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Adaptation of Natural Gradient Boosting Model for Production Environment 4

Adaptation of Natural Gradient Boosting Model for Production...

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4th international conference on Control Systems, Mathematical Modeling, automation and Energy Efficiency, SUMMA 2022

作者： Tyurin, Alexey Sergeevich Saraev, Pavel Viktorovich Lipetsk State Technical University Dept. of Informatics and Computer Engineering Lipetsk Russia Lipetsk State Technical University Lipetsk Russia

ISBN: (数字)9781665456593

ISBN: (纸本)9781665456593

Application of mathematical models in a production environment is associated with solving many complex engineering and analytical problems, one of which is to evaluate the quality of such a model and assess the economic and technological effect. The paper shows how the worst model according to classical metrics can show the best results in production. © 2022 IEEE.

关键词： Training Economics Adaptation models Temperature distribution Time series analysis Production Mathematical models

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Modeling and Simulation of Helicopter Data Link Availability Based on Markov 5

Modeling and Simulation of Helicopter Data Link Availability...

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5th international conference on computer Network, Electronic and automation, ICCNEA 2022

作者： Zhao, Qianqian Lu, Ying Fan, Nierui Liu, Jin Chen, Yusi Fu, Yanfang Xi'an Technological University School of Computer Science and Engineering Xi'an China

ISBN: (数字)9781665491099

ISBN: (纸本)9781665491099

Data link is a communication and command system that transmits and distributes formatted messages, which can connect the originally independent combat platforms with each other. The high reliability service provided by the high availability helicopter data link is the guarantee of the combat command, so it is an urgent need to evaluate the availability of the helicopter data link system. Based on the availability theory and Link-16 data link technology, this paper presents a Markov steady-state availability model for evaluating the availability of data link systems. The experimental results show that the steady-state availability model and service availability model of the proposed data link system have certain credibility and correctness. This provides an operational method for the usability evaluation of data link network system, and has a certain reference value. © 2022 IEEE.

关键词： Availability

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The Impact of Tamil Python Programming in Wikisource 2nd

The Impact of Tamil Python Programming in Wikisource

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2nd international conference on Speech and Language Technologies for Low-Resource Languages, SPELLL 2023

作者： Vinoth, A. Thangasamy, Sathiyaraj Nithya, R. Subalalitha, C.N. Mahendhiran, P.D. Info-Farmer Sri Krishna Adithya College of Arts and Sciences Coimbatore641042 India Avinashi641654 India SRM College of Engineering and Technology Kattankulathur Chennai India Sri Krishna College of Engineering and Technology Coimbatore641042 India Tamil Wikimedian Attur Salem636102 India

ISBN: (纸本)9783031584947

Wikipedia, Wiktionary, Wikisource, Wikinews, Wikiquote, Wikiversity, Wikitour, Meta-Wiki, and Wikimedia are all Wikimedia projects that provide copyright-free data. Among these, Wikisource stands out as an online library utilized by 72 languages. Tamil Wikisource specifically caters to Tamil-language content, converting image-based data into text format. While human resources and automated methods contribute to data improvement, this research paper proposes the implementation of a Python program in Tamil for automation to further enhance or operate the Tamil Wikisource project. Given that most volunteers working on Wikimedia projects in Indian languages may be more comfortable with their native language rather than English, this paper highlights the efforts made by Info Farmer in writing Python programs for Wikisource. This initiative is expected to open up more possibilities for scaling similar projects in other Indian languages, thereby assisting volunteers in Wikimedia projects. Additionally, the individual has developed over a hundred Python programs in Tamil, enhancing more than two lakh pages. This underscores a potential lack of awareness regarding the capability to create computer programming content in native languages, a phenomenon not exclusive to Tamil but applicable to other Indian languages as well. The primary aim of this article is to emphasize that when volunteers from various Indian languages recognize this potential, they can develop the necessary automation tools for their respective languages. Consequently, this research paper delves into topics such as wiki projects, the voluntary contributions of individuals involved, the noteworthy Tamil Python contributions of Info-farmer—a Tamil Wikimedian—the use of Python keywords written and executed in Tamil, an exploration of how Python functions, an overview of PAWS (Python Data Science environment for Jupyter notebooks), PyWikiBot, and outlines plans for future activities in detail. © The Author(s),

关键词： Python

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A Novel Method for Technical Candidate Assessment using Github Repository Inspection automation 12

A Novel Method for Technical Candidate Assessment using Gith...

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12th international conference on computer Communication and Informatics, ICCCI 2022

作者： Gupta, Sambhav Gupta, Bhoomi Gupta, Sachin Maharaja Agrasen Institute of Technology Department of It Delhi India School of Engineering and Technology Mvn University Haryana India

ISBN: (纸本)9781665480352

The IT industry is scaling new peaks of recruitment with every passing month of the year 2021. The recruiters and talent scouts for technical schools are having a hard time finding suitable technical candidates for a preliminary assessment by the resume alone. A solution to this problem can be envisaged in a summary inspection of the public Github repositories of the potential candidates. Given a flood of incoming candidate profiles, the manual process of repository inspection is time consuming and cumbersome, besides being inaccurate and therefore it is needed to automate the Github technical repository inspection process. This paper examines the use of GitHub REST API to fetch the details and repositories of a GitHub user by searching the username and making this a user interactive process through ReactJs. The paper has been written as a part of a Graduate project study, and the objective of repository collection automation has been successfully demonstrated with an appropriate user interface with discussion of the application use cases. © 2022 IEEE.

关键词： Inspection

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AI-Automated System for Ingredient Planner using Machine Learning Algorithms 7

AI-Automated System for Ingredient Planner using Machine Lea...

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7th international conference on I-SMAC (IoT in Social, Mobile, Analytics and Cloud), I-SMAC 2023

作者： Arvindaraj, G. Manikandan, B. Rokesh, R. Abinaya, M. Karpagam Academy of Higher Education Department of Computer Science and Engineering Coimbatore India

ISBN: (纸本)9798350341485

There are numerous delicious Indian recipes available with the same ingredients. The traditional recipes differ based on the availability of vegetables, spices, herbs, and fruits. This necessitates the need to verify the ingredients used in preparing a food recipe. This proposed system, AI-based Industrial automation enabled with mobile access is planned and designed with the help of dataset to be the best possible solution. The aim is to develop an AI-Automated System using a Machine Learning (ML) technique called Adaptive (AdaBoost) and Gradient Boosting algorithm (AGBA) in the food sector to examine the food recipe ingredients. The data gathered for the food items with their requirements has been considered as the data set in this study. By using the data set, Industrial automation System with Ingredient Planner app is developed and automated. The main principle behind these boosting techniques is to build a model with a training dataset and then rectify the faults present in the previously built model. This principle is sustained as long as the faults are reduced and the training dataset is estimated correctly. Further, a multi-functional approach will be implemented to employ Big Data for examining the ingredients of food menu, computational time, labor-intensive estimation time, and food wastage. © 2023 IEEE.

关键词： Machine learning

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Visual Cloud Processing System for Intelligent Management of Real-Time Laboratory Data 14th

Visual Cloud Processing System for Intelligent Management of...

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14th international conference on Frontier Computing, FC 2024

作者： Chen, Licong School of Film Television and Communication Xiamen University of Technology Fujian Xiamen361024 China

ISBN: (纸本)9789819627974

The development of Internet of Things technology provides a real-time data collection platform for laboratory management, and data visualization provides new ideas for object-oriented behavior management. This article introduces an intelligent laboratory management system with a computer as the core and introduces it in detail. This article compares the performance of typical visualization systems at home and abroad, and discusses the development and implementation of a typical intelligent laboratory management system, the visual expression of the system, and its impact on the behavior of experimenters. The article empirically analyzes the role of behavior in laboratory learning and proposes ideas for further development (Before the system was put into use, employees in the position spent 2.18 h processing laboratory data every day, and after the system was put into use, it only took 1.02 h, indicating that the put into use of the system can effectively reduce the time spent on data processing). © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： automation and Data Analysis Laboratory Intelligent Management Real-Time Data Visual Processing

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Prediction based Auto-Pilot Interface for Drone to Object Chasing using Historical TSPI Data 23

Prediction based Auto-Pilot Interface for Drone to Object Ch...

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23rd international conference on Control, automation and Systems, ICCAS 2023

作者： Jang, Shinhyoung Park, Byeonghwi Jeong, Juheon Mahedy, Jack Gebreslassie, Nebey Lee, Minji Matson, Eric T. Chungnam National University Department of Computer Science and Engineering Daejeon34134 Korea Republic of Purdue University Department of Computer and Information Technology West LafayetteIN47906 United States Purdue University Department of Technology West LafayetteIN47906 United States

ISBN: (纸本)9788993215274

Replacing military aircraft with Unmanned Aerial Vehicles (UAV) offers advantages such as reducing costs and risks associated with conventional military aircraft. To defend against enemy UAV attacks, anti-drone systems are used. While most technologies focus on drone detection, this paper proposes a process of tracking targets using arbitrary UAV to enhance camera data quality or directly engage and neutralize targets. The system comprises drone detection, movement prediction, and chasing. Devices such as radar are used to detect drones, and they provide Time-Space-Position Information (TSPI) using suitable data formats. Using Machine Learning (ML) techniques make it feasible to predict an object's future location, represented with equations. Utilizing trained machine learning models, the Auto-pilot Application Programming Interface (API) of the drone is employed to track based on the predicted results. Through experiments, the feasibility of predicting an object's future location using various ML techniques has been confirmed. Furthermore, verification has been conducted to establish the attainability of implementing the Auto-pilot API through the utilization of DJI's API. © 2023 ICROS.

关键词： Drones

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Enhancing Cyber Security in IoT Systems via Federated Learning

Enhancing Cyber Security in IoT Systems via Federated Learni...

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2023 international conference on Power Energy, Environment and Intelligent Control, PEEIC 2023

作者： Ranjan, Vivek Haripriya Jain, Sandeep Kumar Noida Institute of Engineering & Technology Department of Computer Science Uttar Pradesh Greater Noida India Computer Science Engineering Department Bangalore India Vivekananda Global University Department of Electrical Engineering Jaipur India

ISBN: (纸本)9798350357769

The integration of the Internet of Things (IoT) in the evolution of electronic grids, smart neighborhoods, and innovative concepts has empowered decision-makers with data utilization and enhanced automation across various domains. Despite these advancements, the subpar cybersecurity standards in connected devices within the hyper-connected environment of IoT networks pose security threats that could jeopardize the daily operations of medical centers, municipalities, and other organizations. To mitigate potential risks, it is imperative to bolster the security features of IoT devices before their integration into broader platforms. This exploration expected to devise an extensive methodology, comprising of seven phases, for executing solidifying tasks to lessen the assault surface. Utilizing the Favored Detailing Materials for Orderly Examinations and meta-investigation strategies, we led a broad writing audit. By taking on a system that tends to security components at every one of the three degrees of IoT plan, we figured out a suggested approach for assessing the security level of an IoT item. To survey the assault surface, a fitted gamble lattice well defined for IoT was created. At last, a technique enveloping reinforcing and weakness evaluation is proposed to decrease the assault surface and raise the wellbeing rating of a Web of Things (IoT) arrangement. © 2023 IEEE.

关键词： Attack surface Cyber threats Cybersecurity framework Internet of Things IoT hardening IoT security enhancement Risk analysis Security posture and ISO standards Vulnerability assessment

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Cloud Computing Security: A Comprehensive Review of Machine Learning Algorithms 2

Cloud Computing Security: A Comprehensive Review of Machine ...

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2nd IEEE international conference on IoT, Communication and automation Technology, ICICAT 2024

作者： Alsalami, Zaid Salim, Mohammed Hussein Al-Saidi, Imad Al-Din Alaak, H.H. Khaddour, Reem Hamdan Kareem Taaban, Nabaa Abdel Amir, Zahraa Naji The Islamic University College of Technical Engineering Department of Computers Techniques Engineering Najaf Iraq Al-Farahidi University Baghdad Iraq Al-Kunooze University College Computer Engineer Department Basra Iraq The University of Mashreq Baghdad10021 Iraq Mazaya University College Thi-Qar Iraq Kut University College Business Administration Department Wasit Al Kut52001 Iraq Uruk University Baghdad Iraq

ISBN: (纸本)9798350368109

Utilizing the cloud implies having organized assets, particularly information and administration, accessible at whatever point you would like them without requiring uncommon client courses of action. More as of late, CC has developed into a arrange of both open and private datacenters advertising clients a single online course of action. By putting preparing and information capacity closer to the end clients, edge computing may be a forward-thinking approach to computers that guarantees to speed up reaction times and spare transfer speed. Versatile phone applications are dispersed by means of versatile gadgets that give scattered computing. By the by, security concerns with CC and edge computing, such deciding client defenselessness and organization together declaration, make it troublesome to rapidly distinguish compute models. Machine learning is the consider of computational processes on computers that truly gotten to be way better with involvement. In this investigate extend, we offer an examination of CC security dangers, issues, and strategies that utilize one or more ML calculations. Fortification, semi-supervised, uncontrolled, and synchronized learning are among the obvious machine learning computations that are surveyed in arrange to fathom cloud security issues. Following, we compare the points of interest, drawbacks, and focuses of intrigued of each methodology to decide how viably it was executed. Furthermore, we select to investigate up and coming ponders centered on secure CC models. Since cloud computing offers unmatched adaptability, adaptability, and cost-efficiency, it has totally changed how businesses store, process, and oversee information. But this fast acknowledgment has moreover brought up genuine security issues, requiring solid and intelligent security strategies to defend basic information. With the improvement of advanced strategies for danger location, inconsistency recognizable proof, and interruption avoidance, machine learning (ML) a

关键词： Cloud security

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Workflow Task Offloading Upon MEC: A Novel Mobility-Aware and Clustering-Based Approach 31st

Workflow Task Offloading Upon MEC: A Novel Mobility-Aware a...

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31st international conference on Web Services, ICWS 2024, Held as Part of the Services conference Federation, SCF 2024

作者： Wang, Tenghui Feng, Jiafeng Ma, Yong Xia, Yunni Yu, Yang Dong, Yumin Xu, Xifeng Li, Jinpeng Zhao, Han Dai, Mengxuan College of Computer Science Chongqing University Chongqing400030 China China Huadian Corporation Ltd. Guangdong Company Guangzhou510620 China School of Computer and Information Engineering Jiangxi Normal University Jiangxi Nanchang330022 China Guodian Nanjing Automation Co. Ltd. Nanjing210032 China College of Computer and Information Science Chongqing Normal University Chongqing401331 China

ISBN: (纸本)9783031770715

The widespread deployment of intelligent Internet of Things (IoT) devices brings strict latency demands on complex workload patterns such as workflows. In such scenarios, tremendous data is generated and processed in accordance with specific service chains. Mobile Edge Computing (MEC) has proven its feasibility in reducing the traffic in the core network and relieving cloud datacenters of fragmented computational demands. However, existing solutions to multi-workflow scheduling and offloading in MEC are still limited due to the fact that they usually make task dispatching decisions prior to real execution, making it difficult to cope with the dynamicity of the environment and the mobility of users. To address this challenge, we developed a novel computation offloading strategy by synthesizing a Harris Hawks Optimization-based particle filter trajectory prediction algorithm for forecasting future user locations, a clustering-based multi-workflow merging algorithm for identifying redundant tasks and a Lyapunov optimization-based DQN algorithm for yielding computation offloading schedules. Simulation results clearly show that method beats traditional ones across multiple performance metrics. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： Computation offloading

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