Endemic cushions of the Khorassan-Kopet Dagh floristic province show differential responses to future climate change by Zohreh Atashgahi, Mohammad Bagher Erfanian, Hamid Moazzeni, Gelareh Shemirani, Atefeh Pirani

“…The present study investigates the effects of climate change on the distribution of endemic cushion species in the Khorassan-Kopet Dagh (KK) floristic province, the eastern-most part of the Irano-Anatolian Biodiversity Hotspot. We predicted the current and future range of 19 cushions in 2040 and 2100, using 19 bioclimatic layers along with two different SSPs and an ensemble of 12 modeling algorithms. …”
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Improving the efficiency of visual navigation of an unmanned aerial vehicle by choosing the most informative route by N. V. Kim, D. S. Girenko

“…It should be noted that the estimated informative value of the routes is the average predicted value. Specific implementations can produce results that differ significantly from the calculated averages, however, the proposed algorithm allows to adapt the assessment of informativeness using new information.…”
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Phylogenetic and functional assessment of orthologs inference projects and methods. by Adrian M Altenhoff, Christophe Dessimoz

“…We systematically compared their predictions with respect to both phylogeny and function, using six different tests. …”
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Chemoresistance factors in non-small cell lung cancer by А. I. Shevchenko, А. P. Коlesnik, А. V. Каdzhoian, V. А. Кuzmenko

“…Basing on current data we tried to analyze prognostic and predictive value of main chemoresistance factors in NSCLC. …”
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Adaptive Weighted Access Point Technique for Robust Dynamic Indoor Positioning by Aqilah Binti Mazlan, Yin Hoe Ng

“…This approach involves constructing a radio map based on the wireless signal properties and employing matching algorithms, such as the nearest neighbor, to predict the position of target. …”
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Challenges and Opportunities in Remote Sensing-Based Fuel Load Estimation for Wildfire Behavior and Management: A Comprehensive Review by Arnick Abdollahi, Marta Yebra

“…The integration of remote-sensing technologies, along with derived products and advanced machine-learning algorithms, shows potential for enhancing fuel load predictions. …”
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Visceral adiposity index as a predictor of metabolic dysfunction-associated steatotic liver disease: a cross-sectional study by Tuo Zhou, Xiang Ding, Linjie Chen, Qianxiong Huang, Linfang He

“…Weighted multivariable regression models, subgroup analyses, and machine learning algorithms were used to evaluate associations and predictive performance. …”
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Estimation and validation of solubility of recombinant protein in E. coli strains via various advanced machine learning models by Wael A. Mahdi, Adel Alhowyan, Ahmad J. Obaidullah

“…Abstract This study presents a comprehensive approach to predicting solubility of recombinant protein in four E. coli samples by employing machine learning techniques and optimization algorithms. …”
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Integrating Machine Learning, SHAP Interpretability, and Deep Learning Approaches in the Study of Environmental and Economic Factors: A Case Study of Residential Segregation in Las... by Jingyi Liu, Yuxuan Cai, Xiwei Shen

“…By integrating traditional econometric techniques with machine learning and deep learning models, the study investigates (1) the correlation between housing prices, environmental quality, and segregation; (2) the differentiated impacts on various ethnic groups; and (3) the comparative effectiveness of predictive models. Among the tested algorithms, LGBM (Light Gradient Boosting) delivered the highest predictive accuracy and robustness. …”
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Personalized medication recommendations for Parkinson’s disease patients using gated recurrent units and SHAP interpretability by Atiye Riasi, Mehdi Delrobaei, Mehri Salari

“…This study aims to demonstrate the potential of sequence-by-sequence algorithms in recommending personalized medication combinations for patients with PD based on their previous visits. …”
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Characterization of time-variant and time-invariant assessment of suicidality on Reddit using C-SSRS. by Manas Gaur, Vamsi Aribandi, Amanuel Alambo, Ugur Kursuncu, Krishnaprasad Thirunarayan, Jonathan Beich, Jyotishman Pathak, Amit Sheth

“…Suicide is the 10th leading cause of death in the U.S (1999-2019). However, predicting when someone will attempt suicide has been nearly impossible. …”
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Investigating How User's Activities in Both Virtual and Physical World Impact Each Other Leveraging LBSN Data by Zhiwen Yu, Yue Yang, Xingshe Zhou, Yu Zheng, Xing Xie

“…Finally, we conduct link prediction by using the random walk with restart method considering the effect of every node and every edge. …”
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Unsteady Lifting-Line Free-Wake Aerodynamic Modeling for Morphing Wings by Gregorio Frassoldati, Riccardo Giansante, Giovanni Bernardini, Massimo Gennaretti

“…A time-stepping, lifting-line solution algorithm for the prediction of the unsteady aerodynamics of morphing wings is presented. …”
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Short time solar power forecasting using P-ELM approach by Shuqi Shi, Boyang Liu, Long Ren, Yu Liu

“…The results indicate that the P-ELM algorithm achieves higher accuracy in short-term prediction, demonstrating its suitability for ensuring accuracy and reliability in real-time solar power forecasting.…”
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XFEM for Fracture Analysis of Centrally Cracked Laminated Plates Subjected to Biaxial Loads by Shailesh Palekar, Achchhe Lal

“…The effect of loadings on the crack growth and crack propagation direction and their effects on the MSIFs using global tracking crack growth algorithm is also presented. The results of the present investigation will be useful for accurate prediction of fracture response of cracked composite structures, crack growth and crack propagation behavior which ultimately effects on the structural safety and integrity of the composite structures.…”
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Fault Diagnosis of Industrial Process Based on FDKICA-PCA by ZHANG Jing, ZHU Fei-fei, LIU Jia-xing, WANG Jiang-tao

“…Because the dynamic characteristics of autocorrelation and lag correlation in production process are neglected in fault diagnosis,Kernel Independent Component AnalysisPrincipal Component Analysis (KICAPCA) is very poor in detecting small and gradual faults because of lacking available variable contribution analysis.In this paper, a dynamic kernel independent component analysis (KICAPCA) fault diagnosis method based on wavelet packet filtering is proposed.This method integrates wavelet packet filtering theory and AR model prediction data characteristics into KICAPCA to extract the feature information of process variable autocorrelation and lagrelated .In this paper, KICAPCA algorithm is used to extract the independent components and principal components of process variables to determine the control limits of three monitoring indicators T2, SPE,I2.Nonlinear contribution graph is used for fault diagnosis, and the advantage of FDKICAPCA method is verified by simulation results of Tennessee process.…”
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DS-AdaptNet: An Efficient Retinal Vessel Segmentation Framework With Adaptive Enhancement and Depthwise Separable Convolutions by Shuting Chen, Chengxi Hong, Hong Jia

“…Most importantly, DS-AdaptNet achieves these results with only 1.57M parameters and 44.08 GFLOPs—a 94.9% reduction in parameters and 77.2% reduction in computational operations compared to standard U-Net. …”
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Quantitative analysis of deep learning-based denoising model efficacy on optical coherence tomography images with different noise levels by Furkan Kirik, Farid Iskandarov, Kamile Melis Erturk, Hakan Ozdemir

“…Background: To quantitatively evaluate the effectiveness of the Noise2Noise (N2N) model, a deep learning (DL)-based noise reduction algorithm, on enhanced depth imaging-optical coherence tomography (EDI-OCT) images with different noise levels. …”
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Abnormal sound detection method for coal mine belt conveyors based on convolutional autoencoder by SHEN Long, SHAN Haoran, PEI Wenliang, YANG Guixiang, WANG Yongli

“…Background noise in the signals was filtered using the WebRTC noise reduction algorithm, and Mel-Frequency Cepstral Coefficients (MFCC) were calculated from the denoised signals to obtain audio features of normal operation. …”
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Spot Position Extraction Based on High-resolution Parametric Subspace Method without Eigen decomposition by Azad Raheem Kareem

“…A simulated example is provided to evaluate the proposed method and the simulation results shows that the proposed algorithm has the advantages of reduction the computational load and superior estimation performance. …”
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