In this paper, we propose a Secure Energy Management System (SEMS) with anomaly detection and Q-Learning decision modules for Automated Guided Vehicles (AGV). The anomaly detection module is a multi-task learning netw...
详细信息
The integration of brain-machine interface and exoskeleton robot has been widespread application in gait correction, walking assistance, and numerous other scenarios. To effectively extract the electroencephalogram (E...
详细信息
The synthesis of renewable chemical fuels from CO_(2) and H_(2)O via photoelectrochemical(PEC)route reprensents a promising room-temperature approach for transforming greenhouse gas into value-added chemicals(e.g.,syn...
详细信息
The synthesis of renewable chemical fuels from CO_(2) and H_(2)O via photoelectrochemical(PEC)route reprensents a promising room-temperature approach for transforming greenhouse gas into value-added chemicals(e.g.,syngas),but to date it has been hampered by the lack of efficient photocathode for CO_(2) ***,we report efficient PEC CO_(2) reduction into syngas by photocathode *** photocathode is consisting of a planar p-n Si junction for strong light harvesting,GaN nanowires for efficient electron extraction and transfer,and Au/TiO_(2)for rapid electrocatalytic syngas *** photocathode yields a record-high solar energy conversion efficiency of 2.3%.Furthermore,desirable syngas compositions with CO/H_(2)ratios such as 1:2 and 1:1 can be produced by simply varying the size of Au *** calculations reveal that the active sites for CO and H_(2)generation are the facet and undercoordinated sites of Au particles,respectively.
In today’s societies, Road traffic accidents are emerging as some of the major threats that put the lives of people as well as the economy at risk. The strategy of addressing such risks for this study is novel as it ...
详细信息
ISBN:
(数字)9798350367973
ISBN:
(纸本)9798350367980
In today’s societies, Road traffic accidents are emerging as some of the major threats that put the lives of people as well as the economy at risk. The strategy of addressing such risks for this study is novel as it proposes the use of Transformer Learning coupled with Explainable AI. We use MobileNet architecture to predict the accident severity level with approximately the best possible accuracy of 98 percent. MobileNet, commonly used for efficient and other and embedded vision applications, has been adjusted and trained for the severity of the road accident prediction. The research method is built upon the Transformer model that can be applied to determine dependencies in the dataset on accidents as well as provide sound predictions. The use of Explainable AI enhances the understanding of the readers on the proposed model and reveals the relationship between the variables that influence the level of an accident. Such transparency is important to the readers, government institutions as well as traffic management authorities as they can then make the necessary adjustments. It involves data handling of an extensive record of past accidents and seeks to incorporate several variables that may range from climate during a particular accident to the type of roads, to the time of the day the accident occurred. The results of our training and testing are well tuned and checked so that we achieved the prediction accuracy of 98% regarding the probability of an accident and its severity indexes. Furthermore, the Explainable AI part reveals such characteristics influence prediction outcomes and aligns the model characteristics with real-life circumstances; as well as the high efficiency this research reached in terms of predicting the severity of the road traffic accident, it brings AI techniques that make this process fully automated yet easily explained. Therefore, this research is useful in designing safer roads and in aiding decisions in the field of accident prevention an
This paper will explore the possibilities of leveraging the underpinning blockchain technology to drive sustainability in an energy management system using the areas of demand response and supplier baseline assessment...
详细信息
COVID-19 has lately infected a big number of people worldwide. Medical service frameworks are strained as a result of the infection. The emergency unit, which is part of the medical services area, has experienced seve...
详细信息
Fruit harvesting poses a significant labor and financial burden on the fruit industry, which underscore the urgent need for advancements in robotic harvesting solutions. Despite considerable progress in leveraging dee...
详细信息
Reinforcement learning(RL) has roots in dynamic programming and it is called adaptive/approximate dynamic programming(ADP) within the control community. This paper reviews recent developments in ADP along with RL and ...
详细信息
Reinforcement learning(RL) has roots in dynamic programming and it is called adaptive/approximate dynamic programming(ADP) within the control community. This paper reviews recent developments in ADP along with RL and its applications to various advanced control fields. First, the background of the development of ADP is described, emphasizing the significance of regulation and tracking control problems. Some effective offline and online algorithms for ADP/adaptive critic control are displayed, where the main results towards discrete-time systems and continuous-time systems are surveyed, ***, the research progress on adaptive critic control based on the event-triggered framework and under uncertain environment is discussed, respectively, where event-based design, robust stabilization, and game design are reviewed. Moreover, the extensions of ADP for addressing control problems under complex environment attract enormous attention. The ADP architecture is revisited under the perspective of data-driven and RL frameworks,showing how they promote ADP formulation ***, several typical control applications with respect to RL and ADP are summarized, particularly in the fields of wastewater treatment processes and power systems, followed by some general prospects for future research. Overall, the comprehensive survey on ADP and RL for advanced control applications has d emonstrated its remarkable potential within the artificial intelligence era. In addition, it also plays a vital role in promoting environmental protection and industrial intelligence.
DG is a power production strategy that enhances efficiency by reducing carbon demand peaks, emissions, and transmission losses through the deployment of multiple smaller on-site energy sources located within individua...
详细信息
Considering the high energy consumption problem in the wastewater treatment process, this paper proposes a multi-objective optimization control scheme based on NSGA-II algorithm. The proposed scheme can not only ensur...
详细信息
暂无评论