Smart Cognitive HMI With Automated Knowledge Extraction for Machine Tool by Jongsu Park, Jinho Son, Seongwoo Cho, Jumyung Um

“…In the field of machine tools, it is general to use facilities from various vendors with different interfaces. …”
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Unsupervised and Semisupervised Machine Learning Frameworks for Multiclass Tool Wear Recognition by Maryam Assafo, Peter Langendoerfer

“…The underlying methods include Laplacian score, sparse autoencoder (SAE), stacked SAE (SSAE), self-organizing map, Softmax, support vector machine, and random forest. For the semisupervised frameworks, we considered designs where labeled data influence only feature learning, classifier building, or both. …”
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Training of Production Managers for Machine-building Enterprises by I. A. Ivanov, G. E. Persiyanova

“…The result is an acute shortage of qualified top managers and middle managers, whereas university graduates can’t find specialty related occupation.To assess the needs of machine-building industry in production managers and various professionals a study was conducted at Novocherkassk Electric Locomotive Plant, which is the largest machine-building enterprise in Russia for production of mainline freight and passenger electric locomotives. …”
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ML-AMPSIT: Machine Learning-based Automated Multi-method Parameter Sensitivity and Importance analysis Tool by D. Di Santo, C. He, F. Chen, L. Giovannini

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Dynamics Model of 4-PRP+3-UPS&PU Hybrid Machine Tool with Redundant Drive by Liu Na, Mei Ying, Wang Shusen, Hu Weiwei

“…The Lagrange method is applied to build dynamics model of the 6 DOF redundantly actuated hybrid machine tool. …”
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Automated Recipe Generation AI Tool from Food Images using Machine Learning. Approach for Ingredient Extraction and Cooking Instructions by Lwamaza, Eddy, Nuwasiima, Happy

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BIM-Based Machine Learning Application for Parametric Assessment of Building Energy Performance by Panagiotis Tsikas, Athanasios Chassiakos, Vasileios Papadimitropoulos, Antonios Papamanolis

“…Digital tools are currently available for performing energy assessment analyses and can efficiently handle complex and technically demanding buildings. …”
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Aplicación de una herramienta avanzada de análisis de datos en el entorno de la construcción = Application of advanced data analysis tool in building environment. by Arrate Hernández-Arizaga, Ana Picallo-Pérez, José María Sala-Lizarraga

“…The aim of this work is to promote FDD with machine learning applications in building environment. …”
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Time Series Methods and Business Intelligent Tools for Budget Planning—Case Study by Katarzyna Grobler-Dębska, Rafał Mularczyk, Bartłomiej Gawęda, Edyta Kucharska

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TEICHI and the Tools Paradox by Sebastian Pape, Christof Schöch, Lutz Wegner

“…In fact, we suggest that tool developers need to find ways of turning these conflicting aims into concurrent aims if they want to build successful tools and broaden their user base.…”
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Short-Term Power Prediction of Building Integrated Photovoltaic (BIPV) System Based on Machine Learning Algorithms by R. Kabilan, V. Chandran, J. Yogapriya, Alagar Karthick, Priyesh P. Gandhi, V. Mohanavel, Robbi Rahim, S. Manoharan

“…One of the biggest challenges is towards ensuring large-scale integration of photovoltaic systems into buildings. This work is aimed at presenting a building integrated photovoltaic system power prediction concerning the building’s various orientations based on the machine learning data science tools. …”
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Review on the Application of Remote Sensing Data and Machine Learning to the Estimation of Anthropogenic Heat Emissions by Lingyun Feng, Danyang Ma, Min Xie, Mengzhu Xi

“…Commonly applied methods for estimating anthropogenic heat include the inventory method, the energy balance equation method, and the building model simulation method. In recent years, the rapid development of computer technology and the availability of massive data have made machine learning a powerful tool for estimating anthropogenic heat fluxes and assessing its effects. …”
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Predicting Energy and Emissions in Residential Building Stocks: National UBEM with Energy Performance Certificates and Artificial Intelligence by Carlos Beltrán-Velamazán, Marta Monzón-Chavarrías, Belinda López-Mesa

“…The nUBEM is a powerful tool for analyzing residential building stock and supporting data-driven decarbonization strategies. …”
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Statement of the Problem of Determining the Technical Appearance and Design Characteristics of Multi-Apartment Residential Buildings Based on the Expert Systems Method by Alexander A. Merkulov, Yury N. Razoumny, Olga A. Saltykova, Ivan V. Stepanyan

“…The advantages and disadvantages of machine learning methods and various types of logical inference in expert systems for determining the technical appearance and design characteristics of multiapartment residential buildings are analyzed. …”
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Predictive Analytics in Construction: Multi-Output Machine Learning Models for Abrasion Resistance by Shaheen Mohammed Saleh Ahmed, Hakan Güneyli, Süleyman Karahan

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Improving Thermospheric Density Predictions in Low‐Earth Orbit With Machine Learning by Giacomo Acciarini, Edward Brown, Tom Berger, Madhulika Guhathakurta, James Parr, Christopher Bridges, Atılım Güneş Baydin

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COMPILATION METHOD AND EXPERIMENTAL STUDY OF GRINDING MACHINE SPINDLE LOAD SPECTRUM by CHI YuLun, LI HaoLin

“…With high precision grinding technology development,the requirement for machine tool reliability is higher and higher.The load spectrum of grinding is key scientific basis of building the grinding machine spindle reliability experiment platform.Based on bearing ring machine tool grinding process,the load spectrum signal characteristic and processing method is studied through long time grinding spindle load measurement,recoding and analysis.Then,the compilation method is provided to get load spectrum.At last,the programmed load spectrum for "idle-grinding-idle"is drawn,which is consistent with real field load.It provide the loading condition and theory basis for grinding machine tool spindle reliability experiment,and also is very important to improve machine tool spindle design.…”
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Analyzing the relationship between gene expression and phenotype in space-flown mice using a causal inference machine learning ensemble by James A. Casaletto, Ryan T. Scott, Makenna Myrick, Graham Mackintosh, Hamed Chok, Amanda Saravia-Butler, Adrienne Hoarfrost, Jonathan M. Galazka, Lauren M. Sanders, Sylvain V. Costes

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Effect of a Rapid Tooling Technique in a 3D Printed Part for Developing an EDM Electrode by Turki Alamro, Mohammed Yunus, Rami Alfattani, Ibrahim A. Alnaser

“…The copper-coated FDM (CCF) and solid copper (SC) electrodes are used to conduct experiments on a die-sinking EDM machine using tool alloy steel as a workpiece. The CCF polymer electrode can be efficiently used in EDM operations as the build time of any complex shape was substantially reduced. …”
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A recurrence model for non-puerperal mastitis patients based on machine learning. by Gaosha Li, Qian Yu, Feng Dong, Zhaoxia Wu, Xijing Fan, Lingling Zhang, Ying Yu

“…<h4>Conclusion</h4>The machine learning model developed in this study, serving as an effective tool for predicting NPM recurrence, aids doctors in making more individualized treatment decisions, thereby enhancing therapeutic efficacy and reducing the risk of recurrence.…”
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