The identification of activity locations in con- tinuous GPS trajectories is an essential preliminary step in obtaining person trip data and for activity-based trans- portation demand forecasting. In this research, a ...The identification of activity locations in con- tinuous GPS trajectories is an essential preliminary step in obtaining person trip data and for activity-based trans- portation demand forecasting. In this research, a two-step methodology for identifying activity stop locations is pro- posed. In the first step, an improved density-based spatial clustering of applications with noise (DBSCAN) algorithm identifies stop points and moving points; then in the second step, the support vector machines (SVMs) method distin- guishes activity stops from non-activity stops among the identified stop points. A time sequence constraint and a direction change constraint are applied as improvements to DBSCAN (yielding an improved algorithm known as C-DBSCAN). Then three major features are extracted for use in the SVMs method: stop duration, mean distance to the centroid of a cluster of points at a stop location, and the shorter of distances from current location to home and to the workplace. The proposed methodology was tested using GPS data collected from mobile phones in the Nagoya area of Japan. The C-DBSCAN algorithm achieves an accuracy of 90 % in identifying stop points in the first step, while the SVMs method is 96 % accurate in distin- guishing the locations of activity stops from non-activity stops in the second step. Compared to other variants of DBSCAN used to identify activity locations from GPS trajectories, this two-step method is generally superior.展开更多
Objective To construct Cox7a2 fluorescent vector and study its effect on cytochrome C oxidase ( COX) activity in mouse Sertoli cell line TM4. Methods The coding region of CoxTa2 was amplified from mouse Sertoli cell l...Objective To construct Cox7a2 fluorescent vector and study its effect on cytochrome C oxidase ( COX) activity in mouse Sertoli cell line TM4. Methods The coding region of CoxTa2 was amplified from mouse Sertoli cell line TM4 by RT-PCR. PCR product was展开更多
This paper presents a 5-bit active LO phase shifter with a new vector sum method for 9–12 GHz applications. The 5-bit phase shifter is composed of four 3-bit sub phase shifters by adopting the new vector sum method, ...This paper presents a 5-bit active LO phase shifter with a new vector sum method for 9–12 GHz applications. The 5-bit phase shifter is composed of four 3-bit sub phase shifters by adopting the new vector sum method, which reduces the requirements on the resolution of the variable gain amplifier(VGA). The variable gain function is realized by switch on/off parallel input transistor pairs rather than changing the bias current of the VGA,which avoids the linearity variation and drain-source voltage variation existing in the quadrature vector sum active phase shifter. The 5-bit active LO phase shifter is fabricated in TSMC 0.13μm CMOS technology. The measured results show that the phase shifter achieves 5-bit phase shift accuracy. The average conversion gain for 32 phase states is 0:5 to 7 d B from 9 to 12 GHz. The RMS gain error and the RMS phase error are smaller than 0.8 d B and 4° respectively. The current consumption is 27.7 m A from a 1.2 V supply voltage.展开更多
基金supported by Grant-in-Aid for Scientific Research(No.25630215 and 26220906)from the Ministry of Education,Culture,Sports,Science,and Technology,Japanthe Japan Society for the Promotion of Science
文摘The identification of activity locations in con- tinuous GPS trajectories is an essential preliminary step in obtaining person trip data and for activity-based trans- portation demand forecasting. In this research, a two-step methodology for identifying activity stop locations is pro- posed. In the first step, an improved density-based spatial clustering of applications with noise (DBSCAN) algorithm identifies stop points and moving points; then in the second step, the support vector machines (SVMs) method distin- guishes activity stops from non-activity stops among the identified stop points. A time sequence constraint and a direction change constraint are applied as improvements to DBSCAN (yielding an improved algorithm known as C-DBSCAN). Then three major features are extracted for use in the SVMs method: stop duration, mean distance to the centroid of a cluster of points at a stop location, and the shorter of distances from current location to home and to the workplace. The proposed methodology was tested using GPS data collected from mobile phones in the Nagoya area of Japan. The C-DBSCAN algorithm achieves an accuracy of 90 % in identifying stop points in the first step, while the SVMs method is 96 % accurate in distin- guishing the locations of activity stops from non-activity stops in the second step. Compared to other variants of DBSCAN used to identify activity locations from GPS trajectories, this two-step method is generally superior.
文摘Objective To construct Cox7a2 fluorescent vector and study its effect on cytochrome C oxidase ( COX) activity in mouse Sertoli cell line TM4. Methods The coding region of CoxTa2 was amplified from mouse Sertoli cell line TM4 by RT-PCR. PCR product was
基金Project supported by the National Natural Science Foundation of China(No.61376037)the National Twelve-Five Project(No.513***)
文摘This paper presents a 5-bit active LO phase shifter with a new vector sum method for 9–12 GHz applications. The 5-bit phase shifter is composed of four 3-bit sub phase shifters by adopting the new vector sum method, which reduces the requirements on the resolution of the variable gain amplifier(VGA). The variable gain function is realized by switch on/off parallel input transistor pairs rather than changing the bias current of the VGA,which avoids the linearity variation and drain-source voltage variation existing in the quadrature vector sum active phase shifter. The 5-bit active LO phase shifter is fabricated in TSMC 0.13μm CMOS technology. The measured results show that the phase shifter achieves 5-bit phase shift accuracy. The average conversion gain for 32 phase states is 0:5 to 7 d B from 9 to 12 GHz. The RMS gain error and the RMS phase error are smaller than 0.8 d B and 4° respectively. The current consumption is 27.7 m A from a 1.2 V supply voltage.