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Topological magnonic properties of an antiferromagnetic chain

Physical Review B 2024年第14期110卷 144448页

作者： Topojit Debnath Shri Hari Soundararaj Sohee Kwon Alexander A. Balandin Roger K. Lake Laboratory for Terahertz & Terascale Electronics (LATTE) Department of Electrical and Computer Engineering Materials Science and Engineering Department of Materials Science and Engineering

The magnonic excitations of a dimerized, one-dimensional, antiferromagnetic chain can be trivial or topological depending on the signs and magnitudes of the alternating exchange couplings and the anisotropy. The topological phase that occurs when the signs of the two different exchange couplings alternate is qualitatively different from that of the Su-Schrieffer-Heeger model. A material that may exhibit these properties is the quasi-one-dimensional material MoI3 that consists of dimerized chains weakly coupled to adjacent chains. The magnetic ground state and its excitations are analyzed both analytically and numerically using exchange and anisotropy parameters extracted from density functional theory calculations.

关键词： First-principles calculations Magnetic anisotropy Magnetic coupling Magnetic interactions Magnetic order Magnetic phase transitions Magnetic texture Magnetism Magnons Topological phase transition 1-dimensional spin chains Antiferromagnets Classical spin chains Density functional calculations Heisenberg model Holstein-Primakoff method Linear spin wave theory Quantum spin chains

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Revolutionizing Neurological Diagnostics: Integrating 6G Technology with Deep Learning for Enhanced Detection of Multiple Sclerosis and Myelitis

Revolutionizing Neurological Diagnostics: Integrating 6G Tec...

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2024 International Telecommunications Conference, ITC-Egypt 2024

作者： Noureldeen, Rana M. Elshshtawy, Rahma A. Elgohary, Omnia A. Wahba, Fatma Alzahraa A. Attia, Marco K. Abo Elazm, Zeinab B. Khattap, Mohamed G. Galal Eldeen Mohamed Ali Hassan, Hend Mostafa, Mariam Ibrahim, Nayra Ramadan, Reem Refaat, Yomna Khaled, Mennatallah Maher, Ali Abd Elaziz, Mohamed Gamal Abdellatif Ibrahim, Ahmed Faculty of Applied Health Sciences Galala University Suez435611 Egypt Faculty of Computer Science and Engineering Galala University Suez435611 Egypt Artificial Intelligence Science Program Faculty of Computer Science and Engineering Galala University Suez435611 Egypt Air Defense College Department of Electronics and Electrical Communications Engineering Alexandria Egypt

ISBN: (纸本)9798350351408

This paper proposes an alternative detection frame-work for multiple sclerosis (MS) and idiopathic acute transverse myelitis (ATM) within the 6G-enabled Internet of Medical Things (IoMT) environment. The developed framework relies on the implementation of a deep learning technique known as Dense Convolutional Networks (DenseNets) in the 6G-enabled IoMT to enhance prediction performance. To validate the performance of DenseNets, we compared it with other deep learning techniques, including Convolutional Neural Networks (CNN) and MobileNet, using real-world datasets. The experimental results show the high performance of DenseNets in predicting MS and ATM compared to other methods, achieving an accuracy of nearly 90 %. © 2024 IEEE.

关键词： Convolutional neural networks

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Scenario-Based Approach to Systematically Derive Test Cases for Systems

Scenario-Based Approach to Systematically Derive Test Cases ...

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2023 IEEE International Conference on Electro Information Technology, eIT 2023

作者： Nyakundi, Nicholas B.N. Reynolds, Shawn M. Reza, Hassan School of Electrical Engineering and Computer Science University of North Dakota Grand ForksND58202 United States

ISBN: (纸本)9781665493765

Software testing is crucial to ensure the accuracy of systems in all types of applications. Effective test case generation methods are essential to improve the quality of a system that meets its specifications. One widely used method for generating test cases is the scenario-based approach, which relies on user requirements. However, this approach faces numerous challenges, including non-systematic test case generation, lack of proper test coverage criteria, and testing of non-functional requirements. To overcome some of these challenges, this paper proposes a systematic process for generating test cases that optimizes coverage and hence reduces the time complexity of the generation process. Our aim is to improve the scenario-based test case generation process used to test the quality attributes (QAs) of a system under test. © 2023 IEEE.

关键词： Software testing

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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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2023 Joint Conference of the European Frequency and Time Forum and IEEE International Frequency Control Symposium, EFTF/IFCS 2023

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

ISBN: (纸本)9798350311426

In 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. © 2023 IEEE.

关键词： chip-scale atomic clock coherent population trapping intensity distribution laser light shift VCSEL

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Deep Learning based Ultrasound Computed Tomography for Real-Time Construction

Deep Learning based Ultrasound Computed Tomography for Real-...

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2023 IEEE International Ultrasonics Symposium, IUS 2023

作者： Gao, Qinhan Almekkawy, Mohamed Penn State University School of Electrical Engineering and Computer Science University ParkPA16802 United States

ISBN: (纸本)9798350346459

Conventional Ultrasound Computed Tomography (UCT) techniques, which rely on iterative optimization methods, are hindered by their high computational demands, making real-time processing impractical. To address this issue, we introduce an innovative deep learning-based solution that directly addresses the mapping between the received ultrasound signals and Speed of Sound (SoS) distribution images. Our approach employs a Convolutional Neural Network (CNN) that incorporates both 1D and 2D convolutions to process the input signals. Simulation data were generated using the k-wave open-source acoustic wave solver to simulate the wave equation. Remarkably, our experimental outcomes show the effectiveness of the proposed neural network in generating highly accurate SoS images, all achieved within a significantly shorter timeframe than traditional methods. © 2023 IEEE.

关键词： Iterative methods

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Modified U-Net with attention gate for enhanced automated brain tumor segmentation

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Neural Computing and Applications 2025年第7期37卷 5521-5558页

作者： Saifullah, Shoffan Dreżewski, Rafal Yudhana, Anton Wielgosz, Maciej Caesarendra, Wahyu Faculty of Computer Science AGH University of Krakow Krakow30-059 Poland Department of Informatics Universitas Pembangunan Nasional Veteran Yogyakarta Yogyakarta55281 Indonesia Department of Electrical Engineering Universitas Ahmad Dahlan Yogyakarta55191 Indonesia Faculty of Computer Science Electronics and Telecommunications AGH University of Krakow Krakow30-059 Poland Faculty of Mechanical Engineering Opole University of Technology 76 Proszkowska St. Opole45-758 Poland

This study addresses the formidable challenges encountered in automated brain tumor segmentation, including the complexities of irregular shapes, ambiguous boundaries, and intensity variations across MRI modalities. Manual segmentation, plagued by subjectivity and time constraints, further exacerbates the problem. To address these issues, we propose a modified U-Net architecture with an integrated attention gate. The proposed model demonstrates high performance, with notable Dice Similarity Coefficient (DSC) and Jaccard Index (JI) values across various tumor classes, consistently exceeding 0.93 and 0.87, respectively. Incorporating Contrast-Limited Adaptive Histogram Equalization and Histogram Equalization improves segmentation accuracy, particularly in cases of Meningioma. Comparative analyses against established models reveal a DSC of 0.9521 and a JI of 0.9093, underscoring the superiority of our method. Validation in the BraTS 2021 dataset underscores the robustness of the method, achieving high DSC and JI scores in four MRI modalities, with the T2 modality demonstrating the highest performance (DSC: 0.9216, JI: 0.8556). While acknowledging these achievements, we recognize challenges related to dataset specificity and computational intensity associated with the attention gate. Future research efforts should address these issues to improve the generalizability and applicability of the method in real-world scenarios. In addition to presenting a novel automated brain tumor segmentation method, this study contributes comprehensive result values and comparative analyses with previous research, providing valuable insights into the evolving landscape of medical image analysis. © The Author(s), under exclusive licence to Springer-Verlag London Ltd., part of Springer Nature 2025.

关键词： Image segmentation

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A review of electric vehicles charging and discharging patterns and control

A review of electric vehicles charging and discharging patte...

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2024 International Conference on science, engineering and Business for Driving Sustainable Development Goals, SEB4SDG 2024

作者： Onyemenam, John Olulope, Paul Adebiyi, Marion Osaji, Emmanuel Onimisi, Isaac Olaleru, Grace Landmark University Electrical/Information Engineering Omu-Aran Nigeria Ekiti State University Electrical/Information Engineering Ekiti Nigeria Landmark University Computer Science Omu-Aran Nigeria Federal University Lokoja Electrical/Information Engineering Lokoja Nigeria

ISBN: (纸本)9798350358155

The greenhouse effect has accelerated the development of battery-powered, zero-emission electric vehicles, which will rule the transportation industry. Recently, control form concepts for charging and discharging electric vehicles (EVs) using stochastics methods have been introduced by researchers. On the other hand, harmonics that EV chargers may introduce into the grid could lead to instability. They may also overload regional transformers, cause electric cables, circuit breakers, and fuses to overheat, and put undue strain on the electric distribution system, which can lead to problems with voltage regulation during peak hours. The charging and discharging performance were examined in relation to various stochastic methods of charging and discharging in this paper. Thus, a thorough analysis concluded that in order to reduce charging losses, shorten charging times, and increase discharging profits, an intelligent control model with long short-term memory must be included. © 2024 IEEE.

关键词： State of charge

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MEC in IoV: A Review of Resource Issues and Solution Methods * 8

MEC in IoV: A Review of Resource Issues and Solution Methods...

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8th IEEE Asia Pacific Conference on Wireless and Mobile, APWiMob 2023

作者： Obeng, Kobby Asare Ariffin, Sharifah H.S. Muhammad, Nor Aishah Universiti Teknologi Faculty of Electrical Engineering Johor Malaysia Koforidua Technical University Department of Computer Science Ghana

ISBN: (纸本)9798350327861

Multi-access Edge Computing (MEC) has received a lot of traction since its introduction by The European Telecommunications Standards Institute (ETSI) promising the integration of the Telecommunications and Information Technology worlds. The Internet of Vehicles (IoV) is an area that could greatly benefit from the implementation of MEC-based solutions. In this paper we first present an overview of the Internet of Vehicles (IoV) and the key technologies that facilitate its implementation. Next, we categorize varied use cases of Multi-access Edge Computing in the Internet of Vehicles. The results of the categorization show that MEC allows the integration of technologies such as Software Defined Networking, Network Functions Virtualization, Service Function Chaining, Blockchain and Machine Learning to improve IoV network topology design, computational capacity and Quality of Service. This review also discusses the implementation of machine learning approaches with respect to network topology, computational capacity and Quality of Service as a new horizon that will breathe new life into the MEC-IoV landscape. © 2023 IEEE.

关键词： Quality of service

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Comparison of Distance Metrics for Generating Cluster-based Ensemble Learning 23

Comparison of Distance Metrics for Generating Cluster-based ...

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12th International Conference on Software and computer Applications, ICSCA 2023

作者： Yulianti, Lenny Putri Trisetyarso, Agung Santoso, Judhi Surendro, Kridanto School of Electrical Engineering and Informatics Institut Teknologi Bandung Indonesia Computer Science Bina Nusantara University Indonesia

ISBN: (纸本)9781450398589

The basis of ensemble learning is using multiple learning algorithms to improve predictive performance compared to individual learners. Behind the various advantages of ensemble learning, there are several issues that need attention, one of which is related to finding a set of diverse base learners. Recently, clustering has been used to generate diverse base learners as opposed to bagging. The main advantages of cluster-based ensemble learners are their robustness and versatility. The key parameters for implementing a clustering algorithm are the cluster size and distance metrics. The contribution of this study is to compare four distance metrics, including the Euclidean, Manhattan, Chebyshev, and Canberra distances, in the clustering method for ensemble generation and evaluate them based on accuracy, purity, and diversity. The methodology is tested on 10 benchmark UCI datasets. The results show that the use of the Chebyshev and Canberra distances achieved superior accuracy to both the Euclidean and Manhattan distances, while the purity and diversity values of the use of the Chebyshev distance outperformed the other three. © 2023 Copyright held by the owner/author(s).

关键词： Clustering algorithms

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Scalable Quantum Photonic Neural Network Processor via Cavity-Assisted Interactions

Scalable Quantum Photonic Neural Network Processor via Cavit...

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CLEO: Fundamental science, CLEO:FS 2024 - Part of Conference on Lasers and Electro-Optics, CLEO 2024

作者： Basani, Jasvith Raj Niu, Murphy Yuezhen Waks, Edo Department of Electrical and Computer Engineering Institute for Research in Electronics and Applied Physics Joint Quantum Institute University of Maryland College ParkMD20742 United States Department of Computer Science Joint Center for Quantum Information and Computer Science University of Maryland College ParkMD20742 United States

We present an integrated photonic architecture that uses a single atom trapped in a cavity for deterministic high-fidelity quantum operations. Our design is unique in providing a photon-number-selective nonlinearity, ... 详细信息

ISBN: (纸本)9781957171395

关键词： Photonic integrated circuits

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