Comparative analysis of data transformation methods for detecting non-technical losses in electricity grids by Maria Gabriel Chuwa, Daniel Ngondya, Rukia Mwifunyi

“…This study explores various methods for transforming energy consumption patterns into two-dimensional (2D) representations to enhance feature extraction and NTL detection. …”
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EEG-based epilepsy detection using CNN-SVM and DNN-SVM with feature dimensionality reduction by PCA by Yousra Berrich, Zouhair Guennoun

“…Abstract This study focuses on epilepsy detection using hybrid CNN-SVM and DNN-SVM models, combined with feature dimensionality reduction through PCA. The goal is to evaluate the effectiveness and performance of these models in accurately identifying epileptic patterns. …”
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Filamentary Convolution for SLI: A Brain-Inspired Approach with High Efficiency by Boyuan Zhang, Xibang Yang, Tong Xie, Shuyuan Zhu, Bing Zeng

“…While the short-time Fourier transform (STFT) generates time–frequency acoustic features (TFAF) for deep learning networks (DLNs), rectangular convolution kernels cause frequency mixing and aliasing, degrading feature extraction. …”
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Tourism Sentiment Chain Representation Model and Construction from Tourist Reviews by Bosen Li, Rui Li, Junhao Wang, Aihong Song

“…Leveraging multidimensional attribute perceptions derived from tourist reviews, this study proposes a Spatial–Semantic Integrated Model for Tourist Attraction Representation (SSIM-TAR), which holistically encodes the composite attributes and multifaceted evaluations of attractions. Integrating these multidimensional features with inter-attraction relationships, three relational metrics are defined and fused: spatial proximity, resonance correlation, and thematic-sentiment similarity, forming a Tourist Attraction Multidimensional Association Network (MAN-SRT). …”
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Carbon Emissions From Low‐Order Streams in a Tropical, High‐Elevation, Peatland Ecosystem Are Mediated by Catchment Morphology by Keridwen M. Whitmore, Amanda G. DelVecchia, Elizabeth Farquhar, Gerard Rocher‐Ros, Esteban Suárez, Diego A. Riveros‐Iregui

“…However, few studies have examined the spatial variability of CO2 concentrations and fluxes occurring within these systems, particularly as a function of catchment morphology. Here we evaluated spatial patterns of CO2 in three tropical, headwater catchments in relation to the river network and stream geomorphology. …”
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Individualized lesion-symptom mapping using explainable artificial intelligence for the cognitive impact of white matter hyperintensities by Ryanne Offenberg, Alberto De Luca, Geert Jan Biessels, Frederik Barkhof, Wiesje M. van der Flier, Argonde C. van Harten, Ewoud van der Lelij, Josien Pluim, Hugo Kuijf

“…A convolutional neural network (CNN) predicts cognitive scores and is combined with explainable artificial intelligence (XAI) to map the relation between cognition and vascular lesions.This method was evaluated primarily using real white matter hyperintensity maps of 821 memory clinic patients and simulated cognitive data, with weighted lesions and noise levels. …”
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Transfer learning and multi-phase training for accurate diacritization of Arabic poetry by Gheith A. Abandah, Ashraf E. Suyyagh, Mohammad R. Abdel-Majeed

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Soil moisture retrieval and spatiotemporal variation analysis based on deep learning by Zihan Zhang, Jinjie Wang, Jianli Ding, Jinming Zhang, Liya Shi, Wen Ma

“…Nine deep learning models, including three basic architectures (Convolutional Neural Networks (CNN), Long Short-Term Memory Networks (LSTM), Transformer) and six hybrid structures (CNN-LSTM, LSTM-CNN, CNN-with-LSTM, CNN-Transformer, GAN-LSTM, Transformer-LSTM), were systematically compared to evaluate the impact of neural network structure on model performance. …”
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Climate change–Drylands–Food Security Nexus in Africa: From the Perspective of Technical Advances, Challenges, and Opportunities. by Hirwa, Hubert, Fadong, Li, Qiao, Yunfeng, Measho, Simon, Muhirwa, Fabien, Tian, Chao, Leng, Peifang

“…To bridge the gap from science to policy making in the CDF nexus, it is vital to enhance the impacts and feedback of ecohydrological processes on agrarian production, ecosystem service tradeoffs and their effects on livelihoods, and regional development and preservation by optimization of the ecological water security pattern. This state-of-the-art assessment uses acquired information and knowledge to conceptually evaluate the past, current, and future impacts and risks and facilitates decision-making through the delivery of long-term sustainability and socio-ecological resilience.…”
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Water Accounting and Productivity Analysis to Improve Water Savings of Nile River Basin, East Africa: From Accountability to Sustainability. by Hirwa, Hubert, Zhang, Qiuying, Li, Fadong, Qiao, Yunfeng, Measho, Simon, Muhirwa, Fabien, Xu, Ning, Tian, Chao, Cheng, Hefa, Chen, Gang, Ngwijabagabo, Hyacinthe

“…To bridge the gap from science to policy making in the CDF nexus, it is vital to enhance the impacts and feedback of ecohydrological processes on agrarian production, ecosystem service tradeoffs and their effects on livelihoods, and regional development and preservation by optimization of the ecological water security pattern. This state-of-the-art assessment uses acquired information and knowledge to conceptually evaluate the past, current, and future impacts and risks and facilitates decision-making through the delivery of long-term sustainability and socio-ecological resilience.…”
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Deciphering Socio-Spatial Integration Governance of Community Regeneration: A Multi-Dimensional Evaluation Using GBDT and MGWR to Address Non-Linear Dynamics and Spatial Heterogene... by Hong Ni, Jiana Liu, Haoran Li, Jinliu Chen, Pengcheng Li, Nan Li

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Mobile applications for skin cancer detection are vulnerable to physical camera-based adversarial attacks by Junsei Oda, Kazuhiro Takemoto

“…Recent advances in deep neural networks (DNNs) have accelerated the deployment of DNN-based applications for automated skin cancer detection. …”
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Deep Reinforcement Learning-Based Multi-Agent System with Advanced Actor–Critic Framework for Complex Environment by Zihao Cui, Kailian Deng, Hongtao Zhang, Zhongyi Zha, Sayed Jobaer

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A Deep Learning Model for NOx Emissions Prediction of a 660 MW Coal-Fired Boiler Considering Multiscale Dynamic Characteristics by Jianrong Huang, Yanlong Ji, Haiquan Yu

“…This study applies a Multiscale Graph Convolutional Network (MSGNet) designed to capture multiscale dynamic relationships among operational parameters of a 660 MW coal-fired boiler. …”
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A Survey on Event Tracking in Social Media Data Streams by Zixuan Han, Leilei Shi, Lu Liu, Liang Jiang, Jiawei Fang, Fanyuan Lin, Jinjuan Zhang, John Panneerselvam, Nick Antonopoulos

“…As such, it is imperative to conduct research on social events and patterns from the perspectives of conventional sociology to optimize services that originate from social networks. …”
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FD-GRNet: A Dendritic-Driven GRU Framework for Advanced Stock Market Prediction by Tongyan Liu, Jiayi Li, Zihang Zhang, Hang Yu, Shangce Gao

“…The unique architecture of the flexible dendritic-driven gated recurrent network (FD-GRNet) enables it to effectively manage both long-term dependencies and nonlinear patterns in financial time series. …”
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Power transmission system’s fault location, detection, and classification: Pay close attention to transmission nodes by Chiagoziem C. Ukwuoma, Dongsheng Cai, Olusola Bamisile, Ejiyi J. Chukwuebuka, Ekong Favour, Gyarteng S.A. Emmanuel, Acen Caroline, Sabirin F. Abdi

“…The model makes use of a deep graph neural network with multi-scale attention and multi-linear perceptron block which accounts for the power network's structural composition during learning. …”
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Machine Learning Techniques to Model and Predict Airflow Requirements in Underground Mining by Maria Karagianni, Andreas Benardos

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Natural Occlusion-Based Backdoor Attacks: A Novel Approach to Compromising Pedestrian Detectors by Qiong Li, Yalun Wu, Qihuan Li, Xiaoshu Cui, Yuanwan Chen, Xiaolin Chang, Jiqiang Liu, Wenjia Niu

“…Pedestrian detection systems are widely used in safety-critical domains such as autonomous driving, where deep neural networks accurately perceive individuals and distinguish them from other objects. …”
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Exploring the association between phytopharmaceutical use and antibiotic prescriptions in upper respiratory infections: results from a German cohort study evaluating the impact of... by Anna-Jasmin Wetzel, Gunter Laux, Stefanie Joos, Berthold Musselmann, Jan Valentini

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