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Exploring 2D representation and transfer learning techniques for indoor localization

Multimedia Tools and Applications 2025年 1-13页

作者： Kerdjidj, O. Himeur, Y. Atalla, S. Copiaco, A. Sohail, S.S. Amira, A. Fadli, F. Mansoor, W. Gawanmeh, A. Centre of Development of Advanced Techniques Algiers Algeria College of Engineering and Information Technology University of Dubai Dubai United Arab Emirates Department of Computer Science University of Sharjah Sharjah United Arab Emirates Institute of Artificial Intelligence De Montfort University Leicester United Kingdom School of Computing Science and Engineering VIT Bhopal University Kothri Kalan India Department of Architecture & Urban Planning Qatar University Doha2713 Qatar

Indoor localization (IL) plays a critical role in various applications, including asset tracking, emergency response, and indoor navigation. Traditional methods relying on one-dimensional (1D) representations of received signal strength indicator (RSSI) data often suffer from limitations such as low accuracy, environmental sensitivity, and susceptibility to interference. To overcome these challenges, this paper proposes Scalogram-Based Transfer Learning for Indoor Localization (STL-IL), a novel framework that significantly enhances localization performance. The proposed approach transforms 1D RSSI signals into two-dimensional (2D) representations using scalogram-based time-frequency analysis, coupled with advanced transfer learning (TL) techniques. By leveraging the scalogram method to generate image representations of the data and employing diverse wavelet types. Furthermore, pre-trained deep learning models, including GoogleNet and SqueezeNet, are utilized to achieve state-of-the-art performance. Experimental results demonstrate that the STL-IL system achieves remarkable accuracy levels of 95% and 96% for SqueezeNet and GoogleNet, respectively. The proposed framework not only improves localization accuracy but also enhances robustness in dynamic and challenging environments, making it a promising solution for real-world indoor localization applications. © The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2025.

关键词： Deep learning

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Accelerating Data Transfer in Dataflow architectures Through a Look-Ahead Acknowledgment Mechanism

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Journal of Computer Science & Technology 2022年第4期37卷 942-959页

作者： Yu-Jing Feng De-Jian Li Xu Tan Xiao-Chun Ye Dong-Rui Fan Wen-Ming Li Da Wang Hao Zhang Zhi-Min Tang State Key Laboratory of Computer Architecture Institute of Computing TechnologyChinese Academy of SciencesBeijing 100190China Beijing Smartchip Microelectronics Technology Company Limited Beijing 100000China School of Computer and Control Engineering University of Chinese Academy of SciencesBeijing 100190China

The dataflow architecture,which is characterized by a lack of a redundant unified control logic,has been shown to have an advantage over the control-flow architecture as it improves the computational performance and power efficiency,especially of applications used in high-performance computing(HPC).Importantly,the high computational efficiency of systems using the dataflow architecture is achieved by allowing program kernels to be activated in a simultaneous ***,a proper acknowledgment mechanism is required to distinguish the data that logically belongs to different *** solutions include the tagged-token matching mechanism in which the data is sent before acknowledgments are received but retried after rejection,or a handshake mechanism in which the data is only sent after acknowledgments are ***,these mechanisms are characterized by both inefficient data transfer and increased area *** performance of the dataflow architecture depends on the efficiency of data *** order to optimize the efficiency of data transfer in existing dataflow architectures with a minimal increase in area and power cost,we propose a Look-Ahead Acknowledgment(LAA)*** accelerates the execution flow by speculatively acknowledging ahead without *** simulation analysis based on a handshake mechanism shows that our LAA increases the average utilization of computational units by 23.9%,with a reduction in the average execution time by 17.4%and an increase in the average power efficiency of dataflow processors by 22.4%.Crucially,our novel approach results in a relatively small increase in the area and power consumption of the on-chip logic of less than 0.9%.In conclusion,the evaluation results suggest that Look-Ahead Acknowledgment is an effective improvement for data transfer in existing dataflow architectures.

关键词： dataflow model control-flow model high-performance computing application data transfer power efficiency

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OpenFOAM Modelling the Equilibrium and Free-decay Tests of a Semi-submersible FOWT Model 33rd

OpenFOAM Modelling the Equilibrium and Free-decay Tests of a...

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33rd International Ocean and Polar engineering Conference, ISOPE 2023

作者： Zhou, Yang Qian, Ling Li, Qian Department of Computing and Mathematics Manchester Metropolitan University Manchester United Kingdom Department of Naval Architecture Ocean and Marine Engineering University of Strathclyde Glasgow United Kingdom School of Mathematics Computer Science and Engineering City University of London United Kingdom

ISBN: (纸本)9781880653807

This work forms a part of the contribution to the "1st FOWT comparative study" for modelling floating offshore wind turbine(FOWT) hydrodynamics based on the wave tank tests of a 1:70 scaled moored VolturnUS semi-submersible floater model. Two sets of test cases have been simulated-one is a static equilibrium test and the other is the heave decay test to determine the natural frequencies of the coupled floater-mooring system. The numerical modelling is carried out in a numerical wave tank using high-fidelity computational fluid dynamics based on the OpenFOAM toolbox and the results are generally in good agreement with the experimental measurements. In addition, it was found that the mooring lines have a significant influence on the pitch natural frequencies of the coupled system but their impact on the heave natural frequencies was minimal. © 2023 by the International Society of Offshore and Polar Engineers (ISOPE).

关键词： Semisubmersibles

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Modeling and evaluation design of heterogeneous media networks considering quality of experience

Modeling and evaluation design of heterogeneous media networ...

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2024 China Automation Congress, CAC 2024

作者： Cong, Kun Huang, Luzhen He, Ziqi Ding, Lu Huang, Dan Song, Lei School of Aeronautics and Astronautics Shanghai Jiao Tong University Shanghai China Architecture & Technical Innovation Dept Huawei Cloud Computing Technologies Co. Ltd Shenzhen China School of Electronic Information and Electrical Engineering Shanghai Jiao Tong University Shanghai China Center for aerospace systems engineering Shanghai Jiao Tong University Shanghai China

ISBN: (纸本)9798350368604

Aiming at social media platforms with different commercial scenarios, especially for "cloud gaming", this paper proposes a modeling and analysis framework for heterogeneous media networks considering quality of experience, which addresses the challenges of quantifying human impacts. Through standardized definitions of humans and equipment, man-machine information transmission is classified formally. Then, the evaluation of quality of experience for entities and media networks are defined. Finally, a case study about analysis and optimization for media network in the scenario of "cloud gaming" is derived. Different simulation results and the experiment’s comparison imply the applicability and effectiveness of the framework proposed in this paper. © 2024 IEEE.

关键词： Cloud platforms

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A review on evaluation of crack resistance of asphalt mixture by semi-circular bending test

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Journal of Road engineering 2023年第1期3卷 87-97页

作者： Yongjun Meng Weikang Kong Chaoliang Gou Shenwen Deng Yirong Hu Jing Chen Liupeng Fan School of Civil Engineering and Architecture Guangxi UniversityNanning 530004China Key Laboratory of Disaster Prevention and Structural Safety of Ministry of Education Guangxi UniversityNanning 530004China Special Geological Highway Safety Engineering Technology Research Center Guangxi UniversityNanning 530004China National High-performance Computing Center Nanning Branch Nanning 530004China

Although there are many kinds of fracture tests to choose from in evaluating the crack resistance of asphalt mixture,the semi-circular bending(SCB)test has attracted a lot of attention in the academic road engineering community because of its simplicity,stability,and flexibility in testing and *** SCB test has become a common method to study the cracking resistance of asphalt mixture in recent *** paper mainly summarizes the overview of the SCB test,summarizes some research results and common characterization parameters of the SCB test method in monotone test and fatigue test in recent years,and predicts and suggests the research direction of the SCB test in the *** is found that the research on the monotonic SCB test is more comprehensive,and the research on the SCB fatigue test needs to be further improved in the aspects of loading mode,characterization parameter selection,and so *** can flexibly adjust the geometric dimensions and the test parameters of semi-cylindrical specimens,and conduct comprehensive analysis combined with the results of numerical *** crack resistance of asphalt mixture can be comprehensively evaluated by fracture energy,fracture toughness,stiffness,flexibility index and other fracture indicators,combined with the crack propagation of the *** analysis of numerical simulation can confirm the test *** order to standardize the setting of fatigue parameters for future application,it is necessary to standardize the setting of bending performance.

关键词： Asphalt mixture Crack resistance Fatigue performance Semi-circular bending test

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Design of User Experience Optimization System Based on Media Device Network Modeling

Design of User Experience Optimization System Based on Media...

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2024 China Automation Congress, CAC 2024

作者： Ding, Lu Huang, Luzhen Zhang, Guangyuan Li, Bochen Huang, Dan Song, Lei Center for aerospace systems engineering Shanghai Jiao Tong University Shanghai China Architecture Technical Innovation Dept Huawei Cloud Computing Technologies Co. Ltd Shenzhen China School of Electronic Information and Electrical Engineering Shanghai Jiao Tong University Shanghai China School of Aeronautics and Astronautics Shanghai Jiao Tong University Shanghai China

ISBN: (纸本)9798350368604

The media network faces challenges in systematically improving user experience due to the computational transmission tasks of massive data and highly coupled technical processes. Therefore, this paper designs a comprehensive user experience optimization system based on media device network modeling for key business scenarios, with user experience as the core, to achieve comprehensive user experience improvement for media device networks. We first use a network model to model the device network and achieve the mapping from physical space to mathematical space. Secondly we design a multi domain user experience model to map network capabilities to experience indicators. Finally, a multi-objective optimization method based on pareto optimality has been proposed for device networks to optimize their capabilities and achieve the goal of improving the overall quality of experience (QoE). We simulate weak network such as latency and packet loss in cloud gaming scenarios. When the user experience is poor, the proposed method is used to optimize the device network. The experimental results show that the user experience is significantly improved after optimization, proving the effectiveness of the proposed method. © 2024 IEEE.

关键词： media device network network modeling pareto optimality QoE user experience optimization

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Artificial Intelligence in Concrete Mix Design: Advances, Applications and Challenges

Artificial Intelligence in Concrete Mix Design: Advances, Ap...

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Innovation and Intelligence for Informatics, computing, and Technologies (3ICT), International Conference o

作者： Salim Barbhuiya Mhd Saeed Sharif Department of Engineering and Construction UEL London UK School of Architecture Computing and Engineering UEL London Uk

This review paper explores the application of Artificial Intelligence (AI) in concrete mix design and its impact on the concrete industry. The traditional approaches to concrete mix design are first discussed, highlighting their limitations. Subsequently, various applications of AI in concrete mix design are presented, including optimal proportioning of concrete mixes, prediction of concrete properties, quality control and assurance, concrete strength prediction and optimisation and durability assessment and enhancement. The benefits and impact of AI in the concrete industry are then examined, emphasising the advantages and benefits of using AI in concrete mix design. However, challenges and limitations related to data availability and quality, interpretability of AI models and integration with existing design practices are also addressed. Finally, the paper concludes with a summary of key findings and recommendations for future research in this field.

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Review of emulsified asphalt modification mechanisms and performance influencing factors

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Journal of Road engineering 2023年第2期3卷 141-155页

作者： Yongjun Meng Jing Chen Weikang Kong Yirong Hu School of Civil Engineering and Architecture Guangxi UniversityNanning 530004China Key Laboratory of Disaster Prevention and Structural Safety of Ministry of Education Guangxi UniversityNanning 530004China Special Geological Highway Safety Engineering Technology Research Center Guangxi UniversityNanning 530004China National High-performance Computing Center Nanning Branch Nanning 530004China

In recent years,with the improvement of the requirements of road performance,modified emulsified asphalts with better performance has gradually replaced the emulsified asphalt and become the primary material for road *** paper introduces the modified emulsified asphalt materials commonly used in pavement maintenance projects,definitions and modified mechanisms of polymerized styrene butadiene rubber(SBR)modified emulsified asphalt,styrene butadiene styrene block polymer(SBS)modified emulsified asphalt and waterborne epoxy resin(WER)modified emulsified asphalt are *** analysis focused on comparing the effects of modifiers,preparation process,auxiliary additives,and other factors on the performance of modified emulsified *** this paper,it is considered that the greatest impact on the performance of emulsified asphalt is the modifier,emulsifier mainly affects the speed of breaking the emulsion,stabilizers on the basic performance of emulsified asphalt evaporative residue is small;and when the modifier is distributed in the asphalt in a network,the dosage at this time is the recommended optimum ***,this study recommends that in the future,the polymer-asphalt compatibility can be improved through composite modification,chemical grafting and other methods to continue to develop broader applicability and better performance of modified emulsified asphalt.

关键词： Modified emulsified asphalt Performance Influencing factor Modification mechanism

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Cybersecurity in Industrial Networks: Artificial Intelligence Techniques Applied to Intrusion Detection Systems

Cybersecurity in Industrial Networks: Artificial Intelligenc...

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2023 Congress in Computer Science, Computer engineering, and Applied computing, CSCE 2023

作者： Luis De Moura, Ralf Franqueira, Virginia N. L. Pessin, Gustavo Operational Technology Architecture Vale S.A. Vitória Brazil School of Computing University of Kent Canterbury United Kingdom Instituto de Tecnologia Vale Department of Automation Engineering Ouro Preto Brazil

ISBN: (纸本)9798350327595

Industrial control systems (ICS) operate on serial-based networks which lack proper security safeguards by design. They are also becoming more integrated to corporate networks, creating new vulnerabilities which expose ICS networks to in-creasing levels of risk with potentially significant impact. Despite those risks, only a few mechanisms have been suggested and are available in practice as cybersecurity safeguards for the ICS network layer, maybe because they might not be commercially viable. Intrusion detection systems (IDS) are typically deployed in the corporate networks to protect against attacks since they are based on TCP/IP. However, IDS are not used in serial-based ICS networks yet. This study examines and compares modern Artificial Intelligence (AI) techniques applied in IDS that are potentially useful for serial-based ICS networks. The results showed that current AI-based IDS methods are viable in such networks. A mix of AI techniques would be the best way forward to detect known attacks via rules and novel attacks, not previously mapped, via supervised and unsupervised techniques. Despite these strategies' limited use in serial-based networks, their adoption could significantly strengthen cybersecurity of ICS networks. © 2023 IEEE.

关键词： and Intrusion Detection Systems Artificial Intelligence Cybersecurity Industrial Networks Serial Protocols

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Utilising Machine Learning for Precise State-of-Charge Prediction in Li-Ion Batteries

Utilising Machine Learning for Precise State-of-Charge Predi...

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International IEEE Conference on Intelligent Systems, IS

作者： Avinash Khatri Jaswinder Lota Prasanna Nepal Mohammad Hossein Amirhosseini School of Architecture Computing and Engineering University of East London London United Kingdom Department of Electrical and Electronics Engineering Nepal Engineering College Bhaktapur Nepal

ISBN: (数字)9798350350982

ISBN: (纸本)9798350350999

As the popularity of electric propulsion using batteries rises alongside the demand for renewable energy, effective battery management and monitoring are crucial for sustain ability and efficiency in electric vehicles (EVs). The battery monitoring system (BMS) employs IoT/sensor networks to estimate crucial battery metrics like remaining useful life (RUL), state-of-health (SoH), and state-of-charge (SoC), using data on current status, temperature, and voltage. Machine learning (ML) and artificial intelligence (AI) are increasingly utilized to enhance BMS accuracy, addressing challenges like real-time data processing and the accuracy of estimations. This paper investigates the effectiveness of Linear Regression and Random Forest models in estimating SoC. During the hyperparameter tuning phase, the models were optimized using the Grid Search method, and their performance was evaluated at various temperatures: 25°C, 10°C, 0°C, and -10°C. The findings indicate that the models' effectiveness enhances as the temperature increases. The Random Forest model exhibited superior performance at 25°C, achieving an R2 score of 0.99646 and an RMSE score of 0.000264. This paper not only contributes to advancing Li-ion battery monitoring system, but also empowers professionals in this field to harness machine learning capabilities effectively.

关键词： Lithium-ion batteries Analytical models Temperature distribution Accuracy Voltage Predictive models Real-time systems Monitoring Random forests Tuning

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