Structural,electrical, and linear/nonlinear optical characteristics of thermally evaporated molybdenum oxide thin films

Homogeneous thin films of Molybdenum oxide (MoO₃) were grown on quartz and glass substrates using the thermal evaporation method. XRD results showed that the MoO₃ powder has a polycrystalline structure with an orthorhombic crystal system whereas the MoO₃ thin films have amorphous nature. SEM images showed that the MoO₃ thin films have a nearly uniform surfaces with worm-like shape grains. The film thickness influences on the linear and nonlinear optical characteristics of MoO₃ thin films that were examined using spectrophotometric measurements and from which, the linear optical constants of the MoO₃ thin films were estimated. The electronic transition type was determined as a direct allowed one. The values of the optical band gap were obtained to be in the range of 3.88–3.72 eV. The dispersion parameters, third-order nonlinear optical susceptibility, and the nonlinear refractive index of the MoO₃ thin films were determined and interpreted in the light of the single oscillator model. The temperature dependence of the DC electrical conductivity and the corresponding conduction mechanism for the MoO₃ films were investigated at temperatures ranging from 303 to 463 K.     

Various density light field image coding based on distortion minimization interpolation

In recent years, the light field (LF) as a new imaging modality has attracted wide interest. The large data volume of LF images poses great challenge to LF image coding, and the LF images captured by different devices show significant differences in angular domain. In this paper we propose a view prediction framework to handle LF image coding with various sampling density. All LF images are represented as view arrays. We first partition the views into reference view (RV) set and intermediate view (IV) set. The RVs are rearranged into a pseudo sequence and directly compressed by a video encoder. Other views are then predicted by the RVs. To exploit the four dimensional signal structure, we propose the linear approximation prior (LAP) to reveal the correlation among LF views and efficiently remove the LF data redundancy. Based on the LAP, a distortion minimization interpolation (DMI) method is used to predict IVs. To robustly handle the LF images with different sampling density, we propose an Iteratively Updating depth image based rendering (IU-DIBR) method to extend our DMI. Some auxiliary views are generated to cover the target region and then the DMI calculates reconstruction coefficients for the IVs. Different view partition patterns are also explored. Extensive experiments on different types LF images also valid the efficiency of the proposed method.     

Asynchronous control for two‐dimensional hidden Markovian jump systems with partly known mode observation conditional probabilities

This study focuses on the asynchronous control problem for two‐dimensional discrete‐time hidden Markovian jump systems where the mode observation conditional probability matrix is partly known. Considering the original system modes are invisible, the observed modes emitted from an observer serve as an alternative for stability analysis and controller design where a mode observation conditional probability matrix is constructed to characterize the emission between system modes and observed modes. Specially, only partly known information of the mode observation conditional probability matrix is accessible. With the introduction of the free‐connection weighting matrices, the asymptotic mean square stability criterion is firstly derived based on Lyapunov method. This introduction provides a further degree of relaxation and less conservatism is therefore achieved. Secondly, we present synthesis conditions for asynchronous state feedback controller design given in terms of a set of interconnected linear matrix inequalities. Moreover, cluster concept based on the partitions of observed modes is adopted which helps to decrease the number of controllers and simplify the design complexity. A numerical example, regarding the cases with and without clustering of the observed modes, is presented to illustrate the effectiveness of the proposed method.     

Stability and stabilization for singularly perturbed systems with Markovian jumps

This article focuses on the stability and stabilization problems of singularly perturbed jump systems. Here, the singularly perturbed parameter (SPP) is also with Markov switching and satisfies any with positive bound predefined. First, stability conditions expressed ?_i‐free but involving its bound are developed by constructing an ?_i‐dependent Lyapunov function. Then, a method for state feedback stabilization controller depending on SPP is proposed, whose conditions are given in terms of linear matrix inequalities. Moreover, some special cases about deterministic SPP are considered too. Finally, two practical examples are used to demonstrate the effectiveness and superiorities of the proposed methods.     

Evolution of linear edge dislocation in atmospheric turbulence and free space

In accordance with the extended Huygens–Fresnel principle, the evolution of linear edge dislocation propagating through atmospheric turbulence is studied, and the effects of waist width and the slope of linear edge dislocation are investigated. It is shown that when linear edge dislocation beams propagate through atmospheric turbulence, if the waist width is not equal and the slope is not zero, then the linear edge dislocation vanishes and transforms into an optical vortex with a topological charge of ?1 or +1. The optical vortex and an optical vortex that is created annihilate when the transmission distance is far enough. The linear edge dislocation vanishes when the slope is zero. If the waist width is equal, then the linear edge dislocation will vanish regardless of the slope value. For linear edge dislocation beams in free space, when selecting specific parameters, linear edge dislocation always exists.     

Transverse magnetoresistance peculiarities of thermoelectric Lu-doped Bi2Te3 compound due to strong electrical disorder

The n-type thermoelectric Bi_1.9Lu_0.1Te₃ was prepared by microwave-solvothermal method and spark plasma sintering. The magnetic field and temperature dependences of transverse magnetoresistance measured within temperature 2–200 K interval allow finding the peculiarities characteristic for strongly disordered and inhomogeneous semiconductors. The first peculiarity is due to appearance of linear-in-magnetic field contribution to the total magnetoresistance reflected in a crossover from quadratic magnetoresistance at low magnetic fields to linear magnetoresistance at high magnetic fields. The linear magnetoresistance can result from the Hall resistance picked up from macroscopically distorted current paths due to local variations in stoichiometry of the compound studied. The second peculiarity is that both linear magnetoresistance magnitude and crossover field are functions of carrier mobility which is in agreement with the Parish and Littlewood model developed for disordered and inhomogeneous semiconductors. An increase in the mobility due to a decrease in temperature is accompanied by an increase in the magnetoresistance magnitude and a decrease in the crossover field. Finally, the third peculiarity is related to the remarkable deviation of the total magnetoresistance measured at various temperatures from the Kohler's rule. Presence of strong inhomogeneity and disorder in the Bi_1.9Lu_0.1Te₃ structure concluded from the magnetoresistance peculiarities can be responsible for the remarkable reduction in the total thermal conductivity of this compound.     

Prediction of mode I fracture toughness of rock using linear multiple regression and gene expression programming

Prediction of mode I fracture toughness (K_IC) of rock is of significant importance in rock engineering analyses. In this study, linear multiple regression (LMR) and gene expression programming (GEP) methods were used to provide a reliable relationship to determine mode I fracture toughness of rock. The presented model was developed based on 60 datasets taken from the previous literature. To predict fracture parameters, three mechanical parameters of rock mass including uniaxial compressive strength (UCS), Brazilian tensile strength (BTS), and elastic modulus (E) have been selected as the input parameters. A cluster of data was collected and divided into two random groups of training and testing datasets. Then, different statistical linear and artificial intelligence based nonlinear analyses were conducted on the training data to provide a reliable prediction model of K_IC. These two predictive methods were then evaluated based on the testing data. To evaluate the efficiency of the proposed models for predicting the mode I fracture toughness of rock, various statistical indices including coefficient of determination (R²), root mean square error (RMSE), and mean absolute error (MAE) were utilized herein. In the case of testing datasets, the values of R², RMSE, and MAE for the GEP model were 0.87, 0.188, and 0.156, respectively, while they were 0.74, 0.473, and 0.223, respectively, for the LMR model. The results indicated that the selected GEP model delivered superior performance with a higher R² value and lower errors.     

Ecological Planting Imperative: Functional Systems,Not Stylized Ecologies

The ability of landscape architectural projects to mitigate the worst effects of climate change will depend upon designed ecological systems. These systems will be built with plants. Despite the recognition of ecology as an essential driver of landscapes, the professionals of landscape architecture too often lack the knowledge and practical skills to create robust vegetative systems. New approaches and tools are required. This article outlines principles and methods for designing biodiverse plant systems for urban sites. Planting methods that increase species richness, functional diversity, and spatial complexity are emphasized as a way of developing more resilient plantings. Selecting species with similar evolutionary adaptions to stress, disturbance, and competition—as well as creating multi-layered compositions of diverse plant morphologies—allows designers to create compatible, long-lived plant mixes. To balance the increased visual complexity of diverse plant mixes, the article explores design techniques to make plantings more appealing to the public. The strategies explored here are based on the projects, experience, and research of Phyto Studio, a Washington, D.C. based studio. The methods build on work described in the author’s book, Planting in a Post-Wild World, an exploration of how to create designed plant communities.     

Application of full order sliding mode control based on different areas power system with load frequency control

In the traditional sliding mode control method, there always exist the singularity due to the reduced order of the control method. In order to eliminate the singularity, I propose a new full order sliding mode control method in this article, which has been firstly applied to load frequency control. The full order sliding mode control method includes the terminal sliding mode control (TSM) and the linear sliding mode control (LSM). TSM has the good characteristic of eliminating the singularity due to the avoidance of derivative of terms with fractional power factors. While the LSM is easy to design and has fast time convergence comparing to TSM. The model is based on the system with different kinds of turbine or the same kind of turbine, which contains the nonlinearities. The control purpose is to adjust the frequency deviation to zero. Through the simulation results, it is shown that the frequency deviation can be kept to zero in the condition of different load disturbances by the two approaches, which approves the robustness of the proposed methods. In addition, we compare the two methods with the traditional sliding mode control (SMC), which proves the superiority of the two methods in terms of chattering and response time.