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SSRN 2024年

作者： El Aouni, Fatiha Moumane, Karima Idri, Ali Najib, Mehdi Jan, Saeed Ullah Software Project Management Research Team National School of Computer Science and Systems Analysis Mohammed V University in Rabat Rabat10112 Morocco MSDA University Mohamed VI Polytechnic Ben Guerir Morocco TICLab College of Engineering and Architecture International University of Rabat Sala Al Jadida Morocco Higher Education Department Govt Degree College Wari Dir Upper 18200 Pakistan

Context : In today’s fast-paced digital landscape, integrating DevOps, cloud, and agile methodologies is crucial for meeting software demands. However, this integration remains *** : This study explores the integration of Agile, Cloud, and DevOps in today’s software development landscape. It aims to analyze the challenges and benefits associated with merging these three approaches, focusing on its impact on software testing and the role of mindset in successful implementation and identifying the most suitable Agile *** : This investigation utilizes a Systematic Literature Review(SLR) to enrich comprehension of these integrations in current software development *** : The analysis of 31 articles highlights benefits such as improved collaboration and accelerated development, despite challenges with tool proliferation. Platforms like Jenkins, GitLab, Kubernetes, and Docker show promise in addressing these complexities. Our study examines the advantages and challenges of this integration, focusing on its impact on software testing and the role of mindset in successful implementation and identifyingthe most suitable Agile *** : The integration of Agile, DevOps, and Cloud signifies a vital move towards collaborative, scalable, and automated methods, crucial for swift delivery, enhanced quality, and ongoing competitiveness. This unified approach is fundamental for organizational advancement and innovation in the ever-evolving software development realm. Further research should tackle challenges in merging these methods and delve into their interactions with emerging technologies to refine practices for increased efficiency. © 2024, The Authors. All rights reserved.

关键词： Integration

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Learning assistant to acquire the fundamental language skills for non-native learners using AI 2

Learning assistant to acquire the fundamental language skill...

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2nd International Conference on Advancements in Computing, ICAC 2020

作者： Srikanthan, Praveenkumar Nizar, Roshan Ravikumar, Abishaan Lalitharan, Keerthigan Harshanath, S.M.B. Alosius, Jesuthasan Sri Lanka Institute of Information Technology Department of Computer Science and Software Engineering Malabe Sri Lanka Sri Lanka Institute of Information Technology Department of Computer Systems Engineering Malabe Sri Lanka Sri Lanka Institute of Information Technology Department of Information Technology Malabe Sri Lanka

ISBN: (纸本)9781728184128

The ability to speak and learn a language properly requires good practice, experience and good learning strategies but the existing solutions do not provide proper guidance to learn a language with instant feedback. This research is an approach to devise an improved language learning assistant with practices that will help to improve the fundamental language skills for non-native learners and children who are in the early stage of their education. The four main skills focused on this application will be conversation, pronunciation, listening and grammatical skills. The implementation of this research is done by using technologies like natural language processing, machine learning, and deep learning approaches to come up with components to train the learner. The solution of this research is delivered by using a cross-platform application called GLIB which facilities to improve all the English language skills mentioned above along with guides, tips, practices, and feedback based on an evaluation to improve the English language. © 2020 IEEE.

关键词： Deep learning

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Model of Formation of Ecological Competence of Future Engineers-Electromechanics 20

Model of Formation of Ecological Competence of Future Engine...

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20th IEEE International Conference on Modern Electrical and Energy systems, MEES 2021

作者： Soloshych, Iryna Shvedchykova, Iryna Grynyov, Roman Kononets, Natalia Bunetska, Iryna Kremenchuk Mykhailo Ostrohradskyi National University Department of Ecological Safety and Natural Management Kremenchuk Ukraine Kyiv National University of Technologies and Design Department of Computer Engineering and Electromechanics Kyiv Ukraine Ariel University Faculty of Physics Ariel Israel University of Ukoopspilks 'Poltava University of Economics and Trade' Business Economics and Information Systems Department of Economic Cybernetics Poltava Ukraine Lanzhou University Department of Foreign Languages and Literatures Lanzhou China

ISBN: (纸本)9781665423663

The article reveals the concept of environmental competence of future electromechanical engineers as a manifestation of the acquisition of environmental knowledge and skills to apply them in their professional and domestic activities. The components of ecological competence of future electromechanical engineers are characterized as: value-motivational, cognitive, and operational activity. It was found that the allocation of three interdependent and interdependent components allows to quickly manage the process of formation of environmental knowledge, providing mobility and direction, as well as the prerequisites for creating a system of professional activities, consisting of special and environmental activities. The model of formation of ecological competence of future engineers-electromechanics is offered and results of its experimental approbation during the distance educational process are presented. © 2021 IEEE.

关键词： Distance education

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Optimizations of friction stir welding process parameters of AA6063 Aluminium alloy by Taguchi technique

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Materials Today: Proceedings 2021年 46卷 4008-4013页

作者： K. Umanath K. Palanikumar Veeramalai Sankaradass K. Uma Department of Mechanical Engineering Academy of Maritime Education and Training AMET University Chennai 603112 India Sri Sairam Institute of Technology Chennai 600044 India Department of Computer Science and Engineering ISL Engineering College Hyderabad Telangana 500005 India Department of Software and Systems Engineering School of Information Technology and Engineering VIT University Vellore 632014 India

The effects of axial force, rotational speed, welding speed, and shoulder penetration on various Process parameters of Aluminium alloy 6063 butt joint produced by Friction Stir Welding have been analyzed. The mechanical properties like tensile strength , Yield strength, and % Elongation have been tested using a 6 mm thickness plate. The tool used for experimenting was Hot Die Steel (HDS). The welding quality can be improved by enhancing the mechanical properties and minimizing the defects. Hence, analyzing & examining the mechanical or physical properties and other relevant significant factors would enhance the weldability . Tensile Strength (T.S.), Percentage of Elongation & Yield Strength (Y.S.) of FSW Al 6063 alloy has been carried out under different processing conditions using Taguchi's experimental design.

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Reinforcement-Learning Based Method for Accelerating Functional Coverage Closure of Traffic Light Controller Dynamic Digital Design

Reinforcement-Learning Based Method for Accelerating Functio...

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International Conference on computer Theory and Applications (ICCTA)

作者： Youstina M. Halim Khaled A. Ismail Mohamed A. Abd El Ghany Sameh A. Ibrahim Youssef M. Halim Mixel Egypt. Electronics and Communications Engineering Dept. Faculty of Engineering Ain Shams University Cairo Egypt GSI Helmholtz Center for Heavy-Ion Research GmbH (GSI) Germany Electronics Department German University in Cairo Egypt. Integrated Electronic Systems Lab TU Darmstadt Germany Electronics and Communications Engineering Department Faculty of Engineering Ain Shams University Cairo Egypt Computer Engineering and Software Systems Dept. Faculty of Engineering Ain Shams University Cairo Egypt

Functional verification of digital designs is an increasingly complex and time-consuming endeavor. One of the major challenges in functional verification is achieving functional coverage closure in a timely manner. Verification experts have moved from using directed stimulus, towards constrained random stimulus and finally, towards using machine learning to direct stimulus. In this work, reinforcement learning (RL) was used, incorporating three different kinds of RL agents to direct stimulus generation for a traffic light controller system. Two of the agents are based on Q-learning (DQN and SARSA), and one is based on Monte-Carlo method (CEM). The maximum reduction in simulation time needed to achieve a targeted percent of coverage was 97%. The average reduction of simulation time across all testcases and agents used was 70%. The solution is highly reusable, the architecture was integrated with different agents and testcases.

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A performance comparison of graph analytic methods for supporting enterprise architecture model maintenance

A performance comparison of graph analytic methods for suppo...

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2019 Practice of Enterprise Modelling Conference Forum, PoEM 2019 Forum

作者： Rajashekar, Nikhitha Hacks, Simon Silva, Nuno Research Group Software Construction RWTH Aachen University Germany Division of Network and Systems Engineering KTH Royal Institute of Technology Sweden Department of Computer Science and Engineering Technical University of Lisbon Lisbon Portugal

Enterprise Architecture (EA) models help enterprise architects to make business decisions and to support organisations to understand and analyse its structure. Creating and maintaining such an EA model is expensive and time-consuming in large organisations. In this paper, the authors provide a review of how graph analytic methods can be used to support EA model maintenance. To achieve the best results for the duplicate identification, it is necessary to evaluate and optimise different graph analytic and Machine Learning (ML) algorithms to support the maintenance process. Copyright © 2020 for this paper by its authors. Use permitted under Creative Commons License Attribution 4.0 International (CC BY 4.0).

关键词： Machine learning

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Subsentence extraction from text using coverage-based deep learning language models

arXiv

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arXiv 2021年

作者： Lim, JongYoon Sa, Inkyu Ahn, Ho Seok Gasteiger, Norina Lee, Sanghyub John MacDonald, Bruce CARES Department of Electrical Computer and Software Engineering University of Auckland New Zealand CSIRO Data61 Robotics and Autonomous Systems Group Dynamic Platforms

Sentiment prediction remains a challenging and unresolved task in various research fields, including psychology, neuroscience and computer science. This stems from its high-degree of subjectivity and limited input sources that can effectively capture the actual sentiment. This can be even more challenging with only text-based input. Meanwhile, the rise of deep learning and an unprecedented large volume of data have paved the way for artificial intelligence to perform impressively accurate predictions or even human-level reasoning. Drawing inspiration from this, we propose a coverage-based sentiment and subsentence extraction system that estimates a span of input text and recursively feeds this information back to the networks. The predicted subsentence consists of auxiliary information expressing a sentiment. This is an important building block for enabling vivid and epic sentiment delivery (within the scope of this paper) and for other natural language processing tasks such as text summarisation and Q&A. Our approach outperforms the state-of-the-art approaches by a large margin in subsentence prediction (i.e., Average Jaccard scores from 0.72 to 0.89). For the evaluation, we designed rigorous experiments consisting of 24 ablation studies. Finally, our learned lessons are returned to the community by sharing software packages and a public dataset that can reproduce the results presented in this paper. © 2021, CC BY.

关键词： Sentiment analysis

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Optimization of wear properties on AA7075/Sic/Mos 2 hybrid metal matrix composite by response surface methodology

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Materials Today: Proceedings 2021年 46卷 4019-4024页

作者： K. Umanath K. Palanikumar Veeramalai Sankaradass K. Uma Deaprtment of Mechanical Engineering Acadamy of Maritime Education and Training Chennai 603112 India Sri SairamInstitute of Technology Chennai 600044 India Department of Computer Science and Engineering ISL Engineering College Hyderabad Telangana 500005 India Department of Software and Systems Engineering School of Information Technology and Engineering VIT University Vellore 632014 India

Nowadays, composites are profoundly thriving as the replacement of ferrous alloys . The Aluminum manifested into a great substitute due to its properties like lightweight, low density, high strength, and corrosion resistance . The process of fusing the non-ceramics reinforcement like Silicon carbide , Boron carbide , Aluminum oxide , Titanium diboride with a non-metal like Graphite, Molybdenum disulfide or with other non-ceramic to form a hybrid metal matrix composite . In the present paper, an investigation carried out on Aluminum 7075 material by the process of stir casting where the Silicon Carbide (SiC) with three different weight % (i.e., 3%, 6%, 9%) and Molybdenum Disulphide (MoS 2 ) with 1% constant weight % added to the base material. The tensile test and hardness test were then done on a UTM and Rockwell Hardness testing machine, respectively, for all three prepared materials. As the percentage of SiC increases in the material, the hardness value and tensile strength are increasing. The Al7075 + 9%SiC + 1%MoS 2 is the highest of all.

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Accelerating Real-Time Imaging for Radiotherapy: Leveraging Multi-GPU Training with PyTorch 22

Accelerating Real-Time Imaging for Radiotherapy: Leveraging ...

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22nd IEEE International Conference on Machine Learning and Applications, ICMLA 2023

作者： Obe, Ruth Kaufmann, Brandt Baird, Kaelen Kadel, Sam Soltani, Yasmin Cham, Mostafa Gobbert, Matthias K. Barajas, Carlos A. Jiang, Zhuoran Sharma, Vijay R. Ren, Lei Peterson, Stephen W. Poif, Jerimy C. U. of Houston-Clear Lake Dept. of Computer Science and of Software Engineering United States U. of San Francisco Dept. of Mathematics and Statistics United States Skidmore College Dept. of Computer Science and of Mathematics United States Mount Holyoke College Dept. of Computer Science and of Psychology United States U. of Houston Dept. of Biomedical Engineering United States U. of Maryland Dept. of Information Systems Baltimore County United States U. of Maryland Dept. of Mathematics and Statistics Baltimore County United States Medical Physics Graduate Program Duke University United States U. of Maryland School of Medicine Dept. of Radiation Oncology United States U. of Maryland School of Medicine Department of Radiation Oncology United States U. of Cape Town Dept. of Physics South Africa H3D Inc. United States

ISBN: (纸本)9798350345346

Proton beam therapy is an advanced form of cancer radiotherapy that uses high-energy proton beams to deliver precise and targeted radiation to tumors. This helps to mit-igate unnecessary radiation exposure in healthy tissues. Real-time imaging of prompt gamma rays with Compton cameras has been suggested to improve therapy efficacy. However, the camera's non-zero time resolution leads to incorrect interaction classifications and noisy images that are insufficient for accurately assessing proton delivery in patients. To address the challenges posed by the Compton camera's image quality, machine learning techniques are employed to classify and refine the generated data. These machine-learning techniques include recurrent and feedforward neural networks. A PyTorch model was designed to improve the data captured by the Compton camera. This decision was driven by PyTorch's flexibility, powerful capabilities in handling sequential data, and enhanced G PU usage. This accelerates the model's computations on large-scale radiotherapy data. Through hyperparameter tuning, the validation accuracy of our PyTorch model has been improved from an initial 7 % to over 60 %. Moreover, the PyTorch Distributed Data Parallelism strategy was used to train the RNN models on multiple G PU s, which significantly reduced the training time with a minor impact on model accuracy. © 2023 IEEE.

关键词： Clas-sification Compton camera Distributed Data Parallelism Proton beam therapy PyTorch Recurrent neural network

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Research of modern opportunities for obtaining the grant support for innovative projects financing 4

Research of modern opportunities for obtaining the grant sup...

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4th International Scientific Conference on Agribusiness, Environmental engineering and Biotechnologies, AGRITECH-IV 2020

作者： Zolkin, A.L. Aygumov, T.G. Pakhomova, A.I. Bobkov, V.V. Computer and Information Sciences Department Povolzhskiy State University of Telecommunications and Informatics L. Tolstogo Street 23 Samara443010 Russia Department of Computer Engineering Software and Automated Systems Dagestan State Technical University I. Shamyl Street 70 Makhachkala367000 Russia of DSTU in Shakhty Shevchenko Street 147 Shakhty346500 Russia Department of Physical Education and Sports Gubkin Russian State University of Oil and Gas Leninsky prospect 65 Moscow119991 Russia

This paper examines innovative, including social entrepreneurship and modern opportunities for obtaining grant support for financing innovative projects, including social ones. The possibility of receiving grants from various funds is being considered. Detailed attention is paid to the stages of project development for drawing up an application for grant funding. Attention is drawn to certain nuances in the writing and processing of grant applications. We also conduct research on current conditions and factors that influence the development of innovative entrepreneurship, and compare Russian indicators with foreign ones. Detailed attention is paid to economic and innovative conditions, educational factors, measures to promote competition and tax incentives. © Published under licence by IOP Publishing Ltd.

关键词： Taxation

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