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Intelligent wearable vision systems for the visually impaired in Saudi Arabia

Neural Computing and Applications 2025年第14期37卷 8571-8591页

作者： Talaat, Fatma M. El-Shafai, Walid Soliman, Naglaa F. Algarni, Abeer D. El-Samie, Fathi E. Abd Faculty of Artificial Intelligence Kafrelsheikh University Kafrelsheikh33516 Egypt Faculty of Computer Science and Engineering New Mansoura University Gamasa35712 Egypt Security Engineering Lab Computer Science Department Prince Sultan University Riyadh11586 Saudi Arabia Department Electronics and Electrical Communications Engineering Faculty of Electronic Engineering Menoufia University Menouf32952 Egypt Department of Information Technology College of Computer and Information Sciences Princess Nourah Bint Abdulrahman University P.O. Box 84428 Riyadh11671 Saudi Arabia

Navigating the world with visual impairments presents unique challenges, often limiting independence and safety. This research introduces SafeStride, a novel algorithm designed to empower visually impaired individuals through real-time obstacle detection and navigation assistance. SafeStride functions through five interconnected phases: sensor data acquisition, data preprocessing, obstacle detection, path planning, and feedback and guidance. A combination of ultrasonic sensors, cameras, and inertial measurement units (IMUs) feed comprehensive environmental data into the system, enabling accurate obstacle detection and safe path planning. Evaluating SafeStride's performance involved the MNIST dataset for image recognition and a dedicated indoor object detection dataset. Additionally, comparisons were made against three deep learning models—convolutional neural network (CNN), long short-term memory (LSTM), and gated recurrent unit (GRU). The results showcased SafeStride's high accuracy and effectiveness in both obstacle detection and classification. Beyond its impressive performance, SafeStride represents a significant leap forward in navigation aids for the visually impaired. By offering a comprehensive solution that enhances safety and independence in diverse environments, it holds immense potential to improve the lives of countless individuals. Future efforts will focus on further optimizing the algorithm and testing its real-world capabilities, paving the way for a future where safe and independent navigation becomes a reality for all. All three deep learning models (CNN, LSTM, GRU) excelled in the experiment, achieving high accuracy above 0.98, strong recall and F1-scores near 0.99, and exceptional AUC-ROC scores exceeding 0.9998. © The Author(s), under exclusive licence to Springer-Verlag London Ltd., part of Springer Nature 2025.

关键词： Motion planning

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Image Reconstruction on Electromagnetic Simulation by Using a Recurrent Neural Network

Image Reconstruction on Electromagnetic Simulation by Using ...

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Pacific Rim Conference on Lasers and Electro-Optics (CLEO/Pacific Rim)

作者： Hiroshi Fukuda Department of Information System Engineering Chitose Institute of Science and Technology Chitose Hokkaido Japan

This study demonstrates that images can be inferred using a recurrent neural network trained on a large number of electromagnetic field images as time-series data and that the simulation results can be repeatedly and ... 详细信息

ISBN: (数字)9798350372076

ISBN: (纸本)9798350372083

关键词： Electric potential Recurrent neural networks Simulation Electromagnetic fields Electromagnetics Image reconstruction Electo-optic effects

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MISA: Unveiling the Vulnerabilities in Split Federated Learning

MISA: Unveiling the Vulnerabilities in Split Federated Learn...

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International Conference on Acoustics, Speech, and Signal Processing (ICASSP)

作者： Wei Wan Yuxuan Ning Shengshan Hu Lulu Xue Minghui Li Leo Yu Zhang Hai Jin School of Cyber Science and Engineering Huazhong University of Science and Technology National Engineering Research Center for Big Data Technology and System Services Computing Technology and System Lab Hubei Key Laboratory of Distributed System Security Hubei Engineering Research Center on Big Data Security School of Computer Science and Technology Huazhong University of Science and Technology School of Software Engineering Huazhong University of Science and Technology School of Information and Communication Technology Griffith University Cluster and Grid Computing Lab

Federated learning (FL) and split learning (SL) are prevailing distributed paradigms in recent years. They both enable shared global model training while keeping data localized on users’ devices. The former excels in parallel execution capabilities, while the latter enjoys low dependence on edge computing resources and strong privacy protection. Split federated learning (SFL) combines the strengths of both FL and SL, making it one of the most popular distributed architectures. Furthermore, a recent study has claimed that SFL exhibits robustness against poisoning attacks, with a fivefold improvement compared to FL in terms of *** this paper, we present a novel poisoning attack known as $\color{Fuchsia} {{\text{MISA}}}$. It poisons both the top and bottom models, causing a misalignment in the global model, ultimately leading to a drastic accuracy collapse. This attack unveils the vulnerabilities in SFL, challenging the conventional belief that SFL is robust against poisoning attacks. Extensive experiments demonstrate that our proposed MISA poses a significant threat to the availability of SFL, underscoring the imperative for academia and industry to accord this matter due attention.

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Why Does Little Robustness Help? A Further Step Towards Understanding Adversarial Transferability

Why Does Little Robustness Help? A Further Step Towards Unde...

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IEEE Symposium on Security and Privacy

作者： Yechao Zhang Shengshan Hu Leo Yu Zhang Junyu Shi Minghui Li Xiaogeng Liu Wei Wan Hai Jin National Engineering Research Center for Big Data Technology and System Services Computing Technology and System Lab Hubei Engineering Research Center on Big Data Security Hubei Key Laboratory of Distributed System Security School of Cyber Science and Engineering Huazhong University of Science and Technology School of Information and Communication Technology Griffith University School of Software Engineering Huazhong University of Science and Technology Cluster and Grid Computing Lab School of Computer Science and Technology Huazhong University of Science and Technology

ISBN: (数字)9798350331301

ISBN: (纸本)9798350331318

Adversarial examples for deep neural networks (DNNs) are transferable: examples that successfully fool one white-box surrogate model can also deceive other black-box models with different architectures. Although a bunch of empirical studies have provided guidance on generating highly transferable adversarial examples, many of these findings fail to be well explained and even lead to confusing or inconsistent advice for practical *** this paper, we take a further step towards understanding adversarial transferability, with a particular focus on surrogate aspects. Starting from the intriguing "little robustness" phenomenon, where models adversarially trained with mildly perturbed adversarial samples can serve as better surrogates for transfer attacks, we attribute it to a trade-off between two dominant factors: model smoothness and gradient similarity. Our research focuses on their joint effects on transferability, rather than demonstrating the separate relationships alone. Through a combination of theoretical and empirical analyses, we hypothesize that the data distribution shift induced by off-manifold samples in adversarial training is the reason that impairs gradient *** on these insights, we further explore the impacts of prevalent data augmentation and gradient regularization on transferability and analyze how the trade-off manifests in various training methods, thus building a comprehensive blueprint for the regulation mechanisms behind transferability. Finally, we provide a general route for constructing superior surrogates to boost transferability, which optimizes both model smoothness and gradient similarity simultaneously, e.g., the combination of input gradient regularization and sharpness-aware minimization (SAM), validated by extensive experiments. In summary, we call for attention to the united impacts of these two factors for launching effective transfer attacks, rather than optimizing one while ignoring the other, and emphasize the

关键词： Training Privacy Buildings Closed box Minimization Data augmentation Robustness

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Performance Realization for Gas Turbine system: Adaptive Constraint Regulation Framework 6

Performance Realization for Gas Turbine System: Adaptive Con...

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6th International Conference on Electronic engineering and Informatics, EEI 2024

作者： Du, Peihao Zhong, Weimin Li, Hongyi Li, Linlin Peng, Xin He, Kaixun School of Electronic and Information Engineering Chongqing Key Laboratory of Generic Technology and System of Service Robots Southwest University Chongqing400715 China School of Automation and Electrical Engineering University of Science and Technology Beijing Key Laboratory of Knowledge Automation for Industrial Processes of Ministry of Education Beijing100083 China East China University of Science and Technology Key Laboratory of Smart Manufacturing in Energy Chemical Process Ministry of Education Shanghai200237 China Engineering Research Center of Process System Engineering Ministry of Education East China University of Science and Technology Shanghai200237 China College of Electrical Engineering and Automation Shandong University of Science and Technology Qingdao266590 China

ISBN: (纸本)9798350353594

With the excessive consumption of fossil energy and the growing environmental pollution caused by its combustion, the gas turbine system (GTS) plays a key role in distributed renewable energy fields due to its versatility, efficiency and controllability. This paper focuses on the adaptive constraint regulation problem for the GTS with time-varying load disturbance, thereby facilitating exact speed tracking to regulate the fuel flow for the turbine under variable load conditions. Therein, a residual transformation dynamics based on the performance function are established for triggering the preset-time residual convergence and output performance constraints. Then, an adaptive constraint controller is developed to ensure the desired regulation level of the GTS. Simulation results illustrate that the proposed strategy can mitigate the load disturbance effect and guarantee the GTS performance constraints. © 2024 IEEE.

关键词： Gas turbines

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Evaluating the A3RSRP Handover to Determine Optimal Performance in HetNet using Stochastic Petri Net 6

Evaluating the A3RSRP Handover to Determine Optimal Performa...

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6th International Conference on system Reliability and Safety engineering, SRSE 2024

作者： Zhu, Zhiyi Zheng, Junjun Takimoto, Eiji Finnerty, Patrick Ohta, Chikara Kobe University Graduate School of System Informatics Kobe Japan Hiroshima University Graduate School of Advanced Science and Engineering Hiroshima Japan Nara Women's University Information Technology Center Nara Japan

ISBN: (纸本)9798350356083

Handover is necessary for improving user equipment (UE) communication quality among different cells in mobile communication networks. However, the handover decision algorithm (HDA) parameters are often difficult to choose. The use of an inappropriate parameter, such as a handover margin (HOM), causes handover failure (HoF) or frequent handover (FHO), especially in heterogeneous networks (HetNet). Therefore, properly determining a handover parameter is crucial for avoiding the HoF and FHO, as well as improving network performance. In this paper, we propose a stochastic Petri Net (SPN) to model the behavior of a UE in a HetNet. We also evaluate and predict the impact on HoF and FHO by different values of HOM in the steady-state, where the FHO is considered as handover trigger probability (HoT). Finally, the HOM value for optimal handover performance is determined using the absolute difference between the HoF and HoT through numerical experiments. The optimal handover performance was obtained at a HOM value of 6.0 dB using the proposal SPN. © 2024 IEEE.

关键词： Mobile telecommunication systems

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A Software-Defined Reconfigurable Battery system Prototype 29

A Software-Defined Reconfigurable Battery System Prototype

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29th IEEE Asia Pacific Conference on Communications, APCC 2024

作者： Jin, Siyu Liu, Baochang Zhou, Yanglin Liang, Junrui Ci, Song Tsinghua University Department of Electrical Engineering Beijing China ShanghaiTech University School of Information Science and Technology Shanghai China Tsinghua University State Key Laboratory of Power System Operation and Control Beijing China

ISBN: (纸本)9798331517816

In the energy internet era, distributed energy storage systems will be widely used in various industrial, commercial, and residential scenarios. However, the modeling of energy flow and the digital flow of information operate on different temporal and spatial scales in traditional energy storage systems, lacking deep integration between energy flow and information flow. This prevents it from completely addressing the complex battery cell balancing and low safety issues in current distributed energy storage systems. The proposal of software-defined energy storage provides a new approach to solve the inherent problems in the battery industry by introducing the idea of internet shielding terminal differences into energy storage system. We proposed a software-defined reconfiguration battery system (SRBS) in this paper, which can manage different types of energy storage media to adapt to varying loads and operating conditions. Energy-type batteries, power-type batteries, and supercapacitors are integrated together to form an efficient and safe energy storage and power supply system. The hardware architecture and software control method of SRBS are described in detail. Finally, a real-world prototype is charged and discharged to show the successful coexistence and operation of different energy storage media within a single system. © 2024 IEEE.

关键词： Battery management systems

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VulPin: Finer-Grained Slicing for Pinpointing Vulnerability in Binary Programs: Precision in Vulnerability Detection: Advanced Slicing Techniques for Binary Program Analysis 7

VulPin: Finer-Grained Slicing for Pinpointing Vulnerability ...

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7th International Conference on Computer science and Artificial Intelligence, CSAI 2023

作者： Chukkol, Abdulrahman Hamman Adama Luo, Senlin Yunusa, Haruna Yusuf, Abdulganiyu Abdu Mohammed, Abulfatahi School of Information and Electronics Beijing Institute of Technology Beijing China Information System and Security and Countermeasures Experimental Center Beijing Institute of Technology Beijing China School of Automation Science and Electrical Engineering Beihang University Beijing China School of Computer Science Beijing Institute of Technology Beijing China School of Management and Information Technology Modibbo Adama University Yola Nigeria

ISBN: (纸本)9798400708688

Identifying vulnerabilities in binary code with precision is a critical area of study in the field of software security. Most existing techniques fail to pinpoint the vulnerability's exact location, due to the extensive labelled data requirement and lack of targeted approach to improve on the problematic code. In this paper, we introduce VulPin, a system specifically designed to pinpoint vulnerabilities in binary code. This framework uses a hierarchical attention network that analyze program slices along with a vulnerability position matrix. Experimental outcomes indicate that our framework not only outperforms existing approaches but also pinpoints vulnerabilities more rapidly with a high Accuracy and a very low rate of false positives. © 2023 ACM.

关键词： Binary codes

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Mean-Square Exponential Consensus of Nonlinear Multi-Agent systems via Distributed Random Impulsive Control 49

Mean-Square Exponential Consensus of Nonlinear Multi-Agent S...

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49th Annual Conference of the IEEE Industrial Electronics Society, IECON 2023

作者： Yu, Yi He, Wangli Yang, Yanping East China University of Science and Technology Key Laboratory of Smart Manufacturing in Energy Chemical Processes Ministry of Education Shanghai China Engineering Research Center of Process System Engineering Ministry of Education East China University of Science and Technology Shanghai China College of Information Science and Technology and Engineering Research Center of Digitized Donghua University Shanghai China

ISBN: (纸本)9798350331820

This paper aims to study mean-square exponential consensus of nonlinear leader-following multi-agent systems (MASs) in the presence of noise via distributed random impulsive control. The noise is driven by a second-order moment process with bounded mean power. A distributed random impulsive controller whose impulses occur at random moments is designed to ensure the desired consensus performance while enhancing security of the system. Sufficient conditions in terms of the network topology and impulsive parameter are derived, using the Lyapunov-based approach and properties of stochastic process. Finally, a numerical example is presented to demonstrate the effectiveness of our theoretical results. © 2023 IEEE.

关键词： Multi agent systems

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Synergizing the low-phase noise characteristics of a dielectric resonator oscillator and a bichromatic Brillouin laser oscillator

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Optics Letters 2025年第3期50卷 988-991页

作者： Hu, Jiahao Xue, Siyi Xiao, Yanlan Wu, Chenlin Wen, Huashun Zhou, Heng Key Lab of Optical Fiber Sensing and Communication Networks School of Information and Communication Engineering University of Electronic Science and Technology of China Chengdu611731 China Chengdu Simon Electronic Technology Co. Ltd Chengdu China Institute of Intelligent Photonics Nankai University Tianjin300071 China

We introduce a method that synergistically combines the distinct phase noise profiles of a dielectric resonator oscillator (DRO) and bichromatic Brillouin laser oscillator (BBLO), for high spectral purity microwave generation. Typically, free-running DROs exhibit high-phase noise at low-frequency offsets but ultra-low-phase noise at high offsets. In contrast, BBLOs based on photonic devices demonstrate very low-phase noise at low offsets, yet they experience increased phase noise at higher offsets due to photodetector shot noise. By locking the DRO to a frequency-matching BBLO, our experiment combines the merits of both oscillators and generates X-band microwave with exceptional phase noise across the entire frequency offset range, reaching −93 dBc/Hz at 100 Hz offset and −171 dBc/Hz at 10 MHz offset. © 2025 Optica Publishing Group. All rights, including for text and data mining (TDM), Artificial Intelligence (AI) training, and similar technologies, are reserved.

关键词： Photonic devices

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