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11th IEEE International Conference on Computational Cybernetics and Cyber-Medical Systems, ICCC 2024

作者： Jamil, Saqib Jamil, Saima Farooq, Waqas Ardabili, Sina Khan, Adnan Daud Khalil, Usman Khan Mosavi, Amir Sarhad University of Science and Information Technology Department of Electrical Engineering Peshawar Pakistan Virtual University of Pakistan Pakistan University of Mohaghegh Ardabili Department of Biosystem Engineering Ardabil Iran US-Pak Center for Advanced Studies in Energy Uet Peshawar Peshawar Pakistan Cecos University Department of Electrical Engineering Peshawar Pakistan Obuda University John von Neumann Faculty of Informatics Budapest Hungary Ludovika University of Public Service Budapest Hungary

ISBN: (纸本)9798350350142

in a recent study we provided a theoretical framework for plasmonic coupled elliptical nanostructure capable of producing high-intensity spasers or nanolasers. The nanostructure which consists of a gold film substrate, underwent testing for various light polarizations where we selected a simple elliptical shape and then modified it to explore different geometries. The structure exhibited strong coupled resonance modes, particularly localized surface plasmon (LSP). Through finite-element method (FEM) simulations, we investigated the localized surface plasmon resonance (LSPR) of the system. Results revealed that introducing symmetry-breaking techniques, such as creating a symmetry-broken nano-ellipse (SBE), significantly increased both LSPR peaks and local field intensity (LFI). By selecting appropriate gain media, the nanostructure could support various plasmonic resonance modes across different wavelengths. Moreover, it demonstrated potential for developing a compact nanolaser with a broad tunability range. Adjusting light polarization and making structural modifications led to the observation of Surface Plasmon Amplification by Stimulated Emission of Radiation (SPASER) phenomena. The proposed model, with its substantial LSPR values, shows promise for applications like surface-enhanced Raman spectroscopy and sensing. The application of the data-driven methods in modeling the above phenomena has not been explored yet. Due to the complex nature of the phenomena, it is expected that the data-driven models can provide promising results. Consequently, in this article the primary results of proposing ensemble machine learning in modeling the above phenomenon are presented. In this work random forest (RF) and support vector machine (SVM) were employed for modeling and analysis of outcomes. © 2024 IEEE.

关键词： Surface plasmon resonance

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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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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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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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THE DYNAMIC PROBLEM OF AN ELASTICALLY SUPPORTED BEAM ANALYSIS USING NEURAL ARCHITECTURE SEARCH WITH AUTOMATIC DIFFERENTIATION 9

THE DYNAMIC PROBLEM OF AN ELASTICALLY SUPPORTED BEAM ANALYSI...

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9th ECCOMAS Thematic Conference on Computational Methods in Structural Dynamics and Earthquake engineering, COMPDYN 2023

作者： Demertzis, Konstantinos S. Morfidis, Konstantinos E. Kostinakis, Konstantinos G. Iliadis, Lazaros S. School of Science & Technology Informatics Studies Hellenic Open University Greece Terma Dasylliou Thessaloniki55535 Greece Department of Civil Engineering Aristotle University of Thessaloniki Aristotle University Campus Thessaloniki54124 Greece School of Engineering Department of Civil Engineering Faculty of Mathematics Programming and General Courses Democritus University of Thrace Kimmeria Xanthi Greece

The equations of motion for linear structures considered as continuous systems are generally non-homogeneous linear partial differential equations. Their solution is functions of time and spatial variables. The traditional analysis approach involves solving the eigenvalue problem. This yields the eigenvalues and eigenvectors, which can be used to construct the general solution of the differential equations. This approach has been widely used in mechanics and has proven effective in solving many engineering problems. In recent years, machine learning methods, particularly neural networks, have also been used to solve differential equations. These methods can learn the equation's solution directly from data without the need for explicit analytical expressions. This makes them particularly useful for complex problems that may need analytical solutions or for problems where obtaining analytical solutions takes time and effort. This paper compares the performance of these two approaches for a specific problem of the vibration of the Euler-Bernoulli beam on a Winkler-type elastic foundation subjected to a moving load. The machine learning approach learns the solution directly from data generated by solving the differential equation using a Neural Architecture Search (NAS) with Automatic Differentiation (AD) method (NASAD). The paper provides insights into the relative strengths and weaknesses of each method and highlights the potential of machine learning to solve complex problems with high accuracy and low computational sources. © 2023 COMPDYN Proceedings. All rights reserved

关键词： Equations of motion

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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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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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Systematic Approach for Securing and Preserving the Privacy of Blockchain Systems

Systematic Approach for Securing and Preserving the Privacy ...

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International Conference on Computing for Sustainable Global Development (INDIACom)

作者： Ramya Rajamanickam Saumya Chaturvedi National Informatics Centre Lodhi Road New Delhi India Department of Computer Science and Engineering School of Engineering and Technology Sharda University Greater Noida India

Blockchain technology provides a decentralized, irreversible, and verifiable ledger for recording digital asset transactions. This technology has the potential to drastically alter several cutting-edge scenarios. But recently, blockchain has found itself under scrutiny over security and privacy. Multiple heists and hacks have taken place in blockchain systems in this short period of blockchain evolution. Innovative secure privacy blockchain solutions utilizing the crypto-privacy approaches have become the need of the hour to handle privacy issues. The below work discusses ways to bring in state-of-the-art technologies to exculpate the concerns raised on privacy and security uncertainties. Here, the primary emphasis is given to combat the chaos arising in blockchain privacy and security thus contributing to the users and developers of blockchain. We categorically explain that blockchain alone is not sufficient in the current era of heists and attacks, giving the recommendation of the framework in the coming sections, thereby placing the techniques for privacy-preserving blockchain tightly bound to the system.

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Depth Map Estimation of Single-View Image using Smartphone Camera for a 3-Dimension Image Generation in Augmented Reality

Depth Map Estimation of Single-View Image using Smartphone C...

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International Symposium on Computer, Consumer and Control (IS3C)

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

Immersive experience exhibits such as augmented reality (AR) are a way to enjoy museums and art galleries because this way not only may update information easily but also does not require physical existence. However, 3-dimension (3D) images of AR are difficult to apply with one image as depth information either is unknown, or is cost and time consuming. This paper designs a depth map estimation method from single-view image by using smartphone camera to generate a 3D image in AR. Some functions are added into AR Depth Lab [7] in a personal computer (PC). Then, the improve AR Depth Lab [7] is installed into the smartphone. The depth map can be obtained by using patch-based depth estimation [8] and saved into the smartphone. The appropriate parameters of the proposal such as patch size, the cropped image size and the appropriate image models are set by experiments.

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