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Robust text-dependent speaker verification system using gender aware Siamese-Triplet Deep Neural Network.
Network
December 2024
Department of Electronics and Communication Engineering, Dronacharya Group of Institutions, Greater Noida, UP, India.
Speaker verification in text-dependent scenarios is critical for high-security applications but faces challenges such as voice quality variations, linguistic diversity, and gender-related pitch differences, which affect authentication accuracy. This paper introduces a Gender-Aware Siamese-Triplet Network-Deep Neural Network (ST-DNN) architecture to address these challenges. The Gender-Aware Network utilizes Convolutional 2D layers with ReLU activation for initial feature extraction, followed by multi-fusion dense skip connections and batch normalization to integrate features across different depths, enhancing discrimination between male and female speakers.
View Article and Find Full Text PDFSustainable rural development: differentiated paths to achieve rural revitalization with case of Western China.
Sci Rep
December 2024
School of Business, Shanghai Dianji University, Shanghai, China.
Rural Revitalization (RR) is a key national strategy in China aimed at sustainable rural development and has gained significant attention. Given the unique characteristics of different villages, understanding differentiated paths to achieve RR is essential. This study introduces a new "5I Framework" (INDUS-INHAB-INDOC-INFRA-INCOM) to assess RR's overall development status (ODS) and differentiated paths.
View Article and Find Full Text PDFA dual-adaptive stochastic reinforcement chimp optimization algorithm for fire detection and multidimensional problem solving.
Sci Rep
December 2024
Department of Biosciences, Saveetha School of Engineering, Saveetha Institute of Medical and Technical Sciences, Chennai, 602 105, India.
Chimp optimization algorithm (CHOA) is a recently developed nature-inspired technique that mimics the swarm intelligence of chimpanzee colonies. However, the original CHOA suffers from slow convergence and a tendency to reach local optima when dealing with multidimensional problems. To address these limitations, we propose TASR-CHOA, a twofold adaptive stochastic reinforced variant.
View Article and Find Full Text PDFApplication of artificial intelligence based on state grid ESG platform in clean energy scheduling optimization.
Sci Rep
December 2024
School of Public Administration, Guangzhou University, Guangzhou, 510006, China.
The randomness and volatility of existing clean energy sources have increased the complexity of grid scheduling. To address this issue, this work proposes an artificial intelligence (AI) empowered method based on the Environmental, Social, and Governance (ESG) big data platform, focusing on multi-objective scheduling optimization for clean energy. This work employs a combination of Particle Swarm Optimization (PSO) and Deep Q-Network (DQN) to enhance grid scheduling efficiency and clean energy utilization.
View Article and Find Full Text PDFTo achieve carbon neutrality, solar photovoltaic (PV) in China has undergone enormous development over the past few years. PV datasets with high accuracy and fine temporal span are crucial to assess the corresponding carbon reductions. In this study, we employed the random forest classifier to extract PV installations throughout China in 2015 and 2020 using Landsat-8 imagery in Google Earth Engine.
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