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Nonlinear Analysis of Heart Sounds for the Detection of Cardiac Disorders Using Recurrence Quantification Analysis 44

Nonlinear Analysis of Heart Sounds for the Detection of Card...

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44th Computing in Cardiology Conference (CinC)

作者： Ghiasi, Shadi Abdollahpur, Mostafa Madani, Nasimalsadat Ghaffari, Ali KN Toosi Univ Technol Dept Mech Engn Cardiovasc Res Grp CVRG Tehran Iran

ISBN: (纸本)9781538645550;9781538666302

Introduction: Auscultation of heart sounds using digital stethoscope technology is an effective method for the diagnosis of various cardiovascular disorders. The characteristics of phonocardiography (PCG) signals can be represented by developing a computer based algorithm as a complementary tool to facilitate clinicians. Aims: This paper aims to address an effective feature extraction and classification technique to improve the detection of two common categories of cardiac arrhythmias, Mitral Valve Prolapse (MVP) and Coronary Artery Disease (CAD) using the heart sound recordings from PhysioNet/Computing in Cardiology 2016 challenge. Methods: Band pass Butterworth filtering is employed to pre-process PCG signals. After detecting heart beats using common segmentation algorithms, beats which are less contaminated by noise are selected using a combination of time and time-frequency analysis. Since heart murmurs are engendered from various abnormalities in the heart, they show different characteristics. To characterize these complexities in each abnormality, Recurrence Quantification Analysis is applied. In this method the Recurrence plots which represent the mechanisms underlying the heart dynamics are quantified into recursive parameters. These set of nonlinear features show a great discrimination between classes. The resulting features are transformed to a new space using Fisher's discriminant analysis (FDA), a dimensionally reduction technique, to reduce the computational complexity of the algorithm. The classification process is in two stage. First, the new dimension-reduced feature vector is the input of the fuzzy C-means clustering (FCM) to predict normal and abnormal class. Then, the obtained 10 dimensional feature vector form RQA analysis feds into a pattern recognition artificial neural network (ANN) to classify CAD and MVP recordings Results: Using PCG signals of CAD, MVP and normal recordings from PhysioNet/Computing in Cardiology 2016, normal signals are eas

关键词： Phonocardiography Feature extraction Classification algorithms Heuristic algorithms Artificial neural networks Heart beat Heart beat phonocardiography Feature extraction sorting algorithm Artificial neural networks Heuristic algorithms Heart Sounds cisplatin/mitomycin/vindesine NONLINEAR ANALYSIS Heart Recordings Eigenvector Butterworth filters Sensitivity and Specificity DFFB gene

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The Model of Remote Video Surveillance in Hierarchical Autonomous E-testing WbeTS System for Knowledge Testing

The Model of Remote Video Surveillance in Hierarchical Auton...

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37th International Convention on Information and Communication Technology, Electronics and Microelectronics (MIPRO)

作者： Purkovic, Damir Ban, Eugen Fac Humanities & Social Sci Rijeka Croatia Branch Off Rijeka Educ & Teacher Training Agcy Rijeka Croatia

ISBN: (纸本)9789532330816

The web-based system for online knowledge testing (WbeTS) is a hierarchical and modular autonomous system for remote knowledge assessment whose autonomy is based on remote video surveillance as one of the testing validation mechanisms. The main problem facing the system is the physical implementation of the video surveillance unit for remote monitoring of a student, as well as development of a decision making mechanism based on such monitoring. The monitoring would need to take place in conditions of widely available broadband Internet access and the use of a webcam. A possible solution is a model of the remote control described in this paper, which could solve this problem and make the system more reliable. The model is based on built-in elements and algorithms for visual recognition and motion tracking of the student, sound tracking, user (teacher) interface for assessing the validity of testing and of the system's kernel responsible for assessing the validity of the tests and reporting. The model is envisaged to be implemented accordingly to the wishes and needs of users, and can be integrated as a part of an integral e-learning environment. Although the model described is in principle technologically feasible, its practical realization requires professional refinement and experimental validation. Only by in-depth testing and experiences gained from the actual application of the system will be possible to identify all deficiencies and requirements that currently cannot be predicted.

关键词： Internet computer aided instruction decision making object recognition object tracking user interfaces video surveillance broadband Internet access decision making mechanism hierarchical autonomous e-testing WbeTS system integral e-learning environment motion tracking online knowledge testing remote control remote knowledge assessment remote monitoring remote video surveillance sound tracking user interface visual recognition web-based system webcam Classification algorithms Electronic learning Speech Testing Video surveillance video monitoring User Interface Device Component e-learning telemonitoring Web-based systems webcam REMOTE CONTROL computer-assisted instruction sorting algorithm object recognition Speech Internets

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Modeling Anomalies Prevalent In Sensor Network Deployments: A Representative Ground Truth

Modeling Anomalies Prevalent In Sensor Network Deployments: ...

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IEEE 21st Annual International Symposium on Modeling, Analysis and Simulation of Computer and Telecommunication (MASCOTS)

作者： Abuaitah, Giovani Rimon Wang, Bin Wright State Univ BMW Networking Res Lab Dayton OH 45435 USA

ISBN: (纸本)9780769551029

The performance of anomaly detection algorithms is usually measured using the total residual error. This error metric is calculated by comparing the labels assigned by the detection algorithm against a reference ground truth. Obtaining a highly expressive ground truth is by itself a challenging task, if not infeasible. Often, a dataset is manually labeled by domain experts. However, manual labeling is error prone. In real-world sensor network deployments, it becomes even more difficult to label a sensor dataset due to the large amount of samples, the complexity of visualizing the data, and the uncertainty in the existence of anomalies. This paper proposes an automated technique which uses highly representative anomaly models for labeling. We demonstrate the effectiveness of this technique through evaluating a classification algorithm using our designed anomaly models as ground truth. We show that the classification accuracy is similar to that when using manually labeled realworld data points.

关键词： anomaly detection automatic labeling data-centric anomalies ground truth sensor networks ground truth anomaly detection Sensor networks Detection algorithms error prone Manual handling Automated recording sorting algorithm

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Dependency Network Methods for Hierarchical Multi-label Classification of Gene Functions 5

Dependency Network Methods for Hierarchical Multi-label Clas...

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IEEE Symposium on Computational Intelligence and Data Mining (CIDM)

作者： Fabris, Fabio Freitas, Alex A. Univ Kent Sch Comp Canterbury CT2 7NF Kent England

ISBN: (纸本)9781479945184

Hierarchical Multi-label Classification (HMC) is a challenging real-world problem that naturally emerges in several areas. This work proposes two new algorithms using a Probabilistic Graphical Model based on Dependency Networks (DN) to solve the HMC problem of classifying gene functions into pre-established class hierarchies. DNs are especially attractive for their capability of using traditional, "out-of-the-shelf", classification algorithms to model the relationship among classes and for their ability to cope with cyclic dependencies, resulting in greater flexibility with respect to Bayesian Networks. We tested our two algorithms: the first is a stand-alone Hierarchical Dependency Network (HDN) algorithm, and the second is a hybrid between the HDN and the Predictive Clustering Tree (PCT) algorithm, a well-known classifier for HMC. Based on our experiments, the hybrid classifier, using SVMs as base classifiers, obtained higher predictive accuracy than both the standard PCT algorithm and the HDN algorithm, considering 22 bioinformatics datasets and two out of three predictive accuracy measures specific for hierarchical classification (AU((PRC) over bar) and (AUPRC) over bar (w)).

关键词： Bayes methods bioinformatics genetics network theory (graphs) pattern classification support vector machines Bayesian networks DN HMC problem PCT algorithm SVM base classifiers bioinformatics datasets class hierarchies cyclic dependencies gene function classification hierarchical multilabel classification hybrid algorithm hybrid classifier out-of-the-shelf classification algorithms predictive accuracy measures predictive clustering tree algorithm probabilistic graphical model real-world problem stand-alone HDN algorithm stand-alone hierarchical dependency network algorithm standard PCT algorithm Accuracy Classification algorithms Clustering algorithms Inference algorithms Markov processes Prediction algorithms Vectors Support Vector Network sorting algorithm Inference algorithms Bayesian networks Prediction algorithms Clustering algorithms dwarf novae Bayes methods Pattern recognition Bioinformatics Markov chain hardware motion compensation Genetics World problems Hierarchical

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Proposing a high performance face detector based on UKF 7

Proposing a high performance face detector based on UKF

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IEEE/SICE International Symposium on System Integration (SII)

作者： Lamsal, Bikash Matsumoto, Naofumi Ashikaga Inst Technol 268-1 Ohmae Cho Ashikaga Tochigi 3268558 Japan

ISBN: (纸本)9781479969449

In this paper, we propose a high performance algorithm for detecting human faces in a still image. Human faces help to communicate and interact in a better way that may be either in human-human interaction or human-machine interaction. The success points for our algorithm is the use of different individual algorithms along with the Unscented Kalman filter (UKF) process, as a novelty of our process. We have modified the algorithms as well. We used Viola Jones eye detector, skin color detector and the Haar cascade classifier for face detection process. Finally, we have conducted a benchmark test for our proposed algorithm using image databases of CMU-MIT, MIT training sets, INRIA Graz-01, and FDDB database. Then, we clarify its effectiveness using ROC curves.

关键词： Kalman filters eye face recognition human computer interaction image classification image colour analysis nonlinear filters object detection skin visual databases CMU-MIT database FDDB database Haar cascade classifier INRIA Graz-01 database MIT training sets ROC curves UKF Viola Jones eye detector benchmark test high performance face detector human face detection human-human interaction human-machine interaction image databases skin color detector still image unscented Kalman filter Classification algorithms Databases Detectors Face Face detection Image color analysis Skin visual databases Facial Recognition image colour analysis Benchmark testing Still images Kalman filters ROC Curve Face Nonlinear filters sorting algorithm computer human interaction skin Object detection Image classification Face

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MicroEye: Visual Summary of Microblogsphere from the Eye of Celebrities 23

MicroEye: Visual Summary of Microblogsphere from the Eye of ...

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23rd International Conference on Computer Communication and Networks (ICCCN)

作者： Liu, Qingsong Hu, Yifan Chinese Acad Sci Inst Software State Key Lab Comp Sci Beijing 100864 Peoples R China Yahoo Labs New York New York NY USA

ISBN: (纸本)9781479935727

Micro-blogging is a new kind of online broadcast medium rising in latest years which is called weibo in China. Every day, weibo users are fed with a large number of incurious micro-blogs. They may also pay close attention to what celebrities concerned about, but they would rather roughly know the summary of micro-blogs the celebrities, however, they can't add attentions to all the celebrities' friends. In this work, we provide weibo users with an overview of the relevant micro-blogs and offer them a visual summary of the micro-blogs that appeal to famous people. Our goal is to help users select their most interested micro-blogs from a large number of micro-blogs.

关键词： Blogs Classification algorithms Clustering algorithms Force Layout Twitter Visualization Famous Persons sorting algorithm blogs Clustering algorithms Visualization layouts Force Social Media TWITTER Eye Consumers

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Detecting ECG Limb Lead-wire Interchanges Involving the Right Leg Lead-wire 44

Detecting ECG Limb Lead-wire Interchanges Involving the Righ...

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44th Computing in Cardiology Conference (CinC)

作者： Gregg, Richard E. Hancock, E. William Babaeizadeh, Saeed Philips Healthcare Andover MA USA Stanford Univ Palo Alto CA 94304 USA

ISBN: (纸本)9781538645550;9781538666302

ECG lead-wire interchanges involving the right leg (RL) are not always detected. These RL lead-wire interchanges cannot be simulated in the same way as other lead-wire interchanges making database collection a necessity for algorithm development. Adult 12-lead ECGs from a single teaching hospital taken between January 2008 and July 2012 were reviewed for lead-wire interchanges by an expert electrocardiographer. Lead-wire interchanges were confirmed by comparison of serial ECGs. Positive interchanges included left arm / right leg (flat lead III, n = 134) and right arm / right leg (flat lead II, n = 139). A RL lead-wire interchange algorithm was developed by bootstrap aggregation of decision trees with 5-fold cross validation. Test results were summed over the 5-fold cross validation on the partitions not used for training. ECG features included maximum and minimum QRS and T-wave voltages for ECG leads I, II and III. The Haisty algorithm for RA-RL interchange was tested for comparison. algorithm performance was quantified by sensitivity (SE), specificity (SP) and estimated positive predictive value (PPV) based on SE, SP and realistic prevalence. For a prevalence of 0.2%, performance in SE, SP and PPV was: Haisty, 94, 99.4, 24;tree RA-RL: 84, 99.9, 57;tree LA-RL: 87, 99.9, and 57%. Even though SP was high for all three algorithms, the estimated PPVs were modest due to the low prevalence. Conclusion: Lead-wire interchanges involving the right leg wire can be detected with good sensitivity and high specificity. The higher specificity of the tree based algorithms results in more than twice the PPV of the Haisty algorithm.

关键词： Lead Electrocardiography Wires Legged locomotion Electrodes Signal processing algorithms Classification algorithms Interchange Electrocardiography Signal processing algorithms Biped locomotion sorting algorithm ELECTRIC WIRE Rope Right leg Electrodes Lead electrochemical grinding ecg lead p-phenyl vinyl

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Meta-algorithms for Software-based Packet Classification 22

Meta-algorithms for Software-based Packet Classification

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22nd IEEE International Conference on Network Protocols (ICNP)

作者： He, Peng Xie, Gaogang Salamatian, Kave Mathy, Laurent Chinese Acad Sci ICT Beijing Peoples R China Univ CAS Beijing Peoples R China Univ Savoie Chambery France Univ Liege B-4000 Liege Belgium

ISBN: (纸本)9781479962044

We observe that a same ruleset can induce very different memory requirement, as well as varying classification performance, when using various well known decision tree based packet classification algorithms. Worse, two similar rulesets, in terms of types and number of rules, can give rise to widely differing performance behaviour for a same classification algorithms. We identify the intrinsic characteristics of rulesets that yield such performance differences, allowing us to understand and predict the performance behaviour of a ruleset for various modern packet classification algorithms. Indeed, from our observations, we are able to derive a memory consumption model and an offline algorithm capable of quickly identifying which packet classification is suited to a give ruleset. By splitting a large ruleset in several subsets and using different packet classification algorithms for different subsets, our SmartSplit algorithm is shown to be capable of configuring a multi-component packet classification system that exhibits up to 11 times less memory consumption, as well as up to about 4x faster classification speed, than the state-of-art work [20] for large rulesets. Our AutoPC framework obtains further performance gain by avoiding splitting large rulesets if the memory size of the built decision tree is shown by the memory consumption model to be small.

关键词： algorithm design and analysis Decision trees Estimation IP networks Memory management Prediction algorithms Random access memory packet classification Decision Trees algorithm design and analysis random access machine Prediction algorithms Store management Internet Protocol networks Ruleset performance behavior sorting algorithm Rule

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Feature Selection for Twitter Classification

Feature Selection for Twitter Classification

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8th IEEE International Conference on Semantic Computing

作者： Ostrowski, David Alfred Ford Motor Co Res & Innovat Ctr Syst Analyt Dearborn MI 48121 USA

ISBN: (纸本)9781479940035

Twitter-based messages have presented challenges in the identification of features as applied to classification. This paper explores filtering techniques for improved trend detection and information extraction. Starting with a pre-filtered source (Twitter), we will examine the application of both information theory and Natural Language Processing (NLP) based techniques as a means of preprocessing for classification. Results demonstrate that both means allow for improved results in classification among highly idiosyncratic data (Twitter).

关键词： Classification algorithms Filtering theory Market research Measurement Mutual information Twitter Classification Machine learning Natural Language Processing Natural Language Processing filtering theory TWITTER Social Media sorting algorithm market research Feature extraction Taxonomy Artificial Intelligence Machine Learning

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A Novel Capacitor Voltage Balancing Control Strategy for Modular Multilevel Converters (MMC)

A Novel Capacitor Voltage Balancing Control Strategy for Mod...

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International Conference on Electrical Machines and Systems (ICEMS)

作者： Wang, Lin Wang, Ping Li, Zixin Li, Yaohua Chinese Acad Sci Inst Elect Engn Key Lab Power Elect & Elect Dr Beijing 100190 Peoples R China

Recently modular multilevel converters are highly attractive for medium, high-voltage power transition and electrical machine drive. Capacitor voltage sorting is very important for capacitor voltage-balancing control.... 详细信息

ISBN: (纸本)9781479914463;9781479914470

关键词： modular multilevel converters (MMC) voltage-balancing control sorting algorithm

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