An experimental analysis of mechanical properties for a dissimilar pattern structure in the 3-D printing of a PLA5F filament using the Taguchi method by Thamizh Selvan S, Mohandass M

“…Due to its tensile properties and impact strength resistance, these settings can be utilized in potential application in a wide variety of machine parts and vehicle components.…”
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Quantized convolutional neural networks: a hardware perspective by Li Zhang, Olga Krestinskaya, Mohammed E. Fouda, Ahmed M. Eltawil, Khaled Nabil Salama

“…With the rapid development of machine learning, Deep Neural Network (DNN) exhibits superior performance in solving complex problems like computer vision and natural language processing compared with classic machine learning techniques. …”
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Numerical modeling and experimental estimates of structural member fatigue characteristics by Yu. P. Man’shin, E. Yu. Man’shina

“…Based on the analysis of existing methods, it is required to develop recommendations for the calculation of the endurance parameters of structural parts of the agricultural machines. …”
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Investigation of the Applicability of Acoustic Emission Signals for Adaptive Control in CNC Wood Milling by Miroslav Dado, Peter Koleda, František Vlašic, Jozef Salva

“…The results showed that AE signals were sensitive to changes in machining parameters, with higher spindle speeds and feed rates producing increased signal amplitudes and distinct frequency peaks, indicating enhanced cutting efficiency. …”
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Simulation and Evaluation of the Performance of Pneumatic Residual Film Recycler Comb Teeth by Sen Jiang, Baiyu Chen, Haojie Jiang, Pengfei Guo, Xufeng Wang, Can Hu, Wensong Guo

“…This study can provide a reference for the structural design and optimization of working parameters of future deep tillage machines.…”
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A Statistical Optimization Method for Sound Speed Profiles Inversion in the South China Sea Based on Acoustic Stability Pre-Clustering by Zixuan Zhang, Ke Qu, Zhanglong Li

“…Aiming at the problem of accuracy degradation caused by the mixing of spatiotemporal disturbance patterns in sound speed profile (SSP) inversion using the traditional geographic grid division method, this study proposes an acoustic stability pre-clustering framework that integrates principal component analysis and machine learning clustering. Disturbance mode principal component analysis is first used to extract characteristic parameters, and then a machine learning clustering algorithm is adopted to pre-classify SSP samples according to acoustic stability. …”
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Analysis and evaluation of the effectiveness of methods for ensuring the quality of service for software-defined networks of the standard 5G/IMT-2020 by Behrooz Daneshmand

“…QoS requirements for 5G networks have been defined on the basis of three main categories of use cases: extreme mobile broadband (xMBB), massive machine type communications (mMTC) IoT/M2M devices, and highly reliable М2М-communication (ultra-reliable machine-type communications – uMTC). …”
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Water Quality Prediction Using Artificial Intelligence Algorithms by Theyazn H. H Aldhyani, Mohammed Al-Yaari, Hasan Alkahtani, Mashael Maashi

“…The used dataset has 7 significant parameters, and the developed models were evaluated based on some statistical parameters. …”
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Traffic Incident Clearance Time Prediction and Influencing Factor Analysis Using Extreme Gradient Boosting Model by Jinjun Tang, Lanlan Zheng, Chunyang Han, Fang Liu, Jianming Cai

“…This study applies the extreme gradient boosting machine algorithm (XGBoost) to predict incident clearance time on freeway and analyze the significant factors of clearance time. …”
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Capacity allocation method for a hybrid energy storage system participating in secondary frequency regulation based on variational mode decomposition by Taiying Zheng, Minghao Ye, Qinghua Wu

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APPLICATION OF PROTECTIVE COATINGS TO IMPROVE OPERATIONAL CHARACTERISTICS OF THE VESSELS by I. M. Abacharaev, M. M. Abacharaev

“…The novelty criterion is that when using it creates the possibility of a priori determination of the composition and structure kavitatsionnogo material coverage for specific components of ships, the details of their machines and mechanisms. The advantage of the new parameter cavitation resistance of the authors in the fact that it allows you to calculate the period (resource) warranty details in the conditions of influence of cavitation. …”
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Synergistic application of artificial intelligence and response surface methodology for predicting and enhancing in vitro tuber production of potato (Solanum tuberosum). by Rajermani Thinakaran, Ecenur Korkmaz, Başak Ünver, Seyid Amjad Ali, Zeshan Iqbal, Muhammad Aasim

“…Sucrose concentration was the most significant factor for all growth parameters, particularly tuber size and weight. RSRA analysis confirmed the significance of the linear effects of sucrose and BAP on tuberization, while auxins primarily regulated tuber size and weight. …”
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Cooling Load Prediction via Support Vector Regression in Individual and Hybrid Approaches by Honglei Yao, Andrew Topper

“…It enhances these models with two cutting-edge optimization methods: Crystal Structure Algorithm and Reptile Search Algorithm. SVR, a machine learning technique renowned for its flexibility and interpretability, is used in this study to capture complex relationships between various building parameters and cooling load. …”
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Analysis of dynamic process models for aviation battery systems by S. I. Gavrilenkov

“…The methodological potential of MMPEP is supported by the possibility of integration with machine learning methods to refine model parameters. …”
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A novel classification method for balance differences in elite versus expert athletes based on composite multiscale complexity index and ranking forests. by Yuqi Cheng, Dawei Wu, Ying Wu, Youcai Guo, Xinze Cui, Pengquan Zhang, Jie Gao, Yanming Fu, Xin Wang

“…We calculated the CMCI and used four machine learning algorithms-Logistic Regression, Support Vector Machine(SVM), Naive Bayes, and Ranking Forest-to combine these features and assess each participant's balance ability. …”
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Numerical Modelling of the Multiphase Flow in an Agricultural Hollow Cone Nozzle by Paweł Karpiński, Zbigniew Czyż, Stanisław Parafiniuk

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Research on the evaluation method of cooperative jamming effectiveness based on IPSO-ELM by A. Tianjian Yang, B. Xing Wang, C. Siyi Cheng, D. You Chen, E. Xi Zhang

“…For the problem of evaluating the effectiveness of cooperative jamming to group network radar by formation aircraft, a cooperative jamming effectiveness evaluation method based on Improved Particle Swarm Optimization–Extreme Learning Machine (IPSO-ELM) is proposed. First, based on the working parameters of the group network radar and the information fusion rules, the cooperative jamming effectiveness evaluation function is established. …”
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PERFORMANCE EVALUATION OF LIGHTWEIGHT OBJECT DETECTION MODELS FOR REAL-TIME PERSONAL PROTECTIVE EQUIPMENT DETECTION IN THE CONSTRUCTION SITES by Herman, Sandy Alferro Dion, Andik Yulianto

“…Keywords: Object Recognition, Computer Vision, Machine Learning, Lightweight, Personal Protective Equipment, YOLO …”
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An optimized deep learning based hybrid model for prediction of daily average global solar irradiance using CNN SLSTM architecture by Yuvaraj Mariappan, Karthikeyan Ramasamy, Durgadevi Velusamy

“…By using statistical performances metrics, the predictive performance of the developed model is compared with Gated Recurrent Unit, LSTM, CNN-LSTM, SLSTM and machine learning regressor models like Support Vector Machine, Decision Tree, and Random Forest. …”
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Demographic forecast modelling using SSA-XGBoost for smart population management based on multi-sources data. by Jin Wang, Shihan Ma, Qing Lv, Qiang Li

“…The sparrow search algorithm (SSA) is investigated to obtain more reasonable parameters of XGBoost to improve forecast accuracy. …”
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