Numerical Analysis of Boring Bar Vibration Response in Internal Turning with Spherical Mass–Rubber Dynamic Vibration Absorber (MR-DVA) by Aufa Ulin Nuha, Wiwiek Hendrowati

“…Vibration control in boring processes is essential to ensure machining accuracy and stability. This study analyzed the vibration response of a boring bar fitted with a combination of three pairs of spherical Mass–Rubber Dynamic Vibration Absorbers (MR-DVAs) with different stiffness constants during internal turning operations on a lathe machine. …”
Get full text

The Effect of Quadriceps Fatigue on Electromyographic Activity of Some Knee Joint Muscles during Stance Phase of Walking by Behrouz Hajilou, Mehrdad Anbarian, Hamed Esmaili, Sara Sadeghi

“…Leg extension machine was used to induce quadriceps fatigue with 50% of one – repetition maximum load. …”
Get full text

Deep Reinforcement Learning and Auto-Differential Evolution Co-Guided Coal Washing by Mingcheng Zuo

“…Coal washing is a complicated process and difficult to control, which has many controlling parameters with strong coupling relationship. It is still a challenge to realize the self-perception, self-adjustment, and self-evaluation of coal washing machine, improve the quality of coal washing, ensure production safety, and reduce labor cost. …”
Get full text

Physical and physiological quality of soybean seeds at three speeds of the harvester by Carla S. S. Paixão, Camila P. Chrispin, Rouverson P. da Silva, Lucas A. S. Girio, Murilo A. Voltarelli

“…The evaluations were performed based on the following parameters: grain temperature, water content, concave opening, cylinder rotation, mechanical damage and electrical conductivity. …”
Get full text

A Combined Prediction Model for Hog Futures Prices Based on WOA-LightGBM-CEEMDAN by Xiang Wang, Shen Gao, Yibin Guo, Shiyu Zhou, Yonghui Duan, Daqing Wu

“…An integrated hog futures price forecasting model based on whale optimization algorithm (WOA), LightGBM, and Complete Ensemble Empirical Mode Decomposition with Adaptive Noise (CEEMDAN) is proposed to overcome the limitations of a single machine learning model with low prediction accuracy and insufficient model stability. …”
Get full text

Federated learning scheme for mobile network based on reputation evaluation mechanism and blockchain by Ming YANG, Xuexian HU, Qihui ZHANG, Jianghong WEI, Wenfen LIU

“…Federated learning is a new distributed machine learning technology, where training tasks are deployed on user side and training model parameters are sent to the server side.In the whole process, participants do not need to share their own data directly, which greatly avoids privacy issues.However, the trust relationship between mobile users in the learning model has not been established in advance, there is hidden safety when users perform cooperative train with each other.In view of the above problems, a federated learning scheme for mobile network based on reputation evaluation mechanism and blockchain was proposed.The scheme allowed the server side to use subjective logic models to evaluate the reputation of participating mobile users and provided them with credible reputation opinions sharing environment and dynamic access strategy interface based on the technique of smart contract of blockchain.Theoretical and experimental analys is results show that the scheme can enable the server side to select reliable users for training.And it can achieve more fair and effective reputation calculations, which improves the accuracy of federated learning.…”
Get full text

Pansharpening Techniques: Optimizing the Loss Function for Convolutional Neural Networks by Rocco Restaino

“…Pansharpening is a traditional image fusion problem where the reference image (or ground truth) is not accessible. Machine-learning-based algorithms designed for this task require an extensive optimization phase of network parameters, which must be performed using unsupervised learning techniques. …”
Get full text

Tailoring neuromuscular dynamics: A modeling framework for realistic sEMG simulation. by Alvaro Costa-Garcia, Shingo Shimoda, Akihiko Murai

“…Potential applications of this research include the development of comprehensive sEMG databases and elucidating the relationship between sEMG signal characteristics and internal neuromuscular parameters. Future research aims to further explore these applications and enhance the model's performance by leveraging emerging technologies such as machine learning. …”
Get full text

Improving the Forecasting Accuracy Based on the Lunar Calendar in Modeling Rainfall Levels Using the Bi-LSTM Method through the Grid Search Approach by Gumgum Darmawan, Budhi Handoko, Defi Yusti Faidah, Dian Islamiaty

“…The aim of this study is to compare rainfall accuracy between the Gregorian and the lunar calendars using the bidirectional long short-term memory (Bi-LSTM) machine learning model through the grid search approach. …”
Get full text

Research on Modification Method of Internal Gearing Power Honing based on Flexible Dressing of Honing Wheel by Lian Xia, Qing Wang, Jiang Han, Xiaoqing Tian

“…Finally，the final tooth surface of the workpiece is calculated according to the optimized motion parameters of honing，and the tooth contact is analyzed. …”
Get full text

Improvement of part service properties under surface plastic deformation treatment by dynamic methods by Alexandra Sergeyevna Shvedova

“…The process of improving the surface layer quality and service properties of the machine parts in response to the treatment of the surface plastic deformation (SPD) using the dynamic methods is studied. …”
Get full text

Design and Fabrication of a Mobile Water Supply System For Drip Irrigation. by Lutwetwe Shadrack

“…The specific objectives will entail the determination of pertinent parameters for the conceptual design and coming up with the system layout generated from 3D modeling software (DS SOLID WORKS), selecting material, sizing the components that are necessary for the machine, and fabricating the prototype. …”
Get full text

Carbon Nanotubes Decorated with Nickel or Copper as Anti-Wear and Extreme-Pressure Additives for Greases by Magdalena Skrzypek, Łukasz Wojciechowski, Jarosław Kałużny, Sławomir Boncel, Adam A. Marek, Tomasz Runka, Marek Nowicki, Rafał Jędrysiak, Szymon Ruczka, Paulina Błaszkiewicz

Get full text

Analisis Pengendalian Mutu pada Asam Lemak Bebas Minyak Kelapa Sawit Menggunakan Metode SQC by Rizky Syaputra, Sofiyanurriyanti Sofiyanurriyanti Sofiyanurriyanti

“…This observation aims to determine the parameters of free fatty acids in PT. Socfindo Indonesia Seunagan Plantation. …”
Get full text

USE OF THE RAMP METERING SYSTEM AT TWO-LEVEL JUNCTIONS by A. N. Novikov, I. A. Novikov, A. G. Shevtsova, A. G. Burlutskaya

“…The use of intelligent transport systems in cities and urban agglomerations traffic management allows minimizing vehicles delays and such method is quite topical for traffic organization at peak times and reduction of accidents through the use of intelligent machine control of the vehicle flows.Results. The authors develop the approach to the intelligent transport systems’ usage at the entrance areas to the cities and urban agglomerations, which takes into account changes in the basic parameters of traffic flow and geometric parameters of transport interchanges.Conclusion. …”
Get full text

Performance analysis of dual-fuel engines using acetylene and microalgae biodiesel: The role of fuel injection timing by M. Sonachalam, R. Jayaprakash, V. Manieniyan, P.S. Raghavendra Rao, G. Vinodhini, Manish Sharma, Teku Kalyani, Mahammadsalman Warimani, Hasan Sh Majdi, T.M. Yunus Khan, Abdul Saddique Shaik, Keerthi Shetty

“…Optimization of the engine parameters ensured that key metrics, such as brake power (BP) and brake-specific fuel consumption (BSFC), remained within acceptable limits. …”
Get full text

High-density lipoprotein cholesterol subfraction HDL2 is associated with improved endothelial function in systemic lupus erythematosus by Tze Ping Loh, Lieng Hsi Ling, Anselm Mak, Lingli Gong, Nien Yee Kow, Chun En Yau, Sen Hee Tay, Ainsley Ryan Yan Bin Lee, Cheryl Kai Ting Chua, Wan Ling Cheng, Avery Joy Li Chia, Shi Yin Wong, Bernett Teck Kwong Lee

“…In a multiple linear regression model, HDL2 (β=0.024, SE=0.012, p<0.05) remained an independent predictor of higher FMD after adjusting for age, body mass index, LDL1 and systolic blood pressure. The machine learning model included parameters such as HDL2 (positive association), prednisolone dose, LDL cholesterol and LDL1 for prediction of FMD (r=0.433, p<0.01). …”
Get full text

Sustainability analysis of tool wear, energy efficiency, surface quality, and energy during dry, MQL, and wet turning of Inconel 718 by Muhammad Adnan Khan, Riaz Ahmad, Syed Husain Imran Jaffery, Shahid Ikramullah Butt, Muhammad Salman Khan, Danyal Zahid

“…This study explores the effects of various cooling conditions and input parameters such as feed rate, cutting speed, and depth of cut on machining performance during turning of Inconel 718 using coated carbide tools. …”
Get full text

Optimization of AA6351-SiC-B4C Hybrid Composites in Wire EDM Using Grey Relation Technique by Sreeram Hariharan, Uthayakumar Marimuthu, Thirumalai Kumaran Sundaresan, Suresh Kumar Shanmugam, Rajesh Kanna Govindhan Radhakrishnan, Dariusz Mierzwiński, Janusz Walter

“…The current was identified to be the major contributing parameter for the machining of the composite for the output parameters considered. …”
Get full text

Deep Learning-Based Gain Estimation for Multi-User Software-Defined Radios in Aircraft Communications by Viraj K. Gajjar, Kurt L. Kosbar

“…A deep neural network was trained to estimate the GGD parameters based on the parameters of the modulators. …”
Get full text