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Unsupervised Identification Method of Radio-Frequency Fingerprint Based on Deep Clustering

Unsupervised Identification Method of Radio-Frequency Finger...

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intelligent Technology and Embedded systems (ICITES), international conference on

作者： Xiang Li Yu Tang Erkang Li Di Lin School of Information and Software Engineering University of Electronic Science and Technology of China Chengdu China

ISBN: (数字)9798331506292

ISBN: (纸本)9798331506308

the development of radio frequency fingerprint recognition technology is becoming increasingly mature, with abundant research and applications confirming the reliability of supervised radio frequency fingerprint technology. However, in real electromagnetic environments, particularly in areas such as intrusion detection and military confrontation, it is not always feasible to collect and analyze target signals in advance, manually annotate them, and enter the annotated signals into a fingerprint database, as obtaining authentic information about the target devices is often challenging. Additionally, unsupervised clustering of radio frequency fingerprints can identify the number of source devices, effectively detecting impersonation and identity-simulation attacks in wireless network security. In summary, research on unsupervised electromagnetic target blind recognition technology based on radio frequency fingerprints holds significant practical application significance. the method of electromagnetic target identification based on deep clustering aims to extract more effective radio frequency fingerprint features, considering the temporal characteristics of I/Q signals. this approach significantly enhances the precision of target recognition without requiring prior labeling, demonstrating superior performance in practical applications such as wireless network security, intrusion detection, and military operations. this method significantly improves the classification accuracy of radio frequency signals in real-world environments compared to previous studies.

关键词： Target recognition Wireless networks pattern classification Intrusion detection Fingerprint recognition Feature extraction Data models Security Electromagnetics Radiofrequency identification

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Robot Debater: Debate-styled Text Auto-generation System Based on Large Foundation Language Models

Robot Debater: Debate-styled Text Auto-generation System Bas...

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pattern recognition and Machine Learning (PRML), IEEE international conference on

作者： Yu Zhu Yijun Ling Xufeng Ling Jie Yang Shanghai Library (Institute of Scientific and Technical Information of Shanghai) Shanghai China Shanghai Xiangming High School Shanghai China School of Artificial Intelligence Shanghai Normal University Tianhua College Shanghai China Institute of Image Processing and Pattern Recognition Shanghai Jiaotong University Shanghai China

We use a large foundation language model, which is fine-tuned with debate corpora, to develop a robot debater application. To address the limitations of requiring immense computational power in large base language models, this study takes advantage of the Low Rank Adaption characteristic prevalent in domain expert knowledge. By applying Low Rank Adaption technology and fine-tuning with a dedicated dataset, the computational load is reduced to just one-thousandth of what is needed for a large language model, greatly expanding the application scenarios of robot debaters using large language models. In view of the characteristics of debate competitions, this model can preset a variety of debate scenarios and supports personalized debate processes. It employs intelligent voice recognition technology combined with a multi-channel voice input method, allowing for precise localization of different human debaters and improving the accuracy of voice input recognition. the system can support multiple large-scale language generation models and utilize various different voice broadcasting systems, including male and female voice styles, as well as a range of voice emotions. this model can be applied to debate competitions held in universities, high schools, and various industries. It can support human-machine debates as well as machine-to-machine debates.

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Research on UAV intelligent fault diagnosis method based on FS-SVM 4

Research on UAV intelligent fault diagnosis method based on ...

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4th international conference on pattern recognition and Artificial Intelligence, PRAI 2021

作者： Guo-Qing, Liu Xiao-Chun, Shi Ning, Wang Sichuan Engineering Technical College Department of Electrical and Information Engineering Sichuan Deyang China School of Continuing Education Sichuan Engineering Technical College Sichuan Deyang China School of Microelectronics and Solid-State Electronics University of Eledronic Science and Technology of China Sichuan Chengdu China

ISBN: (纸本)9781665413220

For problem that uncertainty of model of the flight control system of an unmanned tandem helicopter, a tandem unmanned helicopter intelligent fault diagnosis method based on support vector machine is proposed. First, the method uses fuzzy sample support vector machine (FS-SVM) diagnostics to conduct actuator fault diagnosis for flight control system. then, the fuzzy membership function is selected according to factors of the cost of the decision-making loss, damage, etc. Meanwhile, the fault pattern classification is conducted more effective, intelligent diagnosis and stability of flight control system of unmanned helicopter fault are achieved. the simulation experiment results show that the proposed algorithm can put all the fault sample accurate grouping, reduce the misjudgment phenomenon. the method can effectively carry out UAVs fault diagnosis, to ensure the safety and reliability of flight control. © 2021 IEEE.

关键词： Failure analysis

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G2OCR: Integrating Speech recognition and Optical Character recognition(OCR) for Automated Transcription of Gujarati Audio-Visual Content

G2OCR: Integrating Speech Recognition and Optical Character ...

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Ubiquitous Computing and intelligent Information systems (ICUIS), international conference on

作者： Jawad Deshmukh Sharique Shah Asif Shaikh Ashfan Bargir Salim Shaikh dept. Computer Engineering A-I-I Kalsekar Technical Campus New Panvel India

ISBN: (数字)9798331529635

ISBN: (纸本)9798331529642

the rapid boom of virtual content in neighborhood languages together with Gujarati has created demanding situations in accessibility and searchability. A sizable part of this content material, in particular audio and video, stays inaccessible to people with listening to impairments due to the lack of transcriptions. additionally, the absence of a searchable layout limits discoverability. G2OCR objectives is to provide a solution through transcribing Gujarati audio-visible content via a gadget that leverages speech recognition and optical individual recognition (OCR) technology. this approach enhances accessibility and preserves the language via making content more searchable. constructing on earlier studies, G2OCR integrates superior strategies to supply a robust device ideal for a selection of environments.

关键词： Accuracy Translation Scalability Optical character recognition Speech recognition Ubiquitous computing Hardware Real-time systems Character recognition Reliability

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recognition of Human Sleep Pressure Posture Image Using Deep Residual Networks 4

Recognition of Human Sleep Pressure Posture Image Using Deep...

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4th international conference on Communications, Information System and Computer Engineering, CISCE 2022

作者： Gao, Hailin Wei, Dapeng Yang, Fuping Chongqing University of Posts and Telecommunications Chongqing China Chongqing Institute of Green and Intelligent Technology Chinese Academy of Sciences Chongqing China Chongqing Institute of Graphene Chongqing China

ISBN: (数字)9781665498487

ISBN: (纸本)9781665498487

Good sleep is essential for people. Sleep posture has been widely studied as a means of evaluating sleep quality. this paper proposes a sleep posture recognition method based on a deep residual network. the computational complexity is reduced by introducing residual blocks and omitting the complex manual feature extraction process. An unconstrained intelligent mattress system based on a flexible pressure sensor array is developed, which provides a comfortable and high-resolution solution for long-term sleep monitoring. Five testers conducted test experiments on the smart mattress to simulate the real sleep scene. the experimental results show that our method can accurately identify the seven categories (sitting, right trunk type, right fetal type, supine, left trunk type, left fetal type, and prone), and the overall recognition rate is 98%. the results showed that the system performed well in sleep research, which provided a basis for subsequent pressure ulcer prevention and drop warning. Our research provides a set of solutions and ideas for the follow-up study of intelligent mattress systems. © 2022 IEEE.

关键词： Convolutional neural networks

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Ensemble learning-based model for fake news detection 4

Ensemble learning-based model for fake news detection

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4th international conference on pattern Analysis and intelligent systems, PAIS 2022

作者： Toumi, Chahrazad Bouramoul, Abdelkrim University of Kasdi Merbah Linati Laboratory Ouargla Algeria University of Abdelhamid Mehri Constantine 2 Misc Laboratory Constantine Algeria

ISBN: (数字)9781665461610

ISBN: (纸本)9781665461610

Technological advances in the 21st century have improved the life quality of humans worldwide. they have morphed the news-delivering sphere from a monopoly controlled by state-owned media to a free-speech-motivated playfield. News is no longer conveyed solely by journalists' articles and printed newspapers. Social media, and the Internet in general, allow anyone to share or deliver news to a large audience in real-time, very quickly and at a low cost. Unfortunately, fake news has spread widely along with true news online. Fake news can cause significant damage to companies, celebrities, and even ordinary individuals. therefore, detecting fake news has become an important task. this paper presents an ensemble learning model that uses CNN, LSTM and C-LSTM to recognize fake news. the aim is to create a model that can effectively detect fake news in both short and long news statements. For this purpose, a combination of two datasets, namely the ISOT and LIAR datasets, were used and combined into a single corpus. Evaluation metrics were used to assess the models' performance: accuracy, recall, precision, and F1-score. When compared to the state-of-the-art, the proposed model achieved good results. Compared to the state-of-the-art, the proposed model achieved competitive results. An accuracy of 89.16% and an F1 score of 95.03% were obtained on the combined corpus, a precision of 89.47% on the ISOT dataset, and an accuracy of 53.23% and an F1-score of 71.80% on the LIAR dataset. © 2022 IEEE.

关键词： Learning systems

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Decentralized Identity and Password Authentication System based on Block Chain 4

Decentralized Identity and Password Authentication System ba...

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4th IEEE international conference on Power, intelligent Computing and systems, ICPICS 2022

作者： Yun, Zhao Chao, Cui Haoling, Wang Tao, Liu Hefang, Jiang Guangdong Provincial Key Lab of Intelligent Measure and Advanced Metering of Power Grid China Southern Power Grid Research Institute Co. Ltd Guangdong Guangzhou China Shenzhen Power Supply Bureau Shenzhen China

ISBN: (数字)9781665467735

ISBN: (纸本)9781665467735

the most widely used user authentication method on the Internet is abstract password authentication, that is to say, the user and his name - password to each server established, and then use it to authenticate. Although they are widely used because of their simple operation and high experience, the security of authentication provided by them is not high, and the server operator is positioned as a trusted party who can fully control the user's identity. To solve this problem, many identity recognition systems adopt the concepts of public key encryption and decentralization,but the requirement that users generate and manage public and private key pairs, and that users often do not have such expertise, has become a key factor in the failure of PKI for many end users. To sum up, this paper proposes a decentralized identity and password authentication system (DIA) based on block chain as an identity and authentication framework. Users can register their own user name password pairs and use them as general credentials. the system provides a global name space, meaningful user names, and the ability to resist user name conflict attacks. User's identity to any server can be applied to authenticate a user, to the server without having to disclose any information relating to the password,, so it is impossible to carry out offline dictionary attack on the password. © 2022 IEEE.

关键词： Smart contract

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the intelligent safety management platform of power distribution station based on system linkage is constructed

The intelligent safety management platform of power distribu...

引用

Electronics, Circuits and Information Engineering (ECIE), international conference on

作者： Haodong Dong Guobing Shi Xian Li Detroit Green Technology Institute Hubei University of Technology Wuhan China Energy Management Center Huazhong Agricultural University Wuhan China

ISBN: (数字)9798350388312

ISBN: (纸本)9798350388329

Ensuring safety is the top priority in the power supply process. Based on the system linkage, using face recognition technology and Internet of things technology, this paper provides an unattended safety management scheme for hydropower supply and distribution sites with active discovery, system linkage and intelligent processing based on system linkage, using face recognition technology and Internet of things technology, and integrating and optimizing video surveillance, smoke detection, data transmission and access control systems, which can actively capture abnormal situations such as intrusion, smoke and operation faults, and trigger the video alarm system to provide on-site images in time.

关键词： Couplings Productivity Face recognition Safety management Power distribution Video surveillance Real-time systems

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Emotion Detection Using pattern recognition from Speech 4th

Emotion Detection Using Pattern Recognition from Speech

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4th international conference on Frontiers in Computing and systems, COMSYS 2023

作者： Somolu, Harshita Dutta, Suchibrota Ghosal, Arijit Support Analyst Cognizant Technology Solutions West Bengal Kolkata India Department of Information Technology and Mathematics Royal Thimphu College Thimphu Bhutan Department of Information Technology St. Thomas’ College of Engineering and Technology West Bengal Kolkata700023 India

ISBN: (纸本)9789819726103

Detection of emotion from speech has immense importance in our present life. Emotion detection plays an important role in music therapy of human being. But detection of emotion is a problematic task. the objective of this work is to detect the underlying emotion in the audio speech along with a high accuracy. Emotion is a very important factor in communication. It has an impact in making decisions. In the virtual world, where people depend on artificial approaches, analyzing a person’s emotion plays an important role. thus, objective is to detect the underlying emotion in a the audio speech and assign it to either joy, anger, boredom, sadness, fear, frustration, annoyance, satisfaction or neutral or any other emotion. this work considers neutral, happy, sad, and angry emotions only from speech signal. Emotions within speech mostly vary in the frequency domain. MFCC (mel-frequency cepstral coefficients) is a very good aural facet for capturing different emotions within speech. MFCC is supported by some other popular frequency domain aural facets as well as some time domain aural facets. ZCR (zero crossing rate) and STE (short time energy) have been used as time domain aural facets, and spectral roll-off, skewness, and spectral flux have been used as frequency domain aural facets. For precise observation, co-occurrence-based facets have also been considered for spectral flux as well as MFCC. For classification task, multi-layer perceptron (neural network), Random Forest, Naïve Bayes, and Logistic Regression have been used. Experimental result exhibits superiority of the work. © the Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.

关键词： Emotion recognition

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Structured Component Welding Automation intelligent Production Control System pattern Research

Structured Component Welding Automation Intelligent Producti...

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Information Technology,Big Data and Artificial Intelligence (ICIBA), international conference on IEEE international conference on

作者： Can Cui Weibing Zhou Xiaoqian Xia Bo Tang Yiyang Vocational and Technical College Yiyang China

ISBN: (数字)9798350363609

ISBN: (纸本)9798350363616

this paper primarily constructs a modular and flexible production management and control system aimed at the automated welding requirements of different enterprises. It forms a customized welding automation production control system model, relying on the existing welding work environment of the enterprise. By combining the requirements of welding automation with the characteristics of the enterprise's structured components, it provides an intelligent production management and control approach according to the production process that matches the enterprise's requirements. this serves as an example for the systematic management of intelligent welding systems in enterprises.

关键词： Production management Automation Systematics Welding Process control Production control Big Data Control systems Data models Information technology

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