Security vulnerabilities in telecommunications networks have become an important issue due to the significant growth of gadgets for smart homes. and its connectivity via the Internet of Things (IoT) This research supp...
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Multi-domain engineering modeling and simulation is becoming more relevant and needed to undergraduate engineering education. The sole idea of synergistically teaching/learning multiple engineering domains-using energ...
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People with disabilities includes deaf and hard of hearing cannot avail the benefits of education, proper health and find difficulty to communicate with others. They need sign language interpreter to communicate. Sign...
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This article reports the findings of a comprehensive investigation that found blockchain technology developed for machine learning can improve clinical trial data security. This research was first submitted to Transac...
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With the increasing demand for edge computing in cyber-physical system (CPS) applications, ensuring the safety and reliability of machine learning models running on edge devices during online model training and infere...
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Distributed machine learning (DML) may train on large datasets even if nodes cannot give accurate results quickly. This exposes more attacker targets than non-distributed. Semi and Basic comprise DML. Central cyberspa...
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The agricultural industry is undergoing significant advancements, yet traditional methods for classifying vegetables by attributes such as size, color, texture, and freshness remain a challenge for farmers and vendors...
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作者：
Heo, JaeChang, SoowonPurdue Univ
Sch Construct Management Technol Smart & Sustainable Human Urban Bldg Interact Lab W Lafayette IN 47907 USA
Electric vehicles (EVs) have been widely adopted with the expectation of reducing CO2 emissions. However, the lack of public fast charging stations has hindered the growth of EVs. Despite extensive research on optimal...
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ISBN:
(数字)9780784485248
ISBN:
(纸本)9780784485248
Electric vehicles (EVs) have been widely adopted with the expectation of reducing CO2 emissions. However, the lack of public fast charging stations has hindered the growth of EVs. Despite extensive research on optimal installation of EV charging stations (EVCS), a decision model for a large scale and diverse spatial conditions has been still lacking. This research intends to explore a deep reinforcement learning model using deep Q-network (DQN) algorithms and test the model for optimal planning of fast EVCS at a large scale. The DQN model considers geographic (e.g., building footprints, street network), economic (e.g., capacity of charging station), and environmental (e.g., solar energy) perspectives. The learning model identifies the energy balance between electricity generation and consumption and investigates spatial patterns nearby potential charging stations. This study can aid in decision-making for suitable EVCS sites with advancing the microgrid approach-based infrastructure systems, ultimately enhancing urban sustainability considering vehicle-to-building integration.
In this research, we present a new adaptive MP3 steganography technique that utilizes adversarial gradients. With the development of deep learning technology and the improvement of GPU computing performance, MP3 stega...
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With the rapid growth of economic and social fields from digitalization to intelligence, the traditional risk management system is not suitable for the new model of financial innovation and development. Based on the a...
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