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Integration of Facial Recognition and Facemask Detection for Enhanced Access Control systems: A Post-epidemic Solution 1

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

作者： Simwinga, Azwel Phiri, Jackson Univ Zambia UNZA Lusaka Zambia

ISBN: (数字)9789819733057

ISBN: (纸本)9789819733040;9789819733057

This project aimed to enhance existing facemask identification technology by incorporating forward-compatible features, particularly focusing on facial recognition. Utilizing TensorFlow Lite, a model was developed and trained on 5092 photos, integrated into a Python program on a Raspberry Pi 4. The system authenticates users using the National Registration Card Number (NRC) and employs facial recognition before transitioning to the facemask detection module. Access is granted only to those complying with facemask rules. The API linkage enables real-time monitoring, reporting, and user access configuration. The system addresses contact tracing, records instances of mask removal, and is adaptable beyond pandemic contexts. With applications in various settings, it enhances security and access control, making it valuable for post-pandemic access control systems.

关键词： Artificial intelligence Object detection Facial recognition Facemask detection Contact tracing

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Industry 4.0 Approaches to the Standardization of Spur Bevel Gears 10th

Industry 4.0 Approaches to the Standardization of Spur Bevel...

引用

International Conference on New Technologies, Development and Application - Advanced Production Processes and Intelligent systems

作者： Ivanov, Viktor Dimitrov, Lubomir Ivanova, Svitlana Urum, Galyna Odessa Natl Polytech Univ Odesa Ukraine Tech Univ Sofia Sofia Bulgaria South Ukrainian Natl Pedag Univ Odesa Ukraine

ISBN: (纸本)9783031662676;9783031662683

Manufacturing technologies and measuring methods of transmissions have undergone great changes, which are usually combined into the concept of Industry 4.0. At the same time, the accuracy standards of bevel gears have remained unchanged for the past ten years. When assembling bevel gearboxes, ANSI/AGMA and ISO standards recommend visual inspection of the contact pattern in the *** additional operation of searching for a satisfactory contact pattern by trial and error method by the operator is also provided. An attempt has been made to regulate installation errors of spur bevel gears, in addition to existing standards, in order to create prerequisites for excluding humans from the assembly process of bevel gears. Mathematical expectation of the load distribution factor was chosen as a criterion for the assembly quality of bevel gears. The probabilistic nature of installation errors was taken into account using the Monte Carlo method. The value of load distribution factor was found depending on the tolerance range for axial displacements and offset error.

关键词： Industry 4.0 probabilistic installation errors spur bevel gears Monte Carlo method tolerances allocation

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Analysis of the Computational Complexity of Backpropagation and Neuroevolution 1

引用

Computing Conference

作者： Weeks, Michael Georgia State Univ Atlanta GA 30303 USA

ISBN: (数字)9783031622816

ISBN: (纸本)9783031622830;9783031622816;9783031622809

This work examines the computational complexity of two algorithms to perform machine learning. The first algorithm is the wellknown backpropagation, based on stochastic gradient descent, where a network of neurons alter their weights based on an error signal passed back from the output. The second algorithm, called neuroevolution, is based on the genetic algorithm. In it, many weight sets are ranked based on how well the network solves the problem, and the best of them combine together to form new weight sets, in a process inspired by biological evolution. We find that the forward computations are the same. Analyzing the number of operations for both weight adjustment algorithms, we find that backpropagation requires more operations to create a new weight set, but that neuroevolution requires many iterations.

关键词： Neural networks Backpropagation Neuroevolution

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Application of New Technologies in Social Media Analytics: Enhancing User Engagement at Global Universities 10th

Application of New Technologies in Social Media Analytics: E...

引用

International Conference on New Technologies, Development and Application - Advanced Production Processes and Intelligent systems

作者： Poturak, Mersid Obucic, Engin Keco, Dino Mekic, Ensar Int Burch Univ Fac Econ & Social Sci Dept Management Francuske Revolucije Bb Sarajevo 71000 Bosnia & Herceg Int Burch Univ Fac Engn Nat & Med Sci Dept Informat Technol Sarajevo 71000 Bosnia & Herceg

ISBN: (纸本)9783031662706;9783031662713

Objective: Based on newtechnologies in Social Media Predictive Analytics Theory in the Higher Education Institutions (HEIs) context, this study aims to predict user engagement in Facebook post images across leading universities in Australia, the United Kingdom, and the United States. Methodlolgy: By employing the Google Cloud Vision API and image features sourced from graphic design and photography literature, a novel methodological combination of image features was developed and employed. Findings: This research contributes to understanding image related user engagement dynamics on Facebook, and it provides pragmatic guidance for global universities to optimise their social media strategies.

关键词： Universities Facebook image features user engagement predictive analytics cross-country analysis social media strategies multiple regression

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Perceived Risk and Behavioral Intention of Customers Using Bayesian Technique 1

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13th Computer Science Online Conference

作者： Dam Tri Cuong Ind Univ Ho Chi Minh City Ho Chi Minh City Vietnam

ISBN: (数字)9783031705182

ISBN: (纸本)9783031705175;9783031705182

In recent decades, the Internet has seen significant development, transforming into an expansive worldwide marketplace facilitating the exchange of various commodities and services. Nevertheless, an increasing number of individuals engaging in online transactions has resulted in a multitude of concerns and challenges. Online customers face a wider range of risks in comparison to those who participate in traditional shop purchasing experiences. The problem of customer perceptions of risk in the context of internet purchasing has emerged as a significant current concern. Thus, the current research used the Bayesian linear regression methodology to investigate the influence of perceived risk on consumers' behavioral intention within the realm of online purchasing. The findings of the research indicate the existence of four distinct categories of perceived risk, namely product risk, financial risk, convenience risk, and non-delivery risk. These risks are evaluated negatively by customers and have a significant impact on their behavioral intention while participating in online purchase activities.

关键词： Perceived Risk Behavioral Intention Bayesian Technique

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Methods of Reduction of Fuel Consumption Measurement Error by Thermo-Anemometric Flow Meter 28th

Methods of Reduction of Fuel Consumption Measurement Error b...

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2024 International Conference Automation

作者： Ilchenko, Andrii Korobiichuk, Igor Polissya Natl Univ Agr Engn & Tech Serv Dept Zhytomyr Ukraine Lukasiewicz Res Network Ind Res Inst Automat & Me Warsaw Poland

ISBN: (纸本)9783031782657;9783031782664

It was analyzed the ways of influence on the indexes of radial heat flow in thermo-anemometric flow meter that will influence the indexes of axial heat flow, will make them more informative and this, in its turn, will affect the consumption measurement error. It was formulated the condition of selecting the temperatures distribution with the minimal measurement error for multi-sectional flow meter, it can be obtained by the indexes of thermal transformers of the very pipe of multi-sectional thermo-anemometric flow meter, where the maximal total temperatures difference between all the neighboring thermal transformers was measured. Expanding the range of fuel consumption measurement by the thermo-anemometric flow meter was suggested due to the application of sequentially axially installed sections with different diameters.

关键词： measurement error internal combustion engine fuel consumption thermo-anemometric flow meter temperature distribution hot wire

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Sign Language Interpreter Using Stacked LSTM-GRU

Sign Language Interpreter Using Stacked LSTM-GRU

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International Conference on Artificial Intelligence: Theory and Applications (AITA)

作者： Fathima, M. Dhilsath Hariharan, R. Shome, Sachi Kharsyiemlieh, Manbha Deepa, J. Jayanthi, K. SRM Inst Sci & Technol Sch Comp Dept Computat Intelligence Kattankulathur Tamil Nadu India Natl Inst Technol Trichy India Veltech Rangarajan Dr Sagunthala R&D Inst Sci & T Dept Informat Technol Chennai Tamil Nadu India SRM Inst Sci & Technol Dept Comp Sci & Engn Tiruchirappalli Tamil Nadu India

ISBN: (纸本)9789819984787;9789819984794

Sign language has been used to communicate with people who are hard of hearing in conveying their thoughts and ideas to ordinary people. People may readily express thoughts using this sort of gesture-based language, which reduces barriers caused by hearing problems. The major issue is that the vast majority of the population lacks the knowledge of using sign language. Sign language detection from live video footage is a challenging problem that can bridge the communication gap. This paper proposes a method for identifying sign language motions in real-time video data that combines computer vision and deep learning approaches. The major contribution of the proposed model is stacking the long short-term memory (LSTM) and gated recurrent unit (GRU) architecture called LSTM-GRU to detect and classify signs from sign language videos. Our built model is run on a real-time video stream using the camera input, and by stacking the LSTM and GRU, we optimize model performance and reach 94.4% prediction accuracy.

关键词： Long short-term memory Gated recurrent unit Sign language Mediapipe OpenCV

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Balancing Plug-In for Stream-Based Classification 1

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

作者： de Arriba-Perez, Francisco Garcia-Mendez, Silvia Leal, Fatima Malheiro, Benedita Burguillo-Rial, Juan Carlos Univ Vigo atlanTTic Informat Technol Grp Vigo Spain Univ Portucalense REMIT Porto Portugal INESC TEC Porto Portugal Polytech Inst Porto ISEP Porto Portugal

ISBN: (数字)9783031456428

ISBN: (纸本)9783031456411;9783031456428

The latest technological advances drive the emergence of countless real-time data streams fed by users, sensors, and devices. These data sources can be mined with the help of predictive and classification techniques to support decision-making in fields like e-commerce, industry or health. In particular, stream-based classification is widely used to categorise incoming samples on the fly. However, the distribution of samples per class is often imbalanced, affecting the performance and fairness of machine learning models. To overcome this drawback, this paper proposes Bplug, a balancing plug-in for stream-based classification, to minimise the bias introduced by data imbalance. First, the plugin determines the class imbalance degree and then synthesises data statistically through non-parametric kernel density estimation. The experiments, performed with real data from Wikivoyage and Metro of Porto, show that Bplug maintains inter-feature correlation and improves classification accuracy. Moreover, it works both online and offline.

关键词： Data bias fairness imbalanced data sets machine learning algorithm stream classification

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Big Data Analytics in the Supply Chain: A Bibliometric Review of Scholarly Research from 2012 to 2023 12th

Big Data Analytics in the Supply Chain: A Bibliometric Revie...

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12th World Conference on Information systems and Technologies (WorldCIST)

作者： Fosso-Wamba, Samuel Guthrie, Cameron de Queiroz, Maciel Manoel TBS Business Sch Toulouse France FGV EAESP Sao Paulo Brazil

ISBN: (纸本)9783031602146;9783031602153

The professional and scholarly interest in big data analytics in the supply chain has rapidly grown over the past decade. This article presents a bibliometric analysis of academic literature to improve our understanding of the evolution and current state of the field. The analysis covers 920 published journal and conference papers identified using the Web of Science database. A descriptive analysis of the corpus first allows us to identify the most influential works, ideas, and authors in the field, leading to the identification of opportunities for future research.

关键词： Big data analytics supply chain bibliometric review

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Evolution of Fintech Companies in Guatemala from Prepandemic to Post Pandemic Period and the Options of Fintech Companies as Financial Provider for Projects 11th

Evolution of Fintech Companies in Guatemala from Prepandemic...

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

作者： Martinez-Mendez, Stephen David Navarro, Fauricio Alban Conejo Jadan-Guerrero, Janio Univ Galileo Gest & Direcc Proyectos Ciudad De Guatemala Guatemala Univ Latina Costa Rica San Jose Costa Rica Univ Tecnol Indoamer Ctr Invest Mectron & Sistemas Interact MIST Quito Ecuador

ISBN: (纸本)9783031456473;9783031456480

On the Pre-pandemic time most of the projects were traditional financial banking methods, that means the biggest companies had have receive 85%, leaving only the 15% for the Small and medium-sized enterprises (SMEs), in the pandemic period financial risk increased and trying to figure out how to survive the biggest companies update them technology for e-commers but SMEs did not have enough money to do it, for that reason they found a solution on fintech technologies. As a result, in the post pandemic era, fintech companies began to have a huge relevance not only as a technology supplier but also as financial provider. The main reason of this research is to find out if Fintech companies could be provider for projects to big companies and SMEs, the outcome shows that project managers of different industries see e-money as a secure payment method and with the fintech establishment on the economic scene they begin to feal more comfortable with the idea of using fintech companies as financial provider for projects in them companies. This research was carried out under the descriptive method, The tool selected to collect information was Google Forms, in this tool a multiple-choice survey was created, and email was sent with access to the survey. The results allow us to understand that they can be a permanent and reliable source to finance projects of different types of industries.

关键词： Prepandemic Pandemic Post pandemic Fintech Projects Financial

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