MATB(Multi-Attribute Task Battery),developed by NASA,simulates real-world task demands and work environments.It assesses human cognitive and executive abilities in high-load,complex task settings,as well as their adap...MATB(Multi-Attribute Task Battery),developed by NASA,simulates real-world task demands and work environments.It assesses human cognitive and executive abilities in high-load,complex task settings,as well as their adaptive capacity for task switching and attention allocation.This article reviews MATB's primary applications and usage,exploring mental workload-related research with MATB,analyzing experimental procedure design,objective physiological signals,and model construction.This analysis facilitates a comprehensive understanding of utilizing MATB for mental workload experiments and improving experimental design.Additionally,it proposes a more comprehensive and scientific experimental procedure for cognitive load research using MATB.Through this review,researchers gain insights into the versatility and potential of MATB as a tool for assessing mental workload and optimizing experimental design in various fields.展开更多
Dynamic voltage scaling （DVS） is an efficient approach to maximize the battery life of portable devices. A novel overall planning strategy （OPS II） balancing slack supply and demand for DVS is proposed. An OPS II-...Dynamic voltage scaling （DVS） is an efficient approach to maximize the battery life of portable devices. A novel overall planning strategy （OPS II） balancing slack supply and demand for DVS is proposed. An OPS II-based slack-nibbling overall planning strategy （SNOPS） algorithm is also proposed, which iteratively nibbles slacks for appropriate tasks selected by an overall planning dynamic priority function to perform DVS until the slack is exhausted and an optimum voltage setting is obtained. For a high-load task set, SNOPS manages to recover battery overload while maintaining schedulability. For random variable-load task sets, SNOPS achieves a saving of 29.51% battery capacity on average, the suboptimal gap is 27.84% narrower than that of our previously proposed OPS-based algorithm, and 92.10% narrower than that of the algorithm proposed by Chowdhury et al. Results indicate that OPS n manages to save battery to various extents while maintaining schedulability, and demonstrates good load compatibility and close-to-optimal performance on average.展开更多
In recent years,multiple-load automatic guided vehicle(AGV)is increasingly used in the logistics transportation fields,owing to the advantages of smaller fleet size and fewer occurrences of traffic congestion.However,...In recent years,multiple-load automatic guided vehicle(AGV)is increasingly used in the logistics transportation fields,owing to the advantages of smaller fleet size and fewer occurrences of traffic congestion.However,one main challenge lies in the deadlock-avoidance for the dispatching process of a multiple-load AGV system.To prevent the system from falling into a deadlock,a strategy of keeping the number of jobs in the system(NJIS)at a low level is adopted in most existing literatures.It is noteworthy that a low-level NJIS will make the processing machine easier to be starved,thereby reducing the system efficiency unavoidably.The motivation of the paper is to develop a deadlock-avoidance dispatching method for a multiple-load AGV system operating at a high NJIS level.Firstly,the deadlock-avoidance dispatching method is devised by incorporating a deadlock-avoidance strategy into a dispatching procedure that contains four sub-problems.In this strategy,critical tasks are recognized according to the status of workstation buffers,and then temporarily forbidden to avoid potential deadlocks.Secondly,three multiattribute dispatching rules are designed for system efficiency,where both the traveling distance and the buffer status are taken into account.Finally,a simulation system is developed to evaluate the performance of the proposed deadlock-avoidance strategy and dispatching rules at different NJIS levels.The experimental results demonstrate that our deadlock-avoidance dispatching method can improve the system efficiency at a high NJIS level and the adaptability to various system settings,while still avoiding potential deadlocks.展开更多
For domestic consumers in the rural areas of northern Kenya, as in other developing countries, the typical source of electrical supply is diesel generators. However, diesel generators are associated with both CO2 emis...For domestic consumers in the rural areas of northern Kenya, as in other developing countries, the typical source of electrical supply is diesel generators. However, diesel generators are associated with both CO2 emissions, which adversely affect the environment and increase diesel fuel prices, which inflate the prices of consumer goods. The Kenya government has taken steps towards addressing this issue by proposing The Hybrid Mini-Grid Project, which involves the installation of 3 MW of wind and solar energy systems in facilities with existing diesel generators. However, this project has not yet been implemented. As a contribution to this effort, this study proposes, simulates and analyzes five different configurations of hybrid energy systems incorporating wind energy, solar energy and battery storage to replace the stand-alone diesel power systems servicing six remote villages in northern Kenya. If implemented, the systems proposed here would reduce Kenya’s dependency on diesel fuel, leading to reductions in its carbon footprint. This analysis confirms the feasibility of these hybrid systems with many configurations being profitable. A Multi-Attribute Trade-Off Analysis is employed to determine the best hybrid system configuration option that would reduce diesel fuel consumption and jointly minimize CO2 emissions and net present cost. This analysis determined that a wind-diesel-battery configuration consisting of two 500 kW turbines, 1200 kW diesel capacity and 95,040 Ah battery capacity is the best option to replace a 3200 kW stand-alone diesel system providing electricity to a village with a peak demand of 839 kW. It has the potential to reduce diesel fuel consumption and CO2 emissions by up to 98.8%.展开更多
文摘MATB(Multi-Attribute Task Battery),developed by NASA,simulates real-world task demands and work environments.It assesses human cognitive and executive abilities in high-load,complex task settings,as well as their adaptive capacity for task switching and attention allocation.This article reviews MATB's primary applications and usage,exploring mental workload-related research with MATB,analyzing experimental procedure design,objective physiological signals,and model construction.This analysis facilitates a comprehensive understanding of utilizing MATB for mental workload experiments and improving experimental design.Additionally,it proposes a more comprehensive and scientific experimental procedure for cognitive load research using MATB.Through this review,researchers gain insights into the versatility and potential of MATB as a tool for assessing mental workload and optimizing experimental design in various fields.
基金Supported by the National High Technology Research and Development Program of China (863 Program) (2002AA1Z1490)the Spe-cialized Research Fund for the Doctoral Program of Higher Education of China (20040486049)
文摘Dynamic voltage scaling （DVS） is an efficient approach to maximize the battery life of portable devices. A novel overall planning strategy （OPS II） balancing slack supply and demand for DVS is proposed. An OPS II-based slack-nibbling overall planning strategy （SNOPS） algorithm is also proposed, which iteratively nibbles slacks for appropriate tasks selected by an overall planning dynamic priority function to perform DVS until the slack is exhausted and an optimum voltage setting is obtained. For a high-load task set, SNOPS manages to recover battery overload while maintaining schedulability. For random variable-load task sets, SNOPS achieves a saving of 29.51% battery capacity on average, the suboptimal gap is 27.84% narrower than that of our previously proposed OPS-based algorithm, and 92.10% narrower than that of the algorithm proposed by Chowdhury et al. Results indicate that OPS n manages to save battery to various extents while maintaining schedulability, and demonstrates good load compatibility and close-to-optimal performance on average.
基金supported by the National Natural Science Foundation of China(Nos.52005427,61973154)the National Defense Basic Scientific Research Program of China(No.JCKY2018605C004)+1 种基金the Natural Science Research Project of Jiangsu Higher Education Institutions(Nos.19KJB510013,18KJA460009)the Foundation of Graduate Innovation Center in Nanjing University of Aeronautics and Astronautics(No.KFJJ20190516)。
文摘In recent years,multiple-load automatic guided vehicle(AGV)is increasingly used in the logistics transportation fields,owing to the advantages of smaller fleet size and fewer occurrences of traffic congestion.However,one main challenge lies in the deadlock-avoidance for the dispatching process of a multiple-load AGV system.To prevent the system from falling into a deadlock,a strategy of keeping the number of jobs in the system(NJIS)at a low level is adopted in most existing literatures.It is noteworthy that a low-level NJIS will make the processing machine easier to be starved,thereby reducing the system efficiency unavoidably.The motivation of the paper is to develop a deadlock-avoidance dispatching method for a multiple-load AGV system operating at a high NJIS level.Firstly,the deadlock-avoidance dispatching method is devised by incorporating a deadlock-avoidance strategy into a dispatching procedure that contains four sub-problems.In this strategy,critical tasks are recognized according to the status of workstation buffers,and then temporarily forbidden to avoid potential deadlocks.Secondly,three multiattribute dispatching rules are designed for system efficiency,where both the traveling distance and the buffer status are taken into account.Finally,a simulation system is developed to evaluate the performance of the proposed deadlock-avoidance strategy and dispatching rules at different NJIS levels.The experimental results demonstrate that our deadlock-avoidance dispatching method can improve the system efficiency at a high NJIS level and the adaptability to various system settings,while still avoiding potential deadlocks.
文摘For domestic consumers in the rural areas of northern Kenya, as in other developing countries, the typical source of electrical supply is diesel generators. However, diesel generators are associated with both CO2 emissions, which adversely affect the environment and increase diesel fuel prices, which inflate the prices of consumer goods. The Kenya government has taken steps towards addressing this issue by proposing The Hybrid Mini-Grid Project, which involves the installation of 3 MW of wind and solar energy systems in facilities with existing diesel generators. However, this project has not yet been implemented. As a contribution to this effort, this study proposes, simulates and analyzes five different configurations of hybrid energy systems incorporating wind energy, solar energy and battery storage to replace the stand-alone diesel power systems servicing six remote villages in northern Kenya. If implemented, the systems proposed here would reduce Kenya’s dependency on diesel fuel, leading to reductions in its carbon footprint. This analysis confirms the feasibility of these hybrid systems with many configurations being profitable. A Multi-Attribute Trade-Off Analysis is employed to determine the best hybrid system configuration option that would reduce diesel fuel consumption and jointly minimize CO2 emissions and net present cost. This analysis determined that a wind-diesel-battery configuration consisting of two 500 kW turbines, 1200 kW diesel capacity and 95,040 Ah battery capacity is the best option to replace a 3200 kW stand-alone diesel system providing electricity to a village with a peak demand of 839 kW. It has the potential to reduce diesel fuel consumption and CO2 emissions by up to 98.8%.
