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Analyzing Land Cover and Land Use Changes Using Remote Sensing Techniques: A Temporal Analysis of Climate Change Detection with Google Earth Engine 22

Analyzing Land Cover and Land Use Changes Using Remote Sensi...

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22nd IEEE International Conference on Trust, Security and Privacy in Computing and Communications, TrustCom 2023

作者： Afzal, Mozina Ali, Kamran Kasi, Mumraiz Khan Ur Rehman, Masood Khoshkholgh, Mohammad Ali Haq, Bushra Shah, Syed Ahmed Balochistan University of Information Technology Engineering and Management Sciences Quetta Pakistan Middlesex University Faculty of Science and Technology London United Kingdom Balochistan University of Information Technology Engineering and Management Sciences Department of Computer Science Quetta Pakistan University of Glasgow Department of Electronic Engineering Glasgow United Kingdom Lahore University of Management Sciences Lahore Pakistan

ISBN: (纸本)9798350381993

The detection of changes in land cover and land use (LCLU) is crucial for various geospatial applications, including urban development and environmental management. One vital aspect of LCLU research involves identifying modifications in impervious surface cover, which has significantly increased due to global economic growth and the rising urban population in many parts of the world. This investigation employs Landsat 9 OLI- 2/TIRS-2 imagery with a 30m spatial resolution to map structures in the Ziarat District of Pakistan, encompassing forests, water bodies, and barren land. It aims to detect changes in tree cover and canopy height. A time series of Landsat 9 OLI-2/TIRS-2 images were utilized to create change detection and land cover maps. The Analysis of Land Cover and Land Use (LCLU) for the Ziarat District was conducted using the GEE platform. The satellite images were classified into broad land cover classes, which include impervious surfaces, forest/tree cover, grassland/cropland, and water. The generated change detection map facilitates the identification of locations that have undergone modifications due to new constructions, offering valuable insights for the implementation of urban development policies and disaster management on a global scale. © 2023 IEEE.

关键词： Land use

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A Systematic Literature Review of Blockchain technology

International Journal of Interactive Mobile Technologies

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International Journal of Interactive Mobile Technologies 2022年第10期16卷 97-108页

作者： Ghazi, Alaan Alisawi, Muthana Wahab, Yousif Mohammed Al-Dawoodi, Aras Abdullah, Sirwan Saber Hammood, Layth Nawaf, Asmaa Yaseen Department of Computer Technical Engineering Al-Qalam University College Kirkuk Iraq Faculty of Applied and Human Sciences University Malaysia Perlis Perlis Malaysia Computer Science College of Computer Science and Information Technology University of Kirkuk Kirkuk Iraq Gazi University Ankara Turkey Information Technology and Communication Department Rafidain Bank Iraq Altinbas University Istanbul Turkey Computer Science College of Computer Science University of Anbar Kirkuk Iraq

The Blockchain technology moves data nodes and data streams from one informatics center to another based on the importance of Bitcoins, resulting in a dedicated, public, and secure network for interpretation and development of the ensuing information chain reaction. Blockchains are frequently formed by connecting interrelated patterns of information in order to conduct a secure transaction. Blockchain has the characteristics of decentralization, transparency, immutability, autonomy, open-source, anonymity, and consensus. Block chains are being utilized in a variety of real-world applications, including business and economics, financial technology, and digital currencies. This article does a comprehensive review of the literature on blockchain technology. While searching for the keyword "blockchain" as a subject, we identified a total of 1882 entries in these databases. After removing the less common record kinds, the papers were reduced to 1246 articles, which were then used for further investigation. © 2022

关键词： Smart contract

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Intelligent Real-Time Hypoglycemia Prediction for Type 1 Diabetes

Intelligent Real-Time Hypoglycemia Prediction for Type 1 Dia...

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Intelligent Methods, Systems, and Applications (IMSA)

作者： Nevien A. Mahdy Ahmed F. Elnokrashy D. A. Hammad Wael A. Mohamed Electrical Engineering Department Benha Faculty of Engineering Benha University Benha Egypt Computer Science Department Faculty of Information Technology and Computer Science Nile University Giza Egypt Basic Engineering Sciences Department Benha Faculty of Engineering Benha University Benha Egypt

ISBN: (数字)9798350362633

ISBN: (纸本)9798350362640

Hypoglycemia in Type 1 Diabetes (T1D) refers to a condition where blood glucose (BG) levels drop to abnormally low levels, typically below 70 mg/dL. This can occur when there is an excessive amount of insulin relative to the blood glucose level, leading to an imbalance that can be dangerous and potentially life-threatening if not promptly treated. The availability of large amounts of data from continuous glucose monitoring (CGM), insulin doses, carbohydrate intake, and additional vital signs, together with deep learning (DL) techniques, has revolutionized algorithmic approaches for BG prediction in T1D, achieving superior performance. In our study, we employed a Long Short-Term Memory (LSTM) neural network architecture to predict hypoglycemia events in patients with T1D. For the training and testing, we utilized the OhioT1DM (2018) dataset. In addition, real-time data collected from an individual patient for the evaluation. This patient utilized the CGM FreeStyle Libre (FSL) system, along with a smartwatch to monitor step count. The LSTM model exhibited performance demonstrating exceptional levels of sensitivity, specificity, and accuracy scores of 97.09%, 94.17%, and 95.63%, respectively, when assessed using the Ohio test dataset. Our research provides strong evidence supporting the system's efficacy in managing hypoglycemia events in individuals diagnosed with T1D.

关键词： Training Wearable Health Monitoring Systems Real-time systems Data models Glucose Diabetes Insulin

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An Enhanced Hybrid Cryptography Model for Online Banking Authentication and Security 2nd

An Enhanced Hybrid Cryptography Model for Online Banking Aut...

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2nd International Conference on Connected Objects and Artificial Intelligence, COCIA 2024

作者： Awotunde, Joseph Bamidele Brahma, Biswajit Adeniyi, Abidemi Emmanuel Lauretta Nkonyeasua, Edogbo Imoize, Agbotiname Lucky Mejdoub, Youssef Department of Computer Science Faculty of Information and Communication Sciences University of Ilorin Ilorin240003 Nigeria McKesson Corporation 32559 Lake Bridgeport Street FremontCA94555 United States Department of Computer Science Bowen University Iwo Nigeria Department of Electrical and Electronics Engineering Faculty of Engineering University of Lagos Akoka Lagos100213 Nigeria RITM Laboratory Higher School of Technology ESTC Hassan II University Casablanca Morocco

ISBN: (纸本)9783031704109

In the digital age, protecting the security and privacy of sensitive data has become of the utmost importance, particularly while conducting online financial transactions. This paper intends to build an advanced hybrid cryptography model, combining the strengths of the Rivest-Shamir-Adleman (RSA) and Advanced Encryption Standard (AES) algorithms, to improve the authentication and security procedures of online banking systems. To provide a strong and effective encryption framework, the suggested model makes use of RSA’s asymmetric key advantages and AES’s symmetric key capabilities. Because AES is quick and efficient at encrypting large amounts of data, it is used to optimize performance while encrypting the actual data being transmitted. Meanwhile, RSA is used to solve the problem of key distribution, secure the exchange of symmetric keys, and enable secure communication. The goal of the paper is to create an extensive system that incorporates this improved hybrid cryptography model into the online banking authentication procedure. User authentication, transaction verification, and data secrecy are the system’s three main building blocks. To ensure the viability and feasibility of the suggested paradigm in real-world online banking scenarios, implementation difficulties such as key management, algorithm integration, and performance optimization are addressed. This research advances cryptographic methods of contemporary banking security by utilizing the advantages of AES and RSA in a hybrid approach. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2024.

关键词： Adversarial machine learning

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A Novel Adaptive Linear Neuron Based on DNA Strand Displacement Reaction Network

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IEEE/ACM Transactions on Computational Biology and Bioinformatics 2022年第3期19卷 1424-1434页

作者： Zou, Chengye Wei, Xiaopeng Zhang, Qiang Zhou, Changjun Anyang Normal University School of Mathematics and Statistics Anyang455000 China Dalian University of Technology Faculty of Electronic Information and Electrical Engineering Dalian116024 China Dalian Minzu University College of Computer Science and Engineering Dalian116024 China

Analog DNA strand displacement circuits can be used to build artificial neural network due to the continuity of dynamic behavior. In this study, DNA implementations of novel catalysis, novel degradation and adjustment reaction modules are designed and used to build an analog DNA strand displacement reaction network. A novel adaptive linear neuron (ADALINE) is constructed by the ordinary differential equations of an ideal formal chemical reaction network, which is built by reaction modules. When reaction network approaches equilibrium, the weights of the ADALINE are updated without learning algorithm. Simulation results indicate that, ADALINE based on the analog DNA strand displacement circuit has ability to implement the learning function of the ADALINE based on the ideal formal chemical reaction networks, and fit a class of linear function. © 2004-2012 IEEE.

关键词： Degradation

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RepATT: Re-parameterization and Attention-guided Hybrid Anchor Classification for Real-time Lane Detection

RepATT: Re-parameterization and Attention-guided Hybrid Anch...

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2023 International Conference on Artificial Intelligence of Things and Systems, AIoTSys 2023

作者： Yao, Xin-Wei Zhang, Kai-Jie Yang, Yang Pu, Gui-Yang Li, Qiang Zhejiang University of Technology College of Computer Science and Technology Hangzhou China Zhejiang University of Technology Institute for Frontier and Interdisciplinary Sciences Hangzhou China Ocean University of China Faculty of Information Science and Engineering Qingdao China Information Technology Co. Ltd Hangzhou China

ISBN: (纸本)9798350312270

Lane detection is a critical technology in autonomous driving, which requires both high detection accuracy and real-time efficiency, especially in complex scenarios like severe occlusions, and dazzling light conditions. To achieve the above requirements, based on re-parameterization and attention mechanism we propose a real-time lane detection network with a classification-based manner named RepATT. A new backbone Extended RepVGG (ExtRep) which subtly decouples the training time and inference time is proposed as the feature extractor. Specifically, the ExtRep has two additional branches of varying complexities and scales compared to the original RepVGG. This enhancement improves the performance without any additional inference cost by enhancing the representational capacity of single convolution with re-parameterization methods. In addition, by integrating the Convolutional Block Attention Module(CBAM), our model improves the performance in the no-visual evidence scenarios. CBAM generates the attention maps via channel and spatial dimensions enabling the model to concentrate more on the lanes. Through comprehensive experiments conducted on CULane and TuSimple datasets, the results demonstrate our proposed method achieves the fastest inference speed, which surpasses the baseline model by 24% to 363 FPS with lower computing cost, while the F1-measure of RepATT also outperforms the previous methods on both datasets. © 2023 IEEE.

关键词： Convolution

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Helmet Detection Recognition Algorithm Based on Improved Yolov5

Helmet Detection Recognition Algorithm Based on Improved Yol...

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Image Processing and computer Vision (IPCV), International Conference on

作者： Shuo Lin Zongmei Li Faculty of Computer and Information Engineering Xiamen University of Technology Xiamen Chin

The existing helmet detection algorithm is mainly based on a single-stage object detection algorithm, which has high detection speed and can achieve the requirement of real-time detection. Still, the accuracy of detecting small objects and objects with obstacles is no high. Based on this, this paper proposes a helmet detection recognition algorithm based on improved YOLOv5. The SE attention mechanism has the advantages of low complexity, few parameters and low computational effort. Firstly, the SE attention module is added to the Yolov5 backbone network to weigh the features of different channels and improve the model's attention to important features. Secondly, using softnms to replace nms in the original network can retain more small target prediction frames, improve the detection accuracy, and improve the model's ability to detect small targets. The experiments show that the average accuracy, precision, and recall of the proposed method reach 96.51%, 95.20%, and 90.08%, respectively, and the real-time performance meets the need for helmet detection in practical work.

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Design and Simulation of a Network Infrastructure for a Multi-Branch Organization Using Cisco Packet Tracer 25

Design and Simulation of a Network Infrastructure for a Mult...

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25th International Arab Conference on Information technology, ACIT 2024

作者： Aljamal, Osama S. Aljamal, Mahmoud Alsarhan, Ayoub Aljaidi, Mohammad Okour, Saif Al-Aiash, Issa Al-Qerem, Ahmad Daoud, Essam Al Elrashidi, Ali Al Hussein Technical University Department of Computer Science Amman Jordan Irbid National University Faculty of Science and Information Technology Department of Cybersecurity Irbid21110 Jordan The Hashemite University Department of Information Technology Zarqa Jordan Zarqa University Department of Computer Science Zarqa Jordan Irbid National University Department of Software Engineering Irbid Jordan Zarqa University Department of Cybersecurity Zarqa Jordan University of Business and Technology Department of Electrical Engineering Jeddah21432 Saudi Arabia

ISBN: (纸本)9798331540012

Designing and simulating a network infrastructure for multi-branch organizations is essential for ensuring seamless connectivity and efficient operations. This paper addresses the challenges faced by organizations in maintaining consistent and reliable network connectivity across multiple locations, including managing network traffic, ensuring security, and optimizing resource allocation while keeping costs under control. The study presents a comprehensive methodology involving the conceptualization of network ideas, designing the network architecture, adding necessary devices and tools, configuring these devices according to the network topology, and troubleshooting to ensure optimal performance. Key elements such as VLANs, routers, switches, and routing protocols like RIP, OSPF, and EIGRP are incorporated, with the entire design and simulation conducted using Cisco Packet Tracer. The findings demonstrate that full connectivity between headquarters and branch sites can be achieved within a budget of $40,000. This paper provides a practical guide for implementing similar network projects, emphasizing the importance of detailed configurations and troubleshooting steps, and recommends adopting this methodology to enhance network infrastructure efficiently and cost-effectively. © 2024 IEEE.

关键词： Budget control

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SAR Complex Images Subpixel Co-registration 22

SAR Complex Images Subpixel Co-registration

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22nd International Symposium on Electrical Apparatus and Technologies, SIELA 2022

作者： Lazarov, Andon Minchev, Dimitar Nikola Vaptsarov Naval Academy Information Technology Department Varna Bulgaria K.N. Toosi University of Technology Aerospace Engineering Faculty Tehran Iran Burgas Free University Faculty of Computer Science and Engineering Burgas Bulgaria

ISBN: (数字)9781665411394

ISBN: (纸本)9781665411394

Generation of correct SAR interferometric images and differential interferometric images, a precise co-registration of SAR complex images is required. In the present study, an algorithm for modeling pseudo SAR images is suggested to illustrate subpixel co-registration. Based on the spectral definition of the spatial SAR images a spectral co-registration algorithm with subpixel precision is developed and numerically experimented. © 2022 IEEE.

关键词： Synthetic aperture radar

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A versatile framework for analyzing galaxy image data by incorporating Human-in-the-loop in a large vision model

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Chinese Physics C 2024年第9期48卷 176-187页

作者： Ming-Xiang Fu Yu Song Jia-Meng Lv Liang Cao Peng Jia Nan Li Xiang-Ru Li Ji-Feng Liu A-Li Luo Bo Qiu Shi-Yin Shen Liang-Ping Tu Li-Li Wang Shou-Lin Wei Hai-Feng Yang Zhen-Ping Yi Zhi-Qiang Zou National Astronomical Observatories Chinese Academy of SciencesBeijing 100101China College of Electronic Information and Optical Engineering Taiyuan University of TechnologyTaiyuan 030024China School of Astronomy and Space Science University of Chinese Academy of SciencesBeijing 101408China Key lab of Space Astronomy and Technology National Astronomical ObservatoriesBeijing 100101China School of Computer Science South China Normal UniversityGuangzhou 510631China CAS Key Laboratory of Optical Astronomy National Astronomical ObservatoriesBeijing 100101China University of Chinese Academy of Sciences NanjingNanjing 211135China University of Science and Technology Beijing Beijing 100083China Shanghai Astronomical Observatory Chinese Academy of SciencesShanghai 200030China School of Computer and Information Dezhou UniversityDezhou 253023China Faculty of Information Engineering and Automation Kunming University of Science and TechnologyKunming 650500China School of Computer Science and Technology Taiyuan University of Science and TechnologyTaiyuan 30024China School of Mechanical Electrical and Information EngineeringShandong UniversityWeihai 264209China Nanjing University of Posts&Telecommunications Nanjing 210023China School of Science University of Science and Technology LiaoningAnshan 114051China

The exponential growth of astronomical datasets provides an unprecedented opportunity for humans to gain insight into the ***,effectively analyzing this vast amount of data poses a significant *** response,astronomers are turning to deep learning techniques,but these methods are limited by their specific training sets,leading to considerable duplicate *** overcome this issue,we built a framework for the general analysis of galaxy images based on a large vision model(LVM)plus downstream tasks(DST),including galaxy morphological classification,image restoration object detection,parameter extraction,and *** the low signal-to-noise ratios of galaxy images and the imbalanced distribution of galaxy categories,we designed our LVM to incorporate a Human-in-the-loop(HITL)module,which leverages human knowledge to enhance the reliability and interpretability of processing galaxy images *** proposed framework exhibits notable fewshot learning capabilities and versatile adaptability for all the abovementioned tasks on galaxy images in the DESI Legacy Imaging *** particular,for the object detection task,which was trained using 1000 data points,our DST in the LVM achieved an accuracy of 96.7%,while ResNet50 plus Mask R-CNN reached an accuracy of 93.1%.For morphological classification,to obtain an area under the curve(AUC)of~0.9,LVM plus DST and HITL only requested 1/50 of the training sets that ResNet18 *** addition,multimodal data can be integrated,which creates possibilities for conducting joint analyses with datasets spanning diverse domains in the era of multi-messenger astronomy.

关键词： artificial intelligence large vision model human-in-the-loop astronomy galaxies

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