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arXiv 2019年

作者： Pakrashi, Arjun Chaudhuri, Bidyut B. Insight Centre for Data Analytics University College Dublin Ireland Computer Vision & Pattern Recognition Unit Indian Statistical Institute 203 B.T. Road Kolkata700108 India

Clustering algorithms have regained momentum with recent popularity of data mining and knowledge discovery approaches. To obtain good clustering in reasonable amount of time, various meta-heuristic approaches and their hybridization, sometimes with K-Means technique, have been employed. A Kalman Filtering based heuristic approach called Heuristic Kalman Algorithm (HKA) has been proposed a few years ago, which may be used for optimizing an objective function in data/feature space. In this paper at first HKA is employed in partitional data clustering. Then an improved approach named HKA-K is proposed, which combines the benefits of global exploration of HKA and the fast convergence of K-Means method. Implemented and tested on several datasets from UCI machine learning repository, the results obtained by HKA-K were compared with other hybrid meta-heuristic clustering approaches. It is shown that HKA-K is atleast as good as and often better than the other compared algorithms. Copyright © 2019, The Authors. All rights reserved.

关键词： Kalman filters

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Towards a Video Browser for the Digital Native

Towards a Video Browser for the Digital Native

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IEEE International Conference on Multimedia and Expo Workshops (ICMEW)

作者： Brett Adams Stewart Greenhill Svetha Venkatesh Institute for Multi-sensor Processing and Content Analysis (IMPCA) Curtin University of Technology Perth WA Australia Centre for Pattern Recognition and Data Analytics (PRaDA) Deakin University Geelong VIC Australia

Almost every aspect of how we create, transmit, and consume video has changed, but video interfaces still mimic those from video's inception. We extend Temporal Semantic Compression for interactive video browsing, which uses an arbitrary frame-by-frame interest measure to sub-sample video in real time, with user interface elements that visualize these measures and the effect of compressing on them. We experiment with a novel interest measure for popularity, and design novel visualizations for expressing interest measures and the compression interaction. We conduct the first formative evaluation of the TSC paradigm, with 8 subjects, and report design implications arising from it.

关键词： Browsers Visualization Motion pictures Color Streaming media Media Semantics

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The influence of pharmacological autonomic blockades on multi-scale measures of heart rate variability

The influence of pharmacological autonomic blockades on mult...

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Joint Conference of the European Medical and Biological Engineering Conference, EMBEC 2017 and Nordic-Baltic Conference on Biomedical Engineering and Medical Physics, NBC 2107

作者： Marzbanrad, Faezeh Karmakar, C.K. Khandoker, A.H. Palaniswami, M. Moritani, T. Jelinek, H.F. Department of Electrical and Computer Systems Engineering Monash University ClaytonVIC3168 Australia Centre for Research in Complex Systems and School of Community Health Charles Sturt University Albury Australia Centre of Pattern Recognition and Data Analytics Deakin University GeelongVIC Australia Khalifa University of Science Technology and Research Abu Dhabi United Arab Emirates The University of Melbourne ParkvilleVIC3010 Australia Kyoto University Kyoto Japan

ISBN: (纸本)9789811051210

Multi-scale measures have been used extensively to characterize non-linear dynamics of heart beats. However a physiological interpretation of the exponents associated with various scales of these measures and the role of the sympathetic and parasympathetic activities have not been attempted. In this study three multi-scale measures were compared at different scales in a pharmacological autonomic blockade experiment, starting with a control phase. It was then followed by injection of propranolol causing sympathetic blockade and injection of atropine resulting in the blockade of both sympathetic and parasympathetic pathways. Multiscale Entropy (MSE), Multi Fractal Detrended Fluctuation Analysis (MFDFA) and Renyi Entropy (RE) were compared using a paired test statistics. The measures performed differently depending on the scale factors and RE showed the best results indicating a good discrimination particularly at higher scale exponents. This study provides a basis for understanding the effect of autonomic activity on multi-scale measures with respect to changes in parasympathetic and sympathetic activity. © Springer Nature Singapore Pte Ltd. 2018.

关键词： Entropy

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Analysing the History of Autism Spectrum Disorder Using Topic Models

Analysing the History of Autism Spectrum Disorder Using Topi...

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International Conference on data Science and Advanced analytics (DSAA)

作者： Adham Beykikhoshk Dinh Phung Ognjen Arandjelović Svetha Venkatesh Centre for Pattern Recognition and Data Analytics Deakin University Geelong Australia School of Computer Science University of St Andrews Fife Scotland United Kingdom University of Saint Andrews Saint Andrews Fife GB

ISBN: (纸本)9781509052073

We describe a novel framework for the discovery of underlying topics of a longitudinal collection of scholarly data, and the tracking of their lifetime and popularity over time. Unlike the social media or news data where the underlying topics evolve over time, the topic nuances in science result in new scientific directions to emerge. Therefore, we model the longitudinal literature data with a new approach that uses topics which remain identifiable over the course of time. Current studies either disregard the time dimension or treat it as an exchangeable covariate when they fix the topics over time or do not share the topics over epochs when they model the time naturally. We address these issues by adopting a non-parametric Bayesian approach. We assume the data is partially exchangeable and divide it into consecutive epochs. Then, by fixing the topics in a recurrent Chinese restaurant franchise, we impose a static topical structure on the corpus such that the topics are shared across epochs and the documents within epochs. We demonstrate the effectiveness of the proposed framework on a collection of medical literature related to autism spectrum disorder. We collect a large corpus of publications and carefully examine two important research issues of the domain as case studies. Moreover, we make the results of our experiment and the source code of the model, freely available to the public. This aids other researchers to analyse our results or apply the model to their data collections.

关键词： data models Autism Computational modeling Analytical models Atomic measurements Probability distribution Probabilistic logic

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Analysing effect of heart rate and age on radial artery pressure derived systolic and diastolic durations in healthy adults

Analysing effect of heart rate and age on radial artery pres...

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Computers in Cardiology (CinC)

作者： Peng Li Chandan Karmakar Chengyu Liu Changchun Liu School of Control Science and Engineering Shandong University Jinan China Centre of Pattern Recognition and Data Analytics (PRaDA) Deakin University Geelong Australia Electrical & Electronic Engineering Department University of Melbourne Melbourne Australia

The measurements of cardiac systolic duration (SD) and diastolic duration (DD) have been well accepted as helpful tools for evaluating the cardiac functionality. In clinical practice, SD and DD are generally measured using echocardiography or heart sound signals. Recent studies have seen the attempts of approximating SD and DD by electrocardiogram (ECG) derived QT and TQ intervals, as well as radial artery pressure (RAP) derived foot-to-notch and notch-to-foot intervals. However, to the best of knowledge, there lacks deep elucidations on their performance when used as surrogate SD and DD data. We investigated the RAP-derived SD, DD, and ratio of SD to DD (S/D), to heart rate (HR) and age in healthy adults. Sixty healthy subjects were enrolled and their ECG and RAP signals were simultaneously recorded. The SD and DD were extracted automatically from RAP with the aid of the acceleration RAP. The HR was calculated using the RR interval extracted from ECG. Their mean values of 10 cardiac cycles were used in the analysis. Results demonstrated a negative linear relationship between SD and HR, a negative nonlinear relationship between DD and HR, and a positive linear relationship between S/D and HR (all p

关键词： Heart rate Pediatrics Wrist Electrocardiography Fitting Hafnium

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Influence of embedding dimension on distribution entropy in analyzing heart rate variability

Influence of embedding dimension on distribution entropy in ...

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Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC)

作者： Radhagayathri K. Udhayakumar Chandan Karmakar Peng Li Marimuthu Palaniswami Department of Electrical & Electronic Engineering The University of Melbourne Melbourne VIC Australia Centre of Pattern Recognition and Data Analytics (PRaDA) Deakin University Geelong VIC Australia The School of Control Science and Engineering Shandong University Jinan China

ISBN: (纸本)9781457702198

Distribution entropy (DistEn) is a recent measure of complexity that is used to analyze Heart Rate Variability (HRV) data. DistEn which is a function of data length N, number of bins M and embedding dimension m is known to be stable and consistent with respect to parameters N and M respectively. Also, (N, M) are known to have a combined effect in deciding performance of DistEn as a classification feature. But, all such analysis have mostly ignored the influence of the third parameter m on DistEn properties. Though a random fixed choice of m value has so far succeeded in portraying the effect of other parameters on DistEn, it is considered equally important to reveal the influence of a varying m on DistEn and its characteristics. This study examines the impact of m on the stability, consistency and performance of DistEn when the latter is used to analyze HRV data belonging to (i) healthy subjects discerned by age and (ii) subjects discerned by their heart's physiologic condition. Here, data length N of each signal is varied from 50 to 1000, while the number of bins M used varies from 100 to 2000. Information pertaining to m variations is obtained by carrying out experiments at four different values of embedding dimension; m = 2, 3,4 and 5. The study shows that the stability, consistency and classification performance of DistEn is not much influenced by changes in m.

关键词： Gold databases Entropy Time series analysis Heart rate variability Stability analysis Physiology

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A novel technique to investigate the effect of ageing on ventricular repolarization characteristics in healthy and LQTS subjects

A novel technique to investigate the effect of ageing on ven...

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Annual International Conference of the IEEE Engineering in Medicine and Biology Society

作者： Mohammad H Imam Chandan K Karmakar M Palanaiswami Ahsan H Khandoker the Department of Electrical & Electronic Engineering The University of Melbourne Melbourne VIC 3010 Australia. the centre for Pattern Recognition and Data Analytics Deakin University Geelong Australia the Department of Biomedical Engineering Khalifa University of Science Technology and Research Abu Dhabi UAE

ISBN: (纸本)9781424492695

Ventricular repolarization(VR) characteristics is affected by ageing alongside several other factors like Heart rate(HR),respiration, modulation of autonomic nervous system, different drug effects, genetical factors affecting the cardiac ion channel characteristics, gender etc. Therefore, total VR variability (i.e. QT interval variability in surface ECG) consists of two components: one dependent on HR variability (HRV) and another independent of HRV. Analysis of QT interval variability (QTV) is crucial for both healthy and pathological conditions as increase in VR variability measured by QTV increases cardiac repolarization instability, which might lead to arrhythmogenesis. Analyzing the effect of ageing using a widely used measure of QTV (i.e. QTVI) is reported inconsistently in Healthy subjects whereas the same for Long QT Syndrome (LQTS) subjects is not widely reported. In this study, we propose a novel time domain measure from beat-to-beat QT-RR distribution to analyze how ageing affects VR in both Healthy and a group of genotyped LQTS1 subjects. A total of 139 Healthy subjects and 134 LQTS1 subjects of three different age groups (i.e. Young: age 20-35, Middle-aged: 40-55 and Old: age>60) were analyzed for this study. The proposed measure is also compared with other existing widely used measures of QTV like SDQT and QTVI in differentiating different age groups. The proposed measure stands out to be more discriminatory than other existing variability measures of QT interval.

关键词： LQTS HRV SDQT

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Approximation vector machines for large-scale online learning

The Journal of Machine Learning Research

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The Journal of Machine Learning Research 2017年第1期18卷

作者： Trung Le Tu Dinh Nguyen Vu Nguyen Dinh Phung Centre for Pattern Recognition and Data Analytics School of Information Technology Deakin University Australia

One of the most challenging problems in kernel online learning is to bound the model size and to promote model sparsity. Sparse models not only improve computation and memory usage, but also enhance the generalization capacity - a principle that concurs with the law of parsimony. However, inappropriate sparsity modeling may also significantly degrade the performance. In this paper, we propose Approximation Vector Machine (AVM), a model that can simultaneously encourage sparsity and safeguard its risk in compromising the performance. In an online setting context, when an incoming instance arrives, we approximate this instance by one of its neighbors whose distance to it is less than a predefined threshold. Our key intuition is that since the newly seen instance is expressed by its nearby neighbor the optimal performance can be analytically formulated and maintained. We develop theoretical foundations to support this intuition and further establish an analysis for the common loss functions including Hinge, smooth Hinge, and Logistic (i.e., for the classification task) and l1, l2, and ε-insensitive (i.e., for the regression task) to characterize the gap between the approximation and optimal solutions. This gap crucially depends on two key factors including the frequency of approximation (i.e., how frequent the approximation operation takes place) and the predefined threshold. We conducted extensive experiments for classification and regression tasks in batch and online modes using several benchmark datasets. The quantitative results show that our proposed AVM obtained comparable predictive performances with current state-of-the-art methods while simultaneously achieving significant computational speed-up due to the ability of the proposed AVM in maintaining the model size.

关键词： big data convergence analysis core set kernel large-scale machine learning online learning sparsity stochastic gradient descent

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Heart rate independent QT variability component can detect subclinical cardiac autonomic neuropathy in diabetes

Heart rate independent QT variability component can detect s...

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Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC)

作者： Mohammad H Imam Chandan K Karmakar Ahsan H Khandoker Herbert F Jelinek M Palaniswami Department of Electrical & Electronic Engineering The University of Melbourne Melbourne VIC Australia Centre for Pattern Recognition and Data Analytics Deakin University Geelong Australia Department of Biomedical Engineering Khalifa University of Science Technology and Research Abu Dhabi UAE School of Community Health Charles Sturt University Albury Australia

ISBN: (纸本)9781457702198

Cardiac autonomic neuropathy (CAN) may lead to life threatening arrhythmia due to denervation of both the parasympathetic and sympathetic branches of autonomic nervous system innervating the heart. CAN is a frequently under diagnosed complication of diabetes, because a patient can have asymptomatic CAN for several years before it is clinically apparent. However, detection of CAN at the early or subclinical stage leads to more effective treatment outcomes. Cardiac autonomic reflex tests (CART) (i.e. Ewing test battery) are normally used for the detection and staging of CAN. These tests have limitations with the necessity of active participation of the patients for test maneuvers, as a majority of patients will not be able to complete all five tests required due to comorbidities such as frailty, obesity or cardiorespiratory disease. CAN affects both heart rate (measured by RR interval dynamics) and ventricular repolarization function (i.e. QT interval dynamics) of the heart, which can be efficiently analyzed from surface ECG. Therefore, ECG based diagnosis techniques of CAN analysis are becoming popular as they can reduce the limitations of CARTs used traditionally for CAN detection and it complements CART results. In this study, the performance of an ECG based QTV feature derived using a model free approach, which can quantify the QTV component not affected directly by the heart rate (HR) variation, is compared with some other measures of QTV and HRV in subclinical CAN detection in diabetes. Short-term ECGs (i.e. 5 min long) of 60 diabetic subjects without CAN and 50 diabetic subjects detected with early level of CAN determined by CART were analyzed. The proposed measure for quantifying the QTV component independent of HR denoted as QTV~RR stands out to be more discriminatory than other existing variability measures of QTV and HRV in subclinical detection of CAN.

关键词： sugar blood cardiovascular system diseases electrocardiography feature extraction medical signal processing

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Hybrid genetic-discretized algorithm to handle data uncertainty in diagnosing stenosis of coronary arteries

Hybrid genetic-discretized algorithm to handle data uncertai...

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作者： Alizadehsani, Roohallah Roshanzamir, Mohamad Abdar, Moloud Beykikhoshk, Adham Khosravi, Abbas Nahavandi, Saeid Plawiak, Pawel Tan, Ru San Acharya, U Rajendra Deakin University GeelongVIC Australia Department of Engineering Fasa Branch Islamic Azad University Fars Fasa Iran Centre for Pattern Recognition and Data Analytics Deakin University GeelongVIC Australia Department of Information and Communications Technology Faculty of Computer Science and Telecommunications Cracow University of Technology Warszawska 24 st. F-3 31-155 Krakow Poland Institute of Theoretical and Applied Informatics Polish Academy of Sciences Baltycka 5 Gliwice44-100 Poland National Heart Centre Singapore Singapore Department of Electronics and Computer Engineering Ngee Ann Polytechnic Singapore Department of Biomedical Engineering School of Science and Technology Singapore University of Social Sciences Singapore Department of Bioinformatics and Medical Engineering Asia University Taiwan

Coronary artery disease (CAD) is the leading cause of morbidity and death worldwide. Invasive coronary angiography is the most accurate technique for diagnosing CAD, but is invasive and costly. Hence, analytical methods such as machine learning and data mining techniques are becoming increasingly more popular. Although physicians need to know which arteries are stenotic, most of the researchers focus only on CAD detection and few studies have investigated stenosis of the right coronary artery (RCA), left circumflex (LCX) artery and left anterior descending (LAD) artery separately. Meanwhile, most of the datasets in this field are noisy (data uncertainty). However, to the best of our knowledge, there is no study conducted to address this important problem. This study uses the extension of the Z-Alizadeh Sani dataset, containing 303 records with 54 features. A new feature selection algorithm is proposed in this work. Meanwhile, by discretization of data, we also handle the uncertainty in CAD prediction. To the best of our knowledge, this is the first study attempted to handle uncertainty in CAD prediction. Finally, the genetic algorithm (GA) is used to determine the hyper-parameters of the support vector machine (SVM) kernels. We have achieved high accuracy for the stenosis diagnosis of each main coronary artery. The results of this study can aid the clinicians to validate their manual stenosis diagnosis of RCA, LCX and LAD coronary arteries. © 2020 John Wiley & Sons, Ltd.

关键词： Feature Selection

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