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20th International Multi-Conference on Systems, Signals and Devices, SSD 2023

作者： Kahouli, Oumayma Hafsa, Mariem Hellara, Hiba Bennour, Imed Eddine Essoukri Ben Amarax, Najoua Kanoun, Olfa University of Sousse National Engineering School of Sousse Department of Computer Science Sousse4023 Tunisia National Engineering School of Sousse Laboratory of Advanced Technology and Intelligent Systems Tunisia Technische Universität Chemnitz Laboratory of Measurement and Sensor Technology Chemnitz Germany University of Sfax Laboratory of Signals Systems Artificial Intelligence and Networks Digital Research Center of Sfax Tunisia

ISBN: (纸本)9798350332568

Electrical Impedance Tomography (EIT) is a clinical imaging technique that gained a lot of attention because it is a non-invasive and radiation-free method. To obtain an inner image of the domain under study, a specific number of electrodes is attached to the surface of the object, then through a pair of electrodes, a low alternative current is injected. Potentials produced by this injection are measured with the remaining electrodes. Based on these boundary voltages measurements, the inner conductivity can be inferred, thus the image is reconstructed. The focus of this paper is to overcome the major weakness of the EIT image reconstruction technique, which is the low spatial resolution of the reconstructed images caused by the non-linearity of EIT inverse problem. This paper considers this problem, an optimization problem that is solved using the Particle Swarm Optimization (PSO) meta-heuristic. A variant of the standard PSO is proposed and validated, first on a circular mesh composed of 686 triangles then on a lung mesh composed of 2707 triangles. © 2023 IEEE.

关键词： Electrodes

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Quantum Image Visualizer: Visual Debugging of Quantum Image Processing Circuits

arXiv

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arXiv 2025年

作者： Heim, Anja Lang, Thomas Gall, Alexander Gröller, Eduard Heinzl, Christoph Fraunhofer Institute of Integrated Circuits IIS Division Development Center X-ray Technology Germany University of Passau Faculty of Computer Science and Mathematics Germany TU Wien Institute of Visual Computing & Human-Centered Technology VRVis Research Center Austria

Quantum computing is an emerging field that utilizes the unique principles of quantum mechanics to offer significant advantages in algorithm execution over classical approaches. This potential is particularly promising in the domain of quantum image processing, which aims to manipulate all pixels simultaneously. However, the process of designing and verifying these algorithms remains a complex and error-prone task. To address this challenge, new methods are needed to support effective debugging of quantum circuits. The Quantum Image Visualizer is an interactive visual analysis tool that allows for the examination of quantum images and their transformation throughout quantum circuits. The framework incorporates two overview visualizations that trace image evolution across a sequence of gates based on the most probable outcomes. Interactive exploration allows users to focus on relevant gates, and select pixels of interest. Upon selection, detailed visualizations enable in-depth inspection of individual pixels and their probability distributions, revealing how specific gates influence the likelihood of pixel color values and the magnitude of these changes. An evaluation of Quantum Image Visualizer was conducted through in-depth interviews with eight domain experts. The findings demonstrate the effectiveness and practical value of our approach in supporting visual debugging of quantum image processing circuits. © 2025, CC BY-NC-SA.

关键词： Distribution functions

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Spatial variations of nutrient and trace metal concentrations in macroalgae across blue carbon habitats of the Saudi Arabian Red Sea

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science of the Total Environment 2024年 956卷 177197页

作者： Cai, Chunzhi Anton, Andrea Duarte, Carlos M. Agusti, Susana Ocean College Zhejiang University Zhoushan316000 China Ocean Research Center of Zhoushan Zhejiang University Zhoushan316021 China Marine Science Program Biological and Environmental Science and Engineering Division King Abdullah University of Science and Technology Thuwal 23955-6900 Saudi Arabia Mediterranean Institute for Advanced Studies Illes Balears Esporles07190 Spain

Macroalgae play a crucial role in blue carbon ecosystems, yet their elemental compositions in the Red Sea are not well documented. This study examined the concentrations of 22 elements in 161 macroalgae blade samples from 19 species (5 unidentified) across 3 phyla in the Saudi Arabian Red Sea. Macroalgae blades collected from coral reef habitats exhibited higher concentrations of K, As, and Sr compared to those from seagrass meadows, but had lower levels of total nitrogen (TN), Na, Mg, Al, P, S, Cr, Mn, Fe, and Zn. These differences may be attributed to the limited or absent sediment in coral reef habitats, as sediment in seagrass meadows acts as a trap for heavy metals, influencing element accumulation. In the Southern Red Sea, macroalgae blades showed lower Sr levels but higher total organic carbon (TOC), TN, P, and Cd than those in the North, a trend influenced by nutrient inflows from the Indian Ocean and the semi-enclosed structure of the Red Sea. The study found that macroalgae blades had lower mean TOC and TN content than seagrass and mangrove leaves from the same research cruises but higher levels of Al, Cr, Ni, Cu, Zn, As, Mo, Cd, and Pb. Among the surveyed red, green, and brown macroalgae blades, Halymenia sp., Caulerpa taxifolia, and Dictyota sp. had the highest TOC, TN, and P contents, while Amphiroa fragilissima, Udotea flabellum, and Padina sp. had higher trace metal contents. Notably, some macroalgae blades, including red macroalgae A. fragilissima, green macroalgae Halimeda tuna, U. flabellum, and brown macroalgae Padina pavonica, Turbinaria ornata, collected from Al Birk, Al Lith, Thuwal, Yanbu, and Al Wajh exhibited concerning levels of Cr (~10.9 mg kg−1) and Ni (~27.2 mg kg−1), surpassing toxicity thresholds. These findings emphasize the urgent need for effective pollution mitigation measures to protect these marine ecosystems. © 2024 Elsevier B.V.

关键词： Heavy metals

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Decoupling the orientation dependence of deformation-induced martensitic transformation via single-crystal micropillar compression

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Journal of Materials science & Technology 2026年 244卷 80-87页

作者： Guosheng Sun Shilong Lv Yunfei Zhang Lirong Xiao Yong Peng Yuntian Zhu Kehong Wang Jizi Liu School of Materials Science and Engineering Nanjing University of Science and Technology Nanjing 210094 China Center of Analytical Facilities Nanjing University of Science and Technology Nanjing 210094 China Department of Materials Science and Engineering Hong Kong Institute for Advanced Study College of Science and Engineering City University of Hong Kong Kowloon 999077 Hong Kong China Mechanical Behavior Division of Shenyang National Laboratory for Materials Science City University of Hong Kong Kowloon 999077 Hong Kong China Nanjing Research Center for Biomedical Electron Microscopy (NRC-BEM) Nanjing Drum Tower Hospital Medical School Nanjing University Nanjing 210093 China

This study explores the significant orientation dependence of deformation-induced martensitic transformation. By employing single crystalline micropillar compression, three typical low-index crystallographic orientations were selected to examine their influence on the martensitic transformation of metastable austenitic stainless steel. Results demonstrate that the [011] orientation significantly inhibits the formation of α'-martensite, whereas the [001] and [111] orientations more effectively facilitate phase transformation, which is closely related to the transformation mechanisms. Specifically, the [001] orientation, which is prone to stacking fault formation, promotes martensitic transformation significantly with the aid of ε-martensite and the decreased effective stacking fault energy during compression. Meanwhile, the [111] oriented pillars demonstrate the highest yield strength, with shear deformation responsible for the relatively high fraction of α'-martensite. Additionally, the non-Schmid behavior occurred in the [011]- and [111]- oriented micropillars were found and discussed. This research advances the understanding of orientation-dependent martensitic transformation and provides an optional way to tailor the Transformation-induced plasticity effect via grain orientation engineering.

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Synergistic improvements of strength and ductility of laser powder bed fusion Inconel 718 with higher carbon content at 650 °C by adding yttrium

引用

Materials science and engineering: A 2025年 941卷

作者： Chen, Ruizhi Zhou, Lin Zhao, Xiangyu Zhang, Huan Lv, Peisen Wu, Di Liang, Jingjing Liu, Lirong Li, Jinguo School of Materials Science and Engineering Shenyang University of Technology Liaoning Shenyang110870 China Shi-changxu Innovation Center for Advanced Materials Superalloys Division Institute of Metal Research Chinese Academy of Sciences 72 Wenhua Road Shenyang110016 China

Nickel-based superalloys prepared by laser powder bed fusion (LPBF) typically exhibit poor mechanical properties at intermediate or high temperatures, particularly in terms of the strength-ductility balance, which limits their application in the aerospace field. Therefore, achieving a better match between strength and ductility under intermediate-temperature serving conditions is crucial for the development of LPBF nickel-based superalloys. This study aims to enhance the strength and ductility at 650 °C by designing the addition of Y in Inconel 718 alloy (IN718) with higher carbon content. In this paper, three IN718 alloys with different Y contents (0, 0.06, 0.34 wt%) were designed, and the effects of Y on the formability, microstructure and mechanical properties were investigated. Results indicated that the addition of a trace amount of Y (0.06 wt %) did not affect the formability of the alloy. However, as the solidification temperature range of the alloy widened by increasing Y content, solidification cracks in grain boundaries formed in the alloy with 0.34 wt% Y. Additionally, the strong affinity of Y to oxygen led to the formation of multi-scale oxides during the LPBF alloy process, which reduced grain size, weakened texture strength, and decreased dislocation density. Tensile tests showed that the ultimate tensile strength of the 0.06Y-IN718 alloy reached 1037 MPa at 650 °C. Due to the addition of Y element, the elongation of 0.06Y-IN718 alloy is 25 % at 650 °C, which is 233.3 % higher than that of 0Y-IN718 alloy and exceeds that of cast and wrought IN718 alloy. In this study, a new composition optimization strategy is proposed, which provides a theoretical basis for the industrial application of high-performance nickel-based superalloys produced by LPBF. © 2025 Elsevier B.V.

关键词： Tensile testing

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Melanoma Detection using advanced Deep Neural Network

Melanoma Detection using Advanced Deep Neural Network

引用

International Conference on Energy, Power and Environment: Towards Sustainable Growth (ICEPE)

作者： Pallabi Sharma Anmol Gautam Rajashree Nayak Bunil Kumar Balabantaray Computer Science and Engineering National Institute of Technology Meghalaya Shillong India Computer Science and Engineering NIT Meghalaya Shillong India Center for Data Science JIS Institute of Advanced Studies and Research Kolkata

Melanoma is a type of skin cancer that starts in the cells (melanocytes) that govern the color of your skin. Melanoma is the most lethal one among all other skin diseases and the only reason for 77% deaths due to skin cancer. The best way to reduce these deaths is to detect cancer at its early stages so it can be treated and cured with minor treatment or surgeries. To speed up and improve the process of early detection, we propose an automatic classification method for melanoma cancer using an advanced deep neural network. Deep learning models require a large dataset to work efficiently, but due to limited time and the heavy workload of doctors, there is a lack of annotated skin can-cer images. Therefore, the proposed model introduces adversarial training for achieving better accuracy even with a small amount of data. The model removes unnecessary details and noise from the image and amplifies the depth and gradient in the dimensions and the shade of the image. This proposed adversarial method uses the gradients of the loss with respect to the input image to create a new adversarial example image that maximizes the loss for an input image. The synthetically generated images are used in the classification system for training and testing purposes. A comparative analysis of training with an adversarial approach and without an adversarial approach on different pre-trained models, namely VGG16, VGG19, Densenet121, and Resnet101, is also introduced in this work. ResNet101 with adversarial training has shown a state-of-the-art accuracy performance of 84.77% for melanoma classification. Therefore, the proposed approach can be considered an efficient method for classifying benign and malignant melanoma.

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A MgNO Method for Multiphase Flow in Porous Media

arXiv

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arXiv 2024年

作者： Liu, Xinliang Yang, Xia Zhang, Chen-Song Zhang, Lian Zhao, Li Computer Electrical and Mathematical Science and Engineering Division King Abdullah University of Science and Technology Thuwal Saudi Arabia Xiangtan University Hunan China LSEC ICMSEC Academy of Mathematics and System Sciences Chinese Academy of Sciences University of Chinese Academy of Sciences China Shenzhen International Center for Industrial and Applied Mathematics Shenzhen Research Institute of Big Data China

This research investigates the application of Multigrid Neural Operator (MgNO), a neural operator architecture inspired by multigrid methods, in the simulation for multiphase flow within porous media. The architecture is adjusted to manage a variety of crucial factors, such as permeability and porosity heterogeneity. The study extendes MgNO to time-dependent porous media flow problems and validate its accuracy in predicting essential aspects of multiphase flows. Furthermore, the research provides a detailed comparison between MgNO and Fourier Neural Opeartor (FNO), which is one of the most popular neural operator methods, on their performance regarding prediction error accumulation over time. This aspect provides valuable insights into the models' long-term predictive stability and reliability. The study demonstrates MgNO's capability to effectively simulate multiphase flow problems, offering considerable time savings compared to traditional simulation methods, marking an advancement in integrating data-driven methodologies in geoscience applications. © 2024, CC BY.

关键词： Porous materials

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The Transition of Threshold Voltage Shift of Al2O3/Si3N4AlGaN/GaN MIS-HEMTs Under Negative Gate Bias Stress From DC to AC

引用

IEEE Transactions on Electron Devices 2024年第3期71卷 1792-1797页

作者： Lee, Ya-Huan Chang, Kai-Chun Tai, Mao-Chou Wang, Yu-Xuan Lin, Hsin-Ni Yeh, Yu-Hsuan Kuo, Hung-Ming Tsai, Xin-Ying Lee, Jason Huang, I-Yu Chang, Ting-Chang Sze, Simon National Sun Yat-sen University Department of Physics Kaohsiung80424 Taiwan National Sun Yat-sen University Department of Photonics Kaohsiung80424 Taiwan Institute of Electronics National Yang Ming Chiao Tung University Hsinchu30010 Taiwan Institute of Electronics National Yang Ming Chiao Tung University Department of Materials and Optoelectronic Science Hsinchu30010 Taiwan Boston University Department of Computer Science BostonMA02215 United States National Sun Yat-sen University College of Semiconductor and Advanced Technology Research Kaohsiung80424 Taiwan National Sun Yat-sen University Department of Physics Center of Crystal Research Kaohsiung80424 Taiwan National Chiao-Tung University Department of Electronics Engineering Institute of Electronics Hsinchu30010 Taiwan

In this study, the reliability issues are discussed under dc and ac negative gate bias stress (ac-NGBS) in Al2O3/Si3N4 metal insulator semiconductor high electron mobility transistors (MIS-HEMTs). Converse degradation between these two stress conditions is discovered. The holes generated by trap-assisted thermionic field emission (TA-TFE) are trapped into the Al2O3 layer, so that the threshold voltage (Vth) decreases under dc negative gate bias stress (dc-NGBS). Vth increases because of the hot electrons injected into the GaN layer, while the device is turned on quickly under ac-NGBS. In addition, the degradation mechanisms under dc-NGBS and ac-NGBS are confirmed by the OFF-state gate and drain leakages, respectively. Silvaco TCAD is used to validate the degradation mechanism under ac-NGBS. Finally, the characteristics of the Vth shift transition from dc to ac NGBS are discussed. © 1963-2012 IEEE.

关键词： Threshold voltage

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Stability Criteria for Neural Networks with Stochastic Impulsive Intensity and Impulsive Density

Stability Criteria for Neural Networks with Stochastic Impul...

引用

Neuromorphic Computing (ICNC), International Conference on

作者： Hao Deng Jingxin Liu Jun Peng Yingxu Wang Fei Chang School of Computer Science and Engineering Chongqing University of Science and Technology Chongqing China College of Electronic and Information Engineering Southwest University Chongqing China Center for Applied Mathematics of Guangxi Guangxi Minzu University Nanning China School of Mathematics and Physics Sciences Chongqing University of Science and Technology Chongqing China Chongqing Research Institute of Intelligent Mathematics and Autonomous AI (RI-IM·AI*) Chongqing China

ISBN: (数字)9798331508661

ISBN: (纸本)9798331508678

This paper studies stability conditions for neural networks with stochastic impulsive intensity and impulsive density. Firstly, the pth moment exponential stability conditions are given, where the impulsive intensities of impulsive neural networks are independent and identically distributed, and the impulsive sequence is defined by impulsive density. Then, taking a linear time-varying impulsive system as an example, it is shown that impulsive sequence defined by average impulsive interval is sometime insufficient in terms of stabilizing such linear time-varying systems. Finally, two examples are presented to verify that impulsive density method is more effective and universal than average impulsive interval method when dealing with time-varying systems.

关键词： Sufficient conditions Stability Neuromorphic engineering Neural networks Stability criteria Control theory Time-varying systems Numerical stability

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Rational Design of Hybrid Electrolyte for All-Solid-State Lithium Battery Based on Investigation of Lithium-Ion Transport Mechanism

SSRN

引用

SSRN 2024年

作者： Park, Jinkyu Shim, Yoonsu Chang, Joon Ha Kim, Se-Hee Kang, Yongku Lee, Jin Woong Jung, Dae Soo Yuk, Jong Min Lee, Chan-Woo Suk, Jungdon Advanced Energy Materials Research Center Advanced Materials Division Korea Research Institute of Chemical Technology 141 Gajeong-ro Yuseong-gu Daejeon34114 Korea Republic of Department of Materials Science and Engineering Korea Advanced Institute of Science and Technology 291 Daehak-ro Yuseong-gu Daejeon34141 Korea Republic of Department of Advanced Materials University of Science and Technology 217 Gajeong-ro Yuseong-gu Daejeon34113 Korea Republic of Research Institute of Industrial Science and Technology Korea Republic of Energy Storage Materials Center Korea Institute of Ceramic Engineering and Technology Gyeongnam Jinju52851 Korea Republic of Computational Science & Engineering Laboratory Korea Institute of Energy Research 152 Gajeong-ro Yuseong-Gu Daejeon34129 Korea Republic of

Lithium all-solid-state batteries (ASSBs) are a promising technology for achieving high energy density, long cycle life, and safe rechargeable battery systems. Among these, Li ASSBs using solid polymer electrolytes (SPEs) have gained attention owing to their processability, lightweight nature, flexibility, and favorable electrode contacts. However, SPEs have low ionic conductivity, low Li+ transference number, and lack mechanical strength, limiting cell performance. Therefore, the present study focuses on the development of hybrid polymer electrolytes (HPEs) by incorporating Li1+xAlxTi2-x(PO4)3 (LATP) of Li/Na superionic conductor-type materials into SPEs. The HPEs with LATP 10 wt% exhibited significant improvements with an ionic conductivity of 7.23 × 10-4 S cm-1 at 45 ℃ and a Li+ transference number of 0.61. Density functional theory calculations supported the enhanced Li-ion migration through the polymer-LATP interface achieved by the optimized LATP content. The addition of LATP particles enhanced the mechanical strength of the electrolytes, effectively suppressing dendrite growth, resulting in a 65.42% capacity retention after 320 cycles, highlighting the crucial role of high-performance HPEs in advanced ASSBs. By addressing the limitations of SPEs, HPEs offer promising opportunities to unlock the full potential of solid-state battery technologies for various energy storage systems. © 2024, The Authors. All rights reserved.

关键词： Ionic conductivity

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