An association rule-based approach for frequent item mining of multi-stage access data by Silong Wu

“…Therefore, a multi-stage frequent item mining method for accessing data based on association rules is proposed. By applying the concepts of clustering analysis and Boolean vector operation, the Apriori algorithm for association rules is improved. …”
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Data Mining Techniques for Early Detection and Classification of Plant Diseases: An Optimization-Based Approach by Wagh Swapnil, Sharma Ruchi

“…Besides, this research aims to investigate the feasibility that employs data mining framework together with optimization algorithms as approaches towards plant diseases identification and categorization systems. …”
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A new hybrid filter for NDVI time series reconstruction and data quality enhancement by Agus Suprijanto, Yumin Tan, Syed Mohammad Masum, Rodolfo Domingo Moreno Santillan

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Cyberattack Detection Systems in Industrial Internet of Things (IIoT) Networks in Big Data Environments by Abdullah Orman

“…The rapid expansion of the Industrial Internet of Things (IIoT) has revolutionized industrial automation and introduced significant cybersecurity challenges, particularly for supervisory control and data acquisition (SCADA) systems. Traditional intrusion detection systems (IDSs) often struggle to effectively identify and mitigate complex cyberthreats, such as denial-of-service (DoS) and distributed denial-of-service (DDoS) attacks. …”
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Multi-point estimation weldment recognition and estimation of pose with data-driven robotics design by Meng XiangYi

“…The proposed MPEE model computes the multi-point in the weldment design with the data-driven model for the estimation of the welding points. …”
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DAugSindhi: a data augmentation approach for enhancing Sindhi language text classification by Raja Vavekanand, Bhagwan Das, Teerath Kumar

“…This paper presents DAugSindhi, a study focused on enhancing Sindhi text classification through data augmentation techniques. These methods aim to address data scarcity by artificially expanding the dataset to improve model performance. …”
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A Data-Driven Comparative Analysis of Machine-Learning Models for Familial Hypercholesterolemia Detection by Tomasz Kocejko

“…The initial dataset comprised over 100 parameters per patient, which was reduced to 48 clinically accessible features to ensure applicability in routine outpatient settings. To preserve balance, the data were stratified according to DLCN score ranges (<0–2>, <3–5>, <6–8>, and ≥9), representing varying levels of FH likelihood. …”
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Handling data sparsity via item metadata embedding into deep collaborative recommender system by Gopal Behera, Neeta Nain

“…However, MF cannot handle the nonlinearity among the data. Deep learning is an advanced learning technique that has shown success in many applications such as image classification, computer vision, natural language processing, etc. …”
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Development and validation of an AI-enabled oral score using large-scale dental data by Sri Kalyan Yarlagadda, Navid Samavati, Mina Ghorbanifarajzadeh, Vlada Levinta, Alireza Sojoudi, Wardah Inam, Teresa A. Dolan

“…The OS-B score aims to address limitations in prior oral health scoring systems by incorporating nuanced clinical data accounting for disease severity, and providing a scalable, data-driven approach to measuring oral health. …”
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A CNN-transformer framework for emotion recognition in code-mixed English–Hindi data by Shreya Patankar, Madhura Phadke

“…Abstract Social media is an open platform for users to express their views and thoughts through emotions about a particular topic in natural language, leading to the generation of a vast amount of emotional data on micro-blogging sites. This data needs to be processed to extract meaningful insights and analyze emotions from text, enhancing various Natural Language Processing (NLP) applications. …”
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Secure data transmission through fractal-based cryptosystem: a Noor iteration approach by Deepak Negi, Rajiv Kumar, Vijay Kumar, Arvind Dhaka

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A comprehensive survey on secure healthcare data processing with homomorphic encryption: attacks and defenses by Chian Hui Lee, King Hann Lim, Sivaraman Eswaran

“…Abstract Healthcare data has risen as a top target for cyberattacks due to the rich amount of sensitive patient information. …”
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Geological object recognition in legacy maps through data augmentation and transfer learning techniques by Wenjia Li, Weilin Chen, Jiyin Zhang, Chenhao Li, Xiaogang Ma

“…Legend data from geological maps offer standardized symbols and annotations. …”
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Introducing MagBERT: A language model for magnesium textual data mining and analysis by Surjeet Kumar, Russlan Jaafreh, Nirpendra Singh, Kotiba Hamad, Dae Ho Yoon

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Deep learning model for patient emotion recognition using EEG-tNIRS data by Mohan Raparthi, Nischay Reddy Mitta, Vinay Kumar Dunka, Sowmya Gudekota, Sandeep Pushyamitra Pattyam, Venkata Siva Prakash Nimmagadda

“…This study presents a novel approach that integrates electroencephalogram (EEG) and functional near-infrared spectroscopy (tNIRS) data to enhance emotion classification accuracy. …”
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An Igneous Rock Lithology Identification Method Based on Data-Algorithm Bidirectional-Driven Framework by HAN Ruiyi, SONG Xiaoni, WANG Xinru, GUO Yuhang

“…To address these challenges, this study proposes a Data-Algorithm Bidirectional-Driven Framework (DABDF) for igneous lithology identification. …”
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Architecture and optimization of data mining modeling for visualization of knowledge extraction: Patient safety care by Gebeyehu Belay Gebremeskel, Birhanu Hailu, Belete Biazen

“…The finding showed a deep understandability for an advanced and dynamic data mining modeling techniques to integrate applications with domain contexts for the optimal and understandable decision process. …”
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Data-Driven Battery Remaining Life Prediction Based on ResNet with GA Optimization by Jixiang Zhou, Weijian Huang, Haiyan Dai, Chuang Wang, Yuhua Zhong

“…As lithium batteries are widely used in mobile electronic devices and electric vehicles, accurately assessing the Remaining Useful Life (RUL) of lithium-ion batteries is crucial to ensure the stable operation of the devices, improve energy efficiency, and safeguard user safety. Although data-driven methods show good prediction potential without the need to understand the reaction mechanism inside the battery, they face the problems of high data demand and feature redundancy that may reduce the model learning accuracy in practical applications. …”
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A Semantically Enhanced Label Prediction Method for Imbalanced POI Data Category Distribution by Hongwei Zhang, Qingyun Du, Shuai Zhang, Renfei Yang

“…POI data play an important role in various location-based services, including navigation, positioning, and local search applications. …”
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Federated Learning for Human Pose Estimation on Non-IID Data via Gradient Coordination by Peng Ni, Dan Xiang, Dawei Jiang, Jianwei Sun, Jingxiang Cui

“…Human pose estimation is an important downstream task in computer vision, with significant applications in action recognition and virtual reality. …”
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