Atomic force microscopy（AFM） is a commonly used technique for graphene thickness measurement.However, due to surface roughness caused by graphene itself and variation introduced in AFM measurement, graphene thicknes...Atomic force microscopy（AFM） is a commonly used technique for graphene thickness measurement.However, due to surface roughness caused by graphene itself and variation introduced in AFM measurement, graphene thickness is difficult to be accurately determined by AFM. In this paper, a histogram method was used for reliable measurements of graphene thickness using AFM. The influences of various measurement parameters in AFM analysis were investigated. The experimental results indicate that significant deviation can be introduced using various order of flatten and improperly selected measurement parameters including amplitude setpoint and drive amplitude. At amplitude setpoint of 100 mV and drive amplitude of 100 m V, thickness of 1 layer（1L）, 2 layers（2L） and 4 layers（4L） graphene were measured.The height differences for 1L, 2L and 4L were 1.51 ± 0.16 nm, 1.92 ± 0.13 nm and 2.73 ± 0.10 nm, respectively. By comparing these values, thickness of single layer graphene can be accurately determined to be0.41 ± 0.09 nm.展开更多
Free energy calculations may provide vital information for studying various chemical and biological processes.Quantum mechanical methods are required to accurately describe interaction energies,but their computations ...Free energy calculations may provide vital information for studying various chemical and biological processes.Quantum mechanical methods are required to accurately describe interaction energies,but their computations are often too demanding for conformational sampling.As a remedy,level correction schemes that allow calculating high level free energies based on conformations from lower level simulations have been developed.Here,we present a variation of a Monte Carlo(MC)resampling approach in relation to the weighted histogram analysis method(WHAM).We show that our scheme can generate free energy surfaces that can practically converge to the exact one with sufficient sampling,and that it treats cases with insufficient sampling in a more stable manner than the conventional WHAM-based level correction scheme.It can also provide a guide for checking the uncertainty of the levelcorrected surface and a well-defined criterion for deciding the extent of smoothing on the free energy surface for its visual improvement.We demonstrate these aspects by obtaining the free energy maps associated with the alanine dipeptide and proton transfer network of the KillerRed protein in explicit water,and exemplify that the MC resampled WHAM scheme can be a practical tool for producing free energy surfaces of realistic systems.展开更多
In this paper, we present a theoretical codebook design method for VQ-based fast face recognition algorithm to im-prove recognition accuracy. Based on the systematic analysis and classification of code patterns, first...In this paper, we present a theoretical codebook design method for VQ-based fast face recognition algorithm to im-prove recognition accuracy. Based on the systematic analysis and classification of code patterns, firstly we theoretically create a systematically organized codebook. Combined with another codebook created by Kohonen’s Self-Organizing Maps (SOM) method, an optimized codebook consisted of 2×2 codevectors for facial images is generated. Experimental results show face recognition using such a codebook is more efficient than the codebook consisted of 4×4 codevector used in conventional algorithm. The highest average recognition rate of 98.6% is obtained for 40 persons’ 400 images of publicly available face database of AT&T Laboratories Cambridge containing variations in lighting, posing, and expressions. A table look-up (TLU) method is also proposed for the speed up of the recognition processing. By applying this method in the quantization step, the total recognition processing time achieves only 28 msec, enabling real-time face recognition.展开更多
基金supported by the Program of National Key Technology R&D Program of the Ministry of Science and Technology of China(2011BAK15B04)
文摘Atomic force microscopy（AFM） is a commonly used technique for graphene thickness measurement.However, due to surface roughness caused by graphene itself and variation introduced in AFM measurement, graphene thickness is difficult to be accurately determined by AFM. In this paper, a histogram method was used for reliable measurements of graphene thickness using AFM. The influences of various measurement parameters in AFM analysis were investigated. The experimental results indicate that significant deviation can be introduced using various order of flatten and improperly selected measurement parameters including amplitude setpoint and drive amplitude. At amplitude setpoint of 100 mV and drive amplitude of 100 m V, thickness of 1 layer（1L）, 2 layers（2L） and 4 layers（4L） graphene were measured.The height differences for 1L, 2L and 4L were 1.51 ± 0.16 nm, 1.92 ± 0.13 nm and 2.73 ± 0.10 nm, respectively. By comparing these values, thickness of single layer graphene can be accurately determined to be0.41 ± 0.09 nm.
基金supported by the Mid-career Researcher Program(No.2017R1A2B3004946)through National Research Foundationfunded by Ministry of Science and ICT of Korea.
文摘Free energy calculations may provide vital information for studying various chemical and biological processes.Quantum mechanical methods are required to accurately describe interaction energies,but their computations are often too demanding for conformational sampling.As a remedy,level correction schemes that allow calculating high level free energies based on conformations from lower level simulations have been developed.Here,we present a variation of a Monte Carlo(MC)resampling approach in relation to the weighted histogram analysis method(WHAM).We show that our scheme can generate free energy surfaces that can practically converge to the exact one with sufficient sampling,and that it treats cases with insufficient sampling in a more stable manner than the conventional WHAM-based level correction scheme.It can also provide a guide for checking the uncertainty of the levelcorrected surface and a well-defined criterion for deciding the extent of smoothing on the free energy surface for its visual improvement.We demonstrate these aspects by obtaining the free energy maps associated with the alanine dipeptide and proton transfer network of the KillerRed protein in explicit water,and exemplify that the MC resampled WHAM scheme can be a practical tool for producing free energy surfaces of realistic systems.
文摘In this paper, we present a theoretical codebook design method for VQ-based fast face recognition algorithm to im-prove recognition accuracy. Based on the systematic analysis and classification of code patterns, firstly we theoretically create a systematically organized codebook. Combined with another codebook created by Kohonen’s Self-Organizing Maps (SOM) method, an optimized codebook consisted of 2×2 codevectors for facial images is generated. Experimental results show face recognition using such a codebook is more efficient than the codebook consisted of 4×4 codevector used in conventional algorithm. The highest average recognition rate of 98.6% is obtained for 40 persons’ 400 images of publicly available face database of AT&T Laboratories Cambridge containing variations in lighting, posing, and expressions. A table look-up (TLU) method is also proposed for the speed up of the recognition processing. By applying this method in the quantization step, the total recognition processing time achieves only 28 msec, enabling real-time face recognition.
