Talking about an emergency in an urgent situation: prosody and information by Charlotte Danino

“…This paper deals with the role of prosody as a semantic component in media speech. Based on CNN’s live broadcast on 9/11, linguistic productions are analyzed as spontaneous but heavily constrained speech since the breaking news format and both the temporal and cognitive pressures shape the ensuing utterances about this still ongoing event. …”
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Periodic Solutions of a System of Nonlinear Difference Equations with Periodic Coefficients by Durhasan Turgut Tollu

“…This paper is dealt with the following system of difference equations xn+1=an/xn+bn/yn,yn+1=cn/xn+dn/yn, where n∈ℕ0=ℕ∪0, the initial values x0 and y0 are the positive real numbers, and the sequences ann≥0, bnn≥0, cnn≥0, and dnn≥0 are two-periodic and positive. …”
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Enhancing Drought Forecast Accuracy Through Informer Model Optimization by Jieru Wei, Wensheng Tang, Pakorn Ditthakit, Jiandong Shang, Hengliang Guo, Bei Zhao, Gang Wu, Yang Guo

“…This study conducted a comparative analysis of VMD-JAYA-ARIMA, VMD-JAYA-LSTM, VMD-JAYA-CNN, and VMD-JAYA-Informer drought prediction models. …”
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Studi Awal Deteksi COVID-19 Menggunakan Citra CT Berbasis Deep Learning by Windra Swastika

“…Proses pelatihan dilakukan menggunakan CNN dengan arsitektur VGG16 dan optimizer SGD dan Adam. …”
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Colorectal cancer detection with enhanced precision using a hybrid supervised and unsupervised learning approach by Akella S. Narasimha Raju, K. Venkatesh, Ranjith Kumar Gatla, Eswara Prasad Konakalla, Marwa M. Eid, Nataliia Titova, Sherif S. M. Ghoneim, Ramy N. R. Ghaly

“…The method entails several steps with CNN models: ADa-22 and AD-22, transformer networks, and an SVM classifier, all inbuilt. …”
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Deep Learning Algorithms for Detection and Classification of Gastrointestinal Diseases by Mosleh Hmoud Al-Adhaileh, Ebrahim Mohammed Senan, Waselallah Alsaade, Theyazn H. H Aldhyani, Nizar Alsharif, Ahmed Abdullah Alqarni, M. Irfan Uddin, Mohammed Y. Alzahrani, Elham D. Alzain, Mukti E. Jadhav

“…In the classification stage, pretrained convolutional neural network (CNN) models are tuned by transferring learning to perform new tasks. …”
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Colorimetric aptasensor coupled with a deep-learning-powered smartphone app for programmed death ligand-1 expressing extracellular vesicles by Adeel Khan, Adeel Khan, Haroon Khan, Nongyue He, Zhiyang Li, Heba Khalil Alyahya, Yousef A. Bin Jardan

“…This combined approach offers a simple, sensitive, and specific tool for lung cancer detection using PD-L1@EVs. The addition of a CNN-powered smartphone app further eliminates the need for specialized equipment, making the colorimetric aptasensor more accessible for low-resource settings.…”
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Structural and functional connectivity coupling as an imaging marker for bone metastasis pain in lung cancer patients by Jiahui Zheng, Chengfang Wang, Xiaoyu Zhou, Yu Tang, Lin Tang, Yong Tan, Jing Zhang, Hong Yu, Jiuquan Zhang, Daihong Liu

“…In addition, the convolutional neural network (CNN) model was selected to analyze and classify three groups based on individualized networks. …”
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Solar Flare Forecasting Using Hybrid Neural Networks by Dan Xu, Pengchao Sun, Song Feng, Bo Liang, Wei Dai

“…We built two solar flare prediction models based on a combination of convolutional neural networks (CNN) and a temporal convolutional network (TCN), called CNN-TCN, and predicted whether a ≥C- or ≥M-class flare event would erupt in ARs in the next 24 hr, respectively. …”
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Comparing Waterbeds and Sand Beds for Cows: A Study at the UF/IFAS Dairy Unit by Klibs N. Galvão, Ori Eizenberg

“…Waterbeds for cows have recently gained popularity because of advertisements, news reports in outlets such as CNN. The UF/IFAS Dairy Unit (DU) provides a good opportunity to compare sand beds and waterbeds at optimal conditions. …”
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EMG- BASED HAND GESTURE RECOGNITION USING DEEP LEARNING AND SIGNAL-TO-IMAGE CONVERSION TOOLS by SABRINA AKTER, BIMAL KUMAR PRAMANIK, MD EKRAMUL HAMID

“…A very deep convolutional neural network (CNN) is proposed as the gesture classifier. The classifier is trained on 10-fold cross-validation framework and we achieve average recognition accuracy of 99.44%, sensitivity of 97.78% and specificity of 99.68% respectively. …”
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Robust Trajectory Tracking of Uncertain Systems via Adaptive Critic Learning by Ziliang Zhao, Qinglin Zhu, Bin Guo

“…To realize the optimal control, the derived Hamilton–Jacobi–Bellman equation (HJBE) is solved by training a critic neural network (CNN). Finally, two innovative critic learning techniques are suggested to calculate the unknown NN weights, where the convergence of NN weights can be guaranteed. …”
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Emotion Estimation Using Noncontact Environmental Sensing with Machine and Deep Learning Models by Tsumugi Isogami, Nobuyoshi Komuro

“…We employed environmental data to develop machine learning models, including Random Forest, Gradient Boosting Decision Trees, and the deep learning model CNN-LSTM, and evaluated their accuracy in estimating emotional states. …”
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Multisource DOA Estimation in Impulsive Noise Environments Using Convolutional Neural Networks by Dong Chen, Young Hoon Joo

“…Therefore, it is concluded that CNN can be well generalized for DOA estimation.…”
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Deteksi Kejadian Lalu Lintas pada Teks Twitter dengan Pendekatan Klasidikasi Multi-Label Berbasis Deep Learning by Luthfi Atikah, Diana Purwitasari, Nanik Suciati

“…Klasifikasi dilakukan dengan menggunakan pendekatan deep learning (CNN dan LSTM) dan word embedding (word2vec dan fastText) dengan augmentasi dan non-augmentasi data. …”
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Deteksi Pneumonia Menggunakan Citra Sinar-X Paru berbasis Residual Network by Muhammad Adzkia, Firzal Arland, Agung Wahyu Setiawan

“…Fokus dari studi ini adalah membandingkan kinerja Mask R-CNN dengan ResNet-50 & 101 sebagai backbone pada deteksi pneumonia menggunakan citra Sinar-X paru. …”
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A Novel Convolutional Neural Network-Based Approach for Fault Classification in Photovoltaic Arrays by Farkhanda Aziz, Azhar Ul Haq, Shahzor Ahmad, Yousef Mahmoud, Marium Jalal, Usman Ali

“…It is observed that the proposed method involving fine-tuned pre-trained CNN outperforms existing techniques, achieving a high fault detection accuracy of 73.53%. …”
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Drug Efficacy Recommendation System of Glioblastoma (GBM) Using Deep Learning by Sajid Naveed, Mujtaba Husnain, Ali Samad, Amna Ikram, Hina Afreen, Ghulam Gilanie, Najah Alsubaie

“…A panel of 47 genes associated with GBM was processed using two deep learning models: Artificial Neural Network (ANN) and Convolutional Neural Network (CNN). This approach addresses the challenge of personalized treatment for GBM, offering the potential for improved therapeutic outcomes. …”
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Sandpiper optimization with hybrid deep learning model for blockchain-assisted intrusion detection in iot environment by Mimouna Abdullah Alkhonaini, Manal Abdullah Alohali, Mohammed Aljebreen, Majdy M. Eltahir, Meshari H. Alanazi, Ayman Yafoz, Raed Alsini, Alaa O. Khadidos

“…Besides, the SPOHDL-ID technique employs the HDL model for intrusion detection, which involves the design of a convolutional neural network with a stacked autoencoder (CNN-SAE) model. The beetle search optimizer algorithm (BSOA) method is used for the hyperparameter tuning procedure to increase the recognition outcomes of the CNN-SAE technique. …”
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Genome data based deep learning identified new genes predicting pharmacological treatment response of attention deficit hyperactivity disorder by Yilu Zhao, Zhao Fu, Eric J. Barnett, Ning Wang, Kangfuxi Zhang, Xuping Gao, Xiangyu Zheng, Junbin Tian, Hui Zhang, XueTong Ding, Shaoxian Li, Shuyu Li, Qingjiu Cao, Suhua Chang, Yufeng Wang, Stephen V. Faraone, Li Yang

“…Notably, the variant that contributed most to the CNN model was NKAIN2, an ADHD-related gene, which is also associated with metabolic processes. …”
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