Hyderabad Medchal India Prince Shri Venkateshwara Padmavathy Engineering College Department of Electronics and Communication Engineering Tamil Nadu Chennai India Saveetha School of Engineering Saveetha Institute of Medical and Technical Sciences Department of Nano Electronics Materials and Sensors Tamil Nadu Chennai India MLR Institute of Technology Department of Electrical and Electronics Engineering Hyderabad India

ISBN: (纸本)9798350364590

More than 1.3 million electric vehicles have been installed throughout the globe, and public charging networks for these vehicles are becoming increasingly common. It has been an area of interest to establish a plan for prioritizing the charging of electric vehicles (EVs) from a single network. This is particularly important in situations when the power source is restricted, such as with renewable energy, and for economic reasons (a higher price per KWh for quicker charging). When used in conjunction with electric vehicle (EV) charging, solar energy significantly decreases our reliance on fossil fuels. An electric car solar charger is created and constructed inside this system. In order to maximize the output from the solar panels, a dc-dc boost converter is used to transfer the voltage from the panels to the station's batteries. Maximum Power Point Tracking (MPPT) is also included. Power the charging station with energy from the solar panels so that the vehicle's rechargeable battery may be charged. The charging station's status can be monitored at any time via the Internet of Things. We have created a solar-powered charging station to provide simple accessibility. Solar power is both a sustainable and accessible renewable energy source. Arduino controller for light-dependent resistor (LDR) light intensity monitoring, solar cell energy observation, battery charging, and cloud storage. The core idea behind the article is the IoT Solar Charging Station (IoTSCS), and it is tested by comparing it to the Classical Solar Charging Station (CSCS), a more traditional scheme, in order to see how well the new scheme works. © 2024 IEEE.

关键词： Charging stations

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Enhancing Acute Ischemic Stroke Diagnosis Using IoMT and Deep Learning Technologies

Enhancing Acute Ischemic Stroke Diagnosis Using IoMT and Dee...

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2024 International Telecommunications Conference, ITC-Egypt 2024

作者： El-Sheikh, Mohamed M. Bayoumy, Aya Ahmed, Nada M. Mohamed Eldeeb, Amany Rabea, Fatma I. Nawar, Amira A. Khattap, Mohamed G. Galal Eldeen Mohamed Ali Hassan, Hend Mostafa, Mariam Ibrahim, Nayra Ramadan, Reem Refaat, Yomna Khaled, Mennatallah Maher, Ali Abd Elaziz, Mohamed Gamal Abdellatif Ibrahim, Ahmed Radiology and Medical Imaging Faculty of Applied Health Sciences Galala University Suez435611 Egypt Faculty of Computer Science and Engineering Galala University Suez435611 Egypt Artificial Intelligence Science Program Faculty of Computer Science and Engineering Galala University Suez435611 Egypt Air Defense College Department of Electronics and Electrical Communications Engineering Alexandria Egypt

ISBN: (纸本)9798350351408

This paper introduces an alternative technique for diagnosing Acute Ischemic Stroke within the IoMT environment. In the proposed approach, the collected data is transmitted to a cloud-based center where the technique utilizes EfficientNet, a deep learning model, designed to extract features from MRI images thereby enhancing the detection of acute ischemic infarctions. The performance of EfficientNet is compared against two other models, CNN and MobileNet, demonstrating its superior efficacy through metrics such as accuracy, precision, recall, and F1-score, which stand at 92.31%, 92.28%, 92.33%, and 92.30%, respectively. © 2024 IEEE.

关键词： Contrastive Learning

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Automatic LPI Radar Waveform Recognition Using Vision Transformer

Automatic LPI Radar Waveform Recognition Using Vision Transf...

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2023 IEEE International Radar Conference, RADAR 2023

作者： Kim, Junseob Cho, Sunghwan Hwang, Sunil Choi, Yeongyoon Korea Military Academy Department of Electrical Engineering 01805 Korea Republic of Defense Acquisition Program Administration Maneuver System Coordination and Contract Team 13809 Korea Republic of Gist Department of Electrical Engineering and Computer Science 61005 Korea Republic of

ISBN: (纸本)9781665482783

This paper investigates the classification of low probability of intercept (LPI) radar signals by exploiting the intrinsic advantages of the Vision Transformer (ViT). Due to the characteristics of LPI radar signals, such as intrapulse modulation, wide frequency bands, and low transmission power, these signals are challenging to be detected and classified using traditional analytic methods. This has led to the adoption of various deep learning techniques to overcome these limitations. On the one hand, the ViT, originally developed for natural language processing, has demonstrated outstanding performance in computer vision by replacing the structure of the convolutional neural network (CNN) with the transformer, specifically leveraging self-attention. Therefore, this paper explores a method based on the ViT technique for classifying LPI signal images. The simulation results show that the proposed ViT method outperforms the traditional CNN method by 12.8% at -10dB SNR. © 2023 IEEE.

关键词： Convolutional neural networks

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