Beyond Global Metrics: The U-Smile Method for Explainable, Interpretable, and Transparent Variable Selection in Risk Prediction Models by Katarzyna B. Kubiak, Agata Konieczna, Anna Tyranska-Fobke, Barbara Więckowska

“…The U-smile method supports both local and global evaluations and complements existing explainable machine learning (XML) and artificial intelligence (XAI) tools without overlapping in their functions. …”
Get full text

Conceptualizing bi- and multilingual disciplinary literacies in CLIL: insights from a European research network by Julia Hüttner, Ana Llinares, Tarja Nikula

“…To illustrate the multi-faceted nature of literacies, we will home in on one discursive aspect, i.e., Cognitive Discourse Functions and exemplify their use across levels, subjects, curricula, and digital practices. …”
Get full text

From 6G to <i>SeaX-G</i>: Integrated 6G TN/NTN for AI-Assisted Maritime Communications—Architecture, Enablers, and Optimization Problems by Anastasios Giannopoulos, Panagiotis Gkonis, Alexandros Kalafatelis, Nikolaos Nomikos, Sotirios Spantideas, Panagiotis Trakadas, Theodoros Syriopoulos

“…Furthermore, the critical Artificial Intelligence/Machine Learning (AI/ML) concepts and algorithms are described to highlight their potential in optimizing maritime functionalities. …”
Get full text

Autoencoder-Driven Fiducial Landmark Identification in 3D Brain MRI for Neuroimaging Alignment by G. Deepali, H. Anitha, B. P. Swathi, M. V. Suhas

“…In this work, we propose a deep learning-based framework using autoencoders to automatically detect fiducial markers in 3D brain MRI scans. …”
Get full text

The impacts of specific place visitations on theft patterns: a case study in Greater London, UK by Tongxin Chen, Kate Bowers, Tao Cheng

“…This study aims to investigate the impact of population activities at different urban functional places on theft levels across different urban areas and distinctive social changing contexts. …”
Get full text

SSDWSN: A Scalable Software-Defined Wireless Sensor Networks by Mohammed Alsaeedi, Mohd Murtadha Mohamad, Anas Al-Roubaiey

“…These policies are designed to efficiently utilize SDWSN network resources and accurately predict the network state by continuously monitoring the synchronized network state within the controller, taking appropriate actions, and updating the learning parameters based on reward functions. The simulation results demonstrate the effectiveness of PPO-ATCP and PPO-NSFP in reducing controller-bound traffic overhead by 57&#x0025; and 85&#x0025;, respectively, while improving energy efficiency by 28&#x0025; and 53&#x0025; in SDWSNs. …”
Get full text

Concept Drift Aware Wireless Key Generation in Dynamic LiFi Networks by Elmahedi Mahalal, Eslam Hasan, Muhammad Ismail, Zi-Yang Wu, Mostafa M. Fouda, Zubair Md Fadlullah, Nei Kato

“…To enable a concept drift aware framework, we propose an adaptive learning strategy using the similarity of channel probability density functions and the mix-of-experts ensemble method. …”
Get full text

Hybrid modeling approaches for predicting COVID-19 mortality: A comparative study across USA, France, and India by B. Uppalaiah, D. Mallikarjuna Reddy, K. Rajalakshmi, P. Vignesh, V. Govindan, Siriluk Donganont

“…The models combine the adaptability of Gaussian Processes with the deep learning functionalities of RBM, LSTM, and CNN to improve prediction precision and uncertainty assessment. …”
Get full text

An Innovative Artificial Intelligence Classification Model for Non-Ischemic Cardiomyopathy Utilizing Cardiac Biomechanics Derived from Magnetic Resonance Imaging by Liqiang Fu, Peifang Zhang, Liuquan Cheng, Peng Zhi, Jiayu Xu, Xiaolei Liu, Yang Zhang, Ziwen Xu, Kunlun He

“…Significant challenges persist in diagnosing non-ischemic cardiomyopathies (NICMs) owing to early morphological overlap and subtle functional changes. While cardiac magnetic resonance (CMR) offers gold-standard structural assessment, current morphology-based AI models frequently overlook key biomechanical dysfunctions like diastolic/systolic abnormalities. …”
Get full text

Design Optimization of an Innovative Instrumental Single-Sided Formwork Supporting System for Retaining Walls Using Physics-Constrained Generative Adversarial Network by Wei Liu, Lin He, Jikai Liu, Xiangyang Xie, Ning Hao, Cheng Shen, Junyong Zhou

Get full text

Effects of a cognitive modulator in the theta and alpha asymmetry during a typewriting task: a sensorimotor integration perspective Efeitos de um modulador cognitivo na assimetria... by Marlo Cunha, Sergio Machado, Luiz Cláudio Miana, Dionis Machado, Victor Hugo Bastos, Bruna Velasques, Maurício Cagy, Luis F. Basile, Roberto Piedade, Pedro Ribeiro

“…Our interpretation is that moderate doses of bromazepam may improve performance on tasks with predictable elements to promote stability of psychomotor functions, but may also impair performance on tasks executed in unpredictable environments.…”
Get full text

Enhancing water saturation predictions from conventional well logs in a carbonate gas reservoir with a hybrid CNN-LSTM model by Ali Gohari Nezhad, Mohammad Emami Niri

“…The network architectures were designed with specific layers and activation functions to enhance predictive capabilities. A robust validation process was conducted using a blind well dataset. …”
Get full text

Support of individual educational trajectories based on the concept of explainable artificial intelligence by I. G. Zakharova, M. S. Vorobeva, Yu. V. Boganyuk

“…Professional education in the context of individual educational trajectories (IET) meets the needs of both students themselves and the labour market due to the relevance of the content, flexibility of the educational process and learning technologies. However, in the context of digitalisation, IET support, including their planning and subsequent management of learning, entails the emergence of new requirements for information, analytical and methodological support of information systems designed to manage the educational process of the university. …”
Get full text

Identification of autophagy-related genes in intestinal ischemia-reperfusion injury and their role in immune infiltration by Yichen Hu, Qinghua Zou, Yanbo Sun, Weiming Li, Zhaochuan Yin, Yuanpei Zhao, Kaiwen Shi, Hongyuan Liu, Jiahui Wang

Get full text

Predicting Financial Market Volatility with Modern Model and Traditional Model by R. G. Aldeki

“…By integrating SVR with the GARCH model (GARCH-SVR) application with various kernels (Radial Basis Kernel Function (RBF), Polynomial Kernel Function (PF), and linear Kernel Function (lF)). …”
Get full text

Establishing a novel model to assess exercise capacity in chronic heart failure based on stress echocardiography by Huan Cen, Sinan Chen, Shen Feng, Xiankun Chen, Huiying Zhu, Wei Jiang, Han Zhang, Hongmei Liu, Bo Liu, Weihui Lu, Pengtao Sun

Get full text

Application of Big Data Technology to Assessments of Female Ovarian Reserve Dysfunction by Xia Ji'An, Ma YunFei, Wu YiYun, Zhao YouLin, Ni HaoRang, Liu XinYan

“…Hadoop and Spark frameworks were used to build a big data platform, and the MLlib parallel machine learning library was used to implement three multivariate classification models&#x2014;multilayer perceptron, one-vs-rest, and random forest classifiers&#x2014;to classify and analyse the ovarian reserve function dataset and evaluate the platform&#x2019;s performance. …”
Get full text

Deep multimodal representations and classification of first-episode psychosis via live face processing by Rahul Singh, Rahul Singh, Rahul Singh, Yanlei Zhang, Dhananjay Bhaskar, Dhananjay Bhaskar, Vinod Srihari, Cenk Tek, Xian Zhang, Xian Zhang, J. Adam Noah, J. Adam Noah, Smita Krishnaswamy, Smita Krishnaswamy, Smita Krishnaswamy, Joy Hirsch, Joy Hirsch, Joy Hirsch, Joy Hirsch, Joy Hirsch, Joy Hirsch

“…These learned representations are subsequently used to describe, classify, and predict the severity of early psychosis in patients, as measured by the Positive and Negative Syndrome Scale (PANSS) and Global Assessment of Functioning (GAF) scores to evaluate the impact of symptomatology. …”
Get full text

Deep Deterministic Policy Gradient Algorithm Based Wind-Photovoltaic-Storage Hybrid System Joint Dispatch by Shuxing ZHANG, Chi MA, Zhixue YANG, Yao WANG, Hao WU, Zhouyang REN

“…First, a joint dispatch model that fully considers the constraints of various wind and solar storage stations is established, where tracking dispatch plans, wind and solar curtailment, and energy storage operation costs are considered in the objective function. Then, the state variables, action variables and reward function under the reinforcement learning framework are defined. …”
Get full text

An Efficient 3D Convolutional Neural Network for Dose Prediction in Cancer Radiotherapy from CT Images by Lam Thanh Hien, Pham Trung Hieu, Do Nang Toan

“…To ensure that the predicted doses do not have negative values, which are not valid for radiation doses, a rectified linear unit (ReLU) function is applied to the output to convert negative values to zero. …”
Get full text