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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Visual impairment is characterized by the loss of vision, encompassing both complete blindness and partial vision loss. Studies reveal a notable prevalence of visual impairment among school-aged children. The signific...
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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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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 rise of the internet and online shopping, the use of credit cards for online purchases skyrocketed and so did the incidents of online financial frauds. In the year 2018 alone, 24.26 Billion USD was lost world...
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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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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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Traditional supervised learning has achieved high accuracy in crack detection tasks. However, due to the complex pavement situation, it often requires millions of data to train model in industry. It is difficult to pr...
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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.
Electric bicycles (e-bikes) have gained considerable popularity due to their environmentally friendly nature and suitability as a mode of transportation. However, they face challenges related to manual switches for po...
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