2022 2nd International Conference on Bioinformatics and Intelligent Computing最新文献

{"title":"The Study of Low-velocity Non-Darcy Flow for Low-permeability Media in North China Plain","authors":"Linxian Huang, Yong Qian, Hongnian Chen, Hao Xu, Guoqing Sang, Yuhong Ma, Hao Liang, Zhizheng Liu","doi":"10.1145/3523286.3524562","DOIUrl":"https://doi.org/10.1145/3523286.3524562","url":null,"abstract":"Vertical leakage across low-permeability strata and underflow from adjacent aquifers (interaquifer flows) can be important sources of recharge for groundwater aquifer. However, in low-permeability porous media, due to small-size pores in porous media and throat radius of a few micrometers, molecular force on the solid-liquid interface increases significantly, which leads to the low-velocity non-Darcy flow. Conventional groundwater modeling methods assume that groundwater flow is described by Darcian principles which are inadequate when the flow is low-velocity non-Darcy flow. In this study, experiments are performed to explore the mathematical relation between flow rate and hydraulic gradient of low-permeability media in North China Plain of China. Mathematical equation has been obtained by curve fitting method based on experiment data.","PeriodicalId":268165,"journal":{"name":"2022 2nd International Conference on Bioinformatics and Intelligent Computing","volume":"49 2 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":"125266419","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}

{"title":"Research on Electric Stimulation System from the Angle of Control Mode","authors":"Daolong Wang, Meng Zhao, Shoushan Liu","doi":"10.1145/3523286.3524568","DOIUrl":"https://doi.org/10.1145/3523286.3524568","url":null,"abstract":"Although a single open-loop electrical stimulation system has achieved relatively good results in the field of rehabilitation treatment, it does not meet people's requirements in terms of comfort, effectiveness, and intelligence. Nowadays, closed-loop control electrical stimulation systems with biofeedback signals are rapidly developing. In this paper, we introduce the principle of electrical stimulation and biofeedback mechanism, and then the research and application of the combination of electrical stimulation system with the EMG signal, the EEG signal, and an impedance signal are described in recent years. This paper does not describe the previous literature according to the type of electrical stimulation, but innovatively describes the development of the electrical stimulation system from open-loop control to closed-loop control in terms of control methods. In various fields of medicine, electrical stimulation systems based on bioelectric signal feedback will be developed better and better in the future.","PeriodicalId":268165,"journal":{"name":"2022 2nd International Conference on Bioinformatics and Intelligent Computing","volume":"6 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":"123818809","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}

{"title":"Data fitting and simulation of hyperelastic and viscoelastic properties of soft tissue","authors":"Chong-lin Yin","doi":"10.1145/3523286.3524548","DOIUrl":"https://doi.org/10.1145/3523286.3524548","url":null,"abstract":"Real deformation modeling of soft tissue is a major difficulty in the development of virtual surgery. The solution of this difficulty requires in-depth research on the mechanical properties of soft tissue. This paper is devoted to the study of constitutive relations in soft tissue mechanical models: viscoelastic model and hyperelastic model. Through a series of experiments and calculations, the stability and applicability of various hyperelastic models were evaluated. The coefficients and exponents of Prony Series in viscoelastic generalized Maxwell model were calculated and optimized. Finally, tensile simulation was carried out based on the existing constitutive model. The results showed that the large intestine soft tissue data fitted by van der Waals model was stable and accurate; The viscoelasticity of large intestine has little influence on the whole stretching process. The viscoelasticity will replace hyperelasticity and dominate the whole stretching process when the viscosity reaches the current 100 times.","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":"123922648","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}

{"title":"Analysis on ozone distribution characteristics and quantative comparison between Chinese satellite navigation ozonesonde and Vaisala ozonesonde","authors":"Dachun Lu, J. Jin, Yong Zhang, Qing Zhou, Mengyun Lou, Xulin Liu, Debao Dong, Yue He, Xiaoping Zhou","doi":"10.1145/3523286.3524524","DOIUrl":"https://doi.org/10.1145/3523286.3524524","url":null,"abstract":"Based on the ozone sounding observation experiment in Beijing in spring 2021, systematic analysis and comparisons of characteristics and eigenvalues of ozone vertical profiles from CYT-1 (made in China) and Vaisala (made in Finland) ozonesondes and verification to ground-based Brewer spectrometer observation were carried out. The results showed that the vertical profile of ozone in spring in Beijing presented a multi-peak pattern, and the partial pressure of ozone (OPP) in the boundary layer normally decreased with height. The maximum OPP, its locating height and the height of the tropopause observed by ozonesondes were similar to studies in the mid-latitudes of the northern hemisphere. The ozone profiles observed by these two types of ozonesondes showed a good consistency in the lower troposphere, while the relative error between two ozonesondes in the stratosphere was within 10% on average. The integrated ozone column from two ozonesondes were generally lower than the results of Brewer spectrometer whereas the correction factors (Cref) of ozonesondes were mostly within the reasonable range, promising the performance reliability of both ozonesondes.","PeriodicalId":268165,"journal":{"name":"2022 2nd International Conference on Bioinformatics and Intelligent Computing","volume":"60 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":"123646715","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}

{"title":"Research on driving mechanism of total energy consumption in Jiangsu province based on the extended STIRPAT model","authors":"Linyuan Wang, Xiaoyu Yuan, Xiaoyan Hu, Yahui Ma","doi":"10.1145/3523286.3524594","DOIUrl":"https://doi.org/10.1145/3523286.3524594","url":null,"abstract":"Grasping the driving factors of energy consumption is an important research topic for effective energy saving and consumption reduction. Based on the classic IPAT model, the extended STIRPAT model is used to analyze the main driving factors of Jiangsu's energy consumption from 2005 to 2020, and quantitatively study the mechanism and influence mechanism of key driving factors on Jiangsu's energy consumption. The research conclusions are as follows: Firstly, the population size, urbanization, and foreign trade are the main factors that promote the growth of energy consumption, and the industrial structure and technological progress are the main factors that inhibit the growth of energy consumption. Secondly, the population size effect reflects Jiangsu's urban function of absorbing employment and agglomerating population on the one hand, and on the other hand illustrates the energy demand caused by population growth and the accompanying urbanization process; While import and export trade is driving economic growth, its energy-consuming import processing and export-oriented trade model has become an important contributor to Jiangsu's energy consumption growth. Finally, industrial structure and energy consumption intensity are the main contributors to curbing the growth of energy consumption during this period. The inhibitory effect of industrial structure on energy growth is stronger than energy consumption intensity. Especially in the adjustment of industrial structure, Jiangsu continues to promote industrial optimization and adjustment, and the proportion of industrial added value continues to decrease, which effectively reduces the growth of energy consumption demand. Energy utilization efficiency is another contributing factor to curb energy consumption growth. Although the energy consumption index of Jiangsu's main industrial products has reached the international advanced level, there is still a big gap between the energy intensity of Jiangsu's unit GDP and the international advanced level.","PeriodicalId":268165,"journal":{"name":"2022 2nd International Conference on Bioinformatics and Intelligent Computing","volume":"41 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":"116304300","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}

{"title":"Study on Origin traceability of Chinese Medicine Codonopsis pilosula based on stable isotope Mass Spectrometry and Machine Learning Strategy","authors":"Le Yu, Zonglin Lei, Yihuan Huang, Bin Li, Haitao Sun, Pengliang Sun","doi":"10.1145/3523286.3524520","DOIUrl":"https://doi.org/10.1145/3523286.3524520","url":null,"abstract":"Origin traceability of Chinese materia medica plays an important role in ensuring the quality and efficacy of Chinese materia medica, maintaining market order and reducing the risk of medical accidents caused by counterfeit Chinese materia medica. As one of the effective techniques of origin traceability, stable isotope technology has theoretical basis and technical advantages for origin traceability of traditional Chinese medicine. In recent years, it has also been widely used in the origin traceability of some valuable traditional Chinese medicine. Discrimination of the origin of Codonopsis Radix, the results show that stable isotope carbon (δ13C and δ15N) has obvious regional characteristics, which can effectively distinguish the origin of Codonopsis Radix; and the stable isotope mass spectrometry can distinguish Codonopsis Radix from four habitats, its accuracy rate is more than 92%. Stable isotope technique combined with PCA-LDA method can effectively trace the origin of Codonopsis Radix. It aims to promote the wide application of stable isotope technology in the origin traceability of traditional Chinese medicine, and promote the establishment and improvement of stable isotope database and traceability technology system of traditional Chinese medicine.","PeriodicalId":268165,"journal":{"name":"2022 2nd International Conference on Bioinformatics and Intelligent Computing","volume":"59 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":"126554991","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}

{"title":"Research and Implementation of Recognition Algorithm of Long-distance Runners Based on Deep Learning","authors":"Yiheng Chen, Huarong Xu","doi":"10.1145/3523286.3524546","DOIUrl":"https://doi.org/10.1145/3523286.3524546","url":null,"abstract":"The recognition of long-distance runners is mainly used to retrieve specific long-distance runner targets across video equipment in long-distance running events, which helps to improve the efficiency of the management of long-distance running events. At present, with the rapid development of artificial intelligence, lots of scholars utilize deep learning-based Person Re-Identification(Re-ID) technology to achieve long-distance runner recognition tasks. However, in practical applications, problems such as occlusion, noise, brightness changes, and color shifts usually affect the collected images of long-distance runners, thereby reducing the recognition accuracy of the existing Re-ID technology. For this reason, this paper proposes a recognition network for long-distance runners named Ldrr-net based on deep learning.Ldrr-net introduces the IGBN structure into the backbone network called Resnet50, which can reduce the adverse effects caused by the captured images, and has stronger robustness. In addition, we modify the loss, and propose Ldrr-loss to train network parameters, so that the network can better achieve intra-class aggregation and inter-class separation in the case of occlusion and similar features, and further improve the accuracy of long-distance runners' recognition. Experiments show that Ldrr-net has certain advantages in the recognition task of long-distance runners.","PeriodicalId":268165,"journal":{"name":"2022 2nd International Conference on Bioinformatics and Intelligent Computing","volume":"116 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":"131568432","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}

{"title":"Singular Value Decomposition and Manifold Regulation-based Multi-label Classification","authors":"Xuting Guo, Youlong Yang, Yuanyuan Liu","doi":"10.1145/3523286.3524543","DOIUrl":"https://doi.org/10.1145/3523286.3524543","url":null,"abstract":"In multi-label classification, an instance may contain multiple labels simultaneously, so it is applied widely in many aspects such as product recommendation, biological function prediction and document annotation. However, the high-dimensional problem of feature space and sparseness problem of label space bring great challenges to multi-label classification. To solve these problems, this paper proposes a Singular Value Decomposition and Manifold Regulation-based Multi-label Classification (SDMR) framework. In this framework, the label space is transformed into latent label space by singular value decomposition (SVD). Then an improved principal component analysis method based on manifold regularization (PCAM) is proposed, which can find a few effective features to maximize the dependence between low-dimensional features and latent labels. Finally, a powerful multi-label classifier is learned from low-dimensional spaces. To verify the effectiveness of the proposed algorithm, extensive experiments are conducted on ten real-world multi-label data sets. Compared with the traditional multi-label classification algorithms, the proposed algorithm through dual spaces reduction can achieve better classification performance.","PeriodicalId":268165,"journal":{"name":"2022 2nd International Conference on Bioinformatics and Intelligent Computing","volume":"47 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":"133695896","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}

{"title":"An automated segmentation model based on CBAM for MR image of glioma tumors","authors":"Yuzhen Cao, Qinhao Zhang, Jinqiu Li, Yuhu Wang, Dongyi Liu, Hui Yu","doi":"10.1145/3523286.3524575","DOIUrl":"https://doi.org/10.1145/3523286.3524575","url":null,"abstract":"As a serious disease endangering human life, the incidence of glioma is increasing in recent years. A semantic segmentation model of glioma based on the deep separable convolution of the attention mechanism is proposed. The model uses an encoder-decoder structure, where the encoder part uses an improved Xception backbone network. In the improved Xception backbone network, CBAM is added after each convolutional layer, thereby improving the segmentation accuracy. In the entire network structure, the Mish activation function is used instead of the ReLU activation function to ensure a smooth gradient descent during training and optimize network performance. The segmentation results of magnetic resonance image slices obtained based on the BraTS2019 data set show that the joint intersection is 83.68%, the Kappa coefficient is 90.74%, and the Dice coefficient is 0.9111, which is better than mainstream semantic segmentation models. The semantic segmentation model proposed in this paper has a high accuracy rate for glioma segmentation. This work can effectively alleviate the complex recognition work of doctors on tumors, and is of practical significance to the medical diagnosis process.","PeriodicalId":268165,"journal":{"name":"2022 2nd International Conference on Bioinformatics and Intelligent Computing","volume":"24 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":"130146922","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}

{"title":"Carbon Emission Forecast of Electric Power Industry Based on Lasso and IPSO-BP Neural Network Model","authors":"Yongli Wang, Chengcong Cai, Z. Liu, Xu Han, Suhang Yao, Chen Liu, Hekun Shen","doi":"10.1145/3523286.3524595","DOIUrl":"https://doi.org/10.1145/3523286.3524595","url":null,"abstract":"Abstract—In the development of low-carbon power, the calculation and prediction of carbon emissions in the power industry are fundamental tasks. In order to improve the prediction accuracy of carbon emissions in the power industry and achieve the energy-saving and emission reduction goals of the power sector, this paper uses the Lasso regression model to screen out five important carbon emissions influencing factors based on the panel data of the power industry from 2001 to 2020. The simulation setting of the value of each influencing factor from 2021-2035 is simulated setting. The IPSO-BP neural network model was established to predict the carbon emissions and peak time of the power industry from 20121-2035. The prediction results show that under the simulated scenario, the carbon emissions of the power industry will increase year by year from 2021 to 2029, and will reach a carbon peak of 482,937,500 tons in 2029, and then decline year by year.","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":"131044903","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}