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8th International Conference on Artificial Intelligence and Security , ICAIS 2022

作者： Xu, Yabin Cui, Lulu Xu, Xiaowei Beijing Advanced Innovation Center for Materials Genome Engineering Beijing Information Science and Technology University Beijing100101 China School of Computer Beijing Information Science and Technology University Beijing100101 China Department of Information Science University of Arkansas at Little Rock Little Rock United States

ISBN: (纸本)9783031067662

The density and viscosity data of the mixture is an important basis for chemical calculation and design. However, there are some problems in obtaining these data, such as complexity, time consuming, low precision, and no-universality. To solve these problems, a prediction model based on multitasking and attention mechanism with the idea of materials genome engineering is proposed. With it, the density and viscosity of the mixture at different components and different experimental environments can be quickly and accurately predicted based on the existing experimental data. The predictive model introduces a Multi-task Learning (MTL) framework on the basis of the Deep fully connected Neural Network (DNN) to fully consider the associated features, and trains the density and viscosity of the mixture in parallel. In addition, an attention mechanism is introduced for each task, so that each task can focus on the most relevant features to itself. In the J. Chem. Eng. Data magazine of the American Chemical Society, with "organic mixture, density, viscosity" as the key word, 10158 experimental data of mixture density and viscosity are collected in 69 documents, including 336 mixture density systems and 331 mixture viscosity systems. The effectiveness of the model on this data set is verified and compared with other methods. Contrast experiment results show that, the model can effectively improve the prediction accuracy and reduce the prediction time at the same time. © 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Mixtures

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Auction Theory and Game Theory Based Pricing of Edge Computing Resources: A Survey

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IEEE Internet of Things Journal 2025年

作者： Yu, Jiguo Liu, Shun Zou, Yifei Wang, Guijuan Hu, Chunqiang University of Electronic Science and Technology of China School of Information and Software Engineering Chengdu610054 China Qilu University of Technology Big Data Institute Jinan250353 China Qufu Normal University School of Computer Science Shandong Rizhao China Shandong University School of Computer Science and Technology Shandong Qingdao266237 China Key Laboratory of Computing Power Network and Information Security Ministry of Education Shandong Computer Science Center Jinan250353 China Shandong Fundamental Research Center for Computer Science Shandong Provincial Key Laboratory of Computer Networks Jinan250353 China Chongqing University School of Big Data and Software Engineering Chongqing400044 China

The proliferation of Internet of Things (IoT) devices and edge computing applications has heightened the demand for efficient resource allocation and pricing mechanisms. Effective pricing strategies play a crucial role in optimizing resource utilization, reducing latency, and ensuring fair resource distribution among users. Both auction theory and game theory have emerged as fundamental economic frameworks for designing pricing mechanisms in edge computing. This paper presents a comprehensive survey of pricing strategies that leverage both auction and game theory, systematically categorizing existing research based on auction mechanisms and game-theoretic models. Unlike previous surveys that focus solely on auction-based pricing, this work integrates game-theoretic perspectives, providing a holistic analysis of strategic interactions in edge computing resource allocation. Furthermore, we discuss key challenges, emerging trends, and future research directions aimed at enhancing efficiency, fairness, and privacy protection in cloud-edge collaborative computing environments. © 2014 IEEE.

关键词： Mobile edge computing

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Can Language Models Serve as Temporal Knowledge Bases?

Can Language Models Serve as Temporal Knowledge Bases?

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2022 Findings of the Association for Computational Linguistics: EMNLP 2022

作者： Zhao, Ruilin Zhao, Feng Xu, Guandong Zhang, Sixiao Jin, Hai National Engineering Research Center for Big Data Technology and System Services Computing Technology and System Lab Cluster and Grid Computing Lab School of Computer Science and Technology Huazhong University of Science and Technology China Data Science and Machine Intelligence Lab University of Technology Sydney Sydney Australia

Recent progress regarding the use of language models (LMs) as knowledge bases (KBs) has shown that language models can act as structured knowledge bases for storing relational facts. However, most existing works only considered the LM-as-KB paradigm in a static setting, which ignores the analysis of temporal dynamics of world knowledge. Furthermore, a basic function of KBs, i.e., the ability to store conflicting information (i.e., 1-N, N-1 and N-M relations), is underexplored. In this paper, we formulate two practical requirements for treating LMs as temporal KBs: (i) the capacity to store temporally-scoped knowledge that contains conflicting information and (ii) the ability to use stored knowledge for temporally-scoped knowledge queries. We introduce a new dataset called LAMA-TK which is aimed at probing temporally-scoped knowledge, and investigate the two above requirements to explore the LM-as-KB paradigm in the temporal domain. On the one hand, experiments show that LMs can memorize millions of temporally-scoped facts with relatively high accuracy and transfer stored knowledge to temporal knowledge queries, thereby expanding the LM-as-KB paradigm to the temporal domain. On the other hand, we show that memorizing conflicting information, which has been neglected by previous works, is still challenging for LMs and hinders the memorization of other unrelated one-to-one relationships. © 2022 Association for Computational Linguistics.

关键词： Computational linguistics

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LowResIR-Net: Lightweight Residual Network for ADL Recognition Using Low-Resolution Infrared Sensor Data 16

LowResIR-Net: Lightweight Residual Network for ADL Recogniti...

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16th International Conference on ENTERprise Information Systems, centerIS 2024 - 12th International Conference on Project MANagement, ProjMAN 2024 - 14th International Conference on Health and Social Care Information Systems and Technologies, HCist 2024

作者： Mekruksavanich, Sakorn Phaphan, Wikanda Jitpattanakul, Anuchit Department of Computer Engineering School of Information and Communication Technology University of Phayao Phayao56000 Thailand Research Group in Statistical Learning and Inference Department of Applied Statistics Faculty of Applied Science King Mongkut's University of Technology North Bangkok Bangkok10800 Thailand Intelligent and Nonlinear Dynamic Innovations Research Center Department of Mathematics Faculty of Applied Science King Mongkut's University of Technology North Bangkok Bangkok10800 Thailand

Detecting activities of daily living (ADL) is crucial for supported living and medical monitoring. Traditional approaches rely on high-resolution sensors and computationally intensive algorithms, limiting their scalability and practical use in real-world settings. This research introduces LowResIR-Net, a compact deep residual network architecture specifically tailored for recognizing ADL utilizing low-resolution infrared sensor data. LowResIR-Net efficiently extracts key features from low-dimensional data by leveraging the advantages of infrared sensing, such as privacy protection and light resilience. Its architecture combines residual connections with depth-wise convolutions, enhancing feature learning while maintaining a compact model size. The model’s performance is evaluated using the Coventry-2018 dataset, containing low-resolution infrared data from three residential sensor locations. Our tests have shown that in all three cases, LowResIR-Net consistently achieves superior performance compared to other cutting-edge deep learning models, such as CNN, LSTM, BiLSTM, GRU, and BiGRU. LowResIR-Net attains the most excellent accuracies of 90.18%, 93.75%, and 93.30%, and F1-scores of 81.81%, 89.55%, and 88.92% for scenarios I, II, and III, respectively. Furthermore, it achieves these results with fewer parameters than most other models. LowResIR-Net’s strong performance highlights its ability to accurately capture complex patterns in low-resolution infrared data for ADL detection. This study demonstrates the potential of lightweight deep learning and low-resolution infrared sensors in developing privacy-focused and computationally efficient wellness monitoring systems. © 2025 The Author(s).

关键词： Infrared detectors

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EMC of Linear and Non-Linear Loads in Different EM Environments;An Issue of Power Quality

EMC of Linear and Non-Linear Loads in Different EM Environme...

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Asia-Pacific Symposium on Electromagnetic Compatibility (APEMC)

作者： Agung Cahyadi Putra Ilman Sulaeman Deny Hamdani Niek Moonen School of Electrical Engineering and Informatics Institut Teknologi Bandung Bandung Indonesia Electrical Engineering Mathematics and Computer Science (EEMCS) University of Twente Enschede the Netherlands School of Electrical Engineering and Informatics Research Center of New and Renewable Energy ITB Institut Teknologi Bandung Bandung Indonesia

ISBN: (数字)9784885523472

ISBN: (纸本)9798350349498

Renewable energy sources (RES) are being widely implemented in electricity systems to decarbonize energy supplies, including those in the most remote areas. In the context of the rural electrification effort in Indonesia, the impact of several common household appliances on grid voltages was determined. Modifications to the supply impedance have emulated the contextual issues that were discussed in previous literature, like extremely long distribution cables or ad-hoc modifications of the RES. The voltage rms fluctuation and voltage total harmonic distortion were examined. The results show that voltage deviation, noise, and harmonic were highly affected in the case of nonlinear loads. In the case of linear loads, as expected, the voltage quality will depend on the supply. Therefore, understanding the source impedance characteristics can be used to help maintain the EMC while using power-efficient nonlinear loads.

关键词： Total harmonic distortion Renewable energy sources Voltage fluctuations Noise Power quality Power system harmonics Electromagnetic compatibility

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Empowering Donors: How Blockchain Technology Can Help Ensure Their Contributions Reach the Right Recipients

Empowering Donors: How Blockchain Technology Can Help Ensure...

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Business Analytics for Technology and Security (ICBATS), International Conference on

作者： Sahar Ajmal Muteeb Bin Muzammil Muhammad Shoaib Muhammad Hassaan Mehmood Department of Software Engineering National University of Computer and Emmerging Sciences Chiniot-Faisalabad Pakistan College of Computing Riphah International University Faisalabad Pakistan Department of Computer Science University of Engineering and Technology Lahore Pakistan School of Computer Science NCBA&E Lahore Pakistan Applied School Research Center Applied Science Private University Amman Jordan

Charity giving is a fundamental aspect of society, but there are concerns about the accountability and transparency of the donation process. Blockchain technology has emerged as a potential solution, offering a secure and auditable platform for managing charitable contributions. In this paper, we explore the concept of empowering donors through blockchain technology and examine how it can help ensure that contributions reach the right recipients. We review existing literature on the topic and identify key areas for future research, including the development of hybrid blockchain solutions along with the implementation of novel consensus mechanisms. Moreover, providing the idea of decentralized autonomous organizations, self-executing smart contracts, and integration of blockchain with artificial intelligence and Internet of things. By providing a comprehensive overview of the current state of the field and outlining a roadmap for future research, we hope to stimulate further exploration of the potential of blockchain technology to revolutionize charity giving, and create a more accountable and transparent system for managing charitable funds. Some research questions are designed for each novel idea. Our analysis suggests that blockchain has the potential to empower donors and ensure that their contributions make a positive impact in the world, but further research is needed to fully realize its potential.

关键词： Decentralized autonomous organization Smart contracts Transforms Blockchains Consensus protocol Internet of Things Security

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HNN: Hierarchical Noise-Deinterlace Net Towards Image Denoising

HNN: Hierarchical Noise-Deinterlace Net Towards Image Denois...

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IEEE computer Society Conference on computer Vision and Pattern Recognition Workshops (CVPRW)

作者： Amogh Joshi Nikhil Akalwadi Chinmayee Mandi Chaitra Desai Ramesh Ashok Tabib Ujwala Patil Uma Mudenagudi Center of Excellence in Visual Intelligence (CEVI) KLE Technological University Hubballi Karnataka India School of Computer Science and Engineering KLE Technological University Hubballi Karnataka India School of Electronics and Communication Engineering KLE Technological University Hubballi Karnataka India

ISBN: (数字)9798350365474

ISBN: (纸本)9798350365481

In this paper, we propose a hierarchical framework for image denoising and term it Hierarchical Noise-Deinterlace Net (HNN). Image denoising techniques aim to recover clean images from noisy observations by reducing unwanted noise and artifacts to enhance the clarity and introduce spatial coherence. Images captured during challenging scenarios suffer from granular noise, inducing fine-scale variations in the image, which occur due to the limitations of imaging technology or environmental conditions. This granular noise can significantly degrade the quality of the image, making it less useful for applications like object detection, image restoration/enhancement, face detection, and image super-resolution. From literature, we infer learning global-local features significantly contribute in reducing unwanted noise and artifacts within images. Typically, researchers rely on residual learning, Generative Adversarial Networks (GANs), and Attention Mechanisms to learn global-local features. However, these methods face challenges such as vanishing gradients, limited generalization of generators in GANs, lack of global context awareness and computation complexity in attention mechanisms leading to drop in performance. Towards this, we propose a hierarchical framework to process both global and local information across distinct levels of hierarchy. More specifically, we propose a hierarchical encoder-decoder network, with a distinct Global-Local Spatio-Contextual (GLSC) block for learning of fine-grained features and high-frequency details in an image. The proposed framework improves image denoising, as it allows the model to capture and utilize information from different scales, ensuring a comprehensive understanding of the image content. We demonstrate the efficacy of proposed HNN framework, on benchmark datasets in comparison with state-of-the-art methods with 5% (↑ in dB) increase in performance.

关键词： Attention mechanisms Noise Superresolution Spatial coherence Imaging Object detection Benchmark testing

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Make 3D Cable Model from Single RGB Image 10

Make 3D Cable Model from Single RGB Image

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10th International Congress on Advanced Applied Informatics, IIAI-AAI 2021

作者： Fan, Zheming Ohashi, Takeshi Hayashi, Toyohiro Graduate School of Computer Science and System Engineering Kyushu Institute of Technology Fukuoka Japan Kyushu Institute of Technology Information Science and Technology Center Fukuoka Japan

ISBN: (纸本)9781665424202

Along with the electrification, there are many electrical equipment are used in our daily life. Using those equipment we need cables to charge and connect them. But, sometimes cables will become problems, like when we clean the room the cables will be annoying. We think if we can resolve this problem with robot, it will save lots of time for people. But, unfortunately, there is no system which can manipulate cables with robot. The key point is cable can deform it's shape. Because of this, we can't recognize and record cables position correctly from picture. And if we want to manipulate cables with robot, the 3D information of cables is far batter than 2D information. Therefore, in this paper, we made a system which can build a 3D voxels model base on 2D image as a beforehand for use robot to manipulate cables. In our system, we cut input image into a series of small pictures and make 3D model based on each pictures then we assemble those 3D model together. So we can get a complete 3D model(output of this system) which is made base on input image and can represent the 3D cables position. Our method can transfer 2D data to 3D data, this let us can get 3D information from image and we think this is useful in robot science. © 2021 IEEE.

关键词： Cables

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Bounds on the ground state energy of quantum p-spin Hamiltonians

arXiv

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arXiv 2024年

作者： Anschuetz, Eric R. Gamarnik, David Kiani, Bobak T. Institute for Quantum Information and Matter Caltech Walter Burke Institute for Theoretical Physics Caltech MIT Center for Theoretical Physics MIT United States Operations Research Center Statistics and Data Science Center Sloan School of Management MIT United States John A. Paulson School of Engineering and Applied Sciences Department of Electrical Engineering and Computer Science MIT Harvard United States

We consider the problem of estimating the ground state energy of quantum p-local spin glass random Hamiltonians, the quantum analogues of widely studied classical spin glass models. Our main result shows that the maximum energy achievable by product states has a well-defined limit (for even p) as n → ∞ and is Eproduct∗ = √2 log p in the limit of large p. This value is interpreted as the maximal energy of a much simpler so-called Random Energy Model, widely studied in the setting of classical spin glasses. The proof of the limit existing follows from an extension of Fekete’s Lemma after we demonstrate near super-additivity of the (normalized) quenched free energy. The proof of the value follows from a second moment method on the number of states achieving a given energy when restricting to an ǫ-net of product states. Furthermore, we relate the maximal energy achieved over all states to a p-dependent constant γ (p), which is defined by the degree of violation of a certain asymptotic independence ansatz over graph matchings. We show that the maximal energy achieved by all states E∗ (p) in the limit of large n is at most pγ (p)Eproduct∗ . We also prove using Lindeberg’s interpolation method that the limiting E∗ (p) is robust with respect to the choice of the randomness and, for instance, also applies to the case of sparse random Hamiltonians. This robustness in the randomness extends to a wide range of random Hamiltonian models including SYK and random quantum max-cut. Copyright © 2024, The Authors. All rights reserved.

关键词： Hamiltonians

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Enhanced Resolution Dispersion Optimized Multiphoton Microscopy with Spatial Frequency Modulation Imaging 23

Enhanced Resolution Dispersion Optimized Multiphoton Microsc...

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Multiphoton Microscopy in the Biomedical sciences XXIII 2023

作者： Scarbrough, Daniel Thomas, Anna Field, Jeff Bartels, Randy Squier, Jeff Colorado School of Mines Department of Physics 1500 Illinois St GoldenCO United States Department of Electrical and Computer Engineering Colorado State University Fort CollinsCO80523 United States Center for Imaging and Surface Science Colorado State University Fort CollinsCO80523 United States School of Biomedical Engineering Colorado State University Fort CollinsCO80523 United States

ISBN: (纸本)9781510658738

Using the structured illumination, single pixel detection imaging technique SPatIal Frequency modulation Imaging (SPIFI), we demonstrate a cascaded Wavelength Domain and Spatial Domain (WD-SD-SPIFI) system enabling real-time, in-line, second order dispersion compensation optimization for multiphoton imaging. Enhanced resolution is demonstrated by imaging a sub-diffractive 140 nm fluorescent nanodiamond with Two Photon Excitation Fluorescence (2PEF) to measure the Point Spread Function (PSF). With a 1034 nm pulsed laser through a Numerical Aperture (NA) of 0.5, a PSF Full Width at Half Max (FWHM) of 780 nm was measured with minimal post processing analysis that only requires Fast Fourier Transforms (FFTs). © 2023 SPIE.

关键词： Optical transfer function

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