VCNet: Optimized Deep Learning framework with deep feature extraction and genetic algorithm for multiclass rice crop disease detection by Sanam Salman Kazi, Bhakti Palkar, Dhirendra Mishra

“…Further the model goes through two level optimization process where optimal hyperparameters identified through experimentation is given as parameters to genetic algorithm for optimization of VCNet during training. …”
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Evaluation of Landslide Susceptibility Zonation applying Fuzzy Gamma Operators in Taleghanroud Watershed of Qazvin Province by Jamal Mosaffaie, Amin Salehpour Jam, Faramarz Sarfaraz, Samad Shadfar

“…A total of 15 landslides were identified, 70% of which were used to model and 30% of which were used to evaluate the results of the models. …”
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3D printing for advanced surgical planning in veterinary medicine—case studies, methods and future perspectives by Ramon Rodrigues de Lima, Lucas Rannier Ribeiro Antonino Carvalho, Lucas Rannier Ribeiro Antonino Carvalho

“…To construct the digital models, the CT data are processed using inVesalius 3.1 software, a Brazilian program for segmentation and rendering of medical images. …”
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Nonlinear Dynamics of a Vibratory Cone Crusher with Hysteretic Force and Clearances by Jing Jiang, Qing-Kai Han, Chao-Feng Li, Hong-Liang Yao, Shu-Ying Liu

“…Based on the analysis on crushing process and hysteresis of material layers, a hysteretic model with symmetrical clearances is presented. …”
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Online evaluation method for MMC submodule capacitor aging based on CapAgingNet by Xinlan Deng, Youhan Deng, Liang Qin, Weiwei Yao, Min He, Kaipei Liu

“…Subsequently, the CapAgingNet model is introduced, incorporating key technical modules to enhance performance: the Deep Stem module, which extracts larger receptive fields through multiple convolution layers and mitigates the impact of data sparsity in capacitor aging on feature extraction; the efficient channel attention (ECA) module, utilizing one-dimensional convolution for dynamic weighting to adjust the importance of each channel, thereby enhancing the ability of the model to process high-dimensional features in capacitor aging data; and the multiscale feature fusion (MSF) module, which integrates capacitor aging information across different scales by combining fine-grained and coarse-grained features, thus improving the capacity of the model to capture high-frequency variation characteristics. …”
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A passage on the dynamics of physical-spatial development of Abar city using GIS by Ali Mohammadi, Shahram Amirentakhabi, Azam Mohamadzade

“…By preparing information layers such as land availability, topography, rural points, slope, communication network, cemetery, river and entering these layers into the GIS environment and analyzing them in the geographic information system database, using the AHP model. …”
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A Framework for the Innovation Management Capacity: Empirical Evidence from the Porto Digital Cluster in Brazil by Sidney de Lima Pinto, Jorge Muniz, Claudia Regina de Freitas, José Roberto Dale Luche

“…This study contributes to the literature by proposing an empirically validated model that addresses gaps related to dynamic capabilities and integrated innovation processes. …”
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Observations of methane net sinks in the upland Arctic tundra by A. Donateo, D. Famulari, D. Giovannelli, D. Giovannelli, D. Giovannelli, D. Giovannelli, D. Giovannelli, A. Mariani, M. Mazzola, S. Decesari, G. Pappaccogli, G. Pappaccogli

“…The observed net summertime methane uptake is correlated with the activation and aeration of soil microorganisms, and it declines in winter due to the presence of snow cover and because of the negative soil temperature which triggers the freezing process of the active layer water content but then rebounds during the melting period. …”
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Mechanistic Study of Oil Adsorption Behavior and CO₂ Displacement Mechanism Under Different pH Conditions by Xinwang Song, Yang Guo, Yanchang Chen, Shiling Yuan

“…Three quartz surface models with varying ionization degrees (0%, 9%, 18%, corresponding to pH 2–4, 5–7, and 7–9) were constructed to simulate different pH environments. …”
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Scottish softwood biochar for water remediation targeting selected persistent organic pollutants by Mohammad Umair Jamal, Ashleigh Fletcher, Alan Baby, Isaac Maso, Lidija Šiller

“…Morphological analysis revealed a layered carbon structure and spectroscopic analysis showed the presence of oxygen and nitrogen-based functionalities alongside 80% atomic carbon. …”
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Conventional Construction and 3D Printing: A Comparison Study on Material Cost in Jordan by Rawan Allouzi, Wael Al-Azhari, Rabab Allouzi

“…Such objects can be constructed in any shape using digital model data. First, this paper presents a state-of-the-art review of the advances in 3D printing processes of construction. …”
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Study on influence of dense medium on impact pressure of detonation waves subjected to contact blasts by MENG Yuanpei, MA Yue, HE Yuan, GUO Lei, LING Qi, ZHOU Jie, WANG Chuanting, HE Yong

“…Additionally, finite element analysis software was used to simulate the initiation processes of three types of explosives with different dense medium acting as buffer layers. …”
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Android Malware Category and Family Identification Using Parallel Machine Learning by Ahmed Hashem El Fiky, Mohamed Ashraf Madkour, Ayman El Shenawy

“…This paper proposes an effective systematic and functional parallel machine-learning model for the dynamic detection of Android malware categories and families.  …”
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EQUIPMENT AND SCIENTIFIC STUDIES OF EXPERIMENTAL DATA ON STORAGE OF WHEAT GRAIN by Yu. F. Markov, A. N. Buriak, L. G. Eresko

“…Such a low value was due, in particular, to the fact that samples of model-stored grain had a limited volume and do not reproduce the mass transfer processes that involve deep layers of the grain mass (because of the mass absence), which takes place during storage of grain in an industrial environment. …”
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A Novel Three‐Phase Interface Premelting Theory for Determining Unfrozen Water Content in Unsaturated Soil by Xusheng Wan, Jishuai Zhu, Wansheng Pei, Weibo Liu, Fengxi Zhou

“…The model resolves the phase transition processes at the interfaces of air‐water‐ice‐soil by determining air‐phase distribution within pore spaces and incorporating interfacial melting effects at air‐ice and soil‐ice boundaries. …”
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Leveraging spatial dependencies and multi-scale features for automated knee injury detection on MRI diagnosis by Jianhua Sun, Ye Cao, Ying Zhou, Baoqiao Qi

“…The integration of Grad-CAM visualizations enhances the interpretability of KneeXNet, enabling radiologists to understand and validate the model’s decision-making process.…”
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A comprehensive framework for multi-modal hate speech detection in social media using deep learning by R. Prabhu, V. Seethalakshmi

“…The framework integrates CNNs to extract n-gram patterns and RNNs to model long-range dependency up to sequences of up to 100 tokens. …”
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Aerosol forces mesoscale secondary circulations occurrence: evidence of emission reduction by Jixiang Li, Haipeng Yu, Markku Kulmala, Tom V. Kokkonen, Kai Tang, Jianmin Ma, Zeyong Hu, Siyu Chen, Yuling Hu, Rong Dai, Bofei Zhang, Hongyu Luo, Shu Tao

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Additive Manufacturing for Automotive Radar Sensors Using Copper Inks and Pastes by Nihesh Mohan, Fabian Steinberger, Sonja Wächter, Hüseyin Erdogan, Gordon Elger

“…AM will allow significant cost reduction by eliminating parts and simplifying the manufacturing process. Different AM technologies for the coils were investigated, first, by applying the conductive traces by fused deposition modeling (FDM), and, second, by printing copper particle-free inks and pastes. …”
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Deteksi Covid-19 pada Citra Sinar-X Dada Menggunakan Deep Learning yang Efisien by Novanto Yudistira, Agus Wahyu Widodo, Bayu Rahayudi

“…In this study, we tested and compared the capabilities of ShuffleNet, EfficientNet, and ResNet because they have a smaller number of parameters than usual deep CNN, such as VGGNet or FullConv which uses a full convolution layers with a robust detection capability. We used 1125 x-ray images and achieved an accuracy of 86.93% with a number of model parameters of 18.55 times less than EfficientNet and 22.36 times less than ResNet50 to detect 3 categories namely Covid-19, Pneumonia, and normal through the 5-fold cross validation. …”
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