Event by Event Analysis of High Multiplicity Events Produced in 158 A GeV/c 208 Pb- 208 Pb Collisions

An extensive analysis of individual high multiplicity events produced in 158 A GeV /c 208Pb- 208Pb collisions is carried by adopting different methods to examine the anomalous behavior of these rare events. A method of selecting the events with densely populated narrow regions or spikes out of a given sample of collision events is discussed.Employing this approach two events with large spikes in their eta- and phi- distributions are selected for further analysis. For the sake of comparison, another two events which do not exhibit such spikes are simultaneously analyzed. The findings suggest that the systematic studies of particle density fluctuations in one- and two-dimensional phase-spaces and comparison with those obtained from the studies of correlation free Monte Carlo events, would be useful for identifying the events with large dynamical fluctuations. Formation of clusters or jet like phenomena in multihadronic final states in individual events is also discussed and the experimental findings are compared with the independent particle emission hypothesis by carrying out Monte Carlo simulations

Modelling and control of a wheelchair on two wheels

Wheelchairs on two wheels are needed for disabled persons to perform some of the essential tasks in their living and work environments. In fact it offers great advantages and efficiency for the user. Besides allowing a disabled to lead independent life, it is expected not to take much space during mobility as compared to when it is on four wheels and thus a wheelchair on two wheels has associated design and development challenges. These include modelling and controller design for the system to perform comparably similar to normal four-wheeled wheelchair. In this paper physical model of a wheelchair on two wheels that mimics double inverted pendulum is designed and a novel fuzzy logic control mechanism is developed and tested with control of the two-wheeled wheelchair

Forward and backward motion control of wheelchair on two wheels

The challenge in designing wheelchair on two wheels involves the design and implementation of suitable control strategies for a two wheeled wheelchair to perform comparably similar to a normal four wheeled wheelchair. It is important to note that a wheelchair on two wheels is expected not to take much space during mobility as compared to when it is on four wheels. Moreover, disabled people are encouraged and expected to perform most activities that others can do and hence lead an independent life. Thus, wheelchairs on two wheels are needed for disabled persons to perform some of the essential tasks in their living and work environments. In this research a model of the standard wheelchair is developed as a test and verification platform using Visual Nastran software. Novel fuzzy logic control strategies are designed for lifting up the chair transforming a four-wheeled wheelchair to a two-wheeled wheelchair) and maintaining stability and balance while on two wheels. Furthermore, position control for forward and backward mobility of the wheelchair on two wheels is developed using fuzzy logic control. Simulation results of the proposed control strategy are presented and discussed

Error Estimation of Numerical Integration Methods

We compare the accuracy of numerical integral methods like Newton-Cotes method and Gaussian Quadrature Rule (GQR) for the model problem and tested for another problem to verify the results. From results we notice that error of GQR is about 10 times less than Newton-Cotes formulas. For this reason we prefer GQR over other methods. But GQR uses nodes and weights which is a tedious work. This difficulty can overcome by using the idea of  ”three-term recurrence” relation. We can transform the problem of finding the nodes and weights for GQR to one of finding eigenvalues and eigenvectors of a symmetric tridiagonal matrix. Keywords: Numerical integration; Gaussian Quadrature rules; error estimate; convergence rate

Spectral Efficiency Maximization of a Single Cell Massive MU-MIMO Down-Link TDD System by Appropriate Resource Allocation

This paper deals with the problem of maximizing the spectral efficiency in a massive multi-user MIMO downlink system, where a base station is equipped with a very large number of antennas and serves single-antenna users simultaneously in the same frequency band, and the beamforming training scheme is employed in the time-division duplex mode. An optimal resource allocation that jointly selects the training duration on uplink transmission, the training signal power on downlink transmission, the training signal power on uplink transmission, and the data signal power on downlink transmission is proposed in such a way that the spectral efficiency is maximized given the total energy budget. Since the spectral efficiency is the main concern of this work, and its calculation using the lower bound on the achievable rate is computationally very intensive, in this paper, we also derive approximate expressions for the lower bound of achievable downlink rate for the maximum ratio transmission (MRT) and zero-forcing (ZF) precoders. The computational simplicity and accuracy of the approximate expressions for the lower bound of achievable downlink rate are validated through simulations. By employing these approximate expressions, experiments are conducted to obtain the spectral efficiency of the massive MIMO downlink time-division duplexing system with the optimal resource allocation and that of the beamforming training scheme. It is shown that the spectral efficiency of the former system using the optimal resource allocation is superior to that yielded by the latter scheme in the cases of both MRT and ZF precoders

A PLS-SEM Neural Network Approach for Understanding Cryptocurrency Adoption

© 2013 IEEE. The majority of previous research on new technology acceptance has been conducted with single-step Structural Equation Modeling (SEM) based methods. The primary purpose of the study is to enhance the new technology acceptance based research with the Artificial Neural Network (ANN) method to enable more precise and in-depth research results as compared to the single-step SEM method. This study measures the relation between technology readiness dimension (optimism, innovativeness, discomfort, insecurity) and the technology acceptance (perceived ease of use and perceived usefulness) - and the intention to use cryptocurrency, such as bitcoin. The contribution of this study include the use of a multi-analytical approach by combining Partial Least Squares- Structural Equation Modeling (PLS-SEM) and Artificial Neural Network (ANN) analysis. First, PLS-SEM was applied to assess which factor has significant influence toward intention to use cryptocurrency. Second, an ANN was employed to rank the relative influence of the significant predictor variables attained from the PLS-SEM. The findings of the two-step PLS-SEM and ANN approach confirm that the use of ANN further verifies the results obtained by the PLS-SEM analysis. Also, ANN is capable of modelling complex linear and non-linear relationships with high predictive accuracy compared to SEM methods. Also, an Importance-Performance Map Analysis (IPMA) of the PLS-SEM results provides a more specific understanding of each factor's importance-performance