Feature Extraction using Histogram of Oriented Gradients and Moments with Random Forest Classification for Batik Pattern Detection by wafiq azizah, soffiana agustin

“…The proposed methodology integrates two feature extraction techniques, Histogram of Oriented Gradients (HOG) and Texture Moments, with the Random Forest machine learning algorithm. The research process encompasses four key stages: pre-processing, feature extraction, classification, and system evaluation, where the accuracy of individual and combined feature extraction methods is analyzed. …”
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Barriers and enhance strategies for green supply chain management using continuous linear diophantine neural networks by Shougi S. Abosuliman, Saleem Abdullah, Nawab Ali

“…Abstract Artificial neural networks, a major element of machine learning, focus additional attention on the decision-making process. …”
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The role of force and torque in friction stir welding: A detailed review by Mostafa Akbari, Milad Esfandiar, Amin Abdollahzadeh

“…A notable advancement in this field is the implementation of machine learning tools, which enhance the ability to predict potential weld defects and improve overall weld quality. …”
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CORE-MD clinical risk score for regulatory evaluation of artificial intelligence-based medical device software by Frank E. Rademakers, Elisabetta Biasin, Nico Bruining, Enrico G. Caiani, Rhodri H. Davies, Stephen H. Gilbert, Eric Kamenjasevic, Gearóid McGauran, Gearóid O’Connor, Jean-Baptiste Rouffet, Baptiste Vasey, Alan G. Fraser

“…Abstract The European CORE–MD consortium (Coordinating Research and Evidence for Medical Devices) proposes a score for medical devices incorporating artificial intelligence or machine learning algorithms. Its domains are summarised as valid clinical association, technical performance, and clinical performance. …”
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Temperature and Humidity Monitoring in Hydroponic Cultivation Based on Internet of Things: Dataset Development for Smart Agriculture by Simon Prananta Barus, Jeriko Ichtus Seo

“…Further research will integrate more monitoring parameters, conduct direct hydroponic cultivation trials, and apply artificial intelligence such as machine learning and deep learning to improve efficiency and effectiveness in hydroponic cultivation.…”
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A Bee Farm Records Management System: A Case Study of Kanyabugunga Kashambya Sub-County. by Maanige, Barnet, Tayebwa, Onesmas

“…Future avenues for enhancement include IoT integration for real-time hive monitoring, machine learning for pest detection, a dedicated mobile application, and expansion to other regions. …”
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Usage of Optimized Least Square SVR to Volume Expansion Estimation of Cement Paste Including Fly Ash and Mgo Expansive Additive by Mazharul Islam, Sadia Afrin

“…To construct and assess machine learning-based algorithms to assess the volume expansion (𝑉𝑒) of cement paste, which consists of 𝐹𝐴 and 𝑀𝐸𝐴, 170 experimental findings from published studies are employed. …”
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A SYSTEMATIC ANALYSIS OF AI-EMPOWERED EDUCATIONAL TOOLS DEVELOPED IN INDIA FOR DISABLED PEOPLE by Shivani, Monika Gupta, Satinder Bal Gupta

“…The Notebook platform utilizes Machine Learning algorithms that provide students with a personalized learning experience. …”
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Effects of Operation Prediction Sharing for Collaborative Avatar Robot by Hyuga Suzuki, Hikari Yukawa, Kouta Minamizawa, Yoshihiro Tanaka

“…The robotic arm was controlled by two operators, while the system predicts operations 0.3 seconds ahead using machine learning based on one operator’s actions. …”
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Implementation Of Convolutional Neural Network (Cnn) Based On Mobile Application For Rice Quality Determination by Muhammad Zainal Altim, Abdullah Basalamah, kasman kasman

“…The method applied is an experimental method that utilizes machine learning technology by using many rice images that are used as datasets. …”
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Sequence-variable attention temporal convolutional network for volcanic lithology identification based on well logs by Hanlin Feng, Zitong Zhang, Chunlei Zhang, Chengcheng Zhong, Qiaoyu Ma

“…., to construct a lithology identification model using SVA-TCN. Compared with machine learning and deep learning methods, the SVA-TCN demonstrates a remarkable accuracy of 99.00%, surpassing the accuracy of the comparison methods by 0.37–17.69%. …”
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Leveraging Quantum LSTM for High-Accuracy Prediction of Viral Mutations by Prashanth Choppara, Bommareddy Lokesh

“…The one-hot encoding technique is a standard technique in machine learning for encoding protein sequences into data that can be used in neural networks.The proposed QLSTM outperformed existing deep learning architectures such as the Attention-Augmented Convolutional Neural Network (AACNN), Stacked Recurrent Neural Network (Stacked RNN), Retention Network (RetNet), and Bidirectional Long Short Term Memory (BiLSTM). …”
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Seurat function argument values in scRNA-seq data analysis: potential pitfalls and refinements for biological interpretation by Mikhail Arbatsky, Ekaterina Vasilyeva, Veronika Sysoeva, Ekaterina Semina, Ekaterina Semina, Valeri Saveliev, Kseniya Rubina

“…Here we narrow our focus down to a small set of mathematical methods applied upon standard processing of scRNA-seq data: preprocessing, dimensionality reduction, integration, and clustering (using machine learning methods for clustering). Normalization and scaling are standard manipulations for the pre-processing with LogNormalize (natural-log transformation), CLR (centered log ratio transformation), and RC (relative counts) being employed as methods for data transformation. …”
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On the implications of artificial intelligence methods for feature engineering in reliability sector with computer knowledge graph by Heling Jiang, Yongping Xia, Changjie Yu, Zhao Qu, Huaiyong Li

“…To improve operational efficiency and lower long-term maintenance costs, policy ideas include standardizing data collection techniques, investing in real-time monitoring systems, and implementing machine learning-based predictive maintenance across industries.…”
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Instruction and demonstration-based secure service attribute generation mechanism for textual data by LI Chenhao, WANG Na, LIU Aodi

“…Traditionally, the calibration of secure service attribute for textual data has been primarily reliant on human experts and machine learning methods, yet the efficiency and few-shot ability are insufficient. …”
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IMPLEMENTATION OF LEARNING MANAGEMENT SYSTEMS WITH GENERATIVE ARTIFICIAL INTELLIGENCE FUNCTIONS IN THE POST-PANDEMIC ENVIRONMENT by Denis-Cătălin Arghir

“…To demonstrate the system's effectiveness, a curriculum was crafted for a specialized field of study - Artificial Intelligence (AI), with a specific focus on the practical application of Machine Learning algorithms. This curriculum incorporates theoretical and practical application components, complemented by a suite of assessment tools and assignments tailored to the proposed subject. …”
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LASSO–MOGAT: a multi-omics graph attention framework for cancer classification by Fadi Alharbi, Aleksandar Vakanski, Murtada K. Elbashir, Mohanad Mohammed

“… The application of machine learning (ML) methods to analyze changes in gene expression patterns has recently emerged as a powerful approach in cancer research, enhancing our understanding of the molecular mechanisms underpinning cancer development and progression. …”
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Evaluation of 3D seed structure and cellular traits in-situ using X-ray microscopy by Marcus Griffiths, Barsanti Gautam, Clara Lebow, Keith Duncan, Xinxin Ding, Pubudu Handakumbura, John C. Sedbrook, Christopher N. Topp

“…Seeds of pennycress (Thlaspi arvense L.) an oilseed cover crop, were scanned and segmented using a machine learning model. Seed morphological analysis and a coat thickness map was applied to compare seed volumes of four genotypes. …”
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Unlocking precision medicine: clinical applications of integrating health records, genetics, and immunology through artificial intelligence by Yi-Ming Chen, Tzu-Hung Hsiao, Ching-Heng Lin, Yang C. Fann

“…Through the synergistic approach of integrating AI across diverse data sets, clinicians gain a holistic view of patient health and potential risks. Machine learning models excel at identifying high-risk patients, predicting disease activity, and optimizing therapeutic strategies based on clinical, genomic, and immunological profiles. …”
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Radial Basis Function Coupling with Metaheuristic Algorithms for Estimating the Compressive Strength and Slump of High-Performance Concrete by Amir Reza Taghavi Khangah, Erfan Khajavi, Hasti Azizi, Amir Reza Alizade Novin

“…The results highlight hybrid machine learning models as the potential to solve complex challenges in civil engineering and provide new approaches toward sustainable and efficient infrastructure development.…”
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