AI and semantic ontology for personalized activity eCoaching in healthy lifestyle recommendations: a meta-heuristic approach by Ayan Chatterjee, Nibedita Pahari, Andreas Prinz, Michael Riegler

“…Methods This study proposes a semantic ontology model to annotate the AI predictions, forecasting outcomes, and personal preferences to conceptualize a personalized recommendation generation model with a hybrid approach. This study considers a mixed activity projection method that takes individual activity insights from the univariate time-series prediction and ensemble multi-class classification approaches. …”
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Towards an Improved High-Throughput Phenotyping Approach: Utilizing MLRA and Dimensionality Reduction Techniques for Transferring Hyperspectral Proximal-Based Model to Airborne Ima... by Ramin Heidarian Dehkordi, Gabriele Candiani, Francesco Nutini, Federico Carotenuto, Beniamino Gioli, Carla Cesaraccio, Mirco Boschetti

“…Furthermore, the generated models were re-calibrated using soil spectra and then transferred to an airborne dataset collected using a CASI-SASI hyperspectral sensor, allowing the estimation of wheat traits across the entire field. …”
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Machine learned daily life history classification using low frequency tracking data and automated modelling pipelines: application to North American waterfowl by Cory Overton, Michael Casazza, Joseph Bretz, Fiona McDuie, Elliott Matchett, Desmond Mackell, Austen Lorenz, Andrea Mott, Mark Herzog, Josh Ackerman

“…Conclusions Automated pipelines generated models producing highly accurate classifications of complex daily activity patterns using relatively low frequency GPS and incorporating more classes than previous GPS studies. …”
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Generation of synthetic tympanic membrane images: Development, human validation, and clinical implications of synthetic data by Krish Suresh, Michael S. Cohen, Christopher J. Hartnick, Ryan A. Bartholomew, Daniel J. Lee, Matthew G. Crowson

“…Our study represents one of the first generative models for synthetic image data within our field of Otolaryngology–Head and Neck Surgery. …”
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Probing the origins of human acetylcholinesterase inhibition via QSAR modeling and molecular docking by Saw Simeon, Nuttapat Anuwongcharoen, Watshara Shoombuatong, Aijaz Ahmad Malik, Virapong Prachayasittikul, Jarl E.S. Wikberg, Chanin Nantasenamat

“…AChE inhibitors were described by a set of 12 fingerprint descriptors and predictive models were constructed from 100 different data splits using random forest. Generated models afforded R2, ${Q}_{\mathrm{CV }}^{2}$ Q CV 2 and ${Q}_{\mathrm{Ext}}^{2}$ Q Ext 2 values in ranges of 0.66–0.93, 0.55–0.79 and 0.56–0.81 for the training set, 10-fold cross-validated set and external set, respectively. …”
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A New Integrated Approach for Landslide Data Balancing and Spatial Prediction Based on Generative Adversarial Networks (GAN) by Husam A. H. Al-Najjar, Biswajeet Pradhan, Raju Sarkar, Ghassan Beydoun, Abdullah Alamri

“…Future studies could explore other generative models for landslide data balancing. By using state-of-the-art GAN, the proposed model can be considered in the areas where the data are limited or imbalanced.…”
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A multiscale computational framework for cement paste by Palkovic, Steven D. (Steven David)

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Image Compression using Sum-Product Networks by Jayashankar, Tejas K.

“…In this thesis, we develop a new separation architecture based on recently proposed sum-product networks (SPNs), a class of tractable probabilistic generative models, to model the source distribution. Our architecture strikes a balance between efficient learning of source structure and fast lossless decoding. …”
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A Model Guided Approach to Evoke Homogeneous Behavior During Temporal Reward and Loss Discounting by Janine Thome, Janine Thome, Mathieu Pinger, Patrick Halli, Daniel Durstewitz, Wolfgang H. Sommer, Peter Kirsch, Peter Kirsch, Georgia Koppe, Georgia Koppe

“…We further compare and evaluate common models in the field through out-of-sample prediction error estimates, to iteratively improve the trial-generating model and paradigm.ResultsThe developed paradigm successfully increases discounting behavior during both reward and loss discounting. …”
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Herniated Lumbar Disc Generation and Classification Using Cycle Generative Adversarial Networks on Axial View MRI by Wafa Mbarki, Moez Bouchouicha, Frederick Tshibasu Tshienda, Eric Moreau, Mounir Sayadi

“…Moreover, their efficiency to synthesize images and data at unprecedented levels of realism also gives hope that the chronic scarcity of labeled data in the medical field can be resolved with the help of these generative models. In our case, having a database that contains several images is a very difficult task. …”
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Extending Multi-Beam Sonar with Structure from Motion Data of Shorelines for Complete Pool Bathymetry of Reservoirs by Izaak Cooper, Rollin H. Hotchkiss, Gustavious Paul Williams

“…The models generated by both approaches are point clouds, which consist of points representing the ground surface in three-dimensional space. Generating models from sUAV-captured images requires ground control points (GCPs), i.e., points with a known location, to anchor model creation. …”
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Key problems on hydro-engineering-environmental geology along the Sichuan-Tibet Railway corridor: Current status and development direction by Yongshuang ZHANG, Changbao GUO, Xiangquan LI, Junbo BI, Jianfei MA, Feng LIU

“…In terms of hydrogeology, such as 1) sequence law of plateau karst development and types of tectonic karst water storage structures, 2) disaster-generating models and prediction methods of water and mud bursts in deep-buried tunnels, 3) active fault control mechanisms and geothermal water circulation models, 4) identification of high-temperature heat hazard risk and geothermal resources utilization technology. …”
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From Forest Dynamics to Wetland Siltation in Mountainous Landscapes: A RS-Based Framework for Enhancing Erosion Control by Gonzalo Hernández-Romero, Jose Manuel Álvarez-Martínez, Ignacio Pérez-Silos, Ana Silió-Calzada, David R. Vieites, Jose Barquín

“…We applied this forest gain to a scenario generator model to derive a 30-year future LULC map that defines the potential forest extent for the study area in 2049. …”
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Models predict change in plasma triglyceride concentrations and long-chain n-3 polyunsaturated fatty acid proportions in healthy participants after fish oil intervention by Tilly I. T. Potter, Graham W. Horgan, Anne J. Wanders, Elizabeth H. Zandstra, Elizabeth H. Zandstra, Peter L. Zock, Helena L. Fisk, Anne M. Minihane, Philip C. Calder, Philip C. Calder, John C. Mathers, Baukje de Roos

“…A secondary goal was to establish if clustering of data prior to FO supplementation would lead to identification of groups of participants who responded differentially.MethodsTo generate models for the outcomes of interest, variable selection methods (forward and backward stepwise selection, LASSO and the Boruta algorithm) were applied to identify suitable predictors. …”
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Understanding social influence using network analysis and machine learning by Adjodah, Dhaval D. K. (Adjodlah, Dhaval Dhamnidhi Kumar)

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Gasification of microalgae Chlorella vulgaris for synthesis gas production by Abdul Raheem

“…Statistical analysis showed that the generated models were sufficiently in agreement with the experimental results. …”
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Production of natural vanillin from cymbopogon citratus using phanerochaete chrysosporium by Hussin, Huszalina

“…The maximum vanillin production was observed with media composition of 1.0 g/L ferulic acid from hydrolysate of C. citratus leaves, 4.43 g/L ammonium chloride (inorganic nitrogen), 0.25 g/L yeast extract (organic nitrogen), 0.2 g/L KH2PO4, 0.013 g/L CaCl22.H2O, 0.5 g/L MgSO4.7H2O and 0.0025 g/L thiamin hydrochloride, at 36.3 °C and pH 6.84 under shaking condition at 150 rpm with inoculum size of 7 % (w/v). The generated model fitted well to the data set with R2 of 0.9059. …”
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Modeling and Simulation of Physical Systems Formed by Bond Graphs and Multibond Graphs by Gilberto Gonzalez-Avalos, Noe Barrera Gallegos, Gerardo Ayala-Jaimes, Aaron Padilla Garcia, Luis Flaviano Ferreyra García, Aldo Jesus Parente Rodríguez

“…Finally, a synchronous generator modeled by (<inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><mi>M</mi><mi>B</mi><mi>G</mi></mrow></semantics></math></inline-formula>-<inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><mi>B</mi><mi>G</mi></mrow></semantics></math></inline-formula>) as a case study is developed, and simulation results using 20-Sim software are shown. …”
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Molecular Docking Simulation Studies Identifies Potential Natural Product Derived-Antiwolbachial Compounds as Filaricides against Onchocerciasis by Samuel K. Kwofie, Emmanuel Broni, Faruk U. Yunus, John Nsoh, Dela Adoboe, Whelton A. Miller, Michael D. Wilson

“…The protein sequence of the WSP with UniProtKB identifier Q0RAI4 was used to model the three-dimensional (3D) structure via homology modelling techniques using three different structure-building algorithms implemented in Modeller, I-TASSER and Robetta. Out of the 15 generated models of WSP, one was selected as the most reasonable quality model which had 82, 15.5, 1.9 and 0.5% of the amino acid residues in the most favored regions, additionally allowed regions, generously allowed regions and disallowed regions, respectively, based on the Ramachandran plot. …”
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Deciphering the Interactions of Bioactive Compounds in Selected Traditional Medicinal Plants against Alzheimer’s Diseases via Pharmacophore Modeling, Auto-QSAR, and Molecular Docki... by  Oluwafemi Adeleke Ojo, Adebola Busola Ojo, Charles Okolie, Mary-Ann Chinyere Nwakama, Matthew Iyobhebhe, Ikponmwosa Owen Evbuomwan, Charles Obiora Nwonuma, Rotdelmwa Filibus Maimako, Abayomi Emmanuel Adegboyega, Odunayo Anthonia Taiwo, Khalaf F. Alsharif, Gaber El-Saber Batiha

“…Most notably, the compounds’ pIC₅₀ values were predicted by a machine learning-based model generated by the AutoQSAR algorithm. The generated model was validated to affirm its predictive model. …”
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