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Optimization Heuristics for computing the Voronoi Skeleton 19th

Optimization Heuristics for Computing the Voronoi Skeleton

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19th Annual international conference on Computational Science (ICCS)

作者： Kotsur, Dmytro Tereshchenko, Vasyl Software Competence Ctr Hagenberg SCCH Softwarepk 21 A-4232 Hagenberg Austria Taras Shevchenko Natl Univ Kyiv Volodymyrska Str 60 UA-01033 Kiev Ukraine

ISBN: (纸本)9783030227340;9783030227333

A skeletal representation of geometrical objects is widely used in computer graphics, computer vision, image processing, and pattern recognition. therefore, efficient algorithms for computing planar skeletons are of high relevance. In this paper, we focus on the algorithm for computing the Voronoi skeleton of a planar object represented by a set of polygons. the complexity of the considered algorithm is O(N log N), where N is the total number of polygon's vertices. In order to improve the performance of the skeletonization algorithm, we proposed theoretically justified shape optimization heuristics, which are based on polygon simplification algorithms. We evaluated the efficiency of such heuristics using polygons extracted from MPEG 7 CE-Shape-1 dataset and measured the execution time of the skeletonization algorithm, computational overheads related to the introduced heuristics and the influence of the heuristic onto the accuracy of the resulting skeleton. As a result, we established the criteria allowing us to choose the optimal heuristics for Voronoi skeleton construction algorithm depending on the critical system's requirements.

关键词： Voronoi diagram Voronoi graph Skeleton Optimization Heuristics

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2nd international conference on Recent Trends in Advanced computing, ICRTAC - DISRUP - TIV INNOVATION 2019

2nd International Conference on Recent Trends in Advanced Co...

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8th international Symposium on Highly-Efficient Accelerators and Reconfigurable Technologies, HEART 2017

the proceedings contain 47 papers. the topics discussed include: damage observation in glass fiber reinforced composites via Î88;-tomography;impact response of sandwich panels with polyurethane and polystyrene...

the proceedings contain 47 papers. the topics discussed include: damage observation in glass fiber reinforced composites via Î¼-tomography;impact response of sandwich panels with polyurethane and polystyrene core and composite facesheets;a method for strain analyses of surfaces with curved boundaries based on measured displacement fields;tow truck frame made of high strength steel under cyclic loading;optical study for springback prediction, thickness reduction and forces variations on single point incremental forming;comparative results of milling strategies implementation;yielding and strain localization effects in gum metal - a unique Ti alloy - investigated by digital image correlation and infrared thermography;and damage monitoring of different concentration carbon nanotube/epoxy glass fiber reinforced composites under quasi-static incremental loadings.

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Test pattern generation using NLFSR for detecting single stuck-at faults 8

Test pattern generation using NLFSR for detecting single stu...

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8th IEEE international conference on Communication and Signal Processing, ICCSP 2019

作者： Varun Teja, N. Prabhu, E. Department of Electronics and Communication Engineering Amrita School of Engineering Coimbatore Amrita Vishwa Vidyapeetham India

ISBN: (纸本)9781538675953

the generation of test patterns for the detection of faults in VLSI circuits is the most integral part of fault detection. the patterns are generated using Pseudorandom Number Generator (PRNG) and applied to the circuits. the most commonly used PRNG is Linear Feedback Shift Register (LFSR). Other than LFSR, Non-Linear Feedback Shift Registers (NLFSR) can also be used as pattern generator. this paper mainly focuses on the advantages of using NLFSRs over ATPG. It compares the fault coverage of single stuck-at faults using NLFSR technique with the fault coverage of single stuck-at faults using ATPG tool for few ISCAS'89 circuits. this paper also shows the reduction in terms of total on-chip power while using NLFSR as pattern generator instead of LFSR. the netlist generation of the circuits is done by using Synopsys Design Compiler tool and ATPG is achieved using Synopsys TetraMax tool. In the NLFSR technique, faults are injected manually and patterns are added to the CUT to get the fault coverage. the faults injected in the circuits are detected in the simulation results of the faulty circuit. the NLFSRs and LFSRs are designed using Xilinx Vivado. the comparison between the fault coverage and power consumption of the techniques are shown in a tabular form and the simulation results for NLFSR technique is shown. It is observed that while the ATPG does not yield 100% fault coverage, NLFSR technique gives 100% coverage. the difference in on-chip power between LFSR and NLFSR is also found to be very large with NLFSR consuming more than 80% less power than LFSR. © 2019 IEEE.

关键词： Feedback

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8th CCF international conference on Natural Language Processing and Chinese computing, NLPCC 2019

8th CCF International Conference on Natural Language Process...

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8th CCF international conference on Natural Language Processing and Chinese computing, NLPCC 2019

ISBN: (纸本)9783030322328

the proceedings contain 65 papers. the special focus in this conference is on Natural Language Processing and Chinese computing. the topics include: Using Bidirectional Transformer-CRF for Spoken Language Understanding;evaluating and Enhancing the Robustness of Retrieval-Based Dialogue Systems with Adversarial Examples;Many vs. Many Query Matching with Hierarchical BERT and Transformer;a Knowledge Selective Adversarial Network for Link Prediction in Knowledge Graph;feature-Level Attention Based Sentence Encoding for Neural Relation Extraction;domain Representation for Knowledge Graph Embedding;evidence Distilling for Fact Extraction and Verification;KG-to-Text Generation with Slot-Attention and Link-Attention;group-Constrained Embedding of Multi-fold Relations in Knowledge Bases;improving Question Answering by Commonsense-Based Pre-training;cosine-Based Embedding for Completing Schematic Knowledge;improved DeepWalk Algorithm Based on Preference Random Walk;learning Stance Classification with Recurrent Neural Capsule Network;learning Unsupervised Word Mapping via Maximum Mean Discrepancy;solving Chinese Character Puzzles Based on Character Strokes;improving Multi-head Attention with Capsule Networks;REET: Joint Relation Extraction and Entity Typing via Multi-task Learning;detecting and Translating Dropped Pronouns in Neural Machine Translation;select the Best Translation from Different Systems Without Reference;word Position Aware Translation Memory for Neural Machine Translation;Multi-strategies Method for Cold-Start Stage Question Matching of rQA Task;cross Aggregation of Multi-head Attention for Neural Machine Translation;target Oriented Data Generation for Quality Estimation of Machine Translation;improved Quality Estimation of Machine Translation with Pre-trained Language Representation;an Analytical Study on a Benchmark Corpus Constructed for Related Work Generation;automated thematic and Emotional Modern Chinese Poetry Composition;charge Prediction with Legal

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A Systematic Literature Review of the Mobile Application for Object recognition for Visually Impaired People

A Systematic Literature Review of the Mobile Application for...

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international conference on Information Technology and Multimedia (ICIM)

作者： Zulfadhlina Amira Nor Hisham Masyura Ahmad Faudzi Azimah Abdul Ghapar Fiza Abdul Rahim College of Computing and Informatics Universiti Tenaga Nasional Malaysia Institute of Informatics and Computing in Energy Universiti Tenaga Nasional Malaysia

ISBN: (数字)9781728173108

ISBN: (纸本)9781728173115

Nowadays, mobile applications or also known as mobile apps are one of the most important sources of communication and gives a lot of benefits to a person. Mobile technology advancements have brought an excessive change in people's daily lifestyles which has led to high demand for developing software that can give benefit to a person that runs on a mobile device. Mobile apps are represented visually on a smartphone, which it is not user-friendly for visually impaired people. the number of visually impaired people are growing in each of the countries in the world. Most technologies are being developed to help people with visual impairment because they still have difficulties in using assistive technologies. this systematic literature review attempts to provide findings on the project for visually impaired people to recognize objects using their smartphones. Systematic Literature Review (SLR) method was used to collect and review the current state of analysis concerning object recognition for visually impaired people on mobile platforms. Overall, this research covered articles published in three databases which are ScienceDirect, IEEE Xplore and Google Scholar and the articles selected are between 2013 until 2019. this paper is based on the Kitchenham methodology where the keyword search and exclusion criteria to select the articles about the topic were used. After reading the total of 371 titles of articles based on keywords, 323 abstracts were examined thoroughly. then, 21 full-text articles were chosen for the final review. the findings show the techniques, tools used and methods on how the system was implemented to recognize object.

关键词： Visualization Systematics Bibliographies Tools Mobile applications Object recognition Testing

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Texture Image Retrieval Using Multiple Filters and Decoded Sparse Local Binary pattern 8th

Texture Image Retrieval Using Multiple Filters and Decoded S...

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8th international conference on pattern recognition and Machine Intelligence (PReMI)

作者： Hatibaruah, Rakcinpha Nath, Vijay Kumar Hazarika, Deepika Tezpur Univ Dept Elect & Commun Engn Tezpur Assam India

ISBN: (纸本)9783030348694;9783030348687

In local pattern based feature extraction, usually the raw spatial image provides limited information about the relationship between the pixels in a local neighborhood. A few recent methods address this issue by first filtering the images with bag of filters and then calculating local pattern over each filtered images. It is observed that the filtered images complement the discriminativeness of local pattern based features which enhances retrieval efficiency. Motivated by these approaches, a new approach based on multiple filters and decoded sparse local binary pattern (MF-DLBP) is proposed in this paper, wherein we first filter the raw spatial image with multiple filters to extract the low frequency and high frequency information. However, unlike previous approaches, we extract features from low pass and high pass filtered images adopting separate strategies, since characteristically they contain contrasting information. From each gradient filtered images, we compute sparse LBPs using LBP4hv (considering only horizontal and vertical neighbors) and LBP4d (considering only diagonal neighbors) techniques. To enhance the discriminativeness of the descriptor, two decoders are also used which compute the inter frequency relationship between the sparse local binary pattern maps of high pass filtered images only. the low pass filtered image is encoded with sign LBP (LBP S) and magnitude LBP (LBP M) to extract sign as well as magnitude information present in this image. the proposed approach is low dimensional and it shows highly competitive retrieval performance when tested on three benchmark texture databases which are Kylberg, Brodatz and STex.

关键词： Local binary pattern Decoder Feature vector Image retrieval CBIR

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proceedings of the 8th international Advance computing conference, IACC 2018

Proceedings of the 8th International Advance Computing Confe...

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8th international Advance computing conference, IACC 2018

ISBN: (纸本)9781538666784

the proceedings contain 60 papers. the topics discussed include: 3D-printed sole with variable density using foot plantar pressure measurements;HUPM: efficient high utility pattern mining algorithm for e-business;Pubworld -A R2rml mapping driven approach to transform relational database data into shareable format;a pattern and polarization reconfigurable antenna for WLAN application;an efficient method for text encryption using elliptic curve cryptography;a machine learning approach to georeferencing;a new paradigm for generation of fuzzy membership function;on the combined use of electromyogram and accelerometer in lower limb motion recognition;comparative analysis of clustering algorithm for facial recognition system;and a new term weight measure for gender and age prediction of the authors by analyzing their written texts.

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Integrating Activity recognition and Nursing Care Records: the System, Experiment, and the Dataset

Integrating Activity Recognition and Nursing Care Records: t...

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international conference on Informatics, Electronics & Vision (ICIEV)

作者： Sozo Inoue Tittaya Mairittha Nattaya Mairittha Tahera Hossain Kyushu Institute of Technology Kitakyushu JAPAN

In this paper, we introduce a system that integrates activity recognition, which collects various activities of the elderly people of a nursing care facility in Japan. this system incorporates various activity levels, sensor data through smartphones, and records by nurses for a period of 4 months. there are 28 activity labels, recorded by a number of staffs/nurses. the system architecture has mobile application to encode data and a networked system in the 6-floored facility, covering a number of residents. the system is designed in such a manner that even a non-expert nurse or user can manage this system. After introducing the entire system and data collection procedure, we recognized the acitivities by exploiting some statistical features and Extremely Randomized Tree. We noticed that there are discrepancies between start and end recording time-stamps. therefore, we explored a time correction technique. the dataset is an extensive one and it can be explored for various activity recognition in smart-homes or elder care facilities. the dataset includes the sensor data from staffs' smartphones, activity labels, and care details input using the system.

关键词： Smart phones Medical services Activity recognition Cloud computing Servers Machine learning Metadata

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A New Algorithm for Designing Θ-Fuzzy Associative Memories Based on Subsethood Measures

A New Algorithm for Designing Θ-Fuzzy Associative Memories ...

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IEEE international conference on Fuzzy Systems (FUZZ-IEEE)

作者： Sussner, Peter Esmi, Estevao Florindo, Joao Univ Estadual Campinas Dept Appl Math IMECC Campinas SP Brazil

ISBN: (纸本)9781538617281

A (weighted) theta-fuzzy associative memory can be viewed as single hidden layer neural network whose inputs are drawn from an arbitrary bounded lattice L. the xi th hidden node applies a function theta(xi) : L -> [0;1] to an input A is an element of L. In this paper, we present a new algorithm for designing theta-FAMs. Roughly speaking, this algorithm consists of the following two stages: 1) Construction of a set of functions theta(xi) : L -> [0;1] where xi = 1, ...,, p;2) Optimization of the weights. Our new algorithm differs from the previous algorithm for tunable equivalence fuzzy associative memories. Instead of merely extracting a subset of functions theta(xi) : L -> [0;1] from a given set, we generate a new set of functions on the basis of the partial ordering of L. the paper includes some experimental results in a set of benchmark classification problems. We also apply a combination of the resulting theta-FAM and a deep convolutional neural network to a problem of image texture classification and compare the classification performance of our approach with the ones of some state-of-the-art methods from the literature.

关键词： lattice computing subsethood measure theta-fuzzy associative memory fundamental memory set classification texture recognition

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Artificial intelligence based network intrusion detection with hyper-parameter optimization tuning on the realistic cyber dataset CSE-CIC-IDS2018 using cloud computing 8

Artificial intelligence based network intrusion detection wi...

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8th IEEE international conference on Communication and Signal Processing, ICCSP 2019

作者： Kanimozhi, V. Prem Jacob, T. Department of Computer Science Sathyabama Institute of Science and Technology Chennai India

ISBN: (纸本)9781538675953

One of the latest emerging technologies is artificial intelligence, which makes the machine mimic human behavior. the most important component used to detect cyber attacks or malicious activities is the Intrusion Detection System (IDS). Artificial intelligence plays a vital role in detecting intrusions and widely considered as the better way in adapting and building IDS. In trendy days, artificial intelligence algorithms are rising as a brand new computing technique which will be applied to actual time issues. In modern days, neural network algorithms are emerging as a new artificial intelligence technique that can be applied to real-time problems. the proposed system is to detect a classification of botnet attack which poses a serious threat to financial sectors and banking services. the proposed system is created by applying artificial intelligence on a realistic cyber defense dataset (CSE-CIC-IDS2018), the very latest Intrusion Detection Dataset created in 2018 by Canadian Institute for Cybersecurity (CIC) on AWS (Amazon Web Services). the proposed system of Artificial Neural Networks provides an outstanding performance of Accuracy score is 99.97% and an average area under ROC (Receiver Operator Characteristic) curve is 0.999 and an average False Positive rate is a mere value of 0.001. the proposed system using artificial intelligence of botnet attack detection is powerful, more accurate and precise. the novel proposed system can be implemented in n machines to conventional network traffic analysis, cyber-physical system traffic data and also to the real-time network traffic analysis. © 2019 IEEE.

关键词： Botnet

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