Activation-Guided Low-Rank Parameter Adaptation for Efficient Model Fine-Tuning by Qingchen Wang, Shengyu Shen

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Methods and reliability study of moral education assessment in universities: A machine learning-based approach by Ting Jin

“…This analysis utilizes Principal Component Analysis (PCA) alongside the k-Nearest Neighbor (k-NN) method, Support Vector Regression (SVR), and Artificial Neural Networks (ANN) to study student performance indices, enabling the prediction of ethical reasoning capabilities for standardized evaluation. …”
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Genome-Wide Methylation Sequencing to Identify DNA Methylation Markers for Early-stage Hepatocellular Carcinoma in Liver and Blood by Siyu Fu, Ruben G. Boers, Joachim B. Boers, Pam E. van der Meeren, Jean Helmijr, Vanja de Weerd, Michail Doukas, Maurice Jansen, Bettina E. Hansen, Roeland F. de Wilde, Dave Sprengers, Joost Gribnau, Saskia M. Wilting, José D. Debes, Andre Boonstra

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Machine learning-guided field site selection for river classification by Zhihao Wang, Gregory Brian Pasternack, Yufang Jin, Costanza Rampini, Serena Alexander, Nikhil Kumar, Rune Storesund, K. Martin Perales, Christopher Lim, Stephanie Moreno, Igor Lacan

“…Sufficient abundance and variety of field site sampling are crucial for obtaining an accurate reach-scale river classification of a regional stream network in support of scientific research and river management. …”
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Forecasting Short- and Long-Term Wind Speed in Limpopo Province Using Machine Learning and Extreme Value Theory by Kgothatso Makubyane, Daniel Maposa

“…This highlights CNN’s superior ability to capture complex patterns in wind speed dynamics over time. Concurrently, the analysis of the <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><mi>G</mi><mi>E</mi><mi>V</mi><msub><mi>D</mi><mi>r</mi></msub></mrow></semantics></math></inline-formula> across various order statistics identified <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><mi>G</mi><mi>E</mi><mi>V</mi><msub><mi>D</mi><mrow><mi>r</mi><mo>=</mo><mn>2</mn></mrow></msub></mrow></semantics></math></inline-formula> as the optimal model, supported by its favourable evaluation metrics in terms of Akaike information criteria (AIC) and Bayesian information criteria (BIC). …”
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Development mode and practice of fault-block oriented shale oil well in the second member of Funing Formation, Qintong Sag, Subei Basin by YAO Hongsheng,YUN Lu,ZAN Ling,ZHANG Longsheng,QIU Weisheng

“…For the multi-layer development of thick shale oil, the rectangular directional well pattern is conducive to the CO2 huff and puff, while the diamond reverse nine-spot well pattern is reasonable for the CO2 flooding. …”
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Primary sclerosing cholangitis–inflammatory bowel disease: Epidemiology, mortality, and impact of diagnostic sequence by Kristel K. Leung, Wenbin Li, Bettina Hansen, Aliya Gulamhusein, Lauren Lapointe-Shaw, Abdel Aziz Shaheen, Amanda Ricciuto, Eric I. Benchimol, Jennifer A. Flemming, Gideon M. Hirschfield

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Proactive Data Placement in Heterogeneous Storage Systems via Predictive Multi-Objective Reinforcement Learning by Suchuan Xing, Yihan Wang

“…Our method employs Long Short-Term Memory networks and Transformer architectures to model complex temporal dependencies in I/O traces, generating predictive access probability distributions for data blocks. …”
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Predicting Excavation-Induced Tunnel Response by Process-Based Modelling by Linlong Mu, Jianhong Lin, Zhenhao Shi, Xingyu Kang

“…This paper proposes an initiative to solve this problem by using process-based modelling, where information generated from the interaction processes between soils, structures, and excavation activities is utilized to gradually reduce uncertainty related to soil properties and to learn the interaction patterns through machine learning techniques. To illustrate such a concept, this paper presents a simple process-based model consisting of artificial neural network (ANN) module, inverse modelling module, and mechanistic module. …”
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Integration of Machine Learning and Wavelet Algorithms for Processing Probing Signals: An Example of Oil Wells by Zukhra Abdiakhmetova, Zhanerke Temirbekova

“…Furthermore, machine learning models, including standard regression algorithms and neural networks, are leveraged to enhance signal interpretation and predictive capabilities. …”
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A new method for determining factors Influencing productivity of deep coalbed methane vertical cluster wells by HUANG Li, XIONG Xianyue, WANG Feng, SUN Xiongwei, ZHANG Yixin, ZHAO Longmei, SHI Shi, ZHANG Wen, ZHAO Haoyang, JI Liang, DENG Lin

“…The dominant factors causing productivity differences are still uncertain, which hinders productivity improvement. To further evaluate the primary factors controlling productivity, a new method for assessing productivity-influencing factors was developed, based on the production dynamic parameters of 36 vertical cluster wells and using neural networks to predict bottom-hole flowing pressure. …”
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Advances in gait research related to Alzheimer’s disease by Shuding Yan, Xiaoping Yun, Qiang Liu, Zhenmei Hong, Yufan Chen, Shuijing Zhang

“…In the future, it is hoped that with the results of clinical manifestations, neuroimaging, and electrophysiology, simple and objective gait analysis results can be used as an alternative biomarker for cognitive decline to diagnose dementia early.Research objectiveThis research offers a comprehensive scoping review of the contemporary landscape of clinical gait evaluation. It delineates the pertinent concepts of gait analysis and machine learning in AD and elucidates the intricate interplay between gait patterns and cognitive status.MethodsA comprehensive literature search was conducted within PubMed for all articles published until march 18, 2024, using a set of keywords, including “machine learning and gait “and “gait and Alzheimer.” original articles that met the selection criteria were included.Results and significanceA strong correlation exists between autonomous gait and cognitive attributes, necessitating further investigation into the selective interplay between gait and mental factors. …”
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A dual-adaptive stochastic reinforcement chimp optimization algorithm for fire detection and multidimensional problem solving by Ziyang Zhang, Lingye Tan, Diego Martín, Leren Qian, Mohammad Khishe, Pradeep Jangir

“…We evaluate TASR-CHOA against 4 categorical optimization techniques as well as 18 top IEEE CEC-BC algorithms. …”
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Fast2Vec, a modified model of FastText that enhances semantic analysis in topic evolution by Ayu Pertiwi, Azhari Azhari, Sri Mulyana

“…Evaluation metrics include Spearman and Pearson correlation coefficients to assess the alignment with human judgments. …”
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Masked and Noise-Masked Multimodal Brain Tumor Image Segmentation Using SegFormer and Shared Encoder Framework by K. Hemalatha, P. R. Vishnu Vardhan, Alfred Dharmaraj Aravindraj, S. Hari Hara Sudhan

“…Additionally, noise-masking introduces a controlled Gaussian noise into the MRI images creating random variations in the pixel intensities and thereby encouraging the model to learn the invariant and essential patterns in MRI images. Evaluation on Brain Tumor Segmentation (BraTS2020) challenge dataset demonstrates that MNMS outperforms conventional convolutional neural network (CNN) based methods, achieving superior accuracy and Dice Similarity Coefficient (DSC) scores. …”
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Attention-Driven Hybrid Ensemble Approach With Bayesian Optimization for Accurate Energy Forecasting in Jeju Island&#x2019;s Renewable Energy System by Muhammad Ali Iqbal, Joon-Min Gil, Soo Kyun Kim

“…To address these challenges, we propose a Attention-driven Bayesian-Optimized Hybrid Ensemble Framework (ABHEF), evaluated on Jeju Island&#x2019;s energy mix data. …”
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Thermodynamic Modeling of Hashtag Dynamics for Social Media Clustering: A Maxwell-Boltzmann Approach by Krishnan Batri, Rajermani Thinakaran, Bhuvana Jayabalan, L. Karthikeyan, S. Lakshmi, R. Sowrirajan, Sivaram Murugan

“…This paper presents a novel thermodynamic framework that conceptualizes social network activity as system &#x201C;temperature&#x201D;, applying statistical mechanics principles to model hashtag importance as process innovation. …”
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To Study the Hydrological System and Watershed by Using Remote Sensing (RS) and Geographic Information System (GIS) in Kannad Taluka, Aurangabad District, MS, India by Eman Mohammed Garoon, Sultan Abduh Al-Horaibi, Mahadeo B. Mule

“…The basin’s mean bifurcation ratio is found to be 1.47 which indicates that the drainage network pattern is not much influenced by geological structures. …”
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Characteristics and Influence Mechanism of Cultural and Creative Enterprise Migration from the Amenity Perspective: A Case Study of Guangzhou by Liao Huihui, Wei Cheng, Luo Peng, Shen Jing

“…Research has shown the following: (1) Unlike the early evolution pattern of cultural and creative enterprises mainly gathering in the central area, and also different from the one-way migration path of manufacturing enterprises mainly transferring from the central area to the periphery, cultural and creative enterprises present more complex migration network relationships. …”
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A Flexible Constrained ICA Approach for Multisubject fMRI Analysis by Hanlu Yang, Trung Vu, Ehsan Ahmed Dhrubo, Vince D. Calhoun, Tülay Adali

“…Large-scale analysis of functional connectivity within intrinsic brain networks using functional magnetic resonance imaging (fMRI) data has been widely used for identifying biomarkers in various psychiatric disorders. …”
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