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检索条件"任意字段=3rd International Conference on Signal and Data Processing, ICSDP 2023"

共 2951 条记录，以下是231-240 订阅

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ICGNI: ICA-based Clustering with GBDT Network Inference Using Single-cell Expression data 3

ICGNI: ICA-based Clustering with GBDT Network Inference Usin...

引用

3rd international conference on Vision, Image and signal processing (ICVISP)

作者： Li, Wenchao Zhang, Wei Zhang, Jianming Zhejiang Univ Inst Cyber Syst & Control Hangzhou Peoples R China

ISBN: (纸本)9781450376259

Biological network inference has always been one of the central topics in systems biology. Network inference can be regarded as a process of determining relations between nodes with efficient measurements. For gene regulatory networks, transcriptomic data such as single cell RNA sequencing (sc RNA-seq) have increasingly act as the main information source in reconstructing network structures. Although many methods have been proposed towards this challenge, most of them do not focus on sing-cell data and omit the characteristics of gene regulatory networks. Here, we presented a new method names ICGNI to solve these problems about gene functional clustering, network inference with single-cell data and hub genes finding. Three single cell datasets were used to evaluate the performance of our method with satisfying results.

关键词： ICA GBDT Network Inference Clustering Single Cell datasets Hub Genes

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Sequential Fusion Filter of Dissimilar Sensor data Based on IAC Algorithm

Sequential Fusion Filter of Dissimilar Sensor Data Based on ...

引用

1996 3rd international conference on signal processing(ICSP’96)

作者： Wang Yueyong Yang Weiqin Ge Xiyuan Department of Automatic Control Beijing Institute of Technology P.R.China College of Electronic and Automatic Engn Beijing Union University P.R.China

ISBN: (纸本)7505338900

Supposing that there are two dissimilar sensor(e.g. radar and infrared detector ),a Multi-Sensor data Sequential Fusion Filter(MSDSFF ) has been proposed. For maneuvering target tracking,Interactive Acceleration Compensation(IAC ) algorithm has been introduced into the MSDSFF(IAC/MSDSFF ).Considered the performance and the computational requirement, IAC/MSDSFF is an effective approach

关键词： Fusion Sensor Sequential Fusion Filter of Dissimilar Sensor data Based on IAC Algorithm Filter IAC

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Meta-data Generation of Analysis Tools and Connection with Structured Meta-data of datasets 3

Meta-data Generation of Analysis Tools and Connection with S...

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3rd international conference on signal processing and Integrated Networks (SPIN)

作者： Hayashi, Teruaki Ohsawa, Yukio Univ Tokyo Sch Engn Dept Syst Innovat Tokyo Japan

ISBN: (纸本)9781467391979

In recent years, the potential benefits of reusing and analyzing the massive quantities of data have been discussed among various stakeholders from diverse domains. In order to take advantage of results of data analyses, instead of forcing to open or share data, it is important to activate a Market of data, where users select data which they want, negotiate with data owners, and get data at reasonable conditions. In previous studies, although the methods for sharing information of datasets have been proposed, a method for sharing information of analysis tools has not been mentioned. In this paper, we discuss a method for generating meta-data of data analysis tools (Tool Jacket). We propose a method for describing the information about analysis tools as Tool Jackets in natural language using rdF. Comparing with the descriptions of DBpedia, we found that Tool Jackets obtain multiple connections with meta-data of datasets, even with a small description.

关键词： Knowledge Structuring rdF data Jacket data Analysis Tool Innovators Marketplace

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Prediction Error and Histogram Shifting Based Reversible data Hiding 3

Prediction Error and Histogram Shifting Based Reversible Dat...

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3rd international conference on signal processing Communication and Networking

作者： Tamilselvi, P. Manikandan, M. Madras Inst Technol Dept Elect Madras Tamil Nadu India

ISBN: (纸本)9781467368230

Objective of this paper is to improve the security for multimedia files and to increase the volume of hidden data in an image. The technique of reversible data hiding is capable of recovering the data embedded and the original image from a stego image without distortion. For some applications such as satellite and medical images, reversible data hiding is the valuable solution to render copyright or authentication. Reversible data hiding scheme is done based on Modification of Prediction Error (MPE). In this proposed MPE method, the histogram of prediction errors modified to prepare vacant positions for data embedding based on the secret data length. So data hiding capacity of an image is increased. The PSNR and embedding capacity of the stego image produced by MPE is more when compared to other techniques. To increase security, the secret data is encrypted using chaotic encryption algorithm. The encrypted secret message is then hide into the image. The complexity of extracting the encrypted secret data from the stego image is more. It is impossible to decrypt the data even though it is hacked. The encryption key generated is based on secret data and chaotic sequence. This improves the security of the multimedia files.

关键词： Modified Prediction Error Chaotic encryption Embedding capacity

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Design and Realization of Distributed Wireless Telemedicine Monitor Center Based on Virtual Instruments

Design and Realization of Distributed Wireless Telemedicine ...

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3rd international conference on Bioinformatics and Biomedical Engineering

作者： Tan Xin Guo Xing-ming Chen Min Guangdong Food & Drug Vocat Coll Guangzhou 510520 Guangdong Peoples R China Chongqing Univ Coll Bioengn Chongqing 400044 Peoples R China

ISBN: (纸本)9781424429011

This paper presents a new model of distributed wireless telemedicine physiological monitor center, which is developed by the Laboratory Virtual Instrument Engineering Workbench (LabVIEW) and integrates general packet radio service (GPRS) technology and signal processing with DSP processor. At the patient's location, a wireless PDA-based monitor is used to continuously acquire the patient's vital signs, including heart rate, ECG, SpO2 and so on. Through the internet and LAN, the patient's physiological signals can be transmitted in real-time to telemedicine monitor central unit, and the unit can access the data and the case history of the patient to medicine database. This paper presents our prototype implementation of signal processing based on a high-performance DSP processor on distributed nodes. The nodes analyze the patient physiology signal data which transmits from the central server through the LAN and transmits the results to telemedicine monitor central through the LAN. The results of the designing also show that the wireless telemedicine physiological monitor center model is superior to the currently used monitors both in mobility and in usability, and, therefore, is better suitable for monitor patients under the state of activities.

关键词： Telemedicine LabVIEW distributed system signal processing

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Interactive Visualization of Transformer Diagnosis Based on Multiple Views 3

Interactive Visualization of Transformer Diagnosis Based on ...

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3rd international conference on Communication, Image and signal processing (CCISP)

作者： Geng, Yujie Lv, Bingcai Guan, Ti Xu, Zheng Ma, Qiang Huang, Jungao State Grid Shandong Elect Power Co 150 Jinger Rd Jinan Shandong Peoples R China Shandong Admiss Examinat Inst West Wenhua Rd Jinan Shandong Peoples R China Nari Technol Dev Co LTD 20 Gaoxin Rd Nanjing Jiangsu Peoples R China

Transformer is one of the most expensive and critical equipment in power industry. The research on condition monitoring and fault diagnosis of transformer is significant for the stability of power system. However, transformer diagnosis involves many factors, so it is very difficult to evaluate transformer operation state effectively and accurately by single diagnosis method. In this paper, we present a novel interactive visualization model of transformer diagnosis based on multiple *** model imitates multi-angle analysis by combining multi-source information including operation information, experiment information and environmental information through multi-view collaborative visualization. data are displayed in different dimensional and a variety of interaction technology are used so that analysts can access the original data from multiple perspectives. With the help of visual perception of human eyes and intelligent cognitive ability of human brain, users can find useful information from large-scale, high-dimensional, or even incomplete data to make effective decisions.

关键词： Visualization

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The Wireless Network signal Detection Using Transfer Learning 3

The Wireless Network Signal Detection Using Transfer Learnin...

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3rd international conference on Smart Generation Computing, Communication and Networking, SMART GENCON 2023

作者： Sharma, Sorabh Centre for Interdisciplinary Research in Business and Technology Chitkara University Institute of Engineering and Technology Chitkara University Punjab India

ISBN: (纸本)9798350319125

Over the last decade, deep learning (DL) applications have exploded in the realm of wireless communications, particularly in the realms of channel estimation and signal identification. However, traditional DL methods need training for each new circumstance. As a result, updating to new wireless systems necessitates retraining. The acquisition of sufficient training data to achieve adequate detection efficiency may be time-consuming and expensive. Traditional DL methods sometimes need extensive amounts of time to train, even if substantial amounts of training data are available. Because of this, it's possible that DL approaches' efficacy and robustness may suffer. This letter presents a transfer learning architecture that may use information gained from an original system to enhance the training procedure of a target system that has access to less data for its training. In regards to channel estimation as well as signal identification, our simulation results show that the suggested solution is superior to state-of-the-art deep learning approaches. © 2023 IEEE.

关键词： DL techniques and Transfer learning signal Detection Transfer Learning Wireless Networks

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A Method of Sleeping State Recognition Based on Pressure-Body Movement-Sleeping Model 3

A Method of Sleeping State Recognition Based on Pressure-Bod...

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3rd IEEE international conference on Cloud Computing and Big data Analysis (ICCCBDA)

作者： Yan, Quya Xu, Chao Anhui Univ Sch Elect & Informat Engn Hefei Anhui Peoples R China Anhui Univ Anhui Engn Lab Agroecol Big Data Hefei Anhui Peoples R China Anhui Univ Minist Educ Key Lab Intelligent Comp & Signal Proc Hefei Anhui Peoples R China

ISBN: (纸本)9781538643013

Sleeping is essential to human health. Recognizing sleeping state accurately is an important prerequisite for analyzing sleeping quality effectively. As different states of sleeping staggered with each other, it is necessary to make the boundaries of the states clearly. The traditional methods of sleeping state recognition are less accurate and more difficult to handle. This paper uses the method based on pressure-body movement-sleeping model to identify different sleeping states. Firstly, the acquired signal of pressure is processed to get the information of body movements, and then the information is used to recognize the different sleeping states of the whole night through the sleeping judgment algorithm. Experiments show that the method used in this paper is not only simple, but also highly accurate and not susceptible to outside interference.

关键词： sleeping state recognition sensor pressure-body movement-sleeping model image processing

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Soccer Match Prediction based on Big data Mining and Multimodal Features 3

Soccer Match Prediction based on Big Data Mining and Multimo...

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3rd international signal processing, Communications and Engineering Management conference, ISPCEM 2023

作者： Zheng, Jiacheng Hangzhou Xuejun High School Hangzhou Zhejiang China

ISBN: (纸本)9798350307023

The sports industry ushered in new development and opportunities in the context of the big data era, especially the big data mining in the sports industry provides technical support for industrial iteration, promotes the innovative development of the sports industry, and accelerates the process of sports industry technology. As a popular sport in the field of soccer, it has received extensive attention from domestic and foreign fans, while data analysis and data mining in the field of soccer are also developing rapidly. Soccer game prediction is due to its many influencing factors, and there are diversity, uncertainty, ambiguity and other problems among the factors. At present, there are various ways to analyze soccer match prediction, and the rating system is not uniform, such as odds judgment, blind guessing based on historical experience, and it is not yet possible to quantify the internal relationship between features according to a set of uniform data mining process. Therefore, this paper proposes a multimodal feature extraction network based on deep learning, which can effectively extract a fusion of low-dimensional feature representations from many different modal features provided in the raw data of soccer matches. Finally, on the basis of solving the unidimensional prediction problem through traditional machine learning models and integration models, an improved Stacking integration model oriented to multidimensional features is innovatively proposed, and ultimately achieves the goal of improving the prediction accuracy and stability of soccer matches. © 2023 IEEE.

关键词： Forecasting

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A Novel signals Splitting Method for Intermittent Sampling in Deficient Period

A Novel Signals Splitting Method for Intermittent Sampling i...

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3rd international conference on Intelligent System and Knowledge Engineering

作者： Sun Zhen-hua Tian Xue-min Wang Ping China Univ Petr Coll Informat & Control Engn Dongying Shandong Peoples R China

ISBN: (纸本)9781424421961

To analyze the real-time status of the Pumping Unit by virtue of its motor electrical information, accurate data analysis was generally required, coupled with a higher sampling frequency. This leads to a higher demand of the hardware and software configuration, especially for on-line analysis. Continuous high-speed sampling brings a large number of data-processing tasks, Which makes the computer's resources lacked. By selecting appropriate schemes of intermittent highspeed data acquisition with an eye to the actual signal characteristics, the awkward situation maybe changed Considering the problem of data-processing during data acquisition, one fitting-first HHT signals splitting method is proposed. It can provide a more feasible idea to improve the analysis precision of the motor electrical information.

关键词： data acquisition

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