SOME FEATURES OF CYTOKINE PROFILE IN SEVERE PYOINFLAMMATORY DISEASES OF FACE AND NECK by L. M. Karzakova, I. A. Sidorov, A. N. Volkov, S. I. Kudrjashov

“…A clinically unfavorable pattern of cytokine profile was specified in patients with severe pyoinflammatory diseases of face and neck region. Its common feature is an imbalance in cytokine network associated with overproduction of immunosuppressive cytokines.…”
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Russian Science and Technology Foresight – 2030: Key Features and First Results by Alexander Sokolov, Alexander Chulok

“… This paper reviews national features in the general evolution of science and technology (S&T) foresight over the last decade. …”
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Ensemble of features for efficient classification of high-resolution remote sensing image by Gladima Nisia T, Rajesh S

“…Recent trend moves in extracting the features from the image using neural networks with no human intervention. …”
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Research on filter-based adversarial feature selection against evasion attacks by Qimeng HUANG, Miaomiao WU, Yun LI

“…With the rapid development and widespread application of machine learning technology, its security has attracted increasing attention, leading to a growing interest in adversarial machine learning.In adversarial scenarios, machine learning techniques are threatened by attacks that manipulate a small number of samples to induce misclassification, resulting in serious consequences in various domains such as spam detection, traffic signal recognition, and network intrusion detection.An evaluation criterion for filter-based adversarial feature selection was proposed, based on the minimum redundancy and maximum relevance (mRMR) method, while considering security metrics against evasion attacks.Additionally, a robust adversarial feature selection algorithm was introduced, named SDPOSS, which was based on the decomposition-based Pareto optimization for subset selection (DPOSS) algorithm.SDPOSS didn’t depend on subsequent models and effectively handles large-scale high-dimensional feature spaces.Experimental results demonstrate that as the number of decompositions increases, the runtime of SDPOSS decreases linearly, while achieving excellent classification performance.Moreover, SDPOSS exhibits strong robustness against evasion attacks, providing new insights for adversarial machine learning.…”
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FSS-ULivR: a clinically-inspired few-shot segmentation framework for liver imaging using unified representations and attention mechanisms by Ripon Kumar Debnath, Md. Abdur Rahman, Sami Azam, Yan Zhang, Mirjam Jonkman

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Contrastive Feature Disentanglement via Physical Priors for Underwater Image Enhancement by Fei Li, Li Wan, Jiangbin Zheng, Lu Wang, Yue Xi

“…To address these challenges, we propose a contrastive feature disentanglement network (CFD-Net) that systematically addresses underwater image degradation. …”
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Improved Energy Efficient Anytime Optimistic Algorithm for PEGASIS to Extend Network Lifetime in Homogeneous and Heterogeneous Networks by Tadele A. Abose, Venumadhav Tekulapally, Samuel T. Daka, Diriba C. Kejela, Alemayehu E. Duguma, Desalegn T. Degaga

“…The proposed algorithm demonstrates a 40% improvement across all evaluated features compared to existing algorithms.…”
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An Investigation into the Utilisation of CNN with LSTM for Video Deepfake Detection by Sarah Tipper, Hany F. Atlam, Harjinder Singh Lallie

“…The integration of Convolutional Neural Network (CNN) with Long Short-Term Memory (LSTM) has proven to be a promising approach for improving video deepfake detection, achieving near-perfect accuracy. …”
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Empowering Smallholder Farmers with UAV-Based Early Cotton Disease Detection Using AI by Halimjon Khujamatov, Shakhnoza Muksimova, Mirjamol Abdullaev, Jinsoo Cho, Cheolwon Lee, Heung-Seok Jeon

“…The proposed model integrates an EfficientNetV2-S backbone with a Dual-Attention Feature Pyramid Network (DA-FPN) and a novel Early Symptom Emphasis Module (ESEM) to enhance sensitivity to subtle visual cues such as chlorosis, minor lesions, and texture irregularities. …”
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Semiconductor Wafer Defect Recognition Based on Improved Coordinate Attention Mechanism by Hao He, Yuanjie Wei, Xionghao Lin, Minmin Zhu, Haizhong Zhang

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A multi-scale multi-channel CNN introducing a channel-spatial attention mechanism hyperspectral remote sensing image classification method by Ru Zhao, Chaozhu Zhang, Dan Xue

“…Aiming the problems that the classification performance of hyperspectral images in existing classification algorithms is highly dependent on spatial-spectral information and that detailed features are ignored in single convolutional channel feature extraction, resulting in poor generalization performance of the feature extraction model, a multi-scale multi-channel convolutional neural network (MMC-CNN) model is proposed in this paper. …”
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Feature Integration Strategies for Neural Speaker Diarization in Conversational Telephone Speech by Juan Ignacio Alvarez-Trejos, Alicia Lozano-Diez, Daniel Ramos

“…This paper addresses the challenge of optimizing end-to-end neural diarization systems for conversational telephone speech, focusing on diverse acoustic features beyond traditional Mel-filterbanks. We present a methodological framework for integrating and analyzing different feature types as input to the well-known End-to-End Neural Diarization with Encoder Decoder Attractors (EEND-EDA) model, focusing on Emphasized Channel Attention, Propagation and Aggregation in Time Delay Neural Network (ECAPA-TDNN) embeddings and Geneva Minimalistic Acoustic Parameter Sets (GeMAPS). …”
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Multi-Scale Hierarchical Feature Fusion for Infrared Small-Target Detection by Yue Wang, Xinhong Wang, Shi Qiu, Xianghui Chen, Zhaoyan Liu, Chuncheng Zhou, Weiyuan Yao, Hongjia Cheng, Yu Zhang, Feihong Wang, Zhan Shu

“…Although convolutional neural networks (CNNs) increase robustness to diverse scenes with a data-driven paradigm, many CNN-based methods are insufficient in capturing fine-grained details necessary for small targets and are less effective during multi-scale feature fusion. …”
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Bitcoin price direction prediction using on-chain data and feature selection by Ritwik Dubey, David Enke

“…The research then explores advanced neural networks for next day price direction prediction, including the Convolutional Neural Network-Long-Short Term Memory (CNN-LSTM) and the Temporal Convolutional Network (TCN). …”
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Predicting danceability and song ratings using deep learning and auditory features by Wei Wu

“…Our model integrates a Bidirectional Long Short-Term Memory (BiLSTM) network to capture sequential and contextual patterns from categorical inputs, alongside a Residual Network (ResNet) that extracts hierarchical representations from numerical auditory features. …”
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Clinical Features and Outcomes of Pediatric MYH7‐Related Dilated Cardiomyopathy by Fernando de Frutos, Juan Pablo Ochoa, Gregory Webster, Mark Jansen, Paloma Remior, Torsten B. Rasmussen, Maria Sabater‐Molina, Roberto Barriales‐Villa, Francesca Girolami, Sergi Cesar, M. Eugenia Fuentes‐Cañamero, Reyes Alvarez García‐Rovés, Karim Wahbi, Javier Limeres, Milos Kubanek, Martijn G. Slieker, Georgia Sarquella‐Brugada, Dominic J. Abrams, Dennis Dooijes, Fernando Domínguez, Pablo Garcia‐Pavia

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Morphology and dynamics of sporadic E layers observed by amateur radio by WenYu Hao, Tao Yu, Yang-Yi Sun, Jin Wang, LiHui Qiu

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Development and evaluation of machine learning models for premixed flame classification in different hydrogen-natural gas proportions using images and audio by Pedro Narvaez, Alejandro Lopez, Jousef E. Karam, Alejandro Restrepo, Andrés A. Amell

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Botnets’ similarity analysis based on communication features and D-S evidence theory by ZANG Tian-ning1, YUN Xiao-chun1, ZHANG Yong-zheng2, MEN Chao-guang1, CUI Xiang2

“…A potential hidden relationship may exist among different zombie groups.A method to analyze the relationship among botnets was proposed based on the communication activities.The method extracted several communication fea-tures of botnet,including the number of flows per hour,the number of packets per flow,the number of flows per IP and the packet payloads.It defined similarity statistical functions of the communication features,and built the analysis model of botnets relationship based on the advanced dempster-shafer（D-S） evidence theory to synthetically evaluate the simi-larities between different zombie groups.The experiments were conducted using several botnet traces.The results show that the method is valid and efficient,even in the case of encrypted botnet communication messages.Moreover,the ideal processing results is achieved by applying our method to analyze the data captured from the security monitoring platform of computer network,as well as compare with similar work.…”
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SPECIFIC STAGE-DEPENDENT FEATURES OF CYTOKINE CASCADE IN THE PATIENTS WITH BRONCHIAL ASTHMA by L. V. Ryabova, A. V. Zurochka

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