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A Modeling Support Tool for a Global Human Model on the Internet

Ken'ichi ASAMI, Tadashi KITAMURA
2002 BME  
Life Support Machines The human models that are shared and customized on the web are linked to life support machines for design, measurement, and control of various kinds of medical and welfare sustaining  ...  Fig. 6 shows the integrative development environment for life-support machines connected to the human model.  ... 
doi:10.11239/jsmbe1987.16.8_60 fatcat:wpyprjmyvvbe5no3fcbg2abo6q

Machine Learning based Prediction of Hierarchical Classification of Transposable Elements [article]

Manisha Panta, Avdesh Mishra, Md Tamjidul Hoque, Joel Atallah
2019 arXiv   pre-print
And eventually, propose a robust approach for the hierarchical classification of TEs, with higher accuracy, using Support Vector Machines (SVM).  ...  The state-of-the-art machine learning classification method utilizes a Multi-Layer Perceptron (MLP), a class of neural network, for hierarchical classification of TEs.  ...  LCPNB provided better or same hierarchical Fmeasure for all the learners, especially for Multi-layer Perceptron (a type of neural network), Randomized Forest (RF), and Support Vector Machine (SVM).  ... 
arXiv:1907.01674v3 fatcat:cqjhu2gakvac7eukq3rusmmkee

A taxonomy and survey of grid resource management systems for distributed computing

Klaus Krauter, Rajkumar Buyya, Muthucumaru Maheswaran
2002 Software, Practice & Experience  
The significance of the different components and functions of the model are also discussed.  ...  MAHESWARAN autonomy, (c) co-allocating resources, (d) supporting quality of service, and (e) meeting computational cost constraints.  ...  ACKNOWLEDGEMENTS The authors would like to acknowledge all developers of the Grid systems described in the paper.  ... 
doi:10.1002/spe.432 fatcat:35mud2v6fnbzlldnczvg3peeqa

A model checking framework for hierarchical systems

Truong Khanh Nguyen, Jun Sun, Yang Liu, Jin Song Dong
2011 2011 26th IEEE/ACM International Conference on Automated Software Engineering (ASE 2011)  
The user has requested enhancement of the downloaded file.  ...  The input language of the popular NuSMV model check has limited support for modular hierarchical descriptions.  ...  modeling support of the CSP# language.  ... 
doi:10.1109/ase.2011.6100143 dblp:conf/kbse/NguyenSLD11 fatcat:ixrgmmbqsrasfmtjyer4o57ofu

Propagative Deployment of Hierarchical Components in a Dynamic Network [chapter]

Didier Hoareau, Yves Mahéo
2005 Lecture Notes in Computer Science  
This paper addresses the distribution and the deployment of hierarchical components on heterogeneous dynamic networks.  ...  We propose a propagative, hierarchically-controlled deployment process for such networks and an ADL extension allowing the specification of this context-aware deployment.  ...  Further details about the distribution and the support of this distributed hierarchical component model can be found in [5] .  ... 
doi:10.1007/11590712_9 fatcat:cel2grhflzhcfjwgom64yypnxi

SynthQA - Hierarchical Machine Learning-based Protein Quality Assessment [article]

Mikhail Korovnik, Kyle Hippe, Jie Hou, Dong Si, Kiyomi Kishaba, Renzhi Cao
2021 bioRxiv   pre-print
Results: We introduce a new single-model QA tool SynthQA that incorporates multi-scale features from protein structures, utilizes the hierarchical architecture of training machine learning models, and  ...  In this research, we used multi-scale features from energy score to topology of the protein structure, and proposed a hierarchical architecture for training machine learning models to tackle the QA problem  ...  of our machine learning model in training.  ... 
doi:10.1101/2021.01.28.428710 fatcat:jwqoryg6gbbedmqymgofs37q6a

Clustering Visualization and Class Prediction using Flask of Benchmark Dataset for Unsupervised Techniques in Machine learning

The experimental analysis calculates the accuracy of the shaped clusters used different machine learning classifiers namely Logistic Regression, K-nearest neighbors, Support Vector Machine, Gaussian Naïve  ...  It is observed that Kmeans and Hierarchical clustering analysis provide a good clustering pattern of the input dataset than the dimensionality reduction techniques.  ...  HCA Hierarchical Clustering Analysis SVM Support Vector Machine LR Logistic Regression DTC Decision Tree Classifier RFC Random Forest Classifier GNB Gaussian Naïve Bayes Ayantika Nath, Shikha Nema.  ... 
doi:10.35940/ijitee.g5943.059720 fatcat:6luux5x22rfvbcsm426tkyzvte

A Hierarchical Approach to Multimodal Classification [chapter]

Andrzej Skowron, Hui Wang, Arkadiusz Wojna, Jan Bazan
2005 Lecture Notes in Computer Science  
The classification performance of these two hierarchical classifiers is compared with C4.5, Support Vector Machine (SVM), rule based classifiers (with the optimisation of rule shortening) implemented in  ...  Rather than seeking a single model, we consider a series of models under gradually relaxing conditions, which form a hierarchical structure.  ...  Examples include neural networks, support vector machines and Bayesian networks.  ... 
doi:10.1007/11548706_13 fatcat:lvjnwmsdc5gb5k3oqqzfrv3qh4

Exploring models of computation with ptolemy II

Christopher X. Brooks, Edward A. Lee, Stavros Tripakis
2010 Proceedings of the eighth IEEE/ACM/IFIP international conference on Hardware/software codesign and system synthesis - CODES/ISSS '10  
A major problem area being addressed is the use of heterogeneous mixtures of models of computation.  ...  Ptolemy II takes a component view of design, in that models are constructed as a set of interacting components.  ...  Directors can be combined hierarchically with state machines to make modal models [4, 5] .  ... 
doi:10.1145/1878961.1879020 dblp:conf/codes/BrooksLT10 fatcat:fkbktwt6pnhvdkpbucny6wgtia

Formal Modeling and Analysis of Scientific Workflows Using Hierarchical State Machines

Ping Yang, Zijiang Yang, Shiyong Lu
2007 Third IEEE International Conference on e-Science and Grid Computing (e-Science 2007)  
based on hierarchical state machines.  ...  In this paper, we propose to model a scientific workflow using a hierarchical state machine and present techniques for verifying and controlling information propagation in scientific workflow environments  ...  In this paper, we propose a model hierarchical state machine for scientific workflow (HSMSW), which is based on hierarchical state machines (HSM) [5, 4, 3] , to formally model and verify scientific workflows  ... 
doi:10.1109/e-science.2007.35 dblp:conf/eScience/YangYL07 fatcat:unrauv6zwjeidnkbmoa5swryrq

Hierarchical Computation in the SPMD Programming Model [chapter]

Amir Kamil, Katherine Yelick
2014 Lecture Notes in Computer Science  
In this paper, we define the recursive single program, multiple data model (RSPMD) that extends SPMD with a hierarchical team mechanism to support hierarchical algorithms and machines.  ...  The model also facilitates optimizations for hierarchical machines, improving scalability of particle in cell by 8x and performance of sorting and a stencil code by up to 40% and 14%, respectively.  ...  We also demonstrated that hierarchical teams enable optimizations for hierarchical machines to be written in the context of a single programming model, enabling increased performance in sorting and better  ... 
doi:10.1007/978-3-319-09967-5_1 fatcat:ycncp2v3pzh2zjwqvv76d3qmkq

Study of Selective Ensemble Learning Methods Based on Support Vector Machine

Kai Li, Zhibin Liu, Yanxia Han
2012 Physics Procedia  
In this paper, we choose support vector machine as base classifier and study four methods of selective ensemble learning which include hill-climbing, ensemble forward sequential selection, ensemble backward  ...  Meanwhile, when using clustering selective strategy, selecting different number of clusters in this experiment also does not impact on the ensemble performance except some dataset.  ...  Acknowledgment The authors would like to thank Hebei Natural Science Foundation for its financial support (No: F2009000236).  ... 
doi:10.1016/j.phpro.2012.05.247 fatcat:3he2qho2f5gz5l6axf42fbcm3a

Adaptive Performance Modeling on Hierarchical Grid Computing Environments

Wahid Nasri, Luiz Angelo Steffenel, Denis Trystram
2007 Seventh IEEE International Symposium on Cluster Computing and the Grid (CCGrid '07)  
In the past, efficient parallel algorithms have always been developed specifically for the successive generations of parallel systems (vector machines, shared-memory machines, distributed-memory machines  ...  Today, due to many reasons, such as the inherent heterogeneity, the diversity, and the continuous evolution of the existing parallel execution supports, it is very hard to solve efficiently a target problem  ...  leading to a wide variety of execution supports.  ... 
doi:10.1109/ccgrid.2007.17 dblp:conf/ccgrid/NasriST07 fatcat:mwvet4iduzb5vhapzitjlbhf6a

Kriya - An end-to-end Hierarchical Phrase-based MT System

Baskaran Sankaran, Majid Razmara, Anoop Sarkar
2012 Prague Bulletin of Mathematical Linguistics  
This paper describes Kriya -a new statistical machine translation (SMT) system that uses hierarchical phrases, which were first introduced in the Hiero machine translation system (Chiang, 2007) .  ...  There are several re-implementations of Hiero in the machine translation community, but Kriya offers the following novel contributions: (a) Grammar extraction in Kriya supports extraction of the full set  ...  statistical machine translation models, including word-based models, phrase-based models and hierarchical phrase-based models. cdec provides support for Hadoop (an implementation of a distributed filesystem  ... 
doi:10.2478/v10108-012-0004-y fatcat:wg5oybrczfellc46ctiprdjp5q

An Approach to Human Machine Teaming in Legal Investigations Using Anchored Narrative Visualisation and Machine Learning

Simon Attfield, Bob Fields, David Windridge, Kai Xu
2019 International Conference on Artificial Intelligence and Law  
In this paper, we propose an approach to this problem by: (a) allowing users to visually externalise their evolving mental models of an investigation domain in the form of thematically organized Anchored  ...  support and enhance investigator cognition and team-based collaboration.  ...  The hierarchical aspect of the problem significantly multiplies the complexity of the machine learning methodology required to approach it.  ... 
dblp:conf/icail/AttfieldFW019 fatcat:icbmfvsffjfb5jkhrnq7qfvdwy
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