Providing a model of purchase intention and customer experience on customer behavior in virtual networks by Kazem Tolooee, Hossein budaghi Khajeh Noubar, Hossein Gharehbiglo, Mojtaba Ramazani

“…The collection tool in this research includes a questionnaire of purchase intention pattern based on customers' experience in designed virtual networks. …”
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Synergized security framework: revolutionizing wireless sensor networks through comparative methodological analysis by Guodong Su, Boliang Zhang

“…Finally, comprehensive evaluations using OMNeT++ with networks of 1–500 nodes demonstrate that our framework outperforms existing protocols (LEAP, SPINS, ESK) by 17–32% in network throughput and 12–26% in node connectivity, while maintaining comparable latency to quantum-based methods (QKD, BB84). …”
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Enhancing agricultural sustainability with water and crop management strategies in modern irrigation and drainage networks by Seyedeh-Zohreh Hashemi, Abdullah Darzi-Naftchali, Fatemeh Karandish, Henk Ritzema, Karim Solaimani

“…This study investigated the potential for enhancing the sustainability of agricultural production in a modern irrigation and drainage network (TIDN) area and evaluated the network's performance under various strategies. …”
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An efficient emerging network and secured hopping scheme employed over the unsecured public channels by Aamir Shahzad, Kaiwen Zhang, René Landry, Neal Xiong, Young-Gab Kim

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Wordline Input Bias Scheme for Neural Network Implementation in 3D-NAND Flash by Hwiho Hwang, Gyeonghae Kim, Dayeon Yu, Hyungjin Kim

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Synergistic Enhancement of Carbon Sinks and Connectivity: Restoration and Renewal of Ecological Networks in Nanjing, China by Renfei Zhang, Hongye Li, Zhicheng Liu

“…This study used Nanjing, China, as a case to construct an ecological network by applying Morphological Spatial Pattern Analysis (MSPA) and the Linkage Mapper (LM) tool based on circuit theory. …”
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A Multifrequency Brain Network-Based Deep Learning Framework for Motor Imagery Decoding by Juntao Xue, Feiyue Ren, Xinlin Sun, Miaomiao Yin, Jialing Wu, Chao Ma, Zhongke Gao

“…We propose a novel multifrequency brain network-based deep learning framework for motor imagery decoding. …”
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Dual orexin receptor antagonists for the treatment of insomnia: systematic review and network meta-analysis by Rebeka Bustamante Rocha, Fernanda Ferreira Bomtempo, Gabriela Borges Nager, Giulia Isadora Cenci, João Paulo Mota Telles

“…Objective To perform a network meta-analysis to evaluate the efficacy of different DORAs in patients with chronic insomnia. …”
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The outcome prediction method of football matches by the quantum neural network based on deep learning by Yang Sun, Hongyang Chu

“…During the model training phase, gradient descent is used to optimize weight parameters, and quantum algorithms are integrated to continuously adjust network weights to minimize prediction errors. The model is trained, parameter tuning is completed, and performance is evaluated using the training, validation, and independent test sets. …”
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Evaluation of machine learning and deep learning algorithms for fire prediction in Southeast Asia by Aditya Eaturu, Krishna Prasad Vadrevu

“…Furthermore, simpler models, such as Simple Persistence and MLP, showed limitations in capturing dynamic patterns and temporal dependencies. Our findings highlight the importance of evaluating various ML and DL models before integrating them into any decision support systems (DSS) for fire management studies. …”
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Deep Learning Algorithm for Optimized Sensor Data Fusion in Fault Diagnosis and Tolerance by M. Elhoseny, Deepak Dasaratha Rao, Bala Dhandayuthapani Veerasamy, Noha Alduaiji, J. Shreyas, Piyush Kumar Shukla

“…Here, the major objective is to locate problems in detection by analysing previous data or sequential patterns of data that cause failure. This study evaluates the use of deep learning for improved sensor data fusion in fault identification and tolerance using the KITTI dataset. …”
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Real‐time object detection for unmanned vehicles in Bangladesh: Dataset, implementation and evaluation by Muhammad Liakat Ali, Topu Biswas, Shahin Akter, Mohammed Farhan Jawad, Hadaate Ullah

“…The MS COCO (Microsoft Common Objects in Context) dataset weights are included in the YOLOv5 deep learning network for transfer learning. Finally, Python TensorBoard was used to evaluate and visualize the model's performance. …”
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Use of Socio-economic, Climatic, and Land use Land Cover Patterns in Solid Waste Forecasting with Integrated Gradient LSTNet Based Model in Lomé, Togo by Kanlanféi Sambiani, Yendoubé Lare, Adamou Zanguina, Satyanarayana Narra

“…This study aimed to develop a new approach of Integrated Gradient Long- and Short-term Time series Network (LSTNet+IG)-based models, assess the baseline neural network models, and provide features influences explanation on MSW generation by using socio-economic, climatic, and Land Use Land Cover (LULC) patterns. …”
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An Emerging Trend of At-Home Uroflowmetry—Designing a New Vibration-Based Uroflowmeter with Artificial Intelligence Pattern Recognition of Uroflow Curves and Comparing with Other T... by Vincent F. S. Tsai, Yao-Chou Tsai, Stephen S. D. Yang, Ming-Wei Li, Yuan-Hung Pong, Yu-Ting Tsai

“…These vibration signals were then analyzed using a convolutional neural network (CNN) to classify six distinct uroflow curve patterns, aiding in diagnostic evaluation. …”
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A Comprehensive Evaluation of Machine Learning and Deep Learning Models for Churn Prediction by Nabil M. AbdelAziz, Mostafa Bekheet, Ahmad Salah, Nissreen El-Saber, Wafaa T. AbdelMoneim

“…The implementation and comparison conducted in this study of models include XGBoost, Convolutional Neural Networks (CNNs), and Ensemble Deep Learning with the pre-trained hybrid approach. …”
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Cost-effectiveness analysis of a multiple health behaviour change intervention in people aged between 45 and 75 years: a cluster randomized controlled trial in primary care (EIRA s... by Ignacio Aznar-Lou, Edurne Zabaleta-Del-Olmo, Marc Casajuana-Closas, Alba Sánchez-Viñas, Elizabeth Parody-Rúa, Bonaventura Bolíbar, Montserrat Iracheta-Todó, Oana Bulilete, Tomàs López-Jiménez, Haizea Pombo-Ramos, María Victoria Martín Miguel, Rosa Magallón-Botaya, Jose Ángel Maderuelo-Fernández, Emma Motrico, Juan Bellón, Ruth Martí-Lluch, Maria Rubio-Valera, Antoni Serrano-Blanco

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From communication to action: using ordered network analysis to model team performance in clinical simulation by Vitaliy Popov, Lauryn R. Rochlen

“…Teams were classified as high- or low-performing based on timely dantrolene administration and appropriate MH treatment actions. Network visualizations and statistical tests compared communication patterns between groups. …”
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A Comparative Evaluation of Transformers and Deep Learning Models for Arabic Meter Classification by A. M. Mutawa, Sai Sruthi

“…While earlier studies primarily relied on conventional machine learning and recurrent neural networks, this work evaluates the effectiveness of transformer-based models—an area not extensively explored for this task. …”
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AI-driven EEG neuroscientific analysis for evaluating the influence of emotions on false memory by V. Mahalakshmi

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Recognition and Evaluation of Architectural Heritage Value in Fujian Overseas Chinese New Villages by Jing Hu, Hanyi Wu, Fan Huo, Zhihong Chen

“…Three primary findings emerged: (1) Spatial distribution patterns revealed core-periphery clustering characteristics, with Xiamen and Zhangzhou forming high-density cores (23.5% concentration ratio) showing KDE values of 4.138–4.976, reflecting historical migration networks and policy-driven site selection logic. (2) Heritage values were categorized into seven dimensions, with historical significance (0.2904), artistic merit (0.1602), and functional utility (0.1638) identified as primary value drivers. (3) A four-tier evaluation system quantified heritage significance through weighted indices, demonstrating 53.89% dominance of intrinsic value components, with historical and cultural factors contributing 29.04% and 18.52% respectively. …”
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