Kernel-based response extraction approach for efficient configurable ring oscillator PUF by Enas Abulibdeh, Hani Saleh, Baker Mohammad, Mahmoud Al-Qutayri, Asif Hussain

“…Abstract The Physically Unclonable Function (PUF) is an emerging hardware security primitive that provides a promising solution for lightweight security. …”
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Priority Roles of Stakeholders for Overcoming the Barriers to Implementing Education 4.0: An Integrated Fermatean Fuzzy Entropy-Based CRITIC-CODAS-SORT Approach by Roselyn Gonzales, Rose Mary Almacen, Gamaliel Gonzales, Felix Costan, Decem Suladay, Lynne Enriquez, Emily Costan, Nadine May Atibing, Joerabell Lourdes Aro, Samantha Shane Evangelista, Fatima Maturan, Egberto Selerio, Lanndon Ocampo

“…., investing in efficient technologies and forging extensive stakeholder collaboration), human resource function (i.e., implementing periodic skills training for educators), and educators (i.e., engaging in continuous learning about cybersecurity threats, integrating awareness of applicable laws against cyberbullying, devising alternative cost-efficient teaching strategies, taking part in initiatives to improve curricula, efficient preparation of learning materials, and participating in skills development initiatives). …”
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Modelo de gestión enfocado en el usuario del Sistema de Bibliotecas de la Pontificia Universidad Católica Argentina = User-focused management model of the Library System of the Pon... by María Soledad Lago

“…Al compartir esta experiencia se pretende contribuir a la reflexión sobre los nuevos roles y funciones del bibliotecario, los posibles modelos de gestión y a concientizar sobre la importancia del cambio cultural organizacional que debe afrontar la comunidad bibliotecaria = In recent years, university libraries have had to discern and define a new role that considers both their social function and their integration into the teaching and learning process. …”
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Skin-lesion segmentation using boundary-aware segmentation network and classification based on a mixture of convolutional and transformer neural networks by Javaria Amin, Marium Azhar, Habiba Arshad, Amad Zafar, Seong-Han Kim

“…In the clinical domain, skin lesions such as melanoma detection are still a challenge due to occlusions, poor contrast, poor image quality, and similarities between skin lesions. Deep-/machine-learning methods are used for the early, accurate, and efficient detection of skin lesions. …”
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Application of Ontology Matching Algorithm Based on Linguistic Features in English Pronunciation Quality Evaluation by Shan Zhu

“…This paper uses the method of tree kernel function to measure the similarity of two ontology trees. …”
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Stability, convergence, and robustness of deterministic multivariable self-tuning control by ZHAO Li, ZHANG Wei-cun, CHU Tian-guang

“…Self-tuning control is an important approach to intelligent control system design because this kind of control system uses online parameter estimation (or learning) to derive the model of the plant, and as a result of model parameter estimation (or learning), the controller parameters can be adjusted online. …”
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Bidirectional f-Divergence-Based Deep Generative Method for Imputing Missing Values in Time-Series Data by Wen-Shan Liu, Tong Si, Aldas Kriauciunas, Marcus Snell, Haijun Gong

“…The imputation process is achieved by training two neural networks, implemented using bidirectional modified gated recurrent units, with f-divergence serving as the objective function to guide optimization. Compared to existing deep learning-based methods, tf-BiGAIN introduces two key innovations. …”
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Reduced Geostatistical Approach With a Fourier Neural Operator Surrogate Model for Inverse Modeling of Hydraulic Tomography by Quan Guo, Yu He, Ming Liu, Yue Zhao, Yuzheng Liu, Jian Luo

“…Abstract In this study, we propose a new approach for inverse modeling of hydraulic tomography (HT) using the Fourier neural operator (FNO) as a surrogate forward model. FNO is a deep learning model that directly parameterizes the integral kernel in Fourier space to learn solution operators for parametric partial differential equations (PDEs). …”
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Integrated Bidding and Battery Scheduling in a Microgrid for Sealed-Bid Double Auction Power Trading With Peer Microgrids Under Uncertainty and Its Blockchain-Based Implementation by Zubin J. B., Sunitha R., Gopakumar Pathirikkat

“…The Q-learning relies solely on its historical bidding outcomes without attempting to predict the bids of other participants. …”
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Stellate ganglion block attenuates chronic stress induced depression in rats. by Weiwei Wang, Weidong Shi, Hua Qian, Xijin Deng, Tong Wang, Wenzhi Li

“…Stress-induced effects and the function of SGB were assessed using measures of body weight, coat state, sucrose consumption, and behavior in open-field and Y-maze tests. …”
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An Advanced Spatio-Temporal Graph Neural Network Framework for the Concurrent Prediction of Transient and Voltage Stability by Chaoping Deng, Liyu Dai, Wujie Chao, Junwei Huang, Jinke Wang, Lanxin Lin, Wenyu Qin, Shengquan Lai, Xin Chen

“…Power system stability prediction leveraging deep learning has gained significant attention due to the extensive deployment of phasor measurement units. …”
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A Novel Method for Intelligent Fault Diagnosis of Bearing Based on Capsule Neural Network by Zhijian Wang, Likang Zheng, Wenhua Du, Wenan Cai, Jie Zhou, Jingtai Wang, Xiaofeng Han, Gaofeng He

“…In order to accelerate the learning rate, the parameters which have bigger change are punished by cost function in the process of training. …”
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Social Brain Perspectives on the Social and Evolutionary Neuroscience of Human Language by Nathan Oesch

“…Here, evidence in support of this view reviews (1) recent developmental studies on language learning in infants and young children, pointing to the important crucial benefits associated with social stimulation for youngsters, including the quality and quantity of incoming linguistic information, dyadic infant/child-to-parent non-verbal and verbal interactions, and other important social cues integral for facilitating language learning and social bonding; (2) studies of the adult human brain, suggesting a high degree of specialization for sociolinguistic information processing, memory retrieval, and comprehension, suggesting that the function of these neural areas may connect social cognition with language and social bonding; (3) developmental deficits in language and social cognition, including autism spectrum disorder (ASD), illustrating a unique developmental profile, further linking language, social cognition, and social bonding; and (4) neural biomarkers that may help to identify early developmental disorders of language and social cognition. …”
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A review on WSN based resource constrained smart IoT systems by Shreeram Hudda, K. Haribabu

“…The proposed approach leverages advanced technologies such as SDN, Machine Learning (i.e. ML), Deep Learning (i.e. DL), D2D communication, Computer Vision, and Network Function Virtualization (i.e. …”
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3D-MRI brain glioma intelligent segmentation based on improved 3D U-net network. by Tingting Wang, Tong Wu, Defu Yang, Ying Xu, Dongyang Lv, Tong Jiang, Hengjiao Wang, Qi Chen, Shengnan Xu, Ying Yan, Baoguang Lin

“…Then, by making the model focus on glioma details and suppressing irrelevant background information, we propose a multi-scale fusion attention mechanism; And finally, to address class imbalance and enhance learning of misclassified voxels, a combination of Dice and Focal loss functions was employed, creating a loss function, this method not only maintains the accuracy of segmentation, It also improves the recognition of challenge samples, thus improving the accuracy and generalization of the model in glioma segmentation.…”
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An Interpretable Siamese Attention Res-CNN for Fingerprint Spoofing Detection by Chengsheng Yuan, Zhenyu Xu, Xinting Li, Zhili Zhou, Junhao Huang, Ping Guo

“…Furthermore, to highlight the difference in RCF, a Siamese attention residual network is devised, and the ridge continuity amplification loss function is designed to optimize the training process. …”
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EfficientTransformer: A Dynamic Anomaly Detection Model for Industrial Control Networks by Jinyang Liu, Guogang Wang, Xuejun Zong, Bowei Ning, Kan He

“…The model uses a 1D Convolutional Neural Network (1D-CNN) to extract local features from the data, while a linear multi-head self-attention mechanism, replacing the traditional Transformer’s multi-head attention mechanism, provides global learning capabilities. This reduces computational complexity and enables efficient parallel learning. …”
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A New Classification Model Using a Decision Tree Generated from Hyperplanes in Dimensional Space by Benjamín Luna-Benoso, José Cruz Martínez-Perales, Úrsula Samantha Morales-Rodríguez, Rolando Flores-Carapia, Víctor Manuel Silva-García

“…One of the issues addressed by machine learning, with applications in various disciplines or fields such as the health sector and the agricultural sector among others, involves data classification. …”
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An Ontology-Based Framework for Complex Urban Object Recognition through Integrating Visual Features and Interpretable Semantics by Xiao Xie, Xiran Zhou, Jingzhong Li, Weijiang Dai

“…This work is conducive to the development of complex urban object recognition toward the fields including multilayer learning algorithms and knowledge graph-based relational reinforcement learning.…”
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Deep Temporal Clustering of Pathological Gait Patterns in Post-Stroke Patients Using Joint Angle Trajectories: A Cross-Sectional Study by Gyeongmin Kim, Hyungtai Kim, Yun-Hee Kim, Seung-Jong Kim, Mun-Taek Choi

“…Rehabilitation of gait function in post-stroke hemiplegic patients is critical for improving mobility and quality of life, requiring a comprehensive understanding of individual gait patterns. …”
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