Abstract
In this letter, a strain sensor with high sensitivity enhancement using a special case of Vernier effect is presented. The sensor configuration is composed of two-fiber loop mirrors in a cascaded configuration with opposite strain responses when individually characterized. Thus, the enhanced Vernier effect is explored, which is the most sensitive of three possible cases Vernier effect. Here, the Vernier response depends on the difference between the sensitivities of each Hi-Bi optical fiber. In addition to this, the fundamental and the first harmonic were also explored. The results obtained are a strain sensitivity of (13.3 +/- 0.3) pm/mu epsilon for the carrier, (80.0 +/- 0.3) pm/mu epsilon or the Vernier envelope of the fundamental case and (120 +/- 1) pm/mu epsilon for the Vernier envelope of the first harmonic. The first harmonic could achieve a magnification factor of 8. Considering that the optical interrogation system allows a minimum resolution of 0.02 nm, the minimum measurement step achievable is 0.2 mu epsilon. This work proves the possibility of applying the concept of enhanced Vernier effect to fiber loop mirrors, obtaining higher sensitivity than a standard fiber loop mirror alone. Besides, the sensitivity can be increased through the usage of harmonics of the Vernier effect. Moreover, the use of large interferometers allows a better discretization of the envelope, which implies a greater ease of analysis.

Abstract
This paper compares the non-dominated sorting genetic algorithm (NSGA-II) and NSGA-III to solve multiobjective sectorization problems (MO-SPs). We focus on the effects of the parameters of the algorithms on their performance and we use statistical experimental design to find more effective parameters. For this purpose, the analysis of variance (ANOVA), Taguchi design and response surface method (RSM) are used. The criterion of the comparison is the number of obtained nondominated solutions by the algorithms. The aim of the problem is to divide a region that contains distribution centres (DCs) and customers into smaller and balanced regions in terms of demands and distances, for which we generate benchmarks. The results show that the performance of algorithms improves with appropriate parameter definition. With the parameters defined based on the experiments, NSGA-III outperforms NSGA-II. © 2020 IEEE.

Abstract
Various companies choose to outsource the delivery of part of their services, so as not to deviate from its core business and improve the service level. This approach leads to a new type of organizations, so-called networked and virtual enterprises, where possibly a great number of companies work together without having direct contact but through a broker, as an intermediary, that streamlines the relationships between them. To enable high level efficiency, as well as some other functional requirements, the meta-organizations and brokering services are conceived as environments and services for networked and virtual enterprises operation and dynamic reconfigurations, representing a model of organizations-of-organizations, as an implementation of one of the Industry 4.0 models and ecosystem for networked and virtual enterprises dynamic reconfiguration. In this paper, the meta-organizations with embedded brokering services, modelled as call centres, are analyzed. Various simulations are presented, based on Erlangs formulas for some of design and performance measures parameters evaluation, such as service level, average waiting time, agent occupancy and service traffic intensity.

Abstract

Abstract
Context. Clouds are ubiquitous in exoplanet atmospheres and they represent a challenge for the model interpretation of their spectra. When generating a large number of model spectra, complex cloud models often prove too costly numerically, whereas more efficient models may be overly simplified. Aims. We aim to constrain the atmospheric properties of the directly imaged planet HR 8799e with a free retrieval approach. Methods. We used our radiative transfer code petitRADTRANS for generating the spectra, which we coupled to the PyMultiNest tool. We added the effect of multiple scattering which is important for treating clouds. Two cloud model parameterizations are tested: the first incorporates the mixing and settling of condensates, the second simply parameterizes the functional form of the opacity. Results. In mock retrievals, using an inadequate cloud model may result in atmospheres that are more isothermal and less cloudy than the input. Applying our framework on observations of HR 8799e made with the GPI, SPHERE, and GRAVITY, we find a cloudy atmosphere governed by disequilibrium chemistry, confirming previous analyses. We retrieve that C/O = 0.60(-0.08)(+0.07). Other models have not yet produced a well constrained C/O value for this planet. The retrieved C/O values of both cloud models are consistent, while leading to different atmospheric structures: either cloudy or more isothermal and less cloudy. Fitting the observations with the self-consistent Exo-REM model leads to comparable results, without constraining C/O. Conclusions. With data from the most sensitive instruments, retrieval analyses of directly imaged planets are possible. The inferred C/O ratio of HR 8799e is independent of the cloud model and thus appears to be a robust. This C/O is consistent with stellar, which could indicate that the HR 8799e formed outside the CO2 or CO iceline. As it is the innermost planet of the system, this constraint could apply to all HR 8799 planets.

Abstract
Despite the growing popularity of 802.11 wireless networks, users often suffer from connectivity problems and performance issues due to unstable radio conditions and dynamic user behavior, among other reasons. Anomaly detection and distinction are in the thick of major challenges that network managers encounter. The difficulty of monitoring broad and complex Wireless Local Area Networks, that often requires heavy instrumentation of the user devices, makes anomaly detection analysis even harder. In this paper we exploit 802.11 access point usage data and propose an anomaly detection technique based on Hidden Markov Model (HMM) and Universal Background Model (UBM) on data that is inexpensive to obtain. We then generate a number of network anomalous scenarios in OMNeT++/INET network simulator and compare the detection outcomes with those in baseline approaches-RawData and Principal Component Analysis. The experimental results show the superiority of HMM and HMM-UBM models in detection precision and sensitivity.