The Settlement Structure Is Reflected in Personal Investments: Distance-Dependent Network Modularity-Based Measurement of Regional Attractiveness by Laszlo Gadar, Zsolt T. Kosztyan, Janos Abonyi

“…How can the structure of investment patterns characterize the attractiveness and development of economic regions? …”
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Probabilistic Forecasting of Crude Oil Prices Using Conditional Generative Adversarial Network Model with Lévy Process by Mohammed Alruqimi, Luca Di Persio

“…Recent research highlights Generative Adversarial Networks (GANs) as a promising alternative approach for capturing intricate patterns in time series data, leveraging the adversarial learning framework. …”
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The use of artificial neural network algorithms to enhance tourism economic efficiency under information and communication technology by Yun Tian, Xiaojie Tang

“…This work proposes an analysis method based on the artificial neural network to predict tourist behavior patterns through big data analysis, thereby optimizing the allocation of tourism resources. …”
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Northern goshawk optimization for optimal reactive power compensation in photovoltaic low-voltage radial distribution networks by Shaikh Sohail Mohiyodin, Rajesh Maharudra Patil, Dr MS Nagaraj

“…Considering the PVs and CBs of the network, a modified IEEE 33-bus test system was used to evaluate the effectiveness of the suggested methodology.…”
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Toward connectivity of a disconnected cluster in partitioned wireless sensor network for time-critical data collection by Kashif Nasr, Noor Muhammad Khan

“…These networks have diverse communication patterns due to non-uniform sensing activities at various locations in the environment being monitored. …”
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Enhanced novelty approaches for resource allocation model for multi-cloud environment in vehicular Ad-Hoc networks by R. Augustian Isaac, P. Sundaravadivel, V. S. Nici Marx, G. Priyanga

“…The proposed method begins by the meticulous feature extraction from the Vehicular network model, with attributes such as mobility patterns, transmission medium, bandwidth, storage capacity, and packet delivery ratio. …”
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Gaitformer: a spatial-temporal attention-enhanced network without softmax for Parkinson’s disease early detection by Shupei Jiao, Hua Huo, Wei Liu, Changwei Zhao, Lan Ma, Jinxuan Wang, Ningya Xu, Chen Zhang, Dongfang Li

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PhishingGNN: Phishing Email Detection Using Graph Attention Networks and Transformer-Based Feature Extraction by Mejdl Safran, Abdulbaset Musleh

“…This study introduces PhishingGNN, a hybrid model that integrates DistilBERT for context-aware text analysis with Graph Attention Networks (GAT) to model email metadata and content as graph structures, detecting subtle phishing patterns overlooked by traditional methods. …”
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Neural Network Approach for Fatigue Crack Prediction in Asphalt Pavements Using Falling Weight Deflectometer Data by Bishal Karki, Sayla Prova, Mayzan Isied, Mena Souliman

“…This study develops an artificial neural network (ANN) model to predict the onset and progression of fatigue cracking. …”
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Sky Temperature Forecasting in Djibouti: An Integrated Approach Using Measured Climate Data and Artificial Neural Networks by Hamda Abdi, Abdou Idris, Anh Dung Tran Le

“…To address these limitations, an ANN model was trained, validated, and tested on the collected data to capture complex patterns and relationships in the data. The ANN model demonstrated superior performance over existing empirical correlations, providing more accurate and reliable sky temperature predictions for Djibouti’s hot and humid climate. …”
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Examining changes in social care referrals during the 2021 Winter Storm Uri in the Unite Texas network by Zackery White, Amanda Terry, Gillian Feldmeth, Alyssa Altstaedter, Halima Ahmadi-Montecalvo

“…Future research should investigate whether these patterns reflect intentional, proactive coordination decisions versus incidental network activity, assess their consistency across different hazards and networks, and evaluate client and provider satisfaction with the referral process and outcomes.…”
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Attention-based integrated deep neural network architecture for predicting the effectiveness of data center power usage by Yang-Cheng Shih, Sathesh Tamilarasan, Chin-Sheng Chen, Omid Ali Zargar, Yean-Der Kuan

“…The integration of convolutional layers processes hourly data inputs efficiently, reducing complexity and improving pattern detection. A subsequent flattening layer optimizes accuracy, while a dual-layered LSTM and a deep neural network delve into frequency, temporal dynamics, and complex data relationships. …”
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Enhancing sound-based classification of birds and anurans with spectrogram representations and acoustic indices in neural network architectures by Fábio Felix Dias, Moacir Antonelli Ponti, Rosane Minghim

“…With that, we propose guidelines for using neural networks to classify species based on their sound patterns, even for a small dataset. …”
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Hybrid Contrastive Learning With Attention-Based Neural Networks for Robust Fraud Detection in Digital Payment Systems by Md Shahin Alam Mozumder, Mohammad Balayet Hossain Sakil, Md Rokibul Hasan, Md Amit Hasan, K. M Nafiur Rahman Fuad, M. F. Mridha, Md Rashedul Islam, Yutaka Watanobe

“…Fraud detection in digital payment systems is a critical challenge due to the growing complexity of transaction patterns and the inherent class imbalance in datasets. …”
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Classification of Short-Segment Pediatric Heart Sounds Based on a Transformer-Based Convolutional Neural Network by Md Hassanuzzaman, Samit Kumar Ghosh, Mohammad Nurul Akhtar Hasan, Mohammad Abdullah Al Mamun, Khawza I. Ahmed, Raqibul Mostafa, Ahsan H. Khandoker

“…Phonocardiograms (PCGs), as a non-invasive and cost-effective diagnostic modality, capture vital acoustic signals that reflect the mechanical activity of the heart and can reveal pathological patterns associated with various CHD types. This study investigates the minimum signal duration required for accurate automatic classification of heart sounds and evaluates signal quality using the root mean square of successive differences (RMSSD) and the zero-crossing rate (ZCR). …”
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Forecasting Stock Market Volatility Using Hybrid of Adaptive Network of Fuzzy Inference System and Wavelet Functions by Abdullah H. Alenezy, Mohd Tahir Ismail, S. Al Wadi, Muhammad Tahir, Nawaf N. Hamadneh, Jamil J. Jaber, Waqar A. Khan

“…This study aims to model and enhance the forecasting accuracy of Saudi Arabia stock exchange (Tadawul) data patterns using the daily stock price indices data with 2026 observations from October 2011 to December 2019. …”
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Attention-Guided Sample-Based Feature Enhancement Network for Crowded Pedestrian Detection Using Vision Sensors by Shuyuan Tang, Yiqing Zhou, Jintao Li, Chang Liu, Jinglin Shi

“…To address this, we introduce a novel architecture termed the Attention-Guided Feature Enhancement Network (AGFEN), designed within the deep convolutional neural network framework. …”
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An Autism Spectrum Disorder Identification Method Based on 3D-CNN and Segmented Temporal Decision Network by Zhiling Liu, Ye Chen, Xinrui Dong, Jing Liu

“…This approach not only enhances the efficiency of spatiotemporal feature extraction but also improves the model’s ability to learn complex brain activity patterns. (3) Results: The proposed method was evaluated on the ABIDE dataset, which includes 1035 subjects from 17 different brain imaging centers. …”
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DepthFormer: Depth‐Enhanced Transformer Network for Semantic Segmentation of the Martian Surface From Rover Images by Yuan Ma, Zhaojin Li, Bo Wu, Ran Duan

“…This semantic information reveals underlying features and patterns, offering valuable scientific insights. Advanced deep learning techniques, particularly Transformers, can enhance semantic segmentation and image interpretation, deepening our understanding of Martian surface features. …”
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Unseen Attack Detection in Software-Defined Networking Using a BERT-Based Large Language Model by Mohammed N. Swileh, Shengli Zhang

“…Our approach transforms network flow data into a format interpretable by language models, allowing BERT-base-uncased to capture intricate patterns and relationships within network traffic. …”
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