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9th IEEE International Conference for Convergence in Technology, I2CT 2024

作者： Basak, Aakashneel Niharika, K. Jayasri, P.V. Usha Sundari Ryali, H.S.V. Sarma, Manju Indian Space Research Organisation Sar Data Processing Division Microwave Data Processing Group Data Processing Area National Remote Sensing Centre India

ISBN: (纸本)9798350394474

Synthetic Aperture Radar (SAR) Calibration & Validation are critical processes to ensure the accuracy, precision and reliability of SAR imaging systems. These activities are particularly essential in dynamic environments over extended periods, where changes in onboard SAR payload, data processing software or environmental conditions can influence the system performance. This paper provides a detailed exposition on the conceptualization and development of a Graphical User Interface (GUI), specifically designed to input essential parameters for comprehensive assessment of radiometric, geometric and polarimetric SAR image quality parameters from both Point and Distributed target data. The software excels in presenting analysis results in a well-organized tabulated format & offers a valuable feature allowing users to have the visual representation of the Impulse Response and Gamma Naught pattern data. A standout attribute of the software lies in its ability to effortlessly store and retrieve analysis data through its interface with SQLite database. This seamlessly integrated database System streamlines the organization and archival of calibration results, establishing a thorough historical record for each analysis. The utilization of the SQLite database guarantees data integrity & empowers users to effortlessly retrieve and compare calibration data over time, fostering effective trend analysis and enabling a comprehensive evaluation of the long-term performance of SAR system. The software has been created with Python programming language as front-end and SQLite as part of back-end. The developed GUI software package represents a significant advancement in SAR system calibration methodologies, providing SAR data analyst with a user-friendly interface for efficient SAR calibration analysis. © 2024 IEEE.

关键词： Synthetic aperture radar

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System Design & Implementation of Automated Batch processing Software for EOS-04 SAR data: Optimizing Radiometric Parameters Estimation 5

System Design & Implementation of Automated Batch Processing...

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5th IEEE International Conference for Emerging Technology, INCET 2024

作者： Basak, Aakashneel Niharika, K. Jayasri, P.V. Sahu, Samvram Usha Sundari Ryali, H.S.V. Sarma, Manju SAR Data Processing Division National Remote Sensing Centre Indian Space Research Organisation Hyderabad India Microwave Data Processing Group National Remote Sensing Centre Indian Space Research Organisation Hyderabad India Data Processing Area National Remote Sensing Centre Indian Space Research Organisation Hyderabad India

ISBN: (纸本)9798350361155

Generally, batch processing concurrently executes multiple jobs in sequential order, breaking down large tasks into smaller parts for efficient offline processing, reducing resource consumption and processor stress. This research paper introduces an automated approach for batch processing of systematic EOS-04 microwave satellite data coverage over Indian region to extract radiometric parameters. Additionally, it discusses batch processing of EOS-04 data over homogeneous rain forests (Amazon, Congo region) to compute gamma naught patterns. A software has been developed with user-friendly Graphical User Interface (GUI) to automate the radiometric analysis of multi-year time series data for the selected opportunistic homogeneous themes. Users can choose an area of interest from a drop-down menu, providing the software with the geographical coordinates needed to process each file in the parent folder for estimating analysis parameters. The extracted parameters are then utilized to perform time series analyses & subsequently stored in a database for future retrieval. The developed GUI features a real-time progress bar for batch processing, allowing users to monitor task progression efficiently. Additionally, the system automatically notifies predefined user IDs and phone numbers via emails and Short Message Service (SMS) alerts upon task completion, providing details on successfully processed files and identifying any failures for streamlined issue resolution. By automating the batch processing of EOS-04 data, this research significantly reduces manual efforts previously required for calibration and validation analysis of large volumes of Synthetic Aperture Radar (SAR) data. The proposed system enhances efficiency, accuracy, and ease of use, offering a valuable tool for researchers involved in SAR sensor data analysis and monitoring. © 2024 IEEE.

关键词： Synthetic aperture radar

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A novel Machine Learning based approach for Detecting Radiometric Artifacts in SAR Imagery 15

A novel Machine Learning based approach for Detecting Radiom...

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15th European Conference on Synthetic Aperture Radar, EUSAR 2024

作者： Sahu, Samvram Jayasri, P.V. Niharika, K. Usha Sundari Ryali, H.S.V. Manju Sarma, S. Data Processing Area National Remote Sensing Centre Indian Space Research Organisation India

ISBN: (纸本)9783800762873

Synthetic Aperture Radar (SAR) images often suffer from radiometric artifacts originating due to many reasons leading to degradation of data product quality. To provide SAR data products with better quality, reliability and integrity, it is highly required to comprehend and detect the radiometric artifacts in SAR images based on its characteristic signature (either in time domain or frequency domain) using suitable approach so as to localize the artifacts for further detection. This paper describes a novel approach suitable for identifying these specific radiometric artifacts in SAR data based on AI-ML & Computer Vision techniques. Localized & global artifacts are dealt with different approaches, feature extraction using hand-crafted feature extractors & deep learning-based extractors are used. Training of classical Machine Learning models on extracted features as well as use of vanilla U-Nets & CNN for segmentation and classification is carried out. The suitability of different methods to increase the detection of varied artifacts is presented. Intersection Over Union (IoU) scores of segmentation based approaches & Recall - Precision score of classification based approach is compared for combination of various models & artifacts. The U-Net is able to handle most of the artifacts with ~0.85 IoU score & the ANN supersedes the other classifiers. © VDE VERLAG GMBH ∙ Berlin ∙ Offenbach.

关键词： Synthetic aperture radar

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Application of GERG and AGA8 Methods for Calculation the Compression Factor of Natural Gas at Low Temperatures

Application of GERG and AGA8 Methods for Calculation the Com...

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2024 International Conference on Industrial Engineering, Applications and Manufacturing, ICIEAM 2024

作者： Kutovoy, Denis Shustrova, Marina Fafurin, Victor Kazan National Research Technological University Department Of The Automated Systems Of Data Obtaining And Processing Kazan Russia

ISBN: (纸本)9798350395013

The article is devoted to the application of calculation methods AGA8- DC 92, AGA8 Report Detail, GERG2004, GERG2008, GERG91, ISO 20765-1 at temperatures of 220.. 250 K. Experimental high-precision values of natural gas compression coefficient are determined and deviations of values obtained by the specified methods are calculated. It is shown that the deviation of the calculation results by AGA8- DC 92, AGA8 Report 1 Detail, GERG2004/2008, ISO 20765-1 from the experiment does not exceed 0.1%. This confirms the possibility of using AGA8-DC92, AGA8 Report 1 Detail, GERG2004/2008, ISO 20765-1 as calculating methods in the temperature range of 220.. 250 K. The results obtained in the framework of this study are highly significant for flow metering, in particular, provide an increase in the accuracy of the procedure for bringing the volume of natural gas to standard conditions at low temperatures. © 2024 IEEE.

关键词： Natural gas

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2D T1-Weighted CE MRI Images Classification with Hybrid Channel Attention Block enhanced VGG-16 and MobileNet 1

2D T1-Weighted CE MRI Images Classification with Hybrid Chan...

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1st IEEE Karachi Section Humanitarian Technology Conference, Khi-HTC 2024

作者： Fareed, Mohammad Jawad Pluempitiwiriyawej, Charnchai Murtaza, Ghulam Chulalongkorn University Multimedia Data Analytics and Processing Research Unit Department of Electircal Engineering Bangkok Thailand

ISBN: (纸本)9798350373042

Motivated by the imperative need for precise and swift classification of brain tumors depicted in MRI images, this study unveils a novel classification network tailored explicitly for this task. Existing lightweight methodologies, although explored extensively, have fallen short of achieving the accuracy benchmarks attained by the model. The approach underwent rigorous testing on a challenging 2D T1-weighted CE-MRI dataset housing three distinct types of brain tumors: Meningioma, Glioma, and Pituitary. Recognizing the susceptibility of models to overfitting during training, introduced was a normalized combined channel and spatial attention mechanism, strategically incorporated to serve as an effective regularizer. Comparative analysis against state-of-the-art methodologies on this dataset highlights a notable performance boost of 2.12 percentage points achieved by integrating this attention mechanism into a base network. Furthermore, the fusion of the model with the pre-trained VGG16 network and GoogleNet into an ensemble demonstrates superior accuracy;however, this amalgamation comes at the expense of execution speed. © 2024 IEEE.

关键词： Image classification

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Multiple Face Detection and Recognition for System-an-Chip FPGAs 21

Multiple Face Detection and Recognition for System-an-Chip F...

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21st International Joint Conference on Computer Science and Software Engineering, JCSSE 2024

作者： Santiwiwat, Siraphop Hajian, Amir Ruangsang, Watchara Aramvith, Supavadee Chulalongkorn University Multimedia Data Analytic and Processing Research Unit Faculty of Engineering Department of Electrical Engineering Bangkok Thailand

ISBN: (纸本)9798350381764

Recognizing multiple faces within a single frame or image presents a significant challenge in facial recognition tasks. This challenge demands robust algorithms capable of handling variations in facial position, unstable brightness, and the presence of accessories such as glasses or hats. However, in current surveillance applications, multiple face recognition is vital for maintaining various security measures. In such applications, there is a need for processors that are compact and deployable in diverse environments. FPGA is popular due to its compact size, cost-effectiveness, and high performance. This paper presents the implementation of multiple face detection and recognition on an SoC FPGA utilizing the Xilinx Kria KV260 platform. We chose the MTCNN algorithm for multiple face detection and the ResNet-20 model for multiple face recognition developed by Vitis AI, and we fine-tuned this model using the CUFace dataset. Our results demonstrate the robust capability to detect and recognize faces of up to 8 individuals within a single frame in just 0.11 seconds, with a recognition rate of 93.77%. © 2024 IEEE.

关键词： System-on-chip

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A numerical magnitude aware multi-channel hierarchical encoding network for math word problem solving

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Neural Computing and Applications 2025年第3期37卷 1651-1672页

作者： Xu, Junjie Chen, Yuzhong Xiao, Lingsheng Liao, Hongmiao Zhong, Jiayuan Dong, Chen College of Computer and Data Science Fuzhou University Fujian Province Fuzhou350108 China Engineering Research Center of Big Data Intelligence Ministry of Education Fuzhou China Fujian Provincial Key Laboratory of Network Computing and Intelligent Information Processing Fujian Province Fuzhou350108 China

Math word problem (MWP) represents a critical research area within reading comprehension, where accurate comprehension of math problem text is crucial for generating math expressions. However, current approaches still grapple with unresolved challenges in grasping the sensitivity of math problem text and delineating distinct roles across various clause types, and enhancing numerical representation. To address these challenges, this paper proposes a Numerical Magnitude Aware Multi-Channel Hierarchical Encoding Network (NMA-MHEA) for math expression generation. Firstly, NMA-MHEA implements a multi-channel hierarchical context encoding module to learn context representations at three different channels: intra-clause channel, inter-clause channel, and context-question interaction channel. NMA-MHEA constructs hierarchical constituent-dependency graphs for different levels of sentences and employs a Hierarchical Graph Attention Neural Network (HGAT) to learn syntactic and semantic information within these graphs at the intra-clause and inter-clause channels. NMA-MHEA then refines context clauses using question information at the context-question interaction channel. Secondly, NMA-MHEA designs a number encoding module to enhance the relative magnitude information among numerical values and type information of numerical values. Experimental results on two public benchmark datasets demonstrate that NMA-MHEA outperforms other state-of-the-art models. © The Author(s), under exclusive licence to Springer-Verlag London Ltd., part of Springer Nature 2024.

关键词： Semantics

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IGED:Towards Intelligent DDoS Detection Model Using Improved Generalized Entropy and DNN

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Computers, Materials & Continua 2024年第8期80卷 1851-1866页

作者： Yanhua Liu Yuting Han HuiChen Baokang Zhao XiaofengWang Ximeng Liu College of Computer and Data Science Fuzhou UniversityFuzhou350108China Engineering Research Center of Big Data Intelligence Ministry of EducationFuzhou350108China Fujian Key Laboratory of Network Computing and Intelligent Information Processing Fuzhou UniversityFuzhou350108China College of Computer National University of Defense TechnologyChangsha410073China

As the scale of the networks continually expands,the detection of distributed denial of service(DDoS)attacks has become increasingly *** propose an intelligent detection model named IGED by using improved generalized entropy and deep neural network(DNN).The initial detection is based on improved generalized entropy to filter out as much normal traffic as possible,thereby reducing data *** the fine detection is based on DNN to perform precise DDoS detection on the filtered suspicious traffic,enhancing the neural network’s generalization *** results show that the proposed method can efficiently distinguish normal traffic from DDoS *** with the benchmark methods,our method reaches 99.9%on low-rate DDoS(LDDoS),flooded DDoS and CICDDoS2019 datasets in terms of both accuracy and efficiency in identifying attack flows while reducing the time by 17%,31%and 8%.

关键词： DDoS real-time improved generalized entropy DNN

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EXISTENCE AND UNIQUENESS OF SOLUTIONS FOR UNCERTAIN NONLINEAR SWITCHED SYSTEMS WITH V-N JUMPS

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UPB Scientific Bulletin, Series A: Applied Mathematics and Physics 2025年第1期87卷 129-140页

作者： Jia, Zhifu Li, Cunlin School of Mathematics and Physics Suqian University Suqian223800 China [Ningxia Key Laboratory of intelligent information and Big Data Processing Governance and Social Management Research Center of Northwest Ethnic Regions North Minzu University Yinchuan China

In this paper, an uncertain nonlinear switched system with V-n jumps, characterized by its sensitivity to subjective uncertainties, is modeled using uncertain differential equations with V-n jumps. To account for the discontinuous jump behavior in each subsystem, a V-n jumps process associated with an uncertain Z-n jumps variable, defined by a jump uncertainty distribution, is introduced. Under the assumptions of linear growth and Lipschitz conditions, an existence and uniqueness theorem for the solutions of uncertain nonlinear switched systems with V-n jumps is established and rigorously proven. An illustrative example is provided to demonstrate the effectiveness and applicability of the theoretical results. © 2025, Politechnica University of Bucharest. All rights reserved.

关键词： Uncertain systems

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Graphical User Interface Development with database Integration for Cal-Val Analysis of Multiple SAR Missions

Graphical User Interface Development with Database Integrati...

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International Conference for Convergence of Technology (I2CT)

作者： Aakashneel Basak Niharika K Jayasri PV Usha Sundari Ryali HSV Manju Sarma SAR Data Processing Division Microwave Data Processing Group Data Processing Area National Remote Sensing Centre Indian Space Research Organisation

ISBN: (数字)9798350394474

ISBN: (纸本)9798350394481

关键词： Visualization Technological innovation Software packages System performance Scalability Radar polarimetry Calibration

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