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Detection of Various Dental Conditions on Dental Panoramic Radiography Using Faster R-CNN

IEEE Access 2023年 11卷 127388-127401页

作者： Chen, Shih-Lun Chen, Tsung-Yi Mao, Yi-Cheng Lin, Szu-Yin Huang, Ya-Yun Chen, Chiung-An Lin, Yuan-Jin Chuang, Mian-Heng Abu, Patricia Angela R. Chung Yuan Christian University Department of Electronic Engineering Taoyuan320314 Taiwan Feng Chia University Department of Electronic Engineering Taichung407102 Taiwan Chang Gung Memorial Hospital Department of General Dentistry Taoyuan61363 Taiwan National Ilan University Department of Computer Science and Information Engineering Yilan26047 Taiwan Academy of Innovative Semiconductor and Sustainable Manufacturing Department of Program on Semiconductor Manufacturing Technology National Cheng Kung University Tainan717005 Taiwan Ming Chi University of Technology Department of Electrical Engineering New Taipei243303 Taiwan Ateneo de Manila University Department of Information Systems and Computer Science Quezon1108 Philippines

The dental panoramic radiograph (DPR) is a pivotal diagnostic tool in dentistry. However, despite the growing prevalence of artificial intelligence (AI) across various medical domains, manual methods remain the prevailing means of interpreting DPR images. This study aims to introduce an advanced identification system for detecting seven dental conditions in DPR images by utilizing Faster R-CNN. The primary objectives are to enhance dentists' efficiency and evaluate the performance of various CNN models as foundational training networks. This study contributes significantly to the field in several notable ways. Firstly, including a Butterworth filter in the training process yielded an approximately 7% enhancement in judgment accuracy. Secondly, the proposed enhancement technology tailored to different dental symptoms effectively bolstered the training model's accuracy. Consequently, all dental conditions attained an accuracy rate exceeding 95% in CNN analysis. These accuracy enhancements ranged from 1.34% to 13.24% compared to existing recognition technologies. Thirdly, this study pioneers the application of Faster R-CNN for identifying dental conditions, achieving an impressive accuracy rate of 94.18%. The outcomes of this study mark a substantial advancement compared to prior research and offer dentists a more efficient and convenient means of pre-diagnosing dental conditions. © 2013 IEEE.

关键词： Image segmentation

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Improved Metaheuristics with Machine Learning Enabled Medical Decision Support System

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computers, materials & Continua 2022年第11期73卷 2423-2439页

作者： Sara A.Althubiti JoséEscorcia-Gutierrez Margarita Gamarra Roosvel Soto-Diaz Romany F.Mansour Fayadh Alenezi Department of Computer Science College of Computer and Information SciencesMajmaah UniversityAl-Majmaah11952Saudi Arabia Research Center-CIENS Escuela Naval de Suboficiales A.R.C.“Barranquilla”BarranquillaColombia Electronics and Telecommunications Engineering Program Universidad Autónoma del CaribeBarranquilla080001Colombia Departament of Computational Science and Electronic Universidad de la CostaCUCBarranquilla080001Colombia Biomedical Engineering Program Universidad Simón BolívarBarranquilla080001Colombia Department of Mathematics Faculty of ScienceNew Valley UniversityEl-Kharga 72511Egypt Department of Electrical Engineering College of EngineeringJouf UniversitySaudi Arabia

Smart healthcare has become a hot research topic due to the contemporary developments of Internet of Things(IoT),sensor technologies,cloud computing,and ***,the latest advances of Artificial Intelligence(AI)tools find helpful for decision-making in innovative healthcare to diagnose several *** Cancer(OC)is a kind of cancer that affects women’s ovaries,and it is tedious to identify OC at the primary stages with a high mortality *** OC data produced by the Internet of Medical Things(IoMT)devices can be utilized to differentiate *** this aspect,this paper introduces a new quantum black widow optimization with a machine learningenabled decision support system(QBWO-MLDSS)for smart *** primary intention of the QBWO-MLDSS technique is to detect and categorize the OC rapidly and ***,the QBWO-MLDSS model involves a Z-score normalization approach to pre-process the *** addition,the QBWO-MLDSS technique derives a QBWO algorithm as a feature selection to derive optimum feature ***,symbiotic organisms search(SOS)with extreme learning machine(ELM)model is applied as a classifier for the detection and classification of ELM model,thereby improving the overall classification *** design of QBWO and SOS for OC detection and classification in the smart healthcare environment shows the study’s *** experimental result analysis of the QBWO-MLDSS model is conducted using a benchmark dataset,and the comparative results reported the enhanced outcomes of the QBWO-MLDSS model over the recent approaches.

关键词： Ovarian cancer decision support system smart healthcare IoMT deep learning feature selection

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Accidental bound states in the continuum in acoustic resonators with rotating obstacles

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Physical Review B 2024年第5期110卷 054201-054201页

作者： Yuhang Yin Qilin Duan Shan Zhu Jing Li Zuoti Xie Cheng-Wei Qiu Huanyang Chen Quantum Science Center of Guangdong–Hong Kong–Macao Greater Bay Area (Guangdong) Shenzhen 518045 China Department of Physics College of Physical Science and Technology and Pen-Tung Sah Institute of Micro-Nano Science and Technology Department of Electrical and Computer Engineering Department of Materials Science and Engineering MATEC

Bound states in the continuum (BICs) are embedded states in the radiation spectrum, which have garnered significant interest across various areas, including photonics and acoustics. In this work, by introducing rotational obstacles into acoustic resonators, we report a series of accidental BICs in coupled waveguide-resonator systems. We demonstrate that a general type of accidental BICs would emerge at specific rotating angles, supported by the mode symmetries at the boundary interface between resonators and attached waveguides. We further demonstrate that the presence or absence of accidental BICs is closely related to the geometric parameters of resonators and obstacles, and can be predicted by the mode evolution within closed resonators. Additionally, we show that two BICs of an individual mode could converge, merge, and vanish in a single resonator by changing the geometry parameters. We also explore the topological origins of these phenomena. Our study provides an efficient way to manipulate and engineer BICs through rotating obstacles in acoustic resonator systems.

关键词： Acoustic wave phenomena Bound states in the continuum Acoustic metamaterials Non-Hermitian systems Waveguides

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Reliability of Deployed Organic Photovoltaic Modules 52

Reliability of Deployed Organic Photovoltaic Modules

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52nd IEEE Photovoltaic Specialist Conference, PVSC 2024

作者： Sheriff, Hafiz K. M. Li, Yongxi Saad, Sammy Forrest, Stephen R. Applied Physics Program University of Michigan Ann ArborMI48109 United States Department of Electrical Engineering University of Michigan Ann ArborMI48109 United States Department of Physics University of Michigan Ann ArborMI48109 United States Department of Materials Science and Engineering University of Michigan Ann ArborMI48109 United States

ISBN: (纸本)9781665464260

The commercial future of organic photovoltaics (OPVs) relies on their efficiency and reliability. Recent progress in the field has ensured the achievement of device efficiency comparable to those of commercial silicon-based photovoltaics (Si-PVs) [1]. In pursuit of reliable devices, recent works have demonstrated the intrinsic stability of both small-molecule, vacuum deposited [2] and non-fullerene acceptor (NFA) - polymer-based devices [3] under controlled laboratory conditions. The final step for outdoor deployment is therefore a demonstration of the reliability of large area OPV modules in the field, subjected to fluctuating environmental conditions such as humidity, temperature, rainfall, snow, and solar intensity. In this work, we develop a customized test facility intended for the study of the reliability of large area OPV modules deployed in outdoor environments. The facility is designed for automated in-situ measurements calibrated to 1 sun solar intensity, AM 1.5 G illumination. Initial data show the modules retain more than 95% of their initial performance for 150 h when exposed to varying solar intensities, temperature fluctuations of -2°C to 10°C, and relative humidity as high as 90%. The only significant extrinsic challenge to device stability observed was the ingress of water into the package. This is mitigated by improved packaging which utilizes polyisobutylene (PIB) encapsulation and a customized insulated glass unit (IGU). © 2024 IEEE.

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Numerical Modelling of Buffer Layers for Advancing CZTSSe Solar Cell Efficiency

arXiv

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arXiv 2025年

作者： Ahamed, Tanzir Rayhan, Fozlur Rahaman, Imteaz Rahman, Md Hamidur Bappy, Md MehediHasan Ahammed, Tanvir Ghosh, Sampad Department of Electrical and Electronic Engineering CCN University of Science and Technology Cumilla3503 Bangladesh Department of Electrical and Electronic Engineering Chittagong University of Engineering and Technology Chattogram4349 Bangladesh Department of Electrical and Computer Engineering Lamar University BeaumontTX77705 United States Department of Electrical and Computer Engineering University of Utah Salt Lake CityUT84112 United States Department of Materials Science and Engineering University of Rajshahi Rajshahi6205 Bangladesh

Kesterite is a leading candidate among inorganic thin-film photovoltaic technologies, offering sustainable and environmentally friendly solutions without reliance on critical raw materials. This study investigates the performance of CZTSSe-based kesterite solar cells using SCAPS-1D simulations. Four device configurations are analyzed by integrating the CZTSSe absorber layer with buffer materials, including CdS, SnS2, IGZO, and ZnSe, selected based on their energy band alignment. Moreover, key parameters influencing device efficiency, such as absorber defect density, buffer layer thickness, and the donor and defect densities of the buffer materials, are systematically examined. The thickness of the absorber layer and acceptor density are optimized, considering practical manufacturing constraints. Following optimization, the i-ZnO/SnS2/CZTSSe/Au configuration achieves a notable efficiency of 28.38%, with a VOC of 0.83 V, a JSC of 39.93 mA/cm2, and a fill factor of 85.4%. Furthermore, the stability of the optimized structures is evaluated under varying conditions, including resistances, temperature, generation and recombination dynamics, as well as JV and QE characteristics. These findings provide valuable insights for advancing the efficiency and stability of CZTSSe solar cells, contributing to the development of sustainable photovoltaic technologies. Copyright © 2025, The Authors. All rights reserved.

关键词： II-VI semiconductors

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An Optimal Framework for SDN Based on Deep Neural Network

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computers, materials & Continua 2022年第10期73卷 1125-1140页

作者： Abdallah Abdallah Mohamad Khairi Ishak Nor Samsiah Sani Imran Khan Fahad RAlbogamy Hirofumi Amano Samih M.Mostafa Department of Industrial Engineering School of Applied Technical Sciences German Jordanian UniversityAmman35247Jordan School of Electrical and Electronic Engineering Universiti Sains MalaysiaNibong Tebal14300Malaysia Center for Artificial Intelligence Technology Faculty of Information Science and TechnologyThe National University of Malaysia(UKM)Bangi43600SelangorMalaysia Department of Electrical Engineering University of Engineering and TechnologyPeshawar814Pakistan Turabah University College Computer Sciences ProgramTaif UniversityTaif21944Saudi Arabia Research Institute for Information Technology Kyushu UniversityFukuoka819-0395Japan Computer Science-Mathematics Department Faculty of ScienceSouth Valley UniversityQena83523Egypt

Software-defined networking(SDN)is a new paradigm that promises to change by breaking vertical integration,decoupling network control logic from the underlying routers and switches,promoting(logical)network control centralization,and introducing network ***,the controller is similarly vulnerable to a“single point of failure”,an attacker can execute a distributed denial of service(DDoS)attack that invalidates the controller and compromises the network security in *** address the problem of DDoS traffic detection in SDN,a novel detection approach based on information entropy and deep neural network(DNN)is *** approach contains a DNN-based DDoS traffic detection module and an information-based entropy initial inspection *** initial inspection module detects the suspicious network traffic by computing the information entropy value of the data packet’s source and destination Internet Protocol(IP)addresses,and then identifies it using the DDoS detection module based on *** assaults were found when suspected irregular traffic was *** reveal that the algorithm recognizes DDoS activity at a rate of more than 99%,with a much better accuracy *** false alarm rate(FAR)is much lower than that of the information entropy-based detection ***,the proposed framework can shorten the detection time and improve the resource utilization efficiency.

关键词： Deep neural network computer networks data security optimization

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Printable Aligned Single-Walled Carbon Nanotube Film with Outstanding Thermal Conductivity and Electromagnetic Interference Shielding Performance

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Nano-Micro Letters 2022年第11期14卷 143-156页

作者： Zhihui Zeng Gang Wang Brendan F.Wolan Na Wu Changxian Wang Shanyu Zhao Shengying Yue Bin Li Weidong He Jiurong Liu Joseph W.Lyding Key Laboratory for Liquid-Solid Structural Evolution and Processing of Materials Ministry of EducationSchool of Materials Science and EngineeringShandong UniversityShandongJinan 250061People’s Republic of China Department of Electrical and Computer Engineering Beckman Institute for Advanced Science and TechnologyUniversity of Illinois at Urbana-ChampaignUrbanaIL 61801USA Department of Chemistry Swiss Federal Institute of Technology in Zurich(ETH Zürich)8092 ZurichSwitzerland School of Materials Science and Engineering Nanyang Technological University50 Nanyang AvenueSingapore 639798Singapore Empa Swiss Federal Laboratories for Materials Science and TechnologyÜberland Strasse 1298600 DübendorfSwitzerland Institute for Advanced Technology Shandong UniversityJinan 250061People’s Republic of China

Ultrathin,lightweight,and flexible aligned single-walled carbon nanotube(SWCNT)films are fabricated by a facile,environmentally friendly,and scalable printing *** aligned pattern and outstanding intrinsic properties render“metal-like”thermal conductivity of the SWCNT films,as well as excellent mechanical strength,flexibility,and ***,the aligned cellular microstructure promotes the electromagnetic interference(EMI)shielding ability of the SWCNTs,leading to excellent shielding effectiveness(SE)of~39 to 90 dB despite a density of only~0.6 g cm^(−3) at thicknesses of merely 1.5-24μm,*** ultrahigh thickness-specific SE of 25693 dB mm^(−1) and an unprecedented normalized specific SE of 428222 dB cm^(2)g^(−1) are accomplished by the freestanding SWCNT films,significantly surpassing previously reported shielding *** addition to an EMI SE greater than 54 dB in an ultra-broadband frequency range of around 400 GHz,the films demonstrate excellent EMI shielding stability and reliability when subjected to mechanical deformation,chemical(acid/alkali/organic solvent)corrosion,and high-/low-temperature *** novel printed SWCNT films offer significant potential for practical applications in the aerospace,defense,precision components,and smart wearable electronics industries.

关键词： Aligned film Single-walled carbon nanotube Lightweight Flexible Thermal conductivity Electromagnetic interference shielding

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Automatic 2D Material Detection in Optical Images using Deep Learning Based computer Vision 4

Automatic 2D Material Detection in Optical Images using Deep...

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AI and Optical Data sciences IV 2023

作者： Ramezani, Fereshteh Parvez, Sheikh Fix, J. Pierce Battaglin, Arthur Whyte, Seamus Borys, Nicholas J. Whitaker, Bradley Electrical and Computer Engineering Department Montana State University Bozeman United States Department of Physics Montana State University Bozeman United States Materials Science Program Montana State University Bozeman United States Optical Technology Center Montana State University Bozeman United States

ISBN: (纸本)9781510659810

computer vision algorithms can quickly analyze numerous images and identify useful information with high accuracy. Recently, computer vision has been used to identify 2D materials in microscope images. 2D materials have important fundamental properties allowing for their use in many potential applications, including many in quantum information science and engineering. In order to use these materials for research and product development, single-layer 2D crystallites must be prepared through an exfoliation procedure and then identified using reflected light optical microscopy. Performing these searches manually is a time-consuming and tedious task. Deploying deep learning-based computer vision algorithms for 2D material search can automate the flake detection task with minimal need for human intervention. In this work, we have implemented a new deep learning pipeline to classify crystallites of 2D materials based on coarse thickness classifications in reflected-light optical micrographs. We have used DetectorRS as the object detector and trained it on 177 images containing hexagonal boron nitride (hBN) flakes of varying thickness. The trained model achieved a high detection accuracy for the rare category of thin flakes ( © 2023 SPIE.

关键词： Object detection

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Dynamic Surrogate Optimization of Vertically Stacked Nanosheet FET Based on Gaussian Process Regression

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IEEE Access 2025年 13卷 95730-95738页

作者： Christofer N. Yalung Doldet Tantraviwat Doctor of Philosophy Program in Nanoscience and Nanotechnology (International Program/Interdisciplinary) Materials Science Research Center Faculty of Science Chiang Mai University Chiang Mai Thailand Department of Electrical Engineering Faculty of Engineering Chiang Mai University Chiang Mai Thailand Center of Excellence in Materials Science and Technology Faculty of Science Chiang Mai University Chiang Mai Thailand

While speed improvements are pivotal for advancing modern transistor technologies and ensuring faster computational performance, the tradeoffs with other critical electrical properties, such as threshold voltage ( $V_{T}$ ) and off-current ( $I_{OFF}$ ), are often overlooked. These tradeoffs can significantly impact the overall device performance. The design of vertically stacked n-type and p-type nanosheet FETs (NSFETs) was applied using a dynamic surrogate optimization-gaussian process regression (DSO-GPR) with batch assessment and halting conditions. A vertically stacked silicon-based system is created and refined. Source extension ( $S_{ext}$ ), drain extension ( $D_{ex\mathrm {t}}$ ), gate length ( $L_{g}$ ), nanosheet height (NSh), nanosheet width (NSw), and number of fin (nfin) make up the input variables. In addition to applying normalization to make the weight assignment to the goal functions easier, a penalty component was incorporated to manage the $V_{T}$ . This study demonstrates the effectiveness of the DSO-GPR framework in optimizing NSFET-based inverter designs by balancing speed, $I_{OFF}$ and $V_{T}$ . Among the three evaluated cases, case 1 achieved the fastest propagation delay (1.05 ps) due to higher $I_{ON}$ and lower $V_{T}$ , albeit with increased $I_{OFF}$ and $V_{T}$ mismatch. Case 2 provided a balanced trade-off, significantly reducing $I_{OFF}$ while maintaining a competitive delay of 1.25 ps and achieving $V_{T}$ matching at 0.11 V for both n-type and p-type NSFETs. The optimum parameters for n-type are ${L} _{g}$ = 5 nm, $N_{Sh} = 9$ nm, $N_{Sw} = 42$ nm, $S_{ext} = 3$ nm and $D_{ext} = 4$ nm, nfin = 5; for p-type, $L_{g} = 7$ nm, $N_{Sh} = 10$ nm, $N_{Sw} = 42$ nm, $S_{ext} = 3$ nm and $D_{ext} = 3$ nm, nfin = 5. Case 3 minimized leakage at the cost of delay, highlighting the trade-off between power and performance. These results validate the framework’s adaptability and automation, with performance-based stopping criteria that balance

关键词： Optimization Logic gates Ions Silicon Performance evaluation Linear programming Gaussian processes Field effect transistors Accuracy Machine learning

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Insulating materials for realising carbon neutrality:Opportunities,remaining issues and challenges

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High Voltage 2022年第4期7卷 610-632页

作者： Chuanyang Li Yang Yang Guoqiang Xu Yao Zhou Mengshuo Jia Shaolong Zhong Yu Gao Chanyeop Park Qiang Liu Yalin Wang Shakeel Akram Xiaoliang Zeng Yi Li Fangwei Liang Bin Cui Junpeng Fang Lingling Tang Yulin Zeng Xingtao Hu Jiachen Gao Giovanni Mazzanti Jinliang He Jianxiao Wang Davide Fabiani Gilbert Teyssedre Yang Cao Feipeng Wang Yunlong Zi The State Key Laboratory of Power System Department of Electrical EngineeringTsinghua UniversityBeijingChina Department of Mechanical and Automation Engineering The Chinese University of Hong KongHong KongChina Simpson Querrey Institute Northwestern UniversityEvanstonIllinoisUSA Department of Materials Science and Engineering The Pennsylvania State UniversityUniversity ParkPennsylvaniaUSA Department of Information Technology and Electrical Engineering ETH ZürichZürichSwitzerland School of Electrical and Information Engineering Tianjin UniversityTianjinChina Department of Electrical and Computer Engineering Mississippi State UniversityMississippi StateMississippiUSA Electrical and Electronic Engineering The University of ManchesterManchesterUK Department of Electrical Engineering School of Electronic Information and Electrical EngineeringShanghai Jiao Tong UniversityShanghaiChina Key Laboratory of Control of Power Transmission and Conversion(SJTU) Ministry of EducationShanghaiChina College of Electrical Engineering Sichuan UniversityChengduChina Shenzhen Institute of Advanced Technology Chinese Academy of Sciences ShenzhenShenzhenChina School of Electrical Engineering Wuhan UniversityWuhanChina School of Integrated Circuits Tsinghua UniversityBeijingChina Jiangsu Jinxin Electric Appliance Co.Ltd. YangzhouChina Tai'an Tiancheng Safety Evaluation Co. Ltd.Tai'anChina Department Electrical Electronic and Information EngineeringUniversity of BolognaBolognaItaly National Engineering Laboratory for Big Data Analysis and Applications Peking UniversityBeijingChina Laplace Paul Sabatier Universityand CNRSToulouseFrance Electrical and Computer Engineering University of ConnecticutStorrsConnecticutUSA State Key Laboratory of Power Transmission Equipment&System Security and New Technology School of Electrical EngineeringChongqing UniversityChongqingChina Thrust of Sustainable Energy and Environment The Hong Kong University of Science and Technology(Guangzhou)GuangzhouChina De

The 2050 carbon-neutral vision spawns a novel energy structure revolution,and the construction of the future energy structure is based on equipment *** material,as the core of electrical power equipment and electrified transportation asset,faces unprecedented challenges and *** goal of carbon neutral and the urgent need for innovation in electric power equipment and electrification assets are first *** engineering challenges constrained by the insulation system in future electric power equipment/devices and electrified transportation assets are *** materials,including intelligent insulating material,high thermal conductivity insulating material,high energy storage density insulating material,extreme environment resistant insulating material,and environmental-friendly insulating material,are cat-egorised with their scientific issues,opportunities and challenges under the goal of carbon neutrality being *** the context of carbon neutrality,not only improves the understanding of the insulation problems from a macro level,that is,electrical power equipment and electrified transportation asset,but also offers opportunities,remaining issues and challenges from the insulating material *** is hoped that this paper en-visions the challenges regarding design and reliability of insulations in electrical equipment and electric vehicles in the context of policies towards carbon neutrality *** authors also hope that this paper can be helpful in future development and research of novel insulating materials,which promote the realisation of the carbon-neutral vision.

关键词： neutral insulation extreme

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