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Parameter Optimization of Intercalated Meltblown Nonwovens Based on NSGA-II 基于NSGA-II的插层熔喷非织造布参数优化
Pub Date : 2023-01-01 DOI: 10.4236/jcc.2023.113011
Peiyuan Jin, Renjie Chu, Quanxi Feng
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引用次数: 0
A Novel Efficient and Effective Preprocessing Algorithm for Text Classification 一种新的高效文本分类预处理算法
Pub Date : 2023-01-01 DOI: 10.4236/jcc.2023.113001
Li-li Zhu, Difan Luo
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引用次数: 0
Design of an E-Administration Platform and Its Cryptography-Based Security Model 电子政务平台的设计及其密码学安全模型
Pub Date : 2023-01-01 DOI: 10.4236/jcc.2023.114008
Ohwobeno Omohwo, Iwasokun Gabriel Babatunde, Boyinbode Olutayo Kehinde, G. Arome
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引用次数: 0
Research on Electromagnetic Acoustic Emission Signal Recognition Based on Local Mean Decomposition and Least Squares Support Vector Machine 基于局部均值分解和最小二乘支持向量机的电磁声发射信号识别研究
Pub Date : 2023-01-01 DOI: 10.4236/jcc.2023.115006
Chenglong Yang, Yushu Lai, Qiuyue Li
{"title":"Research on Electromagnetic Acoustic Emission Signal Recognition Based on Local Mean Decomposition and Least Squares Support Vector Machine","authors":"Chenglong Yang, Yushu Lai, Qiuyue Li","doi":"10.4236/jcc.2023.115006","DOIUrl":"https://doi.org/10.4236/jcc.2023.115006","url":null,"abstract":"","PeriodicalId":67799,"journal":{"name":"电脑和通信(英文)","volume":"1 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"70936440","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
COVID-19 Detection from Chest X-Ray Images Using Convolutional Neural Network Approach 基于卷积神经网络的胸部x线图像COVID-19检测方法
Pub Date : 2023-01-01 DOI: 10.4236/jcc.2023.115003
Md. Harun Or Rashid, Muzakkir Hossain Minhaz, Ananya Sarker, Must. Asma Yasmin, Md. Golam An Nihal
{"title":"COVID-19 Detection from Chest X-Ray Images Using Convolutional Neural Network Approach","authors":"Md. Harun Or Rashid, Muzakkir Hossain Minhaz, Ananya Sarker, Must. Asma Yasmin, Md. Golam An Nihal","doi":"10.4236/jcc.2023.115003","DOIUrl":"https://doi.org/10.4236/jcc.2023.115003","url":null,"abstract":"","PeriodicalId":67799,"journal":{"name":"电脑和通信(英文)","volume":"1 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"70936796","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
Simplified Inception Module Based Hadamard Attention Mechanism for Medical Image Classification 基于简化Inception模块的Hadamard注意机制的医学图像分类
Pub Date : 2023-01-01 DOI: 10.4236/jcc.2023.116001
Yanlin Jin, Zhiming You, Ningyin Cai
{"title":"Simplified Inception Module Based Hadamard Attention Mechanism for Medical Image Classification","authors":"Yanlin Jin, Zhiming You, Ningyin Cai","doi":"10.4236/jcc.2023.116001","DOIUrl":"https://doi.org/10.4236/jcc.2023.116001","url":null,"abstract":"","PeriodicalId":67799,"journal":{"name":"电脑和通信(英文)","volume":"1 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"70937196","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
Comparative Analysis of Different Sampling Rates on Environmental Sound Classification Using the Urbansound8k Dataset 基于Urbansound8k数据集的不同采样率环境声分类比较分析
Pub Date : 2023-01-01 DOI: 10.4236/jcc.2023.116002
Ibrahim Aljubayri
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引用次数: 0
Application of Dual-Energy X-Ray Image Detection of Dangerous Goods Based on YOLOv7 基于YOLOv7的危险物品双能x射线图像检测应用
Pub Date : 2023-01-01 DOI: 10.4236/jcc.2023.117013
Baosheng Liu, Fei Wang, Ming Gao, Lei Zhao
X-ray security equipment is currently a more commonly used dangerous goods detection tool, due to the increasing security work tasks, the use of target detection technology to assist security personnel to carry out work has become an inevitable trend. With the development of deep learning, object detection technology is becoming more and more mature, and object detection framework based on convolutional neural networks has been widely used in industrial, medical and military fields. In order to improve the efficiency of security staff, reduce the risk of dangerous goods missed detection. Based on the data collected in X-ray security equipment, this paper uses a method of inserting dangerous goods into an empty package to balance all kinds of dangerous goods data and expand the data set. The high-low energy images are combined using the high-low energy feature fusion method. Finally, the dangerous goods target detection technology based on the YOLOv7 model is used for model training. After the introduction of the above method, the detection accuracy is improved by 6% compared with the direct use of the original data set for detection, and the speed is 93FPS, which can meet the requirements of the online security system, greatly improve the work efficiency of security personnel, and eliminate the security risks caused by missed detection.
x射线安检设备是目前比较常用的一种危险品检测工具,由于安检工作任务越来越多,利用目标检测技术辅助安检人员开展工作已成为必然趋势。随着深度学习的发展,目标检测技术日趋成熟,基于卷积神经网络的目标检测框架已广泛应用于工业、医疗、军事等领域。为了提高安检人员的工作效率,减少危险品漏检的风险。本文以x射线安检设备采集的数据为基础,采用将危险品插入空包的方法,平衡各类危险品数据,扩大数据集。采用高低能特征融合方法对高低能图像进行组合。最后,利用基于YOLOv7模型的危险品目标检测技术进行模型训练。引入上述方法后,与直接使用原始数据集进行检测相比,检测精度提高了6%,速度为93FPS,可以满足在线安防系统的要求,大大提高了安防人员的工作效率,消除了漏检带来的安全隐患。
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引用次数: 0
Sectional Dimensions Identification of Metal Profile by Image Processing 基于图像处理的金属型材截面尺寸识别
Pub Date : 2023-01-01 DOI: 10.4236/jcc.2023.118008
I. M. Orak, Şaban Şeker
In steel plants, estimation of the production system characteristic is highly critical to adjust the system parameters for best efficiency. Although the sys-tem parameters may be tuned very well, due to the machine and human factors involved in the production line some deficiencies may occur in product. It is important to detect such problems as early as possible. Surface defects and dimensional deviations are the most important quality problems. In this study, it is aimed to develop an approach to measure the dimensions of metal profiles by obtaining images of them. This will be of use in detecting the deviations in dimensions. A platform was introduced to simulate the real-time environment and images were taken from the metal profile using 4 laser light sources. The shape of the material is generated by combining the images taken from different cameras. Real dimensions were obtained by using image processing and mathematical conversion operations on the images. The re-sults obtained with small deviations from the real values showed that this method can be applied in a real-time production line.
在钢铁厂中,对生产系统特性的估计对于调整系统参数以获得最佳效率至关重要。虽然系统参数可以调得很好,但由于生产线中涉及的机器和人为因素,产品可能会出现一些缺陷。尽早发现这些问题很重要。表面缺陷和尺寸偏差是最重要的质量问题。在这项研究中,它的目的是开发一种方法来测量金属型材的尺寸,获得他们的图像。这在检测尺寸偏差时是有用的。介绍了一个模拟实时环境的平台,并使用4个激光光源从金属轮廓上获取图像。材料的形状是由不同相机拍摄的图像组合而成的。通过对图像进行图像处理和数学转换运算,得到实数尺寸。结果表明,该方法与实际值偏差较小,可用于实时生产线。
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引用次数: 0
Channel Coding at Finite Blocklength and Its Application in 6G URLLC 有限块长度信道编码及其在6G URLLC中的应用
Pub Date : 2023-01-01 DOI: 10.4236/jcc.2023.119008
Siyu Huang, Bin Sheng, Chen Ji
To support mission-critical applications, such as factory automation and autonomous driving, the ultra-reliable low latency communications (URLLC) is adopted in the fifth generation (5G) mobile communications network, which requires high level of reliability and low latency. Naturally, URLLC in the future 6G is expected to have a better capability than its 5G version which poses an unprecedented challenge to us. Fortunately, the potential solution can still be found in the well-known classical Shannon information theory. Since the latency constraint can be represented equivalently by blocklength, channel coding at finite blocklength plays an important role in the theoretic analysis of URLLC. Applying these achievements in rapidly development of massive MIMO techniques gives rise to a new theory on space time exchanging. It tells us that channel coding can also be performed in space domain, since it is capable of providing the same coding rate as that in time domain. This space time exchanging theory points out an exciting and feasible direction for us to further reduce latency in 6G URLLC.
为了支持工厂自动化、自动驾驶等关键任务应用,第五代移动通信网络采用超可靠低延迟通信(URLLC),要求高可靠性和低延迟。当然,未来6G的URLLC有望拥有比5G版本更好的功能,这对我们提出了前所未有的挑战。幸运的是,在著名的经典香农信息理论中仍然可以找到潜在的解决方案。由于延迟约束可以用块长度等效表示,因此有限块长度的信道编码在URLLC的理论分析中起着重要的作用。将这些成果应用到快速发展的大规模MIMO技术中,产生了一种新的时空交换理论。它告诉我们,信道编码也可以在空间域中进行,因为它能够提供与时域相同的编码速率。这种时空交换理论为我们进一步降低6G URLLC的延迟指出了一个令人兴奋和可行的方向。
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引用次数: 0
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电脑和通信(英文)
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