Trajectory Learning Using HMM: Towards Surgical Robotics Implementation by Juliana Manrique-Cordoba, Carlos Martorell-Llobregat, Miguel Ángel de la Casa-Lillo, José María Sabater-Navarro

“…These findings support the proposed method as an effective strategy for encoding, simplifying, and learning robotic trajectories in surgical applications.…”
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Automated Computer Vision System for Urine Color Detection by Ban Shamil Abdulwahed, Ali Al-Naji, Izzat Al-Rayahi, Ammar Yahya, Asanka G. Perera

“…In the comparison with the current methods the proposed system has maximum accuracy and minimum error rate. This methodology can pave the way for an additional case study in medical applications, particularly in diagnosis, and patient health monitoring. …”
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SDKU-Net: A Novel Architecture with Dynamic Kernels and Optimizer Switching for Enhanced Shadow Detection in Remote Sensing by Gilberto Alvarado-Robles, Isac Andres Espinosa-Vizcaino, Carlos Gustavo Manriquez-Padilla, Juan Jose Saucedo-Dorantes

“…Additionally, the model’s efficient training process, requiring only 75 epochs, highlights its potential for resource-constrained applications. These results underscore the robustness and adaptability of SDKU-Net, paving the way for advancements in shadow detection and segmentation across diverse fields.…”
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Vector Field-Based Robust Quadrotor Landing on a Moving Ground Platform by Woohyun Byun, Soobin Huh, Hyeokjae Jang, Suhyeong Yu, Sungwon Lim, Seokwon Lee, Woochul Nam

“…The autonomous landing of unmanned aerial vehicles (UAVs) on moving platforms has potential applications across various domains. However, robust landing remains challenging because the detection reliability of UAVs decreases when the UAV is close to a moving platform. …”
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Versatile parallel signal processing with a scalable silicon photonic chip by Shihan Hong, Jiachen Wu, Yiwei Xie, Xiyuan Ke, Huan Li, Linyan Lyv, Yingying Peng, Qingrui Yao, Yaocheng Shi, Ke Wang, Leimeng Zhuang, Pan Wang, Daoxin Dai

“…Here, we propose a scalable parallel signal processor on silicon for versatile applications by interleaving wavelength and temporal optical dimensions. …”
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Prediction of time averaged wall shear stress distribution in coronary arteries’ bifurcation varying in morphological features via deep learning by Mohammad Hossein Sarkhosh, Mohammad Hossein Sarkhosh, Hadis Edrisnia, Mohammad Reza Raveshi, Mahkame Sharbatdar

“…Our results indicate that the proposed algorithms can generate results in less than one second, showcasing their suitability for applications in terms of computational efficiency.DiscussionFurthermore, the DL-based predictions demonstrate strong agreement with results from CFD simulations, with a normalized mean absolute error of only 2.53% across various cases.…”
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Long-Range Distributed Vibration Sensing Based on Phase Extraction From Phase-Sensitive OTDR by Guangyao Yang, Xinyu Fan, Shuai Wang, Bin Wang, Qingwen Liu, Zuyuan He

“…We found that the laser phase noise and phase extraction error caused by the intensity noise in photodetection contribute to the total phase noise. …”
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CALPHAD-enabled design of metallic glasses with target properties: Gold-based glass for jewellery by Owain S. Houghton, Yurii P. Ivanov, Nikolaos T. Panagiotopoulos, A. Lindsay Greer

“…The compositions of current metallic glasses are designed to ensure glass formation, and they can be far from optimal for intended applications. The composition changes needed to improve specific properties can lead to a loss of glass-forming ability. …”
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RESE-CNN: Residual Squeeze-and-Excitation Network for High-Contrast Optical Tomography Reconstruction by Zhu Yingkuang, Pan Zhenhua, Li Huajun, Chen Jianyang, Sheng Yihao

“…Optical tomography, a critical component of process tomography, is an important tool for determining the absorption coefficient of cross-sectional media, with significant applications in multi-phase flow analysis, chemical processing, and combustion studies. …”
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ARTIFICIAL NEURAL NETWORKS FOR PREDICTING SUGARCANE STALK AND TOTAL BIOMASS YIELD BASED ON MICRONUTRIENT RATES APPLIED IN THE PLANTING FURROW AND TO THE LEAVES by Alfredo Bonini Neto, Maikon V. da Silva Lira, Guilherme C. Meirelles, Luiz F. de M. Santos, Carolina dos S. B. Bonini, Reges Heinrichs

“…The model incorporates the effects of micronutrient applications, both in the planting furrow and on the leaves, effectively capturing the complex interactions that influence crop yield. …”
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An adaptive processing model for large superalloy pipeline components by LUO Ziyan, QIN Xiansheng, WANG Zhanxi, LIU Weiwei, LI Shulu

“…At present, the theoretical analysis methods for deformation analysis and error compensation in the adaptive machining of high-temperature alloys are not clear; The precise physical model reconstruction technology is not yet mature and engineering applications are not yet popularized. …”
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0.91 V reference, 3.3 ppm/°C Sub-BGR with second-order compensation and improved PSRR by Chokkakula Ganesh, Satheesh Kumar S, A. Shanthi, Sk Shoukath Vali

“…The second-order compensation method is implemented for design through an optimized error amplifier and a resistor network with a significantly better temperature coefficient performance. …”
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Least-Squares-Based Deep Learning for Sentinel-2 Derived Bathymetry: A Case Study on Anegada’s Southern Coast by Y. Liu, A. Amiri-Simkooei, R. Lindenbergh, M. Snellen

“…LBSDL depth estimation achieved a root-mean-square error (RMSE) of 2.74 m, representing around 10% of the maximum observed depth, with the best performance in the 2–15 m depth range. …”
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Modeling and Simulation of Eddy Current Dissipation Magnetic Acceleration Noise of Space Inertial Sensors by Pengxuan Li, Zhiyin Sun, Wei Gao, Bingzhang Cao, Yunzhao Li, Liyi Li, Lei Wang

“…Using the parameters of the LPF’s TM, the calculation error of the semi-analytical model is reduced by about 4.64% compared with the approximate analytical model. …”
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Design of annular-shaped heater for measurement of anisotropic thermal conductivity using 3-ω method by Doheon Koo, Junyoung Park, Mugyeom Jung, Sangyeun Park, Hye Seok Na, Wondo Kim, Hyun Sung Park, Hongyun So

“…The results indicate that the proposed methodology, which was derived from the line heater, is applicable when the heater radius is sufficiently large (>500 μm). …”
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Combination of a Green and a Traditional Method for Estimating Relative and Absolute Ink Age: A Case Study of Ballpoint Pen Ink Dating in Vietnam by Anh Duc Hoang, Minh Binh Tu, Thi Thao Ta, Manh Hung Hoang

“…The combination of the abovementioned methods demonstrated an acceptable error margin, affording highly practical applications in modern forensic science.…”
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Experimental Demonstration of Continuous Sensor Data Monitoring Using Neural Network-Based Optical Camera Communications by Md. Faisal Ahmed, Moh. Khalid Hasan, Md. Shahjalal, Md. Morshed Alam, Yeong Min Jang

“…The proposed scheme is flicker-free in different frequencies and applicable in both static and mobile scenarios. A neural network is designed for LED detection and improving the bit-error-rate in mobile scenarios. …”
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Physics-informed machine learning to predict solvatochromic parameters of designer solvents with case studies in CO2 and lignin dissolution by Mood Mohan, Nikhitha Gugulothu, Sreelekha Guggilam, T. Rajitha Rajeshwar, Michelle K. Kidder, Jeremy C. Smith

“…The polarity of solvents plays a critical role in various research applications, particularly in their solubilities. Polarity is conveniently characterized by the Kamlet-Taft parameters that is, the hydrogen bonding acidity (α), the basicity (β), and the polarizability (π∗). …”
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An Ultrashort-Term Wind Power Prediction Method Based on a Switching Output Mechanism by Rongqiang Feng, Biheng Wang, Xueqiong Wu, Chenxi Huang, Lei Zhao, Wei Tang, Kun Zhang, Xiaoming Huang, Wei Ding

“…The normalized root mean square error (NRMSE) for the 4 h ahead predicted power reaches 0.0907, which verified the validity and applicability of the proposed model.…”
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Machine learning assisted design of low-carbon aluminosilicate cementitious composites with diverse raw materials and target mechanical strength by Jinyang Jiang, Yi Liu, Junlin Lin, Tao Yang, Fengjuan Wang

“…The well-trained strength prediction model is applicable for almost all supplementary cementitious materials incorporated composites regardless of the diversity of material origin, as long as the proportion of each material is provided with its key chemical constituents. …”
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