Using the Franck-Hertz Experiment To Illustrate Quantization Energy States of the Neon Atom by Electron Impact

na provide students with motivation for the study of quantum mechanics. That microscopic matter exists in quantized states can be demonstrated with modem versions of historic experiments: atomic line spectra (I), resonance potentials, and blackbody radiation. The resonance potentials of mercury were discovered by Franck and Hertz in 1914 (2). Their experiment consisted of bombarding atoms by electrons, and detecting the kinetic energy loss of the scattered electrons (3). Prior to the Franck-Hertz experiment, spectroscopic work bv Balmer and Rvdbere revealed that atoms emitted radiatibn at discrete ekergiis. The Franck-Hertz experiment showed directly that auantized enerm levels in an atom are real, not jist optiEal artifacts. atom can be raised to excited states by inelastic collisions with electrons as well as lowered from excited states by emission of photons. The classic Franck-Hertz experiment is carried out with mercury (4-7). Here we present an experiment for the study of resonance potentials using neon.

Large margin vector quantization

In this paper we describe the Large Margin Vector Quantization algorithm (LMVQ), which uses gradient ascent to maximise the margin of a radial basis function classifier. We present a derivation of the algorithm, which proceeds from an estimate of the class-conditional probability densities. We show that the key behaviour of Kohonen's well-known LVQ2 and LVQ3 algorithms emerge as natural consequences of our formulation. We compare the performance of LMVQ with that of Kohonen's LVQ algorithms on an artificial classification problem and several well known benchmark classification tasks. We find that the classifiers produced by LMVQ attain a level of accuracy that compares well with those obtained via LVQ1, LVQ2 and LVQ3, with reduced storage complexity. We indicate future directions of enquiry based on the large margin approach to Learning Vector Quantization.

Bitrate modeling of scalable videos using quantization parameter, frame rate and spatial resolution

The quality and bitrate modeling is essential to effectively adapt the bitrate and quality of videos when delivered to multiplatform devices over resource constraint heterogeneous networks. The recent model proposed by Wang et al. estimates the bitrate and quality of videos in terms of the frame rate and quantization parameter. However, to build an effective video adaptation framework, it is crucial to incorporate the spatial resolution in the analytical model for bitrate and perceptual quality adaptation. Hence, this paper proposes an analytical model to estimate the bitrate of videos in terms of quantization parameter, frame rate, and spatial resolution. The model can fit the measured data accurately which is evident from the high Pearson correlation. The proposed model is based on the observation that the relative reduction in bitrate due to decreasing spatial resolution is independent of the quantization parameter and frame rate. This modeling can be used for rate-constrained bit-stream adaptation scheme which selects the scalability parameters to optimize the perceptual quality for a given bandwidth constraint.

Vector quantization based Gaussian modeling for speaker verification

Gaussian mixture models (GMMs) have become an established means of modeling feature distributions in speaker recognition systems. It is useful for experimentation and practical implementation purposes to develop and test these models in an efficient manner particularly when computational resources are limited. A method of combining vector quantization (VQ) with single multi-dimensional Gaussians is proposed to rapidly generate a robust model approximation to the Gaussian mixture model. A fast method of testing these systems is also proposed and implemented. Results on the NIST 1996 Speaker Recognition Database suggest comparable and in some cases an improved verification performance to the traditional GMM based analysis scheme. In addition, previous research for the task of speaker identification indicated a similar system perfomance between the VQ Gaussian based technique and GMMs

Metal artifacts from titanium and steel screws in CT, 1.5T and 3T MR images of the tibial Pilon: A quantitative assessment in 3D

Radiographs are commonly used to assess articular reduction of the distal tibia (pilon) fractures postoperatively, but may reveal malreductions inaccurately. While Magnetic Resonance Imaging (MRI) and Computed Tomography (CT) are potential 3D alternatives they generate metal-related artifacts. This study aims to quantify the artifact size from orthopaedic screws using CT, 1.5T and 3T MRI data. Three screws were inserted into one intact human cadaver ankle specimen proximal to and along the distal articular surface, then CT, 1.5T and 3T MRI scanned. Four types of screws were investigated: titanium alloy (TA), stainless steel (SS) (Ø = 3.5 mm), cannulated TA (CTA) and cannulated SS (CSS)(Ø = 4.0 mm, Ø empty core = 2.6 mm). 3D artifact models were reconstructed using adaptive thresholding. The artifact size was measured by calculating the perpendicular distance from the central screw axis to the boundary of the artifact in four anatomical directions with respect to the distal tibia. The artifact sizes (in the order of TA, SS, CTA and CSS) from CT were 2.0 mm, 2.6 mm, 1.6 mm and 2.0 mm; from 1.5T MRI they were 3.7 mm, 10.9 mm, 2.9 mm, and 9 mm; and 3T MRI they were 4.4 mm, 15.3 mm, 3.8 mm, and 11.6 mm respectively. Therefore, CT can be used as long as the screws are at a safe distance of about 2 mm from the articular surface. MRI can be used if the screws are at least 3 mm away from the articular surface except SS and CSS. Artifacts from steel screws were too large thus obstructed the pilon from being visualised in MRI. Significant differences (P < 0.05) were found in the size of artifacts between all imaging modalities, screw types and material types, except 1.5T versus 3T MRI for the SS screws (P = 0.063). CTA screws near the joint surface can improve postoperative assessment in CT and MRI. MRI presents a favourable non-ionising alternative when using titanium hardware. Since these factors may influence the quality of postoperative assessment, potential improvements in operative techniques should be considered.

Linear filtering in DCT IV/DST IV and MDCT/MDST domain

In this paper, expressions for convolution multiplication properties of DCT IV and DST IV are derived starting from equivalent DFT representations. Using these expressions methods for implementing linear filtering through block convolution in the DCT IV and DST IV domain are proposed. Techniques developed for DCT IV and DST IV are further extended to MDCT and MDST where the filter implementation is near exact for symmetric filters and approximate for non-symmetric filters. No additional overlapping is required for implementing the symmetric filtering in the MDCT domain and hence the proposed algorithm is computationally competitive with DFT based systems. Moreover, inherent 50% overlap between the adjacent frames used for MDCT/MDST domain reduces the blocking artifacts due to block processing or quantization. The techniques are computationally efficient for symmetric filters and provides a new alternative to DFT based convolution.

Analysis Of The Energy Quantization Effects On Single Electron Inverter Performance Through Noise Margin Modeling

Possible integration of Single Electron Transistor (SET) with CMOS technology is making the study of semiconductor SET more important than the metallic SET and consequently, the study of energy quantization effects on semiconductor SET devices and circuits is gaining significance. In this paper, for the first time, the effects of energy quantization on SET inverter performance are examined through analytical modeling and Monte Carlo simulations. It is observed that the primary effect of energy quantization is to change the Coulomb Blockade region and drain current of SET devices and as a result affects the noise margin, power dissipation, and the propagation delay of SET inverter. A new model for the noise margin of SET inverter is proposed which includes the energy quantization effects. Using the noise margin as a metric, the robustness of SET inverter is studied against the effects of energy quantization. It is shown that SET inverter designed with CT : CG = 1/3 (where CT and CG are tunnel junction and gate capacitances respectively) offers maximum robustness against energy quantization.

Reduced complexity two stage vector quantization

We address the issue of complexity for vector quantization (VQ) of wide-band speech LSF (line spectrum frequency) parameters. The recently proposed switched split VQ (SSVQ) method provides better rate-distortion (R/D) performance than the traditional split VQ (SVQ) method, even at the requirement of lower computational complexity. but at the expense of much higher memory. We develop the two stage SVQ (TsSVQ) method, by which we gain both the memory and computational advantages and still retain good R/D performance. The proposed TsSVQ method uses a full dimensional quantizer in its first stage for exploiting all the higher dimensional coding advantages and then, uses an SVQ method for quantizing the residual vector in the second stage so as to reduce the complexity. We also develop a transform domain residual coding method in this two stage architecture such that it further reduces the computational complexity. To design an effective residual codebook in the second stage, variance normalization of Voronoi regions is carried out which leads to the design of two new methods, referred to as normalized two stage SVQ (NTsSVQ) and normalized two stage transform domain SVQ (NTsTrSVQ). These two new methods have complimentary strengths and hence, they are combined in a switched VQ mode which leads to the further improvement in R/D performance, but retaining the low complexity requirement. We evaluate the performances of new methods for wide-band speech LSF parameter quantization and show their advantages over established SVQ and SSVQ methods.

Multiple-quantum artifacts in single-quantum two-dimensional correlated NMR spectra of strongly coupled spins

Artifacts in the form of cross peaks have been observed along two- and three-quantum diagonals in single-quantum two-dimensional correlated (COSY) spectra of several peptides and oligonucleotides. These have been identified as due to the presence of a non-equilibrium state of kind I (a state describable by populations which differ from equilibrium) of strongly coupled spins carried over from one experiment to the next in the COSY algorithm.

Modeling and analysis of energy quantization effects on single electron inverter performance

In this paper, for the first time, the effects of energy quantization on single electron transistor (SET) inverter performance are analyzed through analytical modeling and Monte Carlo simulations. It is shown that energy quantization mainly changes the Coulomb blockade region and drain current of SET devices and thus affects the noise margin, power dissipation, and the propagation delay of SET inverter. A new analytical model for the noise margin of SET inverter is proposed which includes the energy quantization effects. Using the noise margin as a metric, the robustness of SET inverter is studied against the effects of energy quantization. A compact expression is developed for a novel parameter quantization threshold which is introduced for the first time in this paper. Quantization threshold explicitly defines the maximum energy quantization that an SET inverter logic circuit can withstand before its noise margin falls below a specified tolerance level. It is found that SET inverter designed with CT:CG=1/3 (where CT and CG are tunnel junction and gate capacitances, respectively) offers maximum robustness against energy quantization.

Impact of Energy Quantization on the Performance of Current-Biased SET Circuits

The current-biased single electron transistor (SET) (CBS) is an integral part of almost all hybrid CMOS SET circuits. In this paper, for the first time, the effects of energy quantization on the performance of CBS-based circuits are studied through analytical modeling and Monte Carlo simulations. It is demonstrated that energy quantization has no impact on the gain of the CBS characteristics, although it changes the output voltage levels and oscillation periodicity. The effects of energy quantization are further studied for two circuits: negative differential resistance (NDR) and neuron cell, which use the CBS. A new model for the conductance of NDR characteristics is also formulated that includes the energy quantization term.

Gravitational charges and the quantization of mass

Abstract is not available.

Quantization noise in binary holograms

The signal-to-noise (S/N) ratio in the reconstructed image from a binary hologram has been quantitatively related to the amplitude and phase quantization levels. The S/N ratio increases monotonically with increasing number of quantization levels. This observation is further supported by experimental results.

Effect of fourier domain quantization on matched filtering

It is shown that the use of a coarsely quantized binary digital hologram as a matched filter on an optical computer does not degrade signal-to-noise ratio (SNR) appreciably.