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Optimization of YOLOv8 for Defect Detection and Inspection in Aircraft Surface Maintenance using Enhanced Hyper Parameter Tuning

Optimization of YOLOv8 for Defect Detection and Inspection i...

引用

2024 International Conference on Electrical, Electronics and Computing Technologies, ICEECT 2024

作者： Pasupuleti, Shailaja Ramalakshmi, K. Pattisapu, Varaha Madhavi Alliance University AU-Centre of Excellence Computer Vision Alliance College of Engineering and Design Bangalore India Bharath Institute of Higher Education and Research Dept. of Computer Science and Engineering Chennai India

ISBN: (纸本)9798350378092

Aviation repair is governed by strict standards, because maintaining the integrity of aircraft surfaces is essential. Conventional inspection techniques, which frequently rely on manual examinations, are time-consuming and prone to human mistake. Through a SEM model picture collection of aircraft surface flaws, this study investigates the improved use of YOLOv8 (You Only Look Once version 8) for diagnosing and identifying surface concerns in aviation maintenance. In order to precisely identify, locate, and classify different defect kinds, such as aggressive pitches and thin resists, it presents a revolutionary ensemble deep learning approach. In order to particularly assess SEM pictures with defects including gaps, potential gaps, line collapses, bridges, and micro bridges, the research entails training MobileNet backbone models. To further enhance detection and classification performance, the suggested approach combines predictions from several models using a Weighted Box Fusion (WBF) ensembling strategy. According to experimental findings, the optimized YOLOv8 model outperforms conventional YOLOv8 models in terms of accuracy and speed thanks to its WBF ensembling and MobileNet backbone. This sophisticated model is excellent at spotting a variety of surface flaws, such as corrosion, fractures, and other irregularities. Aircraft surface restoration has advanced significantly with the integration of MobileNet and WBF into the improved YOLOv8 model, improving Mean Average Precision (mAP) for difficult defect categories. Metrics like the F1-score, accuracy, precision, recall, specificity, and confidence score are used to assess how well this method is at reliably detecting and localizing different types of defects in SEM pictures by utilizing deep learning. © 2024 IEEE.

关键词： Deep learning

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Deep Predictive User Path-Inclusive Service Mobility in B5G/6G Edge Clouds 18

Deep Predictive User Path-Inclusive Service Mobility in B5G/...

引用

18th International Conference on Ubiquitous Information Management and Communication, IMCOM 2024

作者： Mwasinga, Lusungu J. Raza, Syed M. Le, Duc-Tai Kim, Moonseong Chung, Min Young Choo, Hyunseung Dept. of Computer Science and Engineering Sungkyunkwan University Suwon Korea Republic of Dept. of Electrical and Engineering Sungkyunkwan University Suwon Korea Republic of College of Computing and Informatics Sungkyunkwan University Suwon Korea Republic of Dept. of IT Convergence Seoul Theological University Bucheon Korea Republic of

ISBN: (纸本)9798350331011

Multi-access Edge Computing (MEC)-enabled Beyond 5G (B5G) or 6G networks require service migration to maintain service continuity and acceptable quality of experience for high-mobility User Equipment (UE). This involves migration of containerized applications to between Edge Hosts via the backhaul network as the associated UE moves away from its current gNodeB. Although crucial for both UEs and mobile network operators (MNOs), frequent migration not only prolongs service disruption time (downtime) for UEs but also increases operational expenses for the MNO. To address this problem, our study proposes a Deep Predictive User Path-Inclusive Service Mobility (DUPSM) approach for efficient management of the end-to-end migration process including deciding when and where to migrate the service. It features a deep Actor-Critic agent that learns suitable decision policy to balance cost-benefit trade-off interms of migration cost and quality of experience, respectively. As user mobility largely influences migration decisions, the proposed method incorporates user mobility path forecasting through a Generative Adversarial Network (GAN) based prediction technique to enhance ability for selecting suitable Edge Host while considering resource variations. The effectiveness of the proposed method is assessed through simulation experiments, showcasing an average reduction in service downtime of 22% when compared to a baseline scheme. © 2024 IEEE.

关键词： Reinforcement learning

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Product Prediction using Sentiment Analysis and Linear Regression 6

Product Prediction using Sentiment Analysis and Linear Regre...

引用

6th International Conference on Inventive Computation Technologies, ICICT 2023

作者： Patibandla, Joshiaka Sri Nilofuer, Shafia Sidhartha, Musku Raghavendra Sai, N. Dept. of Computer Science and Engineering Koneru Lakshmaiah Education Foundation Greenfields Vaddeswaram Guntur522302 India

ISBN: (纸本)9798350398496

An important research issue is how to carry out rapid and accurate business marketing by learning how to identify successful clients, reduce the cost of business competition, and understand customer feelings and buying preferences. This research work discusses the methodology for the sake of proper analysis of data that relate to client- provided evaluations and surveys for products sold over a period of time in the Amazon commercial centre. The data sets are analysed using sentiment analysis and linear regression analysis. It is discovered that the ratings like best performer rating or the star rating is optimistic and correlated with the reviews that are completely dependent on the analysis of sentiment provided by the classification algorithms like Naive Bayesian classification algorithm. Multiple regression analysis is used to determine the relationship between three indexes: helpful rating, star ratings and reviews. An optimistic correlation within the three indexes is found, and the reputation of the product in the online market improves eventually. It is proposed that positive reviews indicate a potentially successful or failing product depending up on the optimistic reviews that has been received star ratings. Finally, candidate words from the Amazon sentiment dictionary are chosen. © 2023 IEEE.

关键词： Sentiment analysis

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Multi-agent Task Assignment in Unmanned Aerial Vehicle Edge Computing based on Deep Learning Approach 3

Multi-agent Task Assignment in Unmanned Aerial Vehicle Edge ...

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3rd International Conference on Automation, Computing and Renewable Systems, ICACRS 2024

作者： Samuel, Amalorpava Mary Rajee Yamuna Devi, M.M. Madhusudhanan, S. Dept. of Electrical and Information Engineering University of Witwatersrand Johannesburg South Africa Department of Computer Science and Engineering Koneru Lakshmaiah Education Foundatio Vijayawada India Department of Computer Science and Engineering Rajalakshmi Engineering College Chennai India

ISBN: (纸本)9798331532420

Unmanned aerial vehicles (UAVs) are used as supportive edge computing for sparsely located user equipment on a large scale. In this work, we propose and address a collaborative edge computing system involving multiple UAVs as agents in deep reinforcement learning (DRL) approach due to the restricted computation and energy capabilities of UAVs. The challenge of task offloading is being tackled to reduce the total delays in execution and energy usage by simultaneously planning the paths, assigning computation tasks, and managing communication resources of UAVs. Additionally, Lyapunov optimization is incorporated for the system stability of mobile edge computing assisted by multiple UAVs. Exploring a multi-agent deep reinforcement learning framework to achieve a combined strategy to manage task allocation, and power management. The sum rate results of the evaluation show that our method for task offloading using multi-UAV and multi-EC achieves superior performance with 25 % increase when compared to other optimization methods and ability to reduce cost and delay. © 2024 IEEE.

关键词： Energy utilization

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Analysis of ECG Image File Encryption using ECDH and AES-GCM Algorithm 7

Analysis of ECG Image File Encryption using ECDH and AES-GCM...

引用

7th International Workshop on Big Data and Information Security, IWBIS 2022

作者： Oktivasari, Prihatin Agustin, Maria Akbar, Rahmat Esa Mohammad Kurniawan, Asep Zain, Ayu Rosyida Murad, Fachroni Arbi Politeknik Negeri Jakarta Dept. of Informatics and Computer Engineering Depok Indonesia

ISBN: (数字)9781665489508

ISBN: (纸本)9781665489508

Image data is used in various fields, including the health sector. One of the image data in the health sector is an electrocardiogram (ECG). The ECG contains the identifying information of a person which must be guarded and secured. ECG image data security can be done by encrypting image data using encryption algorithms. The encryption algorithms used in this thesis are ECDH and AES-GCM. ECDH is used to generate key pairs which are then used as keys for AES-GCM encryption and decryption. The encryption and decryption process are carried out in the python programming language. The results of the encryption time and decryption time increase because of the dimensions and size of the ECG image file. The nonce value and authentication tag are checked to be able to perform the decryption process. The histogram test results prove the uniformity of pixels in the encrypted ECG image file. PSNR and SSIM test results prove the difference between the initial and encrypted ECG image files. The results of the NIST Statistical Test Suite test prove that the algorithm used produces random output so that it can be used to secure ECG image files. © 2022 IEEE.

关键词： Electrocardiograms

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Exploring User Experience and Challenges with Mobile Wallet Adoption in Emerging Markets 2

Exploring User Experience and Challenges with Mobile Wallet ...

引用

2nd International Conference on Technology Innovation and Its Applications, ICTIIA 2024

作者： Priandito Lutfiani, Ninda Yusuf, Natasya Aprila Goh, Thomas Sumarsan Madani, Muchlisina University of Raharja Dept. of Informatics Engineering Tangerang Indonesia University of Raharja Dept. of Digital Business Tangerang Indonesia University of Raharja Dept. of Information Systems Tangerang Indonesia Universitas Methodist Indonesia Dept. of Management Medan Indonesia University of Raharja Dept. of Computer System Tangerang Indonesia

ISBN: (纸本)9798350351613

This study explores user experiences and challenges in mobile wallet adoption in emerging markets using the UTAUT model. These markets face rapid technological growth alongside infrastructural and economic challenges. The research examines how factors like performance expectancy, effort expectancy, social influence, and facilitating conditions influence adoption. Data from 80 mobile wallet users was collected through an online survey and analyzed using SmartPLS 4.1.0.6. The results show that performance and effort expectancy predict behavioral intention, while facilitating conditions affect actual usage. The study highlights the role of infrastructure in supporting adoption and validates the UTAUT model's relevance in less developed regions. These findings provide insights into enhancing financial inclusion in emerging markets. © 2024 IEEE.

关键词： Emerging Markets Mobile Wallet Technology Adoption User Experience UTAUT

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Increasing Hosting Capacity of Uncontrollable Distributed Energy Resources in Isolated Power Systems

Increasing Hosting Capacity of Uncontrollable Distributed En...

引用

2023 IEEE PES Innovative Smart Grid Technologies Europe, ISGT EUROPE 2023

作者： Therapontos, Phivos Stavrou, Andreas Aristidou, Petros Electricity Authority of Cyprus Nicosia Cyprus Department of Electrical and Computer Engineering Nicosia Cyprus Dept. of Electrical and Computer Engineering and Informatics Cyprus University of Technology Limassol Cyprus

ISBN: (纸本)9798350396782

Due to the push for more sustainable generation, small-scale distributed energy resources (DERs) penetration has increased significantly. Most countries have no remote monitoring and control requirements for DERs below a certain size. Therefore, they can be labeled as uncontrollable DERs (UDERs). In isolated systems, the UDERs hosting capacity is limited due to frequency stability concerns, as it is impossible to modify or curtail their generation in a centralized manner. In this paper, we propose the utilization of the active power over-frequency reduction curve for increasing the hosting capacity of UDERs in isolated power systems. Cyprus’s power system has been used to evaluate the proposed solution’s performance. The optimal settings of the curve have been identified, and it was found that UDERs hosting capacity can be increased significantly with the proposed methodology. © 2023 IEEE.

关键词： frequency stability grid code requirements hosting capacity islanded systems uncontrollable distributed energy resources

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Design of a Simple Tools for Record and Payment of Passengers in City Bus 7

Design of a Simple Tools for Record and Payment of Passenger...

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7th International Conference on Electric Vehicular Technology, ICEVT 2022

作者： Oktivasari, Prihatin Zain, Ayu Rosyida Agustin, Maria Sulaiman, Nur Fauzi Anshor, Muhammad Fabian Fahroji, Muhammad Fatih Karim, Muhammad Arysil Putra, Andika Dwi Politeknik Negeri Jakarta Dept. of Informatics and Computer Engineering Depok Indonesia

ISBN: (数字)9781665409421

ISBN: (纸本)9781665409421

The development and progress of the means of transportation are needed for people to mobilize all activities However, currently conventional public transportation such as urban transportation has become less attractive to the public because of all the factors that cause people not to choose conventional transportation over online-based public transportation. The mechanism of the cost for urban transport is still not by with the passenger route using the city transportation service, for which a passenger record system is established to be able to determine the route of passenger location and the data of each passenger who wishes to ride to use the transportation services of the city, as well as the cost system travel passenger city transportation can be set and set according to the distance of travel from passengers. The system of passenger record method and system control of notification with device and application for public transportation payment consists of components such as Arduino to control and manage RFID RC522 system data to read RFID tag, Real Time Clock (RTC) DS1307 to activate the clock and dates in real-Time, Passive Infrared (PIR) module sensors to detect human presence and desktop applications for charging balances and website applications for databases. © 2022 IEEE.

关键词： Clocks

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Successful Simple Side Channel Analysis: Vulnerability of an atomic pattern kP algorithm implemented with a constant time crypto library to simple electromagnetic analysis attacks 12

Successful Simple Side Channel Analysis: Vulnerability of an...

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12th Mediterranean Conference on Embedded Computing, MECO 2023

作者： Sigourou, Alkistis Aikaterini Kabin, Ievgen Langendorfer, Peter Sklavos, Nicolas Dyka, Zoya Germany University of Patras SCYTALE Group Computer Engineering and Informatics Dept. Greece BTU Cottbus-Senftenberg Cottbus Germany

ISBN: (纸本)9798350322910

Elliptic curve cryptosystem is a widely-used public key cryptosystem that is vulnerable to physical attacks, especially to Side Channel Analysis (SCA) attacks. This paper investigates a version of the atomic patterns kP algorithm for elliptic curves over prime finite fields. The atomic patterns for Elliptic Curve (EC) point doublings and additions are well-known countermeasures against simple SCA attacks. We implemented a binary left-to-right kP algorithm corresponding to the atomic patterns as proposed by Rondepierre and using the FLECC open-source cryptographic library. The library provides constant-time functions for the implementation of different mathematic operations in prime finite fields, making it suitable for SCA-aware implementations of cryptographic protocols, at a theoretical level. We were able to reveal the scalar k processed during a kP execution analyzing the measured electromagnetic trace of the kP execution. We determined at least two parts in the measured trace where the distinction between EC point doublings and EC point additions is good observable. © 2023 IEEE.

关键词： Side channel attack

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Analysis of data from UAVs for surveillance and threat identification in maritime areas 8

Analysis of data from UAVs for surveillance and threat ident...

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8th IEEE/ACIS International Conference on Big Data, Cloud Computing, and Data Science, BCD 2023

作者： Lampropoulos, Fotis Daramouskas, Ioannis Perikos, Isidoros Paraskevas, Michael University of Peloponnese Electrical and Computer Engineering Dept. Patras Greece Hellenic Coast Guard Patras Greece University of Patras Computer Technology Institute and Press "diophantus" Computer Engineering and Informatics Department Patras Greece University of Peloponnese Computer Technology Institute and Press "diophantus" Electrical and Computer Engineering Dept. Patras Greece

ISBN: (纸本)9798350373615

In this paper, we present a methodology for drones for recognizing different types of objects in maritime areas. The concept and the aim is to assist the national maritime surveillance authorities in the identification of treats and the recognition of the exact type of the treat. The methodology relies on the use of deep learning networks and YOLO framework as well as regression models. The YOLO model detects where each object is and which label should be applied. In this way, object detection is subject to the analysis of Machine Learning-based approaches and Deep Learning-based approaches providing more information about the video or an image than traditional approaches to recognition. These approaches are used to identify groups of pixels that may individually belong to an object. This then feeds a regression model with the help of a convolutional neural network and more specifically, R-CNN, Fast R-CNN, Faster R-CNN and after that object detection algorithm approximates the location of the object and gives its label at the same time. The purpose of the application is to detect objects with an emphasis on identifying one or more targets of interest from data of a video or an image capture. An experimental study was conducted in real-world conditions and revealed quite interesting findings. © 2023 IEEE.

关键词： computer vision

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