Until very recently, handheld spectrometers were the domain of major analytical and security instrument companies, with turnkey analyzers using spectroscopic techniques from X-ray fluorescence (XRF) for elemental analysis (metals), to Raman, mid-infrared, and near-infrared (NIR) for molecular analysis (mostly organics). However, the past few years have seen rapid changes in this landscape with the introduction of handheld laser-induced breakdown spectroscopy (LIBS), smartphone spectroscopy focusing on medical diagnostics for low-resource areas, commercial engines that a variety of companies can build up into products, hyphenated or dual technology instruments, low-cost visible-shortwave NIR instruments selling directly to the public, and, most recently, portable hyperspectral imaging instruments. Successful handheld instruments are designed to give answers to non-scientist operators; therefore, their developers have put extensive resources into reliable identification algorithms, spectroscopic libraries or databases, and qualitative and quantitative calibrations. As spectroscopic instruments become smaller and lower cost, “engines” have emerged, leading to the possibility of being incorporated in consumer devices and smart appliances, part of the Internet of Things (IOT). This review outlines the technologies used in portable spectroscopy, discusses their applications, both qualitative and quantitative, and how instrument developers and vendors have approached giving actionable answers to non-scientists. It outlines concerns on crowdsourced data, especially for heterogeneous samples, and finally looks towards the future in areas like IOT, emerging technologies for instruments, and portable hyphenated and hyperspectral instruments.

https://journals.sagepub.com/doi/pdf/10.1177/0003702818809719

EXPRESS: Portable Spectroscopy:

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Statistical Methods for the Analysis of Repeated Measurements.Charles S Davis. Heidelberg: Springer Verlag, 2002, pp. 415, £59.50 (HB) ISBN: 0-387-95370-1.

講座 highway capacity manual 2000(3)2車線道路と多車線道路

This paper introduces a Genetic Algorithm (GA) based optimization for rule base and scaling factors adjustment to enhance the performance of fuzzy logic controllers. First a recursive rule base adjustment algorithm is developed, which has the benefit that it is computationally more efficient for the generation of a decision table. Then utilizing the advantage of GA optimization, a novel approach that each random combination of the optimized parameters (including the membership function selection for the rule base and controller scaling factors) is coded into a Real Coded string and treated as a chromosome in genetic algorithms is given. The optimization for rule base with the correspondent membership function and scaling factors using GA is easy to be realization in engineering. Simulation results are presented to support this thesis.

Computational Intelligence

Spatial evolution game has traditionally assumed that players interact with neighbors on a single network, which is isolated and not influenced by other systems. We introduce the simple game model into the interdependent networks composed of two networks, and show that when the interdependent factor $\alpha$ is smaller than a particular value $\alpha_C$, homogeneous cooperation can be guaranteed. However, as interdependent factor exceeds $\alpha_C$, spontaneous symmetry breaking of fraction of cooperators presents itself between different networks. In addition, our results can be well predicted by the strategy-couple pair approximation method.

Spontaneous Symmetry Breaking in Interdependent Networked Game

Exact wave solutions of the fourth order non-linear partial differential equation of optical fiber pulses by using different methods

Solitons in birefringent fibers for CGL equation with Hamiltonian perturbations and Kerr law nonlinearity using modified extended direct algebraic method

This paper investigates the application of two time series forecasting techniques, namely logistic regression and univariate auto regressive integrated moving average (ARIM A), to predict daily traffic volume for the Egyptian intercity roads. The data of three permanent traffic volume stations was selected in this paper. A total of 14-year traffic data for the selected stations (from 1990 to 2003) were used in the development of the two models to predict traffic volume. All of the data sets were best represented by both logistic regression model and an autoregressive integrated moving - average (ARIM A) model. The data set containing average annual, average monthly and average weekly daily traffic volume for years 1990 through 2001 was used to fit a time series model. The resulting models were used to forecast traffic volumes for year 2002 and 2003. The forecasted traffic volumes for the two models were then compared with the actual traffic volumes. According to the analysis, the ARIMA model seems to be the best forecasting method especially for the average monthly and average weekly daily traffic volume.

Comparison Between Regression and Arima Models in Forecasting Traffic Volume

In this work, the improved modified extended tanh scheme is implemented to extract exact travelling wave solutions for perturbed nonlinear Schrodinger’s equation with Kudryashov’s law of refractive index and dual form of generalized nonlocal nonlinearity. Various types of solutions are extracted such as bright solitons, singular solitons, dark solitons, singular periodic wave solutions, periodic wave solutions, Jacobi elliptic functions, plane wave and hyperbolic wave solutions. Moreover, 3D and contour plots of some solutions are illustrated to show the physical nature of obtained solutions.

Optical soliton perturbation with Kudryashov’s generalized law of refractive index and generalized nonlocal laws by improved modified extended tanh method

Solar Energy is one of the key solutions to future electrical power generation. Photovoltaic Plants (PV) are fast growing to satisfy electrical power demand. Different maximum power point tracking techniques (MPPT) are used to maximize PV systems generated power. In this paper, on grid PV system model in MATLAB SIMULINK is tested under sudden irradiance and cell temperature variations. Incremental Conductance MPPT is used to maximize generated power from the PV system with the help of new adaptive controller to withstand these heavy disturbances. The new adaptive controller is tuned for optimal operation using two different optimization techniques (Invasive weed and Harmony search).Optimization results for the two techniques are compared. .A robustness test is made to check system stability to withstand different random irradiance and cell temperature patterns without failure to track the maximum power point.Finally, a brief comparison is made with a previous literature and the new adaptive controller gives better results.

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Niveen Badra

Papers

Exact wave solutions of the fourth order non-linear partial differential equation of optical fiber pulses by using different methods

Solitons in birefringent fibers for CGL equation with Hamiltonian perturbations and Kerr law nonlinearity using modified extended direct algebraic method

Comparison Between Regression and Arima Models in Forecasting Traffic Volume

Optical soliton perturbation with Kudryashov’s generalized law of refractive index and generalized nonlocal laws by improved modified extended tanh method

Enhancement of On-grid PV System under Irradiance and Temperature Variations Using New Optimized Adaptive Controller