Paucity of optineurin gene variants in Indian juvenile open-angle glaucoma patients by Manoj Yadav, Chand Singh Dhull, Sumit Sachdeva, Anshu Yadav, Aarti Bhardwaj, Vishal Panghal, Ankit Kumari, Ritu Yadav, Sapna Sharma, Mukesh Tanwar

“…Methods: Polymerase chain reaction (PCR) amplification and sequencing were employed to identify nucleotide variants within the coding sequence and intron-exon boundaries of the OPTN gene in 85 JOAG patients and 100 controls. A pathogenicity prediction of identified variants was performed by six distinct online algorithms. …”
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Machine learning approaches reveal methylation signatures associated with pediatric acute myeloid leukemia recurrence by Yushuang Dong, HuiPing Liao, Feiming Huang, YuSheng Bao, Wei Guo, Zhen Tan

“…Therefore, this study provides a valuable reference for enhancing recurrence risk prediction models in AML and clarifying disease pathogenesis, as well as offering broader insights into mechanisms underlying other major diseases.…”
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Innovative Solutions for Oil Well Monitoring: Data-Driven Multiphase Virtual Flow Metering Using Ensemble Machine Learning and Historical Field Data by Wael A. Farag, Hussein H. Ismail, Muhammad Nadeem

“…By combining data-driven ensemble machine-learning algorithms and historical oil field portable test reports, this paper proposes a Data-Drive Multiphase Virtual Flow Meter (DD-MVFM) that estimates oil, gas, and water flow rates and provides real-time monitoring, and predicts future production with appropriate accuracy. …”
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An Ensemble Learning Approach for Drought Analysis and Forecasting in Central Bangladesh by Md. Alomgir Hossain, Momotaz Begum, Md. Nasim Akhtar, Md. Alamin Talukder, Nomanur Rahman, Mahfuzur Rahman

“…The study revealed that integrating ARIMA with ML algorithms improved forecasting accuracy, achieving over 92.0% accuracy in predicting SPI and SPEI, thereby significantly enhancing drought prediction capabilities.…”
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Research Progress on Process Optimization of Metal Materials in Wire Electrical Discharge Machining by Xinfeng Zhao, Binghui Dong, Shengwen Dong, Wuyi Ming

“…It highlights that the integration of AI by optimization algorithms (such as Genetic Algorithms, particle swarm optimization, and manta ray foraging optimization) offers an effective path toward the intelligent evolution of WEDM processes. …”
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Learning the Value of Place: Machine Learning Models for Real Estate Appraisal in Istanbul’s Diverse Urban Landscape by Ahmet Hilmi Erciyes, Toygun Atasoy, Abdurrahman Tursun, Sibel Canaz Sevgen

“…The prediction of real estate values is vital for taxation, transactions, mortgages, and urban policy development. …”
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Intrusion Detection Using Machine Learning for Risk Mitigation in IoT-Enabled Smart Irrigation in Smart Farming by Abhishek Raghuvanshi, Umesh Kumar Singh, Guna Sekhar Sajja, Harikumar Pallathadka, Evans Asenso, Mustafa Kamal, Abha Singh, Khongdet Phasinam

“…Crop irrigation is an important step in crop yield prediction. Field harvesting is very reliant on human supervision and experience. …”
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Applications of Machine Learning and Remote Sensing in Soil and Water Conservation by Ye Inn Kim, Woo Hyeon Park, Yongchul Shin, Jin-Woo Park, Bernie Engel, Young-Jo Yun, Won Seok Jang

“…As analytical tools continue to advance, the variety of ML algorithms and RS sources has expanded, providing opportunities for more sophisticated analyses. …”
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Spatial Quality Control Method for Surface Temperature Observations Based on Multiple Elements by Xiaoling Ye, Xing Yang, Xiong Xiong, Shuai Yang, Yang Chen

“…However, machine learning algorithms are slower than traditional mathematical models. …”
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Low-Illumination Parking Scenario Detection Based on Image Adaptive Enhancement by Xixi Xu, Meiqi Zhang, Hao Tang, Weiye Xu, Bowen Sun, Zhu’an Zheng

“…Aiming at the problem of easily missed and misdetected parking spaces and obstacles in the automatic parking perception task under low-illumination conditions, this paper proposes a low-illumination parking space and obstacle detection algorithm based on image adaptive enhancement. The algorithm comprises an image adaptive enhancement module, which predicts adaptive parameters using CNN and integrates the low-light image enhancement via illumination map estimation and contrast-limited adaptive histogram equalization algorithms for image processing. …”
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Optimizing axial length estimation for intraocular lens power calculation in phacovitrectomy for macula-off retinal detachment by Sukhum Silpa-archa, Chitchanok Samanwongthai, Variya Nganthavee, Korawin Charoensuk

“…The primary outcome was the mean absolute prediction error (MAE) between postoperative AL and preoperative estimates generated by five methods, including two novel algorithms. …”
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Remaining Useful Life Estimation through Deep Learning Partial Differential Equation Models: A Framework for Degradation Dynamics Interpretation Using Latent Variables by Sergio Cofre-Martel, Enrique Lopez Droguett, Mohammad Modarres

“…For the past decade, researchers have explored the application of deep learning (DL) regression algorithms to predict the system’s health state behavior based on sensor readings from the monitoring system. …”
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Design and analysis of quantum machine learning: a survey by Linshu Chen, Tao Li, Yuxiang Chen, Xiaoyan Chen, Marcin Wozniak, Neal Xiong, Wei Liang

“…Thirdly, we conduct discussions on the applications of quantum machine learning in image recognition, drug efficacy prediction and cybersecurity. Finally, we summarise the challenges of quantum machine learning consisting of algorithm design, hardware limitations, data encoding, quantum landscapes, noise and decoherence.…”
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Improved Diagnostics Using Polarization Imaging and Artificial Neural Networks by Jianhua Xuan, Uwe Klimach, Hongzhi Zhao, Qiushui Chen, Yingyin Zou, Yue Wang

“…Polarization image analysis algorithms are then developed to analyze Stokes polarization images for cell or tissue classification. …”
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Integrated single-cell and transcriptome sequencing data reveal the value of IL1RAP in gastric cancer microenvironment and prognosis by Weifeng Yang, Xiaohua Wu, Jian Wang, Wenquan Ou, Xing Huang

“…The CIBERSORT and ssGSEA algorithms elucidated immune infiltration patterns, while TIDE and TCGA predicted immune-related outcomes. …”
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Design and development of full self-service smart shopping system for unmanned supermarket by Xiao Liang, Yu Qi, Shuo Xi, Guanglei Meng, Zhujun Wang

“…Additionally, integrating a distributed DIMP (Discriminative Model Prediction) visual-tracking algorithm and infrared range sensors ensures that the smart shopping cart always follows the customer at a safe distance. …”
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Method for reconstructing safety and arming motion process by integrating Kalman filter and KCF by Yinhuan Zhang, Qinkun Xiao, Xing Liu, Yongquan Wei, Jingyun Xue

“…On the OTB100 dataset, it attains 92.50% accuracy and 68.10% success rate, outperforming other related filtering algorithms. These results highlight significant improvements in tracking accuracy and success rate, demonstrating the algorithm’s robustness in handling challenging tracking scenarios. …”
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Neuro-fuzzy inference system and white shark optimization of coagulation-flocculation of aquaculture wastewater treatment by A.F. Mohamed, H. Rezk

“…The R-squared values for training and testing are 1.0 and 0.82, respectively, and adaptive neuro-fuzzy inference system reduced the root mean square error from 6.8 with analysis of variance to 1.135 with adaptive neuro-fuzzy inference system achieving an 83.5 percent reduction. The R-squared value for prediction rose 7.2 percent from 0.765 via analysis of variance to 0.82 via adaptive neuro-fuzzy inference system.CONCLUSION:  Adaptive neuro-fuzzy inference system succseded to present an accurate model of  wastewater treatment process  and white shark optimizer defined accutrelly the values of chitosan dose, pontential of hydrogen, and settling time to reduce turbidity and salinity. …”
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Research progress on theory and simulation of supercritical CO2 pipeline transportation by Meng LI, Chaofei NIE, Xin OUYANG, Zhenning FAN, Haining LIANG, Jianwu LIU, Zhigang XU, Yan ZHANG

“…Therefore, these models and algorithms need to be modified to incorporate actual engineering data. …”
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Comparison of sample preparation methods for higher heating values in various sugarcane varieties using near-infrared spectroscopy by Kantisa Phoomwarin, Khwantri Saengprachatanarug, Jetsada Posom, Seree Wongpichet, Kittipong Laloon, Arthit Phuphaphud

“…Spectral data were pre-processed using seven techniques to minimize noise, and four variable selection algorithms–Variable Importance in Projection, Successive Projection Algorithm, Genetic Algorithm, and correlation-based selection via Partial Least Squares Regression–were employed to improve modelling accuracy.In parallel, four machine learning models–AdaBoost Regressor, Gradient Boosting, K-Nearest Neighbors, and Random Forest–were applied to the same dataset for Higher heating value prediction. …”
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