Proceedings of the 6th International Conference on Biomedical Engineering and Applications最新文献

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The Relationship Between Pulse Rate and Mandarin Tone Recognition: A Preliminary Study with CCi-Mobile Cochlear Implant Research Processor 基于cci -移动人工耳蜗研究处理器的脉搏率与普通话声调识别关系的初步研究
Yefei Mo, Huali Zhou, Q. Meng, Peina Wu
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引用次数: 0
Development Trend of 3D Printing Bone Tissue Engineering Scaffold Based on Black Phosphorus Nanosheets 基于黑磷纳米片的3D打印骨组织工程支架的发展趋势
Lianyi Huo, Xuetao Shi, Xing Wang, Yuchen Yao, Yiwei Liu
{"title":"Development Trend of 3D Printing Bone Tissue Engineering Scaffold Based on Black Phosphorus Nanosheets","authors":"Lianyi Huo, Xuetao Shi, Xing Wang, Yuchen Yao, Yiwei Liu","doi":"10.1145/3543081.3543104","DOIUrl":"https://doi.org/10.1145/3543081.3543104","url":null,"abstract":"∗ With the increasingly serious problem of population aging, the number of patients with bone defects caused by degenerative dis-eases is gradually increasing, which has brought great pressure to the medical system of various countries. Bone tissue engineering scaffolds made of traditional biomaterials are easy to produce problems such as poor fit, wear and corrosion after repairing bone tissue, especially it is difficult to form bone tissue with biological function. In this paper, the research status of 3D printed bone tissue engineering scaffold technology based on black phosphorus nanosheets (BPNs) is deeply analyzed. It is considered that BPNs have unique advantages and development prospects compared with other traditional bone tissue scaffold materials (such as bioceramics and metal materials). The combination of BPNs and 3D-printed bone tissue engineering scaffolds can overcome the defects of traditional scaffold manufacturing methods and achieve a breakthrough in the personalized, accurate, mechanical strength, pore regulation and spatial structure complexity of scaffolds. This study provides a salutary lesson for the design of 3D printed bone tissue engineering scaffolds and the improvement of antibacterial and stability based on BPNs.","PeriodicalId":432056,"journal":{"name":"Proceedings of the 6th International Conference on Biomedical Engineering and Applications","volume":"19 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-05-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123800491","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
PResearch on Biological Species Improvement Technology Based on Genetic Recombineering 基于基因重组的生物物种改良技术研究
Xuanting Li, Peize Zhao
{"title":"PResearch on Biological Species Improvement Technology Based on Genetic Recombineering","authors":"Xuanting Li, Peize Zhao","doi":"10.1145/3543081.3543095","DOIUrl":"https://doi.org/10.1145/3543081.3543095","url":null,"abstract":"Gene recombination is an essential feature in biological evolution. Genetic recombination is an essential mode of species improvement in microorganisms, plants, and animals. A chromosome consists of a sequence of genes, and a genome is a collection of chromosomes. This paper uses computer signal recognition technology to discover DNA base sequences in gene recombination. Further, the paper uses a filtered deep learning algorithm to locate the starting fragment of gene recombination. In this way, the paper has a predictive model of genetic recombination. Finally, this paper uses the algorithm model to predict the genetic recombination fragments in biological species improvement. The research found that the algorithm's accuracy proposed in this paper is 98.5%.","PeriodicalId":432056,"journal":{"name":"Proceedings of the 6th International Conference on Biomedical Engineering and Applications","volume":"119 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-05-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134018950","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
SVEM: A Signal Variation Elimination Model for EEG Emotion Recognition 基于SVEM的脑电情绪识别信号变异消除模型
Zhaohong Sun, Haomin Li, H. Duan
{"title":"SVEM: A Signal Variation Elimination Model for EEG Emotion Recognition","authors":"Zhaohong Sun, Haomin Li, H. Duan","doi":"10.1145/3543081.3543085","DOIUrl":"https://doi.org/10.1145/3543081.3543085","url":null,"abstract":"Motivated by the non-stationarity characteristics of electroencephalograph (EEG) signals, we propose a signal variation elimination model (SVEM) for emotion recognition. The proposed SVEM enables to capture the topological structures of different EEG channels due to the utilized graph neural network (GNN). Two tricks are proposed to reduce signal variations and improve the model generalization. Firstly, the proposed SVEM is pre-trained by a mask-generation supervised learning where we randomly mask several signal channels in GNN and then generate them. Secondly, the proposed SVEM is fine-tuned by incorporating a domain classifier to reduce the distribution shift between the training and testing sets. To further reduce the subject signal variations of the training set, a subject classifier is incorporated in the fine-tuning process of SVEM. The performance of SVEM is evaluated on the real-world dataset SEED. Experiment results demonstrate that the accuracy of SVEM achieves 87% and 71%, on subject-dependent and subject-independent tasks, respectively.","PeriodicalId":432056,"journal":{"name":"Proceedings of the 6th International Conference on Biomedical Engineering and Applications","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-05-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128876314","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
Proceedings of the 6th International Conference on Biomedical Engineering and Applications 第六届生物医学工程与应用国际会议论文集
{"title":"Proceedings of the 6th International Conference on Biomedical Engineering and Applications","authors":"","doi":"10.1145/3543081","DOIUrl":"https://doi.org/10.1145/3543081","url":null,"abstract":"","PeriodicalId":432056,"journal":{"name":"Proceedings of the 6th International Conference on Biomedical Engineering and Applications","volume":"10 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128444949","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
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