The main goal of introducing Active Suspension System in vehicles is to reduce the vehicle body motion under road obstacles which improves the ride comfort of the passenger. In this paper, the Full Car Model (FCM) with seven Degrees of Freedom is considered and simulated by MATLAB/Simulink. The Terminal Sliding Mode Controller (TSMC) and Fractional Order Terminal Sliding Mode Controller (FOTSMC) are designed to enhance the ride quality, stability and passenger comfort for FCM. The designed FOTSMC has the ability to provide higher control accuracy in a finite time. The performances of the designed controllers are evaluated by measuring the vehicle body vibration in both angular and vertical direction under bump input and ISO-8608 random input against passive suspension system. The FrequencyWeighted Root Mean Square (FWRMS) and Vibration dose value of Body Acceleration as per ISO-2631 are evaluated for FOTSMC, TSMC and PSS. The stability of the FCM is proved by Lyapunouv theory. Further analysis with sprung mass and speed variation of FCM demonstrate the robustness of proposed controller. To investigate the performances of designed controllers, comparison is made with existing Sliding Mode Controller (SMC) which proves that the designed FOTSMC performs better than existing SMC.

Intercultural encounters, among many values, serve as critical incidents that promote understanding, noticing and observing particular cultural as well as linguistic phenomena. Additionally, narrating intercultural encounters may activate the processes commonly associated with LA methodology, i.e.: description, exploration, languaging (understood as making meaning and shaping knowledge and experience through language use; Swain 2010), engagement and refl ection. The aim of this paper is to analyze Ss’ narratives of intercultural encounters and present the impact that these encounters had on students’ language awareness, language sensitivity and language use.

Last decades, rolling bearing faults assessment and their evolution with time have been receiving much interest due to their crucial role as part of the Conditional Based Maintenance (CBM) of rotating machinery. This paper investigates bearing faults diagnosis based on classification approach using Gaussian Mixture Model (GMM) and the Mel Frequency Cepstral Coefficients (MFCC) features. Throughout, only one criterion is defined for the evaluation of the performance during all the cycle of the classification process. This is the Average Classification Rate (ACR) obtained from the confusion matrix. In every test performed, the generated features vectors are considered along to discriminate between four fault conditions as normal bearings, bearings with inner and outer race faults and ball faults. Many configurations were tested in order to determinate the optimal values of input parameters, as the frame analysis length, the order of model, and others. The experimental application of the proposed method was based on vibration signals taken from the bearing datacenter website of Case Western Reserve University (CWRU). Results show that proposed method can reliably classify different fault conditions and have a highest classification performance under some conditions.

This study was conducted to predict the yield and biomass of lentil (Lens culinaris L.) affected by weeds using artificial neural network and multiple regression models. Systematic sampling was done at 184 sampling points at the 8-leaf to early-flowering and at lentil maturity. The weed density and height as well as canopy cover of the weeds and lentil were measured in the first sampling stage. In addition, weed species richness, diversity and evenness were calculated. The measured variables in the first sampling stage were considered as predictive variables. In the second sampling stage, lentil yield and biomass dry weight were recorded at the same sampling points as the first sampling stage. The lentil yield and biomass were considered as dependent variables. The model input data included the total raw and standardized variables of the first sampling stage, as well as the raw and standardized variables with a significant relationship to the lentil yield and biomass extracted from stepwise regression and correlation methods. The results showed that neural network prediction accuracy was significantly more than multiple regression. The best network in predicting yield of lentil was the principal component analysis network (PCA), made from total standardized data, with a correlation coefficient of 80% and normalized root mean square error of 5.85%. These values in the best network (a PCA neural network made from standardized data with significant relationship to lentil biomass) were 79% and 11.36% for lentil biomass prediction, respectively. Our results generally showed that the neural network approach could be used effectively in lentil yield prediction under weed interference conditions.

The ways of the improvement of the method for the determination of steel losses in the electrical devices of basic types are substantiated. The method is refined by taking into account the magnetic system properties at high saturation. The presence of the interrelation between the special features of the domain structure movement and the shape of the hysteresis loop is proved for laminated cores. It enabled the explanation of the causes for the abnormally high values of the losses in the steel and the atypical shapes of the hysteresis loops at its high saturation. The empiric dependence for the determination of steel losses is obtained. It provides for the high convergence of the calculated and experimental data at the actual degree of saturation and can be used in the direct-current operation of the analyzed devices.

A design of microwave installation for energy concentration on a surface of a heated object is proposed. In the installation a dipole lattice on the basis of a single-wire transmission line is used which is located inside of reflector in a form of specular parabolic conducting cylinder. The heated object is placed in the area of microwave energy concentration.

In the article a waveguide field of a surface wave in a reradiation mode is explored. The surface wave is reradiated by a group of vibrators coaxial with the waveguide wire. Results of experimental studies of field distribution along the waveguide operating in various modes are presented. The possibility of efficiency increase in reradiated field and its adjustment by contactless movement of reflector is shown.

The corrosion inhibition behaviour of 1-Ethyl-3-methylimidazolium-methanesulphonate (EMIM[MS]) and 1-Ethyl-3-methylimidazolium acetate (EMIM[Ac]) on API 5L X-52 carbon steel in 2 M HCl was investigated using weight loss, potentiodynamic polarization and electrochemical impedance methods. The corrosion rates of carbon steel decreased in the presence of these ionic liquids. The inhibition efficiencies of the compounds increased with concentration and showed a marginal decrease with a 10°C increase in temperature. Polarization studies showed the compounds to be mixed type inhibitors with stronger anodic character. The adsorption mechanism of both compounds on the metal surface was via physical adsorption and the process obeyed the El-Awardy kinetic-thermodynamic model. The associated activation energy of corrosion and other thermodynamic parameters were calculated to elaborate on the thermodynamics and mechanism of the corrosion inhibition process. EMIM[MS] was found to inhibit the corrosion of carbon steel better than EMIM[Ac] and is attributed to the presence of the highly electronegative sulphur atom in its structure and its larger molecular size.

Thermodynamic optimizations of the ternary Fe-B-Mo system and its binary sub-system B-Mo are presented. The Fe-B-Mo description is then extended to the quaternary Fe-B-Cr-Mo system by assessing the ternary B-Cr-Mo system. The thermodynamic descriptions of the other binaries (Fe-B, Fe-Cr, Fe-Mo, B-Cr, and Cr-Mo) and the other ternaries (Fe-B-Cr and Fe-Cr-Mo) are taken from earlier studies. In this study, the adjustable parameters of the B-Mo, Fe-B-Mo, and B-Cr-Mo systems were optimized using the experimental thermodynamic and the phase equilibrium data from the literature. The solution phases of the system (liquid, bcc and fcc) are described with the substitutional solution model, and most borides are treated as stoichiometric phases or semistoichiometric phases, using a simple two-sublattice model for the latter. The system’s intermetallic phases, Chi, Mu, R, and Sigma (not dissolving boron) as well as boride M3B2, based on a formulation of (Cr,Fe)(Cr,Fe,Mo)2(B)2, are described with a three-sublattice model. Reasonable agreement is obtained between the calculated and measured phase equilibria in all four systems: B-Mo; ­Fe-B-Mo; B-Cr-Mo; and Fe-B-Cr-Mo.

Most construction projects involve subcontracting some work packages. A subcontractor is employed on the basis of their bid as well as according to their availability. A viable schedule must account for resource availability constraints. These resources (e.g. crews, subcontractors) engage in many projects, so they become at the disposal for a new project only in certain periods. One of the key tasks of a planner is thus synchronizing the work of resources between concurrent projects. The paper presents a mathematical model of the problem of selecting subcontractors or general contractor’s crews for a time-constrained project that accounts for the availability of contractors, as well as for the cost of subcontracting works. The proposed mixed integer-binary linear programming model enables the user to perform the time/cost trade-off analysis.