A class imbalance aware hybrid model for accurate rice variety classification by Hanumesh Vaidya, K.V. Prasad, C. Rajashekhar, D Tripathi, Renuka S, Jyoti Shetty, Kumar Swamy, Shobha Y

“…As the complexity of this task has grown, advanced Machine Learning (ML) and Deep Learning (DL) models have emerged as powerful tools for accurate variety identification. …”
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Application of ATR-FTIR spectroscopy and multivariate statistical analysis in cancer diagnosis by Ao Song, Wanli Yang, Jun Wang, Yisa Cai, Lizheng Cai, Nan Pang, Ruihua Yu, Zhikun Liu, Chao Yang, Feng Jiang

“…The findings suggest that the integration of ATR-FTIR spectroscopy with multiple machine learning models represents a promising auxiliary diagnostic method for clinical lung cancer diagnosis, enabling detection at the molecular level.…”
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DEPDC1B, CDCA2, APOBEC3B, and TYMS are potential hub genes and therapeutic targets for diagnosing dialysis patients with heart failure by Wenwu Tang, Wenwu Tang, Zhixin Wang, Xinzhu Yuan, Liping Chen, Haiyang Guo, Zhirui Qi, Ying Zhang, Xisheng Xie

“…Secondly, HF-related genes were screened by WGCNA, and finally the genes intersecting the two were selected as candidate genes. Machine learning was used to identify hub gene and construct a nomogram model, which was verified by ROC curve and RT-qPCR. …”
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Designing host-associated microbiomes using the consumer/resource model by Germán Plata, Karthik Srinivasan, Madan Krishnamurthy, Lukas Herron, Purushottam Dixit

“…For example, there has been a boom in machine-learning models aiding in the design of proteins with user-specified structures or functions. …”
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Self-reports map the landscape of task states derived from brain imaging by Brontë Mckeown, Ian Goodall-Halliwell, Raven Wallace, Louis Chitiz, Bridget Mulholland, Theodoros Karapanagiotidis, Samyogita Hardikar, Will Strawson, Adam Turnbull, Tamara Vanderwal, Nerissa Ho, Hao-Ting Wang, Ting Xu, Michael Milham, Xiuyi Wang, Meichao Zhang, Tirso RJ Gonzalez Alam, Reinder Vos de Wael, Boris Bernhardt, Daniel Margulies, Jeffrey Wammes, Elizabeth Jefferies, Robert Leech, Jonathan Smallwood

“…., those inferred from measures of brain activity). Here, we used machine learning to show that self-reported descriptions of experiences across tasks can reliably map the objective landscape of task states derived from brain activity. …”
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Klasifikasi Ulasan Palsu Menggunakan Borderline Over Sampling (BOS) dan Support Vector Machine (SVM) (Studi Kasus : Ulasan Tempat Makan) by Aisyah Awalina, Fitra Abdurrachman Bachtiar, Indriati Indriati

“…Ulasan palsu bisa secara efektif dibedakan menggunakan machine learning. Namun, banyak dari dataset ulasan palsu ini tidak seimbang (imbalanced dataset) sehingga dapat mempengaruhi hasil klasifikasi. …”
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Supply Capability Evaluation of Intelligent Manufacturing Enterprises Based on Improved BP Neural Network by Quan Quan, Zhongqiang Zhang

“…Based on the background of suppliers in intelligent manufacturing enterprises, the evaluation method of supplier efficiency was studied by using machine learning. In this paper, based on the traditional backpropagation (BP) neural network, combined with the improved particle swarm optimization (PSO) algorithm, and on the basis of the supplier evaluation index system, the supplier efficiency evaluation model of intelligent manufacturing enterprises based on DPMPSO-BP neural network is constructed. …”
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Practical Employment of Granular Computing to Complex Application Layer Cyberattack Detection by Rafał Kozik, Marek Pawlicki, Michał Choraś, Witold Pedrycz

“…Innovative approaches to handle this challenge are undertaken by the scientific community, proposing the utilization of the emerging, advanced machine learning methods. This very paper puts forward a novel approach to the detection of cyberattacks taking inventory of the practical application of information granules. …”
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Sidelink communication technology enhancement and standardization evolution for C-V2X by ZHAO Rui, WEN Xiaoran, ZHENG Shilei, ZHOU Xiaoxing, XI Yifan, LIU Yanqiang, HU Jinling

“…With the rapid development of intelligent transportation systems, sidelink communication technology for cellular vehicle-to-everything (C-V2X) has become the key technology to enable vehicle-to-vehicle, vehicle-to-infrastructure, and vehicle-to-pedestrian communications. 3rd Generation Partnership Project (3GPP) has finished research on sidelink communication technology enhancement, aiming to meet the diverse needs of V2X services, and is actively advancing research and standardization on 6G evolution technologies such as integrated sensing and communication (ISAC), artificial intelligence and machine learning (AI/ML). The development trends of sidelink communication technology in C-V2X were firstly introduced. …”
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Monocular Depth Estimation: A Review on Hybrid Architectures, Transformers and Addressing Adverse Weather Conditions by Kumara Lakindu, Senanayake Nipuna, Poravi Guhanathan

“…Monocular depth estimation has significantly improved over the past couple of years and deep learning-based methods have surpassed traditional and machine learning-based methods. Deep learning-based methods have further been enhanced using transformer and hybrid approaches. …”
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Recent Progress of Anomaly Detection by Xiaodan Xu, Huawen Liu, Minghai Yao

“…Anomaly analysis is of great interest to diverse fields, including data mining and machine learning, and plays a critical role in a wide range of applications, such as medical health, credit card fraud, and intrusion detection. …”
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Real-Time Football Match Prediction Platform by An Zhongqi

“…The platform employs machine learning models, including Random Forest, Support Vector Machines (SVM), and Neural Networks, combined with feature engineering techniques, to generate accurate predictions. …”
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Stochastic Gradient Descent-like relaxation is equivalent to Metropolis dynamics in discrete optimization and inference problems by Maria Chiara Angelini, Angelo Giorgio Cavaliere, Raffaele Marino, Federico Ricci-Tersenghi

“…This is a fundamental question at the time of understanding the most used training algorithm in the field of Machine Learning, but it received no answer until now. …”
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Classification of diabetic retinopathy stages based on neural networks by M. M. Lukashevich, Y. I. Golub

“…Diabetic retinopathy can be detected much faster and more accurately by using machine learning methods for image analyzing of the human retina. …”
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Automated and highly parallelized Bayesian optimization scheme for direct drive fusion experiments on OMEGA by V. Gopalaswamy, A. Lees, R. Ejaz, C. A. Thomas, T. J. B. Collins, K. S. Anderson, W. Ebmeyer, R. Betti

“…On the OMEGA laser facility, predictive machine learning models have been developed to accurately forecast the result of an experiment using only inexpensive simulations and the large dataset of prior experimental data. …”
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Fast panoramic image stitching algorithm based on parameter regression by Fan GUO, Xiaohu LI, Wentao LIU, Jin TANG

“…In reality, the field of view of images acquired by cameras was usually limited, and the demand for panoramic images was increasing.Therefore, a fast panoramic image stitching algorithm based on parameter regression was proposed for panoramic image sequences.The traditional image registration task was transformed into deep learning combined with machine learning, a multi-scale deep convolutional neural network (MDCNN) based on Gaussian difference pyramid was designed to extract features of stitching images, and LightGBM regression model was used to predict stitching parameters.The transformation matrix and the focal length of the camera were obtained to align the images, and a hyperbolic image fusion algorithm was designed to eliminate the stitching seam between the images.The experimental results show that the proposed algorithm can quickly mosaic images and obtain clearer and more natural panoramic mosaic effects than the existing representative algorithms.It also has good adaptability for infrared images.…”
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The Power of Words: A Study of How Search Contents Can Affect Financial Decisions by Du Ni, Xingzhi Li, Zhi Xiao, Ke Gong

“…Therefore, this study was carried out to analyze the emotional meanings of 13,915 English words obtained from Google Trends and the profits gained from the US house market by automatic transactions and discovered that the emotional meanings of the search contents could modulate the financial decision with unsupervised machine learning methods.…”
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Lighting the way forward: The bright future of photonic integrated circuits by M.A. Butt, B. Janaszek, R. Piramidowicz

“…Its synergy with quantum information and machine learning opens innovation pathways. This review explores recent advancements in optical platforms, highlighting ongoing research and developments that are driving technological progress in this field. …”
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Financial Data Anomaly Detection Method Based on Decision Tree and Random Forest Algorithm by Qingyang Zhang

“…With the emergence of machine learning and data mining in recent years, new ideas and methods have emerged in the detection of abnormal network flows. …”
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A priori physical information to aid generalization capabilities of neural networks for hydraulic modeling by Gianmarco Guglielmo, Andrea Montessori, Jean-Michel Tucny, Michele La Rocca, Pietro Prestininzi

“…The application of Neural Networks to river hydraulics and flood mapping is fledgling, despite the field suffering from data scarcity, a challenge for machine learning techniques. Consequently, many purely data-driven Neural Networks have shown limited capabilities when tasked with predicting new scenarios. …”
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