Machine Learning-Based Condition Monitoring for PV Systems: State of the Art and Future Prospects by Tarek Berghout, Mohamed Benbouzid, Toufik Bentrcia, Xiandong Ma, Siniša Djurović, Leïla-Hayet Mouss

“…It also discusses the extension of machine learning to knowledge-driven approaches, including generative models such as adversarial networks and transfer learning. …”
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Revisiting Chiral Recognition Mechanism on Chicken Alpha 1-Acid Glycoprotein: Location of Chiral Binding Sites and Insight into Chiral Binding Mechanism by Jun Haginaka, Taku Yamashita, Hirofumi Tsujino, Mitsuhiro Arisawa

“…Based on chromatographic properties of native and W26-modified cAGP columns and docking simulations of studied compounds into the generated model structure of cAGP, the chiral binding sites were located on cAGP and the chiral binding mechanism was discussed. …”
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Development and evaluation of a stochastic daily rainfall model with long-term variability by A. F. M. K. Chowdhury, A. F. M. K. Chowdhury, N. Lockart, G. Willgoose, G. Kuczera, A. S. Kiem, N. Parana Manage

“…The primary objective of this study is to develop a stochastic rainfall generation model that can match not only the short resolution (daily) variability but also the longer resolution (monthly to multiyear) variability of observed rainfall. …”
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HierTTS: Expressive End-to-End Text-to-Waveform Using a Multi-Scale Hierarchical Variational Auto-Encoder by Zengqiang Shang, Peiyang Shi, Pengyuan Zhang, Li Wang, Guangying Zhao

“…Therefore, we propose HierTTS, a highly expressive end-to-end text-to-waveform generation model. It deeply couples the hierarchical properties of speech with hierarchical variational auto-encoders and models multi-scale latent variables, at the frame, phone, subword, word, and sentence levels. …”
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Cross section generation for a conceptual horizontal, compact high temperature gas reactor by Junsu Kang, Volkan Seker, Andrew Ward, Daniel Jabaay, Brendan Kochunas, Thomas Downar

“…A macroscopic cross section generation model was developed for the conceptual horizontal, compact high temperature gas reactor (HC-HTGR). …”
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The future of software-controlled cooking by Jonathan David Blutinger, Christen Cupples Cooper, Shravan Karthik, Alissa Tsai, Noà Samarelli, Erika Storvick, Gabriel Seymour, Elise Liu, Yorán Meijers, Hod Lipson

“…Food printing is an application of additive manufacturing that utilizes user-generated models to construct 3D shapes from edible food inks and laser cooking uses high-energy targeted light for high-resolution tailored heating. …”
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Business Analytics in Telemarketing: Cost-Sensitive Analysis of Bank Campaigns Using Artificial Neural Networks by Nazeeh Ghatasheh, Hossam Faris, Ismail AlTaharwa, Yousra Harb, Ayman Harb

“…It proposes enhanced Artificial Neural Network models (i.e., cost-sensitive) to mitigate the dramatic effects of highly imbalanced data, without distorting the original data samples. The generated models are evaluated, validated, and consequently compared to different machine-learning models. …”
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Optimal distribution of heat exchanger area for maximum efficient power of thermoelectric generators by Lei Tian, Lingen Chen, Tingting Ren, Yanlin Ge, Huijun Feng

“…Based on the multi-element thermoelectric generator model established in the previous literature, finite-time thermodynamic theory is used to deduce the efficient power expression of the thermoelectric generator. …”
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Extreme scenario generation for renewable energies by Hongqiao Peng, Yuanyuan Lou, Hui Sun, Zhengmin Zuo, Yuliang Liu, Chenxi Wang

“…A case study on a real‐world dataset shows that the authors’ proposed method has superior performance over the state‐of‐the‐art generative models in terms of extreme scenario generation. …”
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Artificial intelligence systems for the design of magic shotgun drugs by José Teófilo Moreira-Filho, Meryck Felipe Brito da Silva, Joyce Villa Verde Bastos Borba, Arlindo Rodrigues Galvão Filho, Eugene N Muratov, Carolina Horta Andrade, Rodolpho de Campos Braga, Bruno Junior Neves

“…We discuss how classical ML methods, cutting-edge generative models, and multi-task deep neural networks can help de novo design and hit-to-lead optimization of multi-target drugs. …”
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A New Loss Generation Body Force Model for Fan/Compressor Blade Rows: An Artificial-Neural-Network Based Methodology by Syamak Pazireh, Jeffrey J. Defoe

“…Recently, accurate, uncalibrated turning force models have been developed, but accurate loss generation models have typically required calibration against higher fidelity computations (especially when flow separation occurs). …”
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Probability Density Function Characterization for Aggregated Large-Scale Wind Power Based on Weibull Mixtures by Emilio Gómez-Lázaro, María C. Bueso, Mathieu Kessler, Sergio Martín-Martínez, Jie Zhang, Bri-Mathias Hodge, Angel Molina-García

“…The Weibull probability distribution has been widely applied to characterize wind speeds for wind energy resources. Wind power generation modeling is different, however, due in particular to power curve limitations, wind turbine control methods, and transmission system operation requirements. …”
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Vision Transformer and Language Model Based Radiology Report Generation by Mashood Mohammad Mohsan, Muhammad Usman Akram, Ghulam Rasool, Norah Saleh Alghamdi, Muhammad Abdullah Aamer Baqai, Muhammad Abbas

“…Auto report generation scenarios in medical imaging through caption generation models is one of the applied scenarios for language models and have strong social impact. …”
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Towards Semi-Automatic Generation of a Steady State Digital Twin of a Brownfield Process Plant by Seppo Sierla, Lotta Sorsamäki, Mohammad Azangoo, Antti Villberg, Eemeli Hytönen, Valeriy Vyatkin

“…The methodology consists of: (1) extracting information from piping and instrumentation diagrams, (2) converting the information to a graph format, (3) applying graph algorithms to preprocess the graph, (4) generating a simulation model from the graph, (5) performing manual expert editing of the generated model, (6) configuring the calculations done by simulation model elements and (7) parameterizing the simulation model according to recent process measurements in order to obtain a digital twin. …”
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Electromechanical transient modeling of energy storage based on virtual synchronous machine technology by Juntao Cui, Zhao Li, Ping He, Zhijie Gong, Jie Dong

“…This paper proposes an electromechanical transient method to build a battery energy storage system-based virtual synchronous generator model, suitable for a large-scale grid. This model consists of virtual synchronous generator control, system limitation and the model interface. …”
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Bonferroni Probabilistic Ordered Weighted Averaging Operators Applied to Agricultural Commodities’ Price Analysis by Luis F. Espinoza-Audelo, Maricruz Olazabal-Lugo, Fabio Blanco-Mesa, Ernesto León-Castro, Victor Alfaro-Garcia

“…In this situation, it is necessary to generate models that allow the incorporation of the knowledge and expectations of the markets and thus include in the results obtained not only the historical information, but also the present and future information. …”
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Elucidating dislocation core structures in titanium nitride through high-resolution imaging and atomistic simulations by J. Salamania, D.G. Sangiovanni, A. Kraych, K.M. Calamba Kwick, I.C. Schramm, L.J.S. Johnson, R. Boyd, B. Bakhit, T.W. Hsu, M. Mrovec, L. Rogström, F. Tasnádi, I.A. Abrikosov, M. Odén

“…Density-functional theory and classical interatomic potential simulations complement STEM observations by recovering the atomic structure of the different dislocation types, estimating Peierls stresses, and providing insights on the chemical bonding nature at the core. The generated models of the dislocation cores suggest locally enhanced metal–metal bonding, weakened Ti-N bonds, and N vacancy-pinning that effectively reduces the mobilities of {110}〈11–0〉 and {111}〈112–〉 dislocations. …”
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AI-Driven De Novo Design and Molecular Modeling for Discovery of Small-Molecule Compounds as Potential Drug Candidates Targeting SARS-CoV-2 Main Protease by Alexander M. Andrianov, Mikita A. Shuldau, Konstantin V. Furs, Artsemi M. Yushkevich, Alexander V. Tuzikov

“…In this study, two deep learning generative models were developed and used in combination with molecular modeling tools for de novo design of small molecule compounds that can inhibit the catalytic activity of SARS-CoV-2 main protease (Mpro), an enzyme critically important for mediating viral replication and transcription. …”
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Children’s Activity Classification for Domestic Risk Scenarios Using Environmental Sound and a Bayesian Network by Antonio García-Domínguez, Carlos E. Galván-Tejada, Ramón F. Brena, Antonio A. Aguileta, Jorge I. Galván-Tejada, Hamurabi Gamboa-Rosales, José M. Celaya-Padilla, Huizilopoztli Luna-García

“…Likewise, models were generated using three classifiers: naive Bayes, semi-naive Bayes and tree-augmented naive Bayes. The generated models, combining the methods of feature selection and the classifiers used, present accuracy of greater than 97% for most of them, with which we can conclude the efficiency of the proposal of the present work in the recognition of potentially detonating activities of domestic accidents.…”
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Remote sensing of sea surface glacial meltwater on the Antarctic Peninsula shelf by B. Jack Pan, Michelle M. Gierach, Michael P. Meredith, Rick A. Reynolds, Oscar Schofield, Alexander J. Orona

“…In this study, we develop a first-generation model for quantifying SSGM that can be applied to both spaceborne (MODIS-Aqua) and airborne (PRISM) ocean color platforms. …”
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