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High-speed multiwavelength InGaAs/InP quantum well nanowire array micro-LEDs for next generation optical communications

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Opto-electronic Science 2023年第5期2卷 1-11页

作者： Fanlu Zhang Zhicheng Su Zhe Li Yi Zhu Nikita Gagrani Ziyuan Li Mark Lockrey Li Li Igor Aharonovich Yuerui Lu Hark Hoe Tan Chennupati Jagadish Lan Fu Australian Research Council Centre of Excellence for Transformative Meta-Optical Systems Department of Electronic Materials EngineeringResearch School of PhysicsThe Australian National UniversityCanberra ACT 2601Australia School of Electronic Science and Engineering Southeast UniversityNanjing 210096China Microstructural Analysis Unit University of Technology SydneySydney NSW 2007Australia Australian National Fabrication Facility ACT Node Research School of PhysicsThe Australian National UniversityCanberra ACT 2601Australia ARC Centre of Excellence for Transformative Meta-Optical Systems Faculty of ScienceUniversity of Technology SydneySydney NSW 2007Australia School of Engineering College of Engineering and Computer ScienceThe Australia National UniversityCanberraCanberra ACT 2601Australia

Miniaturized light sources at telecommunication wavelengths are essential components for on-chip optical communication ***,we report the growth and fabrication of highly uniform p-i-n core-shell InGaAs/InP single quantum well(QW)nanowire array light emitting diodes(LEDs)with multi-wavelength and high-speed ***-dimensional cathodoluminescence mapping reveals that axial and radial QWs in the nanowire structure contribute to strong emission at the wavelength of~1.35 and~1.55μm,respectively,ideal for low-loss optical *** a result of simultaneous contributions from both axial and radial QWs,broadband electroluminescence emission with a linewidth of 286 nm is achieved with a peak power of~17μW.A large spectral blueshift is observed with the increase of applied bias,which is ascribed to the band-filling effect based on device simulation,and enables voltage tunable multi-wavelength operation at the telecommunication wavelength ***-wavelength operation is also achieved by fabricating nanowire array LEDs with different pitch sizes on the same substrate,leading to QW formation with different emission ***,high-speed GHz-level modulation and small pixel size LED are demonstrated,showing the promise for ultrafast operation and ultracompact *** voltage and pitch size controlled multi-wavelength highspeed nanowire array LED presents a compact and efficient scheme for developing high-performance nanoscale light sources for future optical communication applications.

关键词： InGaAs/InP quantum well nanowires LEDs

Integrated Human Activity Sensing and Communications

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arXiv 2022年

作者： Li, Xinyu Cui, Yuanhao Andrew Zhang, J. Liu, Fan Zhang, Daqing Hanzo, Lajos The Faculty of Engineering and Information Technology University of Technology Ultimo SydneyNSW2007 Australia Beijing100876 China The Department of Electronic and Electrical Engineering Southern University of Science and Technology Shenzhen518055 China Telecom SudParis France Peking University China The School of Electronics and Computer Science University of Southampton SouthamptonSO17 1BJ United Kingdom

Advances in wireless communication and signal processing facilitate integrated sensing and communication (ISAC) - a compelling technology that intrinsically combines sensing and communication functionalities for the dual-purpose exploitation of wireless/hardware resources and pursues mutual benefits. Consequently, the next-generation communications network will be perceptive. In this article, we provide a review of human-related sensing in the context of ISAC. We first present a general ISAC receiver signal processing framework, with a focus on human activity recognition (HAR). Based on its specific spatial deployments, we then categorize ISAC HAR into monostatic, bistatic, and distributed deployments, and discuss their properties, critical research problems and solutions. To facilitate the system's realization and improve its recognition performance, we then explore the inherent connections between the physical-layer system parameters and HAR performance metrics. Experimental results are presented for characterizing the sensing potentials of different ISAC systems. Finally, we review the technical challenges and identify the open research problems. © 2022, CC BY.

关键词： Signal receivers

Accurate Base Station Placement in 4G LTE Networks Using Multiobjective Genetic Algorithm Optimization

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Wireless Communications and Mobile Computing 2023年第1期2023卷

作者： Isabona, Joseph Imoize, Agbotiname Lucky Ojo, Stephen Venkatareddy, Prashanth Hinga, Simon Karanja Sánchez-Chero, Manuel Ancca, Sheda Méndez Department of Physics Federal University Lokoja Lokoja260101 Nigeria Department of Electrical and Electronics Engineering Faculty of Engineering University of Lagos Akoka Lagos100213 Nigeria Department of Electrical Engineering and Information Technology Institute of Digital Communication Ruhr University Bochum44801 Germany Department of Electrical and Computer Engineering College of Engineering Anderson University AndersonSC29621 United States Department of Electrical and Electronics Engineering Nitte Meenakshi Institute of Technology Karnataka Bengaluru India Department of Electrical and Electronic Engineering Technical University of Mombasa Mombasa Kenya Facultad de Ingeniería de Industrias Alimentarias y Biotecnología Universidad Nacional de Frontera Sullana Peru Facultad de Arquitectura e Ingeniería Universidad Nacional de Moquegua Moquegua Peru

Cellular mobile communication network planning and optimization involve a complex engineering process that deals with network fundamentals, radio resource elements, and critical decision variables. The continuous evolution of radio access technologies provides new challenges that necessitate efficient radio planning and optimization. Therefore, the planning and optimization algorithms should be highly efficient, advanced, and robust. An important component of 4G LTE network planning is the proper placement of evolved node base stations (eNodeBs) and the configuration of their antenna elements. This contribution proposes a multiobjective genetic algorithm that integrates network coverage, capacity, and power consumption for optimal eNodeB placement in an operational 4G LTE network. The multi-objective-based genetic algorithm optimization has been achieved using the optimization toolbox in MATLAB. By leveraging the proposed method, the effect of different population sizes on the cost of placing the eNodeBs and the percentage coverage of the eNodeBs in a given cell is determined. As a result, the optimal selection technique that minimizes the total network cost without compromising the desired coverage and capacity benchmarks is achieved. The proposed automatic eNodeB antenna placement method can be explored to optimize 4G LTE cellular network planning in related wireless propagation environments. © 2023 Joseph Isabona et al.

关键词： Base stations

Tracking and Calculating Speed of Mixing Vehicles Using YOLOv4 and DeepSORT

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Tracking and Calculating Speed of Mixing Vehicles Using YOLO...

National Foundation for Science and technology Development Conference on Information and computer Science (NICS)

作者： Phat Nguyen Huu Bang Nguyen Anh Vu Tran Ngoc Nam Tran Manh Hoang Tien Dzung Nguyen Quang Tran Minh School of Electrical and Electronic Engineering Hanoi University of Science and Technology Hanoi Vietnam Specialized Math Class HUS High School for Gifted Students Hanoi Vietnam Department of Information Systems Faculty of Computer Science and Engineering Ho Chi Minh City University of Technology Hochiminh Vietnam Vietnam National University HoChiMinh City Hochiminh Vietnam

Today, strong development of socio-economic has promoted participation in traffic. As a result, traffic management is becoming more and more difficult. To effectively solve the problem, artificial intelligence (AI) applications are applied for the improvement of urban traffic management and administration. Therefore, we propose an intelligent algorithm for monitoring and detecting vehicles. We use data collected from cameras and apply deep learning technology to track objects in the paper. The proposed algorithm uses YOLOv4 combined with DeepSORT for tracking and calculating the speed of detected vehicles. Results show that the proposed algorithm improves accuracy up to 95% which is suitable to apply for real applications.

关键词： Deep learning computer science Computational modeling Traffic control Cameras Artificial intelligence Monitoring

A Survey on Temporal Knowledge Graph Completion: Taxonomy, Progress, and Prospects

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arXiv 2023年

作者： Wang, Jiapu Wang, Boyue Qiu, Meikang Pan, Shirui Xiong, Bo Liu, Heng Luo, Linhao Liu, Tengfei Hu, Yongli Yin, Baocai Gao, Wen Beijing Municipal Key Lab of Multimedia and Intelligent Software Technology Beijing Artificial Intelligence Institute Faculty of Information Technology Beijing University of Technology Beijing100124 China The Beacom College of Computer and Cyber Sciences Dakota State University MadisonSD United States Griffith University QLD Australia The Department of Computer Science University of Stuttgart Stuttgart70569 Germany The Department of Data Science and AI Monash University Melbourne Australia The Institute of Digital Media Peking University Beijing100871 China The School of Electronic and Computer Engineering Peking University Shenzhen Graduate School Shenzhen518055 China

Temporal characteristics are prominently evident in a substantial volume of knowledge, which underscores the pivotal role of Temporal Knowledge Graphs (TKGs) in both academia and industry. However, TKGs often suffer from incompleteness for three main reasons: the continuous emergence of new knowledge, the weakness of the algorithm for extracting structured information from unstructured data, and the lack of information in the source dataset. Thus, the task of Temporal Knowledge Graph Completion (TKGC) has attracted increasing attention, aiming to predict missing items based on the available information. In this paper, we provide a comprehensive review of TKGC methods and their details. Specifically, this paper mainly consists of three components, namely, 1) Background, which covers the preliminaries of TKGC methods, loss functions required for training, as well as the dataset and evaluation protocol;2) Interpolation, that estimates and predicts the missing elements or set of elements through the relevant available information. It further categorizes related TKGC methods based on how to process temporal information;3) Extrapolation, which typically focuses on continuous TKGs and predicts future events, and then classifies all extrapolation methods based on the algorithms they utilize. We further pinpoint the challenges and discuss future research directions of TKGC. Copyright © 2023, The Authors. All rights reserved.

关键词： Interpolation

Power silicon carbide schottky diodes as current mode ?-radiation detectors 32

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Power silicon carbide schottky diodes as current mode ?-radi...

32nd IEEE International Conference on Microelectronics, MIEL 2021

作者： Ilic, S.D. Andjelkovic, M.S. Carvajal, M.A. Lallena, A.M. Krstic, M. Stankovic, S. Ristic, G.S. University of Belgrade Center of Microelectronic Technologies Technology and Metallurgy Serbia IHP-Leibniz-Institut für Innovative Mikroelektronik System Architectures Department Frankfurt Germany University of Granada Department of Electronics and Computer Technology Granada Spain Vincca Institute of Nuclear Sciences Department of Radiation and Environmental Belgrade Serbia University of Niš Faculty of Electronic Engineering Department of Microelectronics Niš Serbia

ISBN: (纸本)9781665445283

In this paper, the feasibility of using commercial power Silicon Carbide (SiC) Schottky diodes as a current mode ?-radiation detector have been examined. Diodes with almost identical electric characteristics are purchased from two different manufacturers, On Semiconductor and RoHM. They have been tested under gamma radiation exposure from a Co-60 source. The current response during irradiation has been measured for various dose rates with reversed diode bias. Investigated range of dose rates was from 0.258 Gy/h to 26.312 Gy/h, and reverse diode bias values were 10 V, 20 V, 50 V, 100 V and 200 V. Tested Schottky diodes produce stable current response for the investigated dose rates. Although the manufacturers are different, the results show that the dosimetric characteristics of these diodes have an excellent match. Sensitivity was proportional to the applied reverse bias voltage. A simple power-law can very well describe the dependence of measured radiation-induced current on dose rate. © 2021 IEEE.

关键词： Silicon carbide

VTAE: Variational Transformer Autoencoder with Manifolds Learning

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arXiv 2023年

作者： Shamsolmoali, Pourya Zareapoor, Masoumeh Zhou, Huiyu Tao, Dacheng Li, Xuelong The School of Communication and Electrical Engineering East China Normal University Shanghai China The School of Electronic Information and Electrical Engineering Shanghai Jiao Tong University China The School of Computing and Mathematical Sciences University of Leicester LeicesterLE1 7RH United Kingdom The School of Computer Science Faculty of Engineering The University of Sydney DarlingtonNSW Australia Northwestern Polytechnical University China Ministry of Industry and Information Technology Xi’an China

Deep generative models have demonstrated successful applications in learning non-linear data distributions through a number of latent variables and these models use a non-linear function (generator) to map latent samples into the data space. On the other hand, the non-linearity of the generator implies that the latent space shows an unsatisfactory projection of the data space, which results in poor representation learning. This weak projection, however, can be addressed by a Riemannian metric, and we show that geodesics computation and accurate interpolations between data samples on the Riemannian manifold can substantially improve the performance of deep generative models. In this paper, a Variational spatial-Transformer AutoEncoder (VTAE) is proposed to minimize geodesics on a Riemannian manifold and improve representation learning. In particular, we carefully design the variational autoencoder with an encoded spatial-Transformer to explicitly expand the latent variable model to data on a Riemannian manifold, and obtain global context modelling. Moreover, to have smooth and plausible interpolations while traversing between two different objects' latent representations, we propose a geodesic interpolation network different from the existing models that use linear interpolation with inferior performance. Experiments on benchmarks show that our proposed model can improve predictive accuracy and versatility over a range of computer vision tasks, including image interpolations, and reconstructions. © 2023, CC BY-SA.

关键词： Interpolation

Modern Computing: Vision and Challenges

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arXiv 2024年

作者： Gill, Sukhpal Singh Wu, Huaming Patros, Panos Ottaviani, Carlo Arora, Priyansh Pujol, Victor Casamayor Haunschild, David Parlikad, Ajith Kumar Cetinkaya, Oktay Lutfiyya, Hanan Stankovski, Vlado Li, Ruidong Ding, Yuemin Qadir, Junaid Abraham, Ajith Ghosh, Soumya K. Song, Houbing Herbert Sakellariou, Rizos Rana, Omer Rodrigues, Joel J.P.C. Kanhere, Salil S. Dustdar, Schahram Uhlig, Steve Ramamohanarao, Kotagiri Buyya, Rajkumar School of Electronic Engineering and Computer Science Queen Mary University of London London United Kingdom Center for Applied Mathematics Tianjin University Tianjin China Raygun Performance Monitoring Wellington New Zealand Department of Computer Science York Centre for Quantum Technologies University of York York United Kingdom Microsoft Schiphol Netherlands Distributed Systems Group Vienna University of Technology Vienna Austria Detecon International GmbH Munich Germany Institute for Manufacturing Department of Engineering University of Cambridge Cambridge United Kingdom Department of Engineering Science University of Oxford Oxford United Kingdom Department of Computer Science University of Western Ontario London Canada Faculty of Computer and Information Science University of Ljubljana Ljubljana Slovenia Institute of Science and Engineering Kanazawa University Japan Tecnun School of Engineering University of Navarra Spain Department of Computer Science and Engineering College of Engineering Qatar University Doha Qatar Bennett University Greater Noida India Machine Intelligence Research Labs AuburnWA United States Department of Computer Science and Engineering Indian Institute of Technology Kharagpur India Baltimore United States Department of Computer Science University of Manchester Oxford Road Manchester United Kingdom School of Computer Science and Informatics Cardiff University Cardiff United Kingdom Department of Computer Science College of Computer and Information Sciences King Saud University Riyadh Saudi Arabia COPELABS Lusófona University Lisbon Portugal Sydney Australia The University of Melbourne Victoria Australia Laboratory School of Computing and Information Systems The University of Melbourne Australia

Over the past six decades, the computing systems field has experienced significant transformations, profoundly impacting society with transformational developments, such as the Internet and the commodification of computing. Underpinned by technological advancements, computer systems, far from being static, have been continuously evolving and adapting to cover multifaceted societal niches. This has led to new paradigms such as cloud, fog, edge computing, and the Internet of Things (IoT), which offer fresh economic and creative opportunities. Nevertheless, this rapid change poses complex research challenges, especially in maximizing potential and enhancing functionality. As such, to maintain an economical level of performance that meets ever-tighter requirements, one must understand the drivers of new model emergence and expansion, and how contemporary challenges differ from past ones. To that end, this article investigates and assesses the factors influencing the evolution of computing systems, covering established systems and architectures as well as newer developments, such as serverless computing, quantum computing, and on-device AI on edge devices. Trends emerge when one traces technological trajectory, which includes the rapid obsolescence of frameworks due to business and technical constraints, a move towards specialized systems and models, and varying approaches to centralized and decentralized control. This comprehensive review of modern computing systems looks ahead to the future of research in the field, highlighting key challenges and emerging trends, and underscoring their importance in cost-effectively driving technological progress. © 2024, CC BY.

关键词： Obsolescence

Attention multiple instance learning with Transformer aggregation for breast cancer whole slide image classification

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Attention multiple instance learning with Transformer aggreg...

IEEE International Conference on Bioinformatics and Biomedicine (BIBM)

作者： Jianxin Zhang Cunqiao Hou Wen Zhu Mingli Zhang Ying Zou Lizhi Zhang Qiang Zhang School of Computer Science and Engineering Dalian Minzu University Dalian China Pathology Department First Affiliated Hospital of Dalian Medical University Dalian China McGill Centre for Integrative Neuroscience McGill University Montreal Canada Faculty of Electronic Information and Electrical Engineering Dalian University of Technology Dalian China

ISBN: (数字)9781665468190

ISBN: (纸本)9781665468206

Recently, attention-based multiple instance learning (MIL) methods have received more concentration in histopathology whole slide image (WSI) applications. However, existing attention-based MIL methods rarely consider the cross-channel information interaction of pathology images when identifying discriminant patches. Additionally, they also have limitations on capturing the correlation between different discriminant instances for the bag-level classification. To address these challenges, we present a novel attention-based MIL model (AMIL-Trans) for breast cancer WSI classification. AMIL-Trans first embeds the efficient channel attention to realize the cross-channel interaction of pathology images, thus computing more robust features for instance selection without introducing too much computation cost. Then, it leverages vision Transformer encoder to directly aggregate selected instance features for better bag-level prediction, which effectively considers the correlation between different discriminant instances. Experiment results illustrate that AMIL-Trans respectively achieves its optimal AUC of 94.27% and 84.22% on the Camelyon-16 dataset and MSK external validation dataset, demonstrating the competitive performance compared with state-of-the-art MIL methods on breast cancer WSI classification task. The code will be available at https://*** CunqiaoHou/AMIL-Trans.

关键词： Correlation Costs Histopathology Supervised learning computer architecture Transformers Feature extraction