Securing Automotive Networks from DoS and Fuzzy Attacks with Optimized LSTM Models by W. Beniel Dennyson, C. Jothikumar

“…Abstract Intelligently connected automobiles have come a long way thanks to the deep integration of cutting-edge networked gadgets and advancements in automotive technology. …”
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Compact Dual-Band Wearable Antenna for Wireless Body Area Network Applications by Farzad Mohajeri, Maryam Darabi

“…The antenna achieves fractional bandwidths of 4.89% and 69.13% at 2.4 GHz and 5.8 GHz, respectively. The radiation pattern is omnidirectional at both frequency bands, with a maximum gain exceeding 4 dBi. …”
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An adaptive hexagonal deployment model for resilient wireless sensor networks in precision agriculture by Zhang Yinjun

“…Abstract This study presents an innovative hexagonal deployment model designed specifically for wireless sensor networks (WSNs) with a primary application in precision agriculture. …”
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Short Text Classification Based on Enhanced Word Embedding and Hybrid Neural Networks by Cunhe Li, Zian Xie, Haotian Wang

“…To improve the performance of short text classification, this paper proposes a Word2Vec-based enhanced word embedding method and exhibits the design of a dual-channel hybrid neural network architecture to effectively extract semantic features. …”
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GWO-FNN: Fuzzy Neural Network Optimized via Grey Wolf Optimization by Paulo Vitor de Campos Souza, Iman Sayyadzadeh

“…These evaluations demonstrate the model’s strong capability to extract and clearly express intricate patterns within the data. …”
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Epidemic Dynamics and Intervention Measures in Campus Settings Based on Multilayer Temporal Networks by Xianyang Zhang, Ming Tang

“…This study simulates the spread of epidemics on university campuses using a multilayer temporal network model combined with the SEIR (Susceptible–Exposed–Infectious–Recovered) transmission model. …”
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A novel twin time series network for building energy consumption predicting. by Zhixin Sun, Han Cui, Xiangxiang Mei, Hailei Yuan

“…To overcome these issues, the study proposes Twin Time-Series Networks (T2SNET), which incorporates a time-embedding layer and a Temporal Convolutional Network (TCN) to extract patterns from Complete Ensemble Empirical Mode Decomposition with Adaptive Noise (CEEMDAN), along with an adaptive fusion gate to combine energy consumption and meteorological data. …”
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Spatial attention-guided pre-trained networks for accurate identification of crop diseases by Satrughan Kumar, S. S. Aravinth, Sreedhar Kollem, Munish Kumar, Quadri Noorulhasan Naveed, Azath Mubarakali, Abhishek Bhattacherjee, Addisu Frinjo Emma

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Assessment and Variation of Water Quality in Urban Distribution Networks: From Reservoir to Faucet by Eunhye Jeong, Kyung-Yup Hwang, Sumin Lee, Kwangjun Jung, Hyunjun Kim

“…This study focuses on evaluating the spatiotemporal variations in water quality across a potable water distribution network in D City, South Korea, spanning from a reservoir to a large consumer’s tap. …”
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Neural network-based symmetric encryption algorithm with encrypted traffic protocol identification by Jiakai Hao, Ming Jin, Yuting Li, Yuxin Yang

“…In this study, we first introduce a plaintext guessing model (SCGM model) based on symmetric encryption algorithms, leveraging the strengths of convolutional neural networks to evaluate the plaintext guessing capabilities of four symmetric encryption algorithms. …”
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A hybrid ensemble framework with particle swarm optimization for network anomaly detection by Narinder Verma, Neerendra Kumar, Gourav Kumar, Kuljeet Singh

“…Abstract The increasing complexity of cyber threats necessitates the development of a robust and adaptive Intrusion Detection System (IDS) capable of safeguarding network infrastructures. Traditional IDS approaches often struggle to detect sophisticated attacks due to their reliance on predefined patterns. …”
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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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Optimizing Personalized and Context-Aware Recommendations in Pervasive Computing Environments by A. C. Kaladevi, V. Vinoth Kumar, T. R. Mahesh, Suresh Guluwadi

“…Additionally, metrics, such as precision, recall, and F1-score, are used to evaluate the effectiveness of the hybrid approach in capturing latent factors and patterns. …”
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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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Analysis and Quantification of Demand Flexibility for Resilient Distribution Networks: A Systematic Review by Mohamed Massaoudi, Katherine R. Davis, Khandaker Akramul Haque

“…Modern power systems face increasing operational challenges due to the integration of renewable energy sources (RESs) and evolving demand patterns. Demand flexibility (DF) has emerged as a transformative solution by dynamically adjusting electricity consumption to align with grid conditions. …”
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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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Bayesian network modeling of flood cascade and climate risks in the Pearl River Delta by Wen Zhang, Jianglong Cui, Weike Yao, Mariavittoria Guida, Frederick Kwame Yeboah, Xuanru Zhou, Yafei Li, Lixiao Zhang, Gengyuan Liu

“…To evaluate future flood hazards, downscaled climate projections from global climate models and a stochastic weather generator were employed to simulate extreme precipitation patterns. …”
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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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Wind Speed Forecasting in the Greek Seas Using Hybrid Artificial Neural Networks by Lateef Adesola Afolabi, Takvor Soukissian, Diego Vicinanza, Pasquale Contestabile

“…In this work, various artificial neural networks (ANNs) were developed and evaluated for their wind speed prediction ability using the ERA5 historical reanalysis data for four potential Offshore Wind Farm Organized Development Areas in Greece, selected as suitable for floating wind installations. …”
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