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Architecture of the Conference Organization Software Application 13th

Architecture of the Conference Organization Software Applica...

引用

13th Computer Science Online Conference

作者： Zhyrova, Tetiana Kotenko, Nataliia Yushchenko, Oleksandr State Univ Trade & Econ Kyiv Ukraine

ISBN: (纸本)9783031702846;9783031702853

The article discusses platforms for organizing conferences. These platforms provide for the registration of the conference, registration of its participants: organizers, authors, reviewers, and ensure the organization of the process of working on articles or other publications. Examples of some of the most popular platforms are considered, and their advantages and disadvantages are identified. The article notes that a study has been conducted which found that the existing platforms are difficult to use by people who have little or no experience in organizing and participating in conferences. This situation can demotivate students and young scientists in organizing and participating in conferences. This paper is devoted to the development of a conference organization application using microservice software architecture. The main purpose of the work is to analyse existing platforms for organizing conferences: registration, submission of conference materials and blind peer review. During the survey of satisfaction with the existing platforms of conference participants, the requirements for the new platform were established. To implement the application, modern programming and deployment technologies were used, and the requirements were analysed to make appropriate decisions about the application design. The resulting system can be used for holding scientific conferences, namely for collecting materials and articles, giving ratings, comments, communicating with participants, and searching for articles that meet the requirements of the conference.

关键词： platforms for organizing and holding conferences functionality of the software requirements precedent diagram software product model

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Monitoring Strategies of a Company by the Model Checking-Based Business Process 9th

Monitoring Strategies of a Company by the Model Checking-Bas...

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9th International Congress on Information and Communication Technology (ICICT)

作者： Ouaar, Hanane Mohamed Khider Univ Dept Comp Sci Biskra Algeria Univ Biskra LINFI Lab Biskra Algeria

ISBN: (纸本)9789819735556;9789819735563

An agile system design based on the agent and model checker paradigms is proposed in this study to monitor the company's strategy. The proposed framework addresses tow levels one for the strategy the other for the supervision to develop a multi-agent system that uses monitoring protocol primitives, to carry out a strategy analysis and implements many mobile agents, to take actual measures to improve the internal or external business process efficiency. As a result, the current strategy uses an expanded balanced score card (BSC) to assist decision-making by giving visibility on the status of business processes. When the interaction of a business process planning is specify by formal methods and verified using temporal logic and model checker. The traces of the cooperative behavior has been recorded at a run time without conflicts. The developed system's specificity is associated with its agility, which refers to how simple it is to modify or improve a system component undependably to the rest of the other components.

关键词： Business process Strategy system Formal techniques TCTL Monitoring protocol Agile property

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Method for Intelligent Optimization of Adaptive Terminal Control of Product Output of an Enterprise

Method for Intelligent Optimization of Adaptive Terminal Con...

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International Conference on Intelligent and Fuzzy systems (INFUS)

作者： Shorikov, Andrey F. Russian Acad Sci NN Krasovskii Inst Math & Mech Ural Branch Ekaterinburg Russia Russian Acad Sci Inst Econ Ural Branch Ekaterinburg Russia

ISBN: (纸本)9783031671944;9783031671951

The article discusses the problem of intelligent optimization of adaptive control of product output of a manufacturing enterprise. To simulate the dynamics of the process under consideration, a mathematical model has been developed in the form of a system of linear discrete-time recurrent equations. This model contains the phase vector of the controlled object (an enterprise), the vector of demand for the enterprise's products and the vector of the control influence (control) of the control subject. During the control process, at each time period the control subject knows (measures) the phase vector of the controlled object. The quality of the control process is assessed by a convex objective function, the values of which are determined on the final phase states of the controlled object. This article proposes a mathematical formalization of the problem of intelligent optimization of adaptive terminal control of product output of an enterprise in the presence of a convex objective function. For the problem under study, a constructive method for solving it is given, which allows us to develop numerical algorithms for creating intelligent software systems and automating support for management decision-making by managers of manufacturing enterprises.

关键词： manufacturing enterprise system of a linear discrete-time recurrent equations intelligent optimization of adaptive control convex objective function

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Meta-Learning for Time Series Analysis and/or Forecasting: Concept Review and Comprehensive Critical Comparative Survey 1

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15th International Conference on Autonomous systems

作者： Kambale, Witesyavwirwa Vianney D'Ambrosi, Denis Fasouli, Paraskevi Kyamakya, Kyandoghere Univ Klagenfurt Inst Smart Syst Technol Univ Str 65-67 A-9020 Klagenfurt Austria

ISBN: (数字)9783031614187

ISBN: (纸本)9783031614170;9783031614187

Meta-Learning has emerged as a solution to address the limitations of data unavailability and the lack of extensive computing resources. The aim of this work is to consolidate a discussion on the application of Meta-Learning in Time Series forecasting, specifically by comprehensively contrasting Zero-Shot Learning (ZSL), One-Shot Learning (OSL), and Few-Shot Learning (FSL). In our implementation setup, the comparative analysis of results identifies Few-Shot Learning as the best performer and One-shot learning as the worst. The performance improvement registered for FSL is credited to the additional meta-knowledge learned through the MAML-based method. Implemented as a Siamese network, OSL had to learn the strong periodic components within the time series. However, the selected datasets did not display such strong periodicity;instead, they were dominated by trend and noise components. Future work intends to analyze the asymptotic performance of increasingly complex predictors in tandem with increasingly longer training regimes.

关键词： Zero-shot learning

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Intelligent Rising Sprawl Tuned Autonomous Robot 27th

Intelligent Rising Sprawl Tuned Autonomous Robot

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27th International Conference on Climbing and Walking Robots and Mobile Machine Support Technologies (CLAWAR)

作者： Siboni, Tomer Coronel, Matan Berman, Sigal Zarrouk, David Ben Gurion Univ Negev Dept Mech Engn Beer Sheva Israel Ben Gurion Univ Negev Dept Ind Engn Beer Sheva Israel

ISBN: (纸本)9783031713002;9783031713019

Miniature crawling or driving robots have been developed in recent years for off-road tasks such as search and rescue, excavation, and reconnaissance. Their small dimensions, low weight, and high navigability enable their deployment in large numbers to quickly inspect large areas. There are some examples of palm-sized robots that we designed and created that can crawl or drive, including instances from a particular family of Sprawl-Tuned Autonomous Robots (STAR), i.e., STAR [1] and Rising-STAR [2]. These robots can actively adjust their sprawl angle to change the geometry between wheels and "whegs" in different planes. Using their unique configuration, these robots can move on varying terrain surfaces and traverse obstacles. The Rising-STAR has been simulated and examined with different types of machine learning algorithms [3, 4], to improve its abilities in different aspects.

关键词： Reconfigurable robot Bio-Inspiration Reinforcement learning

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AMEACrypt: Android Mobile Encryption Application Generating Password Using AES Algorithm 9th

AMEACrypt: Android Mobile Encryption Application Generating ...

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9th International Congress on Information and Communication Technology (ICICT)

作者： Borromeo, Jerry E. Pagaduan, Roxanne A. Avestro, Junnel E. Pinca, Ryan Christopher B. Garcia, Jess N. Gremio, Zyrus D. Technol Inst Philippines Quezon City Metro Manila Philippines

ISBN: (纸本)9789819732883;9789819732890

Smartphones have quickly integrated into our daily lives with their numerous applications. Their worth is evident for everything from downloading files to watching online films and reading electronic books. Many people look for software that helps protect their important files, even though others may think downloading files to mobile devices is safe. The mobile application AMEACrypt offers a complete solution, including modules such as password generator, password vulnerability checker, ciphertext encryption and decryption, and file encryption and decryption functions. These elements are crucial for ensuring personal security through stronger passwords or data encryption with a unique decryption key known only to the user. AMEACrypt application includes a password generator, checker, and vulnerability checker for passwords. The Agile Methodology was used due to its effectiveness in delivering a desirable level of development. Feedback and teamwork were used throughout the phases to achieve an acceptable level. Using ISO/ IEC 9126, IT experts, students, and others assessed the application's usability, functionality, dependability, efficiency, maintainability, and portability. According to the end-user evaluation results, the mobile application received a total rating of 5.65 and a strongly agree rating for its interpretation. The result indicates that the mobile application helps users generate passwords, check passwords, encrypt and decrypt ciphertext, and encrypt and decrypt files.

关键词： Mobile application Mobile security Encryption Decryption AES AES-128 Ciphertext Password generation

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Player Performance Analysis 8th

Player Performance Analysis

引用

8th Smart Trends in Computing and Communications (SmartCom)

作者： Nayak, Adithya Darshan Aditya, A. S. Veliyath, Alan Joji Abraham, Ashish Binoy Bharathi, R. Sandesh, B. J. PES Univ Bengaluru 560100 Karnataka India

ISBN: (纸本)9789819713288;9789819713295

Cricket, a game with a rich history, has evolved with various formats and competitions. The objective of this paper is to provide comprehensive insights into player strengths and weaknesses to assist teams by analyzing the player's performance using multiple linear regression on the dataset, which includes batting, bowling, and fielding. As an optimizing strategy for the players, a Player Impact metric is developed using Genetic Algorithm to create a holistic and effective player performance metric. The data includes batting, bowling, and fielding statistics that assist in making strategic decisions. The metric was found to provide accurate assessments of player contributions to their teams, thereby aiding cricket analysis.

关键词： Performance analysis Multiple linear regression Player Impact

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Decision Support System Based on Machine Learning Techniques to Diagnosis Heart Disease Using Four-Lead ECG Recordings 1

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11st World Conference on Information systems and Technologies (WorldCIST)

作者： Hosni, Mohamed Medarhri, Ibtissam Touiti, Soufiane Tazi, Amal Mezalek Ngote, Nabil Moulay Ismail Univ Meknes M253 Lab MOSI Team ENSAM Meknes Morocco MINES Rabat LMAID Lab MMCS Team Rabat Morocco Abulcasis Int Univ Hlth Sci Rabat Morocco Cheikh Zaid Int Univ Hosp Rabat Morocco

ISBN: (数字)9783031456459

ISBN: (纸本)9783031456442;9783031456459

Cardiovascular disease is one of the leading causes of death in the world. Accurately and rapidly diagnosis of this disease remains an important challenge in research. Different decision support systems (DSS) implementing Machine Learning (ML) techniques have been proposed in the literature. In this study, we attempt to build a DSS that implements ML and try to classify patients according to their clinical characteristics and four-lead Electrocardiogram (ECG) recorded by mean of a smart watch. The principal goal of this study is to check whether the proposed DSS can play the same role as a standard ECG. Indeed, the obtained results suggest that this DSS can accurately screen and diagnose heart conditions and may be used as an alternative to a standard ECG. Moreover, among the four optimized ML techniques by grid search optimization technique, the Support Vector Machines achieved the highest accuracy score.

关键词： ECG Machine Learning Cardiovascular Disease Smart Watch Withings ScanWatch

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Fast Tunnel Traversal for Ground Vehicles by Bearing Estimation with Neural networks 6th

Fast Tunnel Traversal for Ground Vehicles by Bearing Estimat...

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6th Iberian Robotics Conference (Robot)

作者： Cano, Lorenzo Tardioli, Danilo Mosteo, Alejandro R. Univ Zaragoza Zaragoza Spain Inst Invest Ingn Aragon Zaragoza Spain Ctr Univ Def Zaragoza Spain

ISBN: (纸本)9783031586750;9783031586767

Underground environments are challenging scenarios for autonomous robotics, as they have a set of properties that make most common self-localization and navigation methods struggle. We propose a system to allow wheeled autonomous vehicles to traverse tunnels at high speeds. Our proposal is built around a Convolutional Neural Network (CNN) trained to predict the bearing that centers the robot into the tunnel as it traverses it. This exploits the generalization capabilities of CNNs, so that the method works in environments outside of the training data, achieving speeds of up to 10m/s.

关键词： Navigation Underground Robotics Deep Learning

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A Machine Learning Framework for Improving Resources, Process, and Energy Efficiency Towards a Sustainable Steel Industry 21st

A Machine Learning Framework for Improving Resources, Proces...

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21st International Conference on Smart Technologies and Education (STE) on Smart Technologies for a Sustainable Future

作者： Fernandez Martinez, Andrea Muinos-Landin, Santiago Gordini, Angelo Ferrari, Luca Chini, Matteo Bianco, Loris Blaga, Mircea AIMEN Technol Ctr Pontevedra Spain OPTIT Srl Bologna Italy Ferriere Nord SpA Osoppo Italy Tenaris Silcotub SA Calarasi Romania

ISBN: (纸本)9783031619045;9783031619052

In response to geopolitical instability, supply chain issues, and environmental concerns, initiatives like the European Green Deal highlight the need for a green transition in the EU industry. The steel sector, as an Energy-Intensive Industry, is crucial in this shift. This work introduces a Machine Learning framework for sustainability in the Steel Industry, addressing Resource, Process, and Energy efficiency with three ML algorithms. The framework, integrated into a Decision Support System, assists plant operators in the transition to a more sustainable process.

关键词： Machine Learning Sustainability Steel Industry Energy Efficiency Process Optimization

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