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MODEL-based RECONSTRUCTION FOR COLLIMATED BEAM ULTRASOUND systems 47

MODEL-BASED RECONSTRUCTION FOR COLLIMATED BEAM ULTRASOUND SY...

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47th IEEE international conference on Acoustics, Speech and signal Processing (ICASSP)

作者： Alanazi, Abdulrahman Venkatakrishnan, Singanallur Santos-Villalobos, Hector Buzzard, Gregery Bouman, Charles Purdue Univ Main Campus W Lafayette IN 47907 USA Oak Ridge Natl Lab One Bethel Valley Rd Oak Ridge TN 37831 USA King Saud Univ KSU Riyadh Saudi Arabia

ISBN: (纸本)9781665405409

Collimated beam ultrasound systems are a novel technology for imaging inside multi-layered structures such as geothermal wells. Such systems include a transmitter and multiple receivers to capture reflected signals. Common algorithms for ultrasound reconstruction use delay-and-sum (DAS) approaches;these have low computational complexity but produce inaccurate images in the presence of complex structures and specialized geometries such as collimated beams. In this paper, we propose a multi-layer, ultrasonic, model-based iterative reconstruction algorithm designed for collimated beam systems. We introduce a physics-based forward model to accurately account for the propagation of a collimated ultrasonic beam in multilayer media and describe an efficient implementation using binary search. We model direct arrival signals, detector noise, and a spatially varying image prior, then cast the reconstruction as a maximum a posteriori estimation problem. Using simulated and experimental data we obtain significantly fewer artifacts relative to DAS while running in near real time using commodity compute resources.

关键词： Non-destructive testing ultrasonic imaging model-based imaging collimated beam multi-layered object

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Deep Learning-based Malware Classification Methodology of Comprehensive Study 2

Deep Learning-based Malware Classification Methodology of Co...

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2nd international conference on Sustainable Computing and Data Communication systems, ICSCDS 2023

作者： Depuru, Sivakumar Santhi, K. Amala, K. Sakthivel, S. Sivanantham, S. Akshaya, V. Dept of Csse Tirupati India Dept. of Cse Tirupati India Dept. of Ece Tirupati India Dept of Cse Tirupati India

ISBN: (纸本)9781665491990

The increasing connectivity of devices and systems in today's world has led to a significant increase in the spread of malware. The rapid advancements in technology have made it easier for cybercriminals to gain access to crucial information and disrupt mechanisms on a very large scale. With the widespread use of the internet, the proliferation of mobile devices, and the growing adoption of these devices, the opportunities for malware to spread have grown exponentially. Malware has the ability to recreate itself and spread across systems through various mechanisms. Malware can spread from any of the following: phishing emails, websites, infected USBs, remote access, and other removable media. As computers have become more integrated into nearly every aspect of our lives, it inadvertently leads to the evolution of malware that can spread more easily. We need a mechanism to differentiate the different kinds of malware by classifying them, so as to pre-emptively fight against the malware. This study uses a combination of convolutional neural network and spatial attention, a deep learning model that classifies 25 malware families using image-based methodologies. © 2023 IEEE.

关键词： Convolutional neural networks

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Compact multidomain single-image dehazing network based on gUNet and test-time training 5

Compact multidomain single-image dehazing network based on g...

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5th international conference on Machine Learning, Big Data and Business Intelligence, MLBDBI 2023

作者： Zhang, Liwei Bian, Haiyi School of Accounting and International Trade Suzhou Institute of Trade&Commerce Suzhou215009 China Faculty of Electronic Information Engineering Huaiyin Institute of Technology Huai'an Jiangsu223003 China Jiangsu Engineering Laboratory for Lake Environment Remote Sensing Technologies Huai'an Jiangsu223003 China

ISBN: (纸本)9798350359930

image dehazing is a field that focuses on enhancing the visibility of hazy images. It is important in various applications such as improving image quality, enhancing surveillance capabilities, and aiding in remote sensing and navigation systems under haze weather. Recently, image dehazing has notably advanced by the development of deep learning. Although compact single-domain single image dehazing network (gUNet) and a technique towards multi-domain single image dehazing (test-time training) have been proposed, compact multi-domain single image dehazing network is still not been implemented. We combine gUNet and test-time training to build such a compact network. A qualitative comparison of dehazed images predicted by our network and gUNet demonstrate the remarkable improvement achieved by our proposal in multidomain single-image dehazing. The peak signal-to-noise ratio and structural similarity index confirm the higher performance of our network. © 2023 IEEE.

关键词： Navigation systems

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Research on Measuring Method of Ball Indentation based on MATLAB image Edge Detection 4th

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4th international conference on 3D Imaging Technologies- Multidimensional signal Processing and Deep Learning, 3D IT-MSP and DL 2022

作者： Zhou, Yuan Wang, Xin Liu, Ya Wang, Xiaoyuan Li, Zheng Wang, Yanying Shandong Institute of Inspection On Product Quality Jinan250102 China

ISBN: (纸本)9789819912292

Ball pressure test is an important test to evaluate the heat resistance of non-metallic materials. At present, most of the tests are judged by manual measurement, with low accuracy. In this paper, the digital image measurement technology of MATLAB is used to transform and enhance the collected indentation image. The Gaussian Laplace operator is used to detect the edge of the image, find the maximum value of the coordinate difference between each element point on the image edge and other element points, traverse all the element points on the image edge, and put the obtained maximum value into the maximum value array;continue to find the maximum value in the maximum value array to obtain the diameter of the ball pressure indentation image, thus improving the measurement accuracy and realizing the intelligent measurement of the diameter of the ball pressure detection image. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Heat resistance

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4th international conference on Advanced Intelligent Technologies, ICAIT 2023

4th International Conference on Advanced Intelligent Technol...

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4th international conference on Advanced Intelligent Technologies, ICAIT 2023

ISBN: (纸本)9789819732098

The proceedings contain 52 papers. The special focus in this conference is on Advanced Intelligent Technologies. The topics include: international Competitive Landscape for Generative Artificial Intelligence technology based on Patent Metrics;A Study on Mobile Robot Path Planning in Constrained Environments Using an Enhanced RRT Algorithm;a Machine-Learning Approach in Assessing the Fama French Three and Fama French Five Factor Model;Deep Learning CNN-based Architecture Applied to Intelligent Near-Infrared Analysis of Water Pollution from Agricultural Irrigation Resources;research on the Application of Digital Twin Model Calculation and Updating Methods in Mining Engineering;research on the Factors Influencing the Horizontal Force of Body Block in the Impact Test of Steering Mechanism based on Orthogonal Test;design and Analysis of Double Arm Robot for Plate Installation;research on Public Opinion Monitoring System based on Improved Fuzzy Controller;context Understanding and Response Algorithm of Chat Robot based on Enhanced Seq2seq Model;lane Departure Detection and Early Warning System for Intelligent Vehicles based on Yolov3 Algorithm;attack Surface Modeling Study of Printing System;non-invasive Sleep Posture Analysis and Anomaly Detection Algorithm based on Computer Vision;design of Intelligent Data Synchronization and Analysis Algorithm Combining Digital Twinning and internet of Things;misalignment Detection Algorithm for Vertical Rigid Tank Channel Joints based on Improved Yolov8n;Research on the Influential Factors of Accuracy Improvement in aPLI Dynamic Calibration;joint Audio Captioning Transformer and Stable Diffusion for Audio-to-image Generation;research on the Design Strategy of Intelligent Rehabilitation Products Suitable for Ageing based on Analytic Hierarchy Process.

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A DC Microgrid Attack Detection Strategy based on Complete Ensemble Empirical Mode Decomposition with Adaptive Noise

A DC Microgrid Attack Detection Strategy based on Complete E...

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2023 international conference on Smart Electrical Grid and Renewable Energy, SEGRE 2023

作者： Wen, Mengfei Wen, Yian Zhang, Yu Zhang, Zhongke Zhu, Ren Changsha Preschool Education College School of Information Technology Changsha China Changsha University of Science and Technology School of Electrical and Information Engineering Changsha China Central South University School of Computer Science and Engineering Changsha China Changsha Preschool Education College School of Preeducation Changsha China

ISBN: (纸本)9798350323269

With the continuous development of renewable energy technologies and intelligent control systems, DC microgrids have become a popular direction for the development of future energy systems with the advantages of high efficiency and flexibility. However, because DC microgrids are closely connected to the internet, their complex network structures and communication protocols make them easy targets for cyber attacks. Therefore, this paper proposes an attack detection strategy based on the complete ensemble empirical mode decomposition with adaptive noise for detecting abnormal output data in DC microgrids. First, the voltage signal with a fast response rate is analyzed based on the effect of data injection on the output of DC microgrids. Secondly, sufficient feature extraction is performed on the output voltage using complete set empirical mode decomposition. Then, calculate the energy of the decomposed feature mode function, and set an anomaly threshold detection scheme based on the energy interval during normal operation of the DC microgrid to complete the detection of the abnormal output of the DC microgrid. Finally, the simulation verifies the reliability and effectiveness of the proposed detection strategy. © 2023 IEEE.

关键词： Renewable energy resources

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Efficient DOA Estimation Algorithm based on Modified Recursive Least Squares Algorithm 5

Efficient DOA Estimation Algorithm Based on Modified Recursi...

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5th IEEE international conference on Power, Intelligent Computing and systems, ICPICS 2023

作者： Zhu, Hongxi Cai, Xingyan Chang, Fengyi College of Internet of Things Engineering Hohai University at Changzhou Changzhou China College of Sydney Smart Technology Northeastern University at Qinhuangdao Qinhuangdao China College of Information and Communication Engineering Harbin Engineering University Harbin China

ISBN: (纸本)9798350333442

Traditional DOA algorithms for estimating based on subspace decomposition have high estimation accuracy, but the number of signal sources should be given and the eigenvalue decomposition of the covariance matrix is required, which has high computational complexity. Existing DOA estimation algorithms based on adaptive filtering overcome the drawbacks of the subspace-based decomposition algorithms. However, they have limitations in practical applications, as the DOA estimation error and resolution probability are significantly worse than that of subspace decomposition class algorithms. In this paper, a modified recursive least squares (mRLS) algorithm is put forward for DOA estimation. We define a new cost function, which introduces the minimum disturbance constraint and generalized convex penalty function into the traditional RLS algorithm. It has better convergence speed and less mean square error compared with the RLS algorithm. Simulations demonstrate that the proposed algorithm has higher estimation accuracy and resolution probability than existing adaptive filtering-based DOA estimation algorithms, and that its performance approximates that of subspace decomposition algorithms with a significant reduction in computational complexity. © 2023 IEEE.

关键词： Adaptive filtering

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IoT-based Blood Glucose Detection System 6

IoT-Based Blood Glucose Detection System

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6th IEEE international conference on Electrical, Electronics and System Engineering, ICEESE 2023

作者： Lim, Shau Ibrahim, Siti Zuraidah Karim, Mohd Nazri A Boonsong, Wasana Masrakin, Khuzairi Mohd Noh, Faridah Hanim Universiti Malaysia Faculty of Electronic Engineering & Technology Perlis Arau Malaysia Faculty of Electronic Engineering & Technology University Malaysia Perlis Arau Malaysia Rajamangala University of Technology Srivijaya Faculty of Industrial Education and Technology Department of Electrical Education Songkla Thailand University Tun Hussein Onn Malaysia Faculty of Engineering Technology Johor Malaysia

ISBN: (纸本)9781665453714

This study presents a non-invasive blood glucose concentration (BGC) system that is based on the internet of Things (IoT) and employs near-infrared sensors (NIR) to detect blood glucose levels through the scanning of fingers. The purpose is to develop a BGC system and assess the accuracy of the proposed system. Constant monitoring and data-driven insights for optimum treatment and enhanced quality of life are made possible by IoT-based systems, and non-invasive glucose monitoring is a critical component of diabetes care. The system that was built comprises of a Light Emitting Diode (LED) that emits signals that are sent via the fingertip, and a phototransistor that is positioned next to the LED to detect any reflected signals. The results of the scanning are then stored in ThingSpeak. The technique used to determine the blood glucose level involves analyzing the variation in received signal intensity that results from reflection. Using regression analysis, a mathematical relationship between glucose concentration and voltage was established and installed in the Arduino. Two sorts of testing were carried out to evaluate the system: in vitro tests on glucose solution and in vivo experiments on the human body. By comparing 10 readings acquired from both types of experiments, the results of the studies indicate that the device's glucose detection accuracy ranges from 1.13 to 16.41%. IoT approach is feasible due to its continuous monitoring capabilities, data analysis, and remote access features, making it a promising tool for effective diabetes control. © 2023 IEEE.

关键词： internet of things

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Autoencoder-based OFDM for Agricultural image Transmission 10

Autoencoder-based OFDM for Agricultural Image Transmission

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10th international conference on Advanced Cloud and Big Data (CBD)

作者： Li, Dongbo Liu, Xiangyu Shao, Yuxuan Sun, Yuchen Cheng, Siyao Liu, Jie Harbin Inst Technol Fac Comp IoT & Ambient Intelligence Res Ctr Harbin Peoples R China Harbin Inst Technol Fac Comp Harbin Peoples R China Harbin Inst Technol Shenzhen Int Res Inst AI Shenzhen Peoples R China

ISBN: (纸本)9798350309713

With the rapid development of the internet of Things (IoT), smart agricultural puts forward higher demands on the transmission of agricultural big data. This paper proposes an end-to-end learning communication with autoencoderbased orthogonal frequency division multiplexing (OFDM-AE) for agricultural image transmission, which solves the problems of delay, congestion and high complexity caused by the processing method to information of independent modularization for the conventional OFDM. It is proposed to construct AE based on convolutional neural network (CNN) to realize global joint optimization of end-to-end communication system. In this paper, the network architecture of OFDM-AE is designed and trained on massive agricultural image data. We analyze the performance of the proposed OFDM-AE in different signal-to-noise ratio (SNR) cases. The experimental results show that the OFDM-AE can retain the image feature information and has a very advantageous complexity performance compared to the conventional OFDM with various modulation methods.

关键词： internet of Things big data autoencoder OFDM agricultural image transmission

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Driving Training-based Optimization-Enabled Key Generation Approach for Secure and Efficient Authentication with Data Sharing Approach in IoT Healthcare 1

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international conference on Advances in signal Processing and Communication Engineering, ICASPACE 2023

作者： Waykar, Sanjay B. Kadu, Rajesh D. Karlekar, Nandkishore P. Shahare, Yogesh Mahatma Gandhi Mission’s College of Engineering and Technology Maharashtra Kamothe Navi Mumbai India School of Computing MIT-ADT University Pune India Department of Business Analytics ITM Skill University Kharghar Navi Mumbai India

ISBN: (数字)9789819705627

ISBN: (纸本)9789819705610

Blockchain technology (BT) offers a solution to the interoperability issues that currently plague health information systems. Additionally, BT provides the cutting-edge standard that ensures the safe exchange of computerized health data among healthcare providers, institutions, people, and medical specialists. Recently, both business and academics recognized the internet of Things (IoT) as one of the top study fields. Nevertheless, a significant issue in IoT healthcare across a number of product domains is the secrecy of patient health data transmission. For secure and effective authentication with data sharing strategy in IoT healthcare, a method called Driving Training-based Optimization (DTBO) Key generation is presented to address these issues. The entities involved in the proposed DTBO_Key generation technique are the user, owner, authenticating minor, blockchain, and IoT server. The suggested technique consists of seven stages: initialization, registration phase, key creation, login phase, data protection, authentication process, and verification phase. A minimum memory consumption of 2.983 MB, a computation cost of 28.008%, and an accuracy of 0.9 were attained using the proposed method. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.

关键词： internet of things

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