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检索条件"丛书名=Communications in Computer and Information Science"

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Assessing Comfort During Human-Robot Collaboration Using Virtual Reality Scenarios 8th

Assessing Comfort During Human-Robot Collaboration Using Vir...

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8th International Conference on computer-Human Interaction Research and Applications-CHIRA-Annual

作者： Notaro, Gina M. Mustari, Ryan Haghighat, Arya K. Gao, Dalong Molazadeh, Vahidreza Saez, Miguel HRL Labs LLC Calabasas CA 91301 USA Gen Motors GM R&D Global Tech Ctr Warren MI 48092 USA

ISBN: (纸本)9783031838446;9783031838453

Maintaining comfort during human-robot collaboration is critical for the efficient use of, and engagement with, emerging robotic technologies. In this paper, we describe our efforts towards designing and implementing a study to investigate the impact of robotic behaviors on human teammate comfort within manufacturing scenarios. We first developed immersive virtual reality (VR) human-robot collaboration scenarios in which we manipulated virtual robotic arm behavior parameters. These experimental manipulations included robot arm movement speed, human-robot proximity, and inconsistency of speed or proximity (i.e., predictability). We found that the lowest overall comfort ratings were reported for the very close proximity and very fast speed robot arm manipulations, particularly for the unpredictable conditions. At the end of the experiment, most participants noted that the very close proximity scenarios made them more uncomfortable than the fast speed conditions, suggesting the virtual robotic arm was considered as social entity with respect to proxemics. These findings and approach combined can help elucidate human perceptions of robotic behaviors for extension to real-world collaboration scenarios, with applications in manufacturing and beyond.

关键词： Human-robot collaboration Virtual reality Manufacturing technologies

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Automated Precision in Food Packaging: A Cost-Effective Solution for Emerging Companies 4th

Automated Precision in Food Packaging: A Cost-Effective Solu...

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4th International Conference on Advanced Research in Technologies information Innovation and Sustainability-ARTIIS-Annual

作者： Diego Terneus, Juan Moya, Viviana Abedrabbo, Faruk Pablo Vasconez, Juan Moya, Marcelo Univ Int Ecuador UIDE Fac Ciencias Tecn Quito 170411 Ecuador Univ Andres Bello Energy Transformat Ctr Fac Engn Santiago 7500971 Chile

ISBN: (纸本)9783031832093;9783031832109

This study aims to automate the packaging process efficiently and enhance production in emerging companies. A prototype that integrates mechanical, electronic, and control design was developed to achieve mass-controlled filling with precise measurements and efficient batch processing. The system features a screw conveyor mechanism and a rotary drum mechanism, employing a cascade control strategy with a Proportional-Integral (PI) controller to accurately regulate motor speed. Extensive testing of the filling machine demonstrated its capability to fill 100 g containers with an error margin of +/- 5 g and an average filling time of 1.08 min per container. These results highlighted the system's exceptional accuracy and efficiency. A cost analysis of implementing this machine in the Ecuadorian Tervide Company was also provided. The proposed methodology shows significant potential to enhance efficiency and accuracy in filling food products for emerging companies, establishing a precedent for sustainable production improvements globally.

关键词： Food Industry Mass-Controlled Filling Automated Packaging Trout Pate

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Bias Reduction in Social Networks Through Agent-Based Simulations 5th

Bias Reduction in Social Networks Through Agent-Based Simula...

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5th International Workshop on Algorithmic Bias in Search and Recommendation

作者： Bartley, Nathan Burghardt, Keith Lerman, Kristina Inst Informat Sci Marina Del Rey CA 90292 USA

ISBN: (纸本)9783031719745;9783031719752

Online social networks use recommender systems to suggest relevant information to their users in the form of personalized timelines. Studying how these systems expose people to information at scale is difficult to do as one cannot assume each user is subject to the same timeline condition and building appropriate evaluation infrastructure is costly. We show that a simple agent-based model where users have fixed preferences affords us the ability to compare different recommender systems (and thus different personalized timelines) in their ability to skew users' perception of their network. Importantly, we show that a simple greedy algorithm that constructs a feed based on network properties reduces such perception biases comparable to a random feed. This underscores the influence network structure has in determining the effectiveness of recommender systems in the social network context and offers a tool for mitigating perception biases through algorithmic feed construction.

关键词： Social Networks Agent-based Models Recommendations

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Enhancing Rural Electrification: Delivering Affordable and Clean Electricity Through Mobile Battery Solutions 5th

Enhancing Rural Electrification: Delivering Affordable and C...

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5th International Conference on Neural Computing for Advanced Applications (NCAA)

作者： Yu, Gang Ye, Xianming Univ Pretoria Dept Elect Elect & Comp Engn ZA-0002 Pretoria South Africa

ISBN: (纸本)9789819770038;9789819770045

This study proposes a mobile battery architecture for rural electrification. Distinguishing itself from traditional grid extensions and off-grid microgrid options, the proposed mobile battery architecture offers advantages in terms of cost-effectiveness, scalability, and rapid deployment. To model the operational process of the proposed mobile battery architecture, a simulation approach is proposed. To improve the affordability of mobile batteries in rural households, the optimal configuration of the mobile battery architecture is studied to minimize the levelized cost of electricity (LCoE). This is achieved by combining the proposed simulation approach with particle swarm optimization. The proposed architecture promises to advance and accelerate rural electrification initiatives.

关键词： Rural electrification mobile battery renewable energy particle swarm optimization

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Wearable Device for Acquiring Biomechanical Variables Applied to the Analysis of Occupational Health Risks in Industrial Environments 12th

Wearable Device for Acquiring Biomechanical Variables Applie...

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12th Ecuadorian Conference on information and Communication Technologies

作者： Calderon-Cordova, Carlos Puchaicela, Victor Sarango, Roger Univ Tecn Particular Loja Loja 1101608 Ecuador

ISBN: (纸本)9783031754302;9783031754319

The activities performed in an industrial environment are classified as high risk for causing occupational diseases because the activities performed demand high frequencies of execution of movements or require high physical efforts on the part of industrial operators. Currently, risk indexes are assessed only based on observation and questionnaires, which adds subjectivity and lack of reliability to the results. The present study proposes the development and evaluation of a wearable technological device to acquire in situ the biomechanical variables of an operator and that these data serve to determine occupational risk indexes in a more objective way. The hardware architecture of the wearable device implemented consists of four modules: signal acquisition, processing, storage, and data transmission. The eleven (11) monitored variables are six myoelectric signals in the forearm, biceps, and back, two back inclination angles, heart rate, skin electrical conductance signal, and body temperature. To evaluate the performance of the implemented device, the eleven monitored variables were acquired, registered, and visualized during the execution of three test exercises by three users of different physiological parameters, resulting in a set of 99 signals. It was observed congruence between the occurrence of peaks of the signals with the characteristics of the executed exercises, in addition, there is no loss of data between the stages of capture, transmission, recording, and visualization.

关键词： Wearables biomechanical signals occupational health Internet of Medical Things (IoMT) embedded systems

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Enhancing Credit Risk Assessment Through Transformer-Based Machine Learning Models 5th

Enhancing Credit Risk Assessment Through Transformer-Based M...

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5th Southern African Conference for Artificial Intelligence Research

作者： Siphuma, Elekanyani van Zyl, Terence Univ Johannesburg Inst Intelligent Syst Johannesburg South Africa

ISBN: (纸本)9783031782541;9783031782558

This study evaluates the effectiveness of transformer-based deep learning models in improving credit risk assessment for predicting default probabilities among credit card customers. By employing the CNN-SFTransformer and GRU-Transformer models, this research aims to enhance predictive accuracy and robustness compared to traditional machine learning methods. The models were trained and tested on diverse datasets from Taiwan, Germany, and Australia, representing various credit risk scenarios. The experimental setup included rigorous hyperparameter tuning and utilized key evaluation metrics such as ROC AUC, KS statistic, and G-(mu) over tilde to assess model performance comprehensively. The CNN-SFTransformer model demonstrated superior performance, consistently surpassing baseline models like LSTM, Support Vector Machines (SVM), and Random Forest across all datasets. This performance indicates its enhanced capability in differentiating between defaulters and non-defaulters. The GRU-Transformer model also showed promising results, further validating the effectiveness of transformer architectures in this domain. Statistical significance of the results was confirmed through the McNemar test, ensuring the robustness and reliability of the proposed models. This research introduces a novel approach to credit risk management by providing scalable and adaptable models that improve the precision of default predictions, thereby aiding financial institutions in making more informed lending decisions with greater confidence.

关键词： Credit Scoring CNN-SFTransformer GRU-Transformer

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A Parameter-Free Normal Estimator on Digital Surfaces 4th

A Parameter-Free Normal Estimator on Digital Surfaces

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4th International Conference on Intelligent Systems and Pattern Recognition-ISPR

作者： Mareche, Aude Debled-Rennesson, Isabelle Feschet, Fabien Phuc Ngo Univ Lorraine CNRS LORIA F-54000 Nancy France Univ Clermont Auvergne CNRS ENSMSE LIMOS F-63000 Clermont Ferrand France

ISBN: (纸本)9783031821493;9783031821509

The processing of 3D digital objects often requires the computation and analysis of their geometrical features. The normal vectors of the object's surface in particular provide important information used in image processing applications. We present in this paper a new method for the estimation of normal vectors on the surface of a 3D digital object. It is both local and parameter-free. The proposed method involves the study of neighborhoods around points using planar sectors. Experimental evaluations using multigrid approaches show that it is both faster and more robust than state-of-the-art methods in the field, while being of comparable accuracy.

关键词： Digital Geometry Digital plane Local surface analysis Normal estimation

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Innovation Processes in Universities: A Conceptual Model Incorporating Digital Transformation and Technological Innovations 4th

Innovation Processes in Universities: A Conceptual Model Inc...

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4th International Conference on Advanced Research in Technologies information Innovation and Sustainability-ARTIIS-Annual

作者： Yordanova, Zornitsa Univ Natl & World Econ Sofia Bulgaria

ISBN: (纸本)9783031840777;9783031840784

This article proposes a conceptual framework for integrating digital transformation and broader technological innovations to optimize innovation processes within universities. By leveraging AI, blockchain, IoT, VR, and other digital tools, the framework aims to enhance creativity, efficiency, and collaboration in innovation management. The study outlines the theoretical foundations, framework development, and potential implications for academia and industry. Transforming the current status quo of innovation processes is crucial, as universities risk being left behind if they do not embrace digital transformation. The proposed framework highlights the critical role of advanced technologies in driving efficiency and fostering continuous improvement and innovation. Moreover, this research emphasizes the urgent need for universities to adapt to the rapidly evolving technological landscape to remain competitive and relevant. The integration of digital technologies into innovation processes not only addresses existing challenges but also opens new avenues for academic and industrial growth. Future research should explore practical applications of this framework to address challenges and opportunities in implementation. The contribution of this research lies in its unique integration of diverse digital technologies into a cohesive model, providing a comprehensive roadmap for universities to enhance their innovation capabilities. This comprehensive approach underscores the importance of a holistic digital transformation strategy to ensure sustained innovation and competitive advantage.

关键词： Innovation Process Digitalization Technology Management Digital Transformation University Innovation AI for innovation

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A Multi-scale Feature Adaptation ConvNeXt for Cross-Domain Fault Diagnosis 5th

A Multi-scale Feature Adaptation ConvNeXt for Cross-Domain F...

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5th International Conference on Neural Computing for Advanced Applications (NCAA)

作者： Huang, Zhe Lan, Qing Li, Mingxuan Wen, Zhihui He, Wangpeng Wuhan Second Ship Design & Res Inst Wuhan 430025 Peoples R China Xidian Univ Xian 710071 Peoples R China

ISBN: (纸本)9789819770069;9789819770076

Real-time monitoring of the operational status of mechanical equipment is crucial in industrial production. The scarcity of fault data, the predominance of unlabeled monitoring data, and the complex and variable operational conditions have gradually become prominent, which limit the accuracy of diagnostic models and affect their effectiveness in new operational conditions. To address these issues, a domain adaptation fault diagnosis method based on a multi-scale feature adaptive ConvNeXt is proposed in this paper. By integrating multi-scale feature fusion, multi-spectral attention mechanisms, and feature adaptive selection modules, the method enhances the ConvNeXt network's capability to capture fault characteristics. It combines conditional domain adversarial techniques to align the cross-domain feature marginal and conditional distributions. Comparative experiments conducted on two bearing datasets demonstrate the effectiveness of the proposed method in addressing the challenge of sparse labeling under target operating conditions, enabling accurate assessments of the health status of mechanical equipment in target conditions.

关键词： Fault Diagnosis Domain Adaptation Multi-scale Feature Adaptive ConvNeXt

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Unveiling the "Vulnerability Cycle" of Migrant Workers in Mauritius: Applying a Grounded Theory Approach to Health and Wellbeing of Migrant Workers 4th

Unveiling the "Vulnerability Cycle" of Migrant Workers in Ma...

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4th International Conference on Society 5.0

作者： Bhundhoo, Sanjayduth Coolen, Preeya Vijayalakshmee Fraser, Roslyn S. Univ Technol Mauritius Dept Environm Sci & Social Sustainabil Port Louis Mauritius Stephen F Austin State Univ Nacogdoches TX USA

ISBN: (纸本)9783031714115;9783031714122

The welfare of migrant workers in Mauritius in terms of their health and wellbeing is the main topic of this research. The aim of this study is to understand the health and wellbeing of migrant workers from a social work perspective through the application of the grounded theory. A qualitative approach was used to gather the data. Semi-structured interviews were carried out with twenty-two migrant workers from Bangladesh, Madagascar, Nepal, South Africa and India who have been employed and reside in Mauritius for more than one year. The respondents are employed in a variety of industries, including vegetable plantations, supermarkets, hotels, building sites, ICT & BPO, Communication and textile factories. This study adds to the body of knowledge on migrant workers' well-being by utilizing the Grounded Theory in Mauritius. The main findings of this research emanate from the application of the Grounded Theory and through the application of the Theoretical Coding which is a qualitative research approach. The findings were presented in terms of initial coding then identifying relationship between the different codes that have been generated and finally developing a re-fined theoretical concept as follows: "The Vulnerability Cycle of Migrant workers": This refined code was generated from the findings of this research by application of the Grounded Theory. It comprises of the different elements such as precarious employment, substandard living conditions, and inadequate healthcare that affect negatively the health and wellbeing of migrant workers working in Mauritius.

关键词： Grounded Theory Migrant Workers Social Work Vulnerability Cycle Wellbeing

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