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Heart Arrhythmia Detection with Novel Approach H3-SAD 8

Heart Arrhythmia Detection with Novel Approach H3-SAD

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8th international conference on Control, Decision and Information Technologies (CoDIT)

作者： Cakal, Kursat Efe, Mehmet Onder Hacettepe Univ Comp Engn Dept TR-06800 Ankara Turkey

ISBN: (纸本)9781665496070

Research on signals collected from the human heart has been a core subject area as the heart displays a rich set of dynamical information that needs careful analysis for medical diagnosis and treatment. the acquisition of the electrical activity signals is a convenient way to analyze, control, evaluate and understand the heart. Electrocardiography (ECG) measurements are used to categorize the heartbeat behaviors to achieve classification. ECG heartbeat signal classification methods range from classical signal processing to convolutional neural networks. Heterogeneous Harmonization of Heartbeat Signals for Arrhythmia Detection (H3-SAD) method based CNN is proposed in this study. H3-SAD method differs from other methods in the literature with its robust and tempered classification ability against heterogeneous spectrums of ECG Signal by targeting being a part of high mobility lifestyle. Literature studies have reasonable estimation rates for MIT-BIH Dataset but not for the heterogeneous acquisition of data in real-life applications. the key point that tempers our classification algorithm is applied dynamic augmentation details towards different signal sources and input values that adduct data to real-life, and heterogeneous augmentation-based CNN architecture.

关键词： Heart Heart beat Heuristic algorithms Pattern classification Electrocardiography Signal processing Classification algorithms

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An Illicit Bitcoin Address Analysis Scheme Based on Subgraph Evolution 24

An Illicit Bitcoin Address Analysis Scheme Based on Subgraph...

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24th IEEE international conference on High Performance Computing and Communications, 8th IEEE international conference on Data Science and Systems, 20th IEEE international conference on Smart City and 8th IEEE international conference on Dependability in Sensor, Cloud and Big Data Systems and Application, HPCC/DSS/SmartCity/DependSys 2022

作者： Yang, Qingqing Xiang, Yuexin Liu, Wenmao Ren, Wei School of Computer Science China University of Geosciences Wuhan430074 China China University of Geosciences Hubei Key Laboratory of Intelligent Geo-Information Processing Wuhan430078 China Nsfocus Technologies Group Co. Ltd. Beijing China

ISBN: (纸本)9798350319934

Bitcoin, due to its decentralization and anonymity, is more frequently utilized in cybercrimes such as money laundering, darknet market, and blackmail. In order to maintain the development of cryptocurrency communities, it is vital to fight against these cryptocurrency-related (e.g., Bitcoin) cybercrimes. To better monitor cryptocurrency-based cybercrime, it is essential for a deeper understanding of the patterns that exist in Bitcoin transactions. In this paper, we propose a novel framework consisting of empirical analysis and machine learning-based analysis for studying three typical categories of Bitcoin addresses from a dynamic perspective of subgraph evolution. Specifically, we collect 22,001 continuous blocks to build a Bitcoin transaction graph and extract subgraphs from the constructed graph for each address in different periods. In the empirical analysis, we have several important findings from three perspectives. While in the machine learning-based analysis, we propose a 110-dimensional feature set for classification tasks among these three types of Bitcoin addresses, where decision tree, k-nearest neighbor algorithm, and random forest are applied. the experimental results illustrate that metrics of all classifiers can achieve 0.88, and the highest accuracy rate reaches 0.95 in the random forest classifier. In addition, we explore the feature importance in the random forest using the SHAP library and discuss several interesting phenomena that appear in the evolution process of the subgraphs. © 2022 IEEE.

关键词： Bitcoin

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Sparse Matrix Ordering for Fine Grain parallel Triangular Solve Using SIMD 15th

Sparse Matrix Ordering for Fine Grain Parallel Triangular S...

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15th international conference on parallel processing and applied mathematics, PPAM 2024

作者： Maarouf, Aboul-Karim Mohamed El Giraud, Luc Guermouche, Abdou Guignon, thomas IFP Energies nouvelles Solaize France Inria Centre of Bordeaux University Talence France LaBRI Université de Bordeaux Bordeaux France

ISBN: (纸本)9783031856969

the evolution of processor hardware increasingly supports fine grain parallelism through SIMD (Single Instruction, Multiple Data) vector instruction sets and hardware threading. For instance, the new ARM SVE instruction set allows for hardware implementation of up to 32 double precision SIMD vector sizes per hardware thread. In this work, we focus on vectorization of the triangular solves required in BiCGStab preconditioned with ILU(0) that is particularly numerically effective for IFPEN applications. In our context, expressing some parallelism can be achieved by changing the sparse structure of the matrices through unknown ordering;that can be recast in terms of graph ordering and coloring. We use a graph coloring method named ColorRCM to exhibit fine grain parallelism to feed the SIMD computing units while improving the convergence of the Krylov solver compared to classical greedy graph coloring method. We first evaluate the performance of SIMD-SpTRSV using the permutation provided by ColorRCM and achieve an acceleration between 1.7 and 6 in AVX2 compared to Intel MKL 21.4. then we examine the impact of ColorRCM ordering on ILU(0)-BiCGStab performance on 201 matrices, including those from the Suite Sparse matrix (the University of Florida Sparse Matrix Collection: https://***/10.1145/2049662.2049663) collection and from the IFPEN porous media flow simulations. the solver configuration uses the ColorRCM ordering and vectorized with AVX2 instructions showed the best convergence times in two thirds of the tests. © the Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： Matrix algebra

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A Real-time Image Capture and processing System for a Wide-area Aerial Camera

A Real-time Image Capture and Processing System for a Wide-a...

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6th international conference on Intelligent Computing and Signal processing (ICSP)

作者： Hongmin Wang Qian Zhang Yun Xu Changhai Liu Baohua Wang Ziwei Zhou Gaojin Wen Beijing Institute of Space Mechanics and Electricity Beijing P.R. China Laboratory of Computational Physics Institute of Applied Physics and Computational Mathematics Beijing P.R. China Troop of 63768 Xian P.R. China

this paper introduces a real-time image capture and processing system for a wide-area aerial camera. the system adopts a very efficient software system architecture, which includes center control, camera control, capture control, platform control, image data processing and other components. Image data processing methods such as geo-location based on feature point matching, field stitching based on camera geometric installation relationship, moving target extraction based on sequence image phase correlation matching and frame difference are proposed to enable the camera system to effectively monitor specific areas. the efficiency and usefulness of the system are verified by multiple image processing tasks.

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Stock Recommendations Using Machine Learning and Natural Language processing 8th

Stock Recommendations Using Machine Learning and Natural La...

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8th international conference on Information and Communication Technology for Competitive Strategies, ICTCS 2023

作者： Sinha, Akruti Anup, Mahin Sinwar, Deepak Kumar, Ashish North Carolina State University RaleighNC United States Pvt. Ltd. Telangana Hyderabad India Department of Computer and Communication Engineering Manipal University Jaipur Jaipur India Department of Mathematics and Statistics Manipal University Jaipur Jaipur India

ISBN: (纸本)9789819702091

Due to the increasing number of investors in the past decade, the financial markets are now accountable for any country’s economic stability. Stock markets have grown increasingly unpredictable in recent years, yet they continue to be the most crucial for both investors and industries. there are several stock trading advice systems on the market that claim to be able to accurately predict future trends. Recommendation systems for stock trading are of great significance to a layperson who wants to benefit from stock trading despite not having a seasoned trader’s capacity or experience. the present study proposed a three-fold function. First, it provides a comparative analysis of the existing recommendation systems. It then applies and compares the results of the four Machine Learning models for price prediction on a real dataset. Finally, six sentiment analysis models are compared for the analysis of stock-based tweets. the best of the two are lastly integrated to arrive at a stock buy or sell recommendation. © the Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.

关键词： Sentiment analysis

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Performance Analysis of Floyd-Warshall Algorithm: Sequential and parallel Execution Using Intel oneAPI

Performance Analysis of Floyd-Warshall Algorithm: Sequential...

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international conference of Electronics, Communication and Aerospace Technology (ICECA)

作者： Sanjay Kumar S Karthik S Srilakshmi P Dharun Viginesh Department of ECE SRM Institute of Science and Technology Vadapalani Chennai India

ISBN: (数字)9798350367904

ISBN: (纸本)9798350367911

the Floyd-Warshall algorithm is a widely utilized graph-based technique designed to address the all-pairs shortest path problem. However, its cubic time complexity $O\left(n^parallel\right)$ creates performance bottlenecks when applied to large graphs, especially in sequential execution. this paper explores the use of Intel oneAPI’s Data parallel C++ (DPC++) programming model to optimize the performance of the Floyd-Warshall algorithm through parallel processing. A comparative performance analysis between sequential and parallel implementations on an Intel Xeon(R) CPU highlights up to a $43 \%$ improvement in execution time for graphs with 800 nodes. the results underscore the potential of parallel computing in significantly reducing computational time for large-scale graph algorithms.

关键词： Shortest path problem Electric potential Memory management parallel processing Robustness Energy efficiency Performance analysis Time complexity Optimization Field programmable gate arrays

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Design and Implementation of Real-time Signal processing Heterogeneous System for Unmanned Platform

Design and Implementation of Real-time Signal Processing Het...

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6th international conference on Intelligent Computing and Signal processing (ICSP)

作者： Xinyu Liu Cheng Jiang Song Yang Bibo Zhu Zhichao Zhao Hangzhou Applied Acoustics Research Institute Hangzhou China

With the development of platform technology and sensor technology, unmanned platforms are widely used in underwater operations, and the functional requirements are gradually increasing with the application scenarios, which also put forward higher requirements for computing performance. In this paper, a real-time signal processing heterogeneous cooperative system based on DSP and FPGA is designed. DSP is used as the main processor to schedule multiple subordinate FPGA processors to complete heterogeneous multitask high-speed signal processing tasks. In order to verify the feasibility, this paper implements the real-time signal processing application of underwater unmanned platform imaging algorithm based on this architecture. the experiment shows that the DSP-FPGA heterogeneous collaborative processing framework can effectively implement the imaging algorithm, complete the online real-time signal processing and output, meet the requirements of low delay, high-speed parallel real-time signal processing of the unmanned platform, and verify the reliability of the system in the actual lake test.

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Improving the efficiency of sparse matrix class processing by using the SPM-CSR parallel algorithm and OpenMP technology 4

Improving the efficiency of sparse matrix class processing b...

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4th international Youth conference on Radio Electronics, Electrical and Power Engineering, REEPE 2022

作者： Al-Saeedi, Adnan Adhab K. Yurievna, Shamaeva Olga Khairi, Teaba W. National Research University 'MPEI' Department of Applied Mathematics and Artificial Intelligence Moscow Russia Al-Furat AL-Awast Technical University Babylon Technical Institute Kufa Iraq University of Technology-Iraq Computer Science Dept Iraq

ISBN: (纸本)9781665414340

the development of computationally efficient algorithms and the improvement of their software implementation are urgent issues that require continuous attention due to the ongoing development of computer system architecture. In multithreading systems bad coordination cause a big problems and give unwilling results. the purpose of the work is to improve performance of the parallel algorithm for sparse matrix multiplication in CSR format by using vector (SpMV-CSR) using OpenMP technology. Using OpenMP technology and reduction directive to solve sparse matrix time execution and bad coordination problem leads to execution time reduction and speed-up increase. Results obtained an acceleration increase of 14% when using reduction. © 2022 IEEE.

关键词： parallel algorithms

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A Transformer-based Method for Skin Fungi Identification from Fluorescent Images 23

A Transformer-based Method for Skin Fungi Identification fro...

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2023 8th international conference on Biomedical Signal and Image processing, ICBIP 2023

作者： Yuan, Yutong Dai, Sizhe Wang, Ziyi Zhu, Min Shanghai Key Laboratory of Multidimensional Information Processing East China Normal University Shanghai200241 China Department of Dermatology Huashan Hospital Fudan University Shanghai2000240 China

ISBN: (纸本)9798400707698

Due to the increasing number of patients with impaired immune function and the widespread use of broad-spectrum antibiotics, the rate of fungal infections is rising and invasive fungal infections (IFD) have become one of the major causes of death. therefore, early diagnosis and treatment of IFD is the focus of medical attention. In order to automatically identify and diagnose the fungal species of infected patients, we propose a fluorescent identification method of skin fungi with a compact model and high identification accuracy. the method uses fluorescence staining to label fungi, and data enhancement processing is applied to the collected sample images to compensate for the shortcomings of less clinical data of some fungal samples. Convolutional Tokenizer and Positional Embedding are applied to provide sample image labeling in the recognition process, and Transformer is used to solve the problem of too many layers of traditional Convolutional Neural Networks and expand the image perceptual field;In the Sequence Pooling module, the attention mechanism is used to pool all the tokens. Finally, it is transformed into the final category output through a Fully Connected layer. the experimental results show that the method takes less training time, has a compact model and a smaller number of parameters, while still maintaining a high recognition accuracy, which is of great practical value in clinical diagnosis. © 2023 ACM.

关键词： Fungi

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Using parallel Plate Electrode Engineering Techniques for Nondestructive Testing of Timber 8th

Using Parallel Plate Electrode Engineering Techniques for No...

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8th international conference on Material Engineering and Nanotechnology, ICMEN 2024

作者： Albtoush, Faten Ismail, Rabah Alsadi, Jamal Al-Canaan, Amer Trrad, Issam Matalkah, Faris Al-Mattarneh, Hashem Malkawi, Ahmad B. Civil Engineering Department Jadara University Irbid21110 Jordan Renewable Energy Engineering Department Jadara University Irbid21110 Jordan Computer and Communication Engineering Department Jadara University Irbid21110 Jordan Civil Engineering Department Yarmouk University Irbid21163 Jordan Civil Engineering Department Al-Balqa Applied University Amman11942 Jordan

ISBN: (纸本)9789819636235

Timber and wood are natural materials with a wide range of physical and mechanical properties, making them challenging to measure. Some methods for evaluating these properties are destructive and time-consuming, while others, though nondestructive, have proven inaccurate results or complexity. this creates a critical need for the development and application of nondestructive testing and evaluation (NDTE) techniques for timber and wood-based materials. this research spans the entire process, from manufacturing to in-service assessment, with a focus on NDTE techniques that could generate data to improve the design and performance of wood in structures, reducing costs and risks for the end-user. the study explored the feasibility of using a simple and portable parallel plate electrode system (PPES) for the nondestructive testing of timber. the findings include the electromagnetic characterization of Malaysian timbers, suggesting a new method for strength grading. the results demonstrate that PPES can accurately estimate the physical and mechanical properties of timber, showing promise for defect detection in timber members. this could potentially improve the current Malaysian timber grading system. © the Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Nondestructive examination

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