检索结果-南通市图书馆

维普期刊数据库

Cost-Efficient Medium Frequency Propagation Research with Software Defined Radio

在线全文

学校读者我要写书评

暂无评论

World Journal of engineering and Technology 2024年第1期12卷 158-169页

作者： Casey M. Hess Sohail Anwar Division of Business Engineering and Information Sciences and Technology Department of Electromechanical Engineering Technology Pennsylvania State University Altoona Campus Altoona Pennsylvania USA Division of Business Engineering and Information Sciences and Technology Department of Engineering Pennsylvania State University Altoona Campus Altoona Pennsylvania USA

Medium Frequency radio holds significance in modern society as it supports broadcasting and individual communications in the public, government, and military sectors. Enhancing the availability and quality of these communications is only possible by enhancing the understanding of medium frequency propagation. While traditional methods of radio wave propagation research can have a high material demand and cost, software defined radio presents itself as a versatile and low-cost platform for medium frequency signal reception and data acquisition. This paper details a research effort that utilizes software defined radio to help characterize medium frequency signal strength in relation to ionospheric and solar weather propagation determinants. Signal strength data from seven medium frequency stations of unique transmission locations and varying transmission powers were retrieved in 24-hour segments via a receiving loop antenna, Airspy HF+ Discovery software defined radio, and SDR Sharp software interface network. Retrieved data sets were visualized and analyzed in MATLAB for the identification of signal strength trends, which were subsequently compared to historical ionospheric and space weather indices in pursuit of a quantifiable correlation between such indices and medium frequency signal strengths. The results of the investigation prove that software defined radio, when used in conjunction with a receiving antenna and data analysis program, provides a versatile mechanism for cost-efficient propagation research.

关键词： Ionosphere Space Weather Airspy SDR SDR Sharp MATLAB Analysis

Next generation multiple access for IMT towards 2030 and beyond

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

Science China(information Sciences) 2024年第6期67卷 448-450页

作者： Zhiguo DING Robert SCHOBER Pingzhi FAN H.Vincent POOR department of Computer and information engineering Khalifa University department of Electrical and Electronic engineering University of Manchester Institute for Digital Communications Friedrich Alexander-University Erlangen-Nurnberg (FAU) CSNMT International Cooperation Research Center (MoST) Southwest Jiaotong University department of Electrical and Computer engineering Princeton University

Multiple access techniques are fundamental to the design of wireless communication systems,since many crucial components of such systems depend on the choice of the multiple access technique[1].For example,the use of ...

关键词：

A Hybrid Cybersecurity Algorithm for Digital Image Transmission over Advanced Communication Channel Models

在线全文

同方期刊数据库

学校读者我要写书评

暂无评论

Computers, Materials & Continua 2024年第4期79卷 201-241页

作者： Naglaa F.Soliman Fatma E.Fadl-Allah Walid El-Shafai Mahmoud I.Aly Maali Alabdulhafith Fathi E.Abd El-Samie department of information Technology College of Computer and Information SciencesPrincess Nourah bint Abdulrahman UniversityP.O.Box 84428Riyadh11671Saudi Arabia department of Electronics and Communications Faculty of EngineeringZagazig UniversityZagazig44519Egypt Security engineering Lab Computer Science DepartmentPrince Sultan UniversityRiyadh11586Saudi Arabia department of Electronics and Electrical Communications engineering Faculty of Electronic EngineeringMenoufia UniversityMenouf32952Egypt

The efficient transmission of images,which plays a large role inwireless communication systems,poses a significant challenge in the growth of multimedia ***-quality images require well-tuned communication *** Single Carrier Frequency Division Multiple Access(SC-FDMA)is adopted for broadband wireless communications,because of its low sensitivity to carrier frequency offsets and low Peak-to-Average Power Ratio(PAPR).Data transmission through open-channel networks requires much concentration on security,reliability,and *** data need a space away fromunauthorized access,modification,or *** requirements are to be fulfilled by digital image watermarking and *** paper ismainly concerned with secure image communication over the wireless SC-FDMA systemas an adopted communication *** introduces a robust image communication framework over SC-FDMA that comprises digital image watermarking and encryption to improve image security,while maintaining a high-quality reconstruction of images at the receiver *** proposed framework allows image watermarking based on the Discrete Cosine Transform(DCT)merged with the Singular Value Decomposition(SVD)in the so-called DCT-SVD *** addition,image encryption is implemented based on chaos and DNA *** encrypted watermarked images are then transmitted through the wireless SC-FDMA *** linearMinimumMean Square Error(MMSE)equalizer is investigated in this paper to mitigate the effect of channel fading and noise on the transmitted *** subcarrier mapping schemes,namely localized and interleaved schemes,are compared in this *** study depends on different channelmodels,namely PedestrianAandVehicularA,with a modulation technique namedQuadratureAmplitude Modulation(QAM).Extensive simulation experiments are conducted and introduced in this paper for efficient transmission of encrypted watermarked *** addition,different variants of SC-FDMA bas

关键词： Cybersecurity applications image transmission channel models modulation techniques watermarking and encryption

Neural Dynamics for Cooperative Motion Control of Omnidirectional Mobile Manipulators in the Presence of Noises: A Distributed Approach

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

IEEE/CAA Journal of Automatica Sinica 2024年第7期11卷 1605-1620页

作者： Yufeng Lian Xingtian Xiao Jiliang Zhang Long Jin Junzhi Yu Zhongbo Sun the department of Control engineering Changchun University of TechnologyChangchun 130012China IEEE the College of information Science and engineering Northeastern UniversityShenyang 110819 the National Mobile Communications Research Laboratory Southeast UniversityNanjing 210096China the School of information Science and engineering Lanzhou UniversityLanzhou 730000China the State Key Laboratory for Turbulence and Complex Systems Department of Advanced Manufacturing and RoboticsCollege of EngineeringPeking UniversityBeijing 100871China

This paper presents a distributed scheme with limited communications, aiming to achieve cooperative motion control for multiple omnidirectional mobile manipulators(MOMMs).The proposed scheme extends the existing single-agent motion control to cater to scenarios involving the cooperative operation of MOMMs. Specifically, squeeze-free cooperative load transportation is achieved for the end-effectors of MOMMs by incorporating cooperative repetitive motion planning(CRMP), while guiding each individual to desired poses. Then, the distributed scheme is formulated as a time-varying quadratic programming(QP) and solved online utilizing a noise-tolerant zeroing neural network(NTZNN). Theoretical analysis shows that the NTZNN model converges globally to the optimal solution of QP in the presence of noise. Finally, the effectiveness of the control design is demonstrated by numerical simulations and physical platform experiments.

关键词： Cooperative motion control noise-tolerant zeroing neural network(NTZNN) omnidirectional mobile manipulator(OMM) repetitive motion planning

维普期刊数据库

Improving Thyroid Disorder Diagnosis via Ensemble Stacking and Bidirectional Feature Selection

在线全文

学校读者我要写书评

暂无评论

Computers, Materials & Continua 2024年第3期78卷 4225-4241页

作者： Muhammad Armghan Latif Zohaib Mushtaq Saad Arif Sara Rehman Muhammad Farrukh Qureshi Nagwan Abdel Samee Maali Alabdulhafith Yeong Hyeon Gu Mohammed A.Al-masni department of Computer and information System Cleveland State UniversityOhio44115USA department of Electrical Electronics and Computer SystemsCollege of Engineering and TechnologyUniversity of SargodhaSargodha40100Pakistan department of Mechanical engineering College of EngineeringKing Faisal UniversityAl-Ahsa31982Saudi Arabia department of Biomedical engineering Riphah International UniversityIslamabad44000Pakistan department of Electrical engineering Riphah International UniversityIslamabad44000Pakistan department of information Technology College of Computer and Information SciencesPrincess Nourah bint Abdulrahman UniversityP.O.Box 84428Riyadh11671Saudi Arabia department of Artificial Intelligence College of Software and Convergence TechnologySejong UniversitySeoul05006Korea

Thyroid disorders represent a significant global health challenge with hypothyroidism and hyperthyroidism as two common conditions arising from dysfunction in the thyroid *** and timely diagnosis of these disorders is crucial for effective treatment and patient *** research introduces a comprehensive approach to improve the accuracy of thyroid disorder diagnosis through the integration of ensemble stacking and advanced feature selection *** forward feature selection,sequential backward feature elimination,and bidirectional feature elimination are investigated in this *** ensemble learning,random forest,adaptive boosting,and bagging classifiers are *** effectiveness of these techniques is evaluated using two different datasets obtained from the University of California Irvine-Machine Learning Repository,both of which undergo preprocessing steps,including outlier removal,addressing missing data,data cleansing,and feature *** experimentation demonstrates the remarkable success of proposed ensemble stacking and bidirectional feature elimination achieving 100%and 99.86%accuracy in identifying hyperthyroidism and hypothyroidism,*** enhancing detection accuracy,the ensemble stacking model also demonstrated a streamlined computational complexity which is pivotal for practical medical *** significantly outperformed existing studies with similar objectives underscoring the viability and effectiveness of the proposed *** research offers an innovative perspective and sets the platform for improved thyroid disorder diagnosis with broader implications for healthcare and patient well-being.

关键词： Ensemble learning random forests boosting dimensionality reduction machine learning smart healthcare computer aided diagnosis

A survey on semantic communications:Technologies,solutions,applications and challenges

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

Digital Communications and Networks 2024年第3期10卷 528-545页

作者： Yating Liu Xiaojie Wang Zhaolong Ning MengChu Zhou Lei Guo Behrouz Jedari School of Communication and information engineering Chongqing University of Posts and TelecommunicationsChongqing 400065China Baotou Vocational&Technical College Baotou 014035China School of information and Electronic engineering Zhejiang Gongshang UniversityHangzhou 310018China department of Electrical and Computer engineering New Jersey Institute of TechnologyNewarkNJ 07102USA Nokia Finland

Semantic Communication(SC)has emerged as a novel communication paradigm that provides a receiver with meaningful information extracted from the source to maximize information transmission throughput in wireless networks,beyond the theoretical capacity *** the extensive research on SC,there is a lack of comprehensive survey on technologies,solutions,applications,and challenges for *** this article,the development of SC is first reviewed and its characteristics,architecture,and advantages are ***,key technologies such as semantic extraction,semantic encoding,and semantic segmentation are discussed and their corresponding solutions in terms of efficiency,robustness,adaptability,and reliability are *** of SC to UAV communication,remote image sensing and fusion,intelligent transportation,and healthcare are also presented and their strategies are ***,some challenges and future research directions are presented to provide guidance for further research of SC.

关键词： Semantic communication Semantic coding Semantic extraction Semantic communication framework Semantic communication applications

The Investigation of Data Voting Algorithm for Train Air-Braking System Based on Multi-Classification SVM and ANFIS

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

Chinese Journal of Electronics 2024年第1期33卷 274-281页

作者： Juhan WANG Ying GAO Yuan CAO Tao TANG School of Electronics and information engineering Beijing Jiaotong University Graduate department China Academy of Railway Science National engineering Research Center of Rail Transportation Operation and Control System Beijing Jiaotong University

The pressure data of the train air braking system is of great significance to accurately evaluate its operation state. In order to overcome the influence of sensor fault on the pressure data of train air braking system, it is necessary to design a set of sensor fault-tolerant voting mechanism to ensure that in the case of a pressure sensor fault, the system can accurately identify and locate the position of the faulty sensor, and estimate the fault data according to other normal data. A fault-tolerant mechanism based on multi-classification support vector machine(SVM) and adaptive network-based fuzzy inference system(ANFIS) is introduced. Multi-classification SVM is used to identify and locate the system fault state, and ANFIS is used to estimate the real data of the fault sensor. After estimation, the system will compare the real data of the fault sensor with the ANFIS estimated data. If it is similar,the system will recognize that there is a false alarm and record it. Then the paper tests the whole mechanism based on the real data. The test shows that the system can identify the fault samples and reduce the occurrence of false alarms.

关键词： Support vector machines Fault diagnosis Pressure sensors Fuzzy logic Fault tolerance Adaptive systems Fault tolerant systems

Optimized Binary Neural Networks for Road Anomaly Detection:A TinyML Approach on Edge Devices

在线全文

同方期刊数据库

学校读者我要写书评

暂无评论

Computers, Materials & Continua 2024年第7期80卷 527-546页

作者： Amna Khatoon Weixing Wang Asad Ullah Limin Li Mengfei Wang School of information engineering Chang’an UniversityXi’an710064China School of information engineering Xi’an Eurasia UniversityXi’an710065China School of Electrical and Electronic engineering Wenzhou UniversityWenzhou325035China

Integrating Tiny Machine Learning(TinyML)with edge computing in remotely sensed images enhances the capabilities of road anomaly detection on a broader *** devices efficiently implement a Binary Neural Network(BNN)for road feature extraction,utilizing quantization and compression through a pruning *** modifications resulted in a 28-fold decrease in memory usage and a 25%enhancement in inference speed while only experiencing a 2.5%decrease in *** showcases its superiority over conventional detection algorithms in different road image *** constrained by computer resources and training datasets,our results indicate opportunities for future research,demonstrating that quantization and focused optimization can significantly improve machine learning models’accuracy and operational *** Cortex-M0 gives practical feasibility and substantial benefits while deploying our optimized BNN model on this low-power device:Advanced machine learning in edge *** analysis work delves into the educational significance of TinyML and its essential function in analyzing road networks using remote sensing,suggesting ways to improve smart city frameworks in road network assessment,traffic management,and autonomous vehicle navigation systems by emphasizing the importance of new technologies for maintaining and safeguarding road networks.

关键词： Edge computing remote sensing TinyML optimization BNNs road anomaly detection quantization model compression

A Novel Tensor Decomposition-Based Efficient Detector for Low-Altitude Aerial Objects With Knowledge Distillation Scheme

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

IEEE/CAA Journal of Automatica Sinica 2024年第2期11卷 487-501页

作者： Nianyin Zeng Xinyu Li Peishu Wu Han Li Xin Luo department of Instrumental and Electrical engineering Xiamen UniversityXiamen 361005China IEEE College of Computer and information Science Southwest UniversityChongqing 400715China

Unmanned aerial vehicles(UAVs) have gained significant attention in practical applications, especially the low-altitude aerial(LAA) object detection imposes stringent requirements on recognition accuracy and computational resources. In this paper, the LAA images-oriented tensor decomposition and knowledge distillation-based network(TDKD-Net) is proposed,where the TT-format TD(tensor decomposition) and equalweighted response-based KD(knowledge distillation) methods are designed to minimize redundant parameters while ensuring comparable performance. Moreover, some robust network structures are developed, including the small object detection head and the dual-domain attention mechanism, which enable the model to leverage the learned knowledge from small-scale targets and selectively focus on salient features. Considering the imbalance of bounding box regression samples and the inaccuracy of regression geometric factors, the focal and efficient IoU(intersection of union) loss with optimal transport assignment(F-EIoU-OTA)mechanism is proposed to improve the detection accuracy. The proposed TDKD-Net is comprehensively evaluated through extensive experiments, and the results have demonstrated the effectiveness and superiority of the developed methods in comparison to other advanced detection algorithms, which also present high generalization and strong robustness. As a resource-efficient precise network, the complex detection of small and occluded LAA objects is also well addressed by TDKD-Net, which provides useful insights on handling imbalanced issues and realizing domain adaptation.

关键词： Attention mechanism knowledge distillation(KD) object detection tensor decomposition(TD) unmanned aerial vehicles(UAVs)

维普期刊数据库