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An Accelerated Coordinate Descent Method for Support Vector Machine

An Accelerated Coordinate Descent Method for Support Vector ...

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international conference of Signal processing and Intelligent Systems (ICSPIS)

作者： Ahmad Kamandi Mohammad M. AlyanNezhadi Zahra Amiri Department of Mathematics University of Science and Technology of Mazandaran Behshahr Iran Department of Computer Science University of Science and Technology of Mazandaran Behshahr Iran Faculty of Computer Engineering Shahrood University of Technology Shahrood Iran

ISBN: (纸本)9781665476249

Support vector machines (SVMs) are famous and important classifiers in classification researches. SVM and its application have been used in an enormous amount of research in various scientific domains in recent years. there are different methods to solve SVM problems. Coordinate descent methods are one of the main categories of methods for solving these problems. In this paper, using the generalization of Aitken’s $\Delta 2$ process to the vector case, a new accelerated coordinate descent algorithm is proposed. the new algorithm is tested with three different datasets. the numerical results indicate the efficiency of the new algorithm in the concept of increasing the speed of convergence.

关键词： Support vector machines Signal processing algorithms Support vector machine classification Signal processing Classification algorithms Intelligent systems Convergence

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Monkeypox Detection from Various Types of Poxes: A Deep Learning Approach

Monkeypox Detection from Various Types of Poxes: A Deep Lear...

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international conference for Convergence of Technology (I2CT)

作者： Anik Pramanik Fayazunnesa Chowdhury Salma Sultana Md. Mahbubur Rahman Md. Hasan Imam Bijoy Md. Sadekur Rahman Department of Computer Science and Engineering Daffodil International University Dhaka Bangladesh Department of Statistics Jahangirnagar University Dhaka Bangladesh

According to World Health Organization (WHO) statistics, monkeypox has been identified as an epidemic in 127 nations so far, and it is spreading quickly over the globe. While the rashes and skin lesions associated with monkeypox usually mimic those of other poxes, including chickenpox and measles. Due to these similarities, it could be challenging for medical professionals to identify monkeypox based just on the appearance of lesions and rashes. Because monkeypox was uncommon before in the current outbreak, healthcare professionals lack knowledge in this area. But the scientific community has demonstrated a rising interest in implementing Artificial Intelligence in Monkeypox prediction and detection from digital skin images as a result of the success of image processing approaches in COVID-19 detection. In this study, we have applied three cutting-edge deep learning models which are InceptionV3, MobileNetV3, and DenseNet201, referred to as transfer learning models, to detect monkeypox on skin images using the publicly available Monkeypox Skin Image Dataset 2022 with four classes. According to our research, transfer learning models can detect monkeypox with a top 93.59% accuracy for the InceptionNet-V3 pre-trained model from three implemented algorithms on digitized skin images. For further research, larger training images are required to train those deep learning models to achieve a higher vigorous detection rate.

关键词： Deep learning Training Transfer learning Organizations Medical services Skin Lesions

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Digitalization of Administrative Documents A Digital Transformation Step in Practice 8

Digitalization of Administrative Documents A Digital Transfo...

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8th NAFOSTED conference on Information and Computer Science, NICS 2021

作者： Van Nguyen, Sinh Nguyen, Dung Anh Pham, Lam Son Quoc International University Vietnam National University of HCMC School of Computer Science and Engineering Ho Chi Minh Viet Nam

ISBN: (纸本)9781665410014

Digital transformation is one of the most popular keyword in recent years. It is not only a trend in science research based on the development of information technology, but also a proposed duty that applied in the companies or organizations nowadays. Digitalization of administrative documents is therefore considered as the first step in digital transformation of public organization. through the digitizing process, the information that were in written format or hard copies will be converted into digital format (e.g. document files) to serve for storing, mining, processing and managing the documents. this paper presents a method to build a web application for digitizing the administrative documents applied in most public organizations. the method is based on the OCR (Optical Character Recognition) combined with the image processing techniques. Our digital process is implemented as following steps. (i) Scanning the hard copies of the administrative documents. (ii) Removing noise data and filtering necessary information in the content based on image processing technique. (iii) Classifying automatically the acquired contents into the respective components of a template form following the structured format of Vietnam Government. (iv) Generating automatically a document file. the application can process a document with a single or multiple pages. To compare with similar applications, our application is processed very fast, without limitation of pages for each document and obtained accuracy as our expectation. © 2021 IEEE.

关键词： Optical character recognition

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Detection of Email Spam using Machine Learning Algorithms: A Comparative Study

Detection of Email Spam using Machine Learning Algorithms: A...

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international conference on Signal processing and Communication (ICSC)

作者： Prazwal thakur Kartik Joshi Prateek thakral Shruti Jain Department of CSE & IT Jaypee University of Information Technology Solan Himachal Pradesh India

ISBN: (纸本)9781665454315

In the digital world a lot of emails are received every day, and most of them are not of any relevance to us, some are containing suspicious links which can cause harm to our system in some way or other. this can be overcome by using spam detection. It is the process of classifying whether the email is a genuine one or if it is some kind of spam. the purpose of spam detection is to deliver relevant emails to the person and separate spam emails. Already every email service provider has spam detection but still, its accuracy is not that much, sometimes they classify useful emails as spam. this paper focuses on the comparative analysis approach, where various Machine Learning models are applied to the same dataset. the different machine learning models were compared based on accuracy and Precision. Support vector machine results in 98.09% accuracy.

关键词： Support vector machines Analytical models Machine learning algorithms Unsolicited e-mail Machine learning Signal processing Regression tree analysis

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A Hybrid Signcryption Scheme with Leakage-resilience Resistant to Side-channel Attacks*

A Hybrid Signcryption Scheme with Leakage-resilience Resista...

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international conference on Imaging, Signal processing and Communication (ICISPC)

作者： Yuh-Min Tseng Ting-Chieh Ho Sen-Shan Huang Tung-Tso Tsai Department of Mathematics National Changhua University of Education Changhua Taiwan Department of Computer Science and Engineering National Taiwan Ocean University Keelung Taiwan

ISBN: (数字)9798350367157

ISBN: (纸本)9798350367164

In public-key cryptography (PKC), a signcryption (SC) scheme is a significant primitive by combining both signature and encryption functionalities in one scheme while reducing computing time. Most SC schemes are based on single PKC setting, such as public-key infrastructure PKC (PKI-PKC), identity-based PKC (ID-PKC), certificate-based PKC (CB-PKC), and certificateless PKC (CL-PKC). For providing practical usage, numerous hybrid SC (HSC) schemes were also presented to suit for the sense that a sender and a recipient belong to different PKC settings (i.e., heterogeneous PKC settings). Recently, side-channel attacks have been realized to endanger the existing SC and HSC schemes. Indeed, the research of leakage-resilient cryptography resistant to side-channel attacks have attracted the attention of researchers. Indeed, several SC schemes with leakage resilience (SC-LR) based on single PKC setting have been proposed. However, little research focuses on HSC scheme with leakage-resilience (HSC-LR). therefore, this paper aims to design the first HSC-LR from senders under a CB-PKC setting to recipients under a PKI-PKC setting, called as the HSC-LR-CBPKI scheme. We formally define a new framework and two security games of the HSC-LR-CBPKI scheme. Two security theorems are proved that the HSC-LR-CBPKI scheme possesses both signature and encryption functionalities (including unforgeability and confidentiality) under side-channel attacks. Finally, the proposed scheme is very efficient by performance analysis.

关键词： Resistance Analytical models Imaging Side-channel attacks Games Signal processing Public key cryptography

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A Methodology for Verifying and Validating the Functional Performance Evaluation of High-Fidelity RADAR Sensor Models at Raw Data and Detection Levels

A Methodology for Verifying and Validating the Functional Pe...

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international conference on Vision, Image and Signal processing (ICVISP)

作者： Arsalan Haider Lukas Haas Abduelkadir Eryildirim thomas Zeh Shotaro Koyama Nils Henning Müllner Martin Jakobi Alexander W. Koch IFM-Institute for Driving Assistance and Connected Mobility Kempten University of Applied Sciences Germany Institute for Measurement Systems and Sensor Technology Technical University of Munich Germany Infineon Technologies Austria AG Advanced Vehicle Research Institute Kanagawa Institute of Technology Japan Institute of Transportation Systems German Aerospace Center DLR Germany

ISBN: (数字)9798331541460

ISBN: (纸本)9798331541477

this paper outlines a comprehensive methodology for verifying and validating the functional performance evaluation of high-fidelity radio detection and ranging (RADAR) sensor models at both the raw data level, specifically the range map (RM) and range-Doppler map (RDM), and the detection level. three key performance parameters (KPPs) are defined at the raw data level: the target's received power, signal-to-noise ratio (SNR), and twoway beam pattern. Four KPPs are identified at the detection level: distance, relative radial velocity, azimuth angle, and elevation angle. this study also introduces three dynamic test scenarios directly applicable to the functional evaluation assessment of RADAR sensor models. Furthermore, a toolchain is presented to integrate real-world test scenarios into the virtual environment, allowing for frame-by-frame validation of the RADAR sensor models' functional evaluation. Quantitative analysis successfully assesses differences between simulations and real measurements, employing the mean absolute percentage error (MAPE) metric. this methodology has been successfully applied to a high-fidelity RADAR sensor model featuring a multiple input and multiple output (MIMO) 2D linear spacing virtual antenna and a complete signal processing toolchain that mimics real RADAR sensors. Results show a strong correlation between the simulation and real measurements, with MAPE values below 7 % for all defined KPPs at raw data and detection levels. Using this methodology, developers can assess whether virtual RADAR sensors are ready for environmental perception during scenario-based automated driving system (ADS) testing.

关键词： Performance evaluation Correlation Radar detection Radar Radar antennas Data models Radar signal processing Distance measurement Signal to noise ratio Testing

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Review Analysis of E-Learning Websites Selection and Ranking Methodologies

Review Analysis of E-Learning Websites Selection and Ranking...

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international conference on Signal processing and Communication (ICSC)

作者： Divya Parveen Sehgal Aakash Gupta Department of Computer Science and Engineering Om Sterling Global University Hisar India Department of Computer Science and Engineering Gateway Institute of Engineering & Technology Sonipat India

ISBN: (纸本)9781665454315

the present research analysis emphasis on the selection and ranking of E-learning websites against a predefined set of selection indexes. this review analysis mainly focuses on how to select and rank E-Learning websites is generally based on conflicting evaluation indexes using MCDM methodologies. the difference between e-learning, online learning and distance learning concept is explained in the introduction section. there are many mythologies which were applied by various researchers for the selection and ranking of e-learning websites but no one is hundred percent optimized and trustworthy. Every methodology has its own advantage and disadvantages. this paper also emphasis on the various MCDM methods such as AHP, ANP, TOPSIS, ELECTRE, COPRAS and VIKOR which were used by the researchers to select and rank the e-learning websites.

关键词： Knowledge engineering Computer aided instruction Electronic learning Signal processing Indexes

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An Efficient Pre-processing Technique using HOLF for 2D Image Interpolation

An Efficient Pre-processing Technique using HOLF for 2D Imag...

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international conference on Signal processing and Communication (ICSC)

作者： Jagyanseni Panda Sukadev Meher Department of ECE NIT Rourkela Study leave from SOA University Rourkela India Department of ECE NIT Rourkela Rourkela India

ISBN: (纸本)9781665454315

A pre-processing interpolation method is suggested for producing edge preserved high resolution (HR) images of greater size from low resolution (LR) images. there are several interpolation techniques that cause non-uniform blurring in the upscaled image. Upscaling, like low pass filtering, produces blurring in the image’s edge region when compared to the flat region. Prior to upscaling, a pre-processing scheme is applied to mitigate blurring artifacts caused by interpolation in order to recover fine details and high frequency (HF). Using a combination of low pass and high pass filters, the LR is decomposed into various frequency sub-bands. the degraded HF bands are extracted and sharpened using higher order laplacian filters (HOLF). this method restores the HF details prior to interpolation to produce an HR image with no blurring artifacts. According to objective and subjective measures, the proposed algorithm outperforms other state-of-the-art methods.

关键词： Interpolation Image resolution Laplace equations Image edge detection Signal processing algorithms Filtering algorithms Signal processing

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Exploration of Optimization Algorithms for Brain-Computer Interfaces Combined with Quantum Computing

Exploration of Optimization Algorithms for Brain-Computer In...

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Advanced Algorithms and Control Engineering (ICAACE), international conference on

作者： Hulin Jin Zhiran Jin Yong-Guk Kim Yutong Zhou Zixu Wang School of Computer Science and Technology Anhui University Hefei China Foothill Preparatory School Temple City California USA Department of Computer Engineering Sejong University seoul South Korea

ISBN: (数字)9798331535087

ISBN: (纸本)9798331535094

Brain-computer interface (BCI) technology, as a key means of human-computer interaction, has a wide range of applications in the fields of neurorehabilitation, brain-control devices, and intelligent medicine. However, existing BCI systems suffer from high computational complexity, low decoding accuracy, and limited real-time performance during neural signal processing, which restricts their practical applications. In this study, a quantum-enhanced BCI optimization algorithm is proposed to address this technical bottleneck by combining the parallel computing capability and nonlinear optimization characteristics of quantum computing. the study constructs a quantum-classical hybrid computing architecture, uses quantum Fourier transform (QFT) to enhance the efficiency of time-frequency analysis of EEG signals, introduces quantum principal component analysis (QPCA) to optimize the dimensionality reduction of high-dimensional data, and enhances the generalization ability of motion intent classification by combining with quantum support vector machines (QSVMs), and verifies the effectiveness of the method in experiments. the results show that the method outperforms the traditional BCI algorithm in terms of decoding accuracy, computational efficiency and real-time performance, and the system end-to-end latency is controlled within 200ms, which meets the demands of online brain-computer interaction. this study provides theoretical support and experimental validation for the application of quantum computing in the field of brain-computer interface, which can be further expanded to closed-loop neuromodulation, intelligent prosthesis control and other application scenarios in the future, providing new ideas for the development of high-efficiency brain-computer interaction technology.

关键词： Support vector machines Quantum computing Fourier transforms Accuracy Signal processing algorithms Brain-computer interfaces Real-time systems Hardware Optimization Principal component analysis

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Control Selection Based on State Change of Chaotic System

Control Selection Based on State Change of Chaotic System

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international conference on Computer and Communications (ICCC)

作者： Jiaxi Zhou Wei Zhang Yuming Feng B. O. Onasanya School of Electronics and Information Engineering Chongqing Three Gorges University Wanzhou Chongqing China Key Laboratory of Intelligent Information Processing and Control Chongqing Three Gorges University Wanzhou Chongqing China School of Three Gorges Artificial Intelligence Chongqing Three Gorges University Wanzhou Chongqing China Department of Mathematics University of Ibadan Ibadan Oyo State Nigeria

Considering that the system may need to meet more needs in the control process, that is, to accelerate or slow down the control intensity according to the system state, the control mode that combines the control cycle and the control method has a wider range of applications. In this paper, the model for state detection and judgment in the second half of the control cycle is studied, and appropriate measures are taken to achieve various control effects of the system. the simulation of the application example illustrates the effectiveness of the controller.

关键词： Analytical models Chaotic communication Process control Control systems Numerical models Optimization

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