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IEEE International Conference on Cognitive Informatics

作者： Yingxu Wang Omar A. Zatarain Mehrdad Valipour Information Systems Lab Packard Stanford University Stanford CA USA Dept. of Electrical and Computer Engineering Hotchkiss Brain Institute University of Calgary Calgary Alberta Canada Dept. of Computer Science and Engineering CU Valles University of Guadalajara Guadalajara Jalisco Mexico

ISBN: (纸本)9781509038473

Concept elicitation is centric for machine knowledge extraction and representation in cognitive robot learning. This paper presents a supervised methodology for machine concept elicitation from informal counterparts described in natural languages. The collective opinions of a given concept in ten selected dictionaries are quantitatively analyzed and formally represented according to the attribute-object-relation (OAR) pattern of formal concepts. The concept elicitation methodology for machine learning is aimed to deal with complex problems inherited in informal concepts of natural languages such as diversity, redundancy, ambiguity, inexplicit semantics, inconsistent attributes/objects, mixed synonyms, and fuzzy hyper-/hypo-concept relations. The system of formal concept elicitation is implemented by an algorithms in MATLAB for formal concept extraction and representation. Experiments on supervised machine learning for creating twenty primitive concepts reveal that a cognitive robot is able to learn synergized concepts in human knowledge in order to build its own cognitive knowledge base.

关键词： Instruments Ink Writing

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Online Machine Learning for Big Data Analytics by Cognitive Robots

Online Machine Learning for Big Data Analytics by Cognitive ...

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2016 IEEE International Conference of Online Analysis and Computing science(ICOACS 2016)

作者： Yingxu Wang FICIC FWIF Information Systems Lab Stanford University Laboratory for Computational Intelligence Denotational Mathematicsand Software Science Dept.of Electrical and Computer EngineeringSchulich School of Engineering and Hotchkiss Brain InstituteUniversity of Calgary

It is recognized that both sources of and solutions to the big data challenges are human collective *** are an abstract representation of the quantity of realistic entities and perceived *** data play an indispensable role not only in a wide range of engineering applications,but also in the cognitive mechanisms of both humans and cognitive robots such as sensation,quantification,qualification,estimation,memory,and *** keynote lecture presents online big data analytic theories by machine learning as well as knowledge extraction by cognitive ***,information,knowledge,and intelligence are the four hierarchical layers of cognitive objects in the brain and cognitive systems from the bottom *** is discovered by the author that,although the cognitive unit of data is bit,that of knowledge is bir,i.e.,a binary relation.A resent finding towards big data science is that big data systems in nature are a recursive ndimensional typed hyperstructure(RNDTHS).This topological property of big data reveals that the mathematical foundation of big data science is underpinned by big data algebra(BDA),which is a denotational mathematical structure for efficiently dealing with the inherited complexities and unprecedented challenges in big data *** leads to a coherent theory for big data modeling,analyses,mining,information elicitation,knowledge extraction,and intelligent generation for cognitive *** experiments demonstrate that cognitive robots may autonomously transform big data in vast linguistic databases(corpuses) into sophistic knowledge bases by cognitive machine learning.

关键词： Big data big data science denotational mathematics mathematical models recursively hierarchical hyperstructures big data algebra cogniitve machine learning formal concepts knowledge extraction knowledge generation cognitive informatics cognitive computing computational intelligence applications

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A server-side framework for the execution of procedurally generated quests in an mmorpg 16

A server-side framework for the execution of procedurally ge...

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16th International Conference on Intelligent Games and Simulation, GAME ON 2015

作者： Doran, Jonathon Parberry, Ian Dept. of Computer Science and Information Systems Bradley University United States Dept. of Computer Science and Engineering University of North Texas United States

ISBN: (纸本)9789077381915

We describe a framework for executing procedurally generated quests implemented in the MMORPG Everquest using the Open Source EQEmu Everquest server. Quests play out at run-time using a collection of triggers, which consist of a testable game state condition and a script that is to be run when the condition is satisfied. We describe the interface between the quest generator and the server which enables the seamless integration of the procedurally generated quests within the existing server architecture. To demonstrate how this process takes place in real time, we analyze a nontrivial procedurally generated quest and describe the key server controlled actions that derive from it.

关键词： MMO Procedural content generation

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Control of Three-Phase Voltage Source Converters with the Derivative-Free Nonlinear Kalman Filter

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Intelligent Industrial systems 2016年第1期2卷 21-33页

作者： G. Rigatos P. Siano N. Zervos C. Cecati Unit of Industrial Automation Industrial Systems Institute Patras Greece Dept. of Industrial Eng. University of Salerno Fisciano Italy Department of Information Engineering Computer Science and Mathematics University of L’ Aquila Via Vetoio L’Aquila Italy

The paper is concerned with proving differential flatness of the three-phase voltage source converter (VSC) model and its resulting description in the Brunovsky (canonical) form. For the linearized canonical model of the converter a feedback controller is designed. At a second stage, a novel Kalman Filtering method (Derivative-free nonlinear Kalman Filtering) is introduced. The proposed Kalman Filter is redesigned as disturbance observer for estimating additive input disturbances to the VSC model. These estimated disturbance terms are finally used by a feedback controller that enables the DC output voltage track desirable setpoints. The efficiency of the proposed state estimation-based control scheme is tested through simulation experiments.

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Identifying the best machine learning algorithms for brain tumor segmentation, progression assessment, and overall survival prediction in the BRATS challenge

arXiv

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arXiv 2018年

作者： Bakas, Spyridon Reyes, Mauricio Jakab, Andras Bauer, Stefan Rempfler, Markus Crimi, Alessandro Shinohara, Russell Takeshi Berger, Christoph Ha, Sung Min Rozycki, Martin Prastawa, Marcel Alberts, Esther Lipkova, Jana Freymann, John Kirby, Justin Bilello, Michel Fathallah-Shaykh, Hassan M. Wiest, Roland Kirschke, Jan Wiestler, Benedikt Colen, Rivka Kotrotsou, Aikaterini Lamontagne, Pamela Marcus, Daniel Milchenko, Mikhail Nazeri, Arash Weber, Marc-Andr Mahajan, Abhishek Baid, Ujjwal Gerstner, Elizabeth Kwon, Dongjin Acharya, Gagan Agarwal, Manu Alam, Mahbubul Albiol, Alberto Albiol, Antonio Albiol, Francisco J. Alex, Varghese Allinson, Nigel Amorim, Pedro H.A. Amrutkar, Abhijit Anand, Ganesh Andermatt, Simon Arbel, Tal Arbelaez, Pablo Avery, Aaron Azmat, Muneeza Pranjal, B. Bai, Wenjia Banerjee, Subhashis Barth, Bill Batchelder, Thomas Batmanghelich, Kayhan Battistella, Enzo Beers, Andrew Belyaev, Mikhail Bendszus, Martin Benson, Eze Bernal, Jose Bharath, Halandur Nagaraja Biros, George Bisdas, Sotirios Brown, James Cabezas, Mariano Cao, Shilei Cardoso, Jorge M. Carver, Eric N. Casamitjana, Adri Castillo, Laura Silvana Cat, Marcel Cattin, Philippe Cérigues, Albert Chagas, Vinicius S. Chandra, Siddhartha Chang, Yi-Ju Chang, Shiyu Chang, Ken Chazalon, Joseph Chen, Shengcong Chen, Wei Chen, Jefferson W. Chen, Zhaolin Cheng, Kun Choudhury, Ahana Roy Chylla, Roger Clrigues, Albert Colleman, Steven Colmeiro, Ramiro German Rodriguez Combalia, Marc Costa, Anthony Cui, Xiaomeng Dai, Zhenzhen Dai, Lutao Daza, Laura Alexandra Deutsch, Eric Ding, Changxing Dong, Chao Dong, Shidu Dudzik, Wojciech Eaton-Rosen, Zach Egan, Gary Escudero, Guilherme Estienne, Tho Everson, Richard Fabrizio, Jonathan Fan, Yong Fang, Longwei Feng, Xue Ferrante, Enzo Fidon, Lucas Fischer, Martin French, Andrew P. Fridman, Naomi Fu, Huan Fuentes, David Gao, Yaozong Gates, Evan Gering, David Gholami, Amir Gierke, Willi Glocker, Ben Gong, Mingming Gonzlez-Vill, Sandra Grosges, T. Guan, Yuanfang Guo, Sheng Gupta, Sudeep Han, Woo-Sup Han, Il Song Harmuth, Ko Center for Biomedical Image Computing and Analytics University of Pennsylvania PhiladelphiaPA United States Department of Radiology Perelman School of Medicine University of Pennsylvania PhiladelphiaPA United States Department of Pathology and Laboratory Medicine Perelman School of Medicine University of Pennsylvania PhiladelphiaPA United States Institute for Surgical Technology and Biomechanics University of Bern Bern Switzerland Center for MR-Research University Children's Hospital Zurich Zurich Switzerland Support Centre for Advanced Neuroimaging Inselspital Institute for Diagnostic and Interventional Neuroradiology Bern University Hospital Bern Switzerland University Hospital of Zurich Zurich Switzerland Center for Clinical Epidemiology and Biostatistics University of Pennsylvania Philadelphia United States Image-Based Biomedical Modeling Group Technical University of Munich Munich Germany Icahn School of Medicine Mount Sinai Health System New YorkNY United States Leidos Biomedical Research Inc. Frederick National Laboratory for Cancer Research FrederickMD21701 United States Cancer Imaging Program National Cancer Institute National Institutes of Health BethesdaMD20814 United States Department of Neurology University of Alabama at Birmingham BirminghamAL United States Department of Diagnostic Radiology University of Texas MD Anderson Cancer Center HoustonTX United States Department of Psychology Washington University St. LouisMO United States Neuroimaging Informatics and Analysis Center Washington University St. LouisMO United States Department of Radiology Washington University St. LouisMO United States Institute of Diagnostic and Interventional Radiology Pediatric Radiology and Neuroradiology University Medical Center Rostock Ernst-Heydemann-Str. 6 Rostock18057 Germany Tata Memorial Centre Homi Bhabha National Institute Mumbai India Shri Guru Gobind Singhji Institute of Engineering and Technology Nanded India NVIDIA Santa Clara

Gliomas are the most common primary brain malignancies, with different degrees of aggressiveness, variable prognosis and various heterogeneous histologic sub-regions, i.e., peritumoral edematous/invaded tissue, necrotic core, active and non-enhancing core. This intrinsic heterogeneity is also portrayed in their radio-phenotype, as their sub-regions are depicted by varying intensity profiles disseminated across multi-parametric magnetic resonance imaging (mpMRI) scans, reflecting varying biological properties. Their heterogeneous shape, extent, and location are some of the factors that make these tumors difficult to resect, and in some cases inoperable. The amount of resected tumor is a factor also considered in longitudinal scans, when evaluating the apparent tumor for potential diagnosis of progression. Furthermore, there is mounting evidence that accurate segmentation of the various tumor sub-regions can offer the basis for quantitative image analysis towards prediction of patient overall survival. This study assesses the state-of-the-art machine learning (ML) methods used for brain tumor image analysis in mpMRI scans, during the last seven instances of the International Brain Tumor Segmentation (BraTS) challenge, i.e., 2012-2018. Specifically, we focus on i) evaluating segmentations of the various glioma sub-regions in pre-operative mpMRI scans, ii) assessing potential tumor progression by virtue of longitudinal growth of tumor sub-regions, beyond use of the RECIST/RANO criteria, and iii) predicting the overall survival from pre-operative mpMRI scans of patients that underwent gross total resection. Finally, we investigate the challenge of identifying the best ML algorithms for each of these tasks, considering that apart from being diverse on each instance of the challenge, the multi-institutional mpMRI BraTS dataset has also been a continuously evolving/growing dataset. Copyright © 2018, The Authors. All rights reserved.

关键词： Tumors

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Modeling method of execution timing of operation to analyze the reaction time from judgment to execution of operation

Modeling method of execution timing of operation to analyze ...

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Annual Conference of Industrial Electronics Society

作者： Kohjiro Hashimoto Shinji Doki Kae Doki Dept. of Control and Information Systems Engineering National Institute of Technology Kumamoto College 2659–2 Suya Koshi Kumamoto Dept. of Electrical Engineering and Computer Science Nagoya University C3-1(631) Furo-cho Chikusa-ku Nagoya Aichi Dept. of Electrical Engineering Aichi Institute of Technology Toyota Aichi

In this study, we aim to evaluate a driver skill based on the driver behavior model generated by the operation and environment data under driving vehicle. When skill of driver is reduced, the operator behavior is delayed, it takes along time of operation, and execution timing of operation is no reproducibility. These mean that reducing skill of driver affects time information of the driver operation. Therefore, we study on the model structure incorporated time information expresses the execution timing of driver's operation to evaluate driver's skill. In particular, we propose a new model structure incorporated timing probabilistic distribution expresses the time until the execution of next operation. Moreover, we propose a modeling method of operator behavior according to proposed model structure. It is considered that the reaction time from the decision to execution of operation and ambiguity of the decision can be read from the timing probabilistic distribution. In this paper, the above usefulness is examined through some experimental results. Moreover, the applicability of the driving skill evaluation based on the proposed operation model is examined.

关键词： Computational modeling Hidden Markov models Time series analysis

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An Intraoperative Glucose Control Benchmark for Formal Verification

An Intraoperative Glucose Control Benchmark for Formal Verif...

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作者： Chen, Sanjian O'Kelly, Matthew Weimer, James Sokolsky, Oleg Lee, Insup Dept. of Computer and Information Science University of Pennsylvania Philadelphia United States Dept. of Electrical and Systems Engineering University of Pennsylvania Philadelphia United States

Diabetes associated complications are affecting an increasingly large population of hospitalized patients. Since glucose physiology is significantly impacted by patient-specific parameters, it is critical to verify that a clinical glucose control protocol is safe across a wide patient population. A safe protocol should not drive the glucose level into dangerous low (hypoglycemia) or high (hyperglycemia) ranges. Verification of glucose controllers is challenging due to the high-dimensional, non-linear glucose physiological models which contain both unobservable states and unmeasurable patient-specific parameters. This paper presents a hybrid system model of a closed-loop physiological system that includes an existing FDA-accepted high-fidelity physiological model tailored to intraoperative settings and a validated improvement to a clinical glucose control protocol for diabetic cardiac surgery patients. We propose the closed-loop model as a physiological system benchmark for verification and present our initial results on verifying the system using the SMT-based hybrid system verification tool dReach. © 2015, IFAC (International Federation of Automatic Control) Hosting by Elsevier Ltd. All rights reserved.

关键词： Medical applications

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Design of a Cloud-based Bike-fleet POI touring service platform 24

Design of a Cloud-based Bike-fleet POI touring service platf...

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24th International Conference on software engineering and Data engineering, SEDE 2015

作者： Ku, Hao-Hsiang Ouyang, Maio Huang, Si-Yuan Dept. of Computer Science and Information Engineering Hwa-Hsia University of Technology New Taipei City Taiwan Dept. of Management Information Systems National Pingtung University of Science and Technology Pingtung Taiwan

ISBN: (纸本)9781510812277

Travel lights are more and more popular. Many residents and travelers enjoy traveling using bikes in Taiwan. Hence, this study designs a Cloud-based Bike-fleet POI Touring Service Platform, which is called C-BOOST, to help people make travel plans. C-BOOST is composed of Bikers and a Cloud-based Digital Convergence Server (CDCS). Bikers can use a smart-phone to get potential Point of Interests (POIs), to get Location-based Services (LBSs), to update traveling itineraries and to manage bike-fleets. Cloud-based Digital Convergence Server is based on Mass Behaviors Model, which provides RSS, Google App Engine (GAE) and Quality Control Adaptor services. Quality Control Adaptor is composed of Ant Colony Optimization (ACO) algorithm, Bayesian Network and Ontology by users' preferences and GPS values, providing potential POIs for bikers. C-BOOST can provide more suitable POIs for bikers.

关键词： Smartphones

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Customizable Holter monitor using off-the-shelf components

Customizable Holter monitor using off-the-shelf components

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International Conference on Advances in Computing, Communications and Informatics (ICACCI)

作者： S Sreekesh Abhimanyu Zala G Keerthi Chavan Neena Goveas Dept. Electrical Electronics & Instrumentation Engineering BITS Pilani K K Birla Goa Campus Goa INDIA Department of Computer Science and Information Systems BITS Pilani K K Birla Goa Campus Goa INDIA

ISBN: (纸本)9781509020300

A Holter Monitor is a device which is worn by patients and is used to collect Electrocardiography (ECG) data for around 24 hours. This device is then connected to a computer by a physician to download the data. An analysis of this data can reveal abnormalities which may not appear in a clinical measurement of shorter duration. Cost of a Holter monitor is a crucial parameter, as this is used by patients for longer duration, unlike other clinical instruments. Availability of devices restricts the number of patients which can be monitored and treated by hospitals. In addition patients require customization of measurements which most of the available device do not offer. The high cost of this device is deterring physicians from long term monitoring use like athletic performance of sportsmen, elderly patients for independent living, patients taking medications causing side-effects etc. In this paper we present a low cost Holter Monitor which can be assembled using off the shelf components. It can be customized for individual needs and is extendable. The software architecture and communication framework developed can be used for any data intensive measurement and transmission.

关键词： Electrocardiography Monitoring Biomedical monitoring Accelerometers Pins Medical services Microcontrollers

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Controller synthesis for autonomous systems interacting with human operators 15

Controller synthesis for autonomous systems interacting with...

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6th ACM/IEEE International Conference on Cyber-Physical systems, ICCPS 2015

作者： Feng, Lu Wiltsche, Clemens Humphrey, Laura Topcu, Ufuk Dept. of Computer and Information Science University of Pennsylvania United States Dept. of Computer Science University of Oxford United Kingdom Control Science Center of Excellence AFRL United Kingdom Dept. of Electrical and Systems Engineering University of Pennsylvania United States

ISBN: (纸本)9781450334556

We propose an approach to synthesize control protocols for autonomous systems that account for uncertainties and imperfections in interactions with human operators. As an illustrative example, we consider a scenario involving road network surveillance by an unmanned aerial vehicle (UAV) that is controlled remotely by a human operator but also has a certain degree of autonomy. Depending on the type (i.e., probabilistic and/or nondeterministic) of knowledge about the uncertainties and imperfections in the operator- Autonomy interactions, we use abstractions based on Markov- decision processes and augment these models to stochastic two-player games. Our approach enables the synthesis of operator-dependent optimal mission plans for the UAV, highlighting the effects of operator characteristics (e.g., workload. proficiency, and fatigue) 011 UAV mission performance;it can also provide informative feedback (e.g., Pareto curves showing the trade-offs between multiple mission objectives), potentially assisting the operator in decision-making.

关键词： Markov processes

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