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6th International Conference on Cybernetics and Intelligent System, ICORIS 2024

作者： Setiawan, Devin Karnyoto, Andrea Stevens Intan, Indo Pardamean, Bens Department of Electrical Engineering and Computer Science University of Kansas Lawrence United States Bioinformatics and Data Science Research Center Bina Nusantara University Jakarta Indonesia Department of Informatics Engineering Universitas Dipa Makassar Makassar Indonesia Computer Science Department BINUS Graduate Program Computer Science Program Bina Nusantara University Jakarta Indonesia

ISBN: (纸本)9798331539603

Breast cancer is an occurrence of cancer that attacks breast tissue and is the most common cancer among women worldwide, affecting one in eight women. In this modern world, breast cancer image classification simplifies the process of analyzing, providing objective and accurate results. By leveraging machine learning algorithms and computer vision techniques, we developed breast cancer detection. The dataset is histopathology dataset from BreakHis and UNHAS Hospital. We chose the ConvNeXt-Tiny model then modified the classifier head as the proposed method. Before the dataset is processed by the model, we augment the images by applying random horizontal and vertical flips, adjustments to brightness, contrast, saturation, and hue using color jitter. The augmentation process simulates real-world variance and enhances the model's ability to generalize to unseen data. Our proposed model gained better performance (accuracy, F1-Score) results compared two other techniques to VGG16 and SVM. According to our experiments, the F1-Score for the ConvNeXt-Tiny model with classifier head modification is higher at 0.9516, than the gain for VGG16 at 0.9292, and the gain for the SVM at 0.83. © 2024 IEEE.

关键词： Lung cancer

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A Study on the Performance Improvement of Axial Flux Permanent Magnet Machines Based on Stator and Rotor Design Modifications

A Study on the Performance Improvement of Axial Flux Permane...

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2024 IEEE Energy Conversion Congress and Exposition, ECCE 2024

作者： Yun, Jangho Grainger, Brandon Ohodnicki, Paul University of Pittsburgh Department of Mechanical Engineering and Materials Science PittsburghPA United States University of Pittsburgh Department of Electrical and Computer Engineering PittsburghPA United States

ISBN: (纸本)9798350376067

Axial flux permanent magnet (AFPM) machines have technological competitiveness for electric propulsion systems that require compact structures and high-power density. However, challenging design and manufacturing problems that reduce the cost competitiveness cause designers to limit designable variables. In this paper, the effects of slot/pole combination, semi-closed slot, magnetic wedge, and segmented PM on performance in double-sided rotor and double-sided stator geometries designed with stator open slots were investigated through 3-D finite element analysis (FEA). FEA results show that the design variables have a significant impact on torque, torque ripple, and losses. Semi-closed slots or magnetic wedges reduce PM losses for each open slot model by more than 80%, significantly reducing losses compared to segmented PMs, and also reducing torque ripple. As an alternative to stator design modification, results indicate the open slot model can be considered with a slot/pole combination for low cogging torque to reduce torque ripple and segmented PMs to reduce PM losses. © 2024 IEEE.

关键词： Stators

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MnBi IPMSM and PMASynRM Torque Density Limitations due to Temperature-Dependent Demagnetization

MnBi IPMSM and PMASynRM Torque Density Limitations due to Te...

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2024 IEEE Energy Conversion Congress and Exposition, ECCE 2024

作者： Brody, Ryan Ohodnicki, Paul Grainger, Brandon University of Pittsburgh Department of Electrical and Computer Engineering PittsburghPA United States University of Pittsburgh Department of Mechanical Engineering and Materials Science PittsburghPA United States

ISBN: (纸本)9798350376067

Permanent magnets (PM) demagnetization occurs when applying external fields opposite the PM's polarity. To a certain degree, this effect is reversible and useful in high-speed permanent magnet synchronous motors (PMSMs) by enabling flux weakening control and reluctance torque. However, relatively large external fields cause irreversible demagnetization, damaging the magnet and, thus, the motor. In PMSMs, irreversible demagnetization can significantly limit torque density, especially when using rare earth (RE) free PMs with low coercivity. Irreversible demagnetization risk can be controlled in motor designs to increase torque density if the motor drive is designed appropriately, but the impact of this relationship has yet to be quantified statistically. Therefore, this paper does so by designing and comparing PMSMs with varying demagnetization risk and comparing their performance in terms of torque density and short circuit current. The motor designs presented here are based on the specifications for the 2011 Nissan Leaf, and electric vehicles (EVs) contribute significantly to RE PM demand by typically using interior permanent magnet motors (IPMSMs) with RE PMs. Therefore, the authors also assess demagnetization risk during EV drive cycles for the MnBi motor designs presented here. Because demagnetization effects are particularly limiting in permanent magnet assisted synchronous reluctance motors (PMASynRM) that use MnBi PMs, this paper focuses on various MnBi PMASynRM designs and compare them to a MnBi IPMSM design previously published by the authors. © 2024 IEEE.

关键词： Demagnetization

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Retinal Blood Vessel Tracking and Diameter Estimation via Gaussian Process With Rider Optimization Algorithm

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IEEE Journal of Biomedical and Health Informatics 2024年第3期28卷 1173-1184页

作者： Ahmad, Nehal Lai, Kuan-Ting Tanveer, M. Indian Institute of Technology Indore Simrol Department of Mathematics Indore453552 India National Taipei University of Technology Department of International Program of Electrical Engineering and Computer Science Taipei106 Taiwan National Taipei University of Technology Department of Electronic Engineering Taipei106 Taiwan

Retinal blood vessels structure analysis is an important step in the detection of ocular diseases such as diabetic retinopathy and retinopathy of prematurity. Accurate tracking and estimation of retinal blood vessels in terms of their diameter remains a major challenge in retinal structure analysis. In this research, we develop a rider-based Gaussian approach for accurate tracking and diameter estimation of retinal blood vessels. The diameter and curvature of the blood vessel are assumed as the Gaussian processes. The features are determined for training the Gaussian process using Radon transform. The kernel hyperparameter of Gaussian processes is optimized using Rider Optimization Algorithm for evaluating the direction of the vessel. Multiple Gaussian processes are used for detecting the bifurcations and the difference in the prediction direction is quantified. The performance of the proposed Rider-based Gaussian process is evaluated with mean and standard deviation. Our method achieved high performance with the standard deviation of 0.2499 and mean average of 0.0147, which outperformed the state-of-the-art method by 6.32%. Although the proposed model outperformed the state-of-the-art method in normal blood vessels, in future research, one can include tortuous blood vessels of different retinopathy patients, which would be more challenging due to large angle variations. We used Rider-based Gaussian process for tracking blood vessels to obtain the diameter of retinal blood vessels, and the method performed well on the 'STrutred Analysis of the REtina (STARE) Database' accessed on Oct. 2020 (https://***/~ahoover/stare/). To the best of our knowledge, this experiment is one of the most recent analysis using this type of algorithm. © 2013 IEEE.

关键词： Blood vessels

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A numerical analysis of a high-efficiency solar cell using a DFT explored nontoxic perovskite material 3

A numerical analysis of a high-efficiency solar cell using a...

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3rd International Conference on Advancement in electrical and Electronic engineering, ICAEEE 2024

作者： Islam, Md. Jahidul Cheragee, Sheikh Hasib Tarek, Muhammad Masud Gulshan, Fahmida Department of Materials and Metallurgical Engineering Dhaka1000 Bangladesh Department of Electrical and Electronic Engineering Dhaka1000 Bangladesh State University of Bangladesh Department of Computer Science and Engineering Dhaka1461 Bangladesh

ISBN: (纸本)9798350388282

In recent years, Perovskites have been a very interesting breakthrough in the field of photovoltaics because of their excellent performance with easy and less complex synthesizability, and cost-effectiveness. This instance suggests a uniquely designed solar cell with a novel perovskite, Rb2 NaGaBr6. The perovskite, used as the active layer, is analyzed through the First Principle Density Functional Theory (DFT) calculation, where the cell is simulated by the SCAPS-1D simulation tool showing a power conversion efficiency (PCE) of 26.86% for this single-junction solar cell. In order to achieve optimum efficiency, the effects of defect concentration and the thickness of the absorber layer are examined and adjusted. Here, the influence of the absorber thickness and defect concentration on fill factor, short-circuit current (J sc ), and open-circuit voltage (V oc ) were also examined in addition to their impact on PCE. Based on the insights gathered from the simulation of the designed cell, FTO /SnO 2 /Rb 2 NaGaBr 6 /CuI /W , the best results were obtained at a thickness of 0.8μm. The simulation indicated that J sc =25.02 ∼mA /cm 2 , a fill factor (FF) of 84.01%, and V oc =1.2777 ∼V , that leads to a PCE of 26.86%. © 2024 IEEE.

关键词： Perovskite

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TrueAdaptTM- AI Based Maskless Patterning to Compensate for Die-Shift in Fan-Out Wafer Level Packaging 73

TrueAdaptTM- AI Based Maskless Patterning to Compensate for ...

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73rd IEEE Electronic Components and Technology Conference, ECTC 2023

作者： Sabbir, Golam Sahoo, Krutikesh Sun, Henry Iver, Subramanian Ouyang, Guangqi Wu, Yilin Ucla Department of Materials Science and Engineering United States Ucla Department of Electrical and Computing Engineering United States Ucla Department of Computer Science United States

ISBN: (纸本)9798350334982

TrueAdapt™ offers an attractive solution to fan-out-wafer-level-packaging (FOWLP) and fan-out-panel-level-packaging, which offers significant cost savings as compared to similar bridge connection technology or interposers. Due to die-placement error and shift during molding, die assemblies on FOWLP can have significant die-shift. Design rules must ensure the accommodation of die-shift and as a result fine-pitch patterning is limited. TrueAdapt™ aims to solve that by utilizing in-line characterization of the die shift, generation of a new layout using the measured offsets, and patterning with direct-write lithography for high throughput wafer-level and panel-level fabrication at fine-pitches. In this work we present the fabrication of an assembly of dies interconnected in a daisy chain network with 10 µm pitch wiring on the FlexTrate™, a bio-compatible polydimethylsiloxane (PDMS) based FOWLP architecture. We measure die shift using optical metrology techniques to generate a stitched image of the assembly. The image is then processed using artificial intelligence (AI) computer vision to identify critical features on the dies (which are used to generate die-offsets for each die). Furthermore, we generate a layout based on measured die-shift that adaptively routes the wiring in between dies. Via and metal layers are subsequently patterned using direct-write lithography using a 405 nm lase. Direct-write lithography enables fine-pitch patterning at the wafer/panel level without the need for mask fabrication, promising significant cost savings. We further demonstrate a novel exposure technique based on focal extension that can be utilized to pattern over 100 µm of topography, making this a truly adaptive patterning process. © 2023 IEEE.

关键词： Dies

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Direct ink writing of gradient shear-stiffening elastomer for enhanced toughness and impact resistance

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Journal of Industrial and engineering Chemistry 2025年 149卷 593-603页

作者： Gong, Liping Zhao, Chunyu Lu, Hongda Zhang, Qingtian Chen, Zexin Yang, Junjie Yang, Jinyu Sun, Shuaishuai Du, Haiping Li, Weihua School of Mechanical Materials Mechatronic and Biomedical Engineering University of Wollongong Wollongong2522 Australia CAS Key Laboratory of Mechanical Behaviour and Design of Materials Department of Modern Mechanics University of Science and Technology of China Hefei230027 China School of Electrical Computer and Telecommunication Engineering University of Wollongong Wollongong2522 Australia

Shear-stiffening materials have garnered significant attention due to their inherent ability to rapidly respond to changes in strain rate. However, conventional studies on these materials exhibit limited mechanical performance and insufficient structural design, hindering applications in material science and smart mechatronics. Inspired by the gradient structure of a squid beak, this study uses a direct-ink-writing (DIW) technology to develop a novel gradient shear-stiffening elastomer (GSSE). Comprehensive characterizations were conducted to optimize the printability of the shear-stiffening elastomer under various testing conditions, including rheology, compression, and tension. Additionally, the toughness and impact resistance of the elastomer were systematically investigated. It is demonstrated that the biomimetic GSSE exhibits enhanced flexibility, efficient energy dissipation, and outstanding impact resistance. Consequently, this work advances the field of shear-stiffening elastomers for diverse applications by leveraging the gradient structure design strategy to achieve superior mechanical performance under complex loading conditions. © 2025 The Author(s)

关键词： Strain rate

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Improved Monitoring of the Water-Cooled Upper Shell of an Electric Arc Furnace Using Fiber-Optic Sensors

Improved Monitoring of the Water-Cooled Upper Shell of an El...

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AISTech 2024 Iron and Steel Technology Conference

作者： Mekala, Yeshwanth Reddy Saha, Rony Kumer Inalegwu, Ogbole C. Roman, Muhammad Mumtaz, Farhan Gerald, Rex E. Smith, Jeffrey D. Huang, Jie O’Malley, Ronald J. Department of Materials Science and Engineering Missouri University of Science and Technology RollaMO65409 United States Department of Electrical and Computer Engineering Missouri University of Science and Technology RollaMO65409 United States

ISBN: (纸本)9780930767259

Modern Electric Arc Furnaces (EAF) employ ultra-high-power electrical input to minimize the scrap melting time. Increasing the operating voltage increases arc length and enhances the active power, but radiation energy losses also increase if the arc is exposed to the furnace, resulting in a drop in thermal efficiency and causing hot spots in the furnace. The present work introduces a novel approach using fiber optic sensors to create a real-time, spatially distributed thermal map of the EAF's water-cooled upper shell, which can be helpful in detecting operational anomalies and improving EAF energy efficiency. Lab-scale testing using fiber-optic sensors on a spray-cooled steel plate achieved a remarkable spatial resolution of 2.3mm and a 1Hz data acquisition rate, paving the way for industrial-scale implementation. These sensors, providing reliable spatial temperature measurements, offer early detection of sidewall hot spots and precise adjustments to voltage and burner positioning based on granular data from the scrap melting stages. This study strongly advocates the use of fiber optic sensors in EAFs, would enhance efficiency and safety in steelmaking. © 2024 by the Association for Iron & Steel Technology.

关键词： Fiber optic sensors

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Quantum receiver enhanced by adaptive learning

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Light(science & Applications) 2022年第12期11卷 3080-3086页

作者： Chaohan Cui William Horrocks Shuhong Hao Saikat Guha Nasser Peyghambarian Quntao Zhuang Zheshen Zhang James C.Wyant College of Optical Sciences University of ArizonaTucsonAZ 85721USA Department of Materials Science and Engineering University of ArizonaTucsonAZ 85721USA Department of Electrical and Computer Engineering University of ArizonaTucsonAZ 85721USA Department of Electrical and Computer Engineering University of Southern CaliforniaLos AngelesCA 90089USA Department of Electrical Engineering and Computer Science University of MichiganAnn ArborMI 48109USA

Quantum receivers aim to effectively navigate the vast quantum-state space to endow quantum information processing capabilities unmatched by classical *** date,only a handful of quantum receivers have been constructed to tackle the problem of discriminating coherent *** receivers designed by analytical approaches,however,are incapable of effectively adapting to diverse environmental conditions,resulting in their quickly diminishing performance as the operational complexities ***,we present a general architecture,dubbed the quantum receiver enhanced by adaptive learning,to adapt quantum receiver structures to diverse operational *** adaptively learned quantum receiver is experimentally implemented in a hardware platform with record-high *** the architecture and the experimental advances,the error rate is reduced up to 40%over the standard quantum limit in two coherent-state encoding schemes.

关键词： quantum coherent matched

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Enhanced Bottom Anode Monitoring in DC Electric Arc Furnaces Using Fiber-Optic Sensors

Enhanced Bottom Anode Monitoring in DC Electric Arc Furnaces...

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AISTech 2024 Iron and Steel Technology Conference

作者： Mekala, Yeshwanth Reddy Inalegwu, Ogbole C. Saha, Rony Kumer Mumtaz, Farhan Gerald, Rex E. Smith, Jeffrey D. Huang, Jie O’Malley, Ronald J. Department of Materials Science and Engineering Missouri University of Science and Technology RollaMO65409 United States Department of Electrical and Computer Engineering Missouri University of Science and Technology RollaMO65409 United States

ISBN: (纸本)9780930767259

A pin style bottom anode employs conductive steel rods that serve as the pathway for the high electrical power through rammed refractory at the bottom of a DC Electric Arc Furnace (EAF). Anode wear during operation is important to monitor, as anode replacement is expensive and impacts EAF productivity. Liquid steel penetration into the un-sintered refractory layer can result from rapid electrical power ramp-up, dips in furnace temperature, or operating the anode for too long between EAF campaigns. In extreme cases, the liquid steel may penetrate the bottom of the furnace when anode wear progresses too close to the bottom shell, which is extremely dangerous and must be avoided. The current state of the art for monitoring bottom anode wear employs thermocouples imbedded in the anode pins at points in the anode. However, this approach is not sensitive enough to detect localized damage to the anode, especially when cracking occurs. The present work utilizes fiber optic sensors to monitor the health of the anode, by creating a real-time spatially distributed temperature map of the anode. Unlike the traditional thermocouples, these sensors can be mounted at significantly greater depths, provide distributed temperature measurements, and can withstand temperatures of up to 900°C. Additionally, they are able to perform temperature measurements with a spatial resolution of 1.3 mm at a 5 Hz acquisition rate, providing unprecedented high-density real time monitoring of anode health and increasing the efficiency, and safety of EAF operation. © 2024 by the Association for Iron & Steel Technology.

关键词： Fiber optic sensors

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