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Quantum essence of particle superfluidity

Nano Research 2022年第6期15卷 5230-5234页

作者： Bo Song Lei Jiang School of Optical-Electrical Computer Engineering University of Shanghai for Science and TechnologyShanghai 200093China Key Laboratory of Bio-inspired Materials and Interfacial Science Technical Institute of Physics and ChemistryChinese Academy of SciencesBeijing 100190China School of Future Technology University of Chinese Academy of SciencesBeijing 100049China

Life systems show an ultralow energy consumption in their high-efficiency bio-activities,implying a high-flux transport of ions and molecules with an ultralow resistivity.A collective motion(CM)of these particles is necessary for this kind of behaviors,different from the traditional Newtonian *** CM is an ordered particle state,resulting from the balance between attraction and repulsion of the particles,in which the attraction is a necessary *** ultralow resistivity of electronic or atomic fluid at low temperature is already described phenomenologically by introducing the interparticle ***,we try to establish a phenomenological expression for the quantum state of ion or molecule CM at ambient temperature,by also considering the attraction of *** studies suggest that the Bose-Einstein condensate potentially exists widely.

关键词： ultralow resistivity flow collective motion ions and molecules Ginzburg-Landau equation

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Discounted Iterative Adaptive Critic Designs With Novel Stability Analysis for Tracking Control

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IEEE/CAA Journal of Automatica Sinica 2022年第7期9卷 1262-1272页

作者： Mingming Ha Ding Wang Derong Liu School of Automation and Electrical Engineering University of Science and Technology BeijingBeijing 100083China Faculty of Information Technology the Beijing Key Laboratory of Computational Intelligence and Intelligent Systemthe Beijing Laboratory of Smart Environmental Protectionand the Beijing Institute of Artificial IntelligenceBeijing University of TechnologyBeijing 100124China Department of Electrical and Computer Engineering University of Illinois at ChicagoChicago IL 60607 USA IEEE

The core task of tracking control is to make the controlled plant track a desired *** traditional performance index used in previous studies cannot eliminate completely the tracking error as the number of time steps *** this paper,a new cost function is introduced to develop the value-iteration-based adaptive critic framework to solve the tracking control *** the regulator problem,the iterative value function of tracking control problem cannot be regarded as a Lyapunov function.A novel stability analysis method is developed to guarantee that the tracking error converges to *** discounted iterative scheme under the new cost function for the special case of linear systems is ***,the tracking performance of the present scheme is demonstrated by numerical results and compared with those of the traditional approaches.

关键词： Adaptive critic design adaptive dynamic programming(ADP) approximate dynamic programming discrete-time nonlinear systems reinforcement learning stability analysis tracking control value iteration(VI)

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DiffSenseNet: Integrating Hierarchical Features and Angular Diffusion for Remote Sensing Object Detection 22

DiffSenseNet: Integrating Hierarchical Features and Angular ...

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

作者： Pei, Songwen Ma, Hongli Qiu, Xinyun Huang, Libo School of Optical-Electrical and Computer Engineering University of Shanghai for Science and Technology Shanghai China Key Laboratory of Fire Detection and Early Warning Technology of Shanghai Emergency Management Bureau Shanghai China National University of Defense Technology Changsha China

ISBN: (纸本)9798331509712

Object detection in remote sensing images is a significant and challenging task. The detection performance is difficult to further improve due to the wide variation in object scale and unpredictable orientations. However, traditional methods typically rely on Region Proposal Networks (RPN) with fixed anchor boxes, which makes it difficult to locate objects of multi-scale and multi-orientation. In this paper, we propose DiffSenseNet, a detection network that integrates Hierarchical Feature Fusion (HFF) and Angular Diffusion Augmentation (ADA). The HFF architecture integrates both bottom-up and top-down pathways to effectively merge features at different scales. The ADA strategy introduces directional information into noisy boxes by adding Gaussian noise to the ground truth boxes. On the DOTA and HRSC2016 datasets, DiffSenseNet achieves the accuracy of 75.89% and 86.24% mAP, respectively. Comprehensive experiments show that DiffSenseNet achieves relatively superior performance compared to previous state-of-the-art jobs. © 2024 IEEE.

关键词： Object tracking

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Depth Estimation of Multi-Modal Scene Based on Multi-Scale Modulation

Depth Estimation of Multi-Modal Scene Based on Multi-Scale M...

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IEEE International Conference on Image Processing

作者： Anjie Wang Zhijun Fang Xiaoyan Jiang Yongbin Gao Gaofeng Cao Siwei Ma School of Electronic and Computer Engineering Peking University Peng Cheng Laboratory School of Computer Science and Technology Donghua University School of Electronic and Electrical Engineering Shanghai University of Engineering Science School of Computer Science Peking University

As multimodal information is complementary, effectively utilizing scene multimodal information has become an increasingly important research topic for many scholars. This paper proposes a novel multi-scale global learning strategy that utilizes both echo and visual modal data as inputs to estimate scene depth. The framework involves constructing a multi-scale feature extraction method using pyramid pooling modules to aggregate contextual information from different regions and improve global information acquisition ability. Furthermore, a recurrent multi-scale feature modulation module is introduced to generate more semantic and accurate spatial representations in each iteration update process. Additionally, a multi-scale fusion method is constructed for the fusion of echo and visual modalities. The proposed method's superior performance is demonstrated through sufficient experiments conducted on the Replica dataset.

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An Enhanced Haar Cascade Face Detection Schema for Gender Recognition

An Enhanced Haar Cascade Face Detection Schema for Gender Re...

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2023 International Conference on Smart Computing and Application, ICSCA 2023

作者： Sridhar, Psvs Chithaluru, Premkumar Kumar, Sunil Cheikhrouhou, Omar Hamam, Habib Computer Science and Engineering Andhra Pradesh Vaddeswaram India Department of Computer Science and Engineering Hyderabad India School of Computer Science University of Petroleum and Energy Studies Dehradun India National School of Engineers of Sfax University of Sfax Ces Laboratory Sfax3038 Tunisia University de Moncton Faculty of Engineering MonctonNBE1A3E9 Canada International Institute of Technology and Management Commune d'Akanda Libreville Gabon School of Electrical Engineering University of Johannesburg Department of Electrical and Electronic Engineering Science Johannesburg2006 South Africa Spectrum of Knowledge Production and Skills Development Sfax Tunisia

ISBN: (纸本)9798350347050

Gender identification software is becoming increasingly popular in the age of machine-to-machine interactions, as the need for person-aligned, effective, and ethical systems become more apparent. In this age of machine-to-machine interactions, automated gender identification software is becoming more popular. The bulk of the systems for gender identification that were examined used either textual or audiovisual data as input to determine their gender. Many different approaches to automatically detect gender based on traits gathered from people's bodies and/or behaviors have been suggested, and there are simply too many to include here. The accuracy of automated gender identification, on the other hand, has always been a topic of worry or a source of criticism. Initial face identification is accomplished by the use of the Haar Cascade face detection method, which is based on the Viola-J ones face recognition algorithm. Facial characteristics such as the eyes, mouth, and nose are then identified. Second, using the Viola-Jones face detection algorithm, the faces and facial characteristics such as the eyes, mouth, and nose are recognized, and the results are shown. In order to increase the accuracy of gender identification, adaptive filters are employed to reduce the amount of noise present before the detection process is carried out. The facial qualities that have been gathered are utilized as input or test data for the neural network, which is subsequently trained on these characteristics. It is intended that the neural network acquires the features of the genders and then functions as a classifier when it comes to detecting them. Instead of saying it another way, a neural network known as Keras is used for feature extraction and gender identification, which is free and open-source software. © 2023 IEEE.

关键词： Feature extraction

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Gait Recognition Based on Modified OVR-CSP Fusion Feature and LSTM 7

Gait Recognition Based on Modified OVR-CSP Fusion Feature an...

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7th International Conference on Advanced Algorithms and Control engineering, ICAACE 2024

作者： Dong, Xiaoyu Gao, Cuiyun Lu, Zhonghai Zhang, Wanli Zhao, Yang Jiang, Xinyu Anhui Jianzhu University Power Quality Analysis And Load Detection Technology Laboratory Hefei China Anhui Jianzhu University Hefei China Power Quality School Of Electrical Engineering And Computer Science Kth Royal Institute Of Technology Stockholm Sweden

ISBN: (纸本)9798350361445

This paper proposes a gait recognition method based on the modified OVR-CSP fusion feature of plantar pressure and Long Short-Term Memory classification (referred to as the OVR-CSP-LSTM model). 10 subjects conducted 4 type of gait experiments including normal speed walking, fast walking, slow walking, imitating stroke gait walking in this paper. Transfer the commonly used Common Spatial Pattern (CSP) feature extraction method for EEG to plantar pressure signals, and splice the OVR-CSP features of 2-class, 3-class and 4-class, adopting Long Short Term Memory Network (LSTM) for classification. In this paper, the Intra-patient mode and Inter-patient mode of 10 people are modeled and compared respectively, and the recognition effects under different sensor number and different position sensors' combination are also studied. The experimental results show that the proposed model has good performance for both modes. The method proposed in this article is expected to be applied to multi-sensor signal processing and classification with spatial characteristics. © 2024 IEEE.

关键词： Long short-term memory

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Achieving Secure Communication Assisted by Physical Layer Encryption 23

Achieving Secure Communication Assisted by Physical Layer En...

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23rd IEEE International Conference on Communication Technology, ICCT 2023

作者： Chen, Zeqing Chen, Rui Zhou, Huan China Three Gorges University Hubei Key Laboratory of Intelligent Vision Based Monitoring for Hydroelectric Engineering Yichang443002 China College of Computer and Information Technology China Three Gorges University Hubei Yichang443002 China School of Computer Science Northwestern Polytechnical University Xi'an710129 China

ISBN: (纸本)9798350325959

Frequency hopping (FH) technique has been extensively used for high security communication because of its strong anti-jamming ability and good confidentiality. However, with the continuous advancement of electronic attacks, plenty of energy limited devices in the Internet of Things (IoT) are experiencing a sharp increase in interference, which poses serious challenges to the current FH sequence generation techniques. In this paper, we propose a novel FH sequence generation scheme by exploiting an ultra-lightweight block cipher (PRESENT), which strikes an effective balance between security and efficiency. Specifically, the values related to channel gain are mapped to corresponding FH codes through the output of lightweight block cipher algorithm. Moreover, the security of the proposed scheme has been analyzed. It turns out that the FH sequences generated by PRESENT algorithm outperform the FH sequences generated by a bit-slice lightweight block cipher suitable for multiple platforms (RECTANGLE) and a lightweight block cipher (LBlock) in terms of uniformity, randomness and complexity. © 2023 IEEE.

关键词： complexity FH sequence lightweight block cipher algorithm randomness security uniformity

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Output Constrained Adaptive Controller Design for Nonlinear Saturation Systems

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IEEE/CAA Journal of Automatica Sinica 2021年第2期8卷 441-454页

作者： Yongliang Yang Zhijie Liu Qing Li Donald C.Wunsch the Key Laboratory of Knowledge Automation for Industrial Processes of Ministry of Education School of Automation and Electrical EngineeringUniversity of Science and Technology BeijingBeijing 100083China the Department of Electrical and Computer Engineering Missouri University of Science and TechnologyRollaMO 65409 USA

This paper considers the adaptive neuro-fuzzy control scheme to solve the output tracking problem for a class of strict-feedback nonlinear *** asymmetric output constraints and input saturation are *** asymmetric barrier Lyapunov function with time-varying prescribed performance is presented to tackle the output-tracking error constraints.A high-gain observer is employed to relax the requirement of the Lipschitz continuity about the nonlinear *** avoid the"explosion of complexity",the dynamic surface control(DSC)technique is employed to filter the virtual control signal of each *** deal with the actuator saturation,an additional auxiliary dynamical system is *** is theoretically investigated that the parameter estimation and output tracking error are semi-global uniformly ultimately *** simulation examples are conducted to verify the presented adaptive fuzzy controller design.

关键词： Asymmetric barrier Lyapunov function input saturation Nussbaum function time-varying prescribed performance

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LateBA: Latent Backdoor Attack on Deep Bug Search via Infrequent Execution Codes 15

LateBA: Latent Backdoor Attack on Deep Bug Search via Infreq...

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15th Asia-Pacific Symposium on Internetware, Internetware 2024

作者： Yi, Xiaoyu Li, Gaolei Huang, Wenkai Lin, Xi Li, Jianhua Liu, Yuchen The School of Electronic Information and Electrical Engineering Shanghai Jiao Tong University Shanghai Key Laboratory of Integrated Administration Technologies for Information Security Shanghai Shanghai China The Department of Computer Science North Carolina State University Raleigh United States

ISBN: (纸本)9798400707056

Backdoor attacks can mislead deep bug search models by exploring model-sensitive assembly code, which can change alerts to benign results and cause buggy binaries to enter production environments. But assembly instructions have strict constraints and dependencies, and these additional model-sensitive assembly codes destroy semantics and syntax and are easily detected by dynamic analysis or context-based detection. To escape from the dynamic analysis-based detection, we propose a novel latent backdoor attack (LateBA) scheme based on the locality principle of program execution, which only poisons a few of infrequent execution codes, minimizing the effects on the original code logic. In LateBA, a progressive seed mutating strategy is designated to change the American Fuzzy Lop (AFL)-based path search tool to pay more attention to infrequent execution codes. With this strategy, the optimal range to positions in the whole program is determined. Subsequently, triggers are target model-sensitive assembly instructions, and try to minimize the variables that have been called in the context instructions in the trigger. Finally, we employ code semantic feature comparisons to select precise trigger injection positions within these ranges. The selection criteria of the trigger injection position is whether the corresponding code segments in this position have a data dependency relationship with other code segments. We evaluate the performance of LateBA over 7 deep bug search tasks. The results demonstrate the attack success rate of the proposed LateBA is considerable and competitive against the baselines. © 2024 Owner/Author.

关键词： Semantics

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Defect Recognition based on Radon Transform in Pentacene organic thin-film Archimedean interdigitated spirals transistor

Defect Recognition based on Radon Transform in Pentacene org...

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2023 International Conference on Clean electrical Power, ICCEP 2023

作者： Sciuto, Grazia Lo Linde, Sivan Shikler, Rafi Kowol, Pawel Coco, Salvo Capizzi, Giacomo Silesian University of Technology Department of Mechatronics Gliwice Poland Ben-Gurion University of the Negev School of Electrical and Computer Engineering Optoelectronic Organic Semiconductor Devices Laboratory Department of Electrical and Computer Engineering Beer-Sheva Israel Ben-Gurion University of the Negev Ilse Katz Institute for Nanoscale Science and Technology Beer-Sheva Israel University of Catania Department of Electrical Electronics and Informatics Engineering Catania Italy

ISBN: (纸本)9798350348378

In this paper the problem of automatic defects detection in thin film transistor is considered in order to increase the efficiency of electronic devices. An effective approach based on defect pattern recognition in organic transistor is developed using the Radon transform. The adopted design and technology in Pentacene organic thin-film transistor exhibits two interdigitated Archimedean spirals pattern. In the conducted experiments, the images acquisition is performed with a microscope camera to capture the various defects of surface morphology on the top of the examined transistors. The defects detection is obtained by using the Radon transform on each channel (R,G,B) of these images. © 2023 IEEE.

关键词： Thin film transistors

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