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Integration of IoT & cloud computing in mobile communication to breach limitation

International Journal of Information Technology (Singapore) 2025年第1期17卷 539-545页

作者： Kanchan, Pradeep Selvakumar, V. Lavanya, P. Kumar, Ravi Mishra, Awakash Haripriya, V. Ahluwalia, Gunveen Department of Computer Science and Engineering NMAM Institute of TechnologyNitte(Deemed to be University) Karnataka India Department of Maths & Statistics Bhavan’s Vivekananda College of Science Humanities and Commerce Hyderabad India Department of Physics & Electronics Bhavan’s Vivekananda College of Science Humanities and Commerce Hyderabad India Centre of Research Impact and Outcome Chitkara University Punjab Rajpura 140417 India Maharishi School of Engineering & Technology Maharishi University of Information Technology Uttar Pradesh Lucknow India Department of Computer Science and Information Technology Jain (Deemed to be University) Karnataka Bangalore India Chitkara Centre for Research and Development Chitkara University Himachal Pradesh 174103 India

The evolution of cloud computing has brought great progress in data processing capabilities but advanced issues still hinder the performance of mobile applications, especially those that require fast interaction and delicate data management. Traditional cloud data centers are geographically distant from end users, which slows data transfer and limits real-time interactions. In response to these challenges, the given paper proposes an Internet of things (IoT) based mobile cloud computing framework for enabling affordable and space-based computing for mobile users. The proposed framework comprises mobile users, controllers and IoT devices. When the mobile client moves across different locations, the data automatically transfers to nearby IoT devices thereby ensuring efficient processing without relying on remote isolated data centres. Lastly, the performance of the proposed framework is validated and compared with existing recent studies based on evaluation metrics such as root mean square error (RMSE), mean absolute error (MAE), computation time (mins) and accuracy (%). © Bharati Vidyapeeth's Institute of computer Applications and Management 2024.

关键词： Cloud computing Computation IoT Latency Mobile agent (M-agent)s

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Unit Cell Design for a Low-Profile Dual-Frequency Dual-Sense Circularly Polarized Folded Transmitarray

Unit Cell Design for a Low-Profile Dual-Frequency Dual-Sense...

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European Conference on Antennas and Propagation, EuCAP

作者： Zhongliang Lu Changjiang Zha Qi Luo Baiqing Tang Yuanming Cai School of Information Engineering Jiangxi University of Science and Technology Jiangxi China School of Physics Engineering and Computer Science University of Hertfordshire UK National Key Laboratory of Antennas and Microwave Technology Xidian University Xi'an China

ISBN: (数字)9788831299107

ISBN: (纸本)9798350366327

This paper presents a unit cell suitable for a dual-band, dual-sense circularly polarized (CP) transmitarray. To achieve dual-band operation, two types of patches are designed and interleaved to form a 2x2 array, serving as the unit cell for the transmitarray. Electromagnetic (EM) simulations under periodic boundary conditions are performed to optimize the unit cell's performance. The simulation results demonstrate that the 2x2 array can convert CP waves with opposite senses: the low-frequency patch transmits right-handed circularly polarized (RHCP) waves at 10.05 GHz, while the high-frequency patch transmits left-handed circularly polarized (LHCP) waves at 12.65 GHz. Moreover, the developed transmitarray element maintains stable CP performance with oblique incidence angles up to 42 degrees, making it well-suited for folded transmitarray designs.

关键词： Mutual coupling Simulation Transmitting antennas Dual band Europe Boundary conditions Antennas and propagation Electromagnetics Frequency control

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Enhancing Privacy-Utility Trade-offs to Mitigate Memorization in Diffusion Models

arXiv

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arXiv 2025年

作者： Chen, Chen Liu, Daochang Shah, Mubarak Xu, Chang School of Computer Science Faculty of Engineering The University of Sydney Australia School of Physics Mathematics and Computing The University of Western Australia Australia Center for Research in Computer Vision University of Central Florida United States

Text-to-image diffusion models have demonstrated remarkable capabilities in creating images highly aligned with user prompts, yet their proclivity for memorizing training set images has sparked concerns about the originality of the generated images and privacy issues, potentially leading to legal complications for both model owners and users, particularly when the memorized images contain proprietary content. Although methods to mitigate these issues have been suggested, enhancing privacy often results in a significant decrease in the utility of the outputs, as indicated by text-alignment scores. To bridge the research gap, we introduce a novel method, PRSS, which refines the classifier-free guidance approach in diffusion models by integrating prompt re-anchoring (PR) to improve privacy and incorporating semantic prompt search (SS) to enhance utility. Extensive experiments across various privacy levels demonstrate that our approach consistently improves the privacy-utility trade-off, establishing a new state-of-the-art. Copyright © 2025, The Authors. All rights reserved.

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Advanced Semantic Communication Techniques for IoT Using Disentangled Information Bottleneck

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IEEE Internet of Things Journal 2025年

作者： Xie, Wenwu Xiong, Ming Yang, Liang Wang, Ji Li, Xingwang Yang, Zhihe School of Information Science and Engineering Hunan Institute of Science and Technology Yueyang414006 China Hunan University College of Computer Science and Electronic Engineering Changsha410082 China Central China Normal University College of Physical Science and Technology Department of Electronics and Information Engineering Wuhan430079 China Henan Polytechnic University School of Physics and Electronic Information Engineering Jiaozuo454003 China

This paper explores the impact of source data compression on the performance of task execution at the receiver side of a communication system, and investigates the interference and impact of channel environment variations on semantic coding features. In order to further optimize the performance of the semantic communication model, a semantic communication framework (DIB-DeepSC) based on Disentangled Information Bottleneck (DisenIB) is proposed, which improves the inference accuracy of the model by separating and decoupling irrelevant information in the source data, thus compressing valid information related to downstream task execution to a greater extent, reduced communication overhead. Meanwhile, the influence of the Lagrange multiplier β in the classical Information Bottleneck (IB) framework is eliminated, which avoids the need to manually optimize β several times in the semantic communication model. And the dynamic coding method (DIB-DE) is further designed based on adaptive weights, which can dynamically adjust the coding features according to the channel conditions and enhance the robustness of the model. Numerous experiments show that the proposed DIB-DeepSC framework combined with the DIB-DE dynamic encoding communication scheme possesses better semantic extraction and task inference performance relative to the benchmark methods. This scheme is expected to realize more efficient and reliable semantic transmission in practical communication systems and provides new ideas for developing practical semantic communication systems. © 2014 IEEE.

关键词： Channel coding

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*** - online tutorials on small-angle scattering data analysis

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Journal of Applied Crystallography 2025年第Pt 2期58卷 603-608页

作者： Larsen, Andreas Haahr Jacobsen, Jeppe Breum Graewert, Melissa Ann Grøndahl, Lau Blom Svaneborg, Carsten Sebastiani, Federica Kikhney, Alexey G. Tyler, Arwen Irene Ingrid Kihara, Shinji Lytje, Kristian Pedersen, Jan Skov Moslehi, Neshat Voets, Ilja Fehér, Bence Holm-Janas, Viktor Bruun, Jesper Pedersen, Martin Cramer Kirkensgaard, Jacob Judas Kain Department of Neuroscience University of Copenhagen Denmark Niels Bohr Institute University of Copenhagen Denmark Hamburg Site Germany Department of Physics Chemistry and Pharmacy University of Southern Denmark Denmark Department of Pharmacy University of Copenhagen Denmark Xenocs Nordic Denmark School of Food Science and Nutrition University of Leeds United Kingdom Aarhus University Denmark Department of Chemical Engineering and Chemistry Eindhoven University of Technology Netherlands Department of Biophysics and Radiation Biology Semmelweis University Hungary Department of Science Education University of Copenhagen Denmark Department of Computer Science University of Copenhagen Denmark Department of Food Science University of Copenhagen Denmark

Small-angle X-ray and neutron scattering (SAXS and SANS) are versatile techniques for studying the structure of various materials and particles, enabling investigations of structures from a few to hundreds of nanometres. However, interpreting SAXS or SANS data can be challenging, hence the need for effective training. Here, we present the website ***, which offers tutorials on small-angle scattering (SAS) data analysis. The website serves as a learning platform that supports active learning both in the classroom and through self-study. The tutorials cover basic concepts, advanced modelling and theoretical aspects of SAS. Each tutorial follows a structure based on the principle of SOLO taxonomy, guiding learners from minimal or no knowledge in a given area to the ability to tackle real-world problems. *** has been developed as a community tool, providing tutorials that encompass a broad range of data analysis types, leveraging various programs and investigating different materials. Moreover, the website and all its data are open source, encouraging contributions from the community. © 2025 Andreas Haahr Larsen et al.

关键词： Teaching

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Characterizing Nonlinear Dynamics via Smooth Prototype Equivalences

arXiv

引用

arXiv 2025年

作者： Friedman, Roy Moriel, Noa Ricci, Matthew Pelc, Guy Weiss, Yair Nitzan, Mor School of Computer Science & Engineering The Hebrew University of Jerusalem Racah Institute of Physics The Hebrew University of Jerusalem Faculty of Medicine The Hebrew University of Jerusalem

Characterizing dynamical systems given limited measurements is a common challenge throughout the physical and biological sciences. However, this task is challenging, especially due to transient variability in systems with equivalent long-term dynamics. We address this by introducing smooth prototype equivalences (SPE), a framework that fits a diffeomorphism using normalizing flows to distinct prototypes — simplified dynamical systems that define equivalence classes of behavior. SPE enables classification by comparing the deformation loss of the observed sparse, high-dimensional measurements to the prototype dynamics. Furthermore, our approach enables estimation of the invariant sets of the observed dynamics through the learned mapping from prototype space to data space. Our method outperforms existing techniques in the classification of oscillatory systems and can efficiently identify invariant structures like limit cycles and fixed points in an equation-free manner, even when only a small, noisy subset of the phase space is observed. Finally, we show how our method can be used for the detection of biological processes like the cell cycle trajectory from high-dimensional single-cell gene expression data. © 2025, CC BY.

关键词： Equivalence classes

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Machine learning-based optimization of photodynamic therapy for human skin affected by malignant melanoma: a Monte Carlo study and 3D renderings 22

Machine learning-based optimization of photodynamic therapy ...

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Dynamics and Fluctuations in Biomedical Photonics XXII 2025

作者： Vasilieva, Elena Vladyko, Ilya Yakovlev, Vladislav Doronin, Alexander School of Engineering and Computer Science Victoria University of Wellington Wellington6140 New Zealand Department of Biomedical Engineering Department of Electrical and Computer Engineering Department of Physics and Astronomy Institute for Quantum Science and Engineering Texas A&M University College StationTX77843 United States

ISBN: (纸本)9781510683846

In this work we developed 3D spacially and volumetrically varying melanoma model an investigate light localization therein for effective optimization of photodynamic therapy applications. Utilizing the MC model developed in house, we simulated photon propagation in turbid media, varying parameters like light source geometry, melanoma size, and melanin and blood concentrations. We utilize Machine Learning for the assessment of the functional properties of melanoma-affected human skin and demonstrate its biophysically-based 3D volumetric renderings, highlighting the impact of varying melanin and blood concentrations on visualizations and PDT signal formation. © 2025 SPIE.

关键词： Rendering (computer graphics)

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Wide-Angular Scanning Performance Enhancement Phased Aarray Using Phase Gradient Metasurface

Wide-Angular Scanning Performance Enhancement Phased Aarray ...

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European Conference on Antennas and Propagation, EuCAP

作者： Yihan Ma Qi Luo Yonggang Zhou Guangwei Yang School of Physics Engineering and Computer Science University of Hertfordshire Hatfield UK School of Electronic and Information Engineering Nanjing University of Aeronautics and Astronautics Nanjing China School of Electronics and Information Northwestern Polytechnical University Xi'an China

ISBN: (数字)9788831299107

ISBN: (纸本)9798350366327

This work proposes a novel concept for improving beam scanning performance in a phased array. Theoretical analysis demonstrates that a 1D linear array integrated with a phase gradient metasurface ground can introduce additional phase delays to the corresponding image elements, enhancing array scanning performance, especially for gain improvement across the entire scanning range as well as sidelobe reduction at large scanning angles. To validate this concept, a printed 1D linear dipole array with a rectangular-shaped digital coding metasurface was designed and fabricated. The proposed phased array achieves accurate angle scanning and low sidelobe levels by adjusting the phase distribution of the metasurface ground. The proposed structure achieves a maximum gain enhancement of 2.7 dBi compared to the conventional phased array with a PEC ground, and the maximum sidelobe level is −9.6 dB when scanning at elevation angle of 60 degree.

关键词： Phased arrays Dipole antennas Communication systems Europe Metasurfaces Encoding Delays Complexity theory Electromagnetics Gain

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Geometry-Aware Self-Supervised Indoor 360° Depth Estimation via Asymmetric Dual-Domain Collaborative Learning

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IEEE Transactions on Multimedia 2025年

作者： Wang, Xu He, Ziyan Zhang, Qiudan Yang, You Zhao, Tiesong Jiang, Jianmin Shenzhen University College of Computer Science and Software Engineering Shenzhen518060 China Huangzhong University of Science and Technology School of Electronic Information and Communications Wuhan430074 China Fuzhou University College of Physics and Information Engineering Fuzhou350108 China

Being able to estimate monocular depth for spherical panoramas is of fundamental importance in 3D scene perception. However, spherical distortion severely limits the effectiveness of vanilla convolutions. To push the envelope of accuracy, recent approaches attempt to utilize Tangent projection (TP) to estimate the depth of 360° images. Yet, these methods still suffer from discrepancies and inconsistencies among patch-wise tangent images, as well as the lack of accurate ground truth depth maps under a supervised fashion. In this paper, we propose a geometry-aware self-supervised 360° image depth estimation methodology that explores the complementary advantages of TP and Equirectangular projection (ERP) by an asymmetric dual-domain collaborative learning strategy. Especially, we first develop a lightweight asymmetric dual-domain depth estimation network, which enables to aggregate depth-related features from a single TP domain, and then produce depth distributions of the TP and ERP domains via collaborative learning. This effectively mitigates stitching artifacts and preserves fine details in depth inference without overspending model parameters. In addition, a frequent-spatial feature concentration module is devised to simultaneously capture non-local Fourier features and local spatial features, such that facilitating the efficient exploration of monocular depth cues. Moreover, we introduce a geometric structural alignment module to further improve geometric structural consistency among tangent images. Extensive experiments illustrate that our designed approach outperforms existing self-supervised 360° depth estimation methods on three publicly available benchmark datasets. © 1999-2012 IEEE.

关键词： Self-supervised learning

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Exploring Quantum Control Landscape and Solution Space Complexity through Optimization Algorithms & Dimensionality Reduction

arXiv

引用

arXiv 2025年

作者： Fentaw, Haftu W. Campbell, Steve Caton, Simon School of Computer Science University College Dublin Dublin Ireland School of Physics University College Dublin Dublin Ireland Centre for Quantum Engineering Science and Technology University College Dublin Dublin Ireland

Understanding the quantum control landscape (QCL) is important for designing effective quantum control strategies. In this study, we analyze the QCL for a single two-level quantum system (qubit) using various control strategies. We employ Principal Component Analysis (PCA), to visualize and analyze the QCL for higher dimensional control parameters. Our results indicate that dimensionality reduction techniques such as PCA, can play an important role in understanding the complex nature of quantum control in higher dimensions. Evaluations of traditional control techniques and machine learning algorithms reveal that Genetic Algorithms (GA) outperform Stochastic Gradient Descent (SGD), while Q-learning (QL) shows great promise compared to Deep Q-Networks (DQN) and Proximal Policy Optimization (PPO). Additionally, our experiments highlight the importance of reward function design in DQN and PPO demonstrating that using immediate reward results in improved performance rather than delayed rewards for systems with short time steps. A study of solution space complexity was conducted by using Cluster Density Index (CDI) as a key metric for analyzing the density of optimal solutions in the landscape. The CDI reflects cluster quality and helps determine whether a given algorithm generates regions of high fidelity or not. Our results provide insights into effective quantum control strategies, emphasizing the significance of parameter selection and algorithm optimization. Copyright © 2025, The Authors. All rights reserved.

关键词： Dimensionality reduction

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