Energy consumption prediction using modified deep CNN-Bi LSTM with attention mechanism by Adel Binbusayyis, Mohemmed Sha

“…Followed by that, Modified Deep CNN-Bi-LSTM (Convolutional Neural Network and Bi-directional Long Short Term Memory) with attention mechanism is utilized for regression which extracts temporal and spatial complex features. …”
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Dual-Branch Deep Learning with Dynamic Stage Detection for CT Tube Life Prediction by Zhu Chen, Yuedan Liu, Zhibin Qin, Haojie Li, Siyuan Xie, Litian Fan, Qilin Liu, Jin Huang

“…This architecture consists of two specialized branches: a residual self-attention BiLSTM (RSA-BiLSTM) and a multi-layer dilation temporal convolutional network (D-TCN). The RSA-BiLSTM branch extracts multi-scale features and also enhances the long-term dependency modeling capability for temporal data. …”
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Detecting Zero-Day Web Attacks with an Ensemble of LSTM, GRU, and Stacked Autoencoders by Vahid Babaey, Hamid Reza Faragardi

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Comparative analysis of machine learning models for predicting water quality index in Dhaka’s rivers of Bangladesh by Mosaraf Hosan Nishat, Md. Habibur Rahman Bejoy Khan, Tahmeed Ahmed, Syed Nahin Hossain, Amimul Ahsan, M. M. El-Sergany, Md. Shafiquzzaman, Monzur Alam Imteaz, Mohammad T. Alresheedi

“…Among the evaluated ML models, ANN and Random Forest Regressor performed the best. …”
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A Novel Approach to Android Malware Intrusion Detection Using Zero-Shot Learning GANs by Syed Atir Raza Shirazi, Mehwish Shaikh

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Deep representation learning using layer-wise VICReg losses by Joy Datta, Rawhatur Rabbi, Puja Saha, Aniqua Nusrat Zereen, M. Abdullah-Al-Wadud, Jia Uddin

“…Abstract This paper presents a layer-wise training procedure of neural networks by minimizing a Variance-Invariance-Covariance Regularization (VICReg) loss at each layer. …”
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Classification of Coronavirus Disease 2019 and Pneumonia Based on US-VM Model by Nursah Dincer, Pelin Görgel

“…Methods: In this study, a model called Unsharp Swin transformer and Vision transformer network with Mobile Network Version 2 (MobileNetV2) (US-VM) was developed to classify the lung images. …”
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UNDERSTANDING THE KNOWLEDGE ECOSYSTEM: CORE AND FORMS by Iryna Kalenyuk, Antonina Djakona, Yevgen Panchenko

“…The authors employ a system-structural analysis to examine the evolution of conceptualisations of the terms "ecosystem" and "knowledge ecosystem". …”
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Graph-enhanced implicit aspect-level sentiment analysis based on multi-prompt fusion by Xu Li, Xinlong Wang, Chunlong Yao, Yang Li

“…The analysis also seeks to determine the sentiment tendency of each aspect in the evaluated sentence. The difficulty of semantic comprehension is greatly increased by the fact that the evaluation texts include omitted expressions. …”
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ViSwNeXtNet Deep Patch-Wise Ensemble of Vision Transformers and ConvNeXt for Robust Binary Histopathology Classification by Özgen Arslan Solmaz, Burak Tasci

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Ultrasound-based machine learning model to predict the risk of endometrial cancer among postmenopausal women by Yi-Xin Li, Yu Lu, Zhe-Ming Song, Yu-Ting Shen, Wen Lu, Min Ren

“…Super-resolution (SR) technique was applied to enhance image quality before feature extraction. Radiomics features were extracted using Pyradiomics, and deep learning features were derived from convolutional neural network (CNN). …”
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Towards Parkinson’s Disease Detection Through Analysis of Everyday Handwriting by Jeferson David Gallo-Aristizabal, Daniel Escobar-Grisales, Cristian David Ríos-Urrego, Jesús Francisco Vargas-Bonilla, Adolfo M. García, Juan Rafael Orozco-Arroyave

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Neural-Driven heuristic for strip packing trained with Black-Box optimization by Mariusz Kaleta, Tomasz Śliwiński

“…In this paper, we propose a neural-driven constructive heuristic that leverages a lightware neural network trained via black-box optimization to dynamically evaluate item placement decisions. …”
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A fact-checking tool based on Artificial Intelligence to fight disinformation on Telegram by Francisco-Javier Cantón-Correa, Lucia Ballesteros-Aguayo, Andrés Montoro-Montarroso

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NMT-translation – basic models, quality assessment by I. A. Borunov

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An integrative conservation and management strategy based on biological and cultural diversity assessment: A case study of Miaoling mountainous region, China by Xiaoqi Li, Jiaojiao Zhu, Xinyi Lyu, Yiyun Sun, Chuandong Tan, Bin Zhang, Paolo Tarolli, Qichi Yang

“…To effectively protect the bio-cultural features in the Miaoling region, this study proposes a strategy for establishing a conservation framework based on the evaluation of bio-cultural diversity for protection. …”
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A Time–Frequency-Based Data-Driven Approach for Structural Damage Identification and Its Application to a Cable-Stayed Bridge Specimen by Naiwei Lu, Yiru Liu, Jian Cui, Xiangyuan Xiao, Yuan Luo, Mohammad Noori

“…The performance of the proposed method was evaluated by comparing it with various traditional pre-trained networks. …”
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Innovative Approach for Diabetic Retinopathy Severity Classification: An AI-Powered Tool using CNN-Transformer Fusion by Khosro Rezaee, Fateme Farnami

“…Objective: This research aimed to develop and evaluate a deep learning structure combining Convolutional Neural Networks (CNNs) and transformer architecture to improve the accuracy, reliability, and generalizability of DR detection and severity classification. …”
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Predicting Architectural Space Preferences Using EEG-Based Emotion Analysis: A CNN-LSTM Approach by Ju Eun Cho, Se Yeon Kang, Yi Yeon Hong, Han Jong Jun

“…Two convolutional neural network long short-term memory deep learning models were trained on the EEG data: one using all the ERP segments, and the other focusing on statistically significant ERP features. …”
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Iterative Assessment of Edge Criticality: Efficiency Enhancement or Hidden Insufficiency Detection by Vasily Lubashevskiy, Hamza Ejjbiri, Ihor Lubashevsky

“…Two main approaches are commonly used to rank edges based on their importance for maintaining network connectivity. The first is the Static approach, which relies on a single evaluation of topological features. …”
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