Machine learning-based optimization of photogrammetric JRC accuracy by Qinzheng Yang, Ang Li, Yipeng Liu, Hongtian Wang, Zhendong Leng, Fei Deng

“…Abstract To improve the accuracy of photogrammetric joint roughness coefficient (JRC) estimation, this study proposes two optimization models based on ground sample distance (GSD), point density, and the root mean square error (RMSE) of checkpoints. First, an algorithm that automatically generates spatial positions for equipment based on the convergence strategy was developed, using principles of Structure from Motion and Multi-View Stereo (SfM-MVS) and the shooting parameter selection algorithm (SPSA). …”
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Low power, non-intrusive 3D localization for underwater mobile robots by Suryansh Sharma, Daniel Van Passen, R. Venkatesha Prasad, Kaushik Chowdhury

“…Pisces enables robust relative localization, especially in swarms of robots with the potential for additional applications like docking. We demonstrate high localization accuracy with a Mean Absolute Error (MAE) of 0.031 m at 0.32 m separation and 0.16 m MAE at 1 m separation. …”
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Models for a Fast Computation of Internal Overvoltages in Medium-Frequency Transformers by Bastian Korthauer, Jurgen Biela

“…Simulation and measurement results show that the proposed models can compute internal overvoltages more than 500 times faster than FEA, while predicting the maximum overvoltage with an error of less than <inline-formula><tex-math notation="LaTeX">$7 \%$</tex-math></inline-formula>. …”
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Selecting Optimal Feature Set in High-Dimensional Data by Swarm Search by Simon Fong, Yan Zhuang, Rui Tang, Xin-She Yang, Suash Deb

“…The comparative experiment results show that Swarm Search is able to attain relatively low error rates in classification without shrinking the size of the feature subset to its minimum.…”
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Finite time trajectory tracking of a switched non inverting buck–boost converter using pulse width modulation by Chandan Kumar, Anjan Kumar Ray

“…Control and monitoring of DC–DC converters have become crucial issues as these devices grow more and more prevalent in power electronics applications, including renewable energy systems, DC microgrids, electric vehicle, and More Electric Aircraft (MEA). …”
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The Comparison of Activation Functions in Feature Extraction Layer using Sharpen Filter by Oktavia Citra Resmi Rachmawati, Ali Ridho Barakbah, Tita Karlita

“…Using a custom-built CNN program module within the researchers’ machine learning library, Analytical Libraries for Intelligent-computing (ALI), the performance of each activation function was evaluated by analyzing mean squared error (MSE) values obtained during the training process. …”
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Crack propagation simulation of fiber-reinforced composite laminates based on non-ordinary state-based peridynamics by Ji Zhou, Songrong Qian

“…The model is validated through a displacement load simulation on a composite laminate under displacement load, and the displacement results agreed well with those obtained from the finite element method, with a displacement error at the midline of 0.73%. Additionally, analyses of composite laminates with defects and real material tensile experiments further verify the detailed processes of damage initiation, propagation, and crack growth. …”
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Optimal Adaptive Robust Pitch Control with Load Mitigation for Uncertain Variable Speed Wind Turbines by Sara Majidi, Reza Shahnazi

“…Another term is a chattering-free continuous robust structure, which can cope with the approximation error. The weights of RBFNN and the gain of the robust structure are derived via the Lyapunov synthesis approach. …”
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Data-driven design of shape-programmable magnetic soft materials by Alp C. Karacakol, Yunus Alapan, Sinan O. Demir, Metin Sitti

“…Abstract Magnetically responsive soft materials with spatially-encoded magnetic and material properties enable versatile shape morphing for applications ranging from soft medical robots to biointerfaces. …”
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BINARY OPTION PRICING USING LATTICE METHOD by Donny Citra Lesmana, Natallia Christina, Ravy Ardian Kusuma, Siti Salwa Nabila

“…Results indicate that all three methods converge towards the exact solution, demonstrating their applicability for pricing binary options, with the Kamrad-Ritchken Trinomial method showing superior accuracy due to the lowest mean relative error. …”
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Locally differentially private continuous location sharing with randomized response by Xingxing Xiong, Shubo Liu, Dan Li, Jun Wang, Xiaoguang Niu

“…To continuously enjoy services of location-based applications, one needs to share his or her location information to the corresponding service providers. …”
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Efficient and accurate framework for genome-wide gene-environment interaction analysis in large-scale biobanks by Yuzhuo Ma, Yanlong Zhao, Ji-Feng Zhang, Wenjian Bi

“…Through extensive simulations and real data analyses of UK Biobank data, we demonstrate that SPAGxECCT and SPAGxEmixCCT are scalable to analyze large-scale study cohort, control type I error rates effectively, and maintain power.…”
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A Bi-Temporal Airborne Lidar Shrub-to-Tree Aboveground Biomass Model for the Taiga of Western Canada: Un Modèle Bitemporal de Biomasse Aérienne D’arbuste à D’arbre Pour le Lidar Aé... by Linda Flade, Chris Hopkinson, Laura Chasmer

“…In addition, to ensure that modeled AGB changes do not incorporate systematic error due to differences between older and newer lidar technologies, model transfer tests are required. …”
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Pulsed vector atomic magnetometer using an alternating fast-rotating field by Tao Wang, Wonjae Lee, Mark Limes, Thomas Kornack, Elizabeth Foley, Michael Romalis

“…This high-dynamic-range, ultrahigh-resolution magnetometer offers exceptional versatility for diverse applications.…”
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Steel Defect Detection Based on YOLO-SAFD by Feihong Yu, Jinshan Zhang, Dingdiao Mu

“…However, traditional inspection methods are labor-intensive and error-prone, while existing deep learning-based detection approaches generally suffer from poor performance in industrial defect detection and insensitivity to small defects. …”
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Uncertainty Impact on Aggregator Performance for Peak Shaving by Ismail Arafat, Eduardo Castillo Guerra, Julian Meng

“…A metric for aggregator reserved capacity loss is introduced, giving insight to the detrimental effects of forecasting errors on peak shaving efficacy, encompassing performance, cost, and temporal implications. …”
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TSSA-NBR: A Burned Area Extraction Method Based on Time-Series Spectral Angle with Full Spectral Shape by Dongyi Liu, Yonghua Qu, Xuewen Yang, Qi Zhao

“…TSSA-NBR achieved a Dice Coefficient (DC) of 87.81%, with commission (CE) and omission errors (OE) of 8.52% and 15.58%, respectively, demonstrating robust performance across all regions. …”
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A Precise and Scalable Indoor Positioning System Using Cross-Modal Knowledge Distillation by Hamada Rizk, Ahmed Elmogy, Mohamed Rihan, Hirozumi Yamaguchi

“…User location has emerged as a pivotal factor in human-centered environments, driving applications like tracking, navigation, healthcare, and emergency response that align with Sustainable Development Goals (SDGs). …”
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Clinical Competency in Anesthesia Nursing Education: A Descriptive Cross-Sectional Study at Jundishapur University of Medical Sciences by Ali Khalafi, Sajjad Choopani, Nooshin Sarvi-Sarmeydani

“… Background: Clinical competence is an essential attribute for anesthesia nurses, as it directly influences patient safety, minimizes medical errors, and enhances surgical outcomes. In Iran, ensuring the clinical competence of anesthesia nurses is vital to addressing the growing demands of modern healthcare. …”
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Automated oil spill detection using deep learning and SAR satellite data for the northern entrance of the Suez Canal by Mohamed Zakzouk, Abdulaziz M. Abdulaziz, Islam Abou El-Magd, Abdel Sattar Dahab, Elham M. Ali

“…These results highlight the benefits of region-specific training in improving segmentation quality and reducing errors. This study emphasizes the potential of AI-driven models for real-time oil spill monitoring, with applications in environmental protection and emergency response.…”
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