2022 19th International Computer Conference on Wavelet Active Media Technology and Information Processing (ICCWAMTIP)最新文献_第4页

Optimizing Drug Screening with Machine Learning 用机器学习优化药物筛选

2022 19th International Computer Conference on Wavelet Active Media Technology and Information Processing (ICCWAMTIP) Pub Date : 2022-12-16 DOI: 10.1109/ICCWAMTIP56608.2022.10016572

Chen Lin, Zhou Xiaoxiao

{"title":"Optimizing Drug Screening with Machine Learning","authors":"Chen Lin, Zhou Xiaoxiao","doi":"10.1109/ICCWAMTIP56608.2022.10016572","DOIUrl":"https://doi.org/10.1109/ICCWAMTIP56608.2022.10016572","url":null,"abstract":"Drug screening is the process by which potential drugs are identified and optimized before the selection of a candidate drug to progress to clinical trials. To find drug candidates with good pharmacokinetic properties and adequate safety in the human body, pharmaceutical researchers need to comprehensively consider the biological activity of compounds and their influence on the human body. More specifically, only when the compound has good biological activity and ADMET (i.e., absorption, distribution, metabolism, excretion, and toxicity) properties can it qualify as a drug candidate.To improve the efficiency of drug screening, we propose a drug candidate screening approach based on machine learning methods, which not only discovers appropriate compounds but also reveals the potential effects of molecular descriptor (i.e., features) values on the properties of compounds. First, an accurate prediction model is trained based on independent variables (i.e., feature values) and dependent variables (i.e., bioactivity values or ADMET properties). Second, we use a feature interpretation algorithm to pick out features with a significant impact on the dependent variables. Third, we search for the approximate optimal values of these important features and analyze their numerical ranges that are beneficial to obtaining better bioactivity and ADMET properties. Experimental results demonstrate that our scheme is accurate, efficient, and reliable.","PeriodicalId":159508,"journal":{"name":"2022 19th International Computer Conference on Wavelet Active Media Technology and Information Processing (ICCWAMTIP)","volume":"38 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123282439","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 Overview of Spikingneural Networks 脉冲神经网络概述

2022 19th International Computer Conference on Wavelet Active Media Technology and Information Processing (ICCWAMTIP) Pub Date : 2022-12-16 DOI: 10.1109/ICCWAMTIP56608.2022.10016558

Tian Jie, Liao Jianping, Wang Guangshuo, Xiao Fei

{"title":"An Overview of Spikingneural Networks","authors":"Tian Jie, Liao Jianping, Wang Guangshuo, Xiao Fei","doi":"10.1109/ICCWAMTIP56608.2022.10016558","DOIUrl":"https://doi.org/10.1109/ICCWAMTIP56608.2022.10016558","url":null,"abstract":"In recent years, Artificial neural network has made great progress in image, machine perception and other aspects, and has a very good performance in the scope of deep learning. As a highly intensive neural network, Artificial neural network's performance has gradually reached saturation in today's increasing network demand, but its efficiency and consumption are still relatively large. Therefore, more and more attention has been paid to the peak neural network with low energy consumption in operating equipment. Spiking neural networks shows good performance of low power consumption when running on hardware. More and more researchers begin to use Spiking neural networks to study the performance of image recognition and other aspects. Although Spiking neural network has many limitations in accuracy and training difficulty, it has stimulated the research enthusiasm of many researchers. Spiking neural networks has developed rapidly, and many training methods can achieve the same or even higher accuracy than Artificial neural networks. In this paper, we further understand the advantages and framework of Spiking neural network through its development.","PeriodicalId":159508,"journal":{"name":"2022 19th International Computer Conference on Wavelet Active Media Technology and Information Processing (ICCWAMTIP)","volume":"46 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121558796","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 And Transparent Inference: Spiking Neural Network For Causal Reasoning 一个智能和透明的推理:用于因果推理的脉冲神经网络

2022 19th International Computer Conference on Wavelet Active Media Technology and Information Processing (ICCWAMTIP) Pub Date : 2022-12-16 DOI: 10.1109/ICCWAMTIP56608.2022.10016487

Li Runyu, Luo Xiaoling, Wang Jun

引用次数: 0

A Novel Beam Selection Scheme Based On Group-Iteration Algorithm 一种新的基于群迭代算法的波束选择方案

2022 19th International Computer Conference on Wavelet Active Media Technology and Information Processing (ICCWAMTIP) Pub Date : 2022-12-16 DOI: 10.1109/ICCWAMTIP56608.2022.10016573

Yi Zhao, Ning Xiao

引用次数: 0

Relation Heterogeneous Graph Neural Network 关系异构图神经网络

2022 19th International Computer Conference on Wavelet Active Media Technology and Information Processing (ICCWAMTIP) Pub Date : 2022-12-16 DOI: 10.1109/ICCWAMTIP56608.2022.10016506

Yu Jielin, Wei Zukuan

引用次数: 0

Sparse Sampled Logistic Chaos-Based Frequency Modulated Signals For Mimo Radar 基于稀疏采样Logistic混沌的Mimo雷达调频信号

2022 19th International Computer Conference on Wavelet Active Media Technology and Information Processing (ICCWAMTIP) Pub Date : 2022-12-16 DOI: 10.1109/ICCWAMTIP56608.2022.10016583

Yang Jin, Zhang Xin, Tan Zhiguo, Teng Shuhua

引用次数: 0

Reliable Semi-Supervised Learning on Imbalanced Evolving Data Stream 不平衡演化数据流的可靠半监督学习

2022 19th International Computer Conference on Wavelet Active Media Technology and Information Processing (ICCWAMTIP) Pub Date : 2022-12-16 DOI: 10.1109/ICCWAMTIP56608.2022.10016598

Pan Liangxu

{"title":"Reliable Semi-Supervised Learning on Imbalanced Evolving Data Stream","authors":"Pan Liangxu","doi":"10.1109/ICCWAMTIP56608.2022.10016598","DOIUrl":"https://doi.org/10.1109/ICCWAMTIP56608.2022.10016598","url":null,"abstract":"Existing semi-supervised learning (SSL) algorithms often heavily depend on some assumptions (e.g., cluster assumption) and usually work on class-balanced static datasets. If the assumption(s) does (do) not hold, the biased prediction of unlabeled data may even hurt accuracy. This issue becomes more problematic in the context of streaming data due to the existence of concept drift. Therefore, it’s of great importance to enhance the reliability of the SSL algorithms on imbalanced concept-drifting data streams. In this paper, we propose a reliable and scalable SSL framework on imbalanced evolving data stream. Instead of relaxing different assumptions, we apply a novel sampling strategy and an additional balanced classifier to reduce the impact of imbalance and introduce the deep metric learning loss to enlarge the class margin to increase the degree of discrimination. We further maintain a small set of reliable micro-clusters dynamically in that embedding space and employ different strategies to update their reliabilities to maintain the most recent concept and cope with concept drifts. We conducted some experiments on real and synthetic stream datasets to evaluate the effectiveness of our proposed model.","PeriodicalId":159508,"journal":{"name":"2022 19th International Computer Conference on Wavelet Active Media Technology and Information Processing (ICCWAMTIP)","volume":"28 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116490376","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

Precise Positioning Method Of UWB In Signal Jamming 信号干扰下超宽带的精确定位方法

2022 19th International Computer Conference on Wavelet Active Media Technology and Information Processing (ICCWAMTIP) Pub Date : 2022-12-16 DOI: 10.1109/ICCWAMTIP56608.2022.10016557

Li Jun, Zhang Ruizhi, S. Xiaofeng

引用次数: 0

Atypical Dynamics of Sub-Networks Predict Restricted Repetitive Patterns of Behaviors in Children with Autism Spectrum Disorder 子网络的非典型动态预测自闭症谱系障碍儿童的限制性重复行为模式

2022 19th International Computer Conference on Wavelet Active Media Technology and Information Processing (ICCWAMTIP) Pub Date : 2022-12-16 DOI: 10.1109/ICCWAMTIP56608.2022.10016510

Jinming Xiao, Duan Xujun, Meng Yao, Li Lei, Xinyue Huang, Chen Huafu

引用次数: 0

Automatic Image Contrast Enhancement Based on Reinfrocement Learning 基于强化学习的图像对比度自动增强

2022 19th International Computer Conference on Wavelet Active Media Technology and Information Processing (ICCWAMTIP) Pub Date : 2022-12-16 DOI: 10.1109/ICCWAMTIP56608.2022.10016571

Deboch Eyob Abera, Tesfay Semere Gerezgiher, Qi Jin, Gebre Fisehatsion Mesfin

引用次数: 0