An Autonomous Vehicle Behavior Decision Method Based on Deep Reinforcement Learning with Hybrid State Space and Driving Risk by Xu Wang, Bo Qian, Junchao Zhuo, Weiqun Liu

“…Compared with advanced algorithms, the method proposed in this paper improves the driving distance of autonomous vehicle by 3.3%, the safety by 2.1%, and the calculation time by 43% in the experiment.…”
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Advanced Ai Tools for Predicting Mechanical Properties of Self-Compacting Concrete by AGRAWAL Achal, CHANDAK Narayan

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Prediction of Enthalpy of Mixing of Binary Alloys Based on Machine Learning and CALPHAD Assessments by Shuangying Huang, Guangyu Wang, Zhanmin Cao

“…Using pure element properties and Miedema’s model parameters as descriptors, we trained and evaluated four machine learning algorithms, finding LightGBM to perform best (R² = 92.2%, MAE = 3.5 kJ/mol). …”
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Designing a Smart Garment for Dynamic Sitting Reminders by Yujie Hou, Zhaohui Wang, Huanhuan Liu, Mengxuan Xia, Xinyi Fan, Qinwen Ye

“…Currently, the sedentary nature of office work has led to a steady increase in the prevalence of spinal disorders, including lower back pain, back pain, and neck pain. Medical research has shown that monitoring and improving sitting posture is an important measure to prevent spinal discomfort. …”
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A Study Investigating Interpretable Deep Learning Models for Predicting Mortality and Survival in Patients with Primary Thyroid Lymphomas by Zihan Yu, Rong Hu, Jiaqing Chen

“…Primary thyroid lymphoma (PTL) is a rare malignancy, and this study aimed to develop a prognostic prediction model for PTL using deep learning algorithms while providing interpretable analyses. Machine learning models were employed for mortality risk prediction, with the SHAP framework introduced for feature interpretation, and a DeepSurv model was constructed for comparison with the Cox proportional hazards (Cox-PH) model. …”
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Wearable devices for patient monitoring in the intensive care unit by Alessandra Angelucci, Massimiliano Greco, Maurizio Cecconi, Andrea Aliverti

“…Further research is necessary to validate the effectiveness of WDs and to integrate them into clinical practice in critical care environments. …”
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Functional control of the technical condition method for aircraft control system sensors under complete parametric uncertainty by J. V. Bondarenko, E. Yu. Zybin

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Load Probability Density Forecasting Under FDI Attacks Based on Double-Layer LSTM Quantile Regression by Pei Zhao, Jie Zhang, Guang Ling

“…The method effectively integrates data-driven and statistical algorithms such as double-layer long short-term memory (DL-LSTM) networks, quantile regression (QR), and kernel density estimation (KDE). …”
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Investigating the Relationship Between Drought Parameters and Food Security Using Data Mining Methods (Case study: Alborz Province) by Mohammad Ansari Ghojghar

“…The purpose of this research is to select a superior model in order to measure the relationship between drought parameters and food security in Alborz province. …”
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Testing Linear Regressions by StatsModel Library of Python for Oceanological Data Interpretation by Polina Lemenkova

“…The study area is focused on the Mariana Trench, west Pacific Ocean. The research aim is to investigate correlation between various factors, such as bathymetric depths, geomorphic shape, geographic location on four tectonic plates of the sampling points along the trench, and their influence on the geologic sediment thickness. …”
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TSCAPE: time series clustering with curve analysis and projection on an Euclidean space by Jeremy Renaud, Raphaël Couturier, Christophe Guyeux, Benoit Courjal

“…The methodology exhibits significant potential for diverse applications, accommodating varied data types and irregular time series shapes. The research compares multiple variants and proposes metrics to assess their effectiveness on two open-access datasets. …”
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Knowledge graph convolutional networks with user preferences for course recommendation by Zhong Hua, Jianbai Yang, Weidong Ji

“…Knowledge graphs (KGs) have been employed in recommendation systems to effectively address the issue of sparse interaction data in the MOOC scenarios for their rich semantic information. Research on KG-enhanced recommendation algorithms has found that the utilization of side information in KGs is crucial for improving accuracy. …”
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Neuro-modelling and fuzzy logic control of a two-wheeled wheelchair system by NIzaruddin M Nasir, Nor Maniha Abdul Ghani, Ahmad Nor Kasruddin Nasir, Mohd Ashraf Ahmad, Mohammad Osman Tokhi

“…Significant challenges posed by two-wheeled wheelchairs control due to their inherent instability, resembling that inverted pendulum system. This research addresses these challenges by developing a dynamic non-linear model and stability control using computational algorithms. …”
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Methodological Approach to the Reengineering of Logistics Business Processes in the Transport Chains with the Implementation of Smart Contracts by T. G. Shul’zhenko

“…The study presents a methodological tool and results of semantic modeling of logistics processes in transport chains that form the necessary basis for further algorithmization of procedures for fulfilling the contractual conditions of a smart contract. …”
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Deep Aramaic: Towards a synthetic data paradigm enabling machine learning in epigraphy. by Andrei C Aioanei, Regine R Hunziker-Rodewald, Konstantin M Klein, Dominik L Michels

“…Our research pioneers an innovative methodology for generating synthetic training data tailored to Old Aramaic letters. …”
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Can Ai Revolutionize Qspr Models for the Chemical Mixtures Hazards? by Guillaume Fayet, Nour Helou, Patricia Rotureau

“…To this end, applications of different machine learning methods were tested to evidence the advantages and limits of these Advanced AI algorithms compared to the more classical MLR approach when developing models for the flammability of liquid mixtures.…”
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Autonomous Drone-Based Pollination Systems for Enhancing Crop Yield in Orchards Using IoT and Machine Learning Optimization by Khan Roohee, Lalnunthari Banti

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A Study on the Fractal-Fractional Epidemic Probability-Based Model of SARS-CoV-2 Virus along with the Taylor Operational Matrix Method for Its Caputo Version by Shahram Rezapour, Sina Etemad, İbrahim Avcı, Hijaz Ahmad, Azhar Hussain

“…Rapid mutations and the creation of new strains cause researchers to focus on the dynamic behaviors of the virus and to analyze it accurately through clinical research and mathematical models. …”
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Unsupervised machine learning-based stratification and immune deconvolution of liver hepatocellular carcinoma by Mae Montserrat Reierson, Animesh Acharjee

“…Immune deconvolution algorithms estimated the proportions of infiltrating immune cells across identified clusters. …”
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SwinVNETR: Swin V-net Transformer with non-local block for volumetric MRI Brain Tumor Segmentation by Maria Nancy A, K. Sathyarajasekaran

“…Brain Tumor Segmentation (BTS) and classification are important and growing research fields. Magnetic resonance imaging (MRI) is commonly used in the diagnosis of brain tumours owing to its low radiation exposure and high image quality. …”
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