A model that rapidly predicts the density components of raw coal is described.It is based on a threegrade fast float/sink test.The recent comprehensive monthly floating and sinking data are used for comparison.The pre...A model that rapidly predicts the density components of raw coal is described.It is based on a threegrade fast float/sink test.The recent comprehensive monthly floating and sinking data are used for comparison.The predicted data are used to draw washability curves and to provide a rapid evaluation of the effect from heavy medium induced separation.Thirty-one production shifts worth of fast float/sink data and the corresponding quick ash data are used to verify the model.The results show a small error with an arithmetic average of 0.53 and an absolute average error of 1.50.This indicates that this model has high precision.The theoretical yield from the washability curves is 76.47% for the monthly comprehensive data and 81.31% using the model data.This is for a desired cleaned coal ash of 9%.The relative error between these two is 6.33%,which is small and indicates that the predicted data can be used to rapidly evaluate the separation effect of gravity separation equipment.展开更多
This paper presents a universal platform "uSensing" to support smartphones to communicate with sensor nodes in Wireless Sensor Networks (WSNs).Since phones have different CPU processers and operating systems...This paper presents a universal platform "uSensing" to support smartphones to communicate with sensor nodes in Wireless Sensor Networks (WSNs).Since phones have different CPU processers and operating systems,it is a challenge to merge these heterogeneities and develop such a universal platform.In this paper,we design both hardware and software to support the "universal" feature of uSensing:1) "uSD" card:an IEEE 802.15.4 physical communication card with SD interface;2) "uSinkWare":a WSNs middleware running on smartphones.Integrated with uSD card and uSinkWare,phones become mobile data sinks to access into WSNs and parse messages from sensor nodes.We demonstrate the proposed uSensing platform in a commercial smartphone to connect with our WSNs testbed,and validate that the smartphone has the same WSNs functions as commercial fixed sink.Additionally,we evaluate the performance of uSensing platform through measuring phone's CPU load and power consumption,and analyze the performance of these metrics theoretically.The results suggest that the phone-based mobile sink has enough capability to serve as a mobile sink of WSNs and can work up to twenty hours due to low power consumption.展开更多
基金National Natural Science Foundation of China (No. 51174202)Doctoral Fund of Ministry of Education of China (No. 20100095110013)
文摘A model that rapidly predicts the density components of raw coal is described.It is based on a threegrade fast float/sink test.The recent comprehensive monthly floating and sinking data are used for comparison.The predicted data are used to draw washability curves and to provide a rapid evaluation of the effect from heavy medium induced separation.Thirty-one production shifts worth of fast float/sink data and the corresponding quick ash data are used to verify the model.The results show a small error with an arithmetic average of 0.53 and an absolute average error of 1.50.This indicates that this model has high precision.The theoretical yield from the washability curves is 76.47% for the monthly comprehensive data and 81.31% using the model data.This is for a desired cleaned coal ash of 9%.The relative error between these two is 6.33%,which is small and indicates that the predicted data can be used to rapidly evaluate the separation effect of gravity separation equipment.
基金supported by the National Natural Science Foundation of China under Grant No.60932005China and Europe Government Cooperation Projects of the Ministry of Science and Technology under Grant No.2010DFA11680the Tsinghua Sci-Tech Project under Grant No.2011THZ0
文摘This paper presents a universal platform "uSensing" to support smartphones to communicate with sensor nodes in Wireless Sensor Networks (WSNs).Since phones have different CPU processers and operating systems,it is a challenge to merge these heterogeneities and develop such a universal platform.In this paper,we design both hardware and software to support the "universal" feature of uSensing:1) "uSD" card:an IEEE 802.15.4 physical communication card with SD interface;2) "uSinkWare":a WSNs middleware running on smartphones.Integrated with uSD card and uSinkWare,phones become mobile data sinks to access into WSNs and parse messages from sensor nodes.We demonstrate the proposed uSensing platform in a commercial smartphone to connect with our WSNs testbed,and validate that the smartphone has the same WSNs functions as commercial fixed sink.Additionally,we evaluate the performance of uSensing platform through measuring phone's CPU load and power consumption,and analyze the performance of these metrics theoretically.The results suggest that the phone-based mobile sink has enough capability to serve as a mobile sink of WSNs and can work up to twenty hours due to low power consumption.
