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Audio Recorder Forensic Identification in 21 Audio Recorders 3

Audio Recorder Forensic Identification in 21 Audio Recorders

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3rd IEEE international conference on Progress in Informatcs and Computing (IEEE PIC)

作者： Zeng, Jinhua Shi, Shaopei Yang, Xu Li, Yan Lu, Qimeng Qiu, Xiulian Zhu, Huaping Minist Justice Inst Forens Sci Shanghai 200063 Peoples R China Tongji Univ Coll Civil Engn Shanghai Peoples R China

ISBN: (纸本)9781467390880

Audio recorder forensic identification is to determine originating devices of questioned audio recordings. In this paper, statistical features both in time and frequency domains were studied and were used to represent and encode device-related information. Statistical techniques in fields of machine learning and pattern recognition were utilized to classify computed features into each originating audio recorder. More specifically, features of sampling histogram and spectral mean were extracted from near-silence segments of digital recordings which were recorded by using 21 audio recorders. A support vector machine classifier was used to learn device-related feature patterns upon one half of the complete set of audio samples, and then was evaluated by using the rest of data. The experimental results show a high accuracy of up to 96.72% in the correct classification of the 21 audio recorders. Our paper was the first study which was to study and evaluate the performances of different features for device-related information encoding in a relatively big audio recorder database. The proposed method would offer a practical guide for forensic identification of audio recorders.

关键词： Audio recorder forensic identification pattern classification Sampling histogram Spectral mean Statistical feature

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Development of a Kinect-Based Physical Rehabilitation System 3

Development of a Kinect-Based Physical Rehabilitation System

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3rd international conference on Image Information Processing (ICIIP)

作者： Uttarwar, Param Mishra, Deepak Space Applicat Ctr Ahmadabad Gujarat India Indian Inst Space Sci & Technol Dept Avion Thiruvanvanthpuram India

ISBN: (纸本)9781509001484

Shoulder injuries are very common in sports and certain labour intensive occupations. While some injuries are minor and full recovery is within 1-2 weeks, some major injuries requires the person to consult a physiotherapist and follow an exercise plan for months for full recovery. With the advent of consumer accessible motion capture (MoCap) technologies, the task of conducting daily rehabilitation routine and evaluation which was previously done by a trained physiotherapist can be now done with computers which can be set up in home. In this paper, we propose a system for medical rehabilitation of patients suffering from shoulder injuries. We use Hidden Markov Models (HMM) for recognition and a histogram-based comparison for computing the accuracy score. The Microsoft Kinect sensor is used to obtain 3D coordinates of human joints. Important features are extracted from the skeletal coordinates which are then quantized into 16 intermediate upper-body poses. Thetemporalpatterns of these upper-body poses are modelled by training an HMM for each exercise. Our system recognizes different exercises performed by the patient and assigns an accuracy score for each exercise carried out in a session. It intends to help the patient by keeping track of daily exercise routine, advising for improvements and maintaining records for doctor to access.

关键词： pattern recognition Rehabilitation Human information processing Real-time systems

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3rd IFIP TC 5/8 international conference on Information and Communication Technology, ICT-EurAsia 2015 and 9th IFIP WG 8.9 Working conference on Research and Practical Issues of Enterprise Information Systems, CONFENIS 2015 held in conjunction with 23rd IFIP World Computer Congress, WCC 2015

3rd IFIP TC 5/8 International Conference on Information and ...

引用

3rd IFIP TC 5/8 international conference on Information and Communication Technology, ICT-EurAsia 2015 and 9th IFIP WG 8.9 Working conference on Research and Practical Issues of Enterprise Information Systems, CONFENIS 2015

ISBN: (纸本)9783319243146

The proceedings contain 46 papers. The special focus in this conference is on System Architecture, Teaching, Education, Authentication and Profiling. The topics include: Reducing keep alive traffic in software-defined mobile networks with port control protocol;a SDN based method of TCP connection handover;SYN flood attack detection and type distinguishing mechanism based on counting bloom filter;integrating mobile openflow based network architecture with legacy infrastructure;analyzing brain waves for activity recognition of learners;a multi-factor biometric based remote authentication using fuzzy commitment and non-invertible transformation;profiler for Smartphone users interests using modified hierarchical agglomerative clustering algorithm based on browsing history;strength of relationship between multi-labeled data and labels;online ad-fraud in search engine advertising campaigns;fitness function in ABC algorithm for uncapacitated facility location problem;comparative study of Monte-Carlo tree search and alpha-beta pruning in amazons;key agreement with modified batch rekeying for distributed group in cognitive radio networks;secure mobility management for mipv6 with identity-based cryptography;secure database using order-preserving encryption scheme based on arithmetic coding and noise function;an approach for evaluating softgoals using weight;identification of corrupted cloud storage in batch auditing for multi-cloud environments and a lossless data hiding strategy based on two-dimensional side-match predictions.

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Handwritten text recognition results on the Bentham collection with improved classical N-Gram-HMM methods 15

Handwritten text recognition results on the Bentham collecti...

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3rd international Workshop on Historical Document Imaging and Processing, HIP 2015

作者： Toselli, Alejandro H. Vidal, Enrique Pattern Recognition and Human Language Technology Research Center Universitat Politècnica de València Spain

ISBN: (纸本)9781450336024

Handwritten Text recognition experiments and results are presented on the historical Bentham text image dataset used in the ICFHR-2014 HTRtS competition. The successful segmentation-free holistic framework is adopted, using traditional modelling approaches based on Hidden Markov optical character models (HMM) and an N-gram language model (LM). Departing from the very basic N-gram-HMM baseline system provided in HTRtS, several improvements are made in text image feature extraction and LM and HMM modeling, including more accurate HMM training by means of discriminative training. As a result, we achieve similar recognition accuracy as some of the best performing (single, uncombined) systems based on (recurrent) Neural Networks (NN), using identical training and testing data. The traditional N-gram/HMM framework offers several advantages over modern approaches based on (hybrid, recurrent) NNs. Perhaps the most important is the much faster training of HMMs and the well understood stability of the results of Baum-Welch training. These advantages become very important when dealing with many historical document collections, which are typically huge and entail very high degrees of variability, making it generally diffcult to re-use models trained on previous collections. © 2015 ACM.

关键词： Recurrent neural networks

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Representing Parametric Concepts with Situation Theory

Representing Parametric Concepts with Situation Theory

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3rd international conference on Innovative Network Systems and Applications (iNetSApp) held in conjunction with Federated conference on Computer Science and Information Systems (FedCSIS)

作者： Loukanova, Roussanka Stockholm Univ Dept Math Stockholm Sweden

ISBN: (纸本)9788360810668

We use higher-order, type-theoretic Situation Theory to model semantic concepts as situation-theoretic objects consisting of parametric information. Situation Theory contributes by representing concepts as classes of parametric objects, in a computational way. We use concepts that are often expressed by human language in taxonomy classifications, as a demonstration of the situation theoretic-approach to model parametric information in abstract concepts.

关键词： pattern classification set theory higher-order type-theoretic situation theory human language parametric concept representation parametric information parametric information model parametric objects semantic concept model situation-theoretic objects taxonomy classifications Computational modeling Context modeling Formal languages Mathematical model Semantics Set theory Syntactics Set Theory Context modeling Formal languages Semantics pattern recognition Computational modeling human language(hl) Mathematical Model Parametric semiotics

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A Novel Region Labeling Method for Blood Cell Images 3

A Novel Region Labeling Method for Blood Cell Images

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3rd IEEE international conference on Progress in Informatcs and Computing (IEEE PIC)

作者： Wu, Xueyan Lu, Zhihai Lu, Siyuan Ji, Genlin Phillips, Preetha Yan, Jie Yang, Jiquan Nanjing Normal Univ Sch Educ Sci & Comp Sci Nanjing 210023 Jiangsu Peoples R China Shepherd Univ Sch Nat Sci & Math Shepherdstown WV 25443 USA Stanford Univ Dept Appl Phys Stanford CA 94305 USA Jiangsu Key Lab 3D Printing Equipment & Mfg Nanjing 210042 Jiangsu Peoples R China

ISBN: (纸本)9781467390880

Blood cell images are difficult for segmentation because of their intrinsic characteristics. We proposed a dual-layer structure to solve the problem: the 1st layer introduces and simplifies pulse coupled neural network to split the images based on traditional Split-Merge method, and Mumford-Shah model was utilized to merge the split areas. The output of the first layer is a coarse segmented image. The second layer extracts the edges via LoG operator with considering the edges whose length are larger than given threshold as cell edge while the opposite as false-edges caused by noises. The output is a non-continuous edge. To obtain the final labeling results, we combined the two layers together with skeleton extraction and thinning from mathematical morphology. Experiments suggested the superiority of proposed method.

关键词： image segmentation pattern recognition computer vision pulse-coupled neural network Laplacian of the Gaussian

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Mapping Evaluation for Semantic Browsing

Mapping Evaluation for Semantic Browsing

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3rd international conference on Innovative Network Systems and Applications (iNetSApp) held in conjunction with Federated conference on Computer Science and Information Systems (FedCSIS)

作者： Osinska, Veslava Jozwik, Adam Osinski, Grzegorz Nicolaus Copernicus Univ Inst Informat Sci & Book Studies Ul Bojarskiego 1 PL-87100 Torun Poland Polish Acad Sci Inst Biocybernet & Biomed Engn Warsaw Poland Coll Social & Media Culture Inst Comp Sci PL-87100 Torun Poland

ISBN: (纸本)9788360810668

The paper contributes to the problem solving in semantic browsing and analysis of scientific articles. With reference to presented visual interface, four - the most popular methods of mapping including own approach - MDS with spherical topology, have been compared. For a comparison quantitative measures were applied which allowed to select the most appropriate mapping way with an accurate reflection of the dynamics of data. For the quantitative analysis the authors used machine learning and pattern recognition algorithms and described: clusterization degree, fractal dimension and lacunarity. Local density differences, clusterization, homogeneity, and gappiness were measured to show the most acceptable layout for an analysis, perception and exploration processes. Visual interface for analysis how computer science evolved through the two last decades is presented on website. Results of both quantitative and qualitative analysis have revealed good convergence.

关键词： Web sites learning (artificial intelligence) problem solving MDS Website local density differences machine learning pattern recognition algorithms semantic browsing visual interface Computer science Data visualization Fractals Layout Semantics Training Visualization

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A Direct Method for Determining the Lower Convex Hull of a Finite Point Set in 3D 1

引用

3rd international conference on Computer Science, Applied Mathematics and Applications (ICCSAMA)

作者： Thanh An Phan Thanh Giang Dinh Vietnam Acad Sci & Technol Inst Math Hanoi Vietnam Univ Lisbon Inst Super Tecn CEMAT Lisbon Portugal Vinh Univ Dept Math Vinh City Vietnam

ISBN: (数字)9783319179964

ISBN: (纸本)9783319179964;9783319179957

Determining the convex hull, its lower convex hull, and Voronoi diagram of a point set is a basic operation for many applications of pattern recognition, image processing, and data mining. To date, the lower convex hull of a finite point set is determined from the entire convex hull of the set. There arises a question "How can we determine the lower convex hull of a finite point set without relying on the entire convex hull?" In this paper, we show that the lower convex hull is wrapped by lower facets starting from an extreme edge of the lower convex hull. Then a direct method for determining the lower convex hull of a finite point set in 3D without the entire convex hull is presented. The actual running times on the set of random points (in the uniform distribution) show that our corresponding algorithm runs significantly faster than the incremental convex hull algorithm and some versions of the gift-wrapping algorithm.

关键词： Convex Hull Extreme Edge Gift-wrapping Algorithm Lower Convex Hull pattern recognition Voronoi Diagram

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3rd international Symposium on Statistical Learning and Data Sciences, SLDS 2015

3rd International Symposium on Statistical Learning and Data...

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3rd international Symposium on Statistical Learning and Data Sciences, SLDS 2015

ISBN: (纸本)9783319170909

The proceedings contain 43 papers. The special focus in this conference is on Statistical Learning and Data Sciences. The topics include: Similarity control and knowledge transfer;statistical inference problems and their rigorous solutions;feature mapping through maximization of the atomic interclassc distances;adaptive design of experiments for sobol indices estimation based on quadratic metamodel;a closer look into the black box;gaussian process regression for structured data sets;adaptive design of experiments based on gaussian processes;forests of randomized shapelet trees;aggregation of adaptive forecasting algorithms under asymmetric loss function;visualization and analysis of multiple time series by beanplot PCA;recursive SVM based on TEDA;an approximate solution for large values of k with an application to fault detection problems;sit-to-stand movement recognition using kinect;additive regularization of topic models for topic selection and sparse factorization;exploring the link between gene expression and protein binding by integrating mRNA microarray and chip-seq data;evolving smart URL filter in a zone-based policy firewall for detecting algorithmically generated malicious domains;lattice-theoretic approach to version spaces in qualitative decision making;a comparison of three implementations of multi-label conformal prediction;modifications to p-values of conformal predictors;cross-conformal prediction with ridge regression;handling small calibration sets in mondrian inductive conformal regressors;conformal anomaly detection of trajectories with a multi-class hierarchy;model selection using efficiency of conformal predictors;confidence sets for classification and conformal clustering and its application to botnet traffic.

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Design and Evaluation of a Multi-model, Multi-level Artificial Neural Network for Eczema Skin Lesion Detection 3

Design and Evaluation of a Multi-model, Multi-level Artifici...

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3rd international conference on Artificial Intelligence, Modelling and Simulation (AIMS)

作者： De Guzman, Launcelot C. Maglaque, Ryan Paolo C. Torres, Vianca May B. Zapido, Simon Philippe A. Cordel, Macario O., II De La Salle Univ Ctr Automat Res Coll Comp Studies Manila Philippines

ISBN: (纸本)9781467386753

There are several current systems developed to identify common skin lesions such as eczema that utilize image processing and most of these apply feature extraction techniques and machine learning algorithms. These systems extract the features from pre-processed images and use them for identifying the skin lesions through machine learning as the core. This paper presents the design and evaluation of a system that implements a multi-model, multi-level system using the Artificial Neural Network (ANN) architecture for eczema detection. In this work, multi-model system is defined as architecture with different models depending on the input characteristic. The outputs of these models are integrated by a decision layer, thus multi-level, which computes the probability of an eczema case. The resulting system has 68.37% average confidence level as opposed to the 63.01% of the single level, i.e. single model, system in the actual testing of eczema versus non-eczema cases. Furthermore, the multi-model, multi-level design produces more stable models in the training phase wherein overfitting was reduced.

关键词： Computer-assisted diagnosis pattern recognition skin lesion detection Artificial Neural Network multi-model multi-level systems

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