Semantic Reasoning Using Standard Attention-Based Models: An Application to Chronic Disease Literature by Yalbi Itzel Balderas-Martínez, José Armando Sánchez-Rojas, Arturo Téllez-Velázquez, Flavio Juárez Martínez, Raúl Cruz-Barbosa, Enrique Guzmán-Ramírez, Iván García-Pacheco, Ignacio Arroyo-Fernández

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Low Power Delay Product 8-bit ALU Design using Decoder and Data Selector by Nagarjuna Telagam, Nehru Kandasamy

“…The proposed ALU has two 4x1 data selectors, 2x4 decoder and an adder circuit as sub modules. …”
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Hybrid GRU–Random Forest Model for Accurate Atmospheric Duct Detection with Incomplete Sounding Data by Yi Yan, Linjing Guo, Jiangting Li, Zhouxiang Yu, Shuji Sun, Tong Xu, Haisheng Zhao, Lixin Guo

“…Atmospheric data forecasting traditionally relies on physical models, which simulate atmospheric motion and change by solving atmospheric dynamics, thermodynamics, and radiative transfer processes. …”
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Comparative Life Cycle Assessment of Perovskite Solar Cell Production: Mesoporous n‐i‐p Versus Inverted p‐i‐n Architectures by Joana Príncipe, Luísa Andrade, Teresa M. Mata, António A. Martins

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A Low Power Memory-Integrated Hardware BNN-MLP Model on an FPGA for Current Signals in a Biosensor by Geon-Hoe Kim, Dong-Gyun Kim, Sung-Jae Lee, Jong-Han Kim, Da-Yeong An, Hyejin Kim, Young-Gun Pu, Heejeong Jasmine Lee, Jun-Eun Park, Kang-Yoon Lee

“…This paper presents a method for processing and digitizing the current signal information output from biosensors and a hardware Artificial Intelligence (AI) model design that classifies data using low-power and compact AI algorithms to minimize the high-power consumption and on chip area of the Convolutional Neural Network (CNN) models used in biosensors. …”
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Doppler Effect Estimation and Compensation for Satellite Systems in Geolocation Problems by Marcello Asciolla, Angela Cratere, Francesco Dell'Olio

“…The main goal of the paper is to give real-time estimation and compensation strategy for the Doppler factor considering only the current instantaneous kinematic information, without the information on the history of the signal over time. Furthermore, data fitted from simulations show that a first degree polynomial model has a maximum error prediction on the order of less than 0.01 percent around Nadir pointing and can be appealing for fast computation of this correction with low-cost hardware based on Field Programmable Gate Array.…”
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Enabling smart parking for smart cities using Internet of Things (IoT) and machine learning by Mofadal Alymani, Lenah Abdulaziz Almoqhem, Dhuha Ahmed Alabdulwahab, Abdulrahman Abdullah Alghamdi, Hussain Alshahrani, Khalid Raza

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Steady-State Model Enabled Dynamic PEMFC Performance Degradation Prediction via Recurrent Neural Network by Qiang Liu, Weihong Zang, Wentao Zhang, Yang Zhang, Yuqi Tong, Yanbiao Feng

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Early Diagnosis of Knee Osteoarthritis With a Natural Language Processing–Driven Approach Based on Clinician Notes: Development and Validation Study by Narathip Thanyakunsajja, Kulsawasd Jitkajornwanich, Shan Xu, Donghee Shin, Pattama Charoenporn

“…ObjectiveWe propose a novel natural language processing–driven approach based on clinicians’ or doctors’ notes of patient-reported symptoms (text data only) for diagnosing knee OA. …”
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Performance Estimation of Low Power and Area-Efficient Parallel Pipelined FFT by Surya P, Arunachalaperumal C, Dhilipkumar S

“…It is also used in image and video processing and is critical for algorithms that manipulate pixels, scale, and compress data when many multiplications need to be performed quickly. …”
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Advanced Trans-BiGRU-QA Fusion Model for Atmospheric Mercury Prediction by Dong-Her Shih, Feng-I. Chung, Ting-Wei Wu, Bo-Hao Wang, Ming-Hung Shih

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Doping investigation of structured GaN devices by highly lateral resolved TOF-SIMS by Patrick Diehle, Stephan Gierth, Mickael Lejoyeux, Karen Geens, Matteo Borga, Frank Altmann

“…We employed highly laterally resolved TOF-SIMS to evaluate the doping levels of the n- and p- doped layers close to the gate trench. A lateral resolution of approx. 100 nm was achieved sufficient to resolve the gate trench geometry. …”
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DMoVGPE: predicting gut microbial associated metabolites profiles with deep mixture of variational Gaussian Process experts by Qinghui Weng, Mingyi Hu, Guohao Peng, Jinlin Zhu

“…DMoVGPE utilizes a dynamic gating mechanism, implemented through a neural network with fully connected layers and dropout for regularization, to select the most relevant Gaussian Process experts. …”
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Experimental Investigation of Large Time–Bandwidth Product Photonic Hilbert Transformer Based on Compact Bragg Grating by B. Liu, C. Sima, W. Yang, C. Cai, D. Liu, Y. Yu, J. Gates, M. Zervas, P. Smith

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An Efficient Ship Target Integrated Imaging and Detection Framework (ST-IIDF) for Space-Borne SAR Echo Data by Can Su, Wei Yang, Yongchen Pan, Hongcheng Zeng, Yamin Wang, Jie Chen, Zhixiang Huang, Wei Xiong, Jie Chen, Chunsheng Li

“…Therefore, we propose a ship target integrated imaging and detection framework (ST-IIDF) for SAR oceanic region data. A two-step filtering structure is added in the SAR imaging process to extract the potential areas of ship targets, which can accelerate the whole process. …”
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Short-term Wind Power Forecasting Based on BWO‒VMD and TCN‒BiGRU by LU Jing, ZHANG Yanru, WANG Rui

“…This combination model aims to use the advantages of TCN and BiGRU to process data and make more accurate predictions. Finally, the pre-dicted values of each subsequence are sequentially stacked to obtain the result, which is expected to provide reliable predictions for wind power generation.Results and DiscussionsThe RF algorithm is strategically employed to screen meteorological features and systematically rank their importance, enabling the accurate selection of features that significantly impact wind power forecasting. …”
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Attention-based integrated deep neural network architecture for predicting the effectiveness of data center power usage by Yang-Cheng Shih, Sathesh Tamilarasan, Chin-Sheng Chen, Omid Ali Zargar, Yean-Der Kuan

“…The integration of convolutional layers processes hourly data inputs efficiently, reducing complexity and improving pattern detection. …”
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COMPARISON OF POROSITY PREDICTION FROM SEISMIC DATA IN THE F3 BLOCK, NETHERLANDS USING MACHINE LEARNING by Urip Nurwijayanto Prabowo, Sudarmaji Sudarmaji, Jarot Setyowiyoto, Sismanto Sismanto

“…This forward generator incorporates geophysical knowledge to mitigate the limited amount of labelled data during the training process. Both generators utilize a convolutional neural network-gated recurrent unit network (CNN-GRU). …”
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Dynamic topology adaptability of adaptive multimodal transmission strategy based on environment perception in multi-hop routing of 5G vehicle network by Shengxia Tan, Xianshuang Zong, Feng Xiao

“…Then, graph sample and aggregation (GraphSAGE) is used to process the network topology and extract node and edge features of the data. …”
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Research on Data Repair of Pile-Type Adjustable Wind Turbine Foundation Monitoring Based on FST-ATTNet by WEI Huanwei, ZHAO Jizhang, ZHENG Xiao, TAN Fang, LIU Cong

“…A frequency-domain attention mechanism is introduced to enhance this process, adaptively assigning weights to frequency components and prioritizing those most relevant for data reconstruction. …”
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