Super-resolved localisation in multipath environments

In the last few decades, the localisation problems have been studied extensively. There are still some open issues that remain unresolved. One of the key issues is the efficiency and preciseness of the localisation in presence of non-line-of-sight (NLoS) path. Nevertheless, the NLoS path has a high occurrence in multipath environments, but NLoS bias is viewed as a main factor to severely degrade the localisation performance. The NLoS bias would often result in extra propagation delay and angular bias. Numerous localisation methods have been proposed to deal with NLoS bias in various propagation environments, but they are tailored to some specif ic scenarios due to different prior knowledge requirements, accuracies, computational complexities, and assumptions. To super-resolve the location of mobile device (MD) without prior knowledge, we address the localisation problem by super-resolution technique due to its favourable features, such as working on continuous parameter space, reducing computational cost and good extensibility. Besides the NLoS bias, we consider an extra array directional error which implies the deviation in the orientation of the array placement. The proposed method is able to estimate the locations of MDs and self-calibrate the array directional errors simultaneously. To achieve joint localisation, we directly map MD locations and array directional error to received signals. Then the group sparsity based optimisation is proposed to exploit the geometric consistency that received paths are originating from common MDs. Note that the super-resolution framework cannot be directly applied to our localisation problems. Because the proposed objective function cannot be efficiently solved by semi-definite programming. Typical strategies focus on reducing adverse effect due to the NLoS bias by separating line-of-sight (LoS)/NLoS path or mitigating NLoS effect. The LoS path is well studied for localisation and multiple methods have been proposed in the literature. However, the number of LoS paths are typically limited and the effect of NLoS bias may not always be reduced completely. As a long-standing issue, the suitable solution of using NLoS path is still an open topic for research. Instead of dealing with NLoS bias, we present a novel localisation method that exploits both LoS and NLoS paths in the same manner. The unique feature is avoiding hard decisions on separating LoS and NLoS paths and hence relevant possible error. A grid-free sparse inverse problem is formulated for localisation which avoids error propagation between multiple stages, handles multipath in a unified way, and guarantees a global convergence. Extensive localisation experiments on different propagation environments and localisation systems are presented to illustrate the high performance of the proposed algorithm compared with theoretical analysis. In one of the case studies, single antenna access points (APs) can locate a single antenna MD even when all paths between them are NLoS, which according to the authors’ knowledge is the first time in the literature.Open Acces

Managerial Response to Hotel Guests’ Review in Bangkok

The service industry is hard to measure due to its characteristics which are perishability, intangibility, inseparability and variability so the service industry like the tourism industry highly relies on the guests’ WOM. This research is aiming to help hotel managers in Bangkok investigate what makes a good response. Since the research is limited to the hotel industry in Bangkok. It is a remarkable way to conduct interviews with managers and tourists to gather data with a qualitative approach. The researcher conducted in-depth interviews with three managers and three tourists to collect data. Due to Covid-19 pandemic regulation, numbers of interviewees are limited; also, some interviews were conducted online by Zoom and Microsoft team. The researcher analyzed data by the classic content analysis technique. The key findings of the research are: first, the speedy managerial response has a positive impact on guests’ opinion; next, response numbers have a positive effect on guests’ WOM; then the manager should concentrate on both positive and negative responses; finally, relevant managerial response affects guest’ points of view. Based on researcher’s findings, managers should be empathy when response to guests’ reviews. Putting them in the guests’ shoes will make it easier to understand what problem guests have faced

A New Family of Iterative Methods Based on an Exponential Model for Solving Nonlinear Equations

We present two new families of iterative methods for obtaining simple roots of nonlinear equations. The first family is developed by fitting the model m(x)=epx(Ax2+Bx+C) to the function f(x) and its derivative f′(x), f″(x) at a point xn. In order to remove the second derivative of the first methods, we construct the second family of iterative methods by approximating the equation f(x)=0 around the point (xn,f(xn)) by the quadratic equation. Analysis of convergence shows that the new methods have third-order or higher convergence. Numerical experiments show that new iterative methods are effective and comparable to those of the well-known existing methods

Some New Variants of Cauchy's Methods for Solving Nonlinear Equations

We present and analyze some variants of Cauchy's methods free from second derivative for obtaining simple roots of nonlinear equations. The convergence analysis of the methods is discussed. It is established that the methods have convergence order three. Per iteration the new methods require two function and one first derivative evaluations. Numerical examples show that the new methods are comparable with the well-known existing methods and give better numerical results in many aspects

Traveling Waves in the Underdamped Frenkel–Kontorova Model

This paper studies a damped Frenkel–Kontorova model with periodic boundary condition. By using Nash–Moser iteration scheme, we prove that such model has a family of smooth traveling wave solutions

A Simulation Study of Carrier Capture Ability of the Last InGaN Quantum Well with Different Indium Content for Yellow-Light-Emitting InGaN/GaN Multiple Quantum Wells

Currently, GaN-based blue- and green-light-emitting devices have achieved successful applications in practice, while the luminescence efficiency of devices with longer wavelengths (such as yellow light) is still very low. Therefore, in this paper, the electroluminescence characterization of yellow-light-emitting InGaN/GaN multiple quantum wells (MQWs) with different In content in the last InGaN quantum well, which is next to the p-type GaN electrode layer, are investigated numerically to reveal a possible physical mechanism by which the different distribution of In content in the active region impacts the carrier capture and the light emission process in yellow InGaN/GaN MQWs. The simulation results show that at low injection currents, the luminescence efficiency of high-In-content yellow MQWs is enhanced, which can be ascribed to the enhanced radiative recombination process induced by the increased carrier concentration in the last InGaN quantum wells with promoted carrier capture ability. However, in the case of high injection condition, the luminescence efficiency of yellow MQWs deteriorates with increasing In content, i.e., the droop effect becomes remarkable. This can be ascribed to both significantly enhanced Auger recombination and electron leakage in the last InGaN quantum well, induced also by the promoted capture ability of charge carriers

A New Method Based on Two-Stage Detection Mechanism for Detecting Ships in High-Resolution SAR Images

Ship detection in synthetic aperture radar (SAR) remote sensing images, being a fundamental but challenging problem in the field of satellite image analysis, plays an important role for a wide range of applications and is receiving significant attention in recent years. Aiming at the requirements of ship detection in high-resolution SAR images, the accuracy, the intelligent level, a better real-time operation and processing efficiency, The characteristics of ocean background and ship target in high-resolution SAR images were analyzed, we put forward a ship detection algorithm in high-resolution SAR images. The algorithm consists of two detection stages: The first step designs a pre-training classifier based on improved spectral residual visual model to obtain the visual salient regions containing ship targets quickly, then achieve the purpose of probably detection of ships. In the second stage, considering the Bayesian theory of binary hypothesis detection, a local maximum posterior probability (MAP) classifier is designed for the classification of pixels. After the parameter estimation and judgment criterion, the classification of pixels are carried out in the target areas to achieve the classification of two types of pixels in the salient regions. In the paper, several types of satellite image data, such as TerraSAR-X (TS-X), Radarsat-2, are used to evaluate the performance of detection methods. Comparing with classical CFAR detection algorithms, experimental results show that the algorithm can achieve a better effect of suppressing false alarms, which caused by the speckle noise and ocean clutter background inhomogeneity. At the same time, the detection speed is increased by 25% to 45%