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检索条件"任意字段=7th International Conference on Computing in Engineering and Technology, ICCET 2022"

共 11084 条记录，以下是721-730 订阅

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Design of Intentional Eye-blink Signal Acquisition and Control System Based on Pressure Sensor 7

Design of Intentional Eye-blink Signal Acquisition and Contr...

引用

7th international conference on Intelligent computing and Signal Processing, ICSP 2022

作者： Shao, Xueqi Ning, Haonan Yang, Wenjun Niu, Yafeng Southeast University School of Mechanical Engineering Department of Industrial Design Nanjing China National Key Laboratory of Science and Technology on Aircraft Control Xi'an China

ISBN: (纸本)9781665478571

Eye-blink control means that users blink intentionally to realize human-computer interaction. An intentional eye-blink signal acquisition and control system based on flexible pressure sensor is designed, which aims to control the object through simple eye movements such as blinking and winking. the system uses two pressure sensors to collect the blink signals at the orbicularis oculi muscles of the left and right eyes respectively. the software part realizes the acquisition and recognition of six intentional eye-blink signals, and transmits blink-control instruction signals through Bluetooth, so as to realize the control of the remote-controlled vehicle. the advantage of this system is that it is not affected by illumination and does not need GUI interface for control. the availability of the system is qualified after system test. © 2022 IEEE.

关键词： Human computer interaction

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User-Centered Carpooling System Based on Compatibility and Feedback 7

User-Centered Carpooling System Based on Compatibility and F...

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2023 7th international conference On computing, Communication, Control And Automation, ICCUBEA 2023

作者： Kadam, Radha Deshmukh, Ganesh Kamble, Anjali Phalke, Aditi Khuspe, Aditi Pimpri Chinchwad College of Engineering Department of Computer Engineering Pune India

ISBN: (纸本)9798350304268

the increasing popularity of ridesharing services is mainly due to their cost-effectiveness, as passengers share a vehicle for their commute, thereby reducing the number of vehicles on the road during rush hours. Advancements in smartphone-based technology have enabled ridesharing services to match customers making similar trips in real time, resulting in reduced rates and minimal inconvenience. However, challenges such as ensuring user compatibility and security still persist. this paper addresses the issue of matching co-passenger compatibility and a feedback system that helps in future rides will enhance the overall ridesharing experience. Our systems aim to promote travel with compatible co-passengers. We strive to achieve this by collaborating with passengers who are more compatible based on features such as gender, age, smoking, and *** doing so, we aim to improve the overall ridesharing experience for passengers while reducing the number of cars on the road during peak hours. this will not only result in cost savings for passengers but also help alleviate traffic congestion and promote environmental sustainability. © 2023 IEEE.

关键词： Co-passenger compatibility Favorite passenger feedback system Environmental impact Machine learning Passenger satisfaction

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Lithium-ion Battery Remaining Useful Life Prediction Based on Hybrid Model 7

Lithium-ion Battery Remaining Useful Life Prediction Based o...

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7th international conference on Intelligent computing and Signal Processing, ICSP 2022

作者： Zou, Gang Song, Lei Yan, Zhen Chinese Academy of Sciences Key Laboratory of Space Utilization Technology and Engineering Center for Space Utilization Beijing China University of Chinese Academy of Sciences Beijing China

ISBN: (纸本)9781665478571

As a prominent new energy battery, lithium-ion batteries are widely used in various industries and fields, including energy vehicles and spacecraft. Accurate remaining useful life (RUL) prediction is an effective way to ensure the safety and reliability of batteries. Although data-driven RUL prediction methods based on data are more advantageous than traditional model-based RUL prediction methods in many tasks, there are still cases where the accuracy is not very high. To solve this problem, a hybrid model-based RUL prediction method for Li-ion batteries is proposed in this paper. this method solves the error accumulation problem encountered in the predicting process through the error compensation model and the time-varying weighting method. the experiments are conducted on a publicly available dataset of lithium-ion batteries based on the University of Maryland. the results show that the proposed method can achieve high accuracy and robustness in the RUL prediction task for lithium-ion batteries. © 2022 IEEE.

关键词： Lithium-ion batteries

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Adaptive Persymmetric Subspace Detector for Distributed Target 7

Adaptive Persymmetric Subspace Detector for Distributed Targ...

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7th international conference on Intelligent computing and Signal Processing, ICSP 2022

作者： Xie, Zikeng Jian, Tao Wei, Guangfen Huang, Xiaodong Tong, Zhuo Naval Aviation University Research Institute of Information Fusion Shandong Yantai264001 China Shandong Technology and Business University School of Information and Electronic Engineering Shandong Yantai264000 China Naval Aviation University Aviation Service College Shandong Yantai264001 China Yantai First Specialized Secondary School Shandong Yantai264001 China

ISBN: (纸本)9781665478571

In this paper, we deal with the problem of adaptive detection for distributed target in homogeneous Gaussian clutter with unknown persymmetric covariance. the distributed target is located in a multi-rank subspace and its coordinates are unknown. We devise a persymmetric subspace detector by utilizing the one-step Rao criteria. Ultimately, the numerical results show that, the proposed detector is constant false alarm rate (CFAR) with respect to unknown clutter covariance matrix. Moreover, it also has the edge on detection performance by comparing with the existing unstructured detectors, especially in training-limited scenarios. © 2022 IEEE.

关键词： Covariance matrix

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Design and Realization of a High-Precision Cavity Optomechanical Accelerometer 7

Design and Realization of a High-Precision Cavity Optomechan...

引用

7th IEEE international conference on Electronic Information and Communication technology, ICEICT 2024

作者： Xian, Chengwei Kuang, Pengju Li, Zhe Li, Xinwei Luo, Xiaoliang Ji, Zhe Wen, Guangjun Huang, Yongjun University of Electronic Science and Technology of China School of Information and Communication Engineering Chengdu China Chengdu Technological University School of Electronic Engineering Chengdu611730 China University of Electronic Science and Technology of China School of Information and Communication Engineering Chengdu611731 China University of Electronic Science and Technology of China School of Automation Engineering Chengdu China National Innovation Institute of Defense Technology Academy of Military Science PLA Beijing China Shijiazhuang Tiedao University School of Mechanical Engineering Shijiazhuang China

ISBN: (纸本)9798350384437

this paper proposes the development of a high-precision cavity optomechanical accelerometer. It is composed of a photonic crystal cavity structure and a straight-beam mechanical oscillator structure that are designed on a silicon on SOI (Silicon-On-Insulator) wafer with a top silicon thickness of 500 nm. the working principle of the cavity optomechanical accelerometer is analyzed, the mechanical modes of the mechanical oscillator and the optical modes of the photonic crystal cavity are simulated, the theoretical detection accuracy of the accelerometer is calculated to be 5.86 ug Hz, and the accelerometer samples are further fabricated by using the micro-nano-machining process. the accelerometer is characterized by high sensitivity and low noise, which can be widely used in the fields of high-precision vibration detection, inertial measurement and inertial navigation. © 2024 IEEE.

关键词： Silicon wafers

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A Detailed Review on Host Overload Detection Techniques 7

A Detailed Review on Host Overload Detection Techniques

引用

2023 7th international conference On computing, Communication, Control And Automation, ICCUBEA 2023

作者： Singh Yadav, Deepak Kumar Sinha, Bharati National Institute of Technology Department of Computer Engineering Kurukshetra India

ISBN: (纸本)9798350304268

Cloud computing (CC) is a famous paradigm which provides computing resources on request via internet. Despite its many benefits, such as scalability, cost savings, and flexibility, cloud computing is vulnerable to host overload, which occurs when a host is unable to handle the workload assigned to it. Host overload can lead to performance degradation and even system failure. thus, to overcome this issues the host overload detection technique is used. Host overload detection refers to the process of identifying when a system or server is experiencing too much demand and is unable to handle the workload efficiently. Overload detection ensures the reliable and efficient operation of systems and applications, minimizing downtime, enhancing user experience, and reducing costs. So, there are plethora of techniques developed by the researchers for host overload detection. thus, this article provides a detailed overview of the methods used for detecting overload in host for cloud, we have divided host overload detection techniques into three categories i.e. Static Utilization threshold, Regression based and Adaptive Utilization threshold based techniques. the strengths and weaknesses of each approach are analyzed, and the challenges and future directions in host overload detection are discussed. © 2023 IEEE.

关键词： Cloud computing Cloud Datacenter Host Overload QoS SLA

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Motion Information Image for Action Recognition 7

Motion Information Image for Action Recognition

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7th international conference on Intelligent computing and Signal Processing, ICSP 2022

作者： Yan, Yue Liu, Jianming Cheng, Qin Lu, Zhenshan Guilin University of Electronic Technology School of Computer Science and Information Security Guilin China Guilin University of Electronic Technology School of Electronic Engineering and Automation Guilin China

ISBN: (纸本)9781665478571

the paper proposes an effective motion information computation method, called Motion Information Image, which can aggregate motion information of multiple frames into one frame to represent the dynamic process of compact motion in video for action recognition. Motion Information Image can adopt an average sampling strategy to represent the temporal modeling relationship of the video, which allows the clever conversion of motion information into image information. Besides, we use convolutional neural networks (CNNs) combined with Motion Information Image to build a new Motion Information Image network for end-to-end action recognition. the performance of the method is improved by 2.0%~3.0% in NTU RGB+D and NTU RGB+D 120 datasets with extensive experimental validation and exhibits significant advantages for recognizing fine-grained actions. © 2022 IEEE.

关键词： Convolutional neural networks

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Deep Intra-Class Similarity Measured Semi-Supervised Learning 7

Deep Intra-Class Similarity Measured Semi-Supervised Learnin...

引用

7th international conference on Intelligent computing and Signal Processing, ICSP 2022

作者： Yang, Yang Hefei University of Technology School of Computer Science and Information Engineering Hefei China

ISBN: (纸本)9781665478571

Recently, how to handle the situation where only a few samples in the dataset are labeled has become a hot academic topic. Semi-Supervised Learning (SSL) has shown its great capacity and potential in this topic. However, existing methods tend to focus more on the relationship between unlabeled samples and labeled samples or focus on unlabeled samples' information while rarely exploring the hidden information between unlabeled data of the same category. To address this shortcoming, we use an intra-class similarity measure to exploit the information between unlabeled samples of the same class and, on this basis, introduce a new intra-class similarity loss term. In addition, to improve the accuracy of pseudo-labels in deep semi-supervised learning, we also propose an adaptive expansion of the Label Propagation algorithm. the proposed method outperforms many state-of-the-art results in CIFAR-10, CIFAR-100 and Mini-ImageNet. the experimental results show that adding the intra-class similarity loss term and the adaptive extension improvement to the deep semi-supervised learning model can effectively improve the model's performance. © 2022 IEEE.

关键词： Computer vision

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Using Bipartite Graph Embedding and Deep Learning Method Predicting RNA Protein Interactions 7

Using Bipartite Graph Embedding and Deep Learning Method Pre...

引用

7th international conference on Computer Information Science and Application technology, CISAT 2024

作者： Li, Danyu Ma, Yunci Chen, Jinhuang Xie, Jiedong Guangzhou Xinhua University School of Information and Intelligent Engineering Dongguan China The Fifth Affiliated Hospital Southern Medical University Division of Nephrology Guangzhou China

ISBN: (纸本)9798350375107

RNA-protein interaction (RPI) play an important role in biological activities. Using deep learning techniques to predict RPI can not only process complex data, but also obtain accurate results. this article first used a bipartite graph network to embed nodes between RNA and protein, obtaining similarity information and interaction data between RNA and protein. then, a convolutional neural network (CNN) was used for high-dimensional feature extraction and prediction. In addition, the graph neural network (GNN) GraphSAGE was combined to aggregate neighboring nodes and supplement ignored nodes. Finally, the results of the CNN and GNN were voted on to obtain the final prediction result. the experiment shown that our model received an AUC of 0.932, an AUPR of 0.935. All evaluation results indicated that that our model outperformed the other state-of-the-art methods. © 2024 IEEE.

关键词： Graph embeddings

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A Music Synthesizing Method for Tinnitus Sound therapy Based on LSTM and Transformer 7

A Music Synthesizing Method for Tinnitus Sound Therapy Based...

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7th international conference on Intelligent computing and Signal Processing, ICSP 2022

作者： Fang, Ancheng He, Peiyu Pan, Fan Yang, Linkun Deng, Mingyue Yu, Weichuang Sichuan University College of Electronics and Information Engineering Chengdu China

ISBN: (纸本)9781665478571

the treatment of tinnitus is a long-term process. Tinnitus sound therapy as an effective and non-intervention treatment has been widely used in clinical therapy. the music used in classical tinnitus treatments such as tinnitus masking therapy, tinnitus retraining therapy and its derivative therapies, has disadvantages like hearing unfriendly, ignoring personal preference or mismatching tinnitus frequency band and play repeatedly. therefore, this paper proposes a new method of composing music with features of hearing friendly, playing un-repeatedly and matching personal preference of the patient for tinnitus sound therapy based on deep learning methods. Also, using MIDI technology to replace instruments covering different frequency bands to match tinnitus frequency more effective. We use two neural networks based on LSTM and Transformer structure to generate MIDI music. then, analyze the results through 1/f fluctuation, fractal features and with tinnitus model based on LMS algorithm. Results indicate that the music generated by neural network has significant effect on tinnitus suppression. thus, it might provide a new method for composing music for tinnitus sound therapy. © 2022 IEEE.

关键词： Music

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