Study on the Compressive Strength Predicting of Steel Fiber Reinforced Concrete Based on an Interpretable Deep Learning Method by Huiming Wang, Jie Lin, Shengpin Guo

“…The results show that the optimized deep learning model has higher prediction accuracy and generalization ability compared to other traditional ML models. …”
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Short-term prediction of trimaran load based on data driven technology by Haoyun Tang, Rui Zhu, Qian Wan, Deyuan Ren

“…Due to the complex flow interference by side hulls, load prediction has been one of the obstacles to achieve structural health monitoring and intelligent navigation of trimarans. According to the machine learning theory, a short-term prediction method towards trimaran loads is studied by using an optimized data-driven model. …”
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Pure pursuit method use to control unmanned motor grader by R. Yu. Sukharev

“…Moreover, the optimal values of the visibility range for various values of the base length, base coefficient and machine speed have been defined according to the proposed efficiency criterion.Results. …”
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基于SVM与GA参数优化的齿轮箱断齿故障诊断方法研究 by 张星辉, 康建设, 曹端超, 孙磊, 滕红智

“…A new method of gearbox fault diagnosis based on SVM（Support vector machine） and GA（Genetic algorithm）which is used to optimize parameters is presented.Firstly,the raw vibration signal is preprocessed by Time Synchronous Average algorithm.Then,the signal wavelet packet decomposition is carried out,standard deviation of wavelet packet coefficients of the signals is considered as the fault feature vector,and the normalization process of the fault feature vector is carried out.In the end,the fault feature vector is used as the input of SVM.In this process,the Daubechies order,wavelet packet decomposition level,c and g of SVM are optimized by GA.After that,the optimized parameter is used in training model which will be used for fault diagnosis.The experimental result shows that SVM and GA can be used to effectively diagnose faults of gearbox.…”
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Analysis of Contact Characteristic of Hollow Tapered Roller Bearing by Fu Yuanning, Yao Tingqiang, Huang Yacheng

“…The tapered roller bearing has great influence on rotary machine with high load,and hollow roller bearing is applied in significant engineering right now.According to Hertz contact theory and FEM,the equivalent three- dimensional simulation model of single roller-ring solid and hollow tapered roller bearing is established in ANSYS separately,the influence rule of various hole rate and load on elastic deformation and contact stress etc is analyzed.As a result,contact stress value is verified by theoretical calculating result.Simultaneously,the analysis one affords reference for optimal design and engineering application of tapered roller bearing.…”
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Supervised contrastive loss helps uncover more robust features for photoacoustic prostate cancer identification by Yingna Chen, Yingna Chen, Feifan Li, Zhuoheng Dai, Ying Liu, Shengsong Huang, Qian Cheng, Qian Cheng

“…Nevertheless, individual heterogeneity persists as a significant factor that impacts discrimination performance.ObjectiveExtracting more reliable features from intricate biological tissue and augmenting discrimination accuracy of the prostate cancer.MethodsSupervised contrastive learning is introduced to explore its performance in photoacoustic spectral feature extraction. Three distinct models, namely the CNN-based model, the supervised contrastive (SC) model, and the supervised contrastive loss adjust (SCL-adjust) model, have been compared, along with traditional feature extraction and machine learning-based methods.ResultsThe outcomes have indicated that the SCL-adjust model exhibits the optimal performance, its accuracy rate has increased by more than 10% compared with the traditional method. …”
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Label-Guided Data Augmentation for Chinese Named Entity Recognition by Miao Jiang, Honghui Chen

“…The LGDA model consists of three key components: a data augmentation module, a label semantic fusion module, and an optimized loss function. …”
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Revealing the Next Word and Character in Arabic: An Effective Blend of Long Short-Term Memory Networks and ARABERT by Fawaz S. Al-Anzi, S. T. Bibin Shalini

“…These output data were processed into Baidu’s Deep Speech model (ASR system) to attain the text corpus. Baidu’s Deep Speech model was implemented to precisely identify the global optimal value rapidly while preserving a low word and character discrepancy rate by attaining an excellent performance in isolated and end-to-end speech recognition. …”
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航空弧齿锥齿轮铣削加工残余应力分析 by 王延忠, 吴林峰, 陈燕燕, 唐文, 吕庆军, 戈红霞, 张祖智

“…The reason of producing residual stress in milling processing of spiral bevel gear by investigating lots of existed literatures is analyzed,and part of three-dimensional model of gear blank and milling tool based on real size is established.The motion of the CNC axes is transformed into the relative position adjustment between the gear blank and the milling cutter.By orthogonal design and changing the ways of milling processing parameters,the influence discipline of different processing parameter to the spiral bevel gear’s residual stress is analyzed by the ABAQUS.A new way of improving the quality and increasing the life span of spiral bevel gear by improving the processing parameter is raised, and it will contribute to the machining optimization technology of spiral bevel gear.…”
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Exoplanet Classification Through Vision Transformers with Temporal Image Analysis by Anupma Choudhary, Sohith Bandari, B. S. Kushvah, C. Swastik

“…This study underscores the importance of further research into optimizing model architectures to enhance automation, performance, and generalization of the model.…”
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六自由度柔性精密传动与定位平台的静态特性分析 by 林超, 邵济明, 才立忠, 纪久祥

“…Firstly,based on the compliant mechanisms,theory of machines and mechanisms and spatial mechanisms,a compliant precision positioning platform with six degrees of freedom and driven by piezoelectric ceramic（ PZT） actuators is designed. …”
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Augmented Reality (AR) for Precision Farming: Enhancing Farmer Decision-Making in Pest Control by Tandi Moti Ranjan, Kumar Yalakala Dinesh

“…This was developed to respond to these challenges through an Augmented Reality (AR) enabled precision farming device to help farmers in optimizing pest management. The combination of this system is to integrate a machine learning model with the data from IoT sensors and drone imaging to predict and visualize pest populations in real-time. …”
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VIS/NIR Spectroscopy as a Non-Destructive Method for Evaluation of Quality Parameters of Three Bell Pepper Varieties Based on Soft Computing Methods by Meysam Latifi Amoghin, Yousef Abbaspour-Gilandeh, Mohammad Tahmasebi, Mohammad Kaveh, Hany S. El-Mesery, Mariusz Szymanek, Maciej Sprawka

“…To optimize wavelength selection, support vector machines (SVMs) were combined with genetic algorithms (GAs), particle swarm optimization (PSO), ant colony optimization (ACO), and imperial competitive algorithm (ICA). …”
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CINNAMON-GUI: Revolutionizing Pap Smear Analysis with CNN-Based Digital Pathology Image Classification [version 1; peer review: 2 approved] by Luca Zammataro

“…Background Medical imaging has seen significant advancements through machine learning, particularly convolutional neural networks (CNNs). …”
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Uncertainty-aware deep learning in healthcare: A scoping review. by Tyler J Loftus, Benjamin Shickel, Matthew M Ruppert, Jeremy A Balch, Tezcan Ozrazgat-Baslanti, Patrick J Tighe, Philip A Efron, William R Hogan, Parisa Rashidi, Gilbert R Upchurch, Azra Bihorac

“…Entrustment could be earned by conveying model certainty, or the probability that a given model output is accurate, but the use of uncertainty estimation for deep learning entrustment is largely unexplored, and there is no consensus regarding optimal methods for quantifying uncertainty. …”
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Adaptive Self-Learning Framework for Resilient Vehicle Classification Through the Integration of Inductive Loops and LiDAR Sensors by Yiqiao Li, Andre Y. C. Tok, Stephen G. Ritchie

“…Consequently, legacy inductive signature-based models may not perform optimally in classifying newer trucks operating on the highways over time. …”
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Anesthesia depth prediction from drug infusion history using hybrid AI by Liang Wang, Yiqi Weng, Wenli Yu

“…Abstract Background Accurately predicting the depth of anesthesia is essential for ensuring patient safety and optimizing surgical outcomes. Traditional regression-based approaches often struggle to model the complex and dynamic nature of patient responses to anesthetic agents. …”
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Efficient BTMS for lithium-ion batteries: A study on PCM/Metal foam, heat pipe, and microchannel integration by Soheil Saeedipour, Ayat Gharehghani, Moeed Rabiei, Amin Mahmoudzadeh Andwari, Sadegh Mehranfar, Carlos Mico Reche, Navid Rabiei

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A Time–Frequency-Based Data-Driven Approach for Structural Damage Identification and Its Application to a Cable-Stayed Bridge Specimen by Naiwei Lu, Yiru Liu, Jian Cui, Xiangyuan Xiao, Yuan Luo, Mohammad Noori

“…Structural damage identification based on structural health monitoring (SHM) data and machine learning (ML) is currently a rapidly developing research area in structural engineering. …”
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High-resolution image inpainting using a probabilistic framework for diverse images with large arbitrary masks by G. Sumathi, M. Uma Devi

“…The most recent image inpainting techniques rely on machine learning models; however, a major limitation of supervised methods is their dependence on end-to-end training. …”
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