Optimized deep neural network architectures for energy consumption and PV production forecasting by Eghbal Hosseini, Barzan Saeedpour, Mohsen Banaei, Razgar Ebrahimy

“…Accurate time-series forecasting of energy consumption and photovoltaic (PV) production is essential for effective energy management and sustainability. Deep Neural Networks (DNNs) are effective tools for learning complex patterns in such data; however, optimizing their architecture remains a significant challenge. …”
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Dynamic graph convolutional networks with Temporal representation learning for traffic flow prediction by Aihua Zhang

“…Abstract In the realm of traffic prediction, emerging are methodologies founded on graph convolutional networks. Nonetheless, existing approaches grapple with issues encompassing insufficient sharing patterns, dependence on static relationship presumptions, and an inability to effectively grasp the intricate trends and cyclic attributes of traffic flow. …”
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Mobile Secured IoT Sensors-Driven Network Using Efficient QoS Management by Mohammad Siraj, Majid Altamimi, Zeeshan Ahmad Abbasi

“…With the use of mobile agents, this research offers quality-aware services and a cooperative protocol for unbalanced IoT networks. Examining the mobility patterns of devices, it effectively achieves massive amounts of data across established connections and lowers communication faults for diverse services. …”
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Analysis and Quantification of Demand Flexibility for Resilient Distribution Networks: A Systematic Review by Mohamed Massaoudi, Katherine R. Davis, Khandaker Akramul Haque

“…This review systematically investigates DF in distribution networks through three critical dimensions: quantification methodologies, regulatory frameworks, and techno-economic impacts. …”
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A Lightweight Tri-Stream Feature Fusion Network for Speech Emotion Recognition by Ronghe Cao, Yunxing Wang, Xiaolong Wu, Shuang Jin, Huiling Niu

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DeepQSP: Identification of Quorum Sensing Peptides Through Neural Network Model by Md. Ashikur Rahman, Md. Mamun Ali, Kawsar Ahmed, Imran Mahmud, Francis M. Bui, Li Chen, Santosh Kumar, Mohammad Ali Moni

“…This study introduces DeepQSP, a novel technique for QSP identification, which combines Latent Semantic Analysis (LSA), a word embedding feature extraction method, with classical amino acid-based extraction Pseudo Amino Acid Composition (PAAC), and a convolutional neural network (CNN) classifier. The DeepQSP model was evaluated using a dataset of 440 peptide sequences, achieving impressive performance metrics: 0.9697 accuracy, 0.9655 sensitivity, 0.9730 specificity, and a Matthews correlation coefficient (MCC) of 0.9385. …”
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Rumor detection using dual embeddings and text-based graph convolutional network by Barsha Pattanaik, Sourav Mandal, Rudra M. Tripathy, Arif Ahmed Sekh

“…Their success is due to their ability to identify structural patterns in rumors and effectively use neighborhood information. …”
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Soil Fungal Diversity, Community Structure, and Network Stability in the Southwestern Tibetan Plateau by Shiqi Zhang, Zhenjiao Cao, Siyi Liu, Zhipeng Hao, Xin Zhang, Guoxin Sun, Yuan Ge, Limei Zhang, Baodong Chen

“…Despite substantial research on how environmental factors affect fungal diversity, the mechanisms shaping regional-scale diversity patterns remain poorly understood. This study employed ITS high-throughput sequencing to evaluate soil fungal diversity, community composition, and co-occurrence networks across alpine meadows, desert steppes, and alpine shrublands in the southwestern Tibetan Plateau. …”
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A coupled model of zebra mussels and chlorine in collective pressurized irrigation networks by J. Burguete, B. Latorre, P. Paniagua, E.T. Medina, J. Fernández-Pato, E. Playán, N. Zapata

“…Simulations predicted similar mussel settlement patterns across all scenarios, suggesting that network morphology and total larval abundance primarily influence settlement distribution. …”
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Enhancing Network Security: A Study on Classification Models for Intrusion Detection Systems by Abeer Abd Alhameed Mahmood, Azhar A. Hadi, Wasan Hashim Al-Masoody

“…The authors utilize three datasets (Knowledge Discovery in Databases 1999 dataset, used for network intrusion detection research), UNSW-NB15 (a dataset capturing contemporary network attack patterns generated at the University of New South Wales), and CICIDS2017 (Canadian Institute for Cybersecurity Intrusion Detection System dataset, containing modern attack scenarios)(KDD99, UNSW NB15, and CICIDS2017) with varying train-test ratios to train the classifiers. …”
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Air Pollution Forecasting Using Artificial and Wavelet Neural Networks with Meteorological Conditions by Qingchun Guo, Zhenfang He, Shanshan Li, Xinzhou Li, Jingjing Meng, Zhanfang Hou, Jiazhen Liu, Yongjin Chen

“…Evaluating twelve algorithms and nineteen network topologies for the ANN and WANN models, we discovered that the optimal input variables for an API forecasting model were the APIs from the 3 preceding days and sixteen selected meteorological factors. …”
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An ingredient co-occurrence network gives insight into e-liquid flavor complexity by Jeroen L. A. Pennings, Ina M. Hellmich, Sanne Boesveldt, Reinskje Talhout

“…We identified two densely connected regions (clusters) in the network. One consisted of six ingredients with sweet-vanilla-creamy flavors. …”
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Adaptive multi-scale phase-aware fusion network for EEG seizure recognition by Yanting Liang, Jingyuan Liu, Xinzhou Zhang

“…However, traditional methods rely heavily on manual feature extraction, and current deep learning-based approaches still face challenges in frequency adaptability, multi-scale feature integration, and phase alignment.MethodsTo address these limitations, we propose an Adaptive Multi-Scale Phase-Aware Fusion Network (AMS-PAFN). The framework integrates three novel components: (1) a Dynamic Frequency Selection (DFS) module employing Gumbel-SoftMax for adaptive spectral filtering to enhance seizure-related frequency bands; (2) a Multi-Scale Feature Extraction (MCFE) module using hierarchical downsampling and temperature-controlled multi-head attention to capture both macro-rhythmic and micro-transient EEG patterns; and (3) a Multi-Scale Phase-Aware Fusion (MCPA) module that aligns temporal features across scales through phase-sensitive weighting.ResultsThe AMS-PAFN was evaluated on the CHB-MIT dataset and achieved state-of-the-art performance, with 98.97% accuracy, 99.53% sensitivity, and 95.21% specificity (Subset 1). …”
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Revealing heterogeneity in mild cognitive impairment based on individualized structural covariance network by Xiaotong Wei, Ronglong Xiong, Ping Xu, Tingting Zhang, Junjun Zhang, Zhenlan Jin, Ling Li

“…Abnormal inter-regional structural covariance suggests disruption of the brain structural network in MCI. Most studies have examined group-level structural covariance alterations while ignoring individual-level differences. …”
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Neural Networks vs. Regression: A Comparative Analysis in Medical Data Processing by Minodora ANDOR, Gheorghe Ioan MIHALAŞ

“… Background and Aim: The increasing adoption of artificial intelligence (AI) in medical research offered alternative methods for medical data processing. This study evaluated comparatively the predictive performance of feedforward neural networks (FFNN) regression versus classical statistical regression analysis in estimating the risk of post-COVID-19 type 2 diabetes based on metabolic factors. …”
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Exploring the interaction effects of subclinical hypothyroidism and major depressive disorder on brain networks by Shuai Zhao, Jindan Wu, Xiaomei Liu, Yishan Du, Xiaoqin Wang, Yi Xia, Hao Sun, Haowen Zou, Xumiao Wang, Zhilu Chen, Rui Yan, Hao Tang, Qing Lu, Zhijian Yao

“…Each participant received resting-state functional magnetic resonance imaging scans and underwent neuropsychological evaluations. Results We found significantly altered functional connectivity (FC) within the resting-state networks (RSNs) of the ventral and dorsal sensorimotor network (VSMN and DSMN) and occipital pole visual network (PVN) (p < 0.05, FDR corrected). …”
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Construction and Overall Protection of Ecological and Marine Cultural Composite Landscape Network in Quanzhou, Fujian by Dongfang LU, Yaru ZHENG, Tianteng HAN, Shunhe CHEN

“…Based on the evaluation results of the gravity model, these corridors are classified into first-class, second class, and third-class corridors, forming the spatial pattern of the Quanzhou ecological network. …”
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Genome-Wide Identification of HSP70 Gene Family and Their Roles in the Hybrid Tea Rose Heat Stress Response by Xinyu Yan, Yaoyao Huang, Minghua Deng, Jinfen Wen

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RNA sequencing reveals dynamic expression of genes related to innate immune responses in canine small intestinal epithelial cells induced by Echinococcus granulosus protoscoleces by Zhengrong Wang, Zhengrong Wang, Na Pu, Na Pu, Na Pu, Wenqing Zhao, Wenqing Zhao, Wenqing Zhao, Xuke Chen, Xuke Chen, Xuke Chen, Yanyan Zhang, Yanyan Zhang, Yan Sun, Yan Sun, Xinwen Bo, Xinwen Bo, Xinwen Bo

“…Therefore, this study aimed to evaluate gene transcription patterns in canine small intestinal epithelial cells (CIECs) following stimulation by E. granulosus protoscoleces (PSCs). …”
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Patterns of opioid use (codeine, morphine or meperidine) in the Canadian population over time: analysis of the Longitudinal National Population Health Survey 1994–2011 by Elizabeth M Badley, Y Raja Rampersaud, Mayilee Canizares, J Denise Power

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