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5G New Radio: Dynamic Time Division Duplex Radio Resource Management Approaches

IEEE ACCESS 2021年 9卷 113850-113865页

作者： Samidi, F. S. Radzi, N. A. M. Ahmad, W. S. H. M. W. Abdullah, F. Jamaludin, M. Z. Ismail, A. Univ Tenaga Nas Inst Informat & Comp Energy IICE Kajang 43000 Selangor Malaysia Univ Tenaga Nas Coll Engn Dept Elect & Elect Engn Kajang 43000 Selangor Malaysia

The Internet of Everything is currently in demand and has burdened the network tremendously. Accommodating this exponential increase in demand will require improved Radio Resource Management technology. This problem can be curbed with higher spectrum bands, reevaluation of Time Division Duplex, deployment of software Defined Network, and Network Function Virtualization into 5G New Radio (NR) network. Therefore, this work aims to provide an in-depth survey on the recent resource management schemes that can be proposed for 5G NR enhancement by exploiting both rule-based algorithms and machine learning methods. Radio resource management consists of managing user allocation, the antenna transmission power, bandwidth, and modulation scheme. Therefore, in this paper, three categories of radio resource management technologies are introduced: resource allocation, energy efficiency, and interference management. The discussion revolves around their potentials and contributions as well as challenges faced to produce efficient 5G resource management schemes.

关键词： 5G mobile communication Transmitting antennas software algorithms Interference Quality of service Machine learning Energy efficiency 5G resource management machine learning wireless communication

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Effort Estimation in Agile software Development Using Autoencoders

Effort Estimation in Agile Software Development Using Autoen...

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International Conference on software Process Improvement (CIMPS)

作者： Eduardo Rodríguez Sánchez Eduardo Vázquez Santacruz Humberto Cervantes Maceda Departamento de Ing. Eléctrica PCyTI Universidad Autónoma Metropolitana Ciudad de México

ISBN: (数字)9798350358568

ISBN: (纸本)9798350358575

Effort estimation is important to correctly plan the use of resources in a software project. When adopting Agile in IT, business value is raised in both performance and quality. A gap in agile effort estimation is the lack of research combining software engineering models and deep learning techniques. During the planning phase the team involved makes an approximate estimation of time and cost based on artifacts and requirements obtained from initial interviews with clients and stakeholders. This paper aims to contribute with a hybrid effort estimation model that uses story points which measure the amount of effort needed to accomplish the project, team velocity which measures how many units of effort the team completes in a typical Sprint, and category size labels of effort, time and cost in order to estimate completion time and total cost of a project developed with agile methods like Scrum, The machine learning techniques used to implement the project are neural networks such as autoencoders and different variations of it. The learning capabilities are assessed through 10-Fold cross validation and the estimates are compared with the original dataset and the results obtained from literature. This research uses 21 projects developed by six software houses, a set of 42 noisy data is used for training created using data augmentation technique. Each project has two dependent variables that the algorithm tries to estimate and they are completion time measured in days and total cost valued in Pakistan rupees. The proposed approach compares the use of the original data as input versus the original data with the addition of category size labels. The main idea is that every project has three main features that are scope, time and cost. Since the current work is based on historical data the scope is always fixed and a single project can be estimated according to a hypothetical time or cost which can be small, medium or large.

关键词： Training Costs Phase measurement software algorithms Estimation Size measurement Time measurement

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An Open Source Platform for Computational Histopathology

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IEEE ACCESS 2021年 9卷 73651-73661页

作者： Yu, Xiaxia Zhao, Bingshuai Huang, Haofan Tian, Mu Zhang, Sai Song, Hongping Li, Zengshan Huang, Kun Gao, Yi ShenzhenUniv Hlth Sci Ctr Sch Biomed Engn Shenzhen 518060 Peoples R China Fourth Mil Med Univ Xijing Hosp Dept Ultrason Med Xian 710032 Peoples R China Fourth Mil Med Univ Xijing Hosp Dept Pathol Xian 710032 Peoples R China Indiana Univ Sch Med Indianapolis IN 46202 USA Regenstrief Inst Hlth Care Indianapolis IN 46202 USA Shenzhen Key Lab Precis Med Hematol Malignancies Shenzhen 518060 Peoples R China Marshall Lab Biomed Engn Shenzhen 518060 Peoples R China Pengcheng Lab Shenzhen 518066 Peoples R China

Computational histopathology is a fast emerging field which converts the traditional glass slide based department to a new examination platform. Such a paradigm shift also brings the in silico computation to the field. Much research have been presented in the past decades on the algorithm development for pathology image analysis. On the other hand, a comprehensive software platform with advanced visualization and computation capability, large developer community, flexible plugin mechanism, and friendly transnational license, would be extremely beneficial for the entire community. In this work, we present SlicerScope: an open platform for whole slide histopathology image computing based on the highly successful 3D Slicer. We present rationale on the choice of such an architecture, introducing new modules/tools for giga-pixel whole slide image viewing, and four specific analytical modules for qualitative presentation, nucleus level analysis, tissue scale computation, and 3D pathology. The entire software is publicly available at https://***/, facilitating the algorithmic, clinical, and transnational researches.

关键词： software Three-dimensional displays Histopathology software algorithms Image color analysis Microscopy Libraries Open-source platform computational pathology reproducibility

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Optimized Global Maximum Power Point Tracking of Photovoltaic Systems Based on Rectangular Power Comparison

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IEEE ACCESS 2021年 9卷 53602-53616页

作者： Bharadwaj, Pallavi John, Vinod MIT Lab Informat & Decis Syst Cambridge MA 02139 USA Indian Inst Sci Dept Elect Engn Bengaluru 560012 India

Global maximum power point tracking (GMPPT) refers to the extraction of the maximum power from photovoltaic (PV) modules in real time under changing ambient conditions. Due to the installation of PV systems in densely built-up areas, partial shading scenarios are commonplace. Commercially established GMPPTs suffer from low tracking speeds and inefficiency. A novel GMPPT algorithm is proposed here based on the rectangular power comparison (RPC), which exploits the fundamental relationship between the shading factor, the bypass diode voltage and the global maximum power point. The entire theoretical formulation of RPC is presented systematically for the first time. This method boasts of increased conversion speeds owing to the precomputation of the module voltage versus the shading factor correlations using the regression of diode model from the experimentally obtained bypass diode characteristics. The proposed method is simple to implement with the computational complexity of order n, which represents the number of uniquely shaded PV modules in a series string. The proposed approach addresses the much-needed intersection problem between the distributed and centralized PV systems and therefore targets PV strings which are most common in residential and small to medium scale commercial PV installations world over. The proposed approach is validated with the in-house developed prototype hardware set-up and software control implementation giving a 99% tracking efficiency with a recorded tracking time of 10 ms. The experimental results show 50 times improvement in speed and 95% increase in power gain as compared to the other popular existing methods namely scanning based GMPPT and local MPPT methods respectively, with negligible computational burden and less than 0.5% added cost to the conventional PV energy conversion system.

关键词： Maximum power point trackers software algorithms software Photovoltaic systems Optimization Inverters Temperature sensors Efficiency optimization global maximum power point tracking partial shading photovoltaic module measurements solar energy conversion

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Quantum Codesign

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IEEE MICRO 2021年第5期41卷 33-40页

作者： Tomesh, Teague Martonosi, Margaret Princeton Univ Comp Sci Dept Princeton NJ 08544 USA Princeton Univ Comp Sci Princeton NJ 08544 USA

Codesign has been an integral part of computer architecture since the very first systems were brought online. From the early days of the field until now, end-user applications inevitably shape the design and capabilities of subsequent generations of hardware. Likewise, the characteristics and capabilities of new computational hardware and systems often impact the algorithms and software that run on them. Quantum computing (QC) is similarly reliant on codesign approaches, particularly now in its resource constrained early days. This article discusses what codesign means in a QC setting, gives examples of its value to QC, and proposes key attributes of QC codesign approaches going forward.

关键词： Hardware Qubit Logic gates Quantum computing Topology software algorithms software

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From Warfighting Needs to Robot Actuation: A Complete Rapid Integration Swarming Solution

Field Robotics

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Field Robotics 2025年 3卷 460-515页

作者： Eugene M. Taranta Adam Seiwert Anthony Goeckner Khiem Nguyen Erin Cherry Northrop Grumman Corporation Mission Systems Orlando FL 32817 Northrop Grumman Corporation Mission Systems Aurora CO 80017 Northrop Grumman Corporation Mission Systems Annapolis MD 21401 Northrop Grumman Corporation Mission Systems McLean VA 22102

Swarm robotics systems have the potential to transform warfighting in urban environments but until now have not seen large-scale field testing. We present the Rapid Integration Swarming Ecosystem (rise), a platform for future multi-agent research and deployment. rise enables rapid integration of third-party swarm tactics and behaviors, which was demonstrated using both physical and simulated swarms. Our physical testbed is composed of more than 250 networked heterogeneous agents and has been extensively tested in mock warfare scenarios at five urban combat training ranges. rise implements live, virtual, constructive simulation capabilities to allow the use of both virtual and physical agents simultaneously, while our “fluid fidelity” simulation enables adaptive scaling between low and high fidelity simulation levels based on dynamic runtime requirements. Both virtual and physical agents are controlled with a unified gesture-based interface that enables a greater than 150:1 agent-to-operator ratio. Through this interface, we enable efficient swarm-based mission execution. rise translates mission needs to robot actuation with rapid tactic integration, a reliable testbed, and efficient operation.

关键词： Robots Robot sensing systems Hardware software Robot kinematics Ecosystems Command and control systems Swarm robotics Surveys software algorithms

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An Enhanced Beam Index Detection Scheme Robust to Timing Offset in a 5G software Modem

An Enhanced Beam Index Detection Scheme Robust to Timing Off...

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International Conference on Electronics, Information and Communications (ICEIC)

作者： Dawoon Lim Juyeop Kim Dept. of Electronic Engineering Sookmyung Women’s University Seoul South Korea

Unlike the Long Term Evolution (LTE), the 5G system faces an additional issue of detecting appropriate beams in a cell search phase. This paper investigates the effect of residual Symbol Timing Offset (rSTO) on the beam index detection in the 5G system and proposes a practical scheme that compensates for the effect of the rSTO in a software (SW) Modem environment. For evaluating the performance at an implementation level, we realize the proposed scheme on a real-time testbed and conduct experiments with commercial 5G base stations. The experimental results prove that the proposed scheme practically improves the detection probability with proper complexity.

关键词： 5G mobile communication software algorithms Symbols Modems Search problems software Real-time systems

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software Defect Prediction using Machine Learning

Software Defect Prediction using Machine Learning

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International Conference on Computing for Sustainable Global Development (INDIACom)

作者： Sayyed Ashar Ali Nihar Ranjan Roy Dharm Raj Department of Computer Science & Engineering School of Engineering &Technology Sharda University Greater Noida U.P. India

software engineering phases and approaches have always targeted to deliver high-performance software designed to fulfill a certain task while optimizing criteria such as length and price. In this particular study, while focusing on ML (machine learning) methodologies, the examination on the SDP (software defect prediction) strategies is performed. The purpose of study is to assess the interoperability of machine learning methods in the prediction of defects. Many experimental data have been provided by academicians that promise improved accuracy in software fault prediction. In the recent past, researchers have adopted Machine learning based techniques for software defect detection. We surveyed a list of notable research publications that have used machine learning approaches to anticipate software flaws. The most prevalent methods are NB (Nave Bayes), RF (Random Forest), and SVM (Support Vector Machine). Out of these it has been found that Naive Bayes performs better followed by Random Forest.

关键词： Support vector machines Radio frequency Machine learning algorithms software algorithms Prediction algorithms software Task analysis

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Artificial Intelligence based Electronics Engineering software Application System

Artificial Intelligence based Electronics Engineering Softwa...

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International Conference on Smart Systems and Inventive Technology (ICSSIT)

作者： Thiagarajan Kittappa C. Sandhya V. Krishnan Shilpa Sharma Deepti Khubalkar G. Ramachandran T. Muthumanickam Department of Mathematics K. Ramakrishnan College of Technology Samayapuram Trichy Management of Science S.A. Engineering College Chennai Department of Mathematics Jamal Mohamed College (Affiliated to Bharathidasan University) Trichy Symbiosis Internation al University Nagpur Maharashtr a ECE Vinayaka Mission’s KirupanandaVariy ar Engineering CollegeVinayaka Mission’s Research Foundation (Deemed to be University) Salem Tamil Nadu India Department of Electronics and Communication Engineering Vinay aka Mission’s Kirupananda Variyar Engineering College Vinay aka Mission’s Research Foundation - Deemed to be University Salem India

Science and technology are in a rapid development stage as a result of the advancement and progress of the times, and it is clear that the contemporary civilization has entered the era of Artificial Intelligence (AI). This research focuses on AI applications in the context of Industry 4.0 concept. This current work discusses AI acceptance in the manufacturing industry and its promotion in intelligence optimization. The Virtual model concept is presented to improve the rationale of various interfaces. The communication and information intelligence AI algorithms are examined in depth. The concept of a smart city and AI applications, as well as how AI plays a role in its implementation have been discussed.

关键词： Manufacturing industries 5G mobile communication Smart cities software algorithms Network security software Communications technology

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Agricultural Robot software with Machine Vision and Cognitive Artificial Intelligence Module

Agricultural Robot Software with Machine Vision and Cognitiv...

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Systems of Signals Generating and Processing in the Field of on Board Communications

作者： S. B. Benevolensky A. A. Sirotkin A. A. Kiryanov V. Yu. Sirotkin V. S. Ershov Moscow Automobile and Road Construction State Technical University (MADI) Moscow Russia LLC "Erlab" Moscow Russia

Article discusses the results of software development for growth and development automating processes the crops based on the artificial intelligence algorithms introduction. The main features of the developed software when using the parallelizing video capture streams method are highlighted. algorithms for the mobile and server parts of the cognitive module are developed, and its construction features are described. Server part program interface sample of the cognitive module obtained in the development course is given. The functional part list that software module performs during its operation is listed. The conclusion part that allows usage of developed software in order to automate and improve various agricultural plants fruit formation processes, while physical intervention factor on them minimizing is obtained.

关键词： Plants (biology) software algorithms Crops Vegetation mapping Prototypes Streaming media software

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