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3rd IEEE International Conference of Electron Devices Society Kolkata Chapter, EDKCON 2024

作者： Ravidas, Babban Kumar Roy, Mukesh Kumar Samajdar, Dip Prakash PDPM Indian Institute of Information Technology Design and Manufacturing Department of Natural Science Jabalpur482005 India PDPM Indian Institute of Information Technology Design and Manufacturing Department of Electronics and Communication Engineering Jabalpur482005 India

ISBN: (纸本)9798350374643

This study deals with the investigation of recombination mechanism in lead-free FA 0.75Cs 0.25SnI 3 -based perovskite solar cell (PSC) to analyze the performance using the SCAPS-1D tool. First, we modelled the device with FA 0.75Cs 0.25SnI 3(FACsSnI 3) as an absorber layer. SnO 2 and PTAA are used as the electron and hole transport layers (ETL and HTL). The recombination losses in the device modulates the performance of PSC. Hence, the investigation of the effect of the Shockley-Read Hall, Radiative, and Auger recombination on the performance of SC is crucial for enhancing the performance of the device. The ITO/SnO 2/FACsSnI 3/PTAA/Au PSC structure was studied and shows a PCE of 25.03 % with V oc of 0.95 V, J sc of 34.71 mA/cm 2, and FF of 76.28 % under the optimal absorber thickness (t) of 0.8 μm, acceptor doping density (N A) of 10 17cm - 3, trap density of 10 15 cm -3, Auger electron/hole capture coefficient (C n/p) of 10 -29cm -6/s and radiative recombination coefficient (B) of 10 -11cm 3/s. Quantum efficiency (QE) reached up to 100% at wavelength of 350 nm under the optimum conditions. This study is helpful to identify the mechanisms responsible for the degradation of the performance of PSCs. © 2024 IEEE.

关键词： Perovskite

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Thermal comfort in Algeria’s vernacular built environment–a systematic review

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International Journal of Environmental Studies 2025年第3期82卷 1099-1122页

作者： Ouahchi, Smail Ab Ghafar, Norafida Sahabuddin, Mohd Firrdhaus Mohd Zemmouri, Noureddine Mahaya, Chafik Priya, R. Shanthi Department of Architecture Faculty of Built Environment University of Malaya Kuala Lumpur Malaysia Department of Architecture Algiers University 1 Algiers Algeria Mohamed Khider University Biskra Algeria School of Architecture and Interior Design Faculty of Engineering & Technology SRM Institute of Science and Technology Chennai India

This paper gathers the results of a systematic Literature Review (SLR), employing the Preferred Reporting Items for systematic Reviews and Meta-Analyses (PRISMA) to show the most effective climate-adaptive strategies and their functional correlations and also potential research gaps. Additionally, it aims to identify various factors that influence vernacular-built environments. The focus is on the role of vernacular built environments in achieving thermal comfort for occupants and the potential contribution of energy-saving techniques to future building design. © 2025 Informa UK Limited, trading as Taylor & Francis Group.

关键词： Thermal comfort

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Large circuit models: opportunities and challenges

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science China(Information sciences) 2024年第10期67卷 25-66页

作者： Lei CHEN Yiqi CHEN Zhufei CHU Wenji FANG Tsung-Yi HO Ru HUANG Yu HUANG Sadaf KHAN Min LI Xingquan LI Yu LI Yun LIANG Jinwei LIU Yi LIU Yibo LIN Guojie LUO Hongyang PAN Zhengyuan SHI Guangyu SUN Dimitrios TSARAS Runsheng WANG Ziyi WANG Xinming WEI Zhiyao XIE Qiang XU Chenhao XUE Junchi YAN Jun YANG Bei YU Mingxuan YUAN Evangeline F.Y.YOUNG Xuan ZENG Haoyi ZHANG Zuodong ZHANG Yuxiang ZHAO Hui-Ling ZHEN Ziyang ZHENG Binwu ZHU Keren ZHU Sunan ZOU Huawei Noah’s Ark Lab School of Integrated Circuits Peking University Faculty of Electrical Engineering and Computer Science Ningbo University Department of Electronic and Computer Engineering Hong Kong University of Science and Technology Department of Computer Science and Engineering The Chinese University of Hong Kong School of Integrated Circuits Southeast University Huawei HiSilicon Peng Cheng Laboratory School of Computer Science Peking University School of Microelectronics State Key Laboratory of Integrated Chips and System Fudan University School of Artificial Intelligence Shanghai Jiao Tong University

Within the electronic design automation(EDA) domain, artificial intelligence(AI)-driven solutions have emerged as formidable tools, yet they typically augment rather than redefine existing methodologies. These solutions often repurpose deep learning models from other domains, such as vision, text, and graph analytics, applying them to circuit design without tailoring to the unique complexities of electronic circuits. Such an “AI4EDA” approach falls short of achieving a holistic design synthesis and understanding,overlooking the intricate interplay of electrical, logical, and physical facets of circuit data. This study argues for a paradigm shift from AI4EDA towards AI-rooted EDA from the ground up, integrating AI at the core of the design process. Pivotal to this vision is the development of a multimodal circuit representation learning technique, poised to provide a comprehensive understanding by harmonizing and extracting insights from varied data sources, such as functional specifications, register-transfer level(RTL) designs, circuit netlists,and physical layouts. We champion the creation of large circuit models(LCMs) that are inherently multimodal, crafted to decode and express the rich semantics and structures of circuit data, thus fostering more resilient, efficient, and inventive design methodologies. Embracing this AI-rooted philosophy, we foresee a trajectory that transcends the current innovation plateau in EDA, igniting a profound “shift-left” in electronic design methodology. The envisioned advancements herald not just an evolution of existing EDA tools but a revolution, giving rise to novel instruments of design-tools that promise to radically enhance design productivity and inaugurate a new epoch where the optimization of circuit performance, power, and area(PPA) is achieved not incrementally, but through leaps that redefine the benchmarks of electronic systems' capabilities.

关键词： AI-rooted EDA large circuit models (LCMs) multimodal circuit representation learning circuit optimization

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Embedded system Development for Detection of Railway Track Surface Deformation Using Contour Feature Algorithm

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Computers, Materials & Continua 2023年第5期75卷 2461-2477页

作者： Tarique Rafique Memon Tayab Din Memon Imtiaz Hussain Kalwar Bhawani Shankar Chowdhry NCRA-HHCMS Lab Mehran University of Engineering&Technology Jamshoro76062Pakistan Department of Electronic Engineering Quaid-e-Awam University of EngineeringScience&Technology Nawabshah67480Pakistan Design and Creative Technology Torrens University Australia196 Flinders StreetMelbourneVIC 3000Australia Department of Electronic Engineering Mehran University of Engineering and TechnologyJamshoro76062Pakistan Department of Electronics and Power Engineering Pakistan Navy Engineering CollegeNUST Karachi75350Pakistan

Derailment of trains is not unusual all around the world,especially in developing countries,due to unidentified track or rolling stock faults that cause massive casualties each *** this purpose,a proper condition monitoring system is essential to avoid accidents and heavy ***,the detection and classification of railway track surface faults in real-time requires massive computational processing and memory resources and is prone to a noisy ***,in this paper,we present the development of a novel embedded system prototype for condition monitoring of railway *** proposed prototype system works in real-time by acquiring railway track surface images and performing two tasks a)detect deformation(i.e.,faults)like squats,shelling,and spalling using the contour feature algorithm and b)the vibration signature on that faulty spot by synchronizing acceleration and image data.A new illumination scheme is also proposed to avoid the sunlight reflection that badly affects the image acquisition *** contour detection algorithm is applied here to detect the uneven shapes and discontinuities in the geometrical structure of the railway track surface,which ultimately detects unhealthy *** works by converting Red,Green,and Blue(RGB)images into binary images,which distinguishes the unhealthy regions by making them white color while the healthy regions in black *** have used the multiprocessing technique to overcome the massive processing and memory *** embedded system is developed on Raspberry Pi by interfacing a vision camera,an accelerometer,a proximity sensor,and a Global Positioning system(GPS)sensors(i.e.,multi-sensors).The developed embedded system prototype is tested in real-time onsite by installing it on a Railway Inspection Trolley(RIT),which runs at an average speed of 15 km/*** functional verification of the proposed system is done successfully by detecting and recording the various railway track surface faul

关键词： Railway track surface faults condition monitoring system fault detection contour detection deep learning image processing rail wheel impact

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Electricity Market-Clearing with Extreme Events

IEEE Transactions on Energy Markets, Policy and Regulation

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IEEE Transactions on Energy Markets, Policy and Regulation 2024年第2期3卷 194-208页

作者： Tapia, Tomas Liang, Zhiriu Konstantinou, Charalambos Dvorkin, Yury Department of Electrical and Computer Engineering Johns Hopkins University Baltimore MD USA Department of Computer Electrical and Mathematical Sciences and Engineering King Abdullah University of Science and Technology Thuwal Makkah Saudi Arabia Department of Electrical and Computer Engineering and Department of Civil and System Engineering Johns Hopkins University Baltimore MD USA

Extreme events jeopardize power network operations, causing beyond-design failures and massive supply interruptions. Existing market designs fail to internalize and systematically assess the risk of extreme and rare events. Efficiently maintaining the reliability of renewable-dominant power systems during extreme weather events requires co-optimizing system resources, while differentiating between large/rare and small/frequent deviations from forecast conditions. To address this gap in both research and practice, we propose managing the uncertainties associated with extreme weather events through an additional reserve service, termed extreme reserve. The procurement of extreme reserve is co-optimized with energy and regular reserve using a large deviation theory chance-constrained (LDT-CC) model, where LDT offers a mathematical framework to quantify the increased uncertainty during extreme events. To mitigate the high additional costs associated with reserve scheduling under the LDT-CC model, we also propose an LDT model based on weighted chance constraints (LDT-WCC). This model prepares the power system for extreme events at a lower cost, making it a less conservative alternative to the LDTCC model. The proposed market design leads to a competitive equilibrium while ensuring cost recovery. Numerical experiments on an illustrative system and a modified 8-zone ISO New England system highlight the advantages of the proposed market design. © 2024 IEEE.

关键词： Weather forecasting

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Hot Compression Mechanical Behavior of Solution Heat‑Treated and Pre‑aged Mg–Zn–Gd–Er Alloys

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Acta Metallurgica Sinica(English Letters) 2023年第3期36卷 469-485页

作者： Bo Che Liwei Lu Longfei Liu Yan Yang Wei Kang Jun Luo Zhiqiang Wu Yongfeng Qiu School of Materials Science and Engineering Hunan University of Science and TechnologyXiangtan 411201China College of Materials Science and Engineering Chongqing UniversityChongqing 400044China Hunan Provincial Key Laboratory of Vehicle Power and Transmission System Hunan Institute of EngineeringXiangtan 411104China Guiyang Aluminum Magnesium Design&Research Institute Co. LtdGuiyang 550081China School of Automation Central South UniversityChangsha 410083China

The mechanical behavior of solution heat-treated and pre-aged Mg–6Zn–1Gd–1Er alloys during hot compression(from 180 to 330℃)has been *** results showed that the flow stress curves of the pre-aged sample(PAS)intersected with that of the solution heat-treated sample(SHTS)during hot *** 180℃,when the true strain is 0.27 and 0.47,the PAS showed larger and smaller stress(210.80 MPa vs.207.58 MPa and 205.67 MPa vs.207.93 MPa)than the SHTS,*** phenomena were due to the stronger interaction of W phase and dislocations/twins under the strain of 0.27,while dynamic recrystallization softening occurred under the strain of *** the temperature increased to 330℃,the flow stress of PAS and SHTS showed an opposite trend to that of 180℃.Continuous dynamic recrystallization and particle stimulated nucleation based on slip operations are the main deformation mechanisms under 330℃.At the true strain is 0.33 and 0.53,the PAS has smaller and larger stress(61.32 MPa vs.63.69 MPa and 58.75 MPa vs.57.09 MPa)than the SHTS,*** increasing deformation resistance of dynamic precipitation improved the flow stress under smaller strain and dynamic recrystallization decreased the flow stress under high strain,which resulted the opposite phenomena of SHTS.

关键词： Mg-6Zn-1Gd-1Er alloy Mechanical behavior Precipitates Twin Dynamic recrystallization

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Theoretical Investigation of CsSn1-xGexI3 Perovskite Solar Cells Using Graded Band Gap Profiles 3

Theoretical Investigation of CsSn1-xGexI3 Perovskite Solar C...

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3rd IEEE International Conference of Electron Devices Society Kolkata Chapter, EDKCON 2024

作者： Narayanan, Arya Ravidas, Babban Kumar Samajdar, Dip Prakash PDPM Indian Institute of Information Technology Design and Manufacturing Department of Electronics and Communication Engineering Jabalpur482005 India PDPM Indian Institute of Information Technology Design and Manufacturing Department of Natural Science Jabalpur482005 India

ISBN: (纸本)9798350374643

The continuous rise in the global energy demand encouraged research in the manufacture of more efficient cost-effective solar cells. Sn and Ge became a promising alternative to the toxic lead used in conventional perovskite solar cells (PSCs) to reduce environmental hazards. For this work, we studied the effect of band gap grading of CsSnI3-based PSCs by varying the concentration of Ge atom as replacement of Sn atom in the absorber material utilizing Vegard's law in SCAPS-1D tool. We have analyzed the variation of power conversion efficiency (PCE) while increasing composition x in CsSn 1-xGe xmathrm I 3 from 0 to 1 in the interval of 0.25. It is observed that PSC having an active layer made of CSSn0 .75Ge 0.25mathrm I 3 with a band gap of 1.375 eV shows a better performance (PCE of 17.57%) as compared to pure planar CsSnI3 (PCE of 16.05%) and CsGeI3 (PCE of 14.28%) based PSCs. We have done the band gap grading studies of the perovskite layer by using the optimized grading profiles. It is found out that the PCE of the device increased from 16.05% for planar CsSnI3 to 20.06% for high gradient double graded absorber (CsSn 1-xGe xmathrm I 3/CsSnI 3/CsSn 1-xGe xmathrm I 3), 19.45 % for high gradient Front Graded (CsSn 1-xGe xmathrm I 3/CsSnI 3) and 17.88% for high gradient Back Graded (CsSnI 3/CsSn 1- xGe xmathrm I 3) PSCs. Note that the band gap grading in PSCs improves the performance of the SC significantly. © 2024 IEEE.

关键词： Perovskite

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Artificial intelligence based machine learning algorithm for prediction of cancer in female anatomy

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Multimedia Tools and Applications 2025年第16期84卷 15735-15761页

作者： Ghantasala, G S Pradeep Hung, Bui Thanh Chakrabarti, Prasun R, Sathiyaraj Pellakuri, Vidyullatha Department of Computer Science and Engineering Alliance College of Engineering and Design Alliance University Karnataka Bangalore India Data Science Laboratory Faculty of Information Technology Industrial University of Ho Chi Minh city Ho Chi Minh City Viet Nam Deputy Provost ITM SLS Baroda University Gujarat Vadodara India Department of CSE GITAM School of Technology GITAM University Bengaluru India Department of Computer Science and Engineering Koneru Lakshmaiah Education Foundation Andhra Pradesh Vaddeswaram Guntur India

Breast and cervical cancers account for more than 85 percent of all cancer-related fatalities in developing nations, according to the World Cancer Research Fund. As a result, breast and cervical cancer have become one of the leading causes of mortality among women worldwide. This field is still in its infancy, with only a few studies in gynaecology and computer science looking into the detection of breast and cervical cancer. According to the researchers, medical records and early testing from individuals with breast and cervical cancer will be used in this study to determine the prognosis of those suffering from the diseases. To assess our cervical cancer predictions, we employed machine learning models such as Optimized Hybrid Ensemble Classifier (OHEC), which were trained on patient behavior and variables revealed to be associated with patient behavior. The datasets in this study have a substantial number of missing values, and the distribution of those values has been altered as a function of the missing values. OHEC classifier performance has been shown to improve when the number of features is reduced and the problem of high-class imbalance is resolved, because the accuracy, sensitivity, and specificity of the classifier, as well as the number of false positives, were used to demonstrate the success of feature selection in the suggested model's predictive analysis. This has been demonstrated through the use of numerous tests involving categorization challenges. The study underscores the critical significance of early detection and prognosis in combating breast and cervical cancers, which remain leading causes of mortality worldwide. Through the utilization of machine learning models like the OHEC, the authors have demonstrated the potential for improved predictive accuracy and clinical outcomes. The findings highlight the importance of addressing challenges such as missing data and class imbalance in enhancing the performance of predictive models for effective

关键词： Diseases

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Coexistence of Distributed Sensing and Ultra-simple Coherent RoF based Front-haul for Radio Access Network

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Journal of Lightwave technology 2025年第12期43卷 5669-5675页

作者： Liu, Maoqi Wang, Jingchuan Liu, Chen Yu, Changyuan Lu, Chao Huazhong University of Science and Technology National Engineering Laboratory for Next Generation Internet Access System School of Optical and Electronic Information Wuhan430074 China The Hong Kong Polytechnic University Photonics Research Institute Department of Electrical and Electronic Engineering Hong Kong

The radio access network requires high-speed transmission and multifunctionality to support the increasing demand for advanced communication services. Radio-over-fiber (RoF) technology fulfills these requirements by enabling the delivery of millimeter-wave (MMW) band wireless signals via optical fiber front-haul. This paper presents an ultra-simple RoF system that achieves the coexistence of distributed sensing and telecommunication. A commercially available coherent modulator achieves signal modulation and remote up-conversion by the beat between the residual carrier and the modulated radio signal. The linear-frequency modulated carrier enables distributed sensing while simultaneously serving as the beat tone of RoF communication, showcasing the potential for integrated sensing and communication (ISAC) applications in next-generation radio access networks. We demonstrate the sensing and transmission performance over a 10-km fiber link and a 1-m wireless MMW channel. The system achieves a distributed sensing detection sensitivity of 28 pΕ/√ Hz and supports 1.6 GBaud 16QAM radio transmission in the Ka-band of 28 GHz. © 1983-2012 IEEE.

关键词： Radio access networks

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Multi‐granularity re‐ranking for visible‐infrared person re‐identification

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CAAI Transactions on Intelligence technology 2023年第3期8卷 770-779页

作者： Yadi Wang Hongyun Zhang Duoqian Miao Witold Pedrycz Department of Computer Science and Technology Tongji UniversityShanghaiChina Key Laboratory of Embedded System and Service Computing Ministry of EducationShanghaiChina Department of Electrical and Computer Engineering University of AlbertaEdmontonAlbertaCanada System Research Institute Polish Academy of SciencesWarsawPoland

Visible‐infrared person re‐identification(VI‐ReID)is a supplementary task of single‐modality re‐identification,which makes up for the defect of conventional re‐identification under insufficient *** is more challenging than single‐modality ReID because,in addition to difficulties in pedestrian posture,camera shoot-ing angle and background change,there are also difficulties in the cross‐modality *** works only involve coarse‐grained global features in the re‐ranking calculation,which cannot effectively use fine‐grained ***,fine‐grained features are particularly important due to the lack of information in cross‐modality re‐*** this end,the Q‐center Multi‐granularity K‐reciprocal Re‐ranking Algorithm(termed QCMR)is proposed,including a Q‐nearest neighbour centre encoder(termed QNC)and a Multi‐granularity K‐reciprocal Encoder(termed MGK)for a more comprehensive feature *** converts the probe‐corresponding modality features into gallery corresponding modality features through modality transfer to narrow the modality *** takes a coarse‐grained mutual nearest neighbour as the dominant and combines a fine‐grained nearest neighbour as a supplement for similarity *** experiments on two widely used VI‐ReID benchmarks,SYSU‐MM01 and RegDB have shown that our method achieves state‐of‐the‐art ***,the mAP of SYSU‐MM01 is increased by 5.9%in all‐search mode.

关键词： computer vision recognition

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