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Free-electron crystals for enhanced X-ray radiation

Light(science & Applications) 2024年第7期13卷 1299-1309页

作者： Lee Wei Wesley Wong Xihang Shi Aviv Karnieli Jeremy Lim Suraj Kumar Sergio Carbajo Ido Kaminer Liang Jie Wong School of Electrical and Electronic Engineering Nanyang Technological University50 Nanyang AvenueSingapore 639798Singapore. Solid State Institute and Faculty of Electrical and Computer Engineering Technion–Israel Institute of TechnologyHaifa 3200003Israel. School of Electrical Engineering Fleischman Faculty of EngineeringTel Aviv UniversityTel Aviv 69978Israel Department of Applied Physics Stanford UniversityStanfordCA 94305USA. Science Mathematics and TechnologySingapore University of Technology and Design8 Somapah RoadSingapore 487372Singapore. Electrical and Computer Engineering Department UCLA420 WestwoodLos AngelesCA 90095USA. Physics and Astronomy Department UCLA475 Portola PlazaLos AngelesCA 90095USA. SLAC National Accelerator Laboratory Stanford University2575 Sand Hill RoadMenlo ParkCA 94025USA

Bremsstrahlung—the spontaneous emission of broadband radiation from free electrons that are deflected by atomic nuclei—contributes to the majority of X-rays emitted from X-ray tubes and used in applications ranging from medical imaging to semiconductor chip ***,we show that the bremsstrahlung intensity can be enhanced significantly—by more than three orders of magnitude—through shaping the electron wavefunction to periodically overlap with atoms in crystalline ***,we show how to shape the bremsstrahlung X-ray emission pattern into arbitrary angular emission profiles for purposes such as unidirectionality and ***,we find that these enhancements and shaped emission profiles cannot be attributed solely to the spatial overlap between the electron probability distribution and the atomic centers,as predicted by the paraxial and nonrecoil theory for free electron light *** work highlights an unprecedented regime of free electron light emission where electron waveshaping provides multi-dimensional control over practical radiation processes like *** results pave the way towards greater versatility in table-top X-ray sources and improved fundamental understanding of quantum electron-light interactions.

关键词： overlap attributed arbitrary

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Improvement of Binocular Reconstruction Algorithm for Measuring 3D Pavement Texture Using a Single Laser Line Scanning Constraint

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computer Modeling in engineering & sciences 2023年第8期136卷 1951-1972页

作者： Yuanyuan Wang RuiWang Xiaofeng Ren Junan Lei Hubei Key Laboratory of Power System Design and Test for Electrical Vehicle Hubei University of Arts and ScienceXiangyang441053China School of Civil Engineering and Architecture Hubei University of Arts and ScienceXiangyang441053China Enterprise Technical Center Xiangyang Road&Bridge Construction Group Co.Ltd.Xiangyang441023China

The dense and accurate measurement of 3D texture is helpful in evaluating the pavement *** form dense mandatory constraints and improve matching accuracy,the traditional binocular reconstruction technology was improved ***,a single moving laser line was introduced to carry out global scanning constraints on the target,which would well overcome the difficulty of installing and recognizing excessive laser ***,four kinds of improved algorithms,namely,disparity replacement,superposition synthesis,subregion segmentation,and subregion segmentation centroid enhancement,were established based on different constraint ***,the improved binocular reconstruction test device was developed to realize the dual functions of 3D texture measurement and precision *** show that compared with traditional algorithms,the introduction of a single laser line scanning constraint is helpful in improving the measurement’s *** various improved algorithms,the improvement effect of the subregion segmentation centroid enhancement method is the *** has a good effect on both overall measurement and single pointmeasurement,which can be considered to be used in pavement function evaluation.

关键词： 3D pavement texture binocular reconstruction algorithm single laser line scanning constraint improved stereo matching

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Post-layout simulation driven analog circuit sizing

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science China(Information sciences) 2024年第4期67卷 289-300页

作者： Xiaohan GAO Haoyi ZHANG Siyuan YE Mingjie LIU David Z.PAN Linxiao SHEN Runsheng WANG Yibo LIN Ru HUANG School of Integrated Circuits Peking University School of Computer Science Peking University Department of Electrical and Computer Engineering University of Texas at Austin Institute of Electronic Design Automation Peking University

Post-layout simulation provides accurate guidance for analog circuit design, but post-layout performance is hard to be directly optimized at early design stages. Prior work on analog circuit sizing often utilizes pre-layout simulation results as the optimization objective. In this work, we propose a post-layoutsimulation-driven(post-simulation-driven for short) analog circuit sizing framework that directly optimizes the post-layout simulation performance. The framework integrates automated layout generation into the optimization loop of transistor sizing and leverages a coupled Bayesian optimization algorithm to search for the best post-simulation performance. Experimental results demonstrate that our framework can achieve over 20% better post-layout performance in competitive time than manual design and the method that only considers pre-layout optimization.

关键词： analog EDA transistor sizing Bayesian optimization post-layout simulation

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Twitter sentiment analysis using conditional generative adversarial network

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International Journal of Cognitive Computing in engineering 2024年第1期5卷 161-169页

作者： Mahalakshmi, V. Shenbagavalli, P. Raguvaran, S. Rajakumareswaran, V. Sivaraman, E. Department of Information Technology Sengunthar College of Engineering Tiruchengode Tiruchengode637205 India Assistant Professor Karunya Institute of Technology and Sciences Coimbatore India Assistant Professor Department of Computational Intelligence School of Computing SRM Institute of Science and Technology SRM Nagar Kattankulathur Kanchipuram Chennai Tamil Nadu 603203 India Assistant Professor Department of Computer Science and Design Erode Sengunthar Engineering College Tamil Nadu Thuduppathi India Department of Electrical and Computer Engineering Curtin University Miri Malaysia

Sentiment analysis, which aims to extract information from textual data indicating people's ideas or attitudes about a particular problem, has developed into one of the most exciting study issues in natural language processing (NLP) with the development of social media. Twitter is a social network with an extensive audience that expresses their thoughts and opinions clearly and readily. Due to the prevalence of slang phrases and incorrect spellings in short phrase styles, Twitter data analysis is more challenging than data analysis from other social networks. Automated feature selection still has several limitations, such as higher computing costs that rise with the number of characteristics. Deep learning, which is self-learned and more accurate at processing vast amounts of data, is utilized to overcome these challenges. This paper introduces a conditional generative adversarial network (GAN) for Twitter sentiment analysis, whereas a convolutional neural network (CNN) has been used to extract traits from Twitter data. Compared to existing works, the proposed work has outperformed in accuracy, recall, precision, and F1 score. The suggested method is the most accurate, with a classification accuracy of 93.33 %. © 2024

关键词： Sentiment analysis

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The Power of Perception in Human-AI Interaction: Investigating Psychological Factors and Cognitive Biases that Shape User Belief and Behavior

arXiv

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arXiv 2024年

作者： Lee, Eunhae Integrated Design and Management Department of Electrical Engineering and Computer Science United States

This thesis investigates the psychological factors that influence belief in AI predictions, comparing them to belief in astrology- and personality-based predictions, and examines the "personal validation effect" in the context of AI, particularly with Large Language Models (LLMs). Through two interconnected studies involving 238 participants, the first study explores how cognitive style, paranormal beliefs, AI attitudes, and personality traits impact perceptions of the validity, reliability, usefulness, and personalization of predictions from different sources. The study finds a positive correlation between belief in AI predictions and belief in astrology- and personality-based predictions, highlighting a "rational superstition" phenomenon where belief is more influenced by mental heuristics and intuition than by critical evaluation. Interestingly, cognitive style did not significantly affect belief in predictions, while paranormal beliefs, positive AI attitudes, and conscientiousness played significant roles. The second study reveals that positive predictions are perceived as significantly more valid, personalized, reliable, and useful than negative ones, emphasizing the strong influence of prediction valence on user perceptions. This underscores the need for AI systems to manage user expectations and foster balanced trust. The thesis concludes with a proposal for future research on how belief in AI predictions influences actual user behavior, exploring it through the lens of self-fulfilling prophecy. Overall, this thesis enhances understanding of human-AI interaction and provides insights for developing AI systems across various applications. © 2024, CC BY.

关键词： Prediction models

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Improved Depth-Aware Circuit Partitioning for Mixed Logic Synthesis

Improved Depth-Aware Circuit Partitioning for Mixed Logic Sy...

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2023 International Symposium of Electronics design Automation, ISEDA 2023

作者： Liao, Chunliu Xiao, Yong Shao, Yun Chu, Zhufei Ningbo University Faculty of Electrical Engineering Computer Science Ningbo315211 China Giga Design Automation Co. Ltd. Shenzhen518055 China

ISBN: (纸本)9798350304510

Mixed logic synthesis takes advantage of distinct logic representations through circuit partitioning, classification and optimization, and merging. How circuits are partitioned plays a significant role in the quality of results (QoR) of mixed logic synthesis. Currently, existing methods employ either a naive or a structurally aware approach. However, the critical path may be destructed by circuit merging due to the critical path segment being disconnected by partitions. To address this issue, we propose an improved depth aware circuit partitioning method for mixed logic synthesis. To be specific, we treat the critical path as an entity and set the partition size dynamically according to the logic depth of the input circuit. Based on the EPFL benchmark suites, XOR-Majority Graph (XMG) achieves a 19% reduction in logic depth with a 6% logic node increase over standard mixed-synthesis. © 2023 IEEE.

关键词： Logic Synthesis

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An Integrated Logic Function Decomposition Flow for XOR-Majority Graphs

An Integrated Logic Function Decomposition Flow for XOR-Majo...

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2023 International Symposium of Electronics design Automation, ISEDA 2023

作者： Ma, Chengyu Xiao, Yong Shao, Yun Chu, Zhufei Ningbo University Faculty of Electrical Engineering Computer Science Ningbo315211 China Giga Design Automation Co. Ltd. Shenzhen518055 China

ISBN: (纸本)9798350304510

Logic function decomposition is critical to logic synthesis. In this paper, we propose an integrated logic function decomposition flow, which consists of disjoint support decomposition, exact synthesis, Shannon decomposition, and the recently proposed majority-of-three (MAJ) decomposition. Through this process, the logic function can be decomposed into any directed acyclic graph (DAG). An experimental evaluation shows that our algorithm leads to better XOR-majority graphs (XMGs) compared to state-of-the-art algorithms. Our experiments show that the proposed method achieves an average of 5% and 6% reduction in the lookup tables (LUTs) size/depth product applied to the EPFL arithmetic and random control benchmarks after LUT mapping, respectively. © 2023 IEEE.

关键词： Table lookup

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BHJO: A Novel Hybrid Metaheuristic Algorithm Combining the Beluga Whale, Honey Badger, and Jellyfish Search Optimizers for Solving engineering design Problems

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computer Modeling in engineering & sciences 2024年第10期141卷 219-265页

作者： Farouq Zitouni Saad Harous Abdulaziz S.Almazyad Ali Wagdy Mohamed Guojiang Xiong Fatima Zohra Khechiba Khadidja Â Kherchouche Department of Computer Science and Information Technology Kasdi Merbah UniversityP.O.Box 30000OuarglaAlgeria Department of Computer Science College of Computing and InformaticsUniversity of SharjahP.O.Box 27272SharjahUnited Arab Emirates Department of Computer Engineering College of Computer and Information SciencesKing Saud UniversityP.O.Box 51178Riyadh11543Saudi Arabia Operations Research Department Faculty of Graduate Studies for Statistical ResearchCairo UniversityGiza12613Egypt Applied Science Research Center Applied Science Private UniversityAmman11937Jordan Guizhou Key Laboratory of Intelligent Technology in Power System College of Electrical EngineeringGuizhou UniversityGuiyang550025China

Hybridizing metaheuristic algorithms involves synergistically combining different optimization techniques to effectively address complex and challenging optimization *** approach aims to leverage the strengths of multiple algorithms,enhancing solution quality,convergence speed,and robustness,thereby offering a more versatile and efficient means of solving intricate real-world optimization *** this paper,we introduce a hybrid algorithm that amalgamates three distinct metaheuristics:the Beluga Whale Optimization(BWO),the Honey Badger Algorithm(HBA),and the Jellyfish Search(JS)*** proposed hybrid algorithm will be referred to as *** this fusion,the BHJO algorithm aims to leverage the strengths of each *** this hybridization,we thoroughly examined the exploration and exploitation capabilities of the BWO,HBA,and JS metaheuristics,as well as their ability to strike a balance between exploration and *** meticulous analysis allowed us to identify the pros and cons of each algorithm,enabling us to combine them in a novel hybrid approach that capitalizes on their respective strengths for enhanced optimization *** addition,the BHJO algorithm incorporates Opposition-Based Learning(OBL)to harness the advantages offered by this technique,leveraging its diverse exploration,accelerated convergence,and improved solution quality to enhance the overall performance and effectiveness of the hybrid ***,the performance of the BHJO algorithm was evaluated across a range of both unconstrained and constrained optimization problems,providing a comprehensive assessment of its efficacy and applicability in diverse problem ***,the BHJO algorithm was subjected to a comparative analysis with several renowned algorithms,where mean and standard deviation values were utilized as evaluation *** rigorous comparison aimed to assess the performance of the BHJOalgorithmabout its counterparts,shedd

关键词： Global optimization hybridization of metaheuristics beluga whale optimization honey badger algorithm jellyfish search optimizer chaotic maps opposition-based learning

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Light Shift Detection Using a Multiple Photodetection Method Suitable for a Chip-Scale Atomic Clock

Light Shift Detection Using a Multiple Photodetection Method...

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IEEE International Frequency Control Symposium

作者： Masahiro Fukuoka Shigeyoshi Goka Department of Electrical Engineering and Computer Science Graduate School of System Design Tokyo Metropolitan University Tokyo Japan

SummaryIn this study, we demonstrated light shift detection in a running atomic clock using the multi-photodetection method. This method enables the observation of atomic resonances with different intensities using the intensity distribution of the laser beam. As it requires only two photodiodes to detect light shifts, it is easily applicable to miniature vapor-cell-based atomic clocks such as chip-scale atomic clocks and miniature atomic clocks.

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DENSE-Guided Deep Motion Networks Accounted by Large Rotations to Improve Myocardial Strain Analysis from Routine Cine MRI 22

DENSE-Guided Deep Motion Networks Accounted by Large Rotatio...

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22nd IEEE International Symposium on Biomedical Imaging, ISBI 2025

作者： Lei, Pengcheng Xing, Jiarui Fang, Faming Epstein, Frederick H. Zhang, Miaomiao University of Virginia Department of Electrical and Computer Engineering United States School of Computer Science and Technology East China Normal University Shanghai China University of Virginia Health System Department of Biomedical Engineering United States

ISBN: (纸本)9798331520526

Myocardial strain imaging provides a valuable tool for detecting subclinical left ventricular (LV) dysfunction and adding prognostic value in assessing various types of heart disease. Recent studies have utilized highly accurate strain-dedicated techniques, such as displacement encoding with stimulated echoes (DENSE), to train a deep learning (DL) framework to predict the myocardial displacements/deformations from routine cine balanced steady state free precession (bSSFP) images. However, these methods have shown limited performance in capturing the large rotational motion of the myocardium associated with twist and torsion over time, which are important aspects of myocardial mechanics. To address this gap, this paper introduces a novel DENSE-guided DL network that explicitly accounts for large rotational motion to further improve strain analysis of standard cine bSSFP images. Specifically, our proposed network includes two key components: (i) a time-series rotation estimation network employing a 3D convolutional encoder-decoder architecture to model the large rotational dynamics of the LV myocardium over time, and (ii) a radial motion prediction network based on deformable image registration. The output of these two sub-networks was integrated and refined through a fusion network to predict the final myocardial displacements, supervised by DENSE ground truth. Experimental results show that our method improves the accuracy of myocardial strain with effectively captured large rotations. © 2025 IEEE.

关键词： Rotation

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