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Speech-based Depression Detection Using Unsupervised Autoencoder 7

Speech-based Depression Detection Using Unsupervised Autoenc...

引用

7th international conference on Signal and Image processing, ICSIP 2022

作者： Sun, Guangyao Zhao, Shenghui Zou, Bochao An, Yubo Beijing Institute of Technology School of Information and Electronics Beijing China University of Science and Technology Beijing School of Computer and Communication Engineering Beijing China

ISBN: (数字)9781665495639

ISBN: (纸本)9781665495639

With the rapid development of society, over three hundred million people worldwide suffer from depression, which has become one of the most serious health problems in the world. As we know, depression detection is of great importance for its timely treatment. In this paper, a speech-based depression detection method using unsupervised autoencoder is proposed. Most previous methods encode the frame-level speech features into sentence-level features with statistical functions which lead to the loss of the temporal information between frames. To solve this, we propose an unsupervised network based on transformer. the unsupervised network is adopted to obtain the audio embedding vector of an audio segment from depressed or non-depressed people. then the embedding audio vector is used for depression detection. the experimental results show that the proposed method achieves superior performance on both the English database DAIC and our self-built Chinese database CMDC. © 2022 IEEE.

关键词： Embeddings

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XLM-RoBERTa Based Sentiment Analysis of Tweets on Metaverse and 6G 15

XLM-RoBERTa Based Sentiment Analysis of Tweets on Metaverse ...

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15th international conference on Ambient Systems, Networks and Technologies Networks, ANT 2024 / the 7th international conference on Emerging Data and Industry 4.0, EDI40 2024

作者： Gaurav, Akshat Gupta, Brij B. Sharma, Sachin Bansal, Ritika Chui, Kwok Tai Ronin Institute MontclairNJ United States Department of Computer Science and Information Engineering Asia University Taichung413 Taiwan State Bank of India India Insights2Techinfo India Hong Kong Hong Kong

this study employs the XLM-RoBERTa transformer model to perform sentiment analysis on Twitter data, focusing on discussions around the Metaverse and 6G technologies. through a comprehensive dataset, we analyzed tweets to discern public sentiment, classifying them into negative, neutral, positive, and a calculated final sentiment score. Our results demonstrate a predominance of neutral and positive sentiments, with negative sentiments less frequent but impactful when present. the analysis, visualized through bar charts, box plots, and histograms, suggests a cautiously optimistic public view towards these cutting-edge technologies. the research highlights the effectiveness of XLM-RoBERTa in processing complex language data and contributes to understanding the public perception that may influence the adoption and development of the Metaverse and 6G. © 2024 Elsevier B.V.. All rights reserved.

关键词： Sentiment analysis

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Recognition Of Facial Images Using Convolution Based Multilayer Perceptron Model 7

Recognition Of Facial Images Using Convolution Based Multila...

引用

7th IEEE international conference on Computational Systems and information technology for Sustainable Solutions, CSITSS 2023

作者： Agarwal, Khushboo Dixit, Manish Mits Department of Computer Science and Engginering Gwalior India

ISBN: (纸本)9798350343144

In this paper, C-MLP based Network is used to restore the image and recognize the facial images, for the purpose of resolving the face recognition issue when the facial images are severely occluded. Multilayer perceptrons (MLPs) provide the ability to effectively represent intricate, non-linear associations within datasets. In Face recognition techniques, faces can manifest diverse non-linear fluctuations as a consequence of factors such as variations in lighting conditions, facial emotions, and position. Multilayer perceptrons (MLPs) have the capability to acquire the ability to detect and represent these detailed patterns, rendering them well-suited for processing the intrinsic intricacy present in facial data. the ICA-NNMF feature extraction approach is employed in this model to extract features, and Convolution based MLP is deployed to recognize faces. Users must modify the reconstructing result in compliance to their particular interests or the properties of the restored image since the perceptual quality of the image is more or less subjective. With this approach, users can regulate the continuous transition between several objectives, such as the trade-off between noise reduction and detail preservation. this model ensures the normal distribution along with parametric optimization contributing to the high performance for restored face recognition. thus, It is analyzed and described how well the framework performs when correctly identifying faces in the generated images. © 2023 IEEE.

关键词： Face recognition

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Grover algorithm circuit optimization and noise analysis on integer factorization 7

Grover algorithm circuit optimization and noise analysis on ...

引用

7th international conference on Intelligent Computing and Signal processing, ICSP 2022

作者： Song, Hui-Chao Liu, Xiao-Nan Jiang, Duo An, Jiale University of Information Engineering State Key Laboratory of Mathematical Engineering and Advanced Computing Zhengzhou China

ISBN: (纸本)9781665478571

the classical computer is restricted by Moore's law and other factors into the development bottleneck, quantum computer by virtue of its natural acceleration advantage into the field of vision. Quantum computing can achieve the acceleration effect compared with classical computing in many fields. In the field of integer decomposition, Shor algorithm can be solved in polynomial time, which breaks the security of RSA public key cryptosystem. However, the quantum bits (logn + 2, where n is the integer to be decomposed) required by Shor algorithm are difficult to be realized on today's quantum computers. therefore, the hybrid quantum algorithm model of "classical + quantum (Grover algorithm)"is tried to realize the decomposition of large integers. In this paper, based on the previous hybrid quantum algorithm model, considering that the continuous accumulation of errors in the circuit of the quantum algorithm will lead to the failure of the algorithm as the depth increases, part of the circuit of the quantum algorithm oracle is optimized to reduce the consumption of the depth, quantum gate and quantum bit in the circuit of the quantum algorithm, so as to make it easier to run on the actual quantum computer. By running the optimized quantum circuit on the back end of the simulator of IBM Q quantum cloud platform, and trying to add thermal relaxation and depolarization noises to the circuit, the influence of different noises on the circuit under different iterations was explored. © 2022 IEEE.

关键词： Quantum computers

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Transmit beam control in low-altitude slow-moving small targets detection 7

Transmit beam control in low-altitude slow-moving small targ...

引用

7th international conference on Intelligent Computing and Signal processing, ICSP 2022

作者： Xu, Chunbao Jin, Songpo Ding, Zhoupeng Kuang, Qi Zhuang, Shanna Li, Hongtao Nanjing University of Science and Technology School of Electronic and Optical Engineering Nanjing China China Electronics Technology Group Corp 54th Research Institute Shijiazhuang China Shijiazhuang Tiedao University School of Information and Science Technology Shijiazhuang China

ISBN: (纸本)9781665478571

Moving targets on the ground would affect the radar detection performance for low-altitude, slow-moving, and small (LSS) targets. this paper proposes a transmit beam control algorithm for phased array radar to minimize the radiation directed at the ground. By minimizing weighted vector norm and implementing different notch level, the admired beam can achieve a deep notch in the region associated with ground moving targets and maintains good mainlobe and sidelobe performance. Moreover, the designed beam is insensitive to array imperfections. the optimization problem can be converted to a second-order cone programming (SOCP) problem and solved with readily available solvers. In addition, the amplitude normalization is implemented on the optimized weight vector to make full use of emission power. Simulation results verify that the proposed approach can synthesize transmit beams that can meet the requirements of mainlobe loss minimization, low sidelobes on the ground side, and deep notch for the ground moving targets. © 2022 IEEE.

关键词： Tracking radar

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Nondestructive Detection of Apple Sugar Degree Based on Smartphones 7

Nondestructive Detection of Apple Sugar Degree Based on Smar...

引用

7th international conference on Intelligent Computing and Signal processing, ICSP 2022

作者： He, Zhiquan Xiao, Yihao Wang, Qi Nanchang Hangkong University School of International Education Nanchang330000 China

ISBN: (纸本)9781665478571

this paper designed a portable detection device for apple sugar content combined with a mobile phone-based on near-infrared spectroscopy technology. We aimed to determine the band range suitable for apple sugar content detection by selecting the characteristic band and completing the high-efficient, portable, and low-cost non-destructive detection of apple sugar content through the combination with a mobile phone. Cell phone cameras can capture effective near-infrared diffuse reflectance spectra. To realize the conversion, we select 15 different kinds of apple (red Fuji, rock candy hearts, marshal Plotkin) in four different parts of the acquisition. the beneath refractometer is used to measure the spectral information standard. the 60 points of data collected were used to establish a regression prediction model of apple sugar content by the partial least square method. Finally, two apples of the above three kinds were selected to test the model. the average relative error obtained was 5.07%, and the minimum measurement error of the rock candy heart was 2.92%. © 2022 IEEE.

关键词： Fruits

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Polarimetric SAR intelligent classification based on dimensionality reduction and filtering preprocessing 7

Polarimetric SAR intelligent classification based on dimensi...

引用

7th international conference on Intelligent Computing and Signal processing, ICSP 2022

作者： Yu, Xuan Zhang, Fang Yin, Zhiping Zhang, Qingyuan Hefei University of Technology School of Microelectronics Hefei China Hefei University of Technology Academy of Opto-Electric Technology Hefei China University of Science and Technology of China School of Information Science and Technology Hefei China

ISBN: (纸本)9781665478571

Polarized synthetic aperture radar (SAR) high resolution remote sensing image technology has been widely used in commerce, agriculture, ocean transportation and other fields. the results show that the Deep Learning method can better mine the image information of high-resolution polarimetric SAR image than the traditional method. In this paper, a new method is proposed, which performs image preprocessing before substituting deep learning framework to improve classification accuracy. Firstly, Pauli, H/A/Alpha, Freeman, Yamaguchi and other characteristic components obtained by polarization decomposition were processed by principal component analysis (PCA) dimensionality reduction algorithm and three images were obtained. Wavelet decomposition and reconstruction, anisotropic filtering and grayscale of each image were performed respectively, and the three images were fused. Finally, the result graph is input into DeepLabV3+ network architecture for training. the data adopted in this paper is Flevoland regional image. By comparing 13 features and 17 features, the training results are brought into DeeplabV3+ network architecture with or without using the proposed method. the results show that the Kappa coefficient of deep learning classification is significantly increased by 2.2-2.3% after using the descending and anisotropic filtering, which proves that the proposed method can improve the classification accuracy of polarimetric SAR from the perspective of image preprocessing without increasing stacking. © 2022 IEEE.

关键词： Synthetic aperture radar

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Real-Time Soil Moisture Sensing Using Arduino for Automated Plant Irrigation System 7th

Real-Time Soil Moisture Sensing Using Arduino for Automated ...

引用

7th IFIP TC 12 international conference on Computational Intelligence in Data Science, ICCIDS 2024

作者： Vijayalakshmi, R. Deepalakshmi, R. Madhavan, T.S. Siva Balasubramanian, G. Department of Computer Science and Engineering Velammal College of Engineering and Technology Tamil Nadu Madurai India Velammal College of Engineering and Technology Tamil Nadu Madurai India

ISBN: (纸本)9783031699856

Irrigation constitutes a fundamental element of agriculture and food production. Outdated methods in both developing and underdeveloped nations result in significant water wastage during this crucial process. this project proposes an inventive method for automating the control of water release valves in micro irrigation networks with prediction of required humidity by weather condition using artificial intelligence (AI). this system seeks to close the gap between water supply and crop demand while also optimizing resource use and reducing environmental impact by using AI-powered soil moisture monitoring and decision-making processes. this project address the key factors like varying demand of water for crops based upon the growth stage, weather conditions and plant type. this reducing the usage by adopting the method of micro irrigation which reduces the usage of water by 70–80% than conventional methods of irrigation. this project also provides a user-friendly interface to efficiently control the watering of plants when needed by the user. © IFIP international Federation for information processing 2024

关键词： Decision making

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Research and Application of Customer Side Security Energy Use Monitoring technology Based on Artificial Intelligence and Digital Power Room 7th

Research and Application of Customer Side Security Energy Us...

引用

7th international conference on Communication, Device and Networking, ICCDN 2024

作者： Li, Jincan Dai, Ying Zhu, Wanting Li, Pei Yang, Xiaqin Liu, Ying Marketing Department of Guangxi Power Grid Co. Ltd. Guangxi Nanning530023 China

ISBN: (纸本)9789819764648

With the development of the power industry, smart grid has become the development direction of the future global power grid. With the help of a new generation of information technology, the collection of power consumption data at the power terminal, and the analysis of power consumption data, and then timely prediction or identification of electrical faults, timely warning to the user or automatic cut off the power supply, can effectively reduce the risk of electrical faults caused by accidents, reduce the loss caused by accidents. therefore, this paper mainly introduces the development and implementation of intelligent electricity safety monitoring system and fault arc identification algorithm. Firstly, the intelligent electricity safety monitoring system is designed. the main functions of the system are as follows: terminal data collection function, LoRa network wireless transmission function, intelligent gateway data exchange function, server human–computer interaction function and intelligent processing algorithm function. Finally, through the system test, it is found that the intelligent electricity monitoring system can identify the fault arc with 96% accuracy, which is suitable for customer-side safety energy monitoring. through the research and application of intelligent electricity safety monitoring technology, users can grasp the status information and operation of electrical equipment in real time, and establish a perfect operation and maintenance management system based on intelligent electricity monitoring technology. © the Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Gateways (computer networks)

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A Blockchain-based and Privacy-Protected Method for Sharing of BIM Big Data 7

A Blockchain-based and Privacy-Protected Method for Sharing ...

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7th international conference on Cloud Computing and Big Data Analytics, ICCCBDA 2022

作者： Wang, Hongwei Hao, Xiaohan Yin, Lian Gong, Peisong Xiong, Feng Ren, Wei Wuhan Municipal Road and Bridge Co. Ltd Wuhan430050 China School of Software University of Technology Sydney UltimoNSW2007 Australia School of Computer Science China University of Geosciences Wuhan430074 China School of Economics and Management China University of Geosciences Wuhan430074 China School of Business Administration Zhongnan University of Economics and Law Wuhan430073 China Hubei Key Laboratory of Intelligent Geo-Information Processing Wuhan430074 China

ISBN: (纸本)9781665487115

Currently, cloud computing and big data are largely applied in smart construction, or so-called industrial Internet of things 4.0. Building information Model (BIM) performs as an elemental information and data unit, which is extensively employed in entire construction processes (lifespan) and inter-Acted with various entities including investors, employers, design institutes, construction companies, and monitors. they thus can achieve quantitative computing, measurement, and managements by sharing BIM data. the accumulation of BIM data will finally approach to a big data for construction intelligence. However, sharing BIM big data may be subtle in terms of privacy leakage, since BIM data may enclose the critical infrastructure information, homeland security data, structure parameters, and design intellectual property. It thus is of urgent importance to protect privacy in the BIM data sharing. In this paper, we propose a blockchain based method to protect data privacy in BIM data sharing, which can be applied for guaranteeing the information security in next generation industrial Internet of things for smart construction. © 2022 IEEE.

关键词： Data privacy Cloud computing Computational modeling information security Big Data Data models Blockchains

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