Music audio emotion regression using the fusion of convolutional neural networks and bidirectional long short-term memory models by Yi Qiu, Yu Lin, Yun Lin

“…This research presents an innovative model that combines convolutional neural networks (CNNs) with bidirectional long short-term memory (BiLSTM) networks to analyze and predict the emotional impact of musical audio. …”
Get full text

Quantifying Three-Dimensional Street Network Orientation Entropy in Chongqing, China: Implications for Urban Spatial Order and Environmental Perception by Hao Rao, Leyao Chen, Cui Liu

“…Although no statistically significant correlation was observed, the findings suggest emerging patterns and underscore the necessity of multidimensional frameworks in evaluating urban spatial experience. …”
Get full text

Multi-Scale Network Analysis of Community-Based Senior Centers: Exploring the Intersection of Spatial Embeddedness and Accessibility in Nanjing, China by Zhixin Xu, Xiaoming Li

“…This study aims to address the research gap by investigating the spatial embeddedness of senior centers using Space Syntax methods and examining its influence on older people’s access patterns. Using a geo-behavioral dataset collected in Nanjing, China, we find that about 70% of the senior centers in the research area are embedded in highly localized settings with limited connections to global street networks, which significantly restricts the access of older people from wider spatial contexts. …”
Get full text

Aggregated approach for interstitial lung diseases classification using attention based CNN and radial basis function neural network by S. Kumarganesh, K.V.M. Shree, P. Rishabavarthani, C. Ganesh, S. Anthoniraj, B. Thiyaneswaran, Lam Dang, K. Martin Sagayam, Linh Dinh, Hien Dang

“…The reduced features were then trained and tested using a radial basis function neural network (RBFNN). In parallel, an attention-based convolutional neural network was used to perform deep learning-based ILD classification using gray and local pattern images. …”
Get full text

Characterizing the Flow and Interaction of Microbubbles in a 2D Capillary Network for Targeted Drug Delivery: A Simulation Study by Sadegh Shurche, Akram Shahidani, Roghaye Bodaghi Hossein Abadi

“…Materials and Methods: We designed the capillary network based on the tree pattern employed in quantitative studies per Murray’s minimum work rule and the cardiovascular network to simulate the hemodynamics of the vessels. …”
Get full text

Papayafreshnet: a hybrid deep learning framework for non-destructive freshness classification of papayas using convolutional and transformer networks by Ayan Sar, Tanupriya Choudhury, Tanmay Sarkar, Ketan Kotecha

“…This article introduces PapayaFreshNet, an innovative deep learning network designed for the automatic categorization of papaya freshness through picture analysis. …”
Get full text

Adoption deep learning approach using realistic synthetic data for enhancing network intrusion detection in intelligent vehicle systems by Said A. Salloum, Tarek Gaber, Mohammed Amin Almaiah, Rami Shehab, Romel Al-Ali, Theyazan H.H Aldahyani

“…We created a diverse dataset involving 100,000 network flows, covering a wide array of benign, malicious, and anomalous traffic patterns, to thoroughly evaluate the detection capabilities of our proposed system. …”
Get full text

Cyber intrusion detection using ensemble of deep learning with prediction scoring based optimized feature sets for IOT networks by Deepesh M. Dhanvijay, Mrinai M. Dhanvijay, Vaishali H. Kamble

“…To capture temporal patterns effectively, our ensemble integrates Global Attention Long Short-Term Memory networks (GA-LSTMs), utilizing layered structures, residual connections, and attention mechanisms. …”
Get full text

Advanced music classification using a combination of capsule neural network by upgraded ideal gas molecular movement algorithm by Peiyan Chen, Jichi Zhang, Arsam Mashhadi

“…Traditional methods have struggled to accurately capture the complex patterns that differentiate one genre from another. …”
Get full text

Hayai-Annotation: A functional gene prediction tool that integrates orthologs and gene ontology for network analysis in plant species by Andrea Ghelfi, Sachiko Isobe

“…This approach aims to improve the visualization of conserved biological processes and functions, highlight species-specific adaptations, and enhance the ability to infer the functions of uncharacterized genes by comparing edge patterns across species. To our knowledge, this is the first attempt to build a network using annotated OrthoDB orthologs and Gene Ontology terms (Molecular Function and Biological Process) as nodes, providing a comprehensive view of gene distribution and function in plant species. …”
Get full text

DAC-GCN: A Dual Actor-Critic Graph Convolutional Network with Multi-Hop Aggregation for Enhanced Recommender Systems by Gholamreza Zare, Nima Jafari, Mehdi Hosseinzadeh, Amir Sahafi

Get full text

Design of drain tube with cone to prevent frost accumulation of drainage hole in household refrigerators using artificial neural network by Suhwan Lee, Dongkuk Kang, Jinxing Fan, Sunghee Kang, Dong Kim, Eunseop Yeom

“…Experiments and computational fluid dynamics (CFD) simulations were conducted to investigate frost formation patterns and the effects of absolute humidity. To reduce the cost of evaluating design variations, an artificial neural network (ANN) was developed as a surrogate model trained on CFD data. …”
Get full text

Conv1D-GRU-Self Attention: An Efficient Deep Learning Framework for Detecting Intrusions in Wireless Sensor Networks by Kenan Honore Robacky Mbongo, Kanwal Ahmed, Orken Mamyrbayev, Guanghui Wang, Fang Zuo, Ainur Akhmediyarova, Nurzhan Mukazhanov, Assem Ayapbergenova

“…A Conv1D extracts spatial features from network traffic, GRU captures temporal dependencies, and Self-Attention emphasizes critical sequence components, collectively enhancing detection of subtle and complex intrusion patterns. …”
Get full text

Comparative analysis of deep neural network architectures for renewable energy forecasting: enhancing accuracy with meteorological and time-based features by Sunawar Khan, Tehseen Mazhar, Muhammad Amir Khan, Tariq Shahzad, Wasim Ahmad, Afsha Bibi, Mamoon M. Saeed, Habib Hamam

Get full text

An electrical load forecasting model based on a novel closed loop neural networks and interaction gain feature selection by Gholamreza Memarzadeh, Faezeh Amirteimoury, Hossein Noori, Farshid Keynia

“…A cascade ensemble approach is proposed, combining wavelet transform (WT), mutual information-interaction gain (MI-IG), and neural networks. This multi-step process begins with the wavelet transform, which decomposes the load data into distinct frequency components, allowing for a detailed analysis of underlying patterns. …”
Get full text

IoT-Driven Intelligent Energy Management: Leveraging Smart Monitoring Applications and Artificial Neural Networks (ANN) for Sustainable Practices by Azza Mohamed, Ibrahim Ismail, Mohammed AlDaraawi

“…The application allows for continuous energy monitoring via modern IoT devices and wireless sensor networks, while ANN-based prediction models evaluate consumption data to dynamically optimize energy use and reduce environmental effect. …”
Get full text

Taking a look at your speech: identifying diagnostic status and negative symptoms of psychosis using convolutional neural networks by Gleb Melshin, Anthony DiMaggio, Nadia Zeramdini, Michael MacKinley, Lena Palaniyappan, Alban Voppel

“…Static acoustic features show potential but often overlook time-varying acoustic cues that clinicians naturally evaluate—such as negative symptoms—during clinical interviews. …”
Get full text

Efficacy and safety of PCSK-9 inhibitors in patients with acute coronary syndrome: a systematic review and network meta-analysis by Guoying Kao, Chuan Chen, Ying Zhang, Yi Xu, Gang Xu

“…In subgroup analysis, Evolocumab produced greater LDL-C reductions, while Alirocumab showed a stronger trend toward MACE reduction, though not statistically significant (OR: 0.84; 95% CI: 0.68–1.03). Network meta-analysis confirmed these patterns but revealed no statistically significant differences between the two agents. …”
Get full text

Effect of different types of exercise on bone mineral density in postmenopausal women: a systematic review and network meta-analysis by Li Xiaoya, Zhu Junpeng, Xu Li, Zhang Haoyang, Fu Xueying, Wang Yu

“…This network meta-analysis aimed to evaluate and compare various exercise types with bone mineral density in PMW to identify the most effective types. …”
Get full text

Computer-aided diagnosis of Haematologic disorders detection based on spatial feature learning networks using blood cell images by Jamal Alsamri, Hamed Alqahtani, Ali M. Al-Sharafi, Abdulbasit A. Darem, Khalid Nazim, Abdul Sattar, Menwa Alshammeri, Ahmad A. Alzahrani, Marwa Obayya

“…Machine learning (ML) and deep learning (DL) have aided the classification and collection of patterns in data, foremost in the growth of AI methods employed in numerous haematology fields. …”
Get full text