Fuzzy logic based adaptive duty cycling for sustainability in energy harvesting sensor actor networks by Sai Krishna Mothku, Rashmi Ranjan Rout

“…In this work, current residual energy, predicted harvesting energy (for a futuristic time slot) and predicted residual energy parameters are considered as fuzzy input variables to estimate duty cycle for a sensor node. …”
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A Hybrid Deep Learning–Based Feature Selection Approach for Supporting Early Detection of Long-Term Behavioral Outcomes in Survivors of Cancer: Cross-Sectional Study by Tracy Huang, Chun-Kit Ngan, Yin Ting Cheung, Madelyn Marcotte, Benjamin Cabrera

“…ObjectiveThis study aimed to create a new feature selection algorithm to improve the performance of machine learning classifiers to predict negative long-term behavioral outcomes in survivors of cancer. …”
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A new method for surge arrester placement in high‐voltage substations considering environmental effects by Faridoddin Safaei, Mohsen Niasati

“…The lightning back flashover (BF) and switching over‐voltages are predicted with the accurate modeling of the transient behavior of all elements of high‐voltage substations and transmission lines, considering the effect of environmental conditions. …”
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METHOD FOR NUMERICAL MODELING OF UNSTEADY SEPARATED FLOW AROUND AIRFOILS MOVING CLOSE TO FLAT SCREEN by T. V. Pogrebnaya, S. D. Shipilov

“…The results of the calculations showed that at low atitudes of airfoil over screen mirror method over predicts lift force compared with movable screen, while fixed screen under predicts it. …”
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Probabilistic Solar Proxy Forecasting With Neural Network Ensembles by Joshua D. Daniell, Piyush M. Mehta

“…Currently, the USAF contracts Space Environment Technologies (SET), which uses a linear algorithm to forecast F10.7cm. In this work, we introduce methods using neural network ensembles with multi‐layer perceptrons (MLPs) and long‐short term memory (LSTMs) to improve on the SET predictions. …”
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Tree Species Classification at the Pixel Level Using Deep Learning and Multispectral Time Series in an Imbalanced Context by Florian Mouret, David Morin, Milena Planells, Cécile Vincent-Barbaroux

“…Validation on independent in situ data shows that all models struggle to predict in areas not well covered by training data, but even in this situation, the RF algorithm is largely outperformed by deep learning models for minority classes. …”
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Integrated systems biology analysis of KSHV latent infection reveals viral induction and reliance on peroxisome mediated lipid metabolism. by Zoi E Sychev, Alex Hu, Terri A DiMaio, Anthony Gitter, Nathan D Camp, William S Noble, Alejandro Wolf-Yadlin, Michael Lagunoff

“…To identify the underlying cellular mechanisms of KSHV alteration of host signaling and endothelial cell activation, we identified changes in the host proteome, phosphoproteome and transcriptome landscape following KSHV infection of endothelial cells. A Steiner forest algorithm was used to integrate the global data sets and, together with transcriptome based predicted transcription factor activity, cellular networks altered by latent KSHV were predicted. …”
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Cooperativity among short amyloid stretches in long amyloidogenic sequences. by Lele Hu, Weiren Cui, Zhisong He, Xiaohe Shi, Kaiyan Feng, Buyong Ma, Yu-Dong Cai

“…The algorithm successfully predicted and classified amyloid segments with an overall accuracy of 75%. …”
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Optimisation of Crystallisation Recipe for Varied Cloud Points Characteristics in Palm Oil Fractions by John Ting Zhi Zhang, Jeng Shiun Lim

“…The artificial neural network (ANN), which uses the Levenberg-Marquardt algorithm, serves as an internal model for predicting process output, whereas the genetic algorithm (GA) investigates a wide range of recipe combinations to maximise yield. …”
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Correlation between shapes and sizes of dentofacial arches and their stable parameters by E. G. Vedeshina, D. A. Domenyuk, S. V. Dmitrienko

“…The study proposed an algorithm for determining the optimised predicted individual parameters of dental arches in people with abnormal shapes and sizes of dentofacial arches. …”
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An artificial intelligence approach for prognosis of COVID-19 course in hospitalized patients by T. L. Karonova, I. N. Korsakov, A. A. Mikhailova, D. I. Lagutina, A. T. Chernikova, М. A. Vashukova, M. A. Smolnikova, D. A. Gusev, A. O. Konradi, E. V. Shlyakhto

“…Aim. To create algorithm and risk calculator for predicting the lethal outcome in patients with COVID-19.Materials and methods. …”
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Proactive Frequency Stability Scheme Based on Bayesian Filters and Spectral Clustering by Gian Paramo, Mario D. Baquedano-Aguilar, Arturo Bretas, Sean Meyn

“…In this work, phasor measurement units are used to predict frequency values. When a disturbance is detected, the state of frequency is predicted a few seconds into the future via a particle filter algorithm. …”
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An Evolutionary Formulation of the Crossing Number Problem by Che Sheng Gan, Wee Chiat Alan Tan, Voon Chet Koo, Kwang Hwai Mak

“…It is shown that the EA implementation provides good confirmation of the predicted crossing numbers.…”
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The structural pathway of interleukin 1 (IL-1) initiated signaling reveals mechanisms of oncogenic mutations and SNPs in inflammation and cancer. by Saliha Ece Acuner Ozbabacan, Attila Gursoy, Ruth Nussinov, Ozlem Keskin

“…In the reconstructed pathway there are 104 interactions between proteins whose three dimensional structures are experimentally identified; only 15 have experimentally-determined structures of the interacting complexes. By predicting the protein-protein complexes throughout the pathway via the PRISM algorithm, the structural coverage increases from 15% to 71%. …”
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Effects of Polypropylene Waste Addition as Coarse Aggregates in Concrete: Experimental Characterization and Statistical Analysis by D. C. Naveen, K. Naresh, B. S. Keerthi Gowda, Madhu Sudana Reddy G, C. Durga Prasad, Ragavanantham Shanmugam

“…The Levenberg–Marquardt algorithm was used in predicting the mechanical properties using the ANN. …”
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A Dynamic Branch-Switching Method for Parametrically Excited Systems by A.Y.T. Leung, T. Ge

“…The branch-switching algorithm in static is applied to steady state dynamic problems. …”
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Modeling the Relationship Between Radon Anomalies and Seismic Activity Using Artificial Neural Networks and Statistical Methods by Kostadin Yotov, Emil Hadzhikolev, Stanka Hadzhikoleva

“…The methodology includes wavelet transformation for noise removal, a multilayer ANN trained using the Levenberg–Marquardt algorithm, and a segmentation approach based on radial zones (annuli) for localized predictions. …”
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PRE-PROCESSING DATA ON MULTICLASS CLASSIFICATION OF ANEMIA AND IRON DEFICIENCY WITH THE XGBOOST METHOD by Fathu Nurrahman, Hari Wijayanto, Aji Hamim Wigena, Nunung Nurjanah

“…Then pre-processing data will be carried out using MissForest imputation, Boruta featuring selection, and SMOTE to help improve the performance of the classification model in predicting a particular class. After the data pre-processing process is carried out, classification modeling will be carried out using the XGBoost algorithm. …”
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Quantitative sub-ice and marine tracing of Antarctic sediment provenance (TASP v1.0) by J. W. Marschalek, E. Gasson, T. van de Flierdt, C.-D. Hillenbrand, M. J. Siegert, M. J. Siegert, L. Holder

“…These results show that the algorithm could be used to predict the provenance signature of past ice sheet configurations. …”
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Multiclass Classification of Solar Flares in Imbalanced Data Using Ensemble Learning and Sampling Methods by Haodi Jiang, Ryoma Matsuura, Jason T. L. Wang

“…They are categorized into four classes: B, C, M, and X, depending on their intensity, with X-class flares being the strongest. Being able to predict a flare’s class before its occurrence is critical for anticipating the severity of its impact on Earth. …”
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