Vibro-Fluidized Bed Drying of Pumpkin Seeds: Assessment of Mathematical and Artificial Neural Network Models for Drying Kinetics by Priyanka Dhurve, Ayon Tarafdar, Vinkel Kumar Arora

“…A feedforward backpropagation ANN model was trained by the Levenberg–Marquardt training algorithm using a TANSIGMOID activation function with 2-10-2 topology. …”
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Universal Modeling for Non-Destructive Testing of Soluble Solids Content in Multi-Variety Blueberries Based on Hyperspectral Imaging Technology by Lingqi Meng, Guoliang Chen, Dayang Liu, Ning Tian

“…The results showed that the PLSR model pretreated by S-G-MSC-SNV had the best performance, and the determination coefficient, root mean square error and residual prediction deviation of the prediction set were 0.94, <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><mn>0.33</mn><mo>%</mo></mrow></semantics></math></inline-formula> and 3.94, respectively. …”
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Implicit Is Not Enough: Explicitly Enforcing Anatomical Priors inside Landmark Localization Models by Simon Johannes Joham, Arnela Hadzic, Martin Urschler

“…Currently, Anatomical Landmark Localization (ALL) is mainly solved by deep-learning methods, which cannot guarantee robust ALL predictions; there may always be outlier predictions that are far from their ground truth locations due to out-of-distribution inputs. …”
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Data-driven axial compressive strength investigation of FRP-confined coral aggregate concrete by Chang Zhou, Kai-Di Peng, Yu-Lei Bai

“…The SHapley Additive exPlanation (SHAP) algorithm is employed to elucidate the prediction mechanisms of the ML models and to clarify the interactions between the eight input features and the axial compressive strength of FRP-confined CAC. …”
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Leveraging hybrid 1D-CNN and RNN approach for classification of brain cancer gene expression by Heba M. Afify, Kamel K. Mohammed, Aboul Ella Hassanien

“…Abstract Leveraging deep learning (DL) approaches in genomics data has led to significant advances in cancer prediction. The continuous availability of gene expression datasets over the preceding years has made them one of the most accessible sources of genome-wide data, advancing cancer bioinformatics research and advanced prediction of cancer genomic data. …”
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Hull form optimization of fully parameterized small ships using characteristic curves and deep neural networks by Jin-Hyeok Kim, Myung-Il Roh, In-Chang Yeo

“…To address this issue, this paper proposes an approach that involves defining a range of hull forms with characteristic curves, predicting their performance using Deep Neural Networks (DNNs), and subsequently determining the optimal hull form based on these predictions. …”
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An efficient enhanced stacked auto encoder assisted optimized deep neural network for forecasting Dry Eye Disease by Steffi Rajan, Suresh Ponnan

“…The approach described here is novel because it merges chaotic maps into FS, employs SLSTM-STSA for improved classification accuracy (CA), and optimizes with the adaptive quantum rotation of the Enhanced Quantum Bacterial Foraging Optimisation Algorithm (EQBFOA). The present study enhances prediction functions by extracting MGD-related features and complicated relationships from the DED dataset. …”
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SPINE: SParse eIgengene NEtwork linking gene expression clusters in Dehalococcoides mccartyi to perturbations in experimental conditions. by Cresten B Mansfeldt, Benjamin A Logsdon, Garrett E Debs, Ruth E Richardson

“…Based on the model predictions, we discovered new response mechanisms for DMC, notably when the bacterium is exposed to solvent toxicity. …”
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Digital mapping of peat thickness and extent in Finland using remote sensing and machine learning by Jonne Pohjankukka, Timo A. Räsänen, Timo P. Pitkänen, Arttu Kivimäki, Ville Mäkinen, Tapio Väänänen, Jouni Lerssi, Aura Salmivaara, Maarit Middleton

“…Additionally, we provided an approach for evaluating spatial prediction uncertainty based on the models’ internal prediction agreement. …”
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Real‐Time Coseismic Slip Estimation via the GNSS Carrier Phase to Fault Slip Approach: A Case Study of the 2016 Kumamoto Earthquake by Yusuke Tanaka, Yusaku Ohta, Shin'ichi Miyazaki

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Battle of Water Demand Forecasting: An Optimized Deep Learning Model by Mohammadali Geranmehr, Alemtsehay G. Seyoum, Mostapha Kalami Heris

“…Ensuring a steady supply of drinking water is crucial for communities, but predicting how much water will be needed is challenging because of uncertainties. …”
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Analysis of time series characteristics using machine learning model and correlation matrix in the tasks of forecasting the state of forest ecosystems by Gusev Pavel, Tavolzhanskij Alexander, Zolnikov Vladimir, Deniskina Antonina

“…Then linear regression models are trained and the quality of predictions for different sets of variables from the sorted list is compared. …”
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Alert processing based on attack graph and multi-source analyzing by Wei-xin LIU, Kang-feng ZHENG, Bin WU, Yi-xian YANG

“…Current attack graph-based alert correlation cannot deal with graph relation between alerts properly,and a large number of redundant attack paths may arise when trying to find out missing alerts and predict future attacks.A multi-source alert analyzing method was proposed,fully utilizing graph relation and threshold to correlate mapped alerts and eventually reduce false positive rate as well as true negative rate.To improve the speed of the algorithm,a parallel alert processing system (AG-PAP) was proposed.AG-PAP is tested on distributed environment which gets satisfied effec-tiveness and performance.…”
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Fast and resource efficient method for indoor localization based on fingerprint with varied scales by Yanfen LE, Zhuo TANG, Cunbao SHENG, Weibin SHI

“…To improve the prediction speed in indoor localization,a novel algorithm based on fingerprint with varied scales was proposed.It divided the region of interest into distinct zones with distinctive coverage indicators,and reference positions with different distribution density were set in the region.According the time relevance and strength vary of the RSS from the anchors,the grids-matching process was greatly sped up for the usage of coverage indictors and the features of the location fingerprint extracted with the PCA,which made the proposed method fit the demand of application with limited power and memory.Experimental results indicate that accuracy of the positioning is ensured with the reduced energy-consuming,and more flexible about the number of anchors and the grid distribution.…”
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MODELING ECONOMIC AGENTS’ EXPECTATIONS AS A TOOL OF FORECASTING SHORT-TERM ECONOMIC CYCLES by Leonid A. Elshin, Maxim V. Savushkin

“…On the basis of quantitative estimation of economic agents’ expectations they designed algorithm for diagnosing cyclic fluctuations of economy, which gives an opportunity to identify rising and declining phases of economic cycles with an advance lag of 1-2 years with the effective trajectory of economic development of national economy.…”
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Modelling the Structure and Dynamics of Biological Pathways. by Laura O'Hara, Alessandra Livigni, Thanos Theo, Benjamin Boyer, Tim Angus, Derek Wright, Sz-Hau Chen, Sobia Raza, Mark W Barnett, Paul Digard, Lee B Smith, Tom C Freeman

“…There is a need for formalised diagrams that both summarise current biological pathway knowledge and support modelling approaches that explain and predict their behaviour. Here, we present a new, freely available modelling framework that includes a biologist-friendly pathway modelling language (mEPN), a simple but sophisticated method to support model parameterisation using available biological information; a stochastic flow algorithm that simulates the dynamics of pathway activity; and a 3-D visualisation engine that aids understanding of the complexities of a system's dynamics. …”
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Achieving precision assessment of functional clinical scores for upper extremity using IMU-Based wearable devices and deep learning methods by Weinan Zhou, Diyang Fu, Zhiyu Duan, Jiping Wang, Linfu Zhou, Liquan Guo

“…Simultaneously, on the basis of the internal correlation between the Fugl–Meyer assessment and the Brunnstrom scale, Brunnstrom stage prediction models of the arm and hand were established via the random forest and extremely randomized trees algorithm. …”
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Quantum Vulnerability Analysis to Guide Robust Quantum Computing System Design by Fang Qi, Kaitlin N. Smith, Travis LeCompte, Nian-feng Tzeng, Xu Yuan, Frederic T. Chong, Lu Peng

“…The QVA determines the cumulative quantum vulnerability (CQV) of the target quantum computation, which quantifies the quantum error impact based on the entire algorithm applied to the target quantum machine. By evaluating the CQV with well-known benchmarks on three 27-qubit quantum computers, the CQV success estimation outperforms the estimated probability of success state-of-the-art prediction technique by achieving on average six times less relative prediction error, with best cases at 30 times, for benchmarks with a real SR rate above 0.1&#x0025;. …”
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SERLogic: A Logic-Integrated Framework for Enhancing Sequential Recommendations by Lihang Fan

“…Sequential recommendation models are used to predict users&#x2019; next top-K preferred items based on their historical interactions. …”
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A mineral-strength conversion model based on LIBS technology and rapid batch testing and application of uniaxial compressive strength by Qinghe ZHANG, Xiaorui WANG, Chuanbing WANG, Weiguo LI, Fengqiang GONG, Xinsheng ZHANG, Jingguo LI

“…The mass fraction of mineral components is analyzed via the support vector regression (SVR) algorithm. In the end, a mineral-strength conversion model is established to calculate the UCS from the predicted values of mineral component concentrations, and its rationality and scientific validity are validated by the standard mechanical tests. …”
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