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检索条件"任意字段=6th International Conference on Bioinformatics Models, Methods and Algorithms, BIOINFORMATICS 2015"

共 231 条记录，以下是101-110 订阅

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Consensus-based prediction of RNA and DNA binding residues from protein sequences 6th

Consensus-based prediction of RNA and DNA binding residues f...

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6th international conference on Pattern Recognition and Machine Intelligence, PReMI 2015

作者： Yan, Jing Kurgan, Lukasz Electrical and Computer Engineering University of Alberta EdmontonT6G 2V4 Canada

Computational prediction of RNA- and DNA-binding residues from protein sequences offers a high-throughput and accurate solution to functionally annotate the avalanche of the protein sequence data. Although many predictors exist, the efforts to improve predictive performance with the use of consensus methods are so far limited. We explore and empirically compare a comprehensive set of different designs of consensuses including simple approaches that combine binary predictions and more sophisticated machine learning models. We consider both DNA- and RNA-binding motivated by similarities in these interactions, which should lead to similar conclusions. We observe that the simple consensuses do not provide improved predictive performance when applied to sequences that share low similarity with the datasets used to build their input predictors. However, use of machine learning models, such as linear regression, Support Vector Machine and Naïve Bayes, results in improved predictive performance when compared with the best individual predictors for the prediction of DNA- and RNA-binding residues. © Springer international Publishing Switzerland 2015.

关键词： Forecasting

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methods for control over learning individual trajectory 6

Methods for control over learning individual trajectory

引用

6th international Scientific Practical conference on Innovative Technologies and Economics in Engineering

作者： Mitsel, A. A. Cherniaeva, N. V. Tomsk Polytech Univ Yurga Inst Technol Engn Sci Yurga Kemerovo Region Russia Tomsk Polytech Univ Yurga Kemerovo Region Russia

the article discusses models, methods and algorithms of determining student's optimal individual educational trajectory. A new method of controlling the learning trajectory has been developed as a dynamic model of... 详细信息

关键词： Trajectories

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Comparison of Angle Measurements Between Integral-Based and Quaternion-Based methods Using Inertial Sensors for Gait Evaluation 7th

Comparison of Angle Measurements Between Integral-Based and ...

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5th international conference on bioinformatics models, methods and algorithms (bioinformatics) is part of 7th international Joint conference on Biomedical Engineering Systems and Technologies (BIOSTEC)

作者： Watanabe, Takashi Teruyama, Yuta Ohashi, Kento Tohoku Univ Grad Sch Biomed Engn Sendai Miyagi 980 Japan Tohoku Univ Grad Sch Engn Sendai Miyagi 980 Japan

ISBN: (纸本)9783319261294;9783319261287

the measurement method of lower limb angles, which were based on the integral of angular velocity with Kalman filter, was validated previously in measurement of angles in a plane with a rigid body model of double pendulum and shown to be practical in measurement of angles in the sagittal plane during gait of healthy subjects. In this paper, in order to realize practical measurements of 3 dimensional (3D) movements with inertial sensors, the previously developed integral-based angle calculation method with variable Kalman gain and a quaternion-based one with fixed gain were tested. First, the quaternion-based method showed higher measurement accuracies for angles in the sagittal and the frontal planes during 3D movements of a rigid body model of lower limb than that of the integral-based one. Second, the integral-based method was shown to be effective in measurement of angles in the sagittal plane of healthy subjects during treadmill walking compared to the quaternion-based one, which suggested effectiveness of the variable Kalman gain method. third, the integral-based method was shown to cause inappropriate results in some cases of calculation of lower limb angles of hemiplegic subjects during gait, while some of such cases could be measured appropriately with the quaternion-based one. the results of this paper suggested that the quaternion-based method would be more effective with a variable Kalman-gain for measurement of 3D movements. the integral-based method was also suggested to be useful for measurement of angles in the sagittal plane of healthy subjects during gait.

关键词： Angle Inertial sensor Kalman filter Integral Quaternion Gait Rehabilitation

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Collective homeostasis and time-resolved models of self-organised task allocation 9

Collective homeostasis and time-resolved models of self-orga...

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9th EAI international conference on Bio-Inspired Information and Communications Technologies, BICT 2015

作者： Meyer, Bernd Weidenmüller, Anja Chen, Rui García, Julián Faculty of IT Monash University Melbourne Australia Department of Neurobiology University of Konstanz Konstanz Germany

One of the main factors behind the amazing ecological success of social insects is their ability to exibly allocate the colony's workforce to all the different tasks it has to address. Insights into the self-organised task allocation methods used for this have given rise to the design of an important class of bio-inspired algorithms for network control, industrial optimisation, and other applications. the most widely used class of models for self-organised task allocation, which also forms the core of these algorithms, are the so-called response threshold models. We revisit response threshold models with new experiments using temperature regulation in bumblebee colonies as the model system. We show that standard response threshold models do not fit our experiments and present a new, alternative behavioural model. this captures a fine-grained, time resolved picture of task engagement, which enables us to investigate task allocation with a different set of statistical methods (survival analysis). Using these we show that our model fits the experiment well and explains its salient aspects. We compare the effectiveness of the behaviour that our model describes with that of response threshold models and demonstrate that it can lead to more efficient task management when demands uctuate. Our results have the potential to provide a basis for the design of new, more efficient task allocation algorithms for dynamic environments and to elucidate important biological questions, such as the functional role of inter-individual variation. © 2016 ICST.

关键词： bioinformatics

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Research and implementation of parameters optimization simulation environment for hydrological models 6th

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6th international conference on Swarm Intelligence, ICSI 2015 held in conjunction with the 2nd BRICS Congress on Computational Intelligence, CCI 2015

作者： Huo, Jiuyuan Zhang, Yaonan School of Electronic and Information Engineering Lanzhou Jiaotong University Lanzhou730070 China Cold and Arid Regions Environmental and Engineering Research Institute Chinese Academy of Sciences Lanzhou730000 China

ISBN: (纸本)9783319204710

For the Hydrological models’ complexity, more model parameters, and most parameters are unpredictable as well as errors of observation data in river basin will lead to lots of errors and uncertainties in Hydrological model parameter calibration, Hydrological modeling and forecasting. therefore, we developed a unified integrated simulation environment of parameter estimation for Hydrological models in Heihe river basin to support the implementation the processes of simulation operation, parameter optimization, parameter evaluation, analysis and simulation results visualization of Hydrological models in Heihe river basin. By using long-term monitoring measured data, we validated the hydrologic models’ parameters estimation integrated simulation environment in Xinanjiang Hydrological model. the results showed that research in this paper would reduce complex workload of data collection and program development, and significantly improve accuracy and efficiency for model simulation. © Springer international Publishing Switzerland 2015.

关键词： Parameter estimation

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6th international conference on Digital Human Modeling, DHM 2015 Held as Part of 17th international conference on Human-Computer Interaction, HCI international 2015

6th International Conference on Digital Human Modeling, DHM ...

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6th international conference on Digital Human Modeling, DHM 2015 Held as Part of 17th international conference on Human-Computer Interaction, HCI international 2015

ISBN: (纸本)9783319210698

the proceedings contain 58 papers. the special focus in this conference is on Anthropometry, Ergonomics, Motion Modeling, Tracking, Human Modeling in Transport and Human Modeling in Medicine. the topics include: Estimation of arbitrary human models from anthropometric dimensions;an approach for intuitive visualization of ergonomic issues;correlation analysis on the main and basic body dimension for Chinese adults;study on the body shape of middle-aged and old women for garment design;the role of virtual ergonomic simulation to develop innovative human centered products;experimental study on grip ergonomics of manual handling;moment analysis of virtual human joint based on jack;body tracking as a generative tool for experience design;real-time static gesture recognition for upper extremity rehabilitation using the leap motion;effect of care gesture on transfer care behavior in elderly nursing home in Japan;MOCAP-based adaptive human-like walking simulation in laser-scanned large-scale as-built environments;process analysis of the hand lay-up method using CFRP prepreg sheets;development of a 3d finite element model of the Chinese 50th male for the analysis of automotive impact;toward a model for effective human-automation interaction;semantically integrated human factors engineering;driving-behavior monitoring using an unmanned aircraft system;automatic identification of below-knee residuum anatomical zones;analyzing requirements using environment modelling and modeling of a virtual open platform for human cranium simulation.

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Infinite dimensional optimization models and PDEs for dejittering 5

Infinite dimensional optimization models and PDEs for dejitt...

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5th international conference on Scale Space and Variational methods in Computer Vision, SSVM 2015

作者： Dong, Guozhi Patrone, Aniello Raffaele Scherzer, Otmar Öktem, Ozan Computational Science Center University of Vienna Oskar-Morgenstern-Platz 1 Wien1090 Austria Austrian Academy of Sciences Altenberger Strasse 69 A Linz4040 Austria Department of Mathematics KTH - Royal Institute of Technology Lindstedtsvägen 25 StockholmSE10044 Sweden

ISBN: (纸本)9783319184609

In this paper we do a systematic investigation of continuous methods for pixel, line pixel and line dejittering. the basis for these investigations are the discrete line dejittering algorithm of Nikolova and the partial differential equation of Lenzen et al for pixel dejittering. To put these two different worlds in perspective we find infinite dimensional optimization algorithms linking to the finite dimensional optimization problems and formal flows associated with the infinite dimensional optimization problems. Two different kinds of optimization problems will be considered: Dejittering algorithms for determining the displacement and displacement error correction formulations, which correct the jittered image, without estimating the jitter. As a by-product we find novel variational methods for displacement error regularization and unify them into one family. the second novelty is a comprehensive comparison of the different models for different types of jitter, in terms of efficiency of reconstruction and numerical complexity. © IFIP international Federation for Information Processing 2015.

关键词： Pixels

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A new post-processing method to detect brain tumor using rough-fuzzy clustering 6th

A new post-processing method to detect brain tumor using rou...

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6th international conference on Pattern Recognition and Machine Intelligence, PReMI 2015

作者： Roy, Shaswati Maji, Pradipta Biomedical Imaging and Bioinformatics Lab Machine Intelligence Unit Indian Statistical Institute Kolkata India

Automatic and accurate brain tumor segmentation from MR images is one of the important problems in cancer research. However, the lack of shape prior and weak contrast at boundary make unsupervised brain tumor segmentation more challenging. In this background, a new brain tumor segmentation method is being developed, integrating judiciously the merits of multiresolution image analysis technique and rough-fuzzy clustering. One of the major issues of the clustering based segmentation method is how to extract brain tumor accurately, since tumors may not have clearly defined intensity or textural boundaries. In this regard, this paper presents a new post-processing method for clustering based brain tumor detection. It combines the merits of mathematical morphology and the concept of rough set based region growing approach to refine the result obtained after clustering, thereby ensuring the accurateness of brain tumor segmentation application. the performance of the proposed approach, along with a comparison with related methods, is demonstrated on a set of synthetic and real brain MR images. © Springer international Publishing Switzerland 2015.

关键词： Mathematical morphology

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A logistic regression approach for identifying hot spots in protein interfaces 6th

A logistic regression approach for identifying hot spots in ...

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6th international conference on Information Technology in Bio- and Medical Informatics, ITBAM 2015

作者： Li, Peipei Ho Ryu, Keun Database/Bioinformatics Laboratory Chungbuk National University Cheongju Korea Republic of

ISBN: (纸本)9783319227405

Protein–protein interactions occur when two or more proteins bind together, often to carry out their biological function. A small fraction of interfaces on protein surface found providing major contributions to the binding free energy are referred as hot spots. Identifying hot spots is important for examining the actions and properties occurring around the binding sites. However experimental studies require significant effort;and computational methods still have limitations in prediction performance and feature interpretation. In this paper we describe a hot spots residues prediction measure which provides a significant improvement over other existing methods. Combining 8 features derived from accessibility, sequence conservation, inter-residue potentials, computational alanine scanning, small-world structure characteristics, phi-psi interaction, and contact number, logistic regression is used to derive a prediction model. To demonstrate its effectiveness, the proposed method is applied to ASEdb. Our prediction model achieves an accuracy of 0.819, F1 score of 0.743. Experimental results show that the additional features can improve the prediction performance. Especially phi-psi has been found to give important effort. We then perform an exhaustive comparison of our method with various machine learning based methods and those previously published prediction models in the literature. Empirical studies show that our method can yield significantly better prediction performance. © Springer international Publishing Switzerland 2015.

关键词： Proteins

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Joint learning of multiple longitudinal prediction models by exploring internal relations 6th

Joint learning of multiple longitudinal prediction models by...

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6th international Workshop on Machine Learning in Medical Imaging, MLMI 2015 and Held in Conjunction with 18th international conference on Medical Image Computing and Computer Assisted Intervention, MICCAI 2015

作者： Lei, Baiying Ni, Dong Wang, Tianfu Department of Biomedical Engineering School of Medicine Shenzhen University National-Regional Key Technology Engineering Laboratory for Medical Ultrasound Guangdong Key Laboratory for Biomedical Measurements and Ultrasound Imaging Shenzhen China

ISBN: (纸本)9783319248875

Longitudinal prediction of the brain disorder such as Alzheimer’s disease (AD) is important for possible early detection and early intervention. Given the baseline imaging and clinical data, it will be interesting to predict the progress of disease for an individual subject, such as predicting the conversion of Mild Cognitive Impairment (MCI) to AD, in the future years. Most existing methods predicted different clinical scores using different models, or predicted multiple scores at different future time points separately. this often misses the chance of coordinated learning of multiple prediction models for jointly predicting multiple clinical scores at multiple future time points. In this paper, we propose a novel method for joint learning of multiple longitudinal prediction models for multiple clinical scores at multiple future time points. First, for each longitudinal prediction model, we explore three important relationships among training samples, features, and clinical scores, respectively, for enhancing its learning. then, we further introduce additional relation among different longitudinal prediction models for allowing them to select a common set of features from the baseline imaging and clinical data, with l2,1 sparsity constraint, for their joint training. We evaluate the performance of our joint prediction models with the data from the Alzheimer’s Disease Neuroimaging Initiative (ADNI) database, showing much better performance than the state-of-the-art methods in predicting multiple clinical scores at multiple future time points. © Springer international Publishing Switzerland 2015.

关键词： Neuroimaging

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