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检索条件"任意字段=12th International Conference on Knowledge-Based Intelligent Information and Engineering Systems"

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25th international conference on intelligent Data engineering and Automated Learning, IDEAL 2024

25th International Conference on Intelligent Data Engineerin...

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25th international conference on intelligent Data engineering and Automated Learning, IDEAL 2024

ISBN: (纸本)9783031777370

the proceedings contain 92 papers. the special focus in this conference is on intelligent Data engineering and Automated Learning. the topics include: Model-based Meta-reinforcement Learning for Hyperparameter Optimization;towards Sustainable Precision: Machine Learning for Laser Micromachining Optimization;association Rules Mining with Auto-encoders;using Contrastive Learning to Map Stylistic Similarities in Narrative Writers;automatic Classification of Signal and Noise in Functional Magnetic Resonance Imaging Scans Using Convolutional Neural Networks;how Resilient are Language Models to Text Perturbations?;emotional Sequential Influence Modeling on False information;CSSDH: An Ontology for Social Determinants of Health to Operational Continuity of Care Data Interoperability;padel Two-Dimensional Tracking Extraction from Monocular Video Recordings;drowsiness Detection Using Vital Sign Sensors and Deep Learning on Smartwatches;Benchmarking Out of the Box Open-Source LLMs for Malware Detection based on API Calls Sequences;multimodal Visio-Lingual Content Analysis to Detect Fake Content on Reddit;MetaLIRS: Meta-learning for Imputation and Regression Selection;pipeline for Semantic Segmentation of Large Railway Point Clouds;preliminary Investigation on Machine Learning and Deep Learning Models for Change of Direction Classification in Running;efficient Radar Scheduling Using Genetic Algorithms and Stochastic Heuristic Initialization;towards a Communication Specification Language for Heterogeneous Service Orchestration based on Process Calculus and Holonic Multi-agent systems;counterfactual Explanations for Sustainable Tourism Indicators;Tracking Healthy Organs in Medical Scans to Improve Cancer Treatment by Using UW-Madison GI Tract Image Segmentation;low Consumption Models for Disease Diagnosis in Isolated Farms;fast and Scalable Recommendation Retrieval Model with Mixed Attention and knowledge Distillation;Federated Learning for Vietnamese SMS Spam Detection Using Pre

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25th international conference on intelligent Data engineering and Automated Learning, IDEAL 2024

25th International Conference on Intelligent Data Engineerin...

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25th international conference on intelligent Data engineering and Automated Learning, IDEAL 2024

ISBN: (纸本)9783031777301

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An Assessment of the Machine Learning-based Intellectual Plant Identification and Categorization System Using IoT 12th

An Assessment of the Machine Learning-Based Intellectual Pla...

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12th international conference on Frontiers of intelligent Computing: theory and Applications, FICTA 2024

作者： Kumar, E. Mamatha, B. Murali, Kanthi Lavanya, G. Jyothi, K. Bharat, H. Swaraj Department of CSE CMR Engineering College Telangana Hyderabad India CMR Technical Campus Telangana Hyderabad India Department of CSE CMR Technical Campus Telangana Hyderabad India Department of CSE CMR College of Engineering and Technology Telangana Hyderabad India CMR College of Engineering and Technology Telangana Hyderabad India

ISBN: (纸本)9789819601424

the main component of a plant is water. Consequently, a plant’s ability to grow is greatly impacted by changes in its water content. Visual identification of items is a relatively easy talent for a human. Still, computer-based picture recognition is a difficult task. More recently, developments in machine learning have led to strong detection and classification methods that perform well in challenging contexts. based on plant recognition and classification, this work proposes a machine learning-based intelligent agricultural architecture. the goal of this project is to organize and expand an intelligent framework that takes machine vision and support vector machines (SVM) into account in order to improve plant development in a regional water scenario. For item recognition in the context of smart agriculture, the approach leverages a strong deep learning-based architecture. this design describes a technique for image identification that focuses on automatically recognizing plants and flowers. It looks for, locates, and classifies disease in leaves and fruit automatically. It then contours the exact site of harm for viewing. the aforementioned mobile iOS application can achieve improved accuracy by employing the SVM as a classification tool with high accuracy for plant conditions, according to the results. © the Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Adversarial machine learning

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A Scrutiny of AES-based Image Encryption and Decryption for Fraudulent Data Security and Defense Against Intrusion Attacks 12th

A Scrutiny of AES-Based Image Encryption and Decryption for ...

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12th international conference on Frontiers of intelligent Computing: theory and Applications, FICTA 2024

作者： Nayak, Himanshu Pravalika, G. Maheswari, K. Pavan, G. Tulasi, P. Pavani, M. CMR Engineering College Telangana Hyderabad India Department of Electronics and Communication Engineering CMR Engineering College Telangana Hyderabad India Department of Computer Science and Engineering CMR Technical Campus Telangana Hyderabad India CMR Technical Campus Telangana Hyderabad India Department of Computer Science and Engineering CMR College of Engineering and Technology Telangana Hyderabad India CMR College of Engineering and Technology Telangana Hyderabad India

ISBN: (纸本)9789819601387

Image data are becoming the most common type of information sent over networks, thanks to advancements in information technology. the advancement of picture encryption technology is occurring concurrently with the growth of photographic data theft technologies. In order to stay up with the growing array of methods used for information theft, we must investigate more robust image encryption strategies. information can now be transmitted quickly and reliably because of advancements in communication technology, which has increased its application across a range of industries, including business, science, the military, and the civilian sector. In computer science, cryptography is the process of transforming readable data, such as plain text, into an encrypted form which can only be decoded by another party with the decryption key. It strengthens security and aids in safeguarding private and sensitive data. Encryption and decryption safeguard data against loss, alteration, or compromise. Numerous technologies, including RSA, BLOW FISH, DES, TRIPLE DES, genetic algorithms, and chaotic maps, have been created. For generations, the security of data has also grown in importance. this solution suggested employing AES (Advanced Encryption Standard) technology for image encryption and decryption in order to address these issues. this technique guarantees secrecy, integrity, and authentication. these methods aid in preventing intrusion attempts. © the Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Network intrusion

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Impact of COVID-19 on Supply Chain Performance: A Case of Civil Railway Construction Projects 16

Impact of COVID-19 on Supply Chain Performance: A Case of Ci...

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16th international conference on ENTERprise information systems, CENTERIS 2024 - 12th international conference on Project MANagement, ProjMAN 2024 - 14th international conference on Health and Social Care information systems and Technologies, HCist 2024

作者： Klingsad, Rada Na Ayudhya, Borvorn Israngkura Civil Engineering Department Rajamangala University of Technology Thanyaburi 12110 Thailand

the COVID-19 pandemic has impacted global supply chains. the pandemic caused an unprecedented crisis in the construction industry, particularly, the material and service supply disruption delaying construction projects. this paper investigated the impact of the pandemic on the supply chain in civil railway projects that owners, contractors, and sub-contractors faced. Authors presented twenty-Two identified factors that have impacted to performance of supplying materials and services to civil railway work projects. these identified factors were based on literature reviews and discussions with experts. the results of 120 questionnaires were analyzed. the Relative Important Index (RII) method was applied to rank and analyze the degree of seriousness of identified factors. the results indicated that material-related delivery jobs were the most affected jobs, followed by labor and technical & equipment-related delivery jobs. the results also showed that the impact of the COVID-19 pandemic caused the unavailability of suppliers, lack of access to equipment, delays in delivery, high cost of materials, and delays in payment to the supply chain in civil railway work projects. this study provided valuable insights into the challenges faced by the civil railway industry during the pandemic. It could potentially help stakeholders devise strategies to mitigate such issues in the future. © 2025 the Author(s).

关键词： Construction industry

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Transformer Models in Education: Summarizing Science Textbooks with AraBART, MT5, AraT5, and mBART 1st

Transformer Models in Education: Summarizing Science Textboo...

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1st international conference on intelligent systems, Blockchain, and Communication Technologies, ISBCom 2024

作者： Masri, Sari Raddad, Yaqeen Khandaqji, Fidaa Ashqar, Huthaifa I. Elhenawy, Mohammed Department of Natural Engineering and Technology Sciences Arab American University P.O. Box 240 Ramallah Palestine Civil Engineering Department Arab American University P.O. Box 240 Jenin Palestine Columbia University New YorkNY United States CARRS-Q Queensland University of Technology Brisbane Australia Centre for Data Science Queensland University of Technology Brisbane Australia

ISBN: (纸本)9783031823763

In an era of rapidly expanding digital archives, effective text summarization tools are crucial for educators and learners. this study presents an advanced text summarization system specifically designed for Arabic textbooks, leveraging state-of-the-art natural language processing (NLP) models. We trained and evaluated four models - AraBART, mBART50, AraT5, and MT5 - on biology textbook content for 11th and 12th grades in the Palestinian curriculum using the ROUGE metric to compare their performance. Our results show that AraBART and mBART50 outperformed the other models in terms of ROUGE-1 (score: 0.24), ROUGE-2 (score: 0.118–0.139) and ROUGE-L (score: 0.24), indicating their effectiveness in summarizing complex biological information while preserving essential details. To further validate the performance of these models, we conducted a subjective evaluation by an educational expert who assessed the summaries for their accuracy, relevance, and overall quality, with AraBART ranking highest due to its ability to capture key concepts and reduce noise in the original text. the study’s findings provide valuable insights into the performance of these models and contribute to the development of effective tools for understanding and generating Arabic text. © the Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： Natural language processing systems

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Neural Networks and Explainable Artificial Intelligence for Breast Cancer Prediction and Classification 16

Neural Networks and Explainable Artificial Intelligence for ...

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作者： Yahata, Erika Santos, Pablo Deoclecia Dos De Souza Pires, Maria Marlene Suyama, Ricardo Simoes, Priscyla Waleska Graduate Program in Information Engineering Federal University of ABC SP Santo André Brazil Graduate Program in Biomedical Engineering Federal University of ABC São Bernardo Do Campo Brazil Pediatrics Department Federal University of Santa Catarina Santa Catarina Brazil

Solutions based on Artificial Intelligence techniques have been proposed in the healthcare sector, however the lack of understanding of the results has been a cause for concern and one of the main barriers to their effective use. To fill the gap in understanding these models considered black boxes, the Explainable Artificial Intelligence was proposed to explain the relationship between input data and the prediction results made by the Artificial Intelligence models. In this study, we present the use of explainability techniques for a black box machine learning model in breast cancer classification. Breast cancer is the type of cancer that causes the most deaths among women in the world and early diagnosis is essential to increase the chances of survival. the study evaluated the explainability of breast tumor predictions based on the Multilayer Perceptron artificial neural networks algorithm, considering a sample that contained data from 164 female patients undergoing Core Biopsy in the southern region of Brazil. the SHAP, LIME, PDP and ICE methods were used for the global and local explainability of the predictions. the results showed that in the global assessment, the BI-RADS® 5 ultrasound and mammography attributes were considered the most important for predicting the malignant tumor. Nodule size greater than 2 cm, presence of a family history and palpable nodule were also considered important for the prediction. In the local evaluation, it was found that the model correctly classified the tumors considering different characteristics of the patients. through the results presented, the methods of explicability show evidence that the predictive model for breast cancer can be interpreted and understood, overcoming the barrier of lack understanding of the results of a black box model. © 2025 Elsevier B.V.. All rights reserved.

关键词： Prediction models

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ICAIW 2022 - Joint Proceedings of the 5th international conference on Applied Informatics Workshops: 3rd international Workshop on Applied Artificial Intelligence, WAAI 2022, 4th international Workshop on Applied Informatics for Economy, Society, and Development, AIESD 2022, 5th international Workshop on Data engineering and Analytics, WDEA 2022, 1st international Workshop on intelligent Transportation systems and Smart Mobility Technology, WITS 2022, 2nd international Workshop on knowledge Management and information Technologies, WKMIT 2022 and 1st international Workshop on systems Modeling, WSSC 2022, co-located with the 5th international conference on Applied Informatics, ICAI 2022

ICAIW 2022 - Joint Proceedings of the 5th International Conf...

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Joint 5th international conference on Applied Informatics Workshops, ICAIW 2022: 3rd international Workshop on Applied Artificial Intelligence, WAAI 2022, 4th international Workshop on Applied Informatics for Economy, Society, and Development, AIESD 2022, 5th international Workshop on Data engineering and Analytics, WDEA 2022, 1st international Workshop on intelligent Transportation systems and Smart Mobility Technology, WITS 2022, 2nd international Workshop on knowledge Management and information Technologies, WKMIT 2022 and 1st international Workshop on systems Modeling, WSSC 2022

the proceedings contain 24 papers. the topics discussed include: analysis on early dropouts in engineering careers;depression diagnosis using text-based AI methods – a systematic review;satellite orbit prediction using a machine learning approach;bibliometric software: the most commonly used in research;bio-business of polymer derived from cassava waste for the industrial plastic sector;dynamic models to determine external factors and their impact on the shrimp price forecast;how to use Instagram to travel the world? an approach to discovering relevant insights from tourist media content;public safety perception in Ecuador: an approach from social networks over data analytics;relationship between corporate social responsibility, assets and income of companies in Ecuador;retrospective of scientific production on e-democracy;sticky floor and glass ceiling in Ecuador. the evolution of the gender wage gap, 2010-2021;and technical indicator for a better intraday understanding of uptrends or downtrends in the financial markets using volume transactions as a trigger.

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Analysing the Behaviour of an Intrusion Detection System Hybrid Model based on a Random Forest Algorithm 12th

Analysing the Behaviour of an Intrusion Detection System Hyb...

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12th international conference on Frontiers of intelligent Computing: theory and Applications, FICTA 2024

作者： Navanitha, Dubbaka Ramasamy, M. Siva Jyothi, Modugula Patra, Raj Kumar Sujani, B. Naga Kavya Kalyani, M. Department of CSE CMR Engineering College Telangana Hyderabad India CMR Engineering College Telangana Hyderabad India Department of IT CMR Technical Campus Telangana Hyderabad India Department of CSE CMR Technical Campus Telangana Hyderabad India CMR College of Engineering and Technology Telangana Hyderabad India Department of CSE CMR College of Engineering and Technology Telangana Hyderabad India

ISBN: (纸本)9789819601424

the damage they cause is what makes malicious threats more well-known. these damages could also result in serious information loss;they are not merely restricted to the system. Furthermore, threats are also accountable for monetary losses. threat kinds and assaults also grow in tandem with technology. Despite the fact that the academic community has looked into a variety of preventive cyber-attack models, it can be difficult for enterprises to identify threats and stop them from accessing data. In businesses, using IDS for attack detection is ubiquitous and well-liked. In the domain of anomaly and attack detection, information mining and hybrid techniques are becoming more and more important in conjunction with IDS these days. In this research, we concentrate on developing an intrusion detection tool that provides data safety and security, utilizing a signature method and the random forest algorithm. Each of the two algorithms functions independently for the IDS system, yet the signature base technique has certain recognized database requirement constraints. In our research article, we presented a hybrid attack detection model that combines a behaviour-based algorithm with a signature-based approach to enable double filtration of intrusions in an application within a single system. this essay discusses the varied threat characteristics, behaviours, and modes of operation. Additional intrusion detection in the hybrid model is an expansion of the basic individual model that focuses on a single signature or performance. © the Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Network intrusion

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Development of the Decision systems for Cloud Security based on AI and ML 12th

Development of the Decision Systems for Cloud Security Based...

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12th international conference on Frontiers of intelligent Computing: theory and Applications, FICTA 2024

作者： Maral, Vikas Balasaheb Tambakhe, Manoj D. Dhage, Prashant Shukla, Jyoti Khalaf, Osamah Ibrahim Pise, Ganesh Shivaji Vishwakarma Institute of Information Technology Maharashtra Pune India Department of Information Technology Sipna College of Engineering and Technology Amravati Maharashtra Amravati India Pune India Department of Computer Science and Engineering Arya College of Engineering Jaipur India Department of Solar Al-Nahrain Research Center for Renewable Energy Al-Nahrain University Jadriya Baghdad Iraq Department of Information Technology PICT Maharashtra Pune India

ISBN: (纸本)9789819601387

One of the most important and crucial factors often considered in keeping a network secure is the adoption of an intrusion detection system. this process is commonly called as an IDS stage which is required to keep the network protected from certain attacks in real time. Due to the wide usage of cloud on a daily purpose, the platform is constantly evolving and becoming more advanced. this has helped the developers comprehend the necessity of advancing the process of IDS. However, there are certain obstacles and issues that might arise with its acceptance. One such factor is the problem of overhead. this problem of overhead occurs when the cloud server is overloaded with existing services and thereby cannot transit other services on urgency. In such a scenario, the working concept of an IDS comes into picture wherein this adaptive design helps the developers to overcome such issues and provide a conventional flow of services to the allocate resource. the primary purpose of the presented research paper is to adapt such a concept and therefore maximize the overall potential of the system. the author of the research paper also tends to enhance and increase the overall capacity required to identify the occurrence of such threats in an online manner which are expected to occur. A CICIDS2017 dataset is used to fulfill the purpose of the same and a recurring infrastructure is therefore built in order to understand the working nature of an intrusion detection system. © the Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Network intrusion

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