A Hybrid CNN–BiLSTM Framework Optimized with Bayesian Search for Robust Android Malware Detection by Ibrahim Mutambik

“…With the rapid proliferation of Android smartphones, mobile malware threats have escalated significantly, underscoring the need for more accurate and adaptive detection solutions. This work proposes an innovative deep learning hybrid model that combines Convolutional Neural Networks (CNNs) with Bidirectional Long Short-Term Memory (BiLSTM) networks for learning both local features and sequential behavior in Android applications. …”
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A Flexible Framework for Simulating the Water Balance of Lakes and Reservoirs From Local to Global Scales: mizuRoute‐Lake by Shervan Gharari, Inne Vanderkelen, Andrew Tefs, Naoki Mizukami, Erik Kluzek, Tricia Stadnyk, David Lawrence, Martyn P. Clark

“…Abstract Lakes and reservoirs are an integral part of the terrestrial water cycle. In this work, we present the implementation of different water balance models of lakes and reservoirs into mizuRoute, a vector‐based routing model, termed mizuRoute‐Lake. …”
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STATIC OF ORTHODONTIC APPLIANCES WITH MOVABLE INCLINED PLANE FOR MESIAL BATE TREATMENT by P.S. Flis, A.I. Hryhorenko, N.M. Doroshenko, M.M. Tormakhov, V.V. Filonenko

“…Mechanics and mathematical modeling of functionally directing appliance with a movable inclined plane static work for improving sagittal dentoalveolar anomalies and deformations treatment methods. …”
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An Improved Strategy for Torque Ripple Reduction of Dual Three-Phase Brushless DC Motor Fed by Two Diode-Clamped, Three-Level Inverters Using Model Predictive Control by Zahra Emami, Abolfazl Halvaei Niasar

“…This paper proposes a new finite control set model predictive control (FCS-MPC) approach with reduction of computational for diode-clamped three-level (DC3L) inverter fed to dual three-phase BLDCM (DTP-BLDCM) by selecting optimal vectors to solve the above problems. …”
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HSTCN-NuSVC: A Homogeneous Stacked Deep Ensemble Learner for Classifying Human Actions Using Smartphones by Sarmela Raja Sekaran, Ying Han Pang, Ooi Shih Yin, Lim Zheng You

“…This work aims to overcome the issues by proposing a lightweight, homogenous stacked deep ensemble model, termed Homogenous Stacking Temporal Convolutional Network with Nu-Support Vector Classifier (HSTCN-NuSVC), for activity classification. …”
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Enhancing flood susceptibility mapping in Meghna River basin by introducing ensemble Naive Bayes with stacking algorithms by Abu Reza Md. Towfiqul Islam, Md. Uzzal Mia, Nourin Akter Nova, Rabin Chakrabortty, Md. Sanjid Islam Khan, Bonosri Ghose, Subodh Chandra Pal, A. B. M. Mainul Bari, Edris Alam, Md Kamrul Islam, Mohammed Ali Alshehri, Hazem Ghassan Abdo, Romulus Costache

“…This article intends to assess flood susceptibility mapping in Meghna River basin (MRB) and identified flood susceptible regions using three benchmark models including random forest (RF), support vector machine (SVM) and bagging with Naïve Bayes (NB) stacking ensemble algorithms (e.g. …”
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GET: Global Envelopes in R by Mari Myllymäki, Tomáš Mrkvička

“… This work describes the R package GET that implements global envelopes for a general set of d-dimensional vectors T in various applications. …”
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Dynamic Error Compensation Control of Direct-Driven Servo Electric Cylinder Terminal Positioning System by Mingwei Zhao, Lijun Liu, Zhi Chen, Qinghua Yang, Xiaowei Tu

“…For this purpose, a cascaded coupling dynamic error model of DDSEC-TPS was established based on the position–pose error model of the parallel motion platform and the rotor field-oriented vector transform. …”
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UNDERSTANDING EDUCATORS’ EXPERIENCE AND ATTITUDE TO GAMIFIED LEARNING APPLICATIONS by Anastasiia V. Tokarieva, Inna V. Сhyzhykova

“…The need to develop serious video games’ and digital learning applications’ courses for educators with an integrated teacher-training program to help educators understand, design, evaluate and apply serious video games and GLAs into their practice, a Digital Learning Unit creation as an indispensable part of a contemporary Ukrainian Higher Educational Institution are seen as the vectors of further research and work.…”
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Investigating Reddit Data on Type 2 Diabetes Management During the COVID-19 Pandemic Using Latent Dirichlet Allocation Topic Modeling and Valence Aware Dictionary for Sentiment Rea... by Meghan Nagpal, Niloofar Jalali, Diana Sherifali, Plinio Morita, Joseph A Cafazzo

“…However, the COVID-19 pandemic impacted how people managed T2D due to work and school closures and social isolation. Moreover, individuals with T2D were at increased risk of complications from COVID-19 and experienced worsened mental health due to stress and anxiety. …”
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Question-matching approach based on gradual machine learning by Xuejian HE, Anqi CHEN, Zhiqiang GUO, Zhiru WANG, Qun CHEN

“…The DNN-based features contain global and local features, where the global features correspond to a question pair’s matching probability as estimated by a DNN model, and the local features correspond to the semantic similarity between two neighboring question pairs estimated by their vector representations in a DNN’s embedding space. …”
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Hidden in Plain Sight: A Data-Driven Approach to Safety Risk Management for Highway Traffic Officers by Loretta Bortey, David J. Edwards, Chris Roberts, Iain Rille

“…The DNN model outperformed the other three models. Findings from the data exploration also show that most work operations undertaken by HTOs have a medium risk level with night shifts posing the greatest risk challenges. …”
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Detecting and measuring social media attacks on American election officials by Sreemanti Dey, Sreemanti Dey, Daniel Ebanks, Daniel Ebanks, Sarah Hashash, Sarah Hashash, R. Michael Alvarez

“…Our study: (1) Proposes a unique measurement and modeling strategy applicable across many social media networks to study toxicity directed at officials, institutions, or groups; (2) Collects a novel dataset of social media conversations about election administration in the 2020 election; (3) Uses joint sentiment-topic modeling to identify toxicity from the reactions of the public and election officials, and uses dynamic vector autoregression models to determine the temporal structure of the toxic conversations directed at election officials; (4) Finds that the level of animosity toward election officials spikes immediately after the election, that hostile topics overall make up about a quarter of the discussion share during this period, increasing to about 60% following the election, and that hostile topics come from left- and right-wing partisans. …”
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Integrating vulnerability and hazard in malaria risk mapping: the elimination context of Senegal by Camille Morlighem, Chibuzor Christopher Nnanatu, Justice Moses K. Aheto, Catherine Linard

“…However, the models trained on the 2020-21 MIS data performed poorly, achieving a median R² of 0.13 at best for the model based on hazard factors, likely due to data collection during the dry season. …”
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Capturing Geological Uncertainty in Salt Cavern Developments for Hydrogen Storage by Hector G. Barnett, Mark Thomas Ireland, Cees Van Der Land

“…In this work, we illustrate the workflow for four areas and geological models in the UK’s Southern North Sea: 1) Basin Scale (58,900 km2) - >48,800 TWh of hydrogen storage with >199,000 cavern locations. 2) Sub-Regional Scale (24,800 km2) - >9,600 TWh of hydrogen storage with >36,000 cavern locations. 3) Block Specific–Salt Wall (79.8 km2) - >580 TWh of hydrogen storage with >400 cavern locations. 4) Block Specific–Layered Evaporite (225 km2) - >263 TWh of hydrogen storage with >500 cavern locations. …”
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Construction of a Structurally Unbiased Brain Template with High Image Quality from MRI Scans of Saudi Adult Females by Noura Althobaiti, Kawthar Moria, Lamiaa Elrefaei, Jamaan Alghamdi, Haythum Tayeb

“…Additionally, we implement computational optimizations, including parallelization and vectorized operations, to increase processing efficiency. …”
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Enhancing personalized learning: AI-driven identification of learning styles and content modification strategies by Md. Kabin Hasan Kanchon, Mahir Sadman, Kaniz Fatema Nabila, Ramisa Tarannum, Riasat Khan

“…The blending ensemble technique with the XGBoost meta-learning model accomplished the best performance for learning style detection with an accuracy of 97.56%. …”
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Remote Sensing-Derived Environmental Variables to Estimate Transmission Risk and Predict Malaria Cases in Argentina: A Pre-Certification Study (1986–2005) by Ana C. Cuéllar, Roberto D. Coello-Peralta, Davis Calle-Atariguana, Martha Palacios-Macias, Paul L. Duque, Liliana M. Galindo, Mario O. Zaidenberg, María J. Dantur-Juri

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Prediction of formation pressure in underground gas storage based on data-driven method by SUI Gulei, FU Yujiang, ZHU Hongxiang, LI Zunzhao, WANG Xiaolin

“…The supervised learning model of formation pressure forecasting is established by three kinds of machine learning algorithms including extreme gradient boosting (XGBoost), support vector regression (SVR), and long short-term memory network (LSTM). …”
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Barr-Zee diagrams at a high-energy muon collider by Samuel Homiller, Jackie Lodman, Aditya Parikh, Matthew Reece

“…A high-energy muon collider could decisively search for new physics at this scale. In this work, we explore this complementarity between colliders and EDM experiments, and note that Barr-Zee diagrams from the aforementioned particles are closely related to vector-boson scattering processes at a muon collider. …”
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