BGNER: A boundary guidance framework for enhanced named entity recognition by Yu He, Li Sun, Qianyu Yue, Haitao Wu, Xiaojuan Wang

“…We design a novel neural architecture to exploit this representation: a boundary-aware global pointer module efficiently scores spans by incorporating boundary context, and an entity-guided 3D convolutional neural network captures local patterns between spans and their boundaries. …”
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Dynamic Text Augmentation for Robust Sentiment Analysis: Enhancing Model Performance With EDA and Multi-Channel CNN by Komang Wahyu Trisna, Jinjie Huang, Yuanjian Chen, I Gede Juliana Eka Putra

“…The MCNN architecture effectively captures local patterns in text using multiple filter sizes, enabling comprehensive feature extraction with low computational overhead. …”
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Social Interactions for Sustainable Food Choices: Meeting the Target for Meat Intake in the United Kingdom by Angela Fontan, Rosemary Green, Karl H Johansson, Patricia Eustachio Colombo

“…The opinion dynamics comprised consumers (i.e., agents), with empirically derived baseline food intake patterns (i.e., initial opinions) and sociodemographic attributes. …”
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Land cover changes in grassland landscapes: combining enhanced Landsat data composition, LandTrendr, and machine learning classification in google earth engine with MLP-ANN scenari... by Cecilia Parracciani, Daniela Gigante, Onisimo Mutanga, Stefania Bonafoni, Marco Vizzari

“…Understanding grassland habitat dynamics in space and time is crucial for evaluating the effectiveness of protection measures and developing sustainable management practices, specifically within the Natura 2000 network and in light of the European Biodiversity Strategy. …”
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Real-time mobile broadband quality of service prediction using AI-driven customer-centric approach by Ayokunle A. Akinlabi, Folasade M. Dahunsi, Jide J. Popoola, Lawrence B. Okegbemi

“…Since the traffic patterns experienced in MBB networks are largely complex, highly dynamic and heterogenous in nature; hence, statistical methods may not adjust adequately to the changing network conditions. …”
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Bankruptcy forecasting in enterprises and its security using hybrid deep learning models by Akshat Gaurav, Brij B. Gupta, Shavi Bansal, Konstantinos E. Psannis

“…In this context, we propose an hybrid deep learning model through the use of convolutional neural network to enhance bankruptcy forecasting models. …”
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EXPLORING AUTOMATED SUMMARIZATION: FROM EXTRACTION TO ABSTRACTION by Svetlana G. Sorokina

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Identifying the role of route choice behavior of motorcycle riders in microscopic simulation modeling under mixed traffic conditions by Siti Raudhatul Fadilah, Hiroaki Nishiuchi, An Minh Ngoc

“…Microscopic simulation models are pivotal in transportation planning for their ability to intricately capture complex traffic patterns. This study specifically explores the role of dynamic route choice behavior within micro-simulation frameworks, emphasizing its application in the context of motorcycle-dominated traffic in Ninh Kiều District, Cần Thơ, Vietnam. …”
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Risk Indices Assessment of Different Cyber-Attack Actions for an SDN-Enabled IEC 61850 Substation Using Markov Decision Process by Zhihao Wu, Sugandh Seth, Haiyu Li, Zhirun Hu, James Yu

“…The proposed approach uses 1) the Purdue Model to model attack scenarios using cyber-physical devices at different layers based on typical protection control device arrangement in a substation and 2) the Markov Decision Process (MDP) model to assess cybersecurity risk indices for the substation. The assessment evaluates all possible attack patterns by an attacker to determine the severity of each attack path within the substation. …”
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A Comprehensive Data Description for LoRaWAN Path Loss Measurements in an Indoor Office Setting: Effects of Environmental Factors by Nahshon Obiri, Kristof van Laerhoven

“…Our empirical analysis confirms that transient phenomena such as reflections, scattering, interference, occupancy patterns (induced by environmental parameter variations), and furniture rearrangements can alter signal attenuation by as much as 10.58 dB, highlighting the dynamic nature of indoor propagation. …”
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Dual stream graph augmented transformer model integrating BERT and GNNs for context aware fake news detection by Hejamadi Rama Moorthy, N. J. Avinash, N. S. Krishnaraj Rao, K. R. Raghunandan, Radhakrishna Dodmane, Jeremy Joseph Blum, Lubna A Gabralla

“…Traditional methods primarily rely on textual analysis, often neglecting the structural patterns of news dissemination, which play a crucial role in determining credibility. …”
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Hybrid Prophet-NAR Model for Short-Term Electricity Load Forecasting by Winita Sulandari, Yudho Yudhanto, Etik Zukhronah, Isnandar Slamet, Hilman Ferdinandus Pardede, Paulo Canas Rodrigues, Muhammad Hisyam Lee

“…Traditional models like SARIMA and Singular Spectrum Analysis (SSA) have been widely used but often need to capture complex nonlinear patterns and deal with data uncertainties. This study aims to develop and evaluate a hybrid forecasting model that combines the Prophet model with a Neural Network Autoregressive (Prophet-NAR) model, referred to as PropNAR. …”
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Peculiarities of teaching students with mosaic thinking by S. A. Polevoy, V. V. Pavlova

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Optimizing rural waste management: Leveraging high-resolution remote sensing and GIS for efficient collection and routing by Xi Cheng, Jieyu Yang, Zhiyong Han, Guozhong Shi, Deng Pan, Likang Meng, Zhuojun Zeng, Zhanfeng Shen

“…Accurate assessment of distribution patterns and dynamic insights into rural populations is pivotal for comprehending domestic waste generation, recycling, and transportation in rural territories. …”
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Artificial intelligence technology in the clinical analysis of a patient with a mental disorder (case report) by Dmitry I. Nozdrachev, Maksim P. Marachev, Pavel S. Evgenov, Natalia N. Petrova

“…The work on "neuromorphizing" neural networks and adapting their analytical apparatus to human thinking patterns seems promising.…”
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AngleCam: Predicting the temporal variation of leaf angle distributions from image series with deep learning by Teja Kattenborn, Ronny Richter, Claudia Guimarães‐Steinicke, Hannes Feilhauer, Christian Wirth

“…AngleCam is based on pattern recognition with convolutional neural networks and trained with leaf angle distributions obtained from visual interpretation of more than 2500 plant photographs across different species and scene conditions. …”
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Time to link camel genomics and traits by bridging the phenotypic gap by Faisal Almathen, Faisal Almathen, Bashir Salim

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DiffuseGaitNet: Improving Parkinson’s Disease Gait Severity Assessment With a Diffusion Model Framework by Arshak Rezvani, Nasrin Ravansalar, Mohammad Ali Akhaee, Andrew J. Greenshaw, Russell Greiner, Maryam S. Mirian, Muhammad Yousefnezhad, Martin J. McKeown

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Layer-by-Layer Multifractal Scanning of Optically Anisotropic Architectonics of Blood Plasma Films: Fundamental and Applied Aspects by Alexander Ushenko, Natalia Pavlyukovich, Oksana Khukhlina, Olexander Pavlyukovich, Mykhaylo Gorsky, Iryna Soltys, Alexander Dubolazov, Yurii Ushenko, Olexander Salega, Ivan Mikirin, Jun Zheng, Zhebo Chen, Lin Bin

“…The practical aspect of this work is to evaluate the diagnostic potential of the Jones-matrix theziography method for identifying and differentiating changes in the birefringence of supramolecular networks in blood plasma facies caused by the long-term effects of COVID-19. …”
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Self-DSNet: A Novel Self-ONNs Based Deep Learning Framework for Multimodal Driving Distraction Detection by Mamun Or Rashid, Md. Mosarrof Hossen, Mohammad Nashbat, Mazhar Hasan-Zia, Ali K. Ansaruddin Kunju, Amith Khandakar, Azad Ashraf, Molla Ehsanul Majid, Saad Bin Abul Kashem, Muhammad E. H. Chowdhury

“…The proposed Self-DSNet model utilizes Self-Organizing Neural Network (Self-ONN) layers to enhance complex pattern learning within the data. …”
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