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Smart parking occupancy detection method using smart app

International Journal of Wireless and Mobile Computing 2024年第1期26卷 99-105页

作者： Rahman, Atiqur Ufiteyezu, Emmanuel Department of Computer Science and Engineering University of Chittagong Hathazari Chittagong Bangladesh Electrical and Electronics Department University of Rwanda Kigali Rwanda

Population growth in cities results in a demand for parking lots from an increasing number of automobiles, which frequently contributes to the global problem of traffic congestion. This study presents the smart parking occupancy detection system as a technique to scientifically enhance the existing parking lot, i.e., parking guidance and information method or something else, occupancy detection system. The smart app named rPark is promoted as a cutting-edge method of parking detection. Ultra-high frequency static radio frequency identification chips are placed on the asphalt and cross-examined by Radio Frequency Identification interrogator aerials over the parking areas to initially assess utilisation status. This plan eliminates the majority of the challenges associated with current up-to-the-minute parking usage identification techniques. The parking detection accuracy of rPark, which was tested and used to illustrate an experimental analysis in a real-world outdoor parking space, has been confirmed to be about 100%. Copyright © 2024 Inderscience Enterprises Ltd.

关键词： Radio frequency identification (RFID)

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Swapped logit distillation via bi-level teacher alignment

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Multimedia Systems 2025年第3期31卷 1-13页

作者： Limantoro, Stephen Ekaputra Lin, Jhe-Hao Wang, Chih-Yu Tsai, Yi-Lung Shuai, Hong-Han Huang, Ching-Chun Cheng, Wen-Huang Department of Electrical Engineering and Computer Science National Yang Ming Chiao Tung University Hsinchu300093 Taiwan Cyberlink New Taipei City231 Taiwan Department of Computer Science and Information Engineering National Taiwan University Taipei10617 Taiwan

Knowledge distillation (KD) compresses the network capacity by transferring knowledge from a large (teacher) network to a smaller one (student). It has been mainstream that the teacher directly transfers knowledge to the student with its original distribution, which can possibly lead to incorrect predictions. In this article, we propose a logit-based distillation via swapped logit processing, namely Swapped Logit Distillation (SLD). SLD is proposed under two assumptions: (1) the wrong prediction occurs when the prediction label confidence is not the maximum;(2) the "natural" limit of probability remains uncertain as the best value addition to the target cannot be determined. To address these issues, we propose a swapped logit processing scheme. Through this approach, we find that the swap method can be effectively extended to teacher and student outputs, transforming into two teachers. We further introduce loss scheduling to boost the performance of two teachers’ alignment. Extensive experiments on image classification tasks demonstrate that SLD consistently performs best among previous state-of-the-art methods. © The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature 2025.

关键词： Students

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Small Sampling Overhead Error Mitigation for Quantum Circuits

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IEEE Transactions on computer-Aided Design of Integrated Circuits and Systems 2024年第3期43卷 826-839页

作者： Hsieh, Cheng-Yun Tsai, Hsin-Ying Lu, Yuan-Hsiang Li, James Chien-Mo National Taiwan University College of Electrical Engineering and Computer Science Taipei10617 Taiwan

Probabilistic error cancellation (PEC) is a promising error mitigation technique that reduces the error rate without auxiliary quantum bits. However, PEC has two problems that need to be resolved: 1) there is no good PEC technique for parameterized gates and 2) sampling overhead (SO) grows exponentially with the number of PEC mitigated gates. We first propose a parameterized gate PEC (PGPEC) that mitigates the error without fully characterizing the gates, as the original PEC requires. The result shows that the number of gates requiring characterization for a thousand random circuits can be reduced by 97% or more. We next propose two novel approaches to solving the second problem. We propose a macro gate PEC (MGPEC) technique that aggregates multiple gates as a single macro gate to reduce the exponent of the SO. MGPEC reduces the SO by 49% on the QFT7 under the IBMQ noise model, which simulates real operation conditions of quantum circuits. We propose a design diversity PEC (DDPEC) technique to reduce the exponential basis of the SO. The results show that our DDPEC with design diversity check reduces overall SO by 13% on the QFT7 circuit under the IBM Q noise model. Combining the DDPEC with the MGPEC, we can reduce overall SO by 73%. © 1982-2012 IEEE.

关键词： Cost reduction

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Identification of Human Activity from Video Streaming Smartphone Data Using Intensified VGG16

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International Journal of engineering, Transactions B: Applications 2025年第6期38卷 1340-1352页

作者： Yadav, R.K. Daniel, A. Semwal, V.B. Department of Computer Science and Engineering Amity University Gwalior India Data Science and Engineering Manipal University Jaipur India Department of Computer Science and Engineering Maulana Azad National Institute Technology Bhopal India

Human activity recognition (HAR) techniques pick out and interpret human behaviors and actions by analyzing data gathered from various sensor devices. HAR aims to recognize and automatically categorize human activities using patterns and attributes taken from sensor data. HAR is complex in implementing the algorithm for a self-recorded dataset, including challenges such as age variation, wearing different clothes, environment and surface, the direction of the smartphone camera, and many more. The paper aims to propose a VGG16 deep learning framework including an activation function and different optimizers for classifying human activity from the real-time captured dataset;further, we compare the evaluated results with existing results. The proposed methods achieved 99.88% accuracy with excellent precision, recall, and F_measure values. Comparing the evaluated result with existing outcomes over the WISDM and UCI-HAR datasets. The new things in the article are a self-captured dataset of various aged male, female, and healthy volunteers to perform seven activities. Furthermore, this research uses Tensor Processing Units (TPU) available on Kaggle to improve classification accuracy while reducing error rates and speeding up execution. ©2025 The author(s).

关键词： Smartphones

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A New Resilient Configuration of Wound Rotor Resolver in Mechanical Fault Conditions

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IEEE Sensors Journal 2025年第11期25卷 19069-19076页

作者： Zare, Fateme Tootoonchian, Farid Nasiri-Gheidari, Zahra Isfahan University of Technology Department of Electrical and Computer Engineering Isfahan84156-83111 Iran Iran University of Science and Technology Department of Electrical Engineering Tehran16846-13114 Iran Sharif University of Technology Department of Electrical Engineering Tehran*** Iran

Resolvers are widely employed as position sensors to detect both rotational and linear displacement. Among the various types, wound rotor (WR) resolvers offer superior accuracy in absolute measurements, especially under mechanical fault conditions, but they present significant manufacturing challenges. This article introduces a novel winding arrangement designed to simplify the manufacturing process of WR resolvers and enhance the accuracy of the sensor under mechanical fault conditions. The performance of the resolver with this new winding configuration is analyzed, with a particular focus on its resilience to eccentricity faults. To validate the high fault tolerance of the proposed design, a prototype of the optimized configuration was developed and tested. The performance of the prototype under these conditions was comprehensively evaluated through experimental measurements. © 2025 IEEE.

关键词： Failure (mechanical)

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Resolution-aware beam scanning for joint detection and communication in ISAC systems

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science China(Information sciences) 2025年第5期68卷 250-266页

作者： Yiming XU Dongfang XU Zhanyuan XIE Zheng JIANG Shenghui SONG Derrick Wing Kwan NG Department of Electronic and Computer Engineering The Hong Kong University of Science and Technology China Telecom Research Institute School of Electrical Engineering and Telecommunications University of New South Wales

Beam scanning for joint detection and communication in integrated sensing and communication(ISAC) systems plays a critical role in continuous monitoring and rapid adaptation to dynamic environments. However, the design of sequential scanning beams for target detection with the required sensing resolution has not been tackled in the *** bridge this gap, this paper introduces a resolution-aware beam scanning design. In particular, the transmit information beamformer, the covariance matrix of the dedicated radar signal, and the receive beamformer are jointly optimized to maximize the average sum rate of the system while satisfying the sensing resolution and detection probability requirements.A block coordinate descent(BCD)-based optimization framework is developed to address the non-convex design problem. By exploiting successive convex approximation(SCA), S-procedure, and semidefinite relaxation(SDR), the proposed algorithm is guaranteed to converge to a stationary solution with polynomial time complexity. Simulation results show that the proposed design can efficiently handle the stringent detection requirement and outperform existing antenna-activation-based methods in the literature by exploiting the full degrees of freedom(DoFs) brought by all antennas.

关键词： integrated sensing and communication (ISAC) detection beam scanning resolution beamwidth

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AR-Light: Enabling Fast and Lightweight Multi-User Augmented Reality via Semantic Segmentation and Collaborative View Synchronization

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IEEE Transactions on computers 2025年第6期74卷 2073-2086页

作者： Wen, Yu Shah, Aamir Bader Cao, Ruizhi Zhang, Chen Chen, Jiefu Wu, Xuqing Xie, Chenhao Fu, Xin University of Houston Department of Electrical and Computer Engineering HoustonTX77204 United States Beihang University School of Computer Science and Engineering Beijing100191 China University of Houston Department of Information Science Technology HoustonTX77204 United States

Multi-user Augmented Reality (MuAR) allows multiple users to interact with shared virtual objects, facilitated by exchanging environment information. Current MuAR systems rely on 3D point clouds for real-world analysis, view synchronization, object rendering, and movement tracking. However, the complexity of 3D point clouds leads to significant processing delays, with approximately 80% of overhead in commercial frameworks. This hampers usability and degrades user experience. Our analysis reveals that maintaining the facing side of the real-world scene in a stable environment provides sufficient information for virtual object placement and rendering. To address this, we introduce a lightweight quadtree structure, representing 2D scenes through semantic segmentation and geometry, as an alternative to 3D point clouds. Additionally, we propose a novel correction method to handle potential shifts in virtual object placement during view synchronization among users. Combining all designs, we implement a fast and lightweight MuAR framework named AR-Light and test our framework on commercial AR devices. The evaluation results on real-world applications demonstrate that AR-Light can achieve high performance in various real-world scenes while maintaining a comparable virtual object placement accuracy. © 1968-2012 IEEE.

关键词： Semantic Segmentation

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Enhancing patient-independent detection of freezing of gait in Parkinson’s disease with deep adversarial network

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Neural Computing and Applications 2025年 1-21页

作者： Fahad, Md Shah Ranjan, Ashish Kumar, Gautam Department of Computer Science and Engineering Birla Institute of Technology Mesra Jharkhand Ranchi India Department of Computer Science and Engineering C. V. Raman Global University Odisha Bhubaneswar India Department of Computer Science and Engineering National Institute of Technology Delhi Delhi India

Freezing of gait (FoG) refers to sudden, relatively brief episodes of gait arrest in Parkinson’s disease, known to manifest in the advanced stages of the condition. Events of freezing are associated with tumbles, traumas, and psychological repercussions, significantly impacting the patient’s quality of life. The use of accelerometer data derived from sensors put on a patient’s body to detect FoG has previously been proposed using convolutional neural network (CNN)-based deep learning algorithms. Here, we combine a CNN + Long short-term Memory (LSTM)-attention model to detect FoG episodes—a first for the detection of FoG using the accelerometer data. CNN facilitates automatic feature extraction from the accelerometer data itself. The output from the CNN is fed to the LSTM network, which is known for capturing sequential information. Further, the attention mechanism introduces relative focus on individual sub-sequences during the training of the LSTM network. The proposed model is made patient independent using adversarial training. The proposed model achieved improvements of +7.60% (without adversarial training) and + 8.36% (with adversarial training) in the sensitivity values over state of the art. This is obtained with little or no compromise in specificity values. The corresponding improvements in accuracy values are +3.81 and +2.23%, respectively. These findings imply that the proposed method can detect FoG gaits satisfactorily and can be effective in achieving accurate monitoring and gait assistance for Parkinson’s disease patients during daily life and rehabilitation therapy. © The Author(s), under exclusive licence to Springer-Verlag London Ltd., part of Springer Nature 2025.

关键词： Accelerometers

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IoT-Based Women Safety Gadgets (WSG): Vision, Architecture, and Design Trends

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computers, Materials & Continua 2023年第7期76卷 1027-1045页

作者： Sharad Saxena Shailendra Mishra Mohammed Baljon Shamiksha Mishra Sunil Kumar Sharma Prakhar Goel Shubham Gupta Vinay Kishore Department of Computer Science and Engineering Thapar Institute of Engineering and TechnologyPatialaPunjab147001India Department of Computer Engineering College of Computer&Information ScienceMajmaah UniversityMajmaah11952Saudi Arabia Department of Computer Science and Engineering National Institute of TechnologyJamshedpur831001India

In recent years,the growth of female employees in the commercial market and industries has *** a result,some people think travelling to distant and isolated locations during odd hours generates new threats to women’s *** exponential increase in assaults and attacks on women,on the other hand,is posing a threat to women’s growth,development,and *** the time of the attack,it appears the women were immobilized and needed immediate *** self-defense isn’t sufficient against abuse;a new technological solution is desired and can be used as quickly as hitting a switch or *** proposed Women Safety Gadget(WSG)aims to design a wearable safety device model based on Internet-of-Things(IoT)and Cloud *** is designed in three layers,namely layer-1,having an android app;layer-2,with messaging and location tracking system;and layer-3,which updates information in the cloud *** can detect an unsafe condition by the pressure sensor of the finger on the artificial nail,consequently diffuses a pepper spray,and automatically notifies the saved closest contacts and police station through messaging and location *** has a response time of 1000 ms once the nail is pressed;the average time for pulse rate measure is 0.475 s,and diffusing the pepper spray is 0.2–0.5 *** average activation time is 2.079 s.

关键词： Perpetrator safety IoT women security GPS tracking GSM

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Error-Correcting Graph Codes 16

Error-Correcting Graph Codes

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16th Innovations in Theoretical computer science Conference, ITCS 2025

作者： Kopparty, Swastik Potukuchi, Aditya Sha, Harry Department of Mathematics Department of Computer Science University of Toronto Canada Department of Electrical Engineering and Computer Science York University Toronto Canada

ISBN: (纸本)9783959773614

In this paper, we construct Error-Correcting Graph Codes. An error-correcting graph code of distance δ is a family C of graphs, on a common vertex set of size n, such that if we start with any graph in C, we would have to modify the neighborhoods of at least δn vertices in order to obtain some other graph in C. This is a natural graph generalization of the standard Hamming distance error-correcting codes for binary strings. Yohananov and Yaakobi were the first to construct codes in this metric. We extend their work by showing 1. Combinatorial results determining the optimal rate vs distance trade-off nonconstructively. 2. Graph code analogues of Reed-Solomon codes and code concatenation, leading to positive distance codes for all rates and positive rate codes for all distances. 3. Graph code analogues of dual-BCH codes, yielding large codes with distance δ = 1 - o(1). This gives an explicit "graph code of Ramsey graphs". Several recent works, starting with the paper of Alon, Gujgiczer, Körner, Milojević, and Simonyi, have studied more general graph codes;where the symmetric difference between any two graphs in the code is required to have some desired property. Error-correcting graph codes are a particularly interesting instantiation of this concept. © Swastik Kopparty, Aditya Potukuchi, and Harry Sha.

关键词： Reed-Solomon codes

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