Local simulation of singlet statistics for restricted set of measurement

The essence of Bell's theorem is that, in general, quantum statistics cannot be reproduced by local hidden variable (LHV) model. This impossibility is strongly manifested while analyzing the singlet state statistics for Bell-CHSH violations. In this work, we provide various subsets of two outcome POVMs for which a local hidden variable model can be constructed for singlet state.Comment: 2 column, 5 pages, 4 figures, new references, abstract modified, accepted in JP

Observation and analysis of Fano-like lineshapes in the Raman spectra of molecules adsorbed at metal interfaces

Surface enhanced Raman spectra from molecules (bipyridyl ethylene) adsorbed on gold dumbells are observed to become increasingly asymmetric (Fano-like) at higher incident light intensity. The electronic temperature (inferred from the anti-Stokes (AS) electronic Raman signal increases at the same time while no vibrational AS scattering is seen. These observations are analyzed by assuming that the molecule-metal coupling contains an intensity dependent contribution (resulting from light-induced charge transfer transitions as well as renormalization of the molecule metal tunneling barrier). We find that interference between vibrational and electronic inelastic scattering routes is possible in the presence of strong enough electron-vibrational coupling and can in principle lead to the observed Fano-like feature in the Raman scattering profile. However the best fit to the observed results, including the dependence on incident light intensity and the associated thermal response is obtained from a model that disregards this coupling and accounts for the structure of the continuous electronic component of the Raman scattering signal. The temperatures inferred from the Raman signal are argued to be only of qualitative value.Comment: 20 pages, 12 figure

Implementing Man-in-the-Middle Attack to Investigate Network Vulnerabilities in Smart Grid Test-bed

The smart-grid introduces several new data-gathering, communication, and information-sharing capabilities into the electrical system, as well as additional privacy threats, vulnerabilities, and cyber-attacks. In this study, Modbus is regarded as one of the most prevalent interfaces for control systems in power plants. Modern control interfaces are vulnerable to cyber-attacks, posing a risk to the entire energy infrastructure. In order to strengthen resistance to cyber-attacks, this study introduces a test bed for cyber-physical systems that operate in real-time. To investigate the network vulnerabilities of smart power grids, Modbus protocol has been examined combining a real-time power system simulator with a communication system simulator and the effects of the system presented and analyzed. The goal is to detect the vulnerability in Modbus protocol and perform the Man-in-the-middle attack with its impact on the system. This proposed testbed can be evaluated as a research model for vulnerability assessment as well as a tool for evaluating cyber-attacks and enquire into any detection mechanism for safeguarding and defending smart grid systems from a variety of cyberattacks. We present here the preliminary findings on using the testbed to identify a particular MiTM attack and the effects on system performance. Finally, we suggest a cyber security strategy as a solution to address such network vulnerabilities and deploy appropriate countermeasures.Comment: 7 pages, 10 figures, Conference paper, Accepted in publication for 2023 IEEE World AI IoT Congress (AIIoT

On Some Discrete Distributions and their Applications with Real Life Data

This article reviews some useful discrete models and compares their performance in terms of the high frequency of zeroes, which is observed in many discrete data (e.g., motor crash, earthquake, strike data, etc.). A simulation study is conducted to determine how commonly used discrete models (such as the binomial, Poisson, negative binomial, zero-inflated and zero-truncated models) behave if excess zeroes are present in the data. Results indicate that the negative binomial model and the ZIP model are better able to capture the effect of excess zeroes. Some real-life environmental data are used to illustrate the performance of the proposed models

Some Ridge Regression Estimators and Their Performances

The estimation of ridge parameter is an important problem in the ridge regression method, which is widely used to solve multicollinearity problem. A comprehensive study on 28 different available estimators and five proposed ridge estimators, KB1, KB2, KB3, KB4, and KB5, is provided. A simulation study was conducted and selected estimators were compared. Some of selected ridge estimators performed well compared to the ordinary least square (OLS) estimator and some existing popular ridge estimators. One of the proposed estimators, KB3, performed the best. Numerical examples were given

A Simulation Study on the Size and Power Properties of Some Ridge Regression Tests

Ridge regression techniques have been extensively used to solve the multicollinearity problem for both linear and non-linear regression models since its inception. This paper studied different ridge regression t-type tests of the individual coefficients of a linear regression model. A simulation study has been conducted to evaluate the performance of the proposed tests with respect to their sizes and powers under different settings of the linear regression model. Our simulation results demonstrated that most of the proposed tests have sizes close to the 5% nominal level and all tests except tAKS, tkM2 and tkM9 have considerable gain in powers over the ordinary OLS t-type test. It is also observed that some of the proposed test statistics are performing better than the HK and HKB tests which are proposed some authors

Testing the Population Coefficient of Variation

The coefficient of variation (CV), which is used in many scientific areas, measures the variability of a population relative to its mean and standard deviation. Several methods exist for testing the population CV. This article compares a proposed bootstrap method to existing methods. A simulation study was conducted under both symmetric and skewed distributions to compare the performance of test statistics with respect to empirical size and power. Results indicate that some of the proposed methods are useful and can be recommended to practitioners

Neural Networks for Template Matching: Application to Real-Time Classification of the Action Potentials of Real Neurons

Much experimental study of real neural networks relies on the proper classification of extracellulary sampled neural signals (i .e. action potentials) recorded from the brains of experimental animals. In most neurophysiology laboratories this classification task is simplified by limiting investigations to single, electrically well-isolated neurons recorded one at a time. However, for those interested in sampling the activities of many single neurons simultaneously, waveform classification becomes a serious concern. In this paper we describe and constrast three approaches to this problem each designed not only to recognize isolated neural events, but also to separately classify temporally overlapping events in real time. First we present two formulations of waveform classification using a neural network template matching approach. These two formulations are then compared to a simple template matching implementation. Analysis with real neural signals reveals that simple template matching is a better solution to this problem than either neural network approach