As sensor networks are increasingly being deployed, there will be more sensors available in the same region, making it strategic to select the suitable ones to execute users＇ applications. We propose a task execution...As sensor networks are increasingly being deployed, there will be more sensors available in the same region, making it strategic to select the suitable ones to execute users＇ applications. We propose a task execution framework, named sTaskAlloc, to execute application energy efficiently by two main parts. First, considering that the energy consumption of an application is inversely proportional to the utilization rate of sensors, we present a hot sensor selection algorithm, HotTasking, to minimize the energy consumption of new added applications by selecting the most suitable sensor. Second, when a sensor is shared by multiple applications, proposed MergeOPT （a concurrent tasks optimization algorithm） is used to optimize energy consumption further by eliminating redundant sampling tasks. Experimental results show that sTaskAlloc can save more than 76% of energy for new added applications compared with existing methods and reduce up to 72% of sampling tasks when a sensor is shared by more than 10 applications.展开更多
Although plasticity in the neural system underlies working memory, and working memory can be improved by training, there is thus far no evidence that children with developmental dyslexia can benefit from working-memor...Although plasticity in the neural system underlies working memory, and working memory can be improved by training, there is thus far no evidence that children with developmental dyslexia can benefit from working-memory training. In the present study, thirty dyslexic children aged 8-11 years were recruited from an elementary school in Wuhan, China. They received working-memory training including training in visuospatial memory, verbal memory, and central executive tasks. The difficulty of the tasks was adjusted based on the performance of each subject, and the training sessions lasted 40 minutes per day, for 5 weeks. The results showed that working-memory training significantly enhanced performance on the nontrained working memory tasks such as the visuospatial, the verbal domains, and central executive tasks in children with developmental dyslexia. More importantly, the visual rhyming task and reading fluency task were also significantly improved by training. Progress on working memory measures was related to changes in reading skills. These experimental findings indicate that working memory is a pivotal factor in reading development among children with developmental dyslexia, and interventions to improve working memory may help dyslexic children to become more proficient in reading.展开更多
基金supported in part by the Strategic Priority Research Program of the Chinese Academy of Sciences under GrantNo.XDA06010403the International Science and Technology Cooperation Program of China under Grant No.2013DFA10690+1 种基金the ational Natural Science Foundation of China under Grant No.61003293the Beijing Natural Science Foundation under GrantNo.4112054
文摘As sensor networks are increasingly being deployed, there will be more sensors available in the same region, making it strategic to select the suitable ones to execute users＇ applications. We propose a task execution framework, named sTaskAlloc, to execute application energy efficiently by two main parts. First, considering that the energy consumption of an application is inversely proportional to the utilization rate of sensors, we present a hot sensor selection algorithm, HotTasking, to minimize the energy consumption of new added applications by selecting the most suitable sensor. Second, when a sensor is shared by multiple applications, proposed MergeOPT （a concurrent tasks optimization algorithm） is used to optimize energy consumption further by eliminating redundant sampling tasks. Experimental results show that sTaskAlloc can save more than 76% of energy for new added applications compared with existing methods and reduce up to 72% of sampling tasks when a sensor is shared by more than 10 applications.
基金supported by grants from the National Natural Science Foundation of China, No. 30872132
文摘Although plasticity in the neural system underlies working memory, and working memory can be improved by training, there is thus far no evidence that children with developmental dyslexia can benefit from working-memory training. In the present study, thirty dyslexic children aged 8-11 years were recruited from an elementary school in Wuhan, China. They received working-memory training including training in visuospatial memory, verbal memory, and central executive tasks. The difficulty of the tasks was adjusted based on the performance of each subject, and the training sessions lasted 40 minutes per day, for 5 weeks. The results showed that working-memory training significantly enhanced performance on the nontrained working memory tasks such as the visuospatial, the verbal domains, and central executive tasks in children with developmental dyslexia. More importantly, the visual rhyming task and reading fluency task were also significantly improved by training. Progress on working memory measures was related to changes in reading skills. These experimental findings indicate that working memory is a pivotal factor in reading development among children with developmental dyslexia, and interventions to improve working memory may help dyslexic children to become more proficient in reading.
