2012 ASE/IEEE International Conference on BioMedical Computing (BioMedCom)最新文献_第2页

Early Results from Metamorphic Testing of Epidemiological Models 流行病学模型变形试验的早期结果

2012 ASE/IEEE International Conference on BioMedical Computing (BioMedCom) Pub Date : 2012-12-14 DOI: 10.1109/BIOMEDCOM.2012.17

L. Pullum, O. Ozmen

引用次数: 34

3-D Tomosynthesis Image Reconstruction Using Total Variation 基于全变分的三维断层合成图像重建

2012 ASE/IEEE International Conference on BioMedical Computing (BioMedCom) Pub Date : 2012-12-14 DOI: 10.1109/BIOMEDCOM.2012.7

M. Ertas, A. Akan, K. Cengiz, M. Kamasak, S. Seyyedi, I. Yildirim

引用次数: 2

Security Engineering Based on Structured Formal Reasoning 基于结构化形式推理的安全工程

2012 ASE/IEEE International Conference on BioMedical Computing (BioMedCom) Pub Date : 2012-12-14 DOI: 10.1109/BIOMEDCOM.2012.30

A. Fuchs, C. Rudolph

引用次数: 0

A Process for Visualizing Disordered Molecular Data with a Case Study in Bulk Water 无序分子数据的可视化过程——以散装水为例

2012 ASE/IEEE International Conference on BioMedical Computing (BioMedCom) Pub Date : 2012-12-14 DOI: 10.1109/BIOMEDCOM.2012.12

Nick Leaf, K. Ma, Cui Zhang, G. Galli

引用次数: 1

Study of HRV Dynamics and Comparison Using Wavelet Analysis and Pan Tompkins Algorithm 基于小波分析和Pan Tompkins算法的HRV动力学研究与比较

2012 ASE/IEEE International Conference on BioMedical Computing (BioMedCom) Pub Date : 2012-12-14 DOI: 10.1109/BIOMEDCOM.2012.13

Y. Goyal, A. Jain

引用次数: 4

Quantifying Uncertainty in Epidemiological Models 量化流行病学模型中的不确定性

2012 ASE/IEEE International Conference on BioMedical Computing (BioMedCom) Pub Date : 2012-12-14 DOI: 10.1109/BIOMEDCOM.2012.20

S. K. Jha, A. Ramanathan

{"title":"Quantifying Uncertainty in Epidemiological Models","authors":"S. K. Jha, A. Ramanathan","doi":"10.1109/BIOMEDCOM.2012.20","DOIUrl":"https://doi.org/10.1109/BIOMEDCOM.2012.20","url":null,"abstract":"Modern epidemiology has made use of a number of mathematical models, including ordinary differential equation (ODE) based models and agent based models (ABMs) to describe the dynamics of how a disease may spread within a population and enable the rational design of strategies for intervention that effectively contain the spread of the disease. Although such predictions are of fundamental importance in preventing the next global pandemic, there is a significant gap in trusting the outcomes/predictions solely based on such models. Hence, there is a need to develop approaches such that mathematical models can be calibrated against historical data. In addition, there is a need to develop rigorous uncertainty quantification approaches that can provide insights into when a model will fail and characterize the confidence in the (possibly multiple) model outcomes/predictions, when such retrospective analysis cannot be performed. In this paper, we outline an approach to develop uncertainty quantification approaches for epidemiological models using formal methods and model checking. By specifying the outcomes expected from a model in a suitable spatio-temporal logic, we use probabilistic model checking methods to quantify the probability with which the epidemiological model satisfies a given behavioral specification. We argue that statistical model checking methods can solve the uncertainty quantification problem for complex epidemiological models.","PeriodicalId":146495,"journal":{"name":"2012 ASE/IEEE International Conference on BioMedical Computing (BioMedCom)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2012-12-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129989011","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: 9

Agent-Based vs. Equation-Based Epidemiological Models: A Model Selection Case Study 基于主体与基于方程的流行病学模型:模型选择案例研究

2012 ASE/IEEE International Conference on BioMedical Computing (BioMedCom) Pub Date : 2012-12-14 DOI: 10.1109/BIOMEDCOM.2012.19

S. Sukumar, J. Nutaro

引用次数: 14

Scalable and Reusable Attack Aware Software 可扩展和可重用的攻击感知软件

2012 ASE/IEEE International Conference on BioMedical Computing (BioMedCom) Pub Date : 2012-12-14 DOI: 10.1109/BIOMEDCOM.2012.23

W. Kim, C. S. Moon, S. Chung, T. Escrig, B. Endicott-Popovsky

引用次数: 1

Verification of Compartmental Epidemiological Models Using Metamorphic Testing, Model Checking and Visual Analytics 用变形检验、模型检验和可视化分析验证区隔流行病学模型

2012 ASE/IEEE International Conference on BioMedical Computing (BioMedCom) Pub Date : 2012-12-14 DOI: 10.1109/BIOMEDCOM.2012.18

A. Ramanathan, C. Steed, L. Pullum

{"title":"Verification of Compartmental Epidemiological Models Using Metamorphic Testing, Model Checking and Visual Analytics","authors":"A. Ramanathan, C. Steed, L. Pullum","doi":"10.1109/BIOMEDCOM.2012.18","DOIUrl":"https://doi.org/10.1109/BIOMEDCOM.2012.18","url":null,"abstract":"Compartmental models in epidemiology are widely used as a means to model disease spread mechanisms and understand how one can best control the disease in case an outbreak of a widespread epidemic occurs. However, a significant challenge within the community is in the development of approaches that can be used to rigorously verify and validate these models. In this paper, we present an approach to quantify and verify the behavioral properties of compartmental epidemiological models under several common modeling scenarios including: birth/death rates and multi-host/pathogen species. We build a workflow that uses metamorphic testing, novel visualization tools and model checking to gain insights into the functionality of compartmental epidemiological models. Our initial results indicate that metamorphic testing can be used to verify the implementation of these models and provide insights into special conditions where these mathematical models may fail. The visualization front-end allows the end-user to scan through a variety of parameters commonly used in these models to elucidate the conditions under which an epidemic can occur. Furthermore, specifying these models using a process algebra allows one to automatically construct behavioral properties that can be rigorously verified using model checking. Together, our approach allows for detecting implementation errors as well as handling conditions under which compartmental epidemiological models may fail to provide insights into disease spread dynamics.","PeriodicalId":146495,"journal":{"name":"2012 ASE/IEEE International Conference on BioMedical Computing (BioMedCom)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2012-12-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130961030","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: 25

Identification of Surface and Deep Layer Muscle Activity by EMG Propagation Direction 肌电图传播方向识别浅层和深层肌肉活动

2012 ASE/IEEE International Conference on BioMedical Computing (BioMedCom) Pub Date : 2012-12-14 DOI: 10.1109/BIOMEDCOM.2012.14

T. Koshio, S. Sakurazawa, M. Toda, J. Akita, K. Kondo, Y. Nakamura

{"title":"Identification of Surface and Deep Layer Muscle Activity by EMG Propagation Direction","authors":"T. Koshio, S. Sakurazawa, M. Toda, J. Akita, K. Kondo, Y. Nakamura","doi":"10.1109/BIOMEDCOM.2012.14","DOIUrl":"https://doi.org/10.1109/BIOMEDCOM.2012.14","url":null,"abstract":"It is generally difficult to identify surface and deep layer muscle activity. If we could identify surface and deep layer muscle activity, we can provide effective tools for rehabilitation. Therefore, in this study, we aim to identify surface and deep layer muscle activity using surface electrodes. We focused on the intersection of muscle fibers of surface layer muscle and deep layer muscle. On such a place, we found that we could measure independent muscle activity along each muscle fiber. In this result, we could confirm that we could measure surface layer muscle activity independently by comparing with the signal which is measured on extended line of surface muscle fiber and on outside of the deep layer muscle. Additionally, we identified propagation direction of EMG signal using electrode array. It was determined from delay time of EMG signal measured on each electrode. When we activated surface and deep layer muscle independently, each propagation direction of EMG signal corresponded to each muscle fiber direction. Thus, we indicated that identification of surface and deep layer muscle activity is possible.","PeriodicalId":146495,"journal":{"name":"2012 ASE/IEEE International Conference on BioMedical Computing (BioMedCom)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2012-12-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122726622","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