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Defective Microstrip Structure Based Phase Shifter with Reduced Size for Phased Antenna Array Applications 12

Defective Microstrip Structure Based Phase Shifter with Redu...

12th IEEE International Conference on Intelligent Data Acquisition and Advanced Computing Systems: Technology and Applications, IDAACS 2023

作者： Khan, Hajra Khan, Shahid Nasir, Jamal Ali Shah, Syed Ahson Dalarsson, Mariana Alibakhshikenari, Mohammad Comsats University Islamabad Department of Electrical and Computer Engineering Pakistan Hanyang University Applied Bioelectronics Laboratory Seoul Korea Republic of School of Electrical Engineering and Computer Science Kth Royal Institute of Technology Stockholm Sweden Universidad Carlos Iii de Madrid Department of Signal Theory and Communications Spain

ISBN: (纸本)9798350358056

In this work, we propose a small-size and low-cost phase shifter based on defective microstrip structure (DMS) technique, with a modified reconfigurable unit cell (MRDMS) for WLAN applications at 5.2 GHz. The phase shifter is made up of an MRDMS unit, created by etching slots on a simple microstrip line with an outline of three bridges. To further increase the phase shift, a T-shaped slot is introduced in the central bridge and PIN diodes on the edges of the outer bridges are used. By switching the diodes on and off, the MRDMS unit cell is capable of operating in a variety of different modes to give a phase shift of 37.71° at 5.2 GHz. Additionally, MRDMS unit cells are cascaded for higher phase shift as required. Cascaded two- and four-cell phase shifters were designed and simulated in HFSS and a parametric study on various parameters was conducted to show the detailed operating properties of the proposed phase shifter. Compared to previously reported research, the present study shows that two cascaded phase shifters introduce 75.08° phase shifts and 151.75°, respectively. To the best of our knowledge, this is the maximum phase shift obtained by a phase shifter based on MRDMS. © 2023 IEEE.

关键词： defected microstrip structure phase shifter reconfigurable microwave system

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How to Succeed in Communicating Software Metrics in Organization? 28

How to Succeed in Communicating Software Metrics in Organiza...

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28th Americas Conference on Information Systems, AMCIS 2022

作者： Lindström, Nataliya Berbyuk Asatiani, Aleksandre Staron, Miroslaw Söder, Ola Department of Applied Information Technology University of Gothenburg Sweden Department of Computer Science and Engineering Chalmers & University of Gothenburg Sweden Axis Communications Lund Sweden

ISBN: (纸本)9781958200001

While software metrics are indispensable for quality assurance, using metrics in practice is complicated. Quality, productivity, speed, and efficiency are important factors to be considered in software development (Holmstrom et al. 2006;Svensson 2005). Measuring correct metrics and using them in the right and transparent way contributes to pushing development in a desirable direction, leading to achieving projected goals and outcomes (Staron and Meding 2018). On the other hand, tracking the wrong metrics, and failing to interpret and communicate them properly results in a stressful work environment, conflicts, distrust, lower engagement, and decreased productivity (de Sá Leitão Júnior 2018;Ellis et al. 1991;Staron 2012). To ensure proper and effective use of metrics in organizations, successful communication around metrics is essential (Lindström et al. 2021;Post et al. 2002;Staron and Meding 2015). The purpose of this study is to understand and improve communication about metrics in contexts of contemporary software development practice in organizations. This is achieved by identifying the bottlenecks in the process of communication around metrics and how to overcome them in practice. Drawing on 38 semi-structured interviews and interactive workshops with metrics teams members and stakeholders from three organizations, we identify three interrelated challenges including limited knowledge about metrics and lack of terminology, uncoordinated use of multiple communication channels, and sensitivity of metrics, which influence workplace communication, trust, and performance. Our study shows the importance of developing metrics terminology to ensure the development of a shared understanding of metrics. Further, raising awareness about the affordances such channels as dashboards, email, MS Teams meetings/chat, stand up meetings, reports, etc., commonly used in software organizations, and how they can be combined to successfully transfer information about metrics is essent

关键词： Terminology

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Edge Intelligent in IoT: Algorithms and Applications 9

Edge Intelligent in IoT: Algorithms and Applications

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9th International Conference on science, Technology, engineering and mathematics, ICONSTEM 2024

作者： Prakash, Kode Jaya Gobimohan, S. Rani, J. Femila Mercy Mageshwari, P. S. Latha Fawad, Iffath Suganya, G. Vnr Vignana Jyothi Institute of Engineering & Technology Department of Mechanical Engineering Telangana Hyderabad500090 India College of Engineering And Technology University of Technology And Applied Sciences Nizwa Oman Dindigul Tamil Nadu 624622 India Department of Mathematics Tamil Nadu Dindigul624622 India Tamil Nadu Kavaraipettai601206 India Dayananda Sagar College of Engineering Department of Electronics And Telecommunication Engineering Karnataka Bengaluru India Dr. Sns Rajalakshmi College of Arts And Science Department of Computer Science Tamil Nadu Coimbatore641049 India

ISBN: (纸本)9798350365092

There are a lot more IoT gadgets and data being made because IoT apps are becoming more common in our daily lives. IoT devices don't have a lot of resources, which makes it harder to handle and store IoT data. Traditional cloud computing helps with some problems caused by the Internet of Things' (IoT) limited resources, but it also causes new problems, like delay in IoT apps that need to work right away. It makes sense that edge-cloud computer technology has changed recently. It is possible to store and handle data at the edge of the network with this technology. Edge computing architectures for the internet of things (ECAsIoT) are grouped in this piece by where the data is stored, the services that help with orchestration, security, and big data. The research looks into and compares each architecture in depth using a number of factors. We look at ECAs-IoT against two other IoT stacked models to see what their pros, cons, chances, and risks are. The research lists the main problems with present ECAs-IoT and suggests ways to fix them. The Internet of Things (IoT) and its effects on edge computing are also talked about in this poll. The research ends with four possible uses for ECAs-IoT in IoT. © 2024 IEEE.

关键词： Internet of things

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Design and Development of Digital Asset Market Platform

Design and Development of Digital Asset Market Platform

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International Conference for Convergence of Technology (I2CT)

作者： Ashritha H A Hari Krishna S M Ayesha Siddiqa Lakshmi Lakshmi Kayani Nawaz Ulla Khan Department of Computer Science and Engineering M S Ramaiah University of Applied Sciences Bangalore India

ISBN: (数字)9798350394474

ISBN: (纸本)9798350394481

In an era characterized by the increasing digitization of assets, the demand for secure, efficient, and user-friendly platforms to facilitate the exchange of digital assets has surged. This project focuses on addressing this need through the creation of a robust marketplace that accommodates a diverse range of digital assets, from cryptocurrencies to digital art and intellectual *** present an innovative avenue for creators, musicians, and artists to showcase their work and monetize their talent. Our objective is to provide users with a decentralized platform, enabling them to promote and acquire these NFTs directly from creators, free from concerns about interference by central authorities in their transactions.

关键词： Shape Scalability Ecosystems Digital art Interference User experience Cryptocurrency

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Design and Surface Flashover Test of 10 kV SiC Power Module for DC Shipboard Application

Design and Surface Flashover Test of 10 kV SiC Power Module ...

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2023 IEEE Energy Conversion Congress and Exposition, ECCE 2023

作者： Li, Xiaoling Liu, Yang Schwartz, Skyler Guo, Ning Karimi, Ebrahim Mantooth, H. Alan Graber, Lukas Cuzner, Robert University of Arkansas Department of Electrical Engineering Fayetteville United States Georgia Institute of Technology School of Electrical & Computer Engineering Atlanta United States University of Wisconsin-Milwaukee College of Engineering and Applied Science Milwaukee United States

ISBN: (纸本)9798350316445

Future all-electric ships will likely use a Medium Voltage DC (MVDC) power distribution system, which has several advantages over MVAC, such as higher power density and higher reliability. As key components for power distribution systems, 10 kV power modules need to meet the insulation requirements for various fault conditions. Grounding faults can cause extremely high electric stress between the module terminals and baseplate hence resulting in surface flashover breakdown. This paper aimed at the insulation challenges of 10 kV power module for the MVDC shipboard application. The maximum voltage stresses of four typical grounding schemes are compared at single line-to-ground faults. The surface flashover tolerance of a 10 kV SiC power module is verified under steady DC voltage and the worst-case transient fault overvoltage. The experimental results can provide a reference for the MV power module insulation design and the module baseplate grounding schemes. © 2023 IEEE.

关键词： 10 kV power module MVDC shipboard power system surface flashover

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AGV indoor localization: a high fidelity positioning and map building solution based on drawstring displacement sensors

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Journal of Ambient Intelligence and Humanized Computing 2024年第4期15卷 2277-2293页

作者： Wang, Shih-Yuan Li, Che-Ming Liong, Sze-Teng Sheng, Yu-Ting Huang, Yen-Chang Liong, Gen-Bing Gan, Yee-Siang Graduate Institute of Architecture National Yang Ming Chiao Tung University Hsinchu Taiwan Department of Electronic Engineering Feng Chia University Taichung40724 Taiwan School of Architecture Feng Chia University Taichung40724 Taiwan Department of Applied Mathematics National University of Tainan Tainan Taiwan Faculty of Computer Science & amp Information Technology University of Malaya Kuala Lumpur50603 Malaysia

The rapid evolution of artificial intelligence (AI) and robotics technologies are bringing drastic changes to society and industry in these recent years. The impressive progress in facilitating smart manufacturing in this era of Industry 4.0 has made our lives much more convenient than ever before. Despite the greater reliability and stability of the robotic system, there are several challenges to overcome such as the restrictions of scenes, obstacles, and hardware specifications. Since a high precision positioning algorithm is of paramount importance in devising a mobile robot, the research in developing simultaneous localization and mapping has been garnered immerse attention especially from domains of the computer vision and autonomous robots. In this paper, a novel method is presented to significantly enhance the positioning precision of indoor unmanned guided vehicles. The approach involves several steps, including setting up hardware configurations and collecting relevant data by installing necessary devices and system packages within the robot operating system (ROS). Trilateration is employed to determine the relative position of the mobile robot using distance measurements. Coordinate transformation is then conducted to convert the collected input data of relative distances and orientations. Trajectory paths are obtained, and occupancy maps are constructed to estimate the resulting trajectory and generate a 2D grid map. Indoor localization and mapping are achieved using three drawstring displacement sensors along with orientation information from an Inertial Measurement Unit (IMU). The proposed method is extensively evaluated through experimentation on predefined navigation paths, and its performance is compared to state-of-the-art methods such as RealSense T265, Hector SLAM, and wheel odometry. The results show that the proposed method exhibits compelling performance in both mean error and occupancy map construction. Ultimately, the findings reported herein

关键词： Mobile robots

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Blockchain and Edge Computing Integration Boosts Scalability and Reduces Latency 2

Blockchain and Edge Computing Integration Boosts Scalability...

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2nd International Conference on Business Analytics for Technology and Security, ICBATS 2023

作者： Mahfuri, Mahmoud Alnawaiseh, Ahmad Enad Asad, Umber Yousif, Muhammad Aslam, Shoukat Chabani, Zakariya Fiaz, Muhammad International University for Science and Technolgy Faculty of Engineering - Computer and Information Technolgy Department Syria Orange-Jordan Telecom Company Jordan NCBA&E Lahore School of Computer Computer Pakistan Canadian University Dubai Faculty of Management Dubai United Arab Emirates NCBA&E Lahore School of Computer Science Pakistan Applied Science Private University Applied Science Research Center Amman11937 Jordan

ISBN: (纸本)9798350335644

Nowadays, the integration of blockchain and edge computing has become important in computer science due to the significant advantages it can bring to a range of real-world applications. By combining the strengths of both technologies, it is Combining the strengths of both technologies makes it possible to create a highly secure and reliable network with reduced latency and efficient transaction processing. This article explores the challenges and opportunities of combining these two technologies, including the scalability barrier of blockchain and the management and security challenges of edge computing. This paper discusses some of the theories and research challenges associated with this integration, including developing efficient consensus algorithms and enabling data sharing and provenance. this paper concludes by highlighting the potential benefits of this technology in the field of medicine and healthcare, finance, supply chain management, and Internet of Things. © 2023 IEEE.

关键词： Blockchain

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No-Reference Image Quality Assessment Using Meta-Learning 3rd

No-Reference Image Quality Assessment Using Meta-Learning

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The 3rd International Conference on Frontiers in Computing and Systems (COMSYS 2022)

作者： Dey, Ratnadeep Bhattacharjee, Debotosh Kejcar, Ondrej Department of Computer Science and Engineering Jadavpur University Kolkata India Center for Basic and Applied Science Faculty of Informatics and Management University of Hradec Kralove Rokitanskeho 62 Hradec Kralove500 03 Czech Republic

ISBN: (纸本)9789819926794

Deep learning-based no-reference image quality assessment faces problems like dependency on a large amount of experimental data and the generalization ability of the learned model. A deep learning model trained on a specific dataset cannot obtain the desired results for testing on other datasets. Similarly, a deep learning model trained with small experiment data does not provide the best result. This paper addresses these problems of the deep learning model using the meta-learning approach in the field of no-reference Image Quality Assessment. The no-reference image quality assessment is a small sample problem, where the amount of experimental data is very less. Although data augmentation techniques have been used to increase the amount of experimental data, they do not increase the variation of the data. Therefore, traditional deep learning-based techniques are unsuitable for no-reference image quality assessment. Another problem is the lack of generalization ability. A deep learning model trained with image quality datasets containing images distorted synthetically cannot efficiently assess the quality of images distorted naturally. This work proposes a meta-learning model that can be trained with more than one image quality dataset, where one image quality assessment dataset contains synthetic images and the other contains real images. Finally, another image quality assessment dataset has tested the trained model. The test result is better than the state-of-the-art methods, and the results establish the fact that the meta-learning model proposed in this paper tries to resolve the problems of the deep learning model. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Image quality

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LEAD: Latency-Efficient Application Deployment for Microservices Architecture

LEAD: Latency-Efficient Application Deployment for Microserv...

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International Conference on Automation and Computing (ICAC)

作者： Mohammad-Ali Mirzaei Parsa Poorsistani Seyyed Ahmad Javadi Department of Computer Engineering Amirkabir University of Technology Tehran Iran Department of Math and Computer Science Amirkabir University of Technology Tehran Iran

ISBN: (数字)9798350360882

ISBN: (纸本)9798350360899

In cloud computing, microservices architecture has become the preferred choice for many applications. Accordingly, several small and decoupled containerized services hosted on different servers communicate through the network. Therefore, communication latency significantly impacts end-to-end latency. Kubernetes, the de facto standard for container orchestration, cannot reduce this overhead due to its lack of awareness of service *** present LEAD, a Latency-Efficient Application Deployment framework that integrates with Kubernetes without modifying its core components. LEAD considers the inter-service relationships and resource constraints, improving service placement to reduce end-to-end latency. The idea behind LEAD is straightforward: keep the cooperating services close to each other to exploit faster in-node communication and automate this process. The proposed idea is realized by leveraging a scoring algorithm and monitoring framework to achieve dynamic improvement of service placement. Our experimental results show an average 20% improvement in the 99 th percentile latency compared to Kubernetes default scheduler.

关键词： Heart Heuristic algorithms Microservice architectures computer architecture Tail Lead Syntactics Servers Monitoring Standards

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AI-Driven Drug Discovery: Unravelling the Potential of Generative Adversarial Networks (GANs) in Pharmaceutical Research 3

AI-Driven Drug Discovery: Unravelling the Potential of Gener...

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3rd International Conference on Technological Advancements in Computational sciences, ICTACS 2023

作者： Burri, Srinivasa Rao Diallo, Mamadou Yero Sharma, Lakshay Dutt, Vishal Western Union DenverCO United States Sharda University Computer Science & Engineering Greater Noida India Indraprastha Institute of Information Technology Computer Science & Applied Mathematics Delhi India Chandigarh University Department of Cse Punjab Mohali India

ISBN: (纸本)9798350342338

This paper examines how AI has revolutionised drug development and medical research using the ChEMBL dataset. The primary study areas are AI-driven therapeutic target identification., computational approaches in drug development., drug repurposing for COVID-19 therapies., and AI methods for natural leather flaw detection. Target selection must balance novelty and confidence., and AI-driven therapeutic target identification is considered. Structure-based virtual screening and profound learning predictions of ligand properties and target activities are considered for application in scaling up to broader chemical spaces. AI is used to discover new links between drugs., targets., and diseases and treat COVID-19. The paper also highlights this field's enforcement challenges and offers solutions. A Generative Adversarial Network (GAN)-based automatic flaw identification system for natural leather is another topic of study. The results show that the suggested strategy is economical and accurate., despite limitations and biases. AI has revolutionised medical diagnostics., medication development., and precision medicine., making this work meaningful. This paper's findings offer a cross-disciplinary perspective on artificial intelligence's potential in healthcare., revealing knowledge gaps and suggesting further research. © 2023 IEEE.

关键词： Artificial Intelligence Chemical Biology Database (ChEMBL) Dataset Computational Approaches COVID-19 Treatments Defect Identification Drug Discovery Drug Repurposing Generative Adversarial Network (GAN) Precision Medicine Therapeutic Target Identification

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