The integration of ICT in HR functions: the impact on operational performance by Amira Benachour, Lamine Tarhlissia, Hanane Abdelmalek, Yasmine Cheriti

“…Moreover, 81.8% of respondents highlight the existence of specific software for various management functions. Access to both internal and external information is also seen as significantly improved due to these technologies. …”
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On Explainability of Reinforcement Learning-Based Machine Learning Agents Trained with Proximal Policy Optimization That Utilizes Visual Sensor Data by Tomasz Hachaj, Marcin Piekarczyk

“…In this paper, we address the issues of the explainability of reinforcement learning-based machine learning agents trained with Proximal Policy Optimization (PPO) that utilizes visual sensor data. …”
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First-Principles Calculations, Machine Learning and Monte Carlo Simulations of the Magnetic Coercivity of Fe_<i>x</i>Co_1−<i>x</i> Bulks and Nanoclusters by Dou Du, Youwei Zhang, Xingwu Li, Namin Xiao

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Investigating Transfer Learning in Noisy Environments: A Study of Predecessor and Successor Features in Spatial Learning Using a T-Maze by Incheol Seo, Hyunsu Lee

“…In discussing these results, we emphasize the critical role of hyperparameter optimization in refining the performance and transfer learning efficacy of learning algorithms. This research advances our understanding of the functionality of PF and SF algorithms, particularly in navigating the inherent uncertainty of transfer learning tasks. …”
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A Learning Framework of Nonparallel Hyperplanes Classifier by Zhi-Xia Yang, Yuan-Hai Shao, Yao-Lin Jiang

“…It is worth mentioning that, in the decision function, the Euclidean distance is replaced by the absolute value |wTx+b|, which keeps the consistency between the decision function and the optimization problem and reduces the computational cost particularly when the kernel function is introduced. …”
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Enhanced DL-Based Breast Cancer Diagnosis and Classification Using Modified DenseNet-121, DenseNet-201, and MobileNetV2: Optimized Architectures and Refined Activation Functions by Khaddouj Taifi, Yassine Sabbar, Hanin Ardah, Abdel-Haleem Abdel-Aty

“…Our results emphasize the effectiveness of architectural tuning and activation function refinement in advancing deep learning-based breast cancer classification.…”
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On Software Defect Prediction Using Machine Learning by Jinsheng Ren, Ke Qin, Ying Ma, Guangchun Luo

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Least Square Regularized Regression for Multitask Learning by Yong-Li Xu, Di-Rong Chen, Han-Xiong Li

“…The study of multitask learning algorithms is one of very important issues. …”
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Audio Deepfake Detection Using Deep Learning by Ousama A. Shaaban, Remzi Yildirim

“…ABSTRACT This study introduces an enhanced Siamese convolutional neural network (Siamese CNN) architecture with a novel StacLoss function and self‐attention modules for efficient identification of audio deepfakes. …”
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Performance of Machine Learning Classifiers for Diabetes Prediction by Mijala Manandhar, Shaikat Baidya, Babalpreet Kaur, Katia Atoji

“…In this study, machine learning (ML) classifiers were evaluated for their effectiveness in predicting diabetes using the Pima Indians Diabetes Database. …”
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Tapping into the vocal learning and rhythmic synchronization hypothesis by Constantina Theofanopoulou

“…Abstract In this article, I present three main points that could benefit the “vocal learning and rhythmic synchronization hypothesis”, encompassing neurogenetic mechanisms of gene expression transmission and single motor neuron function, classification of different behavioral motor phenotypes (e.g., spontaneous vs. voluntary), and other evolutionary considerations (i.e., the involvement of reward mechanisms).…”
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A refined lion optimizer for deep learning by Jian Rong, Chenhao Ma, Qinghui Zhang, Yong Cao, Weili Kou

“…However, due to the discreteness of the sign function, the optimizer’s parameter updates may fail to adapt dynamically with momentum in some models, leading to non-convergence issues. …”
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Ellipsoidal <i>K</i>-Means: An Automatic Clustering Approach for Non-Uniform Data Distributions by Alaa E. Abdel-Hakim, Abdel-Monem M. Ibrahim, Kheir Eddine Bouazza, Wael Deabes, Abdel-Rahman Hedar

Subjects: “…unsupervised learning…”
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Improved YOLOv8-Based Algorithm for Citrus Leaf Disease Detection by Zhengbing Zheng, Yibang Zhang, Luchao Sun

Subjects: “…Wise-IoU loss function…”
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A 23-gene multi-omics signature predicts prognosis and treatment response in non-small cell lung cancer by Yinxu Zhang, Siwang Wang, Xiaoyang Chen, Guangyu Zhang, Yuxi Wang, Xiaomei Liu

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A One-Stage HMDV Algorithm Applied in Multitarget Detection in SAR Images by Lei Pang, Weihe Huang, Fengli Zhang, Yinhong Song

Subjects: “…Deep learning…”
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Effect of Xingbi Gel Nasal Drops on Rats with Allergic Rhinitis Based on the Nasal Mucosa-Hippocampus Neuroimmune Mechanism by FAN Xueqi, QIU Caixia, YAN Shuiping, ZHUANG Xiangli, AI Si, GUO Lihua, ZHENG Jian

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Looking outside the box with a pathology aware AI approach for analyzing OCT retinal images in Stargardt disease by Parisa Khateri, Tiana Koottungal, Damon Wong, Rupert W. Strauss, Lucas Janeschitz-Kriegl, Maximilian Pfau, Leopold Schmetterer, Hendrik P. N. Scholl

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PREDICTING THE LEARNING PATH TO LEARNER’S OPTIMUM COMPREHENSION by Ifeanyi Isaiah Achi, Chukwuemeka Odi Agwu, Christopher Chizoba Nnamene, Sylvester C. Aniobi, Ifebude Barnabas C., Kelechi Christian Oketa, Godson Kenechukwu Ezeh, John Otozi Ugah

“…The evaluation of this research involved brainstorming on the Bellman’s equation with the aid of the Markov Chain transition state framework, resulting in an improved mean value function of 71.7. This indicates an enhanced comprehension state for the learning students compared to the existing mean value function of 46.0. …”
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On the sample complexity of quantum Boltzmann machine learning by Luuk Coopmans, Marcello Benedetti

“…Abstract Quantum Boltzmann machines (QBMs) are machine-learning models for both classical and quantum data. …”
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