Comparative study on carbon emission spatial network and carbon emission reduction collaboration in urban agglomerations by Yongqiang Dong, Lanjian Liu

“…Mismatches exist between collaboration patterns and emission networks: central cities dominate cooperation, while peripheral cities lack initiative; intensity polarization and provincial-level mini-clubs prevail. …”
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COVID-19 Disruption Strategy for Redesigning Global Supply Chain Network across TPP Countries by Takaki Nagao, Hiromasa Ijuin, Tetsuo Yamada, Keisuke Nagasawa, Lei Zhou

“…This enables us to model and evaluate simultaneous considerations of supplier disruption, customs duty, and TPP in redesigning a global supply chain network. …”
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HFFC: A High-Fan-Out and Flexible-Cluster Optical Network Architecture for Data Centers by Aijun Liu, Zixuan Chen, Yucheng Zhang, Jun Qin

“…The performance of the HFFC architecture is evaluated by simulation using synthetic traffic patterns. …”
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Fractional Transfer Entropy Networks: Short- and Long-Memory Perspectives on Global Stock Market Interactions by Ömer Akgüller, Mehmet Ali Balcı, Larissa Margareta Batrancea, Lucian Gaban

“…These findings demonstrate that FTE uncovers nuanced dynamics overlooked by methods focusing solely on either current events or deep-rooted patterns. Although the method relies on price returns and does not differentiate specific shock types, it offers a versatile tool for investors, policymakers, and researchers to gauge financial stability, evaluate contagion risk, and better understand how ephemeral signals and historical legacies jointly govern global market connectivity.…”
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Multi-Modal Fused-Attention Network for Depression Level Recognition Based on Enhanced Audiovisual Cues by Yihan Zhou, Xiaokang Yu, Zixi Huang, Feierdun Palati, Zeyu Zhao, Zihan He, Yuan Feng, Yuxi Luo

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Optimizing Fractional-Order Convolutional Neural Networks for Groove Classification in Music Using Differential Evolution by Jiangang Chen, Pei Su, Daxin Li, Junbo Han, Gaoquan Zhou, Donghui Tang

“…This study presents a differential evolution (DE)-based optimization approach for fractional-order convolutional neural networks (FOCNNs) aimed at enhancing the accuracy of groove classification in music. …”
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Deep learning based predictive models for real time accident prevention in autonomous vehicle networks by Ahmed Almutairi, Abdullah Faiz Al Asmari, Fayez Alanazi, Tariq Alqubaysi, Ammar Armghan

“…The use of autonomous vehicle (AV) networks is a potentially useful solution since they make it possible to react in real time to probable collisions. …”
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RaNet: a residual attention network for accurate prostate segmentation in T2-weighted MRI by Muhammad Arshad, Chengliang Wang, Muhammad Wajeeh Us Sima, Jamshed Ali Shaikh, Salem Alkhalaf, Fahad Alturise

“…To address these challenges, we propose RaNet (Residual Attention Network), a novel framework based on ResNet50, incorporating three key modules: the DilatedContextNet (DCNet) encoder, the Multi-Scale Attention Fusion (MSAF), and the Feature Fusion Module (FFM). …”
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Grafting enhances drought stress tolerance by regulating the proteome and targeted gene regulatory networks in tomato by Pritam Paramguru Mahapatra, Pritam Paramguru Mahapatra, Dong Won Bae, Michitaka Notaguchi, Sowbiya Muneer

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Securing Industrial IoT Environments: A Fuzzy Graph Attention Network for Robust Intrusion Detection by Safa Ben Atitallah, Maha Driss, Wadii Boulila, Anis Koubaa

“…Conventional machine learning methods and typical Graph Neural Networks (GNNs) often struggle to capture the complexity and uncertainty in IIoT network traffic, which hampers their effectiveness in detecting intrusions. …”
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LMSOE-Net: lightweight multi-scale small object enhancement network for UAV aerial images by Zhixing Ma, Peidong Luo, Xiaole Shen

“…This upgrade strengthens the network’s ability to capture fine details and complex patterns, improving multi-scale feature extraction without a significant increase in parameters. …”
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Computational analysis of Annona muricata phytochemicals for targeted modulation of endocrine networks in polycystic ovary syndrome by Babatunji Emmanuel Oyinloye, Oluwaseun Emmanuel Agboola, Aderonke Moyosola Ayeni, Oluwatoyin Mary Oyinloye, Samuel Sunday Agboola, Olajumoke Tolulope Idowu, Makhosazana Siduduzile Mathenjwa-Goqo, Olutunmise Victoria Owolabi, Bolajoko Idiat Ogunyinka, Foluso Oluwagbemiga Osunsanmi, Basiru Olaitan Ajiboye, Olaposi Idowu Omotuyi

“…Detailed structural mapping of emodin and coclaurin uncovered conserved non-covalent interaction patterns, notably hydrogen bonding networks, facilitating the ligands’ competitive receptivity and deep projection into dysfunctionally upregulated pockets. …”
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A hybrid learning network with progressive resizing and PCA for diagnosis of cervical cancer on WSI slides by Nitin Kumar Chauhan, Krishna Singh, Amit Kumar, Ashutosh Mishra, Sachin Kumar Gupta, Shubham Mahajan, Seifedine Kadry, Jungeun Kim

“…Machine learning (ML) algorithms can discover patterns and anomalies in medical images, whereas deep learning (DL) methods, specifically convolutional neural networks (CNNs), are extremely accurate at identifying malignant lesions. …”
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Dual smart sensor data-based deep learning network for premature infant hypoglycemia detection by Muhammad Shafiq, J. Kavitha, Dhruva R. Rinku, N. K. Senthil Kumar, Kamal Poon, Amar Y. Jaffar, V. Saravanan

“…Based on features, the sorted-out data gets evaluated through a GRU-LSTM (Gated Recurrent Unit - Long Short-Term Memory) network to identify the state of the infant as usual and suggestive of hypoglycemia—blood glucose below 70 mg/dL, pale complexion, profuse perspiration. …”
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Weighted explainable federated learning for privacy-preserving and scalable energy optimization in autonomous vehicular networks by Muhammad Saleem, Ali Arishi, Muhammad Sajid Farooq, M.A. Khan, Khan M. Adnan

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BCTDNet: Building Change-Type Detection Networks with the Segment Anything Model in Remote Sensing Images by Wei Zhang, Jinsong Li, Shuaipeng Wang, Jianhua Wan

“…We first construct a dual-feature interaction encoder that employs SAM to extract image features, which are then refined through trainable multi-scale adapters for learning architectural structures and semantic patterns. Moreover, an interactive attention module bridges SAM with a Convolutional Neural Network, enabling seamless interaction between fine-grained structural information and deep semantic features. …”
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COMPARATIVE ANALYSIS OF TIME SERIES FORECASTING MODELS USING ARIMA AND NEURAL NETWORK AUTOREGRESSION METHODS by Melina Melina, Sukono Sukono, Herlina Napitupulu, Norizan Mohamed, Yulison Herry Chrisnanto, Asep ID Hadiana, Valentina Adimurti Kusumaningtyas, Ulya Nabilla

“…In the NNAR model, the lag values of the time series are used as input variables for the neural network. The dataset used is the closing price of gold with 1449 periods from January 2, 2018, to October 5, 2023. …”
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A Blockchain-Based Federated Forest for SDN-Enabled In-Vehicle Network Intrusion Detection System by Ibrahim Aliyu, Marco Carlo Feliciano, Selinde Van Engelenburg, Dong Ok Kim, Chang Gyoon Lim

“…In-vehicle communication systems are usually managed by controller area networks (CAN). By broadcasting packets to their bus, the CAN facilitates the interaction between Electronic Control Units (ECU) that coordinate, monitor and control internal vehicle components. …”
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Development of an Artificial Neural Network-Based Image Retrieval System for Lung Disease Classification and Identification by Atul Pratap Singh, Ajeet Singh, Amit Kumar, Himanshu Agarwal, Sapna Yadav, Mohit Gupta

“…Leveraging the capabilities of ANNs, specifically convolutional neural networks (CNNs), the system aims to capture intricate patterns and features within images that are often imperceptible to human observers. …”
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Insights into gait performance in Parkinson's disease via latent features of deep graph neural networks by Jiecheng Wu, Jiecheng Wu, Ning Su, Xinjin Li, Xinjin Li, Chao Yao, Jipeng Zhang, Xucheng Zhang, Wei Sun

“…Using ST-GCN, we extracted spatial and temporal patterns from these five states directly from the data, thereby enhancing the accuracy of gait parameter calculation. …”
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