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Journal of Optical Communications 2023年第s1期44卷 S823-S831页

作者： Kumar Paul, Bikash Alatwi, Aadel M. Rashed, Ahmed Nabih Zaki Shahriar Parvez, Ahm Ahmed, Kawsar Department of Software Engineering Daffodil International University Sukrabad Dhanmondi Dhaka1207 Bangladesh Department of Information and Communication Technology Mawlana Bhashani Science and Technology University Tangail Santosh1902 Bangladesh Electrical Engineering Department Faculty of Engineering University of Tabuk Tabuk Saudi Arabia Electronics and Electrical Communications Engineering Department Faculty of Electronic Engineering Menoufia University Menouf32951 Egypt Department of Computer Science and Engineering Bangladesh University 15/1 Iqbal Road Mohammadpur Dhaka1207 Bangladesh Department of Computer Science and Engineering Dhaka University of Engineering & Technology Gazipur Bangladesh Group of Bio-photomati Mawlana Bhashani Science and Technology University Tangail Santosh1902 Bangladesh

The paper outlines the divergence of beam and operating wavelength bands effects on free-space optics communication channels in local access networks. The max Q factor and min bit error rate are measured based on the divergence of beam and operating wavelength bands variations. The signal is tested also at the receiver side by using an optical power meter visualizer at various operating signal wavelength bands and under the optimum values of the divergence of the beam. The study has presented the optimum operating conditions for upgrading network operation efficiency. © 2023 Walter de Gruyter GmbH. All rights reserved.

关键词： Bit error rate

Using Microservice Telemetry Data for System Dynamic Analysis

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arXiv 2022年

作者： Al Maruf, Abdullah Bakhtin, Alexander Cerny, Tomas Taibi, Davide Department of Computer Science Baylor University WacoTX United States Software Engineering Group Tampere University TampereFI-33720 Finland

Microservices bring various benefits to software systems. They also bring decentralization and lose coupling across self-contained system parts. Since these systems likely evolve in a decentralized manner, they need to be monitored to identify when possibly poorly designed extensions deteriorate the overall system quality. For monolith systems, such tasks have been commonly addressed through static analysis. However, given the decentralization and possible language diversity across microservices, static analysis tools are lacking. On the other hand, there are available tools commonly used by practitioners that offer centralized logging, tracing, and metric collection for microservices. In this paper, we assess the opportunity to combine current dynamic analysis tools with anomaly detection in the form of quality metrics and anti-patterns. We develop a tool prototype that we use to assess a large microservice system benchmark demonstrating the feasibility and potential of such an approach. © 2022, CC BY.

关键词： Static analysis

Microservice Architecture Reconstruction and Visualization Techniques: A Review

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arXiv 2022年

作者： Cerny, Tomas Abdelfattah, Amr Elsayed S. Bushong, Vincent Maruf, Abdullah Al Taibi, Davide Department of Computer Science Baylor University WacoTX United States Software Engineering Group Tampere University TampereFI-33720 Finland

Microservice system solutions are now mainstream. The older microservices-based systems are not more than 15 years old, and their architecture is by far different than the one originally designed because of several changes applied to the systems due to the implementation of new features and bug fixing. The evolution of these legacy systems is therefore subjected to degradation. One of the most important methods to identify degradation is being able to reconstruct the software architecture of a system based on the current system running in production. Different methods have been proposed in the past: methods based on the static analysis of the source code of the microservices and methods based on the analysis of the log traces collected at runtime. Both static and dynamic analysis-based methods have their pros ad cons. In this work, we review the existing technologies for static and dynamic architectural reconstruction and related tools adopted to visualize the reconstructed architecture. The result of this work can be useful both to practitioners and researchers that can further develop these methods to provide better support for architectural degradation. © 2022, CC BY-NC-ND.

关键词： Visualization

Microvision: Static analysis-based approach to visualizing microservices in augmented reality

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arXiv 2022年

作者： Cerny, Tomas Abdelfattah, Amr S. Bushong, Vincent Maruf, Abdullah Al Taibi, Davide Department of Computer Science Baylor University WacoTX United States Software Engineering Group Tampere University TampereFI-33720 Finland

Microservices are supporting digital transformation;however, fundamental tools and system perspectives are missing to better observe, understand, and manage these systems, their properties, and their dependencies. Microservices architecture leans toward decentralization, which yields many advantages to system operation;it, however, brings challenges to their development. Microservices lack a system-centric perspective to better cope with system evolution and quality assessment. In this work, we explore microservice-specific architecture reconstruction based on static analysis. Such reconstruction typically results in system models to visualize selected system-centric perspectives. Conventional models are limited in utility when the service cardinality is high. We consider an alternative data visualization using 3D space using augmented reality. To begin testing the feasibility of deriving such perspectives from microservice systems, we developed and implemented prototype tools for software architecture reconstruction and visualization of compared perspectives. © 2022, CC BY-NC-ND.

关键词： Visualization

Single Loop Control of a Common DC-Bus-Configured Traction Motor Emulator Using State Feedback Linearization Method

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Single Loop Control of a Common DC-Bus-Configured Traction M...

2021 IEEE Southern Power Electronics Conference, SPEC 2021

作者： Kadam, Arvind H. Williamson, Sheldon S. Group Faculty of Engineering and Applied Science Department of Electrical Computer and Software Engineeirng 2000 Simcoe Street North OshawaONL1G 0C5 Canada

ISBN: (纸本)9781665436236

Nowadays, the LCL (inductor-capacitor-inductor) filter is an integral part of every power electronic converter system operating on current control. Though higher order, the LCL filter due to its high harmonic suppression capability are widely adopted in back-to-back converter systems or grid connected converter systems. Normally, with LCL filter, the control system follows double closed loop with outer loop controlling DC voltage and inner loop controlling AC current. However, for some special applications like common DC-bus-configured motor emulator (ME) system, the DC bus voltage is not required to be controlled. In addition, the presence of LCL filter introduces cross coupling of flux and torque component in case of AC motor emulation. The double closed loop control is generally adopted to decouple torque and flux components, however the controller design is more complex process. Therefore, this paper presents a single loop control of a common DC-bus-configured ME system with LCL filter based on state feedback linearization method. The decoupling equations in direct and quadrature axis are derived here. The simulation results presented for a 2.0 kW PMSM motor validate the stability as well as closed loop operation of the system with single loop control. © 2021 IEEE.

关键词： Synchronous motors

Learning the Relation between Similarity Loss and Clustering Loss in Self-Supervised Learning

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arXiv 2023年

作者： Ge, Jidong Liu, Yuxiang Gui, Jie Fang, Lanting Lin, Ming Kwok, James Tin-Yau Huang, LiGuo Luo, Bin State Key Laboratory for Novel Software Technology Software Institute Nanjing University Nanjing210093 China The School of Cyber Science and Engineering Southeast University Purple Mountain Laboratories Nanjing210000 China *** L.L.C. United States Alibaba Group China The Department of Computer Science and Engineering The Hong Kong University of Science and Technology 999077 Hong Kong The Department of Computer Science Southern Methodist University DallasTX75205 United States

Self-supervised learning enables networks to learn discriminative features from massive data itself. Most state-of-the-art methods maximize the similarity between two augmentations of one image based on contrastive learning. By utilizing the consistency of two augmentations, the burden of manual annotations can be freed. Contrastive learning exploits instance-level information to learn robust features. However, the learned information is probably confined to different views of the same instance. In this paper, we attempt to leverage the similarity between two distinct images to boost representation in self-supervised learning. In contrast to instance-level information, the similarity between two distinct images may provide more useful information. Besides, we analyze the relation between similarity loss and feature-level cross-entropy loss. These two losses are essential for most deep learning methods. However, the relation between these two losses is not clear. Similarity loss helps obtain instance-level representation, while feature-level cross-entropy loss helps mine the similarity between two distinct images. We provide theoretical analyses and experiments to show that a suitable combination of these two losses can get state-of-the-art results. Code is available at https://***/guijiejie/ICCL. Copyright © 2023, The Authors. All rights reserved.

关键词： Image classification

software development processes in ocean system modeling

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arXiv 2021年

作者： Jung, Reiner Gundlach, Sven Hasselbring, Wilhelm Software Engineering Group Department of Computer Science Kiel University Kiel Germany

Scientific modeling provides mathematical abstractions of real-world systems and builds software as implementations of these mathematical abstractions. Ocean science is a multidisciplinary discipline developing scientific models and simulations as ocean system models that are an essential research asset. In software engineering and information systems research, modeling is also an essential activity. In particular, business process modeling for business process management and systems engineering is the activity of representing processes of an enterprise, so that the current process may be analyzed, improved, and automated. In this paper, we employ process modeling for analyzing scientific software development in ocean science to advance the state in engineering of ocean system models and to better understand how ocean system models are developed and maintained in ocean science. We interviewed domain experts in semi-structured interviews, analyzed the results via thematic analysis, and modeled the results via the business process modeling notation BPMN. The processes modeled as a result describe an aspired state of software development in the domain, which are often not (yet) implemented. This enables existing processes in simulation-based system engineering to be improved with the help of these process models. Copyright © 2021, The Authors. All rights reserved.

关键词： Process engineering

Physics-Driven Spectrum-Consistent Federated Learning for Palmprint Verification

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arXiv 2023年

作者： Yang, Ziyuan Teoh, Andrew Beng Jin Zhang, Bob Leng, Lu Zhang, Yi College of Computer Science Sichuan University Chengdu China School of Electrical and Electronic Engineering College of Engineering Yonsei University Seoul Korea Republic of Pattern Analysis and Machine Intelligence Group Department of Computer and Information Science University of Macau Macau China School of Software Nanchang Hangkong University Nanchang China School of Cyber Science and Engineering Sichuan University Chengdu China

Palmprint as biometrics has gained increasing attention recently due to its discriminative ability and robustness. However, existing methods mainly improve palmprint verification within one spectrum, which is challenging to verify across different spectrums. Additionally, in distributed server-client-based deployment, palmprint verification systems predominantly necessitate clients to transmit private data for model training on the centralized server, thereby engendering privacy apprehensions. To alleviate the above issues, in this paper, we propose a physics-driven spectrum-consistent federated learning method for palmprint verification, dubbed as PSFed-Palm. PSFed-Palm draws upon the inherent physical properties of distinct wavelength spectrums, wherein images acquired under similar wavelengths display heightened resemblances. Our approach first partitions clients into short- and long-spectrum groups according to the wavelength range of their local spectrum images. Subsequently, we introduce anchor models for short- and long-spectrum, which constrain the optimization directions of local models associated with long- and short-spectrum images. Specifically, a spectrum-consistent loss that enforces the model parameters and feature representation to align with their corresponding anchor models is designed. Finally, we impose constraints on the local models to ensure their consistency with the global model, effectively preventing model drift. This measure guarantees spectrum consistency while protecting data privacy, as there is no need to share local data. Extensive experiments are conducted to validate the efficacy of our proposed PSFed-Palm approach. The proposed PSFed-Palm demonstrates compelling performance despite only a limited number of training data. The codes will be released at https://***/Zi-YuanYang/PSFed-Palm. Copyright © 2023, The Authors. All rights reserved.

关键词： Biometrics

Data-Aware Gradient Compression for FL in Communication-Constrained Mobile Computing

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arXiv 2023年

作者： Lu, Rongwei Jiang, Yutong Mao, Yinan Tang, Chen Chen, Bin Cui, Laizhong Wang, Zhi Shenzhen International Graduate School Tsinghua University Shenzhen518000 China The AI Cloud Business Group Baidu Incorporated Beijing100085 China The Department of Computer Science and Technology Tsinghua University Beijing100084 China The Department of Computer Science and Technology Harbin Institute of Technology Shenzhen518055 China The College of Computer Science and Software Engineering Shenzhen University Shenzhen518060 China

Federated Learning (FL) in mobile environments faces significant communication bottlenecks. Gradient compression has proven as an effective solution to this issue, offering substantial benefits in environments with limited bandwidth and metered data. Yet, it encounters severe performance drops in non-IID environments due to a one-size-fits-all compression approach, which does not account for the varying data volumes across workers. Assigning varying compression ratios to workers with distinct data distributions and volumes is therefore a promising solution. This work derives the convergence rate of distributed SGD with non-uniform compression, which reveals the intricate relationship between model convergence and the compression ratios applied to individual workers. Accordingly, we frame the relative compression ratio assignment as an n-variable chi-squared nonlinear optimization problem, constrained by a limited communication budget. We propose DAGC-R, which assigns conservative compression to workers handling larger data volumes. Recognizing the computational limitations of mobile devices, we propose the DAGC-A, which is computationally less demanding and enhances the robustness of compression in non-IID scenarios. Our experiments confirm that the DAGC-R and DAGC-A can speed up the training speed by up to 25.43% and 16.65% compared to the uniform compression respectively, when dealing with highly imbalanced data volume distribution and restricted communication. © 2023, CC BY-NC-SA.

关键词： Federated learning

EEG-Based VR Scene Adaptive Generation System for Regulating Emotion

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EEG-Based VR Scene Adaptive Generation System for Regulating...

Virtual Reality (ICVR), IEEE International Conference on

作者： Hui Liang ShiQing Liu Yi Wang Junjun Pan Jialin Fu Yingkai Yuan Department of Software Engineering Zhengzhou University of Lightindustry Zheng zhou China Department of Rehabilitation General Hospital of Pingmei Shenma Group Pingdingshan China Department of Computer Science and Engineering Beihang University Peking China College of Economics and Management Zhengzhou University of LightIndustry Zheng zhou China College of Computer and Communication Engineering Zhengzhou University of LightIndustry Zheng zhou China

Research based on electroencephalogram (EEG) and virtual reality (VR) has developed rapidly in recent years. The integration of EEG and VR technology has been broadly employed in psychological intervention to treat various psychological conditions and alleviate stress. At present, there exist commercial-level EEG emotion recognition products, however, research on the correlation between the content of VR scenarios and emotions remains unavailable. Therefore, this work investigates VR scene construction based on EEG, which incorporates the recovery environment theory and virtual reality technology to construct different three-dimensional dynamic virtual reality interaction scenes. EEG equipment constructs an emotion-adaptive VR system based on EEG signals with the aid of VR interaction equipment. Herein, EEG data feedback was applied to automatically generate VR scenes, and the experimental findings revealed that the system has certain feasibility and application value.

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