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2022 International Conference on science and technology, ICOSTECH 2022

作者： Manurian, Wahyu Padeli Supriati, Ruli Cahyadi, Dede Cesna, Galih Putra University of Raharja Master of Informatics Management Tangerang Indonesia University of Raharja Master of Computer Science Tangerang Indonesia University of Raharja Master of Technology Information Tangerang Indonesia University of Raharja Department of Informatics Engineering Tangerang Indonesia

ISBN: (纸本)9781665479851

Concentrated solar energy technology plays an essential role in today's energy turnarounds. Face our society. The energy generated by this technology is highly dependent on the optical behavior of the reflector material of the solar cell. Corrosion of solar reflectors can be a problem in areas with high corrosion levels Severe environments, such as excessive corrosion of solar mirrors can have a devastating impact on the feasibility of centralized solar thermal systems. This study focuses on modeling the shelf life of four different things. Sunlight reflective material exposed outdoors by accelerated deterioration test. For this purpose, ten suitable locations to concentrate solar thermal applications were classified according to their corrosive aggression. Commercially available free leed and low-cost reflector samples were exposed everywhere to determine the effect of corrosion on durability. Corrosion defects on the solar reflector during outdoor exposure Reproduced correctly in the CASS test. A new life prediction model has been developed for all solar reflectors Depending on the corrosive aggression of the place. Number and thickness of paint layers used in Solar mirrors are recognized as essential parameters for improving energy production. Identified CSP system in a corrosive environment. Expected to reduce capital investment in purchasing solar mirrors For places with low corrosiveness. © 2022 IEEE.

关键词： Durability

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Enhancing Smart Mobility Through Machine Learning and Neural Networks

Enhancing Smart Mobility Through Machine Learning and Neural...

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Wireless and Optical Technologies (GCWOT), 2020 Global Conference on

作者： Muhammad Nadeem Waleej Haider Haris Ahmed Sallar Khan Department of Computer Science & Information Technology Sir Syed University of Engineering & Technology Karachi Pakistan School of Informatics & Cybersecurity Technological University Dublin Dublin Ireland

ISBN: (数字)9798331534271

ISBN: (纸本)9798331534288

This study investigates the prediction of taxi trip durations in New York City using machine learning (ML) models and neural networks (NN). Three models Linear Regression, Random Forest Regressor, and a Neural Network were developed and evaluated on a dataset containing various trip details. The analysis highlighted the importance of geographic and temporal features in predicting trip durations. The Neural Network model outperformed others, achieving a mean squared error (MSE) of 12,577,211 and a root mean squared error (RMSE) of 3,546, significantly better than the comparative models. These results underscore its capacity to capture complex urban mobility patterns effectively. The superior performance of the Neural Network supports its potential to optimize traffic flow and reduce congestion in dense urban environments, offering substantial improvements to urban transportation systems.

关键词： Wireless communication Soft sensors Neural networks Linear regression Urban planning Predictive models Data models Socioeconomics Random forests Public transportation

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OPTIMIZATION METHOD OF THE INDUSTRIAL VALUE CHAIN CONFIGURATION HEADQUARTER-CENTERED GROUP-TYPE MANUFACTURING ENTERPRISES CONSIDERING SYNERGY RELATIONSHIPS 51

OPTIMIZATION METHOD OF THE INDUSTRIAL VALUE CHAIN CONFIGURAT...

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51st International Conference on Computers and Industrial engineering, CIE 2024

作者： Qiu, Xiao-Hui Qu, Ting Huang, Hai-Nan Ma, Lin Nie, Du-Xian Guangdong International Cooperation Base of Science and Technology for GBA Smart Logistics Jinan University Zhuhai519070 China Department of Industrial and Systems Engineering The Hong Kong Polytechnic University 999077 Hong Kong College of Mathematics and Informatics South China Agricultural University Guangzhou510642 China

With the development of Industry 4.0, the distributed manufacturing model has become the mainstream trend. In the new economic environment, the industrial chain as an economic unit pays more attention to macro-level resource coordination and value co-creation. However, current research pays less attention to the multi-dimensional value co-creation and Synergy relationships. Therefore, this paper studies the industrial value chain configuration problem of an assembly product headquarter-centered group-type manufacturing enterprise and proposes a two-stage configuration method. At the same time, it defines multi-dimensional value objectives and synergy relationship coefficients and proposes an industrial value chain optimization configuration method based on the ALC method. © 2024 Computers and Industrial engineering. All rights reserved.

关键词： Smart manufacturing

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Propyl acetate-glycols systems: Thermophysical studies and molecular interactions

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Journal of Molecular Liquids 2025年 418卷

作者： Ghanadzadeh Gilani, A. Moghadam, M. Karimi, K. Benassi, E. Department of Applied Chemistry Faculty of Chemistry University of Guilan Rasht41335-1914 Iran Department of Engineering Science Faculty of Technology and Engineering East of Guilan University of Guilan Rudsar Iran Department of Physics Informatics and Mathematics University of Modena and Reggio Italy

This study presents a comprehensive investigation on the thermophysical characteristics of binary mixtures comprising propyl acetate and three related glycols (1,3-butylene glycol, diethylene glycol, and triethylene glycol), focusing on the intermolecular interactions and mixing behavior. Experimental measurements of permittivity, refractive index, and density were performed over the entire composition range at different temperatures of 293.15–313.15 K and 101 kPa. The obtained data were coherently analyzed using appropriate equations to unravel the system's behavior at a molecular level. The results provide valuable insights into the thermo-physical properties for the studied binary systems. The analysis explores the impact of chemical composition and temperature on intermolecular network and constituent's structure through the different excess quantities. Additionally, a reliable and efficient Add-in tool, StatDiel, implemented in Microsoft Excel, is introduced for the analysis of static dielectric data, facilitating data verification, calculations, fitting processes for the excess data of permittivity, molar volume, Kirkwood correlation factor, Helmholtz free energy, and separating excess dielectric contributions and visualization of results. The findings contribute significantly to the existing literature by providing novel thermophysical data and their interpretation for the studied systems. This study fills a gap in the available literature and offers a deeper understanding of the physicochemical properties of propyl acetate-glycols mixtures, shedding light on molecular interactions and system behavior. © 2024 Elsevier B.V.

关键词： Free energy

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Advancing Color Perception: An IoT-driven Pedagogical System for Visually Impaired Children

Advancing Color Perception: An IoT-driven Pedagogical System...

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Advances in Signal Processing, Power, Communication, and Computing (ASPCC), IEEE International Conference on

作者： Prasandika Balage Nuwan Jayawardene School of Computer Science and Engineering University of Westminster London United Kingdom Department of Computing Informatics Institute of Technology Colombo Sri Lanka

ISBN: (数字)9798350355093

ISBN: (纸本)9798350355109

Visual impairment is characterized by the loss of vision, encompassing both complete blindness and partial vision loss. Studies reveal a notable prevalence of visual impairment among school-aged children. The significance of colors in acquiring and discerning visual information is crucial, aiding children in effectively perceiving and comprehending their surroundings. This study presents an Internet of Things (IoT) system designed for teaching colors to visually impaired children. The system achieved an accuracy rate surpassing 77.8%, and it is operated effectively regardless of surrounding lighting conditions. Given that the target users of the system are visually impaired children, this research was conducted in close alignment with Human-Computer Interaction (HCI) principles.

关键词： Human computer interaction Visualization Accuracy Visual impairment Education Lighting Color Blindness Signal processing Internet of Things

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Robust Millimeter Beamforming via Self-Supervised Hybrid Deep Learning 31

Robust Millimeter Beamforming via Self-Supervised Hybrid Dee...

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31st European Signal Processing Conference, EUSIPCO 2023

作者： Zhu, Fenghao Wang, Bohao Yang, Zhaohui Huang, Chongwen Zhang, Zhaoyang Alexandropoulos, George C. Yuen, Chau Debbah, Mérouane The College of Information Science and Electronic Engineering Zhejiang University Hangzhou310007 China The Department of Informatics and Telecommunications National and Kapodistrian University of Athens Panepistimiopolis Ilissia Athens15784 Greece The School of Electrical and Electronics Engineering Nanyang Technological University Singapore Khalifa University of Science and Technology Abu Dhabi127788 United Arab Emirates

ISBN: (纸本)9789464593600

Beamforming with large-scale antenna arrays has been widely considered in wireless communications research in recent years, playing a significant role in fifth generation (5G) networks, as also expected to happen in their upcoming sixth generation (6G). To improve its performance, various techniques have been leveraged, e.g., optimization schemes and deep learning. Although the late deployment of deep learning approaches has been proven quite attractive in certain scenarios, it has been showcased that when the environment or the dataset changes, the performance of supervised learning gets severely degraded. Therefore, the design of effective neural networks for beamforming, exhibiting strong robustness, is an open research area for intelligent wireless communication systems. In this paper, we propose a robust self-supervised deep neural network for beamforming, which is tested with two different datasets emulating various wireless deployment scenarios. Our simulation results demonstrate that the proposed self-supervised network with hybrid learning performs sufficiently well in both the DeepMIMO and the new WAIR-D datasets, exhibiting strong robustness under various environments. © 2023 European Signal Processing Conference, EUSIPCO. All rights reserved.

关键词： Beamforming

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Innovative Urban Solutions with IoT-Driven Traffic and Pollution Control

Innovative Urban Solutions with IoT-Driven Traffic and Pollu...

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2024 IEEE International Conference on Automation and Computation, AUTOCOM 2024

作者： Yogi, Kottala Sri Sharma, Avinash Dankan Gowda, V. Saxena, Rini Barua, Tarkeshwar Mohiuddin, Khalid Dept of Operations Symbiosis Institute of Business Management Hyderabad Symbiosis International University Pune Telangana Hyderabad India Chandigarh Engineering College Chandigarh Group of Colleges Jhanjeri Department of Computer Science and Engineering Punjab Mohali140307 India Bms Institute of Technology and Management Department of Electronics and Communication Engineering Karnataka Bangalore India King Khalid University College of Business Department of Business Informatics PO Box-3247 Abha61471 Saudi Arabia

ISBN: (纸本)9798350382723

The Internet of Things (IoT) is rethinking the model for building the smart cities, and this paper makes just such a step in that direction. It then examines various ways of cutting urban pollution. Under increasing pressure from rising urbanization, smart cities represent a huge leap forward in regard to efficiency, scalability and livability. The key is IoTtechnology, which collects and analyzes data in real time and allows for more quick-witted and intelligent urban governance. This paper combines literature review, case study analysis and data-driven methods to focus on the opportunities offered by IoT applications for restructuring urban traffic systems and pollution control. This study explains what is missing in modern smart city initiatives, and offers a road map for bringing Internet of things solutions to municipal systems. The results can also serve as some answers to cope with the dilemma and bring more intelligence, cleanness, efficiency in making a city into a smart metropolis. The article ends by highlighting the significance of IoT for future urban development, and ideas for further research into this complex yet rapidly evolving area. © 2024 IEEE.

关键词： Internet of things

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High-Resolution Art Painting Completion using Multi-Region Laplacian Fusion

High-Resolution Art Painting Completion using Multi-Region L...

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International Symposium on Computer, Consumer and Control (IS3C)

作者： Irawati Nurmala Sari Kei Masaoka Jun’Nosuke Takarabe Weiwei Du Department of Information Science Kyoto Institute of Technology Kyoto Japan Department of Informatics Engineering University of Brawijaya Malang Indonesia

Image completion has made impressive advancements based on deep learning approaches. However, even with advanced deep learning such as Generative Adversarial Networks (GAN), the restored area is not always optimal due to small-scale texture synthesis in high resolution and inferring missing information about image content from distant contexts, resulting in distorted lines and unnatural colors, especially in art painting completion with complicated structures and textures. Although several precious art paintings have been well-preserved by curators in museums, some frequent damages such as scratches, torn-out areas, and holes are still visible and require challenging physical repairs. Therefore, for practical refinement, some researchers convert them into high-resolution digital paintings to generate crisp brush strokes, textures, shapes, and tones by assuming similarities with the original physical ones. Based on these observations, we propose proceeding with a high-resolution art painting completion by applying a superior traditional method, named Multi-Region Laplacian Fusion. We attempt to recover irregular missing regions expected as the damages of ordinary paintings that often occur. To address high-resolution inpainting, we integrate two completions using the Laplacian pyramid and patch-based propagation. We then apply Alpha blending among both results to yield the fused reaction completion. Our experiments firmly validate the effectiveness of our proposed method to complete art paintings with random irregular missing regions.

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Accelerating Feedback Control for QoE Fairness in Adaptive Video Streaming Over ICN

Accelerating Feedback Control for QoE Fairness in Adaptive V...

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Consumer Communications and Networking Conference, CCNC IEEE

作者： Rei Nakagawa Satoshi Ohzahata Ryo Yamamoto Department of Electrical Engineering and Computer Science Tokyo University of Agriculture and Technology Tokyo Japan Graduate School of Informatics and Engineering The University of Electro-Communications Tokyo Japan

Today, information centric networking enables adaptive video streaming clients to further improve QoE by applying flexible content-based control. However, an adaptive bitrate algorithm makes a client occupy the bottleneck link at excessively high bitrate, reducing the QoE fairness to other clients sharing the bottleneck link. Then, we propose fairAccel, a method of accelerating bitrate-based feedback control for achieving QoE fairness. fairAccel assigns more bandwidth to clients selecting the lower bitrate while suppressing content requests from clients selecting the highest bitrate on the bottleneck link. In addition, to further improve QoE fairness, fairAccel exploits the symmetric routing of ICN content request / response and applies bidirectional feedback control to the content request / response path. Thus, fairAccel accelerates feedback control by mitigating router queues under control of suppressing content requests before excessive traffic is delivered to the response path. Through simulation experiments, fairAccel improves the average bitrate and further improves QoE fairness for representative ABR algorithms.

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CFGNet: Coarse-to-Fine Grained Network for Image Classification of Confusing Fly Species 7

CFGNet: Coarse-to-Fine Grained Network for Image Classificat...

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7th International Conference on Pattern Recognition and Artificial Intelligence, PRAI 2024

作者： Niu, Lin Wang, Bo Niu, Baomin Zhang, Jin Liang, Danning Wu, Jingpeng Zhou, Rong Deng, Jianqiang School of Biomedical Informatics and Engineering Hainan Medical University Haikou China Hainan Vocational College of Political Science and Law Hainan Gongping Forensic Center Haikou China School of Big Data and Artificial Intelligence Zhengzhou University of Science and Technology Zhengzhou China Center for Educational Technology Hainan Medical University Haikou China Medicine of Hainan Medical University Department of Forensic Haikou China

ISBN: (纸本)9798350350890

In the realm of fine-grained image classification (FGIC), despite substantial technological advancements, models frequently misclassify certain fly species with exceedingly high inter-class similarity, thereby impacting overall classification accuracy. To address this challenge, we propose an innovative Coarse-to-Fine Grained Network Framework (CFGNet). This architecture tackles the issue through two stages: Initially, to alleviate classification complexity, closely related and easily confused categories are amalgamated. Subsequently, a lightweight coarse-grained information extraction network (CM) is introduced to enhance the classification accuracy of samples with relatively larger class differences. In the second stage, for precise identification of challenging samples, a fine-grained feature extraction network (FM) is proposed exclusively for difficult-to-distinguish images. Additionally, we introduce a novel feature reuse method to deeply mine and repurpose coarse-grained features from the previous stage to guide fine-grained classification and improve performance in this stage. To validate our approach, we curated a dataset based on merged confusion classes annotation (Flies-MCC). Experimental results demonstrate that our proposed network architecture achieves significant advancements in fine-grained fly classification and offers a pioneering solution for precise fly identification. © 2024 IEEE.

关键词： Coarse-grained modeling

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