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Low-bias,high-photoresponsivity SnSe2 nanofilm with an Au split-ring array-based THz detector toward 6G communication

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Science China(Information Sciences) 2023年第6期66卷 311-312页

作者： Qi SONG Zhiwen ZHOU Yifei XU Min ZHANG Junbo YANG Huawei LIANG Tianwu WANG Peiguang YAN College of Physics and Optoelectronic Engineering Shenzhen University shandong key laboratory of Optical Communication Science and Technology School of Physics Science and Information TechnologyLiaocheng University College of Liberal Arts and Sciences National University of Defense Technology GBA Research Institute Aerospace Information Research Institute of Chinese Academy of Science

6G technology with the four characteristics of an intelligent endogenous,secure endogenous,multi-domain convergence,and integrated computing network,will help society toward an intelligent era [1]. The low power consumption and high photoresponsivity of 6G core devices,and particularly the improvement of detector performance,

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A Selective Attention Guided Initiative Semantic Cognition Algorithm for Service Robot

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International Journal of Automation and computing 2018年第5期15卷 559-569页

作者： Huan-Zhao Chen Guo-Hui Tian Guo-Liang Liu School of Control Science and Engineering University of Shandong

With the development of artificial intelligence and robotics, the study on service robot has made a significant progress in recent years. Service robot is required to perceive users and environment in unstructured domestic environment. based on the perception,service robot should be capable of understanding the situation and discover service task. So robot can assist humans for home service or health care more accurately and with initiative. Human can focus on the salient things from the mass observation information. Humans are capable of utilizing semantic knowledge to make some plans based on their understanding of the environment. Through intelligent space platform, we are trying to apply this process to service robot. A selective attention guided initiatively semantic cognition algorithm in intelligent space is proposed in this paper. It is specifically designed to provide robots with the cognition needed for performing service tasks. At first, an attention selection model is built based on saliency computing and key area. The area which is highly relevant to service task could be located and referred as focus of attention（FOA）. Second, a recognition algorithm for FOA is proposed based on a neural network. Some common objects and user behavior are recognized in this step. At last, a unified semantic knowledge base and corresponding reasoning engine is proposed using recognition result. Related experiments in a real life scenario demonstrated that our approach is able to mimic the recognition process in humans, make robots understand the environment and discover service task based on its own cognition. In this way, service robots can act smarter and achieve better service efficiency in their daily work.

关键词： Service robot cognition computing selective attention semantic knowledge base artificial neural network.

Research and Implementation of Cancer Gene Data Classification based on Deep Learning

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Journal of Software Engineering and Applications 2023年第6期16卷 155-169页

作者： Yuanzhou Wei Meiyan Gao Jun Xiao Chixu Liu Yuanhao Tian Ya He College of Engineering and computing Florida International University Miami USA College of intelligent Equipment Shandong University of Science and Technology Shandong China Steven J. Green School of International & Public Affairs Florida International University Miami USA School of Economics Capital University of Economics and Business Beijing China

Cancer has become a cause of concern in recent years. Cancer genomics is currently a key research direction in the fields of genetic biology and biomedicine. This paper analyzes 5 different types of cancer genes, such as breast, kidney, colon, lung and prostate through machine learning methods, with the goal of building a robust classification model to identify each type of cancer, which will allow us to identify each type of cancer early, thereby reducing mortality.

关键词： Cancer Healthcare SVM Random Forest Neural network Deep Learning

Tattoo Recognition based on Triplet GAN

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Tattoo Recognition Based on Triplet GAN

Granular classifier:Building traffic granules for encrypted traffic classification based on granular computing

第37届中国控制会议

作者： Cao Jiawang Zhu Yuan School of Automation China University of Geosciences Hubei key laboratory of Advanced Control and intelligent Automation for Complex Systems

An important feature of the deep learning algorithm is that the hidden layer of the neural network is more dependent on more computing resources and a larger amount of data. In this paper, we use Triplet GAN method to identify human body images with tattoos using fewer data sample labels. The model achieved better results（0.9462） than the only Triplet（0.8352） and only GAN（0.9178） in the MNIST dataset, it also achieved higher recognition accuracy（77-82%） under the premise of saving the amount of data, compared with the traditional machine learning algorithm（54-84%）. We provide a new idea for tattoo image recognition applications in embedded computing units.

关键词： Tattoo Recognition Triplet GAN Embedded computing Units

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Digital Communications and networks 2024年第5期10卷 1428-1438页

作者： Xuyang Jing Jingjing Zhao Zheng Yan Witold Pedrycz Xian Li State key laboratory on Integrated Services networks School of Cyber Engineering Xidian University Department of Electrical and Computer Engineering University of Alberta Institute for Future (IFF) Qingdao University

Accurate classification of encrypted traffic plays an important role in network ***,current methods confronts several problems:inability to characterize traffic that exhibits great dispersion,inability to classify traffic with multi-level features,and degradation due to limited training traffic *** address these problems,this paper proposes a traffic granularity-based cryptographic traffic classification method,called Granular Classifier(GC).In this paper,a novel Cardinality-based Constrained Fuzzy C-Means(CCFCM) clustering algorithm is proposed to address the problem caused by limited training traffic,considering the ratio of cardinality that must be linked between flows to achieve good traffic ***,an original representation format of traffic is presented based on granular computing,named Traffic Granules(TG),to accurately describe traffic structure by catching the dispersion of different traffic *** granule is a compact set of similar data with a refined boundary by excluding *** on TG,GC is constructed to perform traffic classification based on multi-level *** performance of the GC is evaluated based on real-world encrypted network traffic *** results show that the GC achieves outstanding performance for encrypted traffic classification with limited size of training traffic and keeps accurate classification in dynamic network conditions.

关键词： Encrypted traffic classification Semi-supervised clustering Granular computing Anomaly detection

Applications of Carbon Nanotubes in the Internet of Things Era

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Nano-Micro Letters 2021年第12期13卷 14-28页

作者： Jinbo Pang Alicja Bachmatiuk Feng Yang Hong Liu Weijia Zhou Mark HRümmeli Gianaurelio Cuniberti Collaborative Innovation Center of Technology and Equipment for Biological Diagnosis and Therapy Institute for Advanced Interdisciplinary Research(iAIR)Universities of ShandongUniversity of JinanShandongJinan 250022People’s Republic of China PORT Polish Center for Technology Development Łukasiewicz Research NetworkUl.Stabłowicka 14754‑066 WrocławPoland Centre of Polymer and Carbon Materials Polish Academy of SciencesM.Curie‐Sklodowskiej 3441‑819 ZabrzePoland Department of Chemistry Southern University of Science and TechnologyShenzhen 518055People’s Republic of China State key laboratory of Crystal Materials Center of Bio&Micro/Nano Functional MaterialsShandong University27 Shandanan RoadJinan 250100People’s Republic of China College of Energy Institute for Energy and Materials InnovationsSoochow UniversitySuzhouSoochow 215006People’s Republic of China key laboratory of Advanced Carbon Materials and Wearable Energy Technologies of Jiangsu Province Soochow UniversitySuzhou 215006People’s Republic of China Centre of Polymer and Carbon Materials Polish Academy of SciencesM.Curie Sklodowskiej 3441‑819 ZabrzePoland Institute for Complex Materials Leibniz Institute for Solid State and Materials Research Dresden(IFW Dresden)20 Helmholtz Strasse01069 DresdenGermany Institute of Environmental Technology VŠB-Technical University of Ostrava17.Listopadu 15Ostrava 70833Czech Republic Institute for Materials Science and Max Bergmann Center of Biomaterials Center for Advancing Electronics DresdenTechnische Universitat Dresden01069 DresdenGermany Dresden Center for Computational Materials Science Dresden Center for Intelligent Materials(GCL DCIM)Technische Universität Dresden01062 DresdenGermany

The post-Moore's era has boosted the progress in carbon nanotube-based ***,the 5 G communication and cloud computing stimulate the research in applications of carbon nanotubes in electronic *** this perspective,we deliver the readers with the latest trends in carbon nanotube research,including high-frequency transistors,biomedical sensors and actuators,brain–machine interfaces,and flexible logic devices and energy *** opportunities are given for calling on scientists and engineers into the emerging topics.

关键词： Carbon nanotubes Transistors Sensors Actuators Brain–machine interfaces Energy storage

Non-rigid 3D models retrieval based on hierarchical matching

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Computer Aided Drafting,Design and Manufacturing 2017年第1期27卷 39-47页

作者： Liu Yujie Li Wei Song Yang Gong Weiqing Li Zongmin Li Hua Department of Computer & Communication Engineering China University of Petroleum ChinaPetro (Karamay) Data Center Sinopec Exploration & Production Research Institute (PEPRIS) key Lab of intelligent Information Processing Institute of Computing TechnologyChinese Academy of Sciences

In 3D models retrieval, feature description and retrieval of non-rigid model face more complex problems due to the isometry transformation of itself. We introduce the hierarchical combination matching into the feature comparison, and build a map between the divided regions of two models, and then achieve accurate feature matching based on patch-by-patch, which successfully introduces the spatial information into feature matching. Verified by experiment, the 3D model retrieval method proposed in this paper based on hierarchical combination matching can make sure more accurate feature matching, so as to enhance the precision of retrieval.

关键词： non-rigid 3D model shape descriptor spatial distribution hierarchical combination matching

Spatial and Contextual Path network for Image Inpainting

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intelligent Automation & Soft computing 2024年第2期39卷 115-133页

作者： Dengyong Zhang Yuting Zhao Feng Li Arun Kumar Sangaiah Hunan provincial key laboratory of intelligent Processing of Big Data on Transportation Changsha University of Science and TechnologyChangsha410114China School of Computer and Communication Engineering Changsha University of Science and TechnologyChangsha410114China International Graduate Institute of AI National Yunlin University of Science and TechnologyYunlinTaiwan Department of Electrical and Computer Engineering Lebanese American UniversityByblosLebanon

Image inpainting is a kind of use known area of information technology to repair the loss or damage to the *** feature extraction is the core of image *** enough space for information and a larger receptive field is very important to realize high-precision image ***,in the process of feature extraction,it is difficult to meet the two requirements of obtaining sufficient spatial information and large receptive fields at the same *** order to obtain more spatial information and a larger receptive field at the same time,we put forward a kind of image restoration based on space path and context path *** the space path,we stack three convolution layers for 1/8 of the figure,the figure retained the rich spatial *** the context path,we use the global average pooling layer,where the accept field is the maximum of the backbone network,and the pooling module can provide global context information for the maximum accept *** order to better integrate the features extracted from the spatial and contextual paths,we study the fusion module of the two *** fusionmodule first path output of the space and context path,and then through themass normalization to balance the scale of the characteristics,finally the characteristics of the pool will be connected into a feature vector and calculate the weight *** of images in order to extract context information,we add attention to the context path refinement *** modules respectively from channel dimension and space dimension to weighted images,in order to obtain more effective *** show that our method is better than the existing technology in the quality and quantity of themethod,and further to expand our network to other inpainting networks,in order to achieve consistent performance improvements.

关键词： Image inpainting attention deep learning convolutional network

Design and Evaluation of an Exergame System of Knee with the Azure Kinect

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国际计算机前沿大会会议论文集 2021年第2期 331-342页

作者： Guangjun Wang Ming Cheng Xueshu Wang Yi Fan Xin Chen Liangliang Yao Hanyuan Zhang Zuchang Ma Hefei Institutes of Physical Science Chinese Academy of SciencesHefei 230031China University of Science and Technology of China Hefei 230026China The University key laboratory of intelligent Perception and computing of Anhui Province Anqing Normal UniversityAnqing 246013China Department of Sports Medicine and Arthroscopic Surgery The First Affiliated Hospital of Anhui Medical UniversityHefei 230022China

Timely and effective knee function evaluation and knee exercises promote the prevention and self-management of knee *** this paper,aKinectbased exergame system is proposed to assess and train the knee *** Kinect was used to capture and generate 3D models of the user and immerse them in an interactive virtual *** software included three functional modules:knee function evaluation,Knee exercises game,and Comprehensive *** stand,step,leg lift,and squat were selected for knee function evaluation and *** volunteers participated in the *** correlation coefficients(ICCs)were calculated to assess the reliability of kinematic measurements of knee angles during the *** ICC of these movements were stand(ICC=0.987),step(ICC=0.997),left leg lift(ICC=0.981),right leg lift(ICC=0.990),stand(ICC=0.998).The results show that the test-retest reliability is *** means that the motion capture data is effective and the data obtained by Kinect is stable.

关键词： Azure Kinect Exergame system Knee function evaluation