2022 2nd International Conference on Bioinformatics and Intelligent Computing最新文献_第4页

Evaluation of indoor air quality in gyms based on grey relational analysis model 基于灰色关联分析模型的体育场馆室内空气质量评价

2022 2nd International Conference on Bioinformatics and Intelligent Computing Pub Date : 2022-01-21 DOI: 10.1145/3523286.3524570

H. Hao, Guiwen Shi, Wenhao Huang, Wen-jian Luo, Hongjun Dong

{"title":"Evaluation of indoor air quality in gyms based on grey relational analysis model","authors":"H. Hao, Guiwen Shi, Wenhao Huang, Wen-jian Luo, Hongjun Dong","doi":"10.1145/3523286.3524570","DOIUrl":"https://doi.org/10.1145/3523286.3524570","url":null,"abstract":"This paper starts with both objective tests and subjective evaluations of gym air quality, The test revealed that the VOC and CO2 levels in the gym exceeded the standard by 85.4% and 73.3%, and the subjective survey found that the indoor occupants suffered from fatigue, breathlessness and other unpleasant symptoms, while the indoor air quality was not accepted by 10.2%.The grey relational analysis model is introduced here to construct a grey relational analysis model from the subjective perception of people and indoor air quality parameters. Grey correlation analysis revealed that the most significant correlation with fatigue symptoms was VOC concentration with a correlation of 0.909 and the most significant correlation with breathlessness symptoms was wind speed with a correlation of 0.941, The highest correlations with the rate of non-acceptance of indoor air quality by personnel were VOC, CO2 concentration and temperature, at 0.882, 0.804 and 0.761 respectively. Finally, according to the relevant codes and indoor air quality standards to determine the indoor air quality evaluation criteria sequence, through the grey relational analysis to determine the gym air quality in the light pollution level.","PeriodicalId":268165,"journal":{"name":"2022 2nd International Conference on Bioinformatics and Intelligent Computing","volume":"30 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-01-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115993445","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Fusion of DET and Time-Frequency Analysis for Obstructive Sleep Apnea Screening DET与时频分析融合筛查阻塞性睡眠呼吸暂停

2022 2nd International Conference on Bioinformatics and Intelligent Computing Pub Date : 2022-01-21 DOI: 10.1145/3523286.3524530

Zhixuan Cui, Chunyu Li

{"title":"Fusion of DET and Time-Frequency Analysis for Obstructive Sleep Apnea Screening","authors":"Zhixuan Cui, Chunyu Li","doi":"10.1145/3523286.3524530","DOIUrl":"https://doi.org/10.1145/3523286.3524530","url":null,"abstract":"Obstructive Sleep Apnea (OSA) is a common disease, whose main feature is repeated episodes of apnea and hypopnea during sleep, and always leading to waking up from sleep. Traditional Heart Rate Variability (HRV) analysis methods for OSA screening are divided into time domain analysis and frequency domain analysis. The time domain analysis has been widely used, it uses the statistical discrete trend analysis method to analyze the variation of heart rate and RR. The law of frequency domain analysis is to use the time domain signal of HRV to do spectrum analysis. However, traditional HRV analysis methods are linear analysis methods, and there are shortcomings such as ignoring the short-term volatility of data and being unable to measure complexity. Therefore, this experiment proposes to perform time domain analysis, frequency domain analysis, and nonlinear DET analysis on the PPG signals of 15 OSA patients and 15 normal people, a total of 30 subjects. Significance, specificity, and accuracy are contrasted. Finally, when the embedding dimension m=6 and the scale factor s=4, the DET method gets better results than the traditional time-domain and frequency-domain analysis methods on significance, accuracy and specificity of OSA screening. This provides a fresh perspective for OSA screening.","PeriodicalId":268165,"journal":{"name":"2022 2nd International Conference on Bioinformatics and Intelligent Computing","volume":"32 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-01-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114388282","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Establishment of Edible Fungus Poverty Alleviation Wisdom Platform 建立食用菌扶贫智慧平台

2022 2nd International Conference on Bioinformatics and Intelligent Computing Pub Date : 2022-01-21 DOI: 10.1145/3523286.3524507

ChaoXi Zhang

引用次数: 0

An improved scattering correction method for model analysis of cone-beam CT 一种改进的锥束CT模型分析散射校正方法

2022 2nd International Conference on Bioinformatics and Intelligent Computing Pub Date : 2022-01-21 DOI: 10.1145/3523286.3524573

Gu-Jun Kang, Yu Han, Xiaoqi Xi, Lei Li, Shuangzhan Yang, Linlin Zhu, Mengnan Liu, Siyu Tan, Bin Yan

{"title":"An improved scattering correction method for model analysis of cone-beam CT","authors":"Gu-Jun Kang, Yu Han, Xiaoqi Xi, Lei Li, Shuangzhan Yang, Linlin Zhu, Mengnan Liu, Siyu Tan, Bin Yan","doi":"10.1145/3523286.3524573","DOIUrl":"https://doi.org/10.1145/3523286.3524573","url":null,"abstract":"Due to the increased area of X-ray interaction with the objects, the cone beam computed tomography (CBCT) systems will bring severe scattering artifacts in reconstructed images, and the correction of which is quite essential to a good image quality. The scatter process modeling methods without Monte Carlo simulation proposed in recent years is relatively efficient to obtain the scattering distribution. In this paper, combined with Compton scattering cross section (K-N) formula, an improved scatter correction method is proposed for single-material objects. After setting the scattering points in the object from the reconstruction image, it is derived that the scattering ratio of any two scattering points at scattering angle 0 ° is approximately equal to the projection ratio of the object on the corresponding path of two scattering points. Therefore, the first-order Compton scattering values of all scattering points at scattering angle 0 ° can be calculated. The scattering probability of the same scattering point at different scattering angles are then normalized to obtain the scattering ratio. The scattering distribution of each scattering point was calculated by combining the scattering value at 0 ° and the included angle and distance between the scattering point and the detector. Since the attenuation coefficient selection and the attenuation path length calculation before the scattering points are omitted, the scattering estimation error is reduced, and the scattering estimation efficiency is improved. The experimental correction results for the CT images of the aircraft aluminum castings show that the proposed method can effectively restore the structural information of scattering effects, enhancing the contrast to noise ratio (CNR) and reducing the cup shadow from 9.07% to 5.49%.","PeriodicalId":268165,"journal":{"name":"2022 2nd International Conference on Bioinformatics and Intelligent Computing","volume":"8 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-01-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122039329","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Implementation and acceleration scheme of Heart sound classification Algorithm based on SOC-FPGA 基于SOC-FPGA的心音分类算法实现及加速方案

2022 2nd International Conference on Bioinformatics and Intelligent Computing Pub Date : 2022-01-21 DOI: 10.1145/3523286.3524551

Guozheng Li, Hongbo Yang, T. Guo, Weilain Wang

{"title":"Implementation and acceleration scheme of Heart sound classification Algorithm based on SOC-FPGA","authors":"Guozheng Li, Hongbo Yang, T. Guo, Weilain Wang","doi":"10.1145/3523286.3524551","DOIUrl":"https://doi.org/10.1145/3523286.3524551","url":null,"abstract":"ABSTRACT-Widespread screening of congenital heart disease is of time-consuming, labor-consuming, and difficult for rural doctors to master the skill of cardiac auscultation. A kind of machine-assisted diagnosis method was put forwarded in this paper to solve the above problems. In which a heart sound classification algorithm and acceleration plan of CNN was implemented on a small scale SoC-FPGA chip with fewer resources. In this method, heart sounds were denoised and segmented into cardio cycles first. Then STFT transformation was done for time-frequency feature extraction. The time-frequency features were used to train the CNN model to extract network model parameters. In hardware implementation, the parallelism of CNN was corresponding to FPGA parallel hardware. In order to make acceleration of the algorithm, loop unrolling, fixed-point of model parameter, and reducing global memory access were done. The experimental results show that the classification speed is 3.13 times as much as one of CPU at the same conditions with the classification accuracy not any dropping significantly. It provides an offline solution for the machine-assisted screening of congenital heart disease.","PeriodicalId":268165,"journal":{"name":"2022 2nd International Conference on Bioinformatics and Intelligent Computing","volume":"81 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-01-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126267156","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 1

An Research on Online Counseling Platform Based on the Artificial Intelligence Technology 基于人工智能技术的在线咨询平台研究

2022 2nd International Conference on Bioinformatics and Intelligent Computing Pub Date : 2022-01-21 DOI: 10.1145/3523286.3524526

Lulu Liu, Yan Liu

引用次数: 1

QRS complex recognition based on adaptive wavelet threshold and Hilbert transform for continuous ECGs 基于自适应小波阈值和希尔伯特变换的连续心电图QRS复合体识别

2022 2nd International Conference on Bioinformatics and Intelligent Computing Pub Date : 2022-01-21 DOI: 10.1145/3523286.3524579

Xiaolei Chen, Tingting Sun, Yilin Xie, Dunan Li, Muhammad Saad Khan

{"title":"QRS complex recognition based on adaptive wavelet threshold and Hilbert transform for continuous ECGs","authors":"Xiaolei Chen, Tingting Sun, Yilin Xie, Dunan Li, Muhammad Saad Khan","doi":"10.1145/3523286.3524579","DOIUrl":"https://doi.org/10.1145/3523286.3524579","url":null,"abstract":"The wearable continuous ECG monitoring and cardiovascular disease detection system has the characteristics of strong noises and big continuous data. It puts forward higher requirements on the accuracy and efficiency of the QRS recognition algorithm. The currently used QRS detection algorithms still have the problem of missed detection and false detection for continuous ECG data. Therefore, a fast R-peak recognition method based on self-adaptive wavelet threshold and Hilbert transform is proposed for processing noisy continuous ECGs. First, wavelet self-adaptive threshold filter is used to denoise the dynamic ECGs, and then the first-order difference, Shannon energy envelope extraction, Hilbert transform and self-adaptive threshold back-check technology are employed for R-peak detection. Using the proposed method, experimental results show that the accuracy, sensitivity, and specificity of the MIT-BIH arrhythmia database are 99.79%, 99.92%, and 99.87%, respectively. Using the PhysioNet/CinC Challenge 2014 dynamic ECG database, the accuracy, sensitivity and specificity are 96.89%, 97.92% and 98.92%, respectively. Furthermore, the realtime ECGs collecting from the portable ECG detector mECG-101 are also used to evaluate the method. The experimental results show that the accuracy, sensitivity and specificity reach to 97.75%, 98.25% and 99.47%, respectively. Compared with Pan-Tompkins algorithm and wavelet transform algorithm, the proposed method has higher detection accuracy and generalization ability, especially for the wide and low-amplitude QRS complexes.","PeriodicalId":268165,"journal":{"name":"2022 2nd International Conference on Bioinformatics and Intelligent Computing","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-01-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129487233","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

An Intelligent Test System for a Radar Array Antenna 雷达阵列天线智能测试系统

2022 2nd International Conference on Bioinformatics and Intelligent Computing Pub Date : 2022-01-21 DOI: 10.1145/3523286.3524583

Shangguang Liu, Chongwei Chen, Yonglei Zhong, Kai Wang, Zhenshuai Yuan

引用次数: 0

Calibration Procedure for Radio Frequency Ablation Instruments 射频消融仪器校正程序

2022 2nd International Conference on Bioinformatics and Intelligent Computing Pub Date : 2022-01-21 DOI: 10.1145/3523286.3524553

Tingting Ren, Yang Xu, Ying Liu, Cheng Zeng, Yanxiang Fu

引用次数: 0

iMSTK-based Microwave Ablation Training System for Liver Tumors 基于imstc的肝脏肿瘤微波消融培训系统

2022 2nd International Conference on Bioinformatics and Intelligent Computing Pub Date : 2022-01-21 DOI: 10.1145/3523286.3524532

Huiqi Tian, Mingwei Gao, Tianyu Fu, Jingfan Fan, Hong Song, Jian Yang

{"title":"iMSTK-based Microwave Ablation Training System for Liver Tumors","authors":"Huiqi Tian, Mingwei Gao, Tianyu Fu, Jingfan Fan, Hong Song, Jian Yang","doi":"10.1145/3523286.3524532","DOIUrl":"https://doi.org/10.1145/3523286.3524532","url":null,"abstract":"In this study, a training system was designed for liver tumor ablation based on iMSTK, a framework for the development of surgical simulation, to meet the training requirements of doctors for the microwave ablation surgery of liver tumors. Important organs such as the skin, bone, blood vessels, tumor, and liver were subjected to surface modeling and tetrahedral meshing. The constraint of the model based on position dynamics was added to the liver to simulate the flexible deformation of soft tissues under external forces. According to the Pennes bioheat equation, the release of the microwave ablation thermal field and the resulting ablation area were modeled. Then, a haptic device was combined to set different forces for various tissues and organs and simulate the force feedback effects of touching tissues and organs. Various modules were eventually coupled together to form a complete simulation system of liver tumor ablation. Results shown that the proposed training system could provide real and effective simulation for the microwave ablation of liver tumors. It also met the requirements for the preliminary training of doctors.","PeriodicalId":268165,"journal":{"name":"2022 2nd International Conference on Bioinformatics and Intelligent Computing","volume":"27 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-01-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125765078","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0