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Designing a Model for Predicting Asthma in Adolescent Using Map Reduce and Federated Learning

Designing a Model for Predicting Asthma in Adolescent Using ...

2024 International Conference on science, Engineering and Business for Driving Sustainable Development Goals, SEB4SDG 2024

作者： Ekpo, Raphael Henshaw Chukwudi Osamor, Victor Azeta, Ambrose A. Akindeji, Kayode Orelaja, Adeyinka Elizabeth Covenant University Department of Computer and Information Sciences Km 10 Idiroko Road Ogun State Ota Nigeria Namibia University of Science and Technology Department of Software Engineering Windhoek Namibia Durban University of Technology Faculty of Engineering and the Built Environment Department of Electrical Power Engineering South Africa Department of Computer Science and Quantitative Methods ClarksvilleTN United States

ISBN: (纸本)9798350358155

This study aims at designing Map Reduce and federated learning-based asthma prediction model for adolescent to provide answers to the problems associated with the existing asthma prediction model for adolescent. This study leveraged on two diverse datasets: the Nigerian Hospital Asthma dataset and the National Survey of Children Health dataset for benchmarking purposes. Symmetrical uncertainty and normalization interaction were employed for feature selection. The model was trained using Federated Artificial Intelligence (AI) Technology Enabler (FATE) and complemented with XGBoost model and one central server for federated algorithm averaging. The study was implemented with python programming language on Google Collaboratory environment. The results of the analysis showed considerable high accuracy of 0.98, precision (0.98%), recall (0.98%) and F1-socre (0.99%) for the asthmatic class and precision of 0.98%, recall of 0.98%, as well as F1-score of 0.99% for the non-asthmatic class. The implemented model was benchmark with the existing asthma prediction models in the literature. Simulated attack was also performed using implemented model with and without Map Reduce. This study concludes that the researchers' model has the potentials to outperform some of the existing machine learning models on asthma prediction in adolescent, thereby facilitating collaborative sharing of the model with other hospitals, protect the patient information from leakage, meeting the criteria of healthcare data protection regulation as well as beneficial for enhancing the security of the dataset. © 2024 IEEE.

关键词： Federated learning

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Unlocking the power of blockchain in education:An overview of innovations and outcomes

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Blockchain(Research and Applications) 2023年第4期4卷 99-117页

作者： Amr El Koshiry Entesar Eliwa Tarek Abd El-Hafeez Mahmoud Y.Shams Department of Curricula and Teaching Methods College of EducationKing Faisal UniversityAl-Ahsa31982Saudi Arabia Faculty of Specific Education Minia UniversityMinia61519Egypt Department of Mathematics and Statistics College of ScienceKing Faisal UniversityAl-Ahsa31982Saudi Arabia Department of Computer Science Faculty of ScienceMinia UniversityMinia61519Egypt Computer Science Unit Deraya UniversityMinia UniversityMinia61519Egypt Faculty of Artificial Intelligence Kafrelsheikh UniversityKafrelsheikh33516Egypt

Blockchain is a revolutionary technology that has the potential to revolutionize various industries,including finance,supply chain management,healthcare,and *** decentralized,secure,and transparent nature makes it ideal for use in industries where trust,security,and efficiency are of paramount *** integration of blockchain technology into the education system has the potential to greatly improve the efficiency,security,and credibility of the educational *** creating secure and transparent platforms for tracking and verifying students’academic achievements,blockchain technology can help to create a more accessible and trustworthy education system,making it easier for students to showcase their skills and knowledge to potential *** the potential benefits of blockchain in education are significant,there are also several challenges that must be addressed in order to fully realize the potential of this technology in the educational *** of the major challenges include adoption,technical knowledge,interoperability,regulation,cost,data privacy and security,scalability,and *** necessary equipment for the implementation of blockchain technology in education is diverse and critical to the success of this innovative *** should carefully consider this equipment when planning their implementation of blockchain technology in education to ensure the efficient and secure transfer of educational data and transactions within the blockchain *** technology has the potential to play a significant role in promoting sustainability education and advancing the sustainability goals of both individuals and *** should consider incorporating blockchain technology into their sustainability education programs,in order to enhance the transparency,verifiability,and efficiency of their sustainability-related *** the use of blockchain technology in education is still i

关键词： Blockchain Education Sustainability Internet of things Machine learning Credential verification

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Heuristic Algorithm for Solving Travelling Salesman Problem: Adding the Endpoints of the Longest Edges 5

Heuristic Algorithm for Solving Travelling Salesman Problem:...

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5th International Conference on Problems of Cybernetics and Informatics, PCI 2023

作者： Nuriyeva, Fidan Dokuz Eylul University Department of Computer Science Izmir Turkey Institute of Control Systems Laboratory of Recognition Identification and Methods of Optimal Solutions Baku Azerbaijan

ISBN: (纸本)9798350319064

This study proposes, a new heuristic algorithm based on insertion heuristic to solve the symmetric Travelling Salesman Problem. In the proposed algorithm, firstly the two longest edges are selected and the starting tour passing through their endpoints is constructed, then the endpoints of the next longest edges are added to this tour and the solution passing through all the vertices is found. This problem is known to be NP-Hard. The proposed method was successfully tested on different-sized problems. The experimental results show that the proposed algorithm outperforms many existing methods. © 2023 IEEE.

关键词： Traveling salesman problem

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Chaos-Based Novel Watermarked Satellite Image Encryption Scheme

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computer Modeling in Engineering & sciences 2025年第4期143卷 1049-1070页

作者： Mohamed Medani Yahia Said Nashwan Adnan Othman Farrukh Yuldashev Mohamed Kchaou Faisal Khaled Aldawood Bacha Rehman Applied College of Muhayil Aseer King Khalid UniversityAbha62529Saudi Arabia Center for Scientific Research and Entrepreneurship Northern Border UniversityArar73213Saudi Arabia Department of Computer Engineering College of EngineeringKnowledge UniversityErbil44001Iraq Department of Computer Engineering Al-Kitab UniversityAltun Kupri36001Iraq Department of Informatics and Its Teaching Methods Tashkent State Pedagogical UniversityTashkent100070Uzbekistan Department of Industrial Engineering College of EngineeringUniversity of BishaBishaP.O.Box 001Saudi Arabia Department of Computer Science Solent UniversitySouthamptonSO140YNUK

Satellite images are widely used for remote sensing and defence applications,however,they are subject to a variety of *** ensure the security and privacy of these images,theymust be watermarked and encrypted before ***,this paper proposes a novel watermarked satellite image encryption scheme based on chaos,Deoxyribonucleic Acid(DNA)sequence,and hash *** watermark image,DNA sequence,and plaintext image are passed through the Secure Hash Algorithm(SHA-512)to compute the initial condition(keys)for the Tangent-Delay Ellipse Reflecting Cavity Map(TD-ERCS),Henon,and Duffing chaotic maps,*** bitwise XOR and substitution,the TD-ERCS map encrypts the watermark *** ciphered watermark image is embedded in the plaintext *** embedded plaintext image is permuted row-wise and column-wise using the Henon chaotic *** permuted image is then bitwise XORed with the values obtained from the Duffing *** additional security,the XORed image is substituted through a dynamic *** evaluate the efficiency and performance of the proposed algorithm,several tests are performed which prove its resistance to various types of attacks such as brute-force and statistical attacks.

关键词： DNA sequence TD-ERCS chaoticmap henon chaoticmap duffing chaotic system SHA-512 encryption technique watermark embedding

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Autoencoder Neural Networks for Anomaly Detection in Wind Turbines 19th

Autoencoder Neural Networks for Anomaly Detection in Wind Tu...

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19th International Conference on Soft Computing Models in Industrial and Environmental Applications, SOCO 2024

作者： Coronel, D. Guevara, C. Santos, M. Computer Science Faculty Complutense University of Madrid Madrid28040 Spain Quantitative Methods Department CUNEF University Madrid28040 Spain Institute of Knowledge Technology Complutense University of Madrid Madrid28040 Spain

ISBN: (纸本)9783031750090

Wind energy has emerged as a crucial solution in the search for sustainable and environmentally friendly energy sources. As global energy demand grows rapidly and the need to reduce greenhouse gas emissions increases, wind turbines have become a key technology for the transition to a cleaner and more sustainable energy future. This paper focuses on the application of autoencoder neural networks for the accurate and efficient detection of anomalies in wind turbines. The main objective is to significantly improve monitoring and predictive maintenance of wind turbines and thus enhance wind energy availability. The dataset used includes records of wind turbines with both, healthy and faulty conditions. Healthy records serve as a baseline to illustrate the expected amplitude of the turbine vibrations under optimal operation conditions. In contrast, failure records arising from blade surface erosion, blade unbalanced, and blade twist are used to evaluate the failure detection model. The proposed algorithm demonstrates a precision of 95.42% for blade unbalanced failures, 94.63% for blade surface erosion, and 87.54% for blade twist faults. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： Windmill

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Online learning of computer science to schoolchildren using interactive educational posters 1

Online learning of computer science to schoolchildren using ...

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1st International Conference on Technology Enhanced Learning in Higher Education, TELE 2021

作者： Kulikova, Natalia Y. Danilchuk, Elena V. Sergeev, Alexey N. Lukicheva, Anna V. Volgograd State Social-Pedagogical University Department of Computer Science and Methods of Teaching Computer Science Volgograd Russia Department of Computer Science and Methods of Teaching Computer Science Russia Municipal Educational Institution Volgograd Russia

ISBN: (纸本)9781665443968

This article deals with questions of organization online schoolchildren training using interactive posters as multidimensional didactic tools for a computer science teacher. The concept of 'interactive posters' discusses and shows their important role for activating and managing the activities of schoolchildren in full-time and remote forms of interaction. We are considering the design and development of interactive posters on the web platform with the specifics of training in informatics and overcoming the problems of modern schoolchildren related to clip thinking. © 2021 IEEE.

关键词： Personnel training

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SP-DSTS-MIMO Scheme-Aided H.266 for Reliable High Data Rate Mobile Video Communication

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computers, Materials & Continua 2023年第1期74卷 995-1010页

作者： Khadem Ullah Nasru Minallah Durre Nayab Ishtiaque Ahmed Jaroslav Frnda Jan Nedoma Department of Computer Systems Engineering University of Engineering and Technology PeshawarPeshawar25000Pakistan National Centre in Big Data and Cloud Computing University of Engineering and Technology Peshawar(NCBC-UETP)Peshawar25000Pakistan Department of Quantitative Methods and Economic Informatics Faculty of Operation and Economics of Transport and CommunicationsUniversity of Zilina01026ZilinaSlovakia Department of Telecommunications Faculty of Electrical Engineering and Computer ScienceVSB-Technical University of OstravaOstrava-PorubaCzech Republic

With the ever growth of Internet users,video applications,and massive data traffic across the network,there is a higher need for reliable bandwidth-efficient multimedia *** Video Coding(VVC/H.266)is finalized in September 2020 providing significantly greater compression efficiency compared to Highest Efficient Video Coding(HEVC)while providing versatile effective use for Ultra-High Definition(HD)*** article analyzes the quality performance of convolutional codes,turbo codes and self-concatenated convolutional(SCC)codes based on performance metrics for reliable future video *** advent of turbo codes was a significant achievement ever in the era of wireless communication approaching nearly the Shannon *** codes are operated by the deployment of an interleaver between two Recursive Systematic Convolutional(RSC)encoders in a parallel *** RSC encoders may be operating on the same or different architectures and code *** proposed work utilizes the latest source compression standards H.266 and H.265 encoded standards and Sphere Packing modulation aided differential Space Time Spreading(SP-DSTS)for video transmission in order to provide bandwidth-efficient wireless video ***,simulation results show that turbo codes defeat convolutional codes with an averaged E_(b)/N_(0) gain of 1.5 dB while convolutional codes outperformcompared to SCC codes with an E_(b)/N_(0) gain of 3.5 dBatBit ErrorRate(BER)of 10−*** Peak Signal to Noise Ratio(PSNR)results of convolutional codes with the latest source coding standard of H.266 is plotted against convolutional codes with H.265 and it was concluded H.266 outperform with about 6 dB PSNR gain at E_(b)/N_(0) value of 4.5 dB.

关键词： H.265 RSC turbo codes SCC SP-DSTS BP-CNN BER PSNR

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Current Trends in Artificial Intelligence for Educational Advancements

Current Trends in Artificial Intelligence for Educational Ad...

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2024 International Conference on Decision Aid sciences and Applications, DASA 2024

作者： Al-Tarawneh, Abdallah M. A. Alomoush, Reem Abdelkareem Ul Islam, Tanveer Janjua, Jamshaid Iqbal Abbas, Tahir Ihsan, Anaum Al-Ahliyya Amman University Clinical Psychology Amman Jordan Yarmouk University Faculty of Educational Sciences Department of Curricula and Methods of Teaching Jordan TIMES Institute Department of Computer Science Multan60000 Pakistan Lahore Pakistan

ISBN: (纸本)9798350369106

The focus of this paper is the integration of artificial intelligence (AI) within the educational field including but not limited to, adaptive learning, teaching evaluation, online learning environments, and individualized instruction. The authors investigate the positive role of AI in enhancing teaching performance and the quality of students' learning experiences. The study aims to demonstrate what role AI may play in the course of education development and practice improvement. It also sheds light on the limitations AI will have in the realm of education, such as accessibility, data ownership, and ethical issues. The paper does not contain only the limitations but the opportunities for this technology as well and describes how AI could be effectively incorporated into education, subsequently providing insights into the evolution of AI-based educational transformation. © 2024 IEEE.

关键词： Federated learning

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A Strategy for Retrospective Evaluation of Students SQL Learning Engagements

A Strategy for Retrospective Evaluation of Students SQL Lear...

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2023 International Conference on Electrical, computer, Communications and Mechatronics Engineering, ICECCME 2023

作者： Obionwu, Chukwuka Victor Oji Kalu, Kalu Blockhaus, Paul Broneske, David Saake, Gunter Otto-von-Guericke University Faculty of Computer Science Magdeburg Germany German Centre for Higher Education Research and Science Studies Research Infrastructure and Methods Department Lower Saxony Hannover Germany

ISBN: (纸本)9798350322972

The adoption of e-learning pedagogy in educational institutions has become increasingly prevalent, and it has proffered solutions to notable deficiencies that existed in the traditional learning pedagogy. However, it has also opened up new sets of challenges. One such challenge is the management of the huge amounts of data generated by students in the course of their daily interaction with various e-learning subsystems. Furthermore, as these systems are mostly online assessment systems, In-depth evaluation of student's interaction is mostly coarse, and a strategy for retrospective evaluation of students' interaction data for improved knowledge acquisition is mostly lacking. In our own peculiar scenario, an understanding of the challenges experienced by students in their pursuit of Structured Query Language knowledge acquisition was necessary. A strategy we adopted to tackle the challenge of gaining retrospective insight into student's learning engagements is the use of error codes, and a real-time analytics. Thus, we are able to understand the extent to which our teaching strategy is effective against reducing stress resulting in exercise task engagement, and other learning challenges that may affect knowledge acquisition by individual students in the course of their learning interactions. We show that the error code strategy is an effective indicator for tracking, and intervening on student's Structured Query Language (SQL) based learning interactions. Our evaluation further showed that syntax errors are the most prevalent type of error encountered by students learning SQL. © 2023 IEEE.

关键词： Students

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Transformative Applications and Key Challenges of Generative AI 7

Transformative Applications and Key Challenges of Generative...

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7th IEEE International Conference and Workshop Obuda on Electrical and Power Engineering, CANDO-EPE 2024

作者： Kovari, Attila Katona, Jozsef Eszterházy Károly Catholic University Institute of Digital Technology Faculty of Computer Science Eger Hungary University of Dunaújváros Department of Institute of Engineering Dunaujvaros Hungary John Von Neumann University GAMF Faculty of Engineering and Computer Science Kecskemét Hungary Institute of Computer Engineering University of Dunaujvaros Department of Software Development and Application Dunaujvaros Hungary Budapest Business University Faculty of Finance and Accountancy Department of Applied Quantitative Methods Budapest Hungary

ISBN: (纸本)9798331531119

The paper discusses the integration and use of generative artificial intelligence technologies in education. Generative AI, such as OpenAI, in particular the GPT model, has fundamentally changed the way humans interact with machines. Advanced technologies in the field of generative AI in education are mostly used to personalize learning experiences by dynamically customizing learning materials according to the needs of learners, thus enabling the improvement of outcomes. This article explores the use of generative AI tools with the aim of assessing how useful students perceive these tools to be. The findings show mixed receptivity from users, highlighting the critical balance in using innovative AI capabilities through AI. © 2024 IEEE.

关键词： Generative adversarial networks

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