IIM: an information interaction mechanism for aspect-based sentiment analysis by Le Chen, Lina Ge, Wei Zhou

“…Most existing studies solve aforesaid subtasks as independent tasks or simply unify the two subtasks without making full use of the relationship between tasks to mine the interaction of text information, which leads to low performance for practical applications. Meanwhile, the learning framework for these studies has a label drift phenomenon (LDP) in the process of predictive learning, increasing the learning error rate. …”
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Self-Adaptive Transtibial Prosthesis: Automatic Detection and Compensation of Leg Length Discrepancy by Dimitrie Cristian Fodor, Dragoș Florin Chitariu, Cristian Aghion, Neculai Eugen Seghedin

“…<b>Results:</b> The proposed prosthesis demonstrated efficient compensation of simulated LLD, with a mean relative error of 8.8% for a 1 mm simulation and 7.2% for a 10 mm simulation. …”
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Machine Learning for Dynamic Pressure Coefficient Prediction in Vertical Water Jets by Amin Salemnia, Seyedehmaryam Hosseini Boldaji, Vida Atashi, Manoochehr Fathi-Moghadam

“…The XGBoost model outperformed others, achieving an R-squared of 0.953 and a Root Mean Squared Error (RMSE) of 0.191. Residual analysis validated its better performance, demonstrating that it delivered the most accurate predictions with minimal bias. …”
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Research on Revolving Speed Measurement with Master-Slave Synchronous Timing Mode Based on Different M/T by XU Jing-bo, YIN Xian-yu, CUI Xiao-meng, LIU Zhi-liang, LI Zhao, LI Jun, CHEN Hao-shu

“…A masterslave synchronous timing mode implementation method of revolving speed measurement is put forward based on different M/T aimed at the rotating machinery in this paper The MCU is set to make two timers synchronously count and cooperatively work, and the external trigger pulse generating circuit is designed The external trigger can start the two timers at the same time, and the master timer can stop the slave timer under the condition of counting terminate that makes the two timers achieve synchronization The counting value of master timer can be dynamically set according to the current speed, which makes this method suitable for high speed and low speed measurement applications Experimental results show that the relative measurement error of this method is less than 02‰, has wide measurement range of 5 r/min~20.000r/min, and the processing routine is simple, easy to implement…”
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The use of artificial intelligence in the diagnosis of oral carcinoma by Francesco Gianfreda, Andrea Danieli, Maria Scarpati Cioffari di Castiglione, Marco Gargari, Patrizio Bollero, Mirko Martelli

“…The use of automatic classifiers has improved early diagnosis and operational efficiency in clinical practice, addressing traditional challenges and reducing diagnostic errors. Conclusions: Incorporating AI in diagnosing and managing oral lesions presents significant opportunities for improving clinical outcomes with high accuracy and speed. …”
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Extraction of individual tree attributes using ultra-high-density point clouds acquired by low-cost UAV-LiDAR in Eucalyptus plantations by Mei Zhou, Chungan Li, Zhen Li

“…The root mean square errors (RMSEs) for direct measurements of diameter at breast height (DBH) and tree height were 14.60% (2.18 cm) and 2.69% (0.31 m), respectively. …”
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Energy Characterization Method of Resource-efficient Multiple Voltage Thresholds Sampling by WANG Fei, ZHOU Jiawen, CAI Chao

“…It involves no extra hardware components and has high count rate, rendering it applicable for a range of applications, including oil detection, medical imaging, etc. …”

Towards an automated protocol for wildlife density estimation using camera‐traps by Andrea Zampetti, Davide Mirante, Pablo Palencia, Luca Santini

“…While Wildlife Insights' performance differed greatly between species (recall: badger = 0.15; roe deer = 0.56; fox = 0.75), CT‐DS estimates did not vary significantly; on the contrary, REM systematically overestimated density, with little overlap in standard errors. We conclude that CT‐DS and REM models can be robust to the loss of images when machine learning algorithms are used to identify animals, with the CT‐DS being an ideal candidate for applications in a fully unsupervised framework. …”
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Synthesis of a reversible quantum Vedic multiplier on IBM quantum computers by Mojtaba Noorallahzadeh, Mohammad Mosleh

“…Vedic multipliers offer a crucial foundation in the design and implementation of digital circuits, recognized for their speed, efficiency, ease of calculations, reduction of errors, and broad applicability. Prior investigations of quantum Vedic multipliers have faced obstacles like elevated Quantum Cost (QC), substantial Garbage Output (GO), Constant Input (CI), augmented Gate Count (GC), and CNOT-V/V+ count, resulting in more resource use and implementation intricacy. …”
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Improving GOCI ocean color data under high solar-zenith angle over open oceans using neural networks by Xiaoming Liu, Menghua Wang

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A Fast-Forward Dilute-and-Shoot Multielement Method for Analysis of 33 Elements in Human Whole Blood, Serum, and Urine by Inductively Coupled Plasma Mass Spectrometry: A Streamline... by Sandra Huber, Jörg Michel, Maurice Reijnen, Maria Averina, Bjørn Bolann, Jon Øyvind Odland, Solrunn Hansen, Jan Brox

“…The developed reagent and instrumental setup were applicable to all three matrices. This minimizes the risk of human errors when switching between analyses of the different sample matrices and allows a rapid and easy analysis of whole blood, serum, and urine within one day if needed. …”
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Identification Method of Dynamic Propagation Process of Rock Fracture Based on Ground Penetrating Radar by CHEN Jun, ZHANG Bo, ZHUANG Xingyue, SONG Zhishu, ZHENG Jun

“…An inversion model, developed based on the analysis of phase mutation points and interference extrema, demonstrates remarkable accuracy in locating the spatial coordinates of fracture endpoints. The localization errors for the endpoints of the horizontally propagating fractures are consistently below 2%, proving the reliability of this method for real-time monitoring and early warning of fracture propagation.In contrast, the vertical propagation of fractures presents a more complex scenario. …”
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Optimisation of Crystallisation Recipe for Varied Cloud Points Characteristics in Palm Oil Fractions by John Ting Zhi Zhang, Jeng Shiun Lim

“…The results show root mean sqaure error (RMSE) of 0.8411 for CP 6, 0.4317 for CP 8, and 0.4105 for CP 10, indicating that ANN is sensitive to dataset volumes. …”
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Automation of maritime industry in the era of digitalization by Ismail Abdel Ghafar

“…Technical feasibility combined with compelling economic advantages, such as improved efficiency, reduced human error, and operating costs, are driving adoption, especially in the maritime industry. …”
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A New Method to Convert the DNA Sequence of Human to a QR Code by Sadoon Abdullah, Zahraa Abdulhamid

“…The data were retrieved completely without any error because QR code is reliable and authentic. …”
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Battery Health Diagnosis via Neural Surrogate Model: From Lab to Field by Hojin Cheon, Jihun Jeon, Byungil Jung, Hongseok Kim

“…The proposed model synthesizes the terminal voltage with a mean absolute error of 6.4 mV for lithium–iron–phosphate (LFP) cells and 49 mV for nickel–cobalt–manganese (NCM) battery modules, respectively, which is only 0.4% and 0.29% of the voltage swing. …”
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Multi-point estimation weldment recognition and estimation of pose with data-driven robotics design by Meng XiangYi

“…The results stated that in a dataset comprising diverse weld joint variations, the system achieves a recognition accuracy of over 95% in real-time applications. Concurrently, employing geometric hashing and iterative closest point algorithms enables precise pose estimation of the welding torch with an average error margin of less than 1 mm.…”
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Optimising the Selection of Input Variables to Increase the Predicting Accuracy of Shear Strength for Deep Beams by Mohammed Majeed Hameed, Faidhalrahman Khaleel, Mohamed Khalid AlOmar, Siti Fatin Mohd Razali, Mohammed Abdulhakim AlSaadi

“…The LWLR-GAITH model showed 29.15% to 47.88% higher performance accuracy in terms of root mean square error (RMSE) than the other hybrid models during the test phase. …”
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A Novel Framework for Financial Cybersecurity and Fraud Detection Using XAI-RNN-SGRU by Smarajit Ghosh

“…The introduced method improves data security, scalability, and efficiency in real financial applications. It outperforms current techniques with a bit error rate of 0.00004 and a data protection score of 98.03%, providing secure and reliable financial operations. …”
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Streamflow estimation in the Indus River Basin using a water balance framework and artificial neural networks with satellite- and model-derived global hydro-climatic data sources by Hira Sattar, Tsuyoshi Kinouchi

“…New hydrological insights for the region: Our findings indicate that MERRA2 reanalysis products for P and E provided the least closure error for the IRB, while ERA5 P performed better for the UIB. …”
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