Linking machine learning and biophysical structural features in drug discovery by Armin Ahmadi, Shivangi Gupta, Vineetha Menon, Jerome Baudry

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A machine learning approach for predicting treatment response of hyponatremia by Tamaki Kinoshita, Shintaro Oyama, Daisuke Hagiwara, Yoshinori Azuma, Hiroshi Arima

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Enhancement Modelling Based on Electrical Discharge Machining Successive Discharges by Farook Nehad Abed, V. Ramesh, Mohanad Fadhil Jwaid, Nidhi Agarwal, Deepika Koundal, Abdelrahman Mohamed Ibrahim

“…The surface roughness of Inconel 718 is predicted using a sequential discharge model for electrical discharge machining (EDM). To begin with, the EDM single pulse discharge machining process was accurately simulated using the finite-element method (FEM). …”
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A scoping review of robustness concepts for machine learning in healthcare by Alan Balendran, Céline Beji, Florie Bouvier, Ottavio Khalifa, Theodoros Evgeniou, Philippe Ravaud, Raphaël Porcher

“…Our findings offer valuable insights for stakeholders seeking to understand and navigate the robustness of machine learning models during their development, validation, and deployment in healthcare settings, where interpretation of robustness may vary.…”
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Online Scheduling on a Single Machine with Grouped Processing Times by Qijia Liu, Long Wan, Lijun Wei

“…We consider the online scheduling problem on a single machine with the assumption that all jobs have their processing times in [p,(1+α)p], where p>0 and α=(5-1)/2. …”
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Rational redistribution of waste of resources. Manufacturing of equipment for cutting machine by Yu. E. Soloviev, I. A. Kovaleva

“…The staff of the Central laboratory LFMI proposed to use waste knives drop-hummer shop for the manufacture of knives for the chopping of the machine SIMA GEL-30. On the basis of the conducted researches the technological scheme was developed for production of knives for the chopping of the machine SIMA GEL-30 cold cutting of reinforcing bar mill 320 the rolling shop № 1.…”
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Milk adulteration identification using hyperspectral imaging and machine learning by Muhammad Aqeel, Ahmed Sohaib, Muhammad Iqbal, Syed Sajid Ullah

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Microplastic Identification Using Impedance Spectroscopy and Machine Learning Algorithms by Juan Sarmiento, Maribel Anaya, Diego Tibaduiza

“…As a contribution to the solution of this problem, this work presents a microplastic detection and classification methodology that uses an electronic tongue system, impedance spectroscopy, and machine learning algorithms for detecting and classifying microplastics. …”
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Cyberinfrastructure for machine learning applications in agriculture: experiences, analysis, and vision by Lucas Waltz, Sushma Katari, Chaeun Hong, Adit Anup, Julian Colbert, Anirudh Potlapally, Taylor Dill, Canaan Porter, John Engle, John Engle, Christopher Stewart, Hari Subramoni, Scott Shearer, Raghu Machiraju, Osler Ortez, Laura Lindsey, Arnab Nandi, Sami Khanal

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Comparison of Machine Learning Techniques for the Prediction of Compressive Strength of Concrete by Palika Chopra, Rajendra Kumar Sharma, Maneek Kumar, Tanuj Chopra

“…A comparative analysis for the prediction of compressive strength of concrete at the ages of 28, 56, and 91 days has been carried out using machine learning techniques via “R” software environment. …”
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EFFICIENCY OF SERVICE ACTIVITIES FOR SERVICING PRODUCTS OF MACHINE-BUILDING ENTERPRISES by N. V. Arsenieva, L. M. Putyatina, N. V. Tarasova

“…The importance of improving the efficiency of the system of service activities for the maintenance of machine-building products has been outlined. Individual types of service and their features have been analysed. …”
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Design, Construction and Testing of a Dry Sand Sieving Machine by Oladeji Akanni Ogunwole

“…This paper reports on the design, construction and Testing of a dry sand sieving machine. The sample to be sieved is uniformly graded. …”
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Accurate Identification of Cancerlectins through Hybrid Machine Learning Technology by Jieru Zhang, Ying Ju, Huijuan Lu, Ping Xuan, Quan Zou

“…They have been identified through computational identification techniques, but these techniques have sometimes failed to identify proteins because of sequence diversity among the cancerlectins. Advanced machine learning identification methods, such as support vector machine and basic sequence features (n-gram), have also been used to identify cancerlectins. …”
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Globality-Locality Preserving Maximum Variance Extreme Learning Machine by Yonghe Chu, Hongfei Lin, Liang Yang, Yufeng Diao, Dongyu Zhang, Shaowu Zhang, Xiaochao Fan, Chen Shen, Deqin Yan

“…An extreme learning machine (ELM) is a useful technique for machine learning; however, the existing extreme learning machine methods cannot exploit the geometric structure information or discriminate information of the data space well. …”
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Design, Construction and Testing of a Dry Sand Sieving Machine by Oladeji Akanni Ogunwole

“…This paper reports on the design, construction and Testing of a dry sand sieving machine. The sample to be sieved is uniformly graded. …”
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Machine learning in echocardiography-based prediction model of cardiovascular diseases by Zubaire Yasheng, Ruohan Zhao, Ye Zhu, Zisang Zhang, Qing Lv, Mingxing Xie, Li Zhang, Ting Gao

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Assessment of the stress-strain state of profile joints of machine components by V. A. Ilinykh, V. Yu. Lineytsev, O. S. Belkina, E. V. Nepomnyashchikh

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The Machine Translation (MT) of Proverbs in the ENG-PL Language Pair by Romaniuk-Cholewska Dominika

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Credit card fraud detection through machine learning algorithm by Agyan Panda, Bharath Yadlapalli, Zhi Zhou

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A Machine Learning Approach to Predict Air Quality in California by Mauro Castelli, Fabiana Martins Clemente, Aleš Popovič, Sara Silva, Leonardo Vanneschi

“…In this paper, we employ a popular machine learning method, support vector regression (SVR), to forecast pollutant and particulate levels and to predict the air quality index (AQI). …”
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