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Context-Aware Augmented Reality Using Human-Computer Interaction Models

Journal of Control and Decision 2024年第1期11卷 1-14页

作者： Ying Sun Qiongqiong Guo Shumei Zhao Karthik Chandran G.Fathima Henan intelligent education and intelligent technology application engineering technology research center Zhengzhou Railway Vocational and technical collegeZhengzhouHenanPeople’s Republic of China Henan Provincial Research Center of Wisdom Education and Intelligent Technology Application Engineering Technology Zhengzhou Railway Vocational and technical collegeZhengzhouHenanPeople’s Republic of China Department of Mechatronics Engineering Jyothi Engineering CollegeKeralaIndia CSE Adhiyamaan College of Engineering HosurTamilnaduIndia

Augmented Reality is a technique that allows users to overlap digital information with their physical *** Augmented Reality(AR)displays have an exceptional characteristic from the Human–Computer Interaction(HCI)*** to its increasing popularity and application in diverse domains,increasing user-friendliness and AR usage are ***-aware is one approach since an AR application can adapt to the user,environment,needs and enhance ergonomic principles and *** paper proposes the intelligent Contextaware Augmented Reality Model(ICAARM)for Human–Computer Interaction *** study explores and reduces interaction uncertainty by semantically modeling user-specific interaction with context,allowing personalised *** information is captured from an AR device to understand user interactions and *** depictions carry semantics to Augmented Reality applications about the user’s intention to interact with a specific device ***,this study describes personalised gesture interaction in VR/AR applications for immersive/intelligent environments.

关键词： Augmented Reality Context-aware Human–Computer Interaction

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Partial Attention-Based Direction-Aware Vehicle Re-identification 18th

Partial Attention-Based Direction-Aware Vehicle Re-identific...

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18th International Conference on Computer Science and Education, ICCSE 2023

作者： Zhou, Yujie Yuan, Caihong Su, Chenshuang Zou, Mingdong Zhu, Xiaoke Liang, Wenjuan School of Computer and Information Engineering Henan University Henan Engineering Research Center of Intelligent Technology and Application Henan Province Spatial Information Processing Engineering Technology Research Center Kaifeng China

ISBN: (纸本)9789819707294

With the rapid development of urban transportation, vehicle re-identification has become a focal point in traffic management and vehicle tracking problems. In order to address the problem of small inter-class similarity among vehicles, previous studies utilize vehicle parsing models to extract local features. Therefore, we introduce the Squeeze-and-Excitation attention mechanism to extract important discriminative information from these local features. Furthermore, we propose a local co-occurrence attention mechanism to represent the proportion of common parts feature matching. To address the issue of large intra-class differences caused by vehicle direction change, we propose a lightweight and effective direction weighted fusion strategy. Experiments on two large datasets show that the proposed algorithm performs competitively. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.

关键词： Urban transportation

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A Survey of Privacy Preserving Methods based on Differential Privacy for Medical Data 7

A Survey of Privacy Preserving Methods based on Differential...

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7th World Conference on Computing and Communication Technologies, WCCCT 2024

作者： Yan, Haicao Yin, Menghan Yan, Chaokun Liang, Wenjuan Henan University School of Computer and Information Engineering Kaifeng China Henan University Henan Engineering Research Center of Intelligent Technology and Application Kaifeng China

ISBN: (纸本)9798350372328

Using deep learning and federated learning in the medical domain has facilitated convenience in diagnosing and treating patients. However, the current privacy leakage problem has made patients more cautious about personal privacy security. Privacy security has become an urgent issue. Differential privacy is a cryptography technique that makes it impossible for attackers to identify personal data by adding noise to the training process. In this work, we first provide a complete overview of differential privacy technologies. Then, we will review existing differential privacy works in the medical field. Finally, we analyze the existing problems of differential privacy and propose possible avenues for further research. © 2024 IEEE.

关键词： Deep learning

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Multimodal Interaction Fusion Network for Cloth-Changing Person Re-Identification 22

Multimodal Interaction Fusion Network for Cloth-Changing Per...

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22nd IEEE International Symposium on Parallel and Distributed Processing with applications, ISPA 2024

作者： Yuan, Caihong Xu, Yuanchen Guan, Zhijie Chen, Xiaopan Zhu, Xiaoke Liang, Wenjuan Henan University School of Computer and Information Engineering Kaifeng China Henan Engineering Research Center of Intelligent Technology and Application Henan Province Spatial Information Processing Engineering Technology Research Center Kaifeng China

ISBN: (纸本)9798331509712

Cloth-Changing Person Re-Identification (CC-ReID) refers to the technology that can identify the same individual in surveillance scenarios, even after changing their clothes. The core of CC-ReID is to exact cloth-irrelevant identity features. Existing methods usually extract them from body contours, skeletons, human faces, etc. However, information extracted from a single modality is often insufficient. Therefore, we propose a novel Multimodal Interaction Fusion (MIF) framework that could facilitate the deep integration of multimodal information, thereby enhancing the generalization ability of CC-ReID. Specifically, we design a triple-interaction collaborative module that strategically integrates features captured from body posture, original RGB images, and clothes-erased images, maximizing the advantages of each modality and overcoming their limitations. Additionally, we develop an Adapt-Blend Pool (ABP) module that effectively improves pooling methods to enhance the model's ability to process images with complex backgrounds and varied features. Following training, our framework effectively harnesses a variety of modal inputs to capture identity representations independent of clothing accurately. Extensive experimental results on PRCC, LTCC, and VC-Clothes datasets demonstrate the effectiveness of the proposed method. © 2024 IEEE.

关键词： Image enhancement

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Optimization Design of Axial Flux Permanent Magnet Synchronous Motor Based on Multi-Objective Genetic Algorithm

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Progress in Electromagnetics research C 2025年 155卷 85-93页

作者： Liu, Huijun College of Mechanical and Electrical Engineering Zhumadian Vocational and Technical College Zhumadian463000 China Henan Intelligent Sorting Technology Application Engineering Research Center Zhumadian Vocational and Technical College Zhumadian463000 China

As a new type of motor, axial flux permanent magnet synchronous motor has the advantages of compact structure and high power density. It shows good application prospects in new energy vehicles, unmanned aerial vehicles, and other fields. However, axial flux permanent magnet synchronous motor needs to consider the balance of multiple objectives during the design process, which makes its optimal design a complex multi-objective optimization problem. Therefore, the study proposes a motor optimization method based on multi-objective genetic algorithm. The method optimizes the rotor and stator parameters of the motor by establishing an analytical model of the motor’s magnetic field and combining it with a multi-objective genetic algorithm. The experimental results indicated that the optimized motor with multi-objective genetic algorithm reached 92% in terms of efficiency, 25% in terms of power density; energy consumption was reduced to 2.5 kWh; failure rate was reduced to 1.5%; and noise level was reduced to 65 dB. In addition, the multi-objective genetic algorithm significantly improved the control stability index, which increased to 98%, indicating a more stable motor response under varying loads. The disturbance rejection capability was enhanced to 99%, demonstrating strong resistance to external noise and parameter fluctuations. Furthermore, the system response frequency reached 100 Hz, reflecting a faster dynamic response to input variations. It is indicated that the optimization method based on multi-objective genetic algorithm can effectively enhance the comprehensive performance of axial flux permanent magnet synchronous motor and significantly improve its competitiveness in high power density and high efficiency applications. © 2025, Electromagnetics Academy. All rights reserved.

关键词： Multiobjective optimization

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A Helmet Detection Algorithm Based on Transformers with Deformable Attention Module

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Chinese Journal of Electronics 2025年第1期34卷 229-241页

作者： Songle Chen Hongbo Sun Yuxin Wu Lei Shang Xiukai Ruan Engineering Research Center of Post Big Data Technology and Application of Jiangsu Province Nanjing University of Posts and Telecommunications State Key Lab for Novel Software Technology Nanjing University Institute of Intelligent Locks Wenzhou University

Wearing a helmet is one of the effective measures to protect workers' safety. To address the challenges of severe occlusion, multi-scale, and small target issues in helmet detection, this paper proposes a helmet detection algorithm based on deformable attention transformers. The main contributions of this paper are as follows. A compact end-to-end network architecture for safety helmet detection based on transformers is proposed. It cancels the computationally intensive transformer encoder module in the existing detection transformer(DETR) and uses the transformer decoder module directly on the output of feature extraction for query decoding, which effectively improves the efficiency of helmet detection. A novel feature extraction network named Swin transformer with deformable attention module(DSwin transformer) is proposed. By sparse cross-window attention, it enhances the contextual awareness of multi-scale features extracted by Swin transformer, and keeps high computational efficiency simultaneously. The proposed method generates the query reference points and query embeddings based on the joint prediction probabilities, and selects an appropriate number of decoding feature maps and sparse sampling points for query decoding, which further enhance the inference capability and processing speed. On the benchmark safety-helmet-wearing-dataset(SHWD), the proposed method achieves the average detection accuracy mAP@0.5 of 95.4% with 133.35G floating-point operations per second(FLOPs) and 20 frames per second(FPS), the state-of-the-art method for safety helmet detection.

关键词： Head Accuracy Network architecture Benchmark testing Transformers Feature extraction Safety Decoding Computational efficiency Detection algorithms

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Self-assembled Fe_(3)O_(4)nanoparticles on V2C MXene for enhanced supercapacitor and microwave absorption applications

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Journal of Advanced Ceramics 2025年第3期14卷 183-196页

作者： Qixun Xia Ranlu Miao Wen Guo Min Xia Libo Wang Qianku Hu Aiguo Zhou School of Materials Science and Engineering Henan Polytechnic UniversityJiaozuo 454003China Henan Province Expressway Efficient Energy Storage Technology and Application Engineering Research Center Zhengzhou 450121China Department of Macromolecular Science Fudan UniversityShanghai 200438China Henan Radio Requlation Information System Backup Center Zhengzhou 450008China

Rapid advancements in modern electronic devices necessitate the development of materials that can simultaneously provide efficient energy storage and effective microwave ***,a novel composite material was prepared via the self-assembly of Fe_(3)O_(4)nanoparticles on the surface of V2C *** composite exhibited characteristics suitable for supercapacitor and electromagnetic absorption applications,highlighting the synergistic relationship between energy storage and electromagnetic wave absorption *** electrochemical tests revealed that the specific capacity of the V_(2)C MXene/Fe_(3)O_(4)composite(42.67 mAh·g^(−1))considerably improved compared with those of the raw *** prepared V2C MXene/Fe_(3)O_(4)//V_(2)C MXene/Fe_(3)O_(4)symmetric supercapacitor(SSC)demonstrated an energy density of 44.8 Wh·L^(−1),a power density of 959.4 W·L−1,and a capacity retention of 80.14%after 8000 ***,the V2C MXene/Fe_(3)O_(4)composite exhibited an optimal reflection loss(RL)of−42.4 dB in the Ku band,with an effective absorption bandwidth of 1.9 GHz(14.6–16.5 GHz).This composite material has broad application potential in modern electronic devices owing to its high energy storage capacity and effective electromagnetic wave *** dual functionality improves device performance and offers a compact solution for energy storage and effective microwave absorption.

关键词： MXenes Fe_(3)O_(4) two-dimensional(2D)materials supercapacitors microwave absorption

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Multi-Motor Synchronous Control Strategy Based on Fuzzy Internal Model PID and Virtual Spindle Synchronous Control

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Progress in Electromagnetics research C 2025年 152卷 187-195页

作者： Yan, Wei Li, Shasha College of Mechanical and Electronic Engineering Huanghe Jiaotong University Jiaozuo454950 China Henan Engineering Technology Research Center on Intelligent Manufacturing Technology and Equipment Jiaozuo454950 China

To achieve high-precision synchronous control of multiple motors, this study utilizes a permanent magnet synchronous motor as a case study. It adopts a fuzzy internal model proportional-integral-derivative algorithm with integral separation for single-motor control. On this basis, the virtual spindle synchronization strategy of multi-motor synchronous control and fuzzy control algorithm are further introduced to adjust the feedback torque compensation coefficient dynamically, optimizing the virtual spindle synchronization strategy. The results showed that in single-motor control, the dual closed-loop fuzzy proportional-integral control algorithm achieved a torque fluctuation error of 4 N · m when the load torque changed significantly. The fuzzy internal model proportional-integral-derivative control algorithm with integral separation had a relatively smooth adjustment process, and the maximum torque fluctuation did not exceed 1 N · m. In multi-motor synchronous control, the improved virtual spindle synchronous control strategy had a synchronization error of only 14.2 r/min between motor 1 and motor 2, as well as between motor 1 and motor 3. The single-motor and multi-motor synchronous control strategies used in the study have high control accuracy and response efficiency, which is conducive to improving the synchronization accuracy and coordination between motors. The improved strategy provides a reliable control scheme for industrial automation systems. © 2025, Electromagnetics Academy. All rights reserved.

关键词： Permanent magnets

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Graph Neural Network-Based User Preference Model for Social Network Access Control

Informatica (Slovenia)

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Informatica (Slovenia) 2025年第16期49卷 21-36页

作者： Zhang, Yuan Xuchang Vocational Technical College Xuchang461000 China Henan Province Data Intelligence and Security Application Engineering Technology Research Center Xuchang461000 China

The popularity and deepening of social networks have increased the risk of personal information leakage for users. To enhance the security of social networks, this study constructed an access control model based on the preferences of social network users. This model utilizes graph neural networks to generate access control strategies based on user preferences, and introduces a multi-layer attention mechanism to optimize the graph neural network. To better capture user preference information, the study sets the learning rate to 0.0001. The experimental results demonstrated that in the Twitter dataset, the accuracy of the proposed model reached 95.7% and the F1 score reached 96.2%, which were significantly higher than those of other models. These results indicated that the model could more accurately classify access control in social networks and reduce false positives. The area under the receiver operation characteristic curve of the proposed model was 0.982, which was higher than other models. The decision time was 13.77 seconds, significantly lower than other models. This indicated that the model could more effectively distinguish different types of user access requests and provide more reliable guarantees for secure access to social networks. The user's preferred social network access control model based on graph neural networks has superior performance, effectively ensuring the information security of social network users and laying the foundation for further development of access control technology. © 2025 Slovene Society Informatika. All rights reserved.

关键词： Access control models

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Optimizing Solar-Energy Harvesting Communication Systems: An energy allocation scheme for maximizing data transmission 4

Optimizing Solar-Energy Harvesting Communication Systems: An...

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4th International Conference on Internet of Things and Smart City, IoTSC 2024

作者： Li, Shuai Yao, Zhonghao Chen, Shengbo Schoool of Software Henan University Henan Kaifeng China School of Computer Science & Technology Beijing Institute of Technology Beijing China School of Computer and Information Engineering Henan University Henan Kaifeng China Henan Engineering Research Center of Intelligent Technology and Application Henan University Henan Kaifeng China

ISBN: (纸本)9781510681767

The solar energy harvesting communication system is the basic support layer that is associated with the Internet of Things (IoT). However, the inherent stochasticity of solar energy brings about extensive research on energy allocation in the system. In this paper, we propose an energy allocation algorithm for maximizing the data transfer (MDT) of a solar energy harvesting communication system while jointly considering the practical constraints of battery capacity and link capacity restrictions. We can solve it through the convex optimization problem, but the solution is extremely complicated. This complexity is the result of the coupling of energy allocation problems caused by restricted battery capacity and link capacity. To simplify the solution process, we propose a decoupled energy allocation (DEA) algorithm. Simulation experiments are conducted through real energy harvesting data sets, and the results show that DEA outperforms the other two heuristic schemes. © 2024 SPIE.

关键词： Convex optimization

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