Wirel. Commun. Mob. Comput.最新文献_第8页

Performance of the DBS Satellite Receiver under the Impact of Rainfall and Terrestrial Interference 降雨和地面干扰对DBS卫星接收机性能的影响

Wirel. Commun. Mob. Comput. Pub Date : 2021-09-08 DOI: 10.1155/2021/5595294

Z. Shamsan, Ahmed M. Al-Saman

引用次数: 4

Role of Internet of Things Technology in Promoting the Circulation Industry in the Transformation of a Resource-Based Economy 物联网技术在资源型经济转型中对流通业的促进作用

Wirel. Commun. Mob. Comput. Pub Date : 2021-09-06 DOI: 10.1155/2021/7124086

Dongqing Zhu, T. Li, Can Zhang, Ying Ren, Huan Wang, X. Duan

{"title":"Role of Internet of Things Technology in Promoting the Circulation Industry in the Transformation of a Resource-Based Economy","authors":"Dongqing Zhu, T. Li, Can Zhang, Ying Ren, Huan Wang, X. Duan","doi":"10.1155/2021/7124086","DOIUrl":"https://doi.org/10.1155/2021/7124086","url":null,"abstract":"In recent years, the business scale of my country’s circulation industry has continued to expand, and the output value has continued to increase. The leading role in guiding the transformation of the industrial economy has become more and more important. Based on this, this article discusses the research on the promotion of the Internet of Things technology to the circulation industry in the transformation of the resource-based economy. The application of RFID technology and wireless sensor technology in the Internet of Things in the circulation industry can greatly improve work efficiency and information transmission accuracy. This article establishes the circulation industry based on the principles of science, system, safety, and relative independence. The evaluation index system analyzes the role of the circulation industry in the transformation of the resource-based economy in terms of circulation scale, circulation structure, circulation efficiency, circulation innovation, etc., and uses the analytic hierarchy process and entropy method to analyze the collected data. With the support of RFID technology, the output value of the circulation industry in Province Y has reached 140.508 billion yuan in 2019, accounting for about 27% of the tertiary industry, and the number of employees in the circulation industry has also increased to 57.88%, which is a strong boost to the economy of Province Y. It has a greater contribution to the total economic volume. The research of this article has realized the economic transformation of resource-based cities in the circulation industry and has a certain reference effect for the transformation and upgrading of similar cities.","PeriodicalId":23995,"journal":{"name":"Wirel. Commun. Mob. Comput.","volume":"90 1","pages":"7124086:1-7124086:12"},"PeriodicalIF":0.0,"publicationDate":"2021-09-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"80447694","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 3

Research on the Detection and Tracking Algorithm of Moving Object in Image Based on Computer Vision Technology 基于计算机视觉技术的图像运动目标检测与跟踪算法研究

Wirel. Commun. Mob. Comput. Pub Date : 2021-09-06 DOI: 10.1155/2021/1127017

Chunsheng Chen, Ding Li

引用次数: 13

Application of Wireless Communication in Experimental Research of the Interface Bonding Condition between Asphalt Layers by Tensile Testing 无线通信在沥青层间界面粘结状态拉伸试验研究中的应用

Wirel. Commun. Mob. Comput. Pub Date : 2021-09-06 DOI: 10.1155/2021/2488947

Huaijun Yin, Daming Wang, Jianwei Zou, Y. Zhu

{"title":"Application of Wireless Communication in Experimental Research of the Interface Bonding Condition between Asphalt Layers by Tensile Testing","authors":"Huaijun Yin, Daming Wang, Jianwei Zou, Y. Zhu","doi":"10.1155/2021/2488947","DOIUrl":"https://doi.org/10.1155/2021/2488947","url":null,"abstract":"The vigorous development of communication technology, especially the development of wireless network communication technology, has accelerated its informatization process in more and more industrial applications. In the field of monitoring and detection applications, the many advantages of wireless network transmission technology provide an important reference for high-quality compaction monitoring. Engineering practice shows that the construction technology of asphalt pavement is the ultimate guarantee of engineering quality. It is important to recognize that pavement performance is greatly influenced by interface bonding condition and interface failure can reduce the serviceability of pavements rather than their overall structural lifetime. This paper presents a laboratory test to investigate the bonding tensile performance between asphalt layers by tensile testing. The test methods and devices for determining the bond regarding tensile testing are summarized as follows. Different interface conditions have been analyzed herein: 0.2, 0.4, and 0.6 kg/m2 with corresponding emulsified asphalt (MA) and SBS-modified MA. It is found that the stress-strain relationship of tensile testing for interface bonding is similar with low-carbon steels and it can be categorized into four zones. The results of tensile strength and damage displacement are discussed which are key parameters in describing the interface bonding condition and evaluating pavement performance.","PeriodicalId":23995,"journal":{"name":"Wirel. Commun. Mob. Comput.","volume":"117 1","pages":"2488947:1-2488947:5"},"PeriodicalIF":0.0,"publicationDate":"2021-09-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"73635970","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 1

A Hybrid Reliable Routing Algorithm Based on LQI and PRR in Industrial Wireless Networks 基于LQI和PRR的工业无线网络混合可靠路由算法

Wirel. Commun. Mob. Comput. Pub Date : 2021-09-04 DOI: 10.1155/2021/6039900

Jie Li, Yangyang Pan, Shi-Xiang Ni, Feng Wang

{"title":"A Hybrid Reliable Routing Algorithm Based on LQI and PRR in Industrial Wireless Networks","authors":"Jie Li, Yangyang Pan, Shi-Xiang Ni, Feng Wang","doi":"10.1155/2021/6039900","DOIUrl":"https://doi.org/10.1155/2021/6039900","url":null,"abstract":"In Industrial Wireless Networks (IWNs), the communication through Machine-to-Machine (M2M) is often affected by the noise in the industrial environment, which leads to the decline of communication reliability. In this paper, we investigate how to improve route stability through M2M in an industrial environment. We first compare different link quality estimations, such as Signal-Noise Ratio (SNR), Received Signal Strength Indicator (RSSI), Link Quality Indicator (LQI), Packet Reception Ratio (PRR), and Expected Transmission Count (ETX). We then propose a link quality estimation combining LQI and PRR. Finally, we propose a Hybrid Link Quality Estimation-Based Reliable Routing (HLQEBRR) algorithm for IWNs, with the object of maximizing link stability. In addition, HLQEBRR provides a recovery mechanism to detect node failure, which improves the speed and accuracy of node recovery. OMNeT++-based simulation results demonstrate that our HLQEBRR algorithm significantly outperforms the Collection Tree Protocol (CTP) algorithm in terms of end-to-end transmission delay and packet loss ratio, and the HLQEBRR algorithm achieves higher reliability at a small additional cost.","PeriodicalId":23995,"journal":{"name":"Wirel. Commun. Mob. Comput.","volume":"5 1","pages":"6039900:1-6039900:16"},"PeriodicalIF":0.0,"publicationDate":"2021-09-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"74285202","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Music Style Classification Algorithm Based on Music Feature Extraction and Deep Neural Network 基于音乐特征提取和深度神经网络的音乐风格分类算法

Wirel. Commun. Mob. Comput. Pub Date : 2021-09-04 DOI: 10.1155/2021/9298654

Kedong Zhang

{"title":"Music Style Classification Algorithm Based on Music Feature Extraction and Deep Neural Network","authors":"Kedong Zhang","doi":"10.1155/2021/9298654","DOIUrl":"https://doi.org/10.1155/2021/9298654","url":null,"abstract":"The music style classification technology can add style tags to music based on the content. When it comes to researching and implementing aspects like efficient organization, recruitment, and music resource recommendations, it is critical. Traditional music style classification methods use a wide range of acoustic characteristics. The design of characteristics necessitates musical knowledge and the characteristics of various classification tasks are not always consistent. The rapid development of neural networks and big data technology has provided a new way to better solve the problem of music-style classification. This paper proposes a novel method based on music extraction and deep neural networks to address the problem of low accuracy in traditional methods. The music style classification algorithm extracts two types of features as classification characteristics for music styles: timbre and melody features. Because the classification method based on a convolutional neural network ignores the audio’s timing. As a result, we proposed a music classification module based on the one-dimensional convolution of a recurring neuronal network, which we combined with single-dimensional convolution and a two-way, recurrent neural network. To better represent the music style properties, different weights are applied to the output. The GTZAN data set was also subjected to comparison and ablation experiments. The test results outperformed a number of other well-known methods, and the rating performance was competitive.","PeriodicalId":23995,"journal":{"name":"Wirel. Commun. Mob. Comput.","volume":"40 1","pages":"9298654:1-9298654:7"},"PeriodicalIF":0.0,"publicationDate":"2021-09-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"81314469","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 25

Network Threat Detection Based on Group CNN for Privacy Protection 基于群CNN的隐私保护网络威胁检测

Wirel. Commun. Mob. Comput. Pub Date : 2021-09-03 DOI: 10.1155/2021/3697536

Yanping Xu, Xia Zhang, Chengdan Lu, Zhenliang Qiu, Chunfang Bi, Yuping Lai, Jian Qiu, Hua Zhang

{"title":"Network Threat Detection Based on Group CNN for Privacy Protection","authors":"Yanping Xu, Xia Zhang, Chengdan Lu, Zhenliang Qiu, Chunfang Bi, Yuping Lai, Jian Qiu, Hua Zhang","doi":"10.1155/2021/3697536","DOIUrl":"https://doi.org/10.1155/2021/3697536","url":null,"abstract":"The Internet of Things (IoT) contains a large amount of data, which attracts various types of network attacks that lead to privacy leaks. With the upgrading of network attacks and the increase in network security data, traditional machine learning methods are no longer suitable for network threat detection. At the same time, data analysis techniques and deep learning algorithms have developed rapidly and have been successfully applied to a variety of tasks for privacy protection. Convolutional neural networks (CNNs) are typical deep learning models that can learn and reconstruct features accurately and efficiently. Therefore, in this paper, we propose a group CNN models that is based on feature correlations to learn features and reconstruct security data. First, feature correlation coefficients are computed to measure the relationships among the features. Then, we sort the correlation coefficients in descending order and group the data by columns. Second, a 1D group CNN model with multiple 1D convolution kernels and 1D pooling filters is built to address the grouped data for feature learning and reconstruction. Third, the reconstructed features are input to shadow machine learning models for network threat prediction. The experimental results show that features reconstructed by the group CNN can reduce the dimensions and achieve the best performance compared to the other present dimension reduction algorithms. At the same time, the group CNN can decrease the floating point of operations (FLOP), parameters, and running time compared to the basic 1D CNN.","PeriodicalId":23995,"journal":{"name":"Wirel. Commun. Mob. Comput.","volume":"159 1","pages":"3697536:1-3697536:18"},"PeriodicalIF":0.0,"publicationDate":"2021-09-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"88127969","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 5

UAV-Based Collaborative Electronic Reconnaissance Network for 6G 基于无人机的6G协同电子侦察网络

Wirel. Commun. Mob. Comput. Pub Date : 2021-09-03 DOI: 10.1155/2021/5827665

Fucheng Yang, Jie Song, Wei Xiong, Xutao Cui

引用次数: 1

High-Precision 3D Reconstruction of Cooperative Markers under Motion Blur 运动模糊下协同标记的高精度三维重建

Wirel. Commun. Mob. Comput. Pub Date : 2021-09-03 DOI: 10.1155/2021/6467337

Yun Shi, C. Tao, Xiaoping Wang, Liyan Zhang

引用次数: 1

Data Transmission Evaluation and Allocation Mechanism of the Optimal Routing Path: An Asynchronous Advantage Actor-Critic (A3C) Approach 最优路由路径的数据传输评估与分配机制:一种异步优势行动者-批评家(A3C)方法

Wirel. Commun. Mob. Comput. Pub Date : 2021-09-02 DOI: 10.1155/2021/6685722

Yahui Ding, Jianli Guo, Xu Li, Xiujuan Shi, Pengfei Yu

{"title":"Data Transmission Evaluation and Allocation Mechanism of the Optimal Routing Path: An Asynchronous Advantage Actor-Critic (A3C) Approach","authors":"Yahui Ding, Jianli Guo, Xu Li, Xiujuan Shi, Pengfei Yu","doi":"10.1155/2021/6685722","DOIUrl":"https://doi.org/10.1155/2021/6685722","url":null,"abstract":"The delay tolerant networks (DTN), which have special features, differ from the traditional networks and always encounter frequent disruptions in the process of transmission. In order to transmit data in DTN, lots of routing algorithms have been proposed, like “Minimum Expected Delay,” “Earliest Delivery,” and “Epidemic,” but all the above algorithms have not taken into account the buffer management and memory usage. With the development of intelligent algorithms, Deep Reinforcement Learning (DRL) algorithm can better adapt to the above network transmission. In this paper, we firstly build optimal models based on different scenarios so as to jointly consider the behaviors and the buffer of the communication nodes, aiming to ameliorate the process of the data transmission; then, we applied the Deep Q-learning Network (DQN) and Advantage Actor-Critic (A3C) approaches in different scenarios, intending to obtain end-to-end optimal paths of services and improve the transmission performance. In the end, we compared algorithms over different parameters and find that the models build in different scenarios can achieve 30% end-to-end delay decline and 80% throughput improvement, which show that our algorithms applied in are effective and the results are reliable.","PeriodicalId":23995,"journal":{"name":"Wirel. Commun. Mob. Comput.","volume":"1 1","pages":"6685722:1-6685722:21"},"PeriodicalIF":0.0,"publicationDate":"2021-09-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"90194396","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0