Electrical ground looks simple on a schematic; unfortunately, the actual performance of a circuit is dictated by its layout （and by its printed-circuit-board）. When the ground node moves, system performance suffers ...Electrical ground looks simple on a schematic; unfortunately, the actual performance of a circuit is dictated by its layout （and by its printed-circuit-board）. When the ground node moves, system performance suffers and the system radiates electromagnetic interferences. But the understanding of the physics of ground noise can provide an intuitive sense for reducing the problem. Ground bounce can produce transients with amplitudes of volts; most often changing magnetic flux is the cause; in this work, the authors use a Finite-Difference Time-Domain to begin to understand such phenomena. Additionally, predicting substrate cross-talks in mixed-signal circuits has become a critical issue to preserve signal integrity in future integrated systems. Phenomena that involve parasitic signal propagation into the substrate are discussed. A simple methodology to predict the substrate cross-talk and some associated tools are presented. Finally, the authors indicate a stochastic method which could grasp both outer or inner RF （Radio-Frequency） radiations and substrate parasites.展开更多
Diyala River is the third largest tributary of the Tigris River running 445 km length and draining an area of 32,600 km2. The river is the major source of water supply for Diyala City for municipal, domestic, agricult...Diyala River is the third largest tributary of the Tigris River running 445 km length and draining an area of 32,600 km2. The river is the major source of water supply for Diyala City for municipal, domestic, agriculture and other purposes. Diyala River Basin currently is suffering from water scarcity and contamination problems. Up-to-date studies have shown that blue and green waters of a basin have been demonstrating increasing variability contributing to more severe droughts and floods seemingly due to climate change. To obtain better understanding of the impacts of climate change on water resources in Diyala River Basin in near 2046-2064 and distant future 2080~2100, SWAT （soil and water assessment tool） was used. The model is first examined for its capability of capturing the basin characteristics, and then, projections from six GCMs （general circulation models） are incorporated to assess the impacts of climate change on water resources under three emission scenarios： A2, AIB and B1. The results showed deteriorating water resources regime into the future.展开更多
This paper describes the procedure of using the GM (1,1) weighted Markov chain (GMWMC) to forecast the utility water supply, a quantity that usually has significant temporal variability. The GMWMC is formulated into f...This paper describes the procedure of using the GM (1,1) weighted Markov chain (GMWMC) to forecast the utility water supply, a quantity that usually has significant temporal variability. The GMWMC is formulated into five steps: (1) use GM (1,1) to fit the trend of the data, and obtain the relative error of the fitted values; (2) divide the relative error into ‘state’ data based on pre-set intervals; (3) calibrate the weighted Markov chain model: herein the parameters are the pre-set interval and the step of transition matrix (TM); (4) by using auto-correlation coefficient as the weight, the Markov chain provides the prediction interval. Then the mid-value of the interval is selected as the relative error for the data. Upon combining the data and its relative error, the predicted magnitude in a specific time period is obtained; and, (5) validate the model. Commonly, static intervals are used in both model calibration and validation stages, usually causing large errors. Thus, a dynamic adjustment interval (DAI) is proposed for a better performance. The proposed procedure is described and demonstrated through a case study, which shows that the DAI can usually achieve a better performance than the static interval, and the best TM may exist for certain data.展开更多
文摘Electrical ground looks simple on a schematic; unfortunately, the actual performance of a circuit is dictated by its layout （and by its printed-circuit-board）. When the ground node moves, system performance suffers and the system radiates electromagnetic interferences. But the understanding of the physics of ground noise can provide an intuitive sense for reducing the problem. Ground bounce can produce transients with amplitudes of volts; most often changing magnetic flux is the cause; in this work, the authors use a Finite-Difference Time-Domain to begin to understand such phenomena. Additionally, predicting substrate cross-talks in mixed-signal circuits has become a critical issue to preserve signal integrity in future integrated systems. Phenomena that involve parasitic signal propagation into the substrate are discussed. A simple methodology to predict the substrate cross-talk and some associated tools are presented. Finally, the authors indicate a stochastic method which could grasp both outer or inner RF （Radio-Frequency） radiations and substrate parasites.
文摘Diyala River is the third largest tributary of the Tigris River running 445 km length and draining an area of 32,600 km2. The river is the major source of water supply for Diyala City for municipal, domestic, agriculture and other purposes. Diyala River Basin currently is suffering from water scarcity and contamination problems. Up-to-date studies have shown that blue and green waters of a basin have been demonstrating increasing variability contributing to more severe droughts and floods seemingly due to climate change. To obtain better understanding of the impacts of climate change on water resources in Diyala River Basin in near 2046-2064 and distant future 2080~2100, SWAT （soil and water assessment tool） was used. The model is first examined for its capability of capturing the basin characteristics, and then, projections from six GCMs （general circulation models） are incorporated to assess the impacts of climate change on water resources under three emission scenarios： A2, AIB and B1. The results showed deteriorating water resources regime into the future.
基金Project supported by the National Natural Science Foundation of China (No. 50778121)the National Basic Research Program of China (No. 2007CB407306-1)the National Water Pollution Control and Management of Science and Technology Project of China (No. 2008ZX07317-005)
文摘This paper describes the procedure of using the GM (1,1) weighted Markov chain (GMWMC) to forecast the utility water supply, a quantity that usually has significant temporal variability. The GMWMC is formulated into five steps: (1) use GM (1,1) to fit the trend of the data, and obtain the relative error of the fitted values; (2) divide the relative error into ‘state’ data based on pre-set intervals; (3) calibrate the weighted Markov chain model: herein the parameters are the pre-set interval and the step of transition matrix (TM); (4) by using auto-correlation coefficient as the weight, the Markov chain provides the prediction interval. Then the mid-value of the interval is selected as the relative error for the data. Upon combining the data and its relative error, the predicted magnitude in a specific time period is obtained; and, (5) validate the model. Commonly, static intervals are used in both model calibration and validation stages, usually causing large errors. Thus, a dynamic adjustment interval (DAI) is proposed for a better performance. The proposed procedure is described and demonstrated through a case study, which shows that the DAI can usually achieve a better performance than the static interval, and the best TM may exist for certain data.
