发布求助
文献互助 智能选刊 最新文献

2021 International Conference on Advanced Technologies for Communications (ATC)最新文献

筛选
英文 中文
A Novel ZF and MMSE Receiver for Modified Walsh-Hadamard Code Division Multiplexing in Helicopter Satellite Communications 直升机卫星通信中用于改进沃尔什-阿达玛尔码分复用的新型ZF和MMSE接收机
2021 International Conference on Advanced Technologies for Communications (ATC) Pub Date : 2021-10-14 DOI: 10.1109/atc52653.2021.9598285
T. Kojima, Tsubasa Yamada
{"title":"A Novel ZF and MMSE Receiver for Modified Walsh-Hadamard Code Division Multiplexing in Helicopter Satellite Communications","authors":"T. Kojima, Tsubasa Yamada","doi":"10.1109/atc52653.2021.9598285","DOIUrl":"https://doi.org/10.1109/atc52653.2021.9598285","url":null,"abstract":"In helicopter satellite communications, overcoming periodic signal blockage caused by rotor blades is an important issue. Modified Walsh-Hadamard code division multiplexing (MWHCDM) is a promising solution. However, it is adversely affected by the inter-code interference (ICI) due to the periodic blockage. This paper proposes an ICI reduction scheme for MWHCDM. The proposed one utilizes the structure of the MWHCDM signal for reducing the ICI with zero-forcing (ZF) and minimum mean square error (MMSE) detection. The results of computer simulation demonstrated that the proposed one achieves both excellent bit error rate performance and superior spectral efficiency in the periodic blockage channel.","PeriodicalId":196900,"journal":{"name":"2021 International Conference on Advanced Technologies for Communications (ATC)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-10-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130963447","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
ℋ2/ℋ− Distributed Fault Detection and Isolation for Heterogeneous Multi-Agent Systems 异构多智能体系统的分布故障检测与隔离
2021 International Conference on Advanced Technologies for Communications (ATC) Pub Date : 2021-10-14 DOI: 10.1109/atc52653.2021.9598228
Thiem V. Pham, Q. T. T. Nguyen
{"title":"ℋ2/ℋ− Distributed Fault Detection and Isolation for Heterogeneous Multi-Agent Systems","authors":"Thiem V. Pham, Q. T. T. Nguyen","doi":"10.1109/atc52653.2021.9598228","DOIUrl":"https://doi.org/10.1109/atc52653.2021.9598228","url":null,"abstract":"The paper deals with the problem of distributed fault detection and isolation (FDI) for a group of heterogeneous multi-agent systems. The developed formation for the FDI is taken into account as a distributed observer design methodology, where the interaction between the agent and its neighbors is described as a vector of distributed relative output measurements. Based on two performance indexes ℋ2 and ℋ−, sufficient conditions are given to ensure the residual signals robust to the disturbances and sensitive with respect to the fault signals. In addition, we show that by using our proposed approach, each agent is able to estimate both its own states and states of its nearest neighbors in the presence of disturbances and faults. Finally, numerical simulations are provided to demonstrate the effectiveness of the theoretically analyzed results.","PeriodicalId":196900,"journal":{"name":"2021 International Conference on Advanced Technologies for Communications (ATC)","volume":"45 2 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-10-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125691426","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
Simulation of Hybrid Autonomous Underwater Vehicle based on ROS and Gazebo 基于ROS和Gazebo的混合自主水下航行器仿真
2021 International Conference on Advanced Technologies for Communications (ATC) Pub Date : 2021-10-14 DOI: 10.1109/atc52653.2021.9598242
Andy T. Ngo, Ngoc-Huy Tran, T. Ton, Hung-Cuong Nguyen, T. Tran
{"title":"Simulation of Hybrid Autonomous Underwater Vehicle based on ROS and Gazebo","authors":"Andy T. Ngo, Ngoc-Huy Tran, T. Ton, Hung-Cuong Nguyen, T. Tran","doi":"10.1109/atc52653.2021.9598242","DOIUrl":"https://doi.org/10.1109/atc52653.2021.9598242","url":null,"abstract":"Simulation is a crucial task in algorithm testing for autonomous vehicles. Furthermore, simulation also helps to observe the possible errors precedent to the empirical experiment, thus optimizing the time and effort of researchers. This paper will illustrate the simulation method of Hybrid Autonomous Underwater Vehicle(AUV), a new AUV platform utilizing Robotic Operating System (ROS) and Gazebo. Gazebo will simulate 3D behaviors and movements of AUV based on calculations regarding the effect of hydrodynamic and hydrostatic force, the objective relation of the actuator as well as the sensor simulation, in which ROS is used for control algorithm development.","PeriodicalId":196900,"journal":{"name":"2021 International Conference on Advanced Technologies for Communications (ATC)","volume":"22 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-10-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114189477","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: 4
Artificial Cognition for Early Leaf Disease Detection using Vision Transformers 基于视觉变压器的早期叶病检测人工认知
2021 International Conference on Advanced Technologies for Communications (ATC) Pub Date : 2021-10-14 DOI: 10.1109/atc52653.2021.9598303
Huy-Tan Thai, Nhu-Y Tran-Van, Kim-Hung Le
{"title":"Artificial Cognition for Early Leaf Disease Detection using Vision Transformers","authors":"Huy-Tan Thai, Nhu-Y Tran-Van, Kim-Hung Le","doi":"10.1109/atc52653.2021.9598303","DOIUrl":"https://doi.org/10.1109/atc52653.2021.9598303","url":null,"abstract":"There are many kinds of cassava leaf diseases firmly harm cassava yield, including four main types as followings: Cassava Bacterial Blight (CBB), Cassava Brown Streak Disease (CBSD), Cassava Green Mottle (CGM), and Cassava Mosaic Disease (CMD). In a traditional way, leaf diseases were diagnosed intuitively by farmers. This process is inefficient and unreliable. Several studies have recently relied on deep neural networks for identifying leaf diseases. In this research, we exploit the novel model named Vision Transformer (ViT) in place of a convolution neural network (CNN) for classifying cassava leaf diseases. Experimental results show that this model can obtain competitive accuracy at least 1% higher than popular CNN models (EfficientNet, Resnet50d) on Cassava Leaf Disease Dataset. These results also indicate the potential superiority of the ViT over established methods in analyzing leaf diseases. Next, we quantize the original model and successfully deploy it onto the Edge device named Raspberry Pi 4, which can be attached to a drone that allows farmers to automatically and efficiently detect infected leaves. This result has a significant capability for many future applications in smart agriculture.","PeriodicalId":196900,"journal":{"name":"2021 International Conference on Advanced Technologies for Communications (ATC)","volume":"69 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-10-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131983195","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: 21
BMI estimation from facial images using residual regression model 残差回归模型在面部图像BMI估计中的应用
2021 International Conference on Advanced Technologies for Communications (ATC) Pub Date : 2021-10-14 DOI: 10.1109/atc52653.2021.9598340
Q. Pham, A. Luu, Thanh-Hai Tran
{"title":"BMI estimation from facial images using residual regression model","authors":"Q. Pham, A. Luu, Thanh-Hai Tran","doi":"10.1109/atc52653.2021.9598340","DOIUrl":"https://doi.org/10.1109/atc52653.2021.9598340","url":null,"abstract":"Body Mass Index (BMI) has the potential to disclose a variety of health and lifestyle concerns. Predicting BMI from facial images is an interesting but challenging problem in computer vision. Previous works focus mainly on feature extraction step of the whole BMI estimation process. Little attention has been paid to the regression module. In this paper, we propose a new architecture for the regression module which composes of multiple blocks. Each block has several sub-blocks composing of dense layer, batch-normalization, activation, dropout. In addition, we take advantage of the residual principle from ResNet by adding residual connections in the regression blocks. We integrate the proposed regression model just after the state-of-the-art feature extractor ResNet and train the network in an end-to-end manner. Extensive experiments on the VIP Attributes dataset show that thanks to the new residual regression model, the estimation error reduces up to 22% in comparison to the original method.","PeriodicalId":196900,"journal":{"name":"2021 International Conference on Advanced Technologies for Communications (ATC)","volume":"12 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-10-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132333166","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: 2
A study of 10-bit 2-MS/s Successive Approximation Register ADC with low power in 180nm technology 180nm工艺下低功耗10位2 ms /s连续逼近寄存器ADC的研究
2021 International Conference on Advanced Technologies for Communications (ATC) Pub Date : 2021-10-14 DOI: 10.1109/atc52653.2021.9598210
Nam Anh Ha, Trang Hoang
{"title":"A study of 10-bit 2-MS/s Successive Approximation Register ADC with low power in 180nm technology","authors":"Nam Anh Ha, Trang Hoang","doi":"10.1109/atc52653.2021.9598210","DOIUrl":"https://doi.org/10.1109/atc52653.2021.9598210","url":null,"abstract":"This paper presents Successive Approximation Register (SAR) ADC design in 180nm TSMC technology. The ADC can provide a high effective number of bits (ENOB), high speed and low power. At a 1.8-V supply and 2 MS/s, our design achieves an SNDR of 59.5 dB, ENOB 9.59 bit and consumes 1.17 mW, resulting in a figure of merit (FOM) of 759 fJ/conversion-step. To attain the mentioned results, the SAR architecture is proposed to use SAR ADC fully differential with S/H circuit, Capacitive DAC, Dynamic latch comparator, SAR Logic.","PeriodicalId":196900,"journal":{"name":"2021 International Conference on Advanced Technologies for Communications (ATC)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-10-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123225270","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
Modulated Wideband Converter Compressed Sensing Spectrum Reconstruction in Multi-Level Power of Transmitters Signal Scenarios 多功率发射机信号场景下的调制宽带变换器压缩感知频谱重构
2021 International Conference on Advanced Technologies for Communications (ATC) Pub Date : 2021-10-14 DOI: 10.1109/atc52653.2021.9598313
L. Nguyen, A. Fiche, R. Gautier
{"title":"Modulated Wideband Converter Compressed Sensing Spectrum Reconstruction in Multi-Level Power of Transmitters Signal Scenarios","authors":"L. Nguyen, A. Fiche, R. Gautier","doi":"10.1109/atc52653.2021.9598313","DOIUrl":"https://doi.org/10.1109/atc52653.2021.9598313","url":null,"abstract":"This paper studies the impacts of transmitters power levels on spectrum reconstruction performances in order to monitor a wideband spectrum. A sub-Nyquist blind sampling scheme based on the Modulated Wideband Converter (MWC) has been considered to achieve this task. Reconstruction performances are evaluated in simulation in terms of correct reconstruction and false alarm rates by studying several multi-level power scenarios. The study shows that the performance of reconstruction depends on the In-Band Signal-to-Noise ratio (IBSNR) of each transmitter. Based on these results, a threshold of In-Band Signal-to-Noise ratio to ensure the correct reconstruction is proposed.","PeriodicalId":196900,"journal":{"name":"2021 International Conference on Advanced Technologies for Communications (ATC)","volume":"83 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-10-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128614378","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
Convolutional Neural Network Hardware Implementation for Flower Classification 基于卷积神经网络的花卉分类硬件实现
2021 International Conference on Advanced Technologies for Communications (ATC) Pub Date : 2021-10-14 DOI: 10.1109/atc52653.2021.9598209
Trang Hoang, Thinh Do Quang
{"title":"Convolutional Neural Network Hardware Implementation for Flower Classification","authors":"Trang Hoang, Thinh Do Quang","doi":"10.1109/atc52653.2021.9598209","DOIUrl":"https://doi.org/10.1109/atc52653.2021.9598209","url":null,"abstract":"Flower classification becomes more and more important as the medical and industrial world grows. Based on that emergency, Convolutional Neural Network (CNN) proposed a way for computer to recognize flowers in place of human as the data becomes enormous. This study proposes the hardware architecture for CNN which is tested with FPGA. Numbers and type of layers, as well as their properties are also proposed for effective hardware implementation. Math functions that engine the CNN are also well-cared for the smoothness of both feed forward and back propagation processes. Measurements were taken on the proposed CNN; its accuracy and yield were verified. It also appeared that the classification accuracy of the CNN is strongly affected by the training conditions as well as the flower characteristics. This indicates that further image pre-processing can improve the accuracy of the CNN, which can be implemented separately with the CNN or embedded in CNN’s first layers by controlling the weights.","PeriodicalId":196900,"journal":{"name":"2021 International Conference on Advanced Technologies for Communications (ATC)","volume":"68 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-10-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125942049","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
Multi-model Deep Learning Drone Detection and Tracking in Complex Background Conditions 复杂背景条件下多模型深度学习无人机检测与跟踪
2021 International Conference on Advanced Technologies for Communications (ATC) Pub Date : 2021-10-14 DOI: 10.1109/atc52653.2021.9598317
Kim-Phuong Phung, Thai-Hoc Lu, Trung-Thanh Nguyen, Ngoc-Long Le, Huu-Hung Nguyen, Van‐Phuc Hoang
{"title":"Multi-model Deep Learning Drone Detection and Tracking in Complex Background Conditions","authors":"Kim-Phuong Phung, Thai-Hoc Lu, Trung-Thanh Nguyen, Ngoc-Long Le, Huu-Hung Nguyen, Van‐Phuc Hoang","doi":"10.1109/atc52653.2021.9598317","DOIUrl":"https://doi.org/10.1109/atc52653.2021.9598317","url":null,"abstract":"The recent popularity of drones with quadcopter layouts is threatening public safety and personal privacy. With the ability to hover and perform complex maneuvers even in indoor conditions, equipped with video cameras as well as capable of carrying hazardous materials, drones can truly become a security threat, especially to vulnerable organizations. Therefore, detecting and tracking drones in secured areas poses an urgent task for the surveillance system. In this paper, we design a real-time drone detection and tracking system with the combination of multiple deep learning and computer vision techniques: 1) Yolo-v4 model for detecting drones and 2) visual models for tracking drones. Besides, we have collected and labeled a larger drone dataset by mixing the existing datasets with our collected images. We evaluated three deep learning models for drone detection on this dataset and acquired the Yolo-V4 model to be the highest detection performance with AP = 34.63%. Combining this detection model and the existing visual tracking modules can boost the drone tracking up to more than 20fps for different backgrounds at around 700m by using an usual PC without GPU.","PeriodicalId":196900,"journal":{"name":"2021 International Conference on Advanced Technologies for Communications (ATC)","volume":"65 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-10-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114374472","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: 2
A High-gain and WideBand Patch Antenna for 5G Millimeter-wave Applications 5G毫米波应用的高增益宽带贴片天线
2021 International Conference on Advanced Technologies for Communications (ATC) Pub Date : 2021-10-14 DOI: 10.1109/atc52653.2021.9598276
Thi Them Truong, Thi Ngok Anh Vu, Trong Toan Do, Duc Nhat Nguyen, D. H. Hoang, V. Nguyen, M. Le
{"title":"A High-gain and WideBand Patch Antenna for 5G Millimeter-wave Applications","authors":"Thi Them Truong, Thi Ngok Anh Vu, Trong Toan Do, Duc Nhat Nguyen, D. H. Hoang, V. Nguyen, M. Le","doi":"10.1109/atc52653.2021.9598276","DOIUrl":"https://doi.org/10.1109/atc52653.2021.9598276","url":null,"abstract":"In this paper, we present a novel millimeter-wave antenna using the Grounded coplanar waveguide (GCPW)-to- Substrate Integrated Waveguide (SIW) transition. This high-gain and wideband antenna consists of four patches and each patch is fed by the SIW and a cross-shaped aperture. The antenna operates from 27.1 GHz to 31.9 GHz (S11 ≤ -10dB) with a peak gain of 10 dBi, and an efficiency of 89%.","PeriodicalId":196900,"journal":{"name":"2021 International Conference on Advanced Technologies for Communications (ATC)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-10-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129239206","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
首页 上一页 下一页 尾页
0
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整，为了账户安全，请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
请完成安全验证×
相关产品
×
本文献相关产品
联系我们：info@booksci.cn Book学术提供免费学术资源搜索服务，方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号：604180095
Book学术官方微信