检索结果-内蒙古大学图书馆

HY-PC:Enabling Consistent Positioning and Communication Using Visible Light

China Communications 2023年第4期20卷 180-194页

作者： Xiangyu Liu Yaoheng Chen Lei Guo Song Song School of Information Science and Engineering Shenyang Ligong UniversityShenyang 110158China Department of Computer Science and Engineering Southern University of Science and TechnologyShenzhen 518055China School of Communication and Information Engineering Chongqing University of Posts and TelecommunicationsChongqing 400065China Hangzhou Institute of Advanced Technology Hangzhou 310056China Institute of Intelligent Communications and Network Security Chongqing University of Posts and TelecommunicationsChongqing 400065China

Visible light(VL)plays an important role in achieving high-precision positioning and low bit error radio(BER)data ***,most VL-based systems can not achieve positioning and communication,*** are two problems:1)the hybrid systems are difficult to extract distinguishable positioning beacon features without affecting communication performance,2)in the hybrid systems,the lost data bits in the inter-frame gap(IFG)are hard to recover,which affects positioning and communication ***,in this article,we propose a novel VL-based hybrid positioning and communication system,named HY-PC system,to solve the above ***,we propose the robust T-W mapping for recognizing specific Light Emitting Diodes(LEDs),which can provide stable LED recognition accuracy without adding extra beacon data and does not decrease the communication ***,we also propose the novel linear block coding and bit interleaving mechanism,which can recover the lost data bits in the IFG and improve data communication ***,we use commercial off-the-shelf devices to implement our HY-PC system,extensive experimental results show that our HY-PC system can achieve consistent high-precision positioning and low-BER data communication,simultaneously.

关键词： visible light positioning visible light communication T-W Mapping linear block coding bit interleaving

来源：评论

学校读者我要写书评

暂无评论

A Resilient Voice-Based Speaker Identification Approach Using Deep Learning 8

A Resilient Voice-Based Speaker Identification Approach Usin...

引用

8th Competitive Advantage in the Digital Economy, CADE 2022

作者： Alsaify, Baha A. Abu Arja, Hadeel S. Maayah, Bakal Y. Al-Taweel, Masa M. Alazrai, Rami Department of Network Engineering and Security Jordan University of Science and Technology Irbid Jordan German Jordanian University Department of Computer Engineering Amman Jordan

ISBN: (数字)9781839537424

ISBN: (纸本)9781839537998

Speaker recognition technology has achieved tremendous success over the years as it has become more affordable and reliable. Much research have been conducted in the speaker recognition area, but little progress has been made by the researchers. While deep learning surpassed most machine learning techniques, it has became widely used on the topics of speech technology and its new advanced solutions. In this work, we are proposing a resilient approach for speaker identification with middle-eastern accents. experiments have been carried out in the field of speaker recognition based on deep learning methods. The long short-term memory model was used with Mel-frequency cepstral coefficients. The deep neural network model was used with statistical features and Mel-frequency cepstral coefficients. A spectrogram of each sample was generated as an input for the convolutive neural networks model. © 2022 IET Conference Proceedings. All rights reserved.

关键词： Neural network models

来源：评论

学校读者我要写书评

暂无评论

Sum-Rate Maximization for RSMA-Enabled Energy Harvesting Aerial networks With Reinforcement Learning 14

Sum-Rate Maximization for RSMA-Enabled Energy Harvesting Aer...

引用

14th International Conference on Information and Communication Technology Convergence, ICTC 2023

作者： Seong, Jaehyup Toka, Mesut Shin, Wonjae Ajou University Department of Artificial Intelligence Convergence Network Suwon Korea Republic of Ajou University Department of Electrical and Computer Engineering Suwon Korea Republic of Korea University School of Electrical Engineering Seoul Korea Republic of

ISBN: (纸本)9798350313277

In this paper, we propose a joint power and precoder design framework for energy-harvesting aerial networks, where an aerial base station serves multiple users via rate-splitting multiple access (RSMA) using harvested energy. To maximize the sum-rate from the long-term perspective, we utilize a deep reinforcement learning (DRL) approach to allocate optimal transmission power at each time based on the randomness property of the channel environment, harvested energy, and battery power information. Moreover, we employ sequential least squares programming (SLSQP) to design the RSMA precoder maximizing the sum-rate with the allocated power. Numerical results show the superiority of the proposed scheme over baseline methods in terms of the average sum-rate performance. © 2023 IEEE.

关键词： DRL Energy harvesting networks RSMA

来源：评论

学校读者我要写书评

暂无评论

Time Series Facebook Prophet Model and Python for COVID-19 Outbreak Prediction

引用

computers, Materials & Continua 2021年第6期67卷 3781-3793页

作者： Mashael Khayyat Kaouther Laabidi Nada Almalki Maysoon Al-zahrani Department of Information Systems and Technology Collage of Computer Science and EngineeringUniversity of JeddahJeddah23218Saudi Arabia Department of Computer and Network Engineering Collage of Computer Science and EngineeringUniversity of JeddahJeddah23218Saudi Arabia and University of TunisElmanarTunisia

COVID-19 comes from a large family of viruses identied in 1965;to date,seven groups have been recorded which have been found to affect *** the healthcare industry,there is much evidence that Al or machine learning algorithms can provide effective models that solve problems in order to predict conrmed cases,recovered cases,and *** researchers and scientists in the eld of machine learning are also involved in solving this dilemma,seeking to understand the patterns and characteristics of virus attacks,so scientists may make the right decisions and take specic ***,many models have been considered to predict the Coronavirus outbreak,such as the retro prediction model,pandemic Kaplan’s model,and the neural forecasting *** research has used the time series-dependent face book prophet model for COVID-19 prediction in India’s various ***,we proposed a prediction and analysis model to predict COVID-19 in Saudi *** time series dependent face book prophet model is used to t the data and provide future *** study aimed to determine the pandemic prediction of COVID-19 in Saudi Arabia,using the Time Series Analysis to observe and predict the coronavirus pandemic’s spread daily or *** found that the proposed model has a low ability to forecast the recovered cases of the COVID-19 *** contrast,the proposed model of death cases has a high ability to forecast the COVID-19 ***,obtaining more data could empower the model for further validation.

关键词： COVID-19 time series analysis prediction face book prophet model python

来源：评论

学校读者我要写书评

暂无评论

network Bandwidth Prediction Method Based on Hidden Markov model in High-speed Railway 11

Network Bandwidth Prediction Method Based on Hidden Markov m...

引用

11th International Conference on Computing and Pattern Recognition, ICCPR 2022

作者： Wang, Luyao Guo, Jia Zhu, Yexuan Song, Heying Wei, Yanmin Wang, Jinao Tianjin Normal University China Wireless Network Laboratory Department of Computer and Information Engineering China

ISBN: (纸本)9781450397056

In the context of the full commercial use of 5G, high-speed rail passengers have higher and higher requirements for wireless network service quality. However, in the current high-speed rail 5G network streaming media transmission, due to the fast moving speed, the base station is frequently switched, and the user bandwidth does not match the streaming media bit rate, resulting in a poor user network experience and a poor streaming media experience. In view of the above problems, this paper focuses on the bandwidth prediction of network users in the high-speed rail environment, and proposes a bandwidth prediction algorithm High speed 5G Environment Bandwidth Predict(H5EBP) based on the hidden Markov model in different states of the high-speed rail. So as to improve the user's streaming media experience. After comparative evaluation with other existing bandwidth prediction algorithms, H5EBP can greatly improve the accuracy of bandwidth prediction, thereby improving the user's streaming media experience. © 2022 ACM.

关键词： Hidden Markov models

来源：评论

学校读者我要写书评

暂无评论

Cloud and AI-supported Mobile Information Multi-agent System for Smart Energy-saving 5

Cloud and AI-supported Mobile Information Multi-agent System...

引用

5th IEEE International Conference on Knowledge Innovation and Invention, ICKII 2022

作者： Yang, Sheng-Yuan Lunghwa University of Science and Technology Department of Computer Information and Network Engineering Taoyuan City Taiwan

ISBN: (数字)9781665479295

ISBN: (纸本)9781665479295

This study aims to explore a cloud and AI-supported mobile multi-agent system to quickly and precisely provide good quality and real-time information, provided by the Dr. What-Info system, for smart energy-saving. The illustrated system and experiments verify and validate the effectiveness and efficiency of the proposed system. © 2022 IEEE.

关键词： Multi agent systems

来源：评论

学校读者我要写书评

暂无评论

Cost and Efficiency Analysis of Steganography in the IEEE 802.11ah IoT Protocol

引用

computers, Materials & Continua 2022年第8期72卷 3929-3943页

作者： Akram A.Almohammedi Vladimir Shepelev Sam Darshi Mohammed Balfaqih Fayad Ghawbar Automobile Transportation Department South Ural State UniversityChelyabinsk454080Russia Electrical and Electronics Engineering Department Karabük University Karabük78050Turkey Department of Electrical Engineering Indian Institute of Technology RoparPunjab140001India Department of Computer and Network Engineering University of JeddahJeddah23218Saudi Arabia Faculty of Engineering Technology University Tun Hussein Onn MalaysiaPagoh Campus86400Malaysia

The widespread use of the Internet of Things(IoT)applications has enormously increased the danger level of data leakage and theft in IoT as data transmission occurs through a public *** a result,the security of the IoT has become a serious challenge in the field of information *** on the network is a critical tool for preventing the leakage of private information and enabling secure and encrypted *** primary purpose of steganography is to conceal sensitive information in any form of media such as audio,video,text,or photos,and securely transfer it through wireless *** this paper,we analyse the performance characteristics of one of the steganography techniques called Hidden Communication System for Corrupted networks(HCCNETs)for hiding sensitive *** performance analysis includes the efficiency and the cost of the system in Wireless Local Area networks(WLANs),specifically in the IEEE 802.11ah IoT *** analysis is mainly based on a two-dimensional Markov chain model in the presence of an error ***,the model considers packet arrival rate,back-off timer freezing,back-off stages,and short retry limit to ensure compliance with IEEE 802.11ah *** stresses the importance of taking these elements into consideration while modeling the efficiency and cost of the steganographic channel *** parameters often result in a high precise channel access estimation,a more accurate and efficient accuracy measurements system,efficient channel utilisation,avoidance of throughput saturation overestimation,and ensuring that no packet is served *** results demonstrate that HCCNETs is an effective approach at low cost.

关键词： IoT HCCNETs steganography markov chain model

来源：评论

学校读者我要写书评

暂无评论

Artificial intelligence learning platform in a visual programming environment: exploring an artificial intelligence learning model

引用

Educational Technology Research and Development 2024年第2期72卷 997-1024页

作者： Chang, Jui-Hung Wang, Chi-Jane Zhong, Hua-Xu Weng, Hsiu-Chen Zhou, Yu-Kai Ong, Hoe-Yuan Lai, Chin-Feng Department of Computer Science and Information Engineering Computer and Network Center National Cheng Kung University No.1 University Rd. Tainan 701 Taiwan Department of Nursing College of Medicine National Cheng Kung University No.1 University Rd. Tainan 701 Taiwan Department of Engineering Science National Cheng Kung University No.1 University Rd. Tainan 701 Taiwan Department of Computer Science and Information Engineering National Cheng Kung University No.1 University Rd. Tainan 701 Taiwan

Amidst the rapid advancement in the application of artificial intelligence learning, questions regarding the evaluation of students’ learning status and how students without relevant learning foundation on this subject can be trained to familiarize themselves in the field of artificial intelligence are important research topics. This study employed the use of a self-built AI platform (Ladder) for students to systematically learn and apply AI learning model established by the partial least squares (PLS) method to investigate the influence between variables (learning attitudes, self-regulated learning, AI anxiety, individual impact, computational thinking abilities, cognitive styles). This study was particularly conducted in the department of computer Science and Information engineering of a top national university in Southern Taiwan. The valid data were collected from 65 students (55 male students;10 female students). Furthermore, this study demonstrated the relationship between cognitive style, self-regulated learning and computational thinking. For the first time, it explored the impact of AI anxiety and completed existing research on it. The results of this study show that interest in learning positively affects learning attitudes. In addition, learning attitudes have a positive influence on each individual’s performance. Based on multiple theories and the artificial intelligence learning platform, the model proposed in this study effectively understood students’ learning status. © 2023, Association for Educational Communications and Technology.

关键词： Artificial intelligence Cognitive style Computational thinking Learning platform Self-regulated learning

来源：评论

学校读者我要写书评

暂无评论

Transferring fashion to surveillance with weak labels

引用

Neural Computing and Applications 2023年第18期35卷 13021-13035页

作者： Zheng, Qi He, Zheng Liang, Chao Chen, Jun Lin, Chia-Wen Tao, Dapeng National Engineering Research Center for Multimedia Software School of Computer Science Wuhan University Wuhan430072 China Hubei Key Laboratory of Multimedia and Network Communication Engineering Wuhan University Wuhan430072 China Collaborative Innovation Center of Geospatial Technology Wuhan430079 China Department of Electrical Engineering National Tsing Hua University Hsinchu Taiwan School of Information Science and Engineering Yunnan University Yunnan Kunming650504 China

In this paper, we address the problem of automatic clothing parsing in surveillance images using the information from user-generated tags, such as "jeans" and "T-shirt." Although clothing parsing has achieved great success in the fashion domain, it is quite challenging to parse target under practical surveillance conditions due to the presence of complex environmental interference, such as that from low resolution, viewpoint variations and lighting changes. Our method is developed to capture target information from the fashion domain and apply this information to a surveillance domain by weakly supervised transfer learning. Most target tags convey strong location information (e.g., "T-shirt" is always shown in the upper region), which can be used as weak labels for our transfer method. Both quantitative and qualitative experiments conducted on practical surveillance datasets demonstrate the effectiveness of the proposed surveillance data enhancing method. © 2020, Springer-Verlag London Ltd., part of Springer Nature.

关键词： Monitoring

来源：评论

学校读者我要写书评

暂无评论

Development of a Miniature Self-Driving Car Using SoC and NPU

Development of a Miniature Self-Driving Car Using SoC and NP...

引用

IEEE International Conference on Consumer Electronics (ICCE)

作者： Akira Kojima Department of Computer and Network Engineering Hiroshima City University Hiroshima City Japan

ISBN: (数字)9798331521165

ISBN: (纸本)9798331521172

For the ICCE2025 design contest, we are developing a miniature self-driving car system using Raspberry Pi5 and Hailo-8L Neural Processing Unit (NPU). Previously, we had implemented the object detection part on AMD/Xilinx FPGA using DPU softcore IP. Now the hardcore NPU chip dedicated to neural network processing is available, we are implementing the object detection part using the NPU and building our system. We compare the performance of the NPU implementation with that of the previous FPGA implementation.

关键词： Neural networks Robot vision systems Buildings Object detection Cameras Data models Autonomous automobiles IP networks Field programmable gate arrays Consumer electronics

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：