Towards the Development of the Clinical Decision Support System for the Identification of Respiration Diseases via Lung Sound Classification Using 1D-CNN by Syed Waqad Ali, Muhammad Munaf Rashid, Muhammad Uzair Yousuf, Sarmad Shams, Muhammad Asif, Muhammad Rehan, Ikram Din Ujjan

“…A One-Dimensional Convolutional Neural Network (1D-CNN) consisting of convolutional layers, max pooling layers, dropout layers, and fully connected layers, was designed to classify the processed clips into four categories: normal, crackles, wheezes, and combined crackles and wheezes. …”
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Improved smart city security using a deep maxout network-based intrusion detection system with walrus optimization by Wahid Rajeh, Majed Aborokbah, Manimurugan S., Umar Albalawi, Ahamed Aljuhani, Osama Shibl Abdalghany Younes, Karthikeyan Periyasami

“…The DMN is configured with an architecture that includes multiple layers with maxout activation functions. These layers are capable of capturing complex patterns in the data, making the DMN particularly effective for identifying anomalies in IoT network traffic. …”
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An Effective Deep Neural Network Architecture for EEG-Based Recognition of Emotions by Khadidja Henni, Neila Mezghani, Amar Mitiche, Lina Abou-Abbas, Amel Benazza-Ben Yahia

“…Traditional methods often struggle to extract relevant features from noisy and high-dimensional data, and they typically fail to capture the complex temporal dependencies within EEG signals. …”
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Study on vibration characteristics of drill rod system in a coal mine drilling robot under interlaced soft and hard inclined coal seams by KANG Mingxia, WANG Zhongbin, LIU Xinhua, WEI Dong, ZHAO Lala

“…Horizontal drilling experiments were conducted under various layering conditions of soft and hard coal seams and different seam inclination angles. …”
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Towards Standardization of the Earth Observation Data Product Supply Chain – Are OCI Artifacts the Key to Ubiquitous and Scalable EO Data Handling? by S. Achtsnit, S. Achtsnit, M. Rösel, S. Meißl

“…By comparing self-contained data packages with modular, layered asset stores, we highlight trade-offs in retrieval performance, interoperability, and client complexity. …”
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Numerical investigation for optimizing thermal performance of Al2O3-TiO2/water hybrid nanofluid: An artificial neural network approach based on Levenberg–Marquardt algorithm by Khalid Arif, Syed Tauseef Saeed, Talha Anwar, Shajar Abbas, Muhammad Nauman Aslam

“…Magnetic fields and porosity influence the boundary layers and flow resistance, while thermal radiation facilitates heat dissipation. …”
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On the sensing performance improvement in SPR biosensor using ZnO and TMDCs architecture for cancer detection by Elham Jalili Tazekande Janze, Sholeh Alaei, Bahar Meshginqalam

“…The high sensitivity, specificity, and ability to analyze complex biological samples make them valuable tools in the struggle against cancer. …”
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Research on fuzzy evaluation of ecological safety of land resources in Pearl river Delta area based on DPSIR framework by Weihua Deng, Meng Li, Yanlong Guo

“…At the same time, it can reveal the complex factors affecting the eco-safety of land resources in the region and their interaction mechanisms. …”
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Characterization of “sweet spots” and optimization of volume fracturing parameters in deep tight reservoirs of Subei Basin by TANG Jiandong, ZHANG Shunkang, LIN Shiwei, GE Zhengjun, LIN Bo

“…In line with the strategy of “finding oil layers beneath oil layers”, exploration and development in the Jiangsu Oilfield have progressively extended into deeper formations. …”
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Integrating geospatial, hydrogeological, and geophysical data to identify groundwater recharge potential zones in the Sulaymaniyah basin, NE of Iraq by Sarkhel H. Mohammed, Musaab A. A. Mohammed, Hawber Ata Karim, Diary A. Mohammed AL-Manmi, Bakhtiar Qader Aziz, Asaad I. Mustafa, Péter Szűcs

“…These layers were ranked based on their relative influence on groundwater recharge and integrated using GIS-based weighted overlay analysis to generate groundwater potential maps. …”
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Optimized CNN-Bi-LSTM–Based BCI System for Imagined Speech Recognition Using FOA-DWT by Meenakshi Bisla, Radhey Shyam Anand

“…The designed CNN consists of one-dimensional (1-D) convolutional layers and max pooling layers for familiarizing local associations along with mining hierarchical connections, and the Bi-LSTM network acquires long-term dependencies from the features learned by the former CNN. …”
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MTLNFM: A Multi-Task Framework Using Neural Factorization Machines to Predict Patient Clinical Outcomes by Rui Yin, Jiaxin Li, Qiang Yang, Xiangyu Chen, Xiang Zhang, Mingquan Lin, Jiang Bian, Ashwin Subramaniam

“…Accurately predicting patient clinical outcomes is a complex task that requires integrating diverse factors, including individual characteristics, treatment histories, and environmental influences. …”
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Intelligent Functional Clustering and Spatial Interactions of Urban Freight System: A Data-Driven Framework for Decoding Heavy-Duty Truck Behavioral Heterogeneity by Ruixu Pan, Quan Yuan, Chen Liu, Jiaming Cao, Xingyu Liang

“…The results show that HDT travel patterns are not merely responses to freight demand but complex reflections of urban industrial structures, infrastructure networks, and policy environments. …”
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Feature pyramid attention network for audio‐visual scene classification by Liguang Zhou, Yuhongze Zhou, Xiaonan Qi, Junjie Hu, Tin Lun Lam, Yangsheng Xu

“…Abstract Audio‐visual scene classification (AVSC) poses a formidable challenge owing to the intricate spatial‐temporal relationships exhibited by audio‐visual signals, coupled with the complex spatial patterns of objects and textures found in visual images. …”
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Research on power data security full-link monitoring technology based on alternative evolutionary graph neural architecture search and multimodal data fusion by Zhenwan Zou, Bin Wang, Tao Chen, Jia Chen

“…Abstract This paper proposes a new framework for power data security monitoring, which aims to cope with complex and changeable network attacks. The current evolutionary graph neural architecture search (GNAS) method mainly focuses on the topological connection and feature fusion between network layers, but it often requires a lot of computing resources, and the real-time performance of the GNN (graph neural network) model is difficult to meet the requirements when facing dynamic attacks and changing data. …”
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Ensemble genetic and CNN model-based image classification by enhancing hyperparameter tuning by Wajahat Hussain, Muhammad Faheem Mushtaq, Mobeen Shahroz, Urooj Akram, Ehab Seif Ghith, Mehdi Tlija, Tai-hoon Kim, Imran Ashraf

“…In image classification, selecting the appropriate hyperparameters can substantially boost the model’s ability to learn intricate patterns and features from complex image data. Hyperparameter optimization helps to prevent overfitting by finding the right balance between complexity and generalization of a model. …”
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Simulation of a Multi-Stage Stress Field and Regional Prediction of Structural Fractures in the Tucheng Syncline, Western Guizhou, China by Jilin Wang, Lijun Jiang, Tiancheng Cang, Xiaozhi Zhou, Bicong Wang

“…The prediction of structural fractures in concealed coal-bearing strata has always been a complex problem. The purpose of this study was to clarify the tectonic evolution of the study area, i.e., the Tucheng syncline, since the coal-forming period and to predict the development of structural fractures. …”
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Prediction of crystalline structure evolution during solidification of aluminum at different cooling rates using a hybrid neural network model by Rafi B. Dastagir, Shorup Chanda, Farsia K. Chowdhury, Shahereen Chowdhury, K. Arafat Rahman

“…This research introduces a novel approach that employs a hybrid deep learning architecture, combining 1-dimensional convolutional neural network (Conv1D) layers with long short-term memory (LSTM) units, aimed at forecasting the crystallization behavior of pure aluminum throughout the solidification process. …”
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Calculation method of dewatering settlement in saturated loess stratum by Guohua DENG, Huyan GAO, Jianguo ZHENG, Wenlong YU, Jiawei KANG

“…In the construction of underground engineering with complex surrounding environment, reasonable prediction and evaluation of the influence of precipitation on the surrounding environment is a key problem to control the feasibility of the project. …”
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A Variational Multi-Scale Error Compensation Network for Single-Pixel Imaging by Jian Lin, Qiurong Yan, Quan Zou, Shida Sun, Zhen Wei, Hua Du

“…Deep learning-based compressed reconstruction networks can circumvent the complex iterative computations of traditional algorithms and achieve fast, high-quality reconstruction. …”
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