Combining Ecological Momentary Assessment and Social Network Analysis to Study Youth Physical Activity and Environmental Influences: Protocol for a Mixed Methods Feasibility Study by Tyler Prochnow, Genevieve F Dunton, Kayla de la Haye, Keshia M Pollack Porter, Chanam Lee

“…Participants will first complete a baseline survey to report their general social network patterns and environmental perceptions. Then participants will wear an ActiGraph LEAP accelerometer and respond to EMA prompts via smartphone for 7 days. …”
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Traffic flow modelling of vehicles on a six lane freeway: Comparative analysis of improved group method of data handling and artificial neural network model by Isaac Oyeyemi Olayode, Alessandro Severino, Frimpong Justice Alex, Elmira Jamei

“…The primary objective of this study was to evaluate the predictive accuracy and efficacy of both models in replicating complex traffic patterns and to provide insights into their suitability for real-time traffic flow applications. …”
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CoAt-Set: Transformed coordinated attack dataset for collaborative intrusion detection simulationMendeley Data by Aulia Arif Wardana, Grzegorz Kołaczek, Parman Sukarno

“…CoAt-Set is compatible with standard machine learning frameworks, offering researchers and practitioners a comprehensive resource for developing, testing, and evaluating CIDS models. It is suitable for various applications, including collective threat intelligence research, analyzing distributed threat patterns, developing machine learning algorithms for distributed systems, and training simulations designed for heterogeneous network environments.…”
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Chiller power consumption forecasting for commercial building based on hybrid convolution neural networks-long short-term memory model with barnacles mating optimizer by Mohd Herwan Sulaiman, Zuriani Mustaffa

“…Despite advances in deep learning, existing forecasting models often struggle with the complex temporal dependencies and non-linear patterns in chiller operation data. This paper presents an innovative approach using a hybrid Convolutional Neural Network-Long Short-Term Memory (CNN-LSTM) model optimized by the Barnacles Mating Optimizer (BMO). …”
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Evaluating Ionospheric Total Electron Content (TEC) Variations as Precursors to Seismic Activity: Insights from the 2024 Noto Peninsula and Nichinan Earthquakes of Japan by Karan Nayak, Rosendo Romero-Andrade, Gopal Sharma, Charbeth López-Urías, Manuel Edwiges Trejo-Soto, Ana Isela Vidal-Vega

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Hybrid quantum enhanced federated learning for cyber attack detection by G. Subramanian, M. Chinnadurai

“…The novel STAN used in the proposed work captures the spatio-temporal patterns in the network traffic data. The optimization model QIFA utilizes quantum principles to enhance the federated learning procedure. …”
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XAI-Based Photovoltaic Energy Management Framework for Smart Cities by Malini Alagarsamy, Umamaheswari Rajasekaran, Sriram Ganesan, Ramyavarshini Palanivel

“…A recursive forecasting strategy was employed, leveraging Recurrent Neural Networks (RNN) to reduce error accumulation over a 5-year forecast horizon. …”
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Deep learning in time series forecasting with transformer models and RNNs by Rogerio Pereira dos Santos, João P. Matos-Carvalho, Valderi R. Q. Leithardt

“…Given the increasing need for accurate weather forecasts, the use of neural networks, especially transformer and recurrent neural networks (RNNs), has been highlighted for their ability to capture complex patterns in time series. …”
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Evaluation of Fengyun-4B Satellite Temperature Profile Products Using Radiosonde Observations and ERA5 Reanalysis over Eastern Tibetan Plateau by Yuhao Wang, Xiaofei Wu, Haoxin Zhang, Hong-Li Ren, Kaiqing Yang

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Metabolomics and network pharmacology–guided analysis of TNF-α expression by Argemone mexicana (Linn) targeting NF-kB the signalling pathway in cancer cell lines by Sunanda Kulshrestha, Anjana Goel, Subhadip Banerjee, Rohit Sharma, Mohammad Rashid Khan, Kow-Tong Chen, Kow-Tong Chen

“…Network pharmacology analysis used Binding DB, STRING, DAVID, and KEGG for data mining to evaluate predicted compounds using functional annotation analysis. …”
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Study on User Fraud Identification of PV Expansion Based on a Bottom-Up Approach of a DELM Algorithm Improved by SSA for a Power Distribution Network by Wang Jinpeng, Wei Haojie, Dou Shunyao, Jeremy-Gillbanks, Zhao Xin

“…Finally, the proposed approach is validated both in simulation and using measurement data from real networks. The algorithm’s performance in detecting fraudulent behavior in outdated electromagnetic meters is evaluated and verified. …”
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Technology and Application Development of Medical Foundation Model by Xiaohong Chen, Liu Liu, Yige Yuan, Junpu Wang, Dayuan Li, Jianhua Qiu

“…The medical foundation model performs efficient processing and pattern recognition of complex medical data based on a deep neural network architecture, providing a new type of decision support for intelligent medical care. …”
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A Highly Robust Encoder–Decoder Network with Multi-Scale Feature Enhancement and Attention Gate for the Reduction of Mixed Gaussian and Salt-and-Pepper Noise in Digital Images by Milan Tripathi, Waree Kongprawechnon, Toshiaki Kondo

“…HREDN integrates a multi-scale feature enhancement block in the encoder, allowing the network to capture features at various scales and handle complex noise patterns more effectively. …”
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Optimizing load demand forecasting in educational buildings using quantum-inspired particle swarm optimization (QPSO) with recurrent neural networks (RNNs):a seasonal approach by Sunawar Khan, Tehseen Mazhar, Tariq Shahzad, Tariq Ali, Muhammad Ayaz, Yazeed Yasin Ghadi, EL-Hadi M. Aggoune, Habib Hamam

“…Abstract This study uses Quantum Particle Swarm Optimization (QPSO) optimized Recurrent Neural Networks (RNN), standard RNN, and autoregressive integrated moving average (ARIMA) models to anticipate educational building power demand accurately. …”
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K-Means Clustering and Classification of Breast Cancer Images Using Histogram of Oriented Gradients Features and Convolutional Neural Network Models: Diagnostic Image Analysis Stud... by Said Salloum

“…The proposed hybrid method included three stages: (1) unsupervised clustering using K-means to group visually similar features; (2) feature extraction using Histogram of Oriented Gradients (HOG) to capture texture and shape patterns; and (3) classification using a CNN trained on the extracted features. …”
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Efficient scheme for user's trajectory privacy by Feng-hua LI, Cui ZHANG, Ben NIU, Hui LI, Jia-feng HUA, Guo-zhen SHI

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Bidirectional Long Short-Term Memory–Based Detection of Adverse Drug Reaction Posts Using Korean Social Networking Services Data: Deep Learning Approaches by Chung-Chun Lee, Seunghee Lee, Mi-Hwa Song, Jong-Yeup Kim, Suehyun Lee

“… Abstract BackgroundSocial networking services (SNS) closely reflect the lives of individuals in modern society and generate large amounts of data. …”
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AirQuaNet: A Convolutional Neural Network Model With Multi-Scale Feature Learning and Attention Mechanisms for Air Quality-Based Health Impact Prediction by Sreeni Chadalavada, Suleyman Yaman, Abdulkadir Sengur, Ravinesh C. Deo, Abdul Hafeez-Baig, Tracy Kolbe-Alexander, Niranjana Sampathila, U. Rajendra Acharya

“…This work presents Air Quality Network (AirQuaNet), a novel convolutional neural network (CNN) designed to predict air quality levels accurately. …”
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A cosine similarity-based method for improving the accuracy of GIS discharge spectrum recognition by CHEN Xiaoxin, ZHOU Tonghao, LIU Jiangming, DAI Pengfei, LIU Yanqi, LI Wendong, ZHANG Guanjun

“…To enhance the precision and reliability of GIS partial discharge detection by utilizing the phase information in discharge spectra， this paper proposes a neural network-based PD pattern recognition method that incorporates cosine similarity. …”
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Text Select-Backdoor: Selective Backdoor Attack for Text Recognition Systems by Hyun Kwon, Jang-Woon Baek

“…Deep neural networks exhibit excellent image, voice, text, and pattern recognition performance. …”
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