Explaining drivers of housing prices with nonlinear hedonic regressions by Heng Wan, Pranab K. Roy Chowdhury, Jim Yoon, Parin Bhaduri, Vivek Srikrishnan, David Judi, Brent Daniel

“…We then conduct sensitivity and Partial Dependence Plot (PDP) analyses to interpret the fitted ANN model. We find that the ML model achieves higher predictive accuracy and explains 16 % more of housing price variance than a traditional linear regression model. …”
Get full text

Surface Defect Detection Algorithm for Wind Turbine Blades Based on HSCA-YOLOv7 by Bing LI, Yunshan BAI, Kuan ZHAO, Congbin GUO, Yongjie ZHAI

“…The focal EIoU loss function is used to solve the problem that the length and width of the prediction box are wrongly amplified and improve the positioning ability of the model for blade defects. …”
Get full text

Inorganic carbon assimilation by planktonic community in Santos Basin, Southwestern Atlantic Ocean by Deborah S. Kutner, Jeff S. Bowman, Flávia M. P. Saldanha-Corrêa, Mateus G. Chuqui, Pedro M. Tura, Daniel L. Moreira, Frederico P. Brandini, Camila N. Signori

“…Rates were analyzed using statistical tests to verify spatial differences between groups of samples and generalized linear models to identify correlations with environmental variables (temperature, salinity, density, mixed layer depth, dissolved oxygen, nitrite, nitrate, silicate, phosphate, turbidity, CDOM, and phycoerythrin and chlorophyll-a concentrations). …”
Get full text

Inorganic carbon assimilation by planktonic community in Santos Basin, Southwestern Atlantic Ocean by Deborah S. Kutner, Jeff S. Bowman, Flávia M. P. Saldanha-Corrêa, Mateus G. Chuqui, Pedro M. Tura, Daniel L. Moreira, Frederico P. Brandini, Camila N. Signori

“…Rates were analyzed using statistical tests to verify spatial differences between groups of samples and generalized linear models to identify correlations with environmental variables (temperature, salinity, density, mixed layer depth, dissolved oxygen, nitrite, nitrate, silicate, phosphate, turbidity, CDOM, and phycoerythrin and chlorophyll-a concentrations). …”
Get full text

Panchromatic Simulated Galaxy Observations from the NIHAO Project by Nicholas Faucher, Michael R. Blanton, Andrea V. Macciò

“…These features are likely to affect SED modeling accuracy.…”
Get full text

The Emerging Role of Omics-Based Approaches in Plant Virology by Viktoriya Samarskaya, Nadezhda Spechenkova, Natalia O. Kalinina, Andrew J. Love, Michael Taliansky

“…In this review, we discuss the current state-of-the-art applications of such key omics techniques, their challenges, future, and combinatorial use (e.g., single cell and spatial omics coupled with super-resolution high-throughput imaging methods and artificial intelligence-based predictive models) to obtain new mechanistic insights into plant–virus interactions, which could be exploited for more effective plant disease management and monitoring.…”
Get full text

“Sunshade World”: A fully coupled GCM evaluation of the climatic impacts of geoengineering by D. J. Lunt, A. Ridgwell, P. J. Valdes, A. Seale

“…We investigate the magnitude and nature of this climate change for the first time within a fully coupled General Circulation Model. We find significant cooling of the tropics, warming of high latitudes and related sea ice reduction, a reduction in intensity of the hydrological cycle, reduced ENSO variability, and an increase in Atlantic overturning. …”
Get full text

A New Climate vulnerability Index Sistan and Baluchistan province by esmaeail ahmadi, zahra hejazizadeh, bohlol alijani, Mohammad saligheh, Hassan danaie fard

“…Area with very high vulnerability label expanded from 57.5% to 100%, which reflects the spatial expansion of vulnerability over SB. The overall result is that vulnerability reduction needs for accurate and continuous measurement, on the increase adaptation capacity and mitigate climate sensitivity.…”
Get full text

Image Reconstruction Algorithm Based on Extreme Learning Machine for Electrical Capacitance Tomography by SU Ziheng, CHEN Deyun, WANG Lili

“…Aiming at the problem that the traditional ECT is not accurate in complex situations, this paper proposes a depth learning based inversion method Through the improvement and optimization of the traditional extreme learning machine, the image feature information obtained by the reconstructed image method is used as the training data, and the result obtained by inputting the data into the predictive model is used as the prior information The cost function is used to encapsulate the prior knowledge and domain expertise, and spatial regularizers and time regularizers are introduced to enhance sparsity The separated Bregman (SB) algorithm and the iterative shrinkage threshold (FIST) method are used to solve the specified cost function The final imaging result is obtained The simulation results show that the image reconstructed by this method has less than 10% error compared with the original flow pattern, and reduces artifacts and distortion, which improves the reconstructed image quality…”
Get full text

CABAD: A video dataset for benchmarking child aggression recognition by Shehzad Ali, Md Tanvir Islam, Ik Hyun Lee, Mohammad Hijji, Khan Muhammad

“…Leveraging CABAD, we propose CABA_Net, a multi-stage deep-learning framework integrating MobileViT for spatial feature extraction, Temporal Convolutional Networks (TCN) for sequential modeling, and an Attention LSTM for refined temporal attention on behavioral patterns. …”
Get full text

Application of PSO-Optimized Twin Support Vector Machine in Medium and Long-Term Load Forecasting under the Background of New Normal Economy by Xiang He, Yan Chen, Kai Hu, Lin Wan

“…Moreover, this paper uses the algorithm to debug the filter and studies the accurate prediction of the fine model by the progressive spatial mapping algorithm and the processing of the data by the vector fitting algorithm. …”
Get full text

Comparative Analysis of Non-Negative Matrix Factorization in Fire Susceptibility Mapping: A Case Study of Semi-Mediterranean and Semi-Arid Regions by Iraj Rahimi, Lia Duarte, Wafa Barkhoda, Ana Cláudia Teodoro

Get full text

Computed Tomography‐Based Habitat Analysis for Prognostic Stratification in Colorectal Liver Metastases by Chaoqun Zhou, Hao Xin, Lihua Qian, Yong Zhang, Jing Wang, Junpeng Luo

“…Compared with CRS and TBS, the habitat model demonstrated superior predictive accuracy, particularly for DFS and liver‐specific DFS, with higher time‐dependent AUC values and improved model calibration (lower IBS). …”
Get full text

Research on the Error Estimation Method for Electric Energy Meters of Electric Vehicle Charging Piles based on Deep Learning by Wang Juan, Liu Wei, Zhang Yong, Liu Zhi, Zheng Xiaolei, Wang Yuxin, Hao Jianshu, Dai Xuanding

“…First, the convolutional module is combined with the highway network to extract spatial features from smart meter data for charging facilities while retaining some original information to improve model prediction performance. …”
Get full text

Activation of Adenosine Phosphate Signaling Promotes Antitumor Immunity in Tumor Microenvironment and Facilitate Immunotherapy by Yantao Xu, Ying Wang, Zixi Jiang, Yi He, Guowei Zhou, Benliang Wei, Jiachen Liu, Xiang Chen

“…We developed an adenosine phosphate signaling model (APsig) that showed promising prognostic value in melanoma, as well as predictive efficacy of immunotherapy across 1068 tumor samples in 9 independent public cohorts. …”
Get full text

Oscillatory Forward-Looking Sonar Based 3D Reconstruction Method for Autonomous Underwater Vehicle Obstacle Avoidance by Hui Zhi, Zhixin Zhou, Haiteng Wu, Zheng Chen, Shaohua Tian, Yujiong Zhang, Yongwei Ruan

“…Furthermore, the method is integrated with the Ego-Planner path planning algorithm and nonlinear Model Predictive Control (MPC) algorithm, creating a comprehensive underwater 3D perception, planning, and control system. …”
Get full text

Exploring the determinants of thyroid disorders in high-altitude western Himalaya: a geospatial and epidemiological study by Arshad Ahmed, Kheraj, Alireza Mohammadi, Robert Bergquist

“…Geographic information systems were utilized to map the spatial distribution of thyroid disorder prevalence, and the model’s predictive accuracy was validated using receiver operating characteristic (ROC). …”
Get full text

Assessing Clouds in GFDL's AM4.0 With Different Microphysical Parameterizations Using the Satellite Simulator Package COSP by Huan Guo, Levi G. Silvers, David Paynter, Wenhao Dong, Songmiao Fan, Xianwen Jing, Ryan Kramer, Kristopher Rand, Kentaroh Suzuki, Yuying Zhang, Ming Zhao

“…Model biases include the under‐prediction of total and low‐level clouds, especially optically thin/intermediate clouds with cloud optical depth of less than 23, but the over‐prediction of thick clouds, indicating “too few, too bright” biases. …”
Get full text

RoofMapNet: Utilizing geometric primitives for depicting planar building roof structure from high-resolution remote sensing imagery by Jiaqi Wang, Guanzhou Chen, Xiaodong Zhang, Tong Wang, Xiaoliang Tan, Qingyuan Yang, Wenlin Zhou, Kun Zhu

“…This strategy enhances the model’s robustness in junction prediction under heterogeneous sample distribution scenarios. …”
Get full text

Spatio-Temporal Travel Speed Estimation in Mixed Traffic Conditions: A Probe Vehicle-Based Approach With Autonomous Vehicle Sensor Integration by Hyungjoo Kim, Seongeun Na, Jongho Kim, Sangsoo Lee, Jiho Yeo

“…Future research directions include integrating vehicle-to-everything (V2X) communication and machine learning models to further refine estimation accuracy and predictive capabilities in dynamic urban mobility environments.…”
Get full text