IEEE International Conference on Systems Biology : [proceedings]. IEEE International Conference on Systems Biology最新文献

{"title":"Modelling of Double-Pendulum Based Energy Harvester for Railway Wagon","authors":"V. Bučinskas, Andrius Dzedzickis, N. Sesok, E. Šutinys, I. Iljin","doi":"10.1007/978-3-319-48923-0_9","DOIUrl":"https://doi.org/10.1007/978-3-319-48923-0_9","url":null,"abstract":"","PeriodicalId":90521,"journal":{"name":"IEEE International Conference on Systems Biology : [proceedings]. IEEE International Conference on Systems Biology","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2016-05-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"91396536","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":"Homogeneity Tests for Interval Data","authors":"S. S. Vozhov, E. Chimitova","doi":"10.1007/978-3-319-48923-0_83","DOIUrl":"https://doi.org/10.1007/978-3-319-48923-0_83","url":null,"abstract":"","PeriodicalId":90521,"journal":{"name":"IEEE International Conference on Systems Biology : [proceedings]. IEEE International Conference on Systems Biology","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2016-05-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"91397228","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":"Identification for control of biomedical systems using a very short experiment","authors":"K. Soltesz, P. Mercader","doi":"10.1109/ICSMB.2016.7915107","DOIUrl":"https://doi.org/10.1109/ICSMB.2016.7915107","url":null,"abstract":"This paper presents a combined experiment and identification procedure, well suited to obtain low-order dynamic models of a patients' response to continuous drug administration. The experiment requires no a priori information and is of very short duration. The identification method provides both a parametric low-order model, and an estimate of the parameter error covariance. It has been demonstrated to work well with very noisy measurements, as typically encountered in drug dosing applications.","PeriodicalId":90521,"journal":{"name":"IEEE International Conference on Systems Biology : [proceedings]. IEEE International Conference on Systems Biology","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2016-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"90964346","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":"PRECISE:PRivacy-prEserving Cloud-assisted quality Improvement Service in hEalthcare.","authors":"Feng Chen,&nbsp;Shuang Wang,&nbsp;Noman Mohammed,&nbsp;Samuel Cheng,&nbsp;Xiaoqian Jiang","doi":"10.1109/ISB.2014.6990752","DOIUrl":"https://doi.org/10.1109/ISB.2014.6990752","url":null,"abstract":"<p><p>Quality improvement (QI) requires systematic and continuous efforts to enhance healthcare services. A healthcare provider might wish to compare local statistics with those from other institutions in order to identify problems and develop intervention to improve the quality of care. However, the sharing of institution information may be deterred by institutional privacy as publicizing such statistics could lead to embarrassment and even financial damage. In this article, we propose a PRivacy-prEserving Cloud-assisted quality Improvement Service in hEalthcare (PRECISE), which aims at enabling cross-institution comparison of healthcare statistics while protecting privacy. The proposed framework relies on a set of state-of-the-art cryptographic protocols including homomorphic encryption and Yao's garbled circuit schemes. By securely pooling data from different institutions, PRECISE can rank the encrypted statistics to facilitate QI among participating institutes. We conducted experiments using MIMIC II database and demonstrated the feasibility of the proposed PRECISE framework.</p>","PeriodicalId":90521,"journal":{"name":"IEEE International Conference on Systems Biology : [proceedings]. IEEE International Conference on Systems Biology","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2014-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1109/ISB.2014.6990752","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"34260895","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Comparison of Multi-Sample Variant Calling Methods for Whole Genome Sequencing.","authors":"Kwangsik Nho,&nbsp;John D West,&nbsp;Huian Li,&nbsp;Robert Henschel,&nbsp;Apoorva Bharthur,&nbsp;Michel C Tavares,&nbsp;Andrew J Saykin","doi":"10.1109/ISB.2014.6990432","DOIUrl":"https://doi.org/10.1109/ISB.2014.6990432","url":null,"abstract":"<p><p>Rapid advancement of next-generation sequencing (NGS) technologies has facilitated the search for genetic susceptibility factors that influence disease risk in the field of human genetics. In particular whole genome sequencing (WGS) has been used to obtain the most comprehensive genetic variation of an individual and perform detailed evaluation of all genetic variation. To this end, sophisticated methods to accurately call high-quality variants and genotypes simultaneously on a cohort of individuals from raw sequence data are required. On chromosome 22 of 818 WGS data from the Alzheimer's Disease Neuroimaging Initiative (ADNI), which is the largest WGS related to a single disease, we compared two multi-sample variant calling methods for the detection of single nucleotide variants (SNVs) and short insertions and deletions (indels) in WGS: (1) reduce the analysis-ready reads (BAM) file to a manageable size by keeping only essential information for variant calling (\"<i>REDUCE</i>\") and (2) call variants individually on each sample and then perform a joint genotyping analysis of the variant files produced for all samples in a cohort (\"<i>JOINT</i>\"). <i>JOINT</i> identified 515,210 SNVs and 60,042 indels, while <i>REDUCE</i> identified 358,303 SNVs and 52,855 indels. <i>JOINT</i> identified many more SNVs and indels compared to <i>REDUCE</i>. Both methods had concordance rate of 99.60% for SNVs and 99.06% for indels. For SNVs, evaluation with HumanOmni 2.5M genotyping arrays revealed a concordance rate of 99.68% for <i>JOINT</i> and 99.50% for <i>REDUCE</i>. <i>REDUCE</i> needed more computational time and memory compared to <i>JOINT</i>. Our findings indicate that the multi-sample variant calling method using the <i>JOINT</i> process is a promising strategy for the variant detection, which should facilitate our understanding of the underlying pathogenesis of human diseases.</p>","PeriodicalId":90521,"journal":{"name":"IEEE International Conference on Systems Biology : [proceedings]. IEEE International Conference on Systems Biology","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2014-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1109/ISB.2014.6990432","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"34002504","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"eWave: Leveraging Energy-Awareness for In-line Deduplication Clusters","authors":"Raúl Gracia-Tinedo, M. Sánchez-Artigas, P. García-López","doi":"10.1145/2611354.2611361","DOIUrl":"https://doi.org/10.1145/2611354.2611361","url":null,"abstract":"In-line deduplication clusters provide high throughput and scalable storage/archival services to enterprises and organizations. Unfortunately, high throughput comes at the cost of activating several storage nodes on each request, due to the parallel nature of superchunk routing. This may prevent storage nodes from exploiting disk standby times to preserve energy, even for low load periods. We aim to enable deduplication clusters to exploit load valleys to save up disk energy. To this end, we explore the feasibility of deferred writes, diverted access and workload consolidation in this setting. We materialize our insights in eWave: a novel energy-efficient storage middleware for deduplication clusters. The main goal of eWave is to enable the energy-aware operation of deduplication clusters without modifying the deduplication layer. Via extensive simulations and experiments in an 8--machine cluster, we show that eWave reduces disk energy from 16% to 60% in common scenarios with moderate impact on performance during low load periods.","PeriodicalId":90521,"journal":{"name":"IEEE International Conference on Systems Biology : [proceedings]. IEEE International Conference on Systems Biology","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2014-06-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"89349320","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":"Time-Delay System Identification Using Genetic Algorithm - Part Two: FOPDT/SOPDT Model Approximation","authors":"Zhenyu Yang, G. T. Seested","doi":"10.3182/20130902-3-CN-3020.00117","DOIUrl":"https://doi.org/10.3182/20130902-3-CN-3020.00117","url":null,"abstract":"Abstract The First-Order-Plus-Dead-Time (FOPDT) or Second-Order-Plus-Dead-Time (SOPDT) model approximation to a complicated process system can be carried out through either a kind of model reduction approach or a kind of system identification approach. This paper investigates this model approximation problem through an identification approach using the real coded Genetic Algorithm (GA). The desired FOPDT/SOPDT model is directly identified based on the measured system's input and output data. In order to evaluate the quality and performance of this GA-based approach, the proposed method is compared with two typical model reduction methods, namely Skogestad's rules and Sung et al method. The obtained results exhibit a very promising capability of GA in handling the data-driven time-delay system approximation.","PeriodicalId":90521,"journal":{"name":"IEEE International Conference on Systems Biology : [proceedings]. IEEE International Conference on Systems Biology","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2013-09-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"85754624","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":"Learning Control of a Robotic System Using Neural Networks","authors":"Zhixun Li, W. He, Zui Tao, Chang Liu","doi":"10.3182/20130902-3-CN-3020.00172","DOIUrl":"https://doi.org/10.3182/20130902-3-CN-3020.00172","url":null,"abstract":"Abstract In this paper, deterministic learning control using neural networks (NNs) is presented for a robotic system with unknown system dynamics. The dynamics of the robotic system are represented by an n-link strict robotic manipulator. The adaptive NNs is employed as the first control strategy to approximate the unknown model of the system and adapt interactions between the robot and a patient. Deterministic learning control using learned knowledge from direct NNs with Radial Basis Functions (RBFs) is employed as the second control strategy to improve the system intelligence for energy conservation and reduce control tasks. Uniform ultimate boundedness (UUB) of the closed loop system is achieved under the condition of the Lyapunov's stability with full state feedback control. Extensive simulations are carried out to expound the efficacy of the proposed control strategies and the advancement of learning control.","PeriodicalId":90521,"journal":{"name":"IEEE International Conference on Systems Biology : [proceedings]. IEEE International Conference on Systems Biology","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2013-09-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"76875475","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":"Adaptive NN Control for a Class of Stochastic Nonlinear Systems with Unmodeled Dynamics","authors":"Zifu Li, Tie-shan Li","doi":"10.3182/20130902-3-CN-3020.00055","DOIUrl":"https://doi.org/10.3182/20130902-3-CN-3020.00055","url":null,"abstract":"Abstract This paper addresses the problem of adaptive neural networks output feedback control for a class of stochastic nonlinear system with unmodeled dynamics. Only a neural network (NN) is employed to compensate for all unknown nonlinear functions, so that the designed controller is simpler than the existing results and reduces the computation loads. With the concept of input-to-state practical stability (ISpS) and nonlinear small-gain theorem extended to the stochastic case, together with the RBF NN technique, an adaptive NN output feedback controller is proposed. It is shown that the solutions of the closed-loop system are bounded in probability.","PeriodicalId":90521,"journal":{"name":"IEEE International Conference on Systems Biology : [proceedings]. IEEE International Conference on Systems Biology","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2013-09-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"91079404","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":"Unambiguous Radial Velocity Estimation Based on Delay-Interferometry in Range Frequency Domain","authors":"Xuepan Zhang","doi":"10.3182/20130902-3-CN-3020.00107","DOIUrl":"https://doi.org/10.3182/20130902-3-CN-3020.00107","url":null,"abstract":"Abstract To solve the problem that the estimated radial velocity of fast moving target is ambiguity in synthetic aperture radar/ground moving target indication (SAR/GMTI), an approach is proposed to estimate the radial velocity unambiguously in the paper. The method utilizes the processing of delay and interferometry in range frequency domain. After range compression and delay, the dual-channel data possess the same Doppler chirp rate. Then, interferometric processing is done in range frequency domain, obtaining the linear relationship between the interferometric phase and range frequency, with the slope containing the information of radial velocity. Since the slope is no ambiguity, radial velocity is estimated unambiguously. The maximum unambiguous radial velocity of the proposed method is also analyzed. Numerical simulations demonstrate the validity of the proposed method with high accuracy of estimation.","PeriodicalId":90521,"journal":{"name":"IEEE International Conference on Systems Biology : [proceedings]. IEEE International Conference on Systems Biology","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2013-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"73658912","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}