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Non-Hermitian chiral degeneracy of gated graphene metasurfaces

Light(Science & Applications) 2023年第5期12卷 766-775页

作者： Soojeong Baek Sang Hyun Park Donghak Oh Kanghee Lee Sangha Lee Hosub Lim Taewoo Ha Hyun Sung Park Shuang Zhang Lan Yang Bumki Min Teun-Teun Kim Department of Mechanical Engineering Korea Advanced Institute of Science and Technology(KAIST)Daehak-ro 291Daejeon 34141Republic of Korea Department of Electrical and Computer Engineering University of Minnesota200 Union street SEMinneapolisMN 55455USA Harvard Institute of Medicine Harvard Medical SchoolHarvard UniversityBrigham and Women's Hospital25 Shattuck StreetBostonMA 02215USA Center for Integrated Nanostructure Physics Institute for Basic Science(IBS)Sungkyunkwan UniversitySeobu-ro 2066Suwon 16419Republic of Korea Samsung Advanced Institute of Technology Samsung ElectronicsSamsung-roSuwon 16678Republic of Korea Department of Physics The University of Hong KongPokfulam RoadHong Kong Special Administrative RegionChina Department of Electrical and Systems Engineering Washington University1 Brookings DriveSaint LouisMO 63130USA Department of Physics Korea Advanced Institute of Science and Technology(KAIST)Daehak-ro 291Daejeon 34141Republic of Korea Department of Physics University of UlsanDaehakroUlsan 44610Republic of Korea Korea Research Institute of Standards and Science(KRISS) Gajeong-ro 267Daejeon 34113Republic of Korea

Non-Hermitian degeneracies,also known as exceptional points(EPs),have been the focus of much attention due to their singular eigenvalue surface ***,as pertaining to a non-Hermitian metasurface platform,the reduction of an eigenspace dimensionality at the EP has been investigated mostly in a passive repetitive ***,we propose an electrical and spectral way of resolving chiral EPs and clarifying the consequences of chiral mode collapsing of a non-Hermitian gated graphene *** specifically,the measured non-Hermitian Jones matrix in parameter space enables the quantification of nonorthogonality of polarisation eigenstates and half-integer topological charges associated with a chiral ***,the output polarisation state can be made orthogonal to the coalesced polarisation eigenstate of the metasurface,revealing the missing dimension at the chiral *** addition,the maximal nonorthogonality at the chiral EP leads to a blocking of one of the cross-polarised transmission pathways and,consequently,the observation of enhanced asymmetric polarisation *** anticipate that electrically controllable non-Hermitian metasurface platforms can serve as an interesting framework for the investigation of rich non-Hermitian polarisation dynamics around chiral EPs.

关键词： structure chiral integer

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Price Estimation of Used Cars Using Machine Learning Algorithms 3rd

Price Estimation of Used Cars Using Machine Learning Algorit...

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3rd EAI International Conference on Cognitive Computing and Cyber Physical systems, IC4S 2022

作者： Valarmathi, B. Gupta, N. Srinivasa Santhi, K. Chellatamilan, T. Kavitha, A. Raahil, Armaan Padmavathy, N. Department of Software and Systems Engineering School of Information Technology and Engineering Vellore Institute of Technology Tamil Nadu Vellore India Department of Manufacturing Engineering School of Mechanical Engineering Vellore Institute of Technology Tamil Nadu Vellore India Department of Analytics School of Computer Science and Engineering Vellore Institute of Technology Tamil Nadu Vellore India Department of Mathematics School of Advanced Sciences Vellore Institute of Technology Tamil Nadu Vellore India Department of Information Technology School of Information Technology and Engineering Vellore Institute of Technology Tamil Nadu Vellore India Department of Electronics and Communication Engineering Vishnu Institute of Technology Andhra Pradesh Bhimavaram India

ISBN: (纸本)9783031289743

In this study, machine learning (ML) techniques are employed to predict used car prices. Several features are used to calculate the price of used cars, but in this paper, we find efficient ways to find the most precise car prices. Despite the fact that there are websites offering this service, they could not employ the most precise prediction system. It is also possible to predict a used car's true market value using a variety of models and techniques. It's important to understand their genuine market value before buying or selling. Both buyers and sellers will be benefitted from these accurate predictions. Support Vector regression, Random Forest regression, and CatBoost regression techniques are used in the proposed system. In the existing method [13], mean absolute error for decision tree regression was 0.6711, which was the least among other algorithms like Linear regression, Lasso regression, Ridge regression, Bayesian Ridge regression, and etc., they used. In the proposed system, mean absolute error (MAE) for Support Vector regression, CatBoost regression and Random Forest regression techniques are 0.1459, 0.1371 and 0.1284 respectively. The prices of second hand/used cars are predicted using the CatBoost regression, Support Vector regression, and Random Forest regression techniques. The accuracy of these algorithms are 86.28%, 85.40% and 87.16%. Among these three algorithms, Random Forest regression gives the least MAE of 0.1317 and the highest accuracy of 87.16%. © 2023, ICST Institute for computer Sciences, Social Informatics and Telecommunications engineering.

关键词： Forecasting

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Development of a VS ultrasound diagnostic system with image evaluation functions 11

Development of a VS ultrasound diagnostic system with image ...

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11th IEEE Global Conference on Consumer Electronics, GCCE 2022

作者： Zhou, Jiayi Koizumi, Norihiro Nishiyama, Yu Tsumura, Ryosuke Tsukihara, Hiroyuki Matsumoto, Naoki The University of Electro-Communications Department of Mechanical and Intelligent Systems Tokyo Japan The University of Electro-Communications Department of Computer and Network Engineering Tokyo Japan Health and Medical Research Institute National Institute of Advanced Industrial Science and Technology Tokyo Japan The University of Tokyo Graduate School of Engineering Tokyo Japan Nihon University Department of Gastroenterology and Hepatology Tokyo Japan

ISBN: (纸本)9781665492324

An inevitable feature of ultrasound-based diagnoses is that the quality of the ultrasound images produced depends directly on the skill of the physician operating the probe. This is because physicians have to constantly adjust the probe position to obtain a cross-section of the target organ, which is constantly shifting due to patient respiratory motions. Therefore, we developed an ultrasound diagnostic robot that works in cooperation with a visual servo system based on deep learning that will help alleviate the burdens imposed on physicians. Two different image processing methods (BiSeNet V2) were used to detect the target kidney location, as well as to evaluate the appropriateness of the obtained ultrasound images (ResNet 50) in developed system. © 2022 IEEE.

关键词： Visual servoing

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Development of Virtual Learning Factory Toolkit for Production engineering Education 13

Development of Virtual Learning Factory Toolkit for Producti...

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13th International DAAAM Baltic Conference and 29th International Baltic Conference, BALTMATTRIB 2021

作者： Mahmood, Kashif Otto, Tauno Kuts, Vladimir Terkaj, Walter Urgo, Marcello Haidegger, Geza Department of Mechanical and Industrial Engineering Tallinn University of Technology Tallinn Estonia STIIMA-CNR Institute of Intelligent Industrial Technologies and Systems for Advanced Manufacturing National Research Council Milan Italy Manufacturing and Production Systems Division Department of Mechanical Engineering Politecnico di Milano Milan Italy SZTAKI – Institute for Computer Science and Control Budapest Hungary

The advent of industry 4.0 and the continuous digitalization of production ask for the enhancement of human skills and competences in the field of information and communication technology (ICT). Therefore, higher education has to keep pace with the global market needs for the necessary ICT skills and the overall understanding of the complexity of industries in 21st century. This paper focuses on the development and integration of Virtual Learning Factory (VLF) tools that can be used in production management and engineering education. The digital tools integrated in VLF toolkit can help students to exploit enabling technologies like simulation and virtual reality in their manufacturing studies and practical projects with industrial companies. © 2021 DAAAM International. All rights reserved.

关键词： engineering education

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Real-time Lightning 3D Imaging and Forecasting Project in Malaysia for Sustainable and Reliable Supply of Energy and Storm Disaster Early Warning 12

Real-time Lightning 3D Imaging and Forecasting Project in Ma...

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12th Asia-Pacific International Conference on Lightning, APL 2023

作者： Morimoto, Takeshi Ahmad, Mohd Riduan Baharuddin, Mohd Zafri Wang, Daohong Yamamoto, Kazuo Kudo, Takeshi Kahtani, Ammar Nasser Al Aziz, Mohamad Zoinol Abidin Abd Akita, Manabu Takayanagi, Yuji Kawasaki, Zen-Ichiro Torii, Tatsuo Kindai University Depertment of Electrical Electronic and Communication Engineering Osaka Japan Melaka Malaysia Universiti Tenaga Nasional Department of Electrical and Electronic Engineering Kajang Malaysia Gifu University Department of Electrical Electronic and Computer Engineering Gifu Japan Chubu University Deptment. of Electrical and Electronic Engineering Aichi Japan Fundamental and Advanced Research Group Otowa Electric Co. Ltd Hyogo Japan Universiti Tenaga Nasional Department of Electrical and Electronics Engineering Kajang Malaysia The University of Electro-Communications Department of Mechanical and Intelligent Systems Engineering Tokyo Japan Osaka University Osaka Japan Research Institute of Nuclear Engineering University of Fukui Fukui Japan

ISBN: (纸本)9781665456852

A joint research project 'real-time lightning 3D imaging and forecasting project for sustainable and reliable supply of energy and storm disaster early warning' has been selected for Science and Technology Research Partnership for Sustainable Development (SATREPS) program. Held in the coastal area of the Straits of Malacca in Malaysia, which suffers from serious lightning disasters with more than 200 lightning days per year, this research aims to contribute to disaster prevention by forecasting lightning strikes by constructing the world's highest lightning observation network. This research project is to conduct the field campaigns associated with artificial rocket-triggered lightning in the coastal area of the Straits of Malacca, where the thunderstorm activity is very high and there are many positive cloud-to-ground flashes that may damage electric, communication and other equipments. Measurements of radio waves in various frequency bands and high-energy radiations, and several Rogowski coils are set up surrounding the strike points. It is planned to realize an electromagnetic field observation network in VHF and LF bands to observe the entire progression of each lightning in detail in a wide area. 3D charge distribution in the thundercloud and the amounts of neutralized charges estimated from the information where the lightning discharge begins, how it progresses, and where it terminates. Then, it is examined by the lightning current waveform measured directly with the high structure and rocket-triggered lightning. By comprehensively grasping the charge behavior in the air related to lightning discharge, it is possible to estimate the charge distribution in the cloud and to predict lightning strike. In addition, promoting the control of electric power equipment using IoT, and the early warning system of severe weather disasters to be implemented in the society. This project further researches on active and adaptive lightning resistance and protection as well as

关键词： Imaging systems

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Formulation of Optimization Problems with Radiation Field Phases as Design Variables for Pattern Synthesis of Linear Antenna Arrays

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China Communications 2022年第12期19卷 86-100页

作者： Fei Zhao Jun He Sanyou Zeng Changhe Li Qinghui Xu Zhigao Zeng School of Mechanical Engineering and Electronic Information China University of GeosciencesWuhan 430074China Science and Technology on Blind Signal Processing Laboratory Southwest Electronics and Telecommunication Technology Research InstituteChengdu 610041China School of Automation China University of GeosciencesWuhan 430074China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan 430074China College of Computer Hunan University of TechnologyZhuzhou CityHunan Province412007China

Pattern synthesise of antenna arrays is usually complicated optimization problems,while evolutionary algorithms(EAs)are promising in solving these *** paper does not propose a new EA,but does construct a new form of optimization *** new optimization formulation has two differences from the common *** is the objective function is the field error between the desired and the designed,not the usual amplitude error between the desired and the *** difference is beneficial to decrease complexity in some *** second difference is that the design variables are changed as phases of desired radiation field within shaped-region,instead of excitation *** difference leads to the reduction of the number of design variables.A series of synthesis experiments including equally and unequally spaced linear arrays with different pattern shape requirements are applied,and the effectiveness and advantages of the proposed new optimization problems are *** results show that the proposing a new optimization formulation with less complexity is as significant as proposing a new algorithm.

关键词： pattern synthesis evolutionary algorithms linear antenna arrays

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STARGATE: Spatial Transcriptomic Analysis with Recurrent and Graph Attention Techniques using Ensemble Learning

STARGATE: Spatial Transcriptomic Analysis with Recurrent and...

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IEEE International Conference on Bioinformatics and Biomedicine (BIBM)

作者： Ning Li Jiayidaer Badai Dengjie Chen Ming Xiao Le Zhang College of Computer Science Sichuan University Chengdu China College of Mechanical and Electrical Engineering Fujian A&F University Fuzhou China College of Computer Science Sichuan University Key Laboratory of Systems Health Science of Zhejiang Province School of Life Science Hangzhou Institute for Advanced Study University of Chinese Academy of Sciences Chengdu China

ISBN: (数字)9798350386226

ISBN: (纸本)9798350386233

Previous research has identified hematoma as the primary cause of mortality and disability in intraventricular hemorrhage (IVH), yet neurologic outcomes post-IVH have not significantly improved following hematoma evacuation. Therefore, utilizing spatial transcriptomics sequencing technology to acquire and analyze IVH data is of significant importance for the early diagnosis and treatment of acute cerebral hemorrhage. However, existing spatial transcriptomics clustering algorithms often overlook local information, fail to integrate multimodal data, and suffer from performance instability. To address these issues, we developed a multimodal spatial transcriptomics clustering algorithm named STARGATE, which initially captures the global spatial topology and local long-sequence gene set features of cells by integrating Graph Convolutional Networks (GCNs) based on self-attention mechanisms and Long Short-Term Memory networks (LSTMs), subsequently fuses gene expression, tissue imagery, morphological, and spatial coordinate features using Gated Recurrent Units (GRUs), and finally enhances the accuracy and robustness of predictions through ensemble learning methods. Our key experimental results include: (1) In clustering experiments on our proprietary mouse IVH spatial transcriptomics dataset, the STARGATE model achieved Adjusted Rand Index (ARI), Normalized Mutual Information (NMI), and Fowlkes-Mallows Index (FMI) scores of 0.80, 0.84, and 0.82, respectively, all superior to classic algorithms such as stLearn and CCST. (2) In clustering experiments on the mouse IVH dataset, the STARGATE model reached an accuracy of 89.63%, with an excellent confusion matrix, demonstrating outstanding accuracy and stability. (3) In clustering experiments on the public dataset DLFPC, which is known for its high data complexity leading to generally lower clustering metrics, the STARGATE model's ARI, NMI, and FMI indicators still outperformed classic algorithms such as SpaGCN and Seurat.

关键词： Accuracy Transcriptomics Stability criteria Clustering algorithms Data models Spatial databases Topology Indexes Ensemble learning Hemorrhaging

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Measurement of Absorption Current of Polyester Coated Enameled Wires with Q(t) Meter

Measurement of Absorption Current of Polyester Coated Enamel...

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International Symposium on Electrical Insulating Materials

作者： Akinao Watanabe Masumi Fukuma Yoitsu Sekiguchi Advanced Electronic and Information Systems Course National Institute of Technology Matsue College Matsue Japan Department of Electrical Engineering and Computer Science National Institute of Technology Matsue College Matsue Japan Energy and Electronics Materials R&D Laboratories Sumitomo Electric Industries Osaka Japan

A Q(t) meter is used to measure electrical properties in insulating materials. Here, Q(t) is the integral value of circuit current with time t. It is possible to measure the Q(t) of the insulation material of a capacitor and a cable by using Q(t) meter. The current through an insulating material is divided into an instantaneous charging current, an absorption current and an equilibrium leakage current. It is considered that the absorption current is related to charge accumulation in the insulating materials. In this paper, an enameled wire (1.6 PEW) is used to prepare a cable sample, the Q(t) of the coated polyester (PEs) is measured, and extraction of absorption current components from measured Q(t) are reported.

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Non-Rigid Registration with Volumetric Mesh for Liver Surgery

SSRN

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SSRN 2024年

作者： Zhang, Yanying Liu, Peter xiaoping Hou, Wenguo School of Mechanical Engineering Zhejiang Sci-Tech University Zhejiang Hangzhou China School of Information Science and Engineering Zhejiang Sci-Tech University Zhejiang Hangzhou China Shenzhen Institute of Advanced Technology Chinese Academy of Sciences Guangdong Shenzhen China Department of Systems and Computer Engineering Carleton University OttawaONKIS 5B6 Canada

In image-guided liver surgery, the registration of preoperative reconstructed liver model with intraoperative captured surfaces is extremely challenging, due to the limited visibility of liver surfaces and the impact of soft tissue deformation. In order to solve this problem, this paper presents a novel nonrigid registration method that achieves accurate alignment between the preoperative reconstructed volumetric liver mesh and a portion of the intraoperative captured liver surface. A deformation subspace is incorporated to characterize the deformation of volumetric liver mesh during registration, ensuring volume preservation of the liver mesh. The proposed method enables to capture both surface and inside deformation of the liver, thus improving the flexibility and accuracy of the *** majorization-minimization (MM) algorithm with limited-memory broyden fletcher goldfarb shanno (L-BFGS) is introduced to solve the optimization problem in the registration process, thereby effectively improves the computational efficiency of the non-rigid registration. The experimental results show that the volume relative error is less than 2% and the registration error is less than 1mm. The proposed method can reduce mesh distortion, and maintain organ volume. It provides a promising solution for aligning the liver mesh between preoperative and intraoperative periods. © 2024, The Authors. All rights reserved.

关键词： Computational efficiency

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An innovative evaluation of microstructure and tribological behavior of AISI 1060 and CuZn37Pb2 under laboratory and complex working conditions

Tribologia: Finnish Journal of Tribology

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Tribologia: Finnish Journal of Tribology 2024年第3期41卷 16-36页

作者： Bougoffa, M. Seyf Eddine Benchaa, Sayhia Abdelhak, Hadibi Ouissem, Benmesbah Si-Hem, Benkhaled Yasmine, Labiod Laboratory of Advanced Technologies in Mechanical Production Department of Mechanical Engineering University of Badji Mokhtar Laboratory LMI Annaba Algeria Faculté des Mathématiques et des Sciences de la Matière Université de Ouargla Ouargla30000 Algeria Laboratory Networks and Systems Laboratory-LRS Department of computer science University of Badji Mokhtar P.o.Box 12 Annaba23000 Algeria

Wear is a significant industrial issue caused by the interaction of multiple complex factors rather than solely by material properties. CuZn37Pb2 and AISI 1060 steel are particularly susceptible to wear due to extensive industrial applications. This study developed a wear test tool, machined on a horizontal lathe, for testing under dry and lubricated conditions. A tribological comparison was conducted between the lathe test and a tribometer, examining factors like surface roughness, load, sliding speed, wear track diameter, track width, contact temperature, wear loss, and wear rate relative to the friction coefficient. Experiments were performed with torques ranging from 25 to 100 N, speeds of 0.30, 0.40, and 0.50 m/s, and wear track diameters of 4, 6, 8, and 10 mm. Worn surfaces and wear tracks were analyzed using optical microscopy and SEM-EDS. The influence of temperature (50 °C to 200 °C) on friction properties was studied, showing that sample morphology and test type greatly affect tribological response. Despite a wear rate calculation error below 8.12%, results indicated differences between laboratory and real-world tribological responses. This study enhances wear understanding by examining numerous previously unstudied characteristics and shows that, although wear cannot be entirely eliminated, it can be significantly minimized. Laboratory testing provides prototypes for industrial challenges, effectively linking academic research with industry needs. © 2024 The Authors.

关键词： Tribology

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