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36th IEEE/IFIP Network Operations and Management Symposium, NOMS 2023

作者： Revisnyei, Péter Mogyorósi, Ferenc Papp, Zsófia Töros, István Pašić, Alija Budapest University of Technology and Economics Faculty of Electrical Engineering and Informatics Department of Telecommunications and Media Informatics Muegyetem rkp. 3. BudapestH-1111 Hungary Ericsson Research ELKH-BME Information Systems Research Group Budapest Hungary

ISBN: (纸本)9781665477161

Indoor localization is one of the most requested applications for 5G networks. With the continuous deployment of new 5G networks, the implementation of a reliable, robust, and accurate indoor positioning algorithm has become a widely and thoroughly researched topic. However, the solutions realized for real-world environments still do not meet all performance expectations. In this paper, a real-world 5G environment is investigated and the feasibility of the measurements collected for positioning is discussed. Based on these findings, a framework for indoor positioning is proposed and evaluated using Time Difference of Arrival (TDOA) measurements. Within the framework, an iterative algorithm is implemented to minimize a non-linear least squares function extended with four additional methods to mitigate the measurement errors caused mainly by non-line-of sight propagation. The best parameter settings are determined with hyperparameter optimization, and it is shown that with these settings, sub-meter positioning error is a viable goal in certain scenarios. © 2023 IEEE.

关键词： 5G mobile communication systems

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Optimizing beyond boundaries: empowering the salp swarm algorithm for global optimization and defective software module classification

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Neural Computing and Applications 2024年第30期36卷 18727-18759页

作者： Kassaymeh, Sofian Al-Betar, Mohammed Azmi Rjoubd, Gaith Fraihat, Salam Abdullah, Salwani Almasri, Ammar Software Engineering Department Faculty of Information Technology Aqaba University of Technology Aqaba Jordan College of Engineering and Information Technology Ajman University Ajman United Arab Emirates Department of Information Technology Al-Huson University College Al-Balqa Applied University Irbid Jordan Concordia Institute for Information Systems Engineering Concordia University Montreal Canada Artificial Intelligence Department Faculty of Information Technology Aqaba University of Technology Aqaba Jordan Data Mining and Optimization Research Group Center for Artificial Intelligence Technology Universiti Kebangsaan Malaysia Bangi Malaysia Management Information Systems Department Al-Balqa Applied University Amman Jordan

This work presents a new version of the salp swarm optimizer (SSA), called "mSSA," that uses complex mathematical expressions to dynamically manipulate the crucial control parameter (c1) during optimization. These expressions are carefully designed to modulate the shift in search strategy from exploratory to exploitative, improving the flexibility and speed of convergence of the algorithm. To evaluate the performance of the developed mSSA variants, a thorough examination is carried out on twenty-three benchmark test functions alongside their application to the complex task of software module classification. The process of classifying defective software modules involves developing a multilayer perceptron (MLP) classifier that is suited to the particular complexity and heterogeneity of the task. Selecting the best optimizer is made easier by systematically evaluating the different mSSA versions as MLP classifier trainers. Based on metrics like classification accuracy, convergence speed, and avoidance of local minima, a comparative analysis in opposition to six previously published metaheuristic optimizers shows that mSSA3, when combined with the developed MLP classifier, outperforms both other mSSA variations and state-of-the-art metaheuristic optimizers in terms of overall performance. The excellent classification accuracy, swift convergence, and ability to avoid local minima of mSSA3 highlight its superiority and establish it as a cutting-edge method in the application of metaheuristic algorithms. © The Author(s), under exclusive licence to Springer-Verlag London Ltd., part of Springer Nature 2024.

关键词： Global optimization

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Sentinel: An Aggregation Function to Secure Decentralized Federated Learning 27

Sentinel: An Aggregation Function to Secure Decentralized Fe...

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27th European Conference on Artificial Intelligence, ECAI 2024

作者： Feng, Chao Celdrán, Alberto Huertas Baltensperger, Janosch Beltrán, Enrique Tomás Martínez Sánchez, Pedro Miguel Sánchez Bovet, Gérôme Stiller, Burkhard Communication Systems Group CSG Department of Informatics University of Zurich UZH ZürichCH-8050 Switzerland Department of Information and Communications Engineering University of Murcia Murcia30100 Spain Armasuisse Science & Technology Cyber-Defence Campus ThunCH-3602 Switzerland

ISBN: (纸本)9781643685489

Decentralized Federated Learning (DFL) emerges as an innovative paradigm to train collaborative models, addressing the single point of failure ***, the security and trustworthiness of FL and DFL are compromised by poisoning attacks, negatively impacting its *** defense mechanisms have been designed for centralized FL and they do not adequately exploit the particularities of ***, this work introduces Sentinel, a defense strategy to counteract poisoning attacks in *** leverages the accessibility of local data and defines a three-step aggregation protocol consisting of similarity filtering, bootstrap validation, and normalization to safeguard against malicious model *** has been evaluated with diverse datasets and data ***, various poisoning attack types and threat levels have been *** results improve the state-of-the-art performance against both untargeted and targeted poisoning attacks when data follows an IID (Independent and Identically Distributed) ***, under non-IID configuration, it is analyzed how performance degrades both for Sentinel and other state-of-the-art robust aggregation methods. © 2024 The Authors.

关键词： Federated learning

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Encryption Algorithm for Securing Non-Disclosure Agreements in Outsourcing Offshore software Maintenance

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Computers, Materials & Continua 2022年第11期73卷 3827-3845页

作者： Atif Ikram Masita Abdul Jalil Amir Bin Ngah Nadeem Iqbal Nazri Kama Azri Azmi Ahmad Salman Khan Yasir Mahmood Assad Alzayed Faculty of Ocean Engineering Technology and Informatics University Malaysia TerengganuKuala TerengganuMalaysia Department of Computer Science&Information Technology Faculty of Information TechnologyThe University of LahoreLahore54000Pakistan Department of Software Engineering Faculty of Information TechnologyThe University of LahoreLahore54000Pakistan Advanced Informatics Department Razak Faculty of Technology and InformaticsUniversiti Teknologi Malaysia54100Kuala LumpurMalaysia Computer Science and Information Systems Department College of Business Studies Public Authority for Applied Education and Training(PAAET)AdailiyaKuwait

Properly created and securely communicated,non-disclosure agreement(NDA)can resolve most of the common disputes related to outsourcing of offshore software maintenance(OSMO).Occasionally,these NDAs are in the form of *** the work is done offshore,these agreements or images must be shared through the Internet or stored over the *** breach of privacy,on the other hand,is a potential threat for the image owners as both the Internet and cloud servers are not void of *** article proposes a novel algorithm for securing the NDAs in the form of *** an agreement is signed between the two parties,it will be encrypted before sending to the cloud server or travelling through the public network,the *** the image is input to the algorithm,its pixels would be scrambled through the set of randomly generated rectangles for an arbitrary amount of *** confusion effects have been realized through an XOR operation between the confused image,and chaotic ***,5D multi-wing hyperchaotic system has been employed to spawn the chaotic vectors due to good properties of chaoticity it *** machine experimentation and the security analysis through a comprehensive set of validation metric vividly demonstrate the robustness,defiance to the multifarious threats and the prospects for some real-world application of the proposed encryption algorithm for the NDA images.

关键词： Non-disclosure agreement encryption decryption secret key chaoticmap confusion diffusion

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Peer to Peer Federated Learning: Towards Decentralized Machine Learning on Edge Devices 7

Peer to Peer Federated Learning: Towards Decentralized Machi...

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7th South-East Europe Design Automation, Computer engineering, Computer Networks and Social Media Conference, SEEDA-CECNSM 2022

作者： Karras, Aristeidis Karras, Christos Giotopoulos, Konstantinos C. Tsolis, Dimitrios Oikonomou, Konstantinos Sioutas, Spyros University of Patras Decentralized Systems Computing Group Computer Engineering and Informatics Department Patras Greece University of Patras Department of Management Science and Technology Patras Greece Ionian University Department of Informatics Corfu Greece

ISBN: (数字)9798350398588

ISBN: (纸本)9798350398588

Federated Learning (FL) is an emerging technique that assures user privacy and data integrity in distributed machine learning environments. To perform so, chunks of data are trained across edge devices and a high performance cluster server maintains a local copy without exchanging it with other parties. In this work, we investigate a FL scenario in a real-world case study using 5, 10 and 20 Raspberry Pi devices acting as clients. Under this setup, we employ the widely known FedAvg algorithm which trains each client for several local epochs and then the weight of each model is aggregated. Moreover we perform experiments across imbalanced and noisy data so as to explore scalability and robustness based on real-world datasets were noise is present and we also propose two innovative algorithms where the FL scenario is considered as a peer-to-peer formulation. Ultimately, to ensure that each device is not oversampled a client-balancing Dirichlet sampling algorithm with probabilistic guarantees is proposed. © 2022 IEEE.

关键词： Computer aided instruction

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Vehicle type recognition: a case study of MobileNetV2 for an image classification task 28th

Vehicle type recognition: a case study of MobileNetV2 for an...

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28th International Conference on Knowledge Based and Intelligent information and engineering systems, KES 2024

作者： Kobiela, Dariusz Groth, Jan Hajdasz, Michal Erezman, Mateusz Gdansk University of Technology Faculty of Electronics Telecommunications and Informatics Department of Software Engineering Gabriela Narutowicza 11/12 Gdansk80-233 Poland Gdansk University of Technology Faculty of Electronics Telecommunications and Informatics Department of Algorithms and Systems Modelling Gabriela Narutowicza 11/12 Gdansk80-233 Poland Gdansk University of Technology Faculty of Electronics Telecommunications and Informatics Gabriela Narutowicza 11/12 Gdansk80-233 Poland

The goal of the research was to demonstrate the full data science lifecycle through a use case of the MobileNetv2 model for vehicle image classification task using various validation and test sets, each with different difficulty level. Diverse model variations were employed, each designed to recognize images of ground vehicles and classify them into one of five possible classes: car, truck, motorcycle, bicycle, or bus. In terms of validation accuracy, the highest results were obtained by the model trained with uniformly designed train and val sets (with data normalization and augmentation), where train set also contained validation set. This model also obtained the highest accuracy results on both test sets. The superiority of MODEL 3 BASELINE is confirmed by other metrics as well: test loss, f1-score, AUC and confusion matrices (for both test sets). Results between MODEL 1 BASELINE and MODEL 2 BASELINE differed according to the test set 1 and 2 and other metrics and it was not possible to declare the superiority of one method of datasets preparation over another (original class distribution [no data normalization and no data augmentation] versus uniformly designed [with data normalization and augmentation]). The article also presents challenges and findings - the problems, key issues, and their solutions that arose during the process of data collection and tagging, as well as the preparation and evaluation of the model. © 2024 The Authors.

关键词： Classification (of information)

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Texture and Orientation-based Feature Extraction for Robust Facial Expression Recognition 21

Texture and Orientation-based Feature Extraction for Robust ...

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21st IEEE/ACIS International Conference on software engineering Research, Management and Applications, SERA 2023

作者： Khan, Sajid Ali Bin Abdulrahman Alawairdhi, Mohammed Al-Akhras, Mousa Foundation University Islamabad Department of Software Engineering Islamabad Pakistan Saudi Electronic University College of Computing and Informatics Saudi Arabia The University of Jordan Amman King Abdullah II School for Information Technology Computer Information Systems Department Jordan

ISBN: (纸本)9798350345889

Facial expressions are the most effective way to characterize people's motives, emotions, and feelings. Several new methods are proposed each year;however, the accuracy of facial expression recognition still needs to be improved especially in uncontrolled conditions. In this paper, we propose a hybrid facial expression model that considers both texture and orientation features to classify expressions. Two types of descriptors namely Local binary pattern and Weber local descriptor are used to preserve the local intensity information and orientation of edges. In the next step, computing the Histograms of oriented gradients (HOG) features from the Local binary pattern and Weber local descriptor images to capture micro-expressions. Then, the AdaBoost feature selection algorithm is utilized to choose the best features from the combined HOG features. The results of the experiments demonstrate that the method proposed in this study performs better than existing methods. © 2023 IEEE.

关键词： Local binary pattern

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SimulateIoT-Federations: Domain Specific Language for designing and executing IoT simulation environments with Fog and Fog-Cloud federations (Poster) 10

SimulateIoT-Federations: Domain Specific Language for design...

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STAF 2022 Workshop: 10th International Workshop on Bidirectional Transformations, BX 2022, 2nd International Workshop on Foundations and Practice of Visual Modeling, FPVM 2022 and 2nd International Workshop on MDE for Smart IoT systems, MeSS 2022

作者： Barriga, José A. Clemente, Pedro J. Quercus Software Engineering Group Department of Computer and Telematic Systems Engineering University of Extremadura Av. Universidad S/n Cáceres10003 Spain

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Enhancing Machine Learning Based Solar Generation Forecasting with Time Data Utilization

Enhancing Machine Learning Based Solar Generation Forecastin...

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2023 IEEE PES Generation, Transmission and Distribution International Conference and Exposition, GTD 2023

作者： Pasic, Lejla Pasic, Azra Pasic, Alija Vokony, Istvan Biro, Jozsef Budapest University of Technology and Economics Faculty of Electrical Engineering and Informatics Muegyetem rkp. 3 BudapestH-1111 Hungary Department of Telecommunications and Media Informatics Hungary Department of Electric Power Engineering Hungary ELKH-BME Information Systems Research Group 1117 Magyar Tudosok krt. 2 Budapest Hungary

ISBN: (纸本)9781728170251

Solar energy is expected to have a key role in the transition to a cleaner and environment-friendlier energy system, but given its highly weather dependent and intermittent nature, it creates operational challenges for the electric power grid because of the uncertainty involved in the output. Thus renewable energy generation forecasting becomes an increasingly important task in regard to not just the reliable operation of the energy system, but also from a financial standpoint. Here it is analyzed how the information carried by the timestamp can be utilized in order to improve solar generation forecasting accuracy. We devised and implemented our own time feature input, which we tested on several techniques based on machine learning for solar energy generation forecasting. In this paper, we demonstrate that, though often overlooked, the information carried by the timestamp is significant and can greatly improve the forecasting accuracy. © 2023 IEEE.

关键词： Forecasting

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B2A, A Straight-Through Approach from Basics to Advanced Level: Case Study for Python Course 11

B2A, A Straight-Through Approach from Basics to Advanced Lev...

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11th Workshop on software Quality Analysis, Monitoring, Improvement, and Applications, SQAMIA 2024

作者： Shazmeen, Abbasi Dakić, Pavle Zoltan, Alwahab Dhulfiqar Department of Programming Languages and Compilers Faculty of Informatics Eötvös Loránd University 1/C Pázmány Péter st. BudapestH-1117 Hungary Faculty of Informatics and Computing Singidunum University Danijelova 32 Belgrade Serbia Institute of Informatics Information Systems and Software Engineering Faculty of Informatics and Information Technologies Slovak University of Technology in Bratislava Ilkovičova 2 Bratislava842 16 Slovakia

In this study, we present a straightforward teaching strategy for teaching the Python programming language. Our method emphasizes a clear progression from fundamental to sophisticated concepts. Beginning with a thorough explanation of core Python ideas, we show a beginner-level script that dissects each line of code and displays the results. One distinguishing feature of our system is that students use ChatGPT to optimize code, which encourages them to improve the core program with fewer lines. After getting the updated solutions, students carefully compare the original and optimized programs to discover improvements and potential flaws. This study underlines the effectiveness of the Straight-Through Approach, which focuses on improving Python understanding while also developing critical thinking and code optimization skills. Our findings show that this strategy is a simple and effective way for teachers to assist students in growing from basic to advanced Python abilities, resulting in a dynamic and successful learning environment. The proposed technique will teach students how to use AI-driven modules correctly, such as ChatGPT. © 2024 Copyright for this paper by its authors.

关键词： Python

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