Correlation between the golden ratio and nanowire transistor performance

An observation was made in this research regarding the fact that the signatures of isotropic charge distributions in silicon nanowire transistors (NWT) displayed identical characteristics to the golden ratio (Phi). In turn, a simulation was conducted regarding ultra-scaled n-type Si (NWT) with respect to the 5-nm complementary metal-oxide-semiconductor (CMOS) application. The results reveal that the amount of mobile charge in the channel and intrinsic speed of the device are determined by the device geometry and could also be correlated to the golden ratio (Phi). This paper highlights the issue that the optimization of NWT geometry could reduce the impact of the main sources of statistical variability on the Figure of Merit (FoM) of devices. In the context of industrial early successes in fabricating vertically stacked NWT, ensemble Monte Carlo (MC) simulations with quantum correction are used to accurately predict the drive current. This occurs alongside a consideration of the degree to which the carrier transport in the vertically stacked lateral NWTs are complex

Correlation Between Student Collaboration Network Centrality and Academic Performance

We compute nodal centrality measures on the collaboration networks of students enrolled in three upper-division physics courses, usually taken sequentially, at the Colorado School of Mines. These are complex networks in which links between students indicate assistance with homework. The courses included in the study are intermediate Classical Mechanics, introductory Quantum Mechanics, and intermediate Electromagnetism. By correlating these nodal centrality measures with students' scores on homework and exams, we find four centrality measures that correlate significantly with students' homework scores in all three courses: in-strength, out-strength, closeness centrality, and harmonic centrality. These correlations suggest that students who not only collaborate often, but also collaborate significantly with many different people tend to achieve higher grades. Centrality measures between simultaneous collaboration networks (analytical vs. numerical homework collaboration) composed of the same students also correlate with each other, suggesting that students' collaboration strategies remain relatively stable when presented with homework assignments targeting different skills. Additionally, we correlate centrality measures between collaboration networks from different courses and find that the four centrality measures with the strongest relationship to students' homework scores are also the most stable measures across networks involving different courses. Correlations of centrality measures with exam scores were generally smaller than the correlations with homework scores, though this finding varied across courses.Comment: 10 pages, 4 figures, submitted to Phys. Rev. PE

Iterative Reweighted Algorithms for Sparse Signal Recovery with Temporally Correlated Source Vectors

Iterative reweighted algorithms, as a class of algorithms for sparse signal recovery, have been found to have better performance than their non-reweighted counterparts. However, for solving the problem of multiple measurement vectors (MMVs), all the existing reweighted algorithms do not account for temporal correlation among source vectors and thus their performance degrades significantly in the presence of correlation. In this work we propose an iterative reweighted sparse Bayesian learning (SBL) algorithm exploiting the temporal correlation, and motivated by it, we propose a strategy to improve existing reweighted $\ell_2$ algorithms for the MMV problem, i.e. replacing their row norms with Mahalanobis distance measure. Simulations show that the proposed reweighted SBL algorithm has superior performance, and the proposed improvement strategy is effective for existing reweighted $\ell_2$ algorithms.Comment: Accepted by ICASSP 201

INTRINSIC AND EXTRINSIC MOTIVATION - AN INVESTIGATION OF PERFORMANCE CORRELATION

A series of research untaken in the last decade have revealed some interesting aspects regarding the effects of different types of motivation on performance. Among the researchers who have shown interest in this field we can number: Richard Ryan, Edward Deci, Sam Glucksberg, Dan Ariely, Robert Eisenhower, Linda Shanock, analysts from London School of Economics, and others. Their findings suggest that extrinsic incentives may have a negative impact on overall performance, but a general agreement in this respect has not been reached. In this paper we intend to shed some light upon the relationship between intrinsic and extrinsic motivation and performance. Experts define intrinsic motivation as being the execution of a task or activity because of the inherent satisfaction arising from it rather than due to some separate outcome. In contrast with intrinsic motivation, we speak of extrinsic motivation whenever an activity is done in order to attain some separable outcome. With the purpose of contributing to the clarification of the links between concepts, we initiated and conducted an explanatory research. The research is based on the analysis of the relations between the results obtained by third year students and their predominant type of motivation. For this, we formulated and tested four work hypotheses using a combination of quantitative methods (investigation) and qualitative methods (focus group). After the validation of the questionnaires, the respondents were divided into four categories: intrinsically motivated, extrinsically motivated, both intrinsically and extrinsically motivated and unmotivated. To analyze the collected data, we made use of Excel and SPSS. Some of the primary conclusions of the research are as follows: as the average increases, the percent of individuals having both extrinsic and intrinsic motivation is decreasing; the highest percentage of unmotivated students is concentrated in the highest average category; Female students tend to have better performance at university level. The research intends to be nearly a first step in the attempt to clarify the relationship between intrinsic (and extrinsic) motivation and performance. Further research is needed.intrinsic motivation, extrinsic motivation, performance, correlation

A Correlation-Based Fingerprint Verification System

In this paper, a correlation-based fingerprint verification system is presented. Unlike the traditional minutiae-based systems, this system directly uses the richer gray-scale information of the fingerprints. The correlation-based fingerprint verification system first selects appropriate templates in the primary fingerprint, uses template matching to locate them in the secondary print, and compares the template positions of both fingerprints. Unlike minutiae-based systems, the correlation-based fingerprint verification system is capable of dealing with bad-quality images from which no minutiae can be extracted reliably and with fingerprints that suffer from non-uniform shape distortions. Experiments have shown that the performance of this system at the moment is comparable to the performance of many other fingerprint verification systems

Performance of internal Covariance Estimators for Cosmic Shear Correlation Functions

Data re-sampling methods such as the delete-one jackknife are a common tool for estimating the covariance of large scale structure probes. In this paper we investigate the concepts of internal covariance estimation in the context of cosmic shear two-point statistics. We demonstrate how to use log-normal simulations of the convergence field and the corresponding shear field to carry out realistic tests of internal covariance estimators and find that most estimators such as jackknife or sub-sample covariance can reach a satisfactory compromise between bias and variance of the estimated covariance. In a forecast for the complete, 5-year DES survey we show that internally estimated covariance matrices can provide a large fraction of the true uncertainties on cosmological parameters in a 2D cosmic shear analysis. The volume inside contours of constant likelihood in the $\Omega_m$-$\sigma_8$ plane as measured with internally estimated covariance matrices is on average $\gtrsim 85\%$ of the volume derived from the true covariance matrix. The uncertainty on the parameter combination $\Sigma_8 \sim \sigma_8 \Omega_m^{0.5}$ derived from internally estimated covariances is $\sim 90\%$ of the true uncertainty.Comment: submitted to mnra