The use of elastic elements in actuators can be effective in improving their performance. The present paper examines the different layouts of the elastic element in actuators, choosing the appropriate design, and then designing a series elastic actuator for use in an active knee orthosis. For this purpose, the design elements of actuators were extracted using the knee data for walking. In the next step, considering the effect of the spring stiffness on the energy consumption and actuator’s peak power, its optimum amount for gait was calculated. Afterwards, the effect of adding the spring has been shown at an optimal value. Since the human knee in a gait cycle involves position and force control, designing an efficient controller to track the force and position of the knee during the gait cycle is the next section of this study. Due to the specific application of this actuator, its volume and size are important for the user. For this reason, it is necessary to design and construct an actuator with a suitable size and weight, with good output. For this purpose, a lightweight and low volume actuator was fabricated.

Dynamic pricing is a kind of pricing strategy in which the price of products varies based on present demand value. So far, several research works have been reported for using neural network for pricing, such as predicting demand and modeling the customer's choices. However, less work has been performed on using them for optimizing pricing policies. In this project, we try to explain the way of combining neural network and evolutionary algorithms to optimize pricing policies. We create a neural network on the basis of demand model and benefit from evolutionary algorithms for optimizing the resulted model. This has got two privileges: First, necessary flexibilities are created by using neural network to model different demand scenarios that is occurred with different products and services, and second, using evolutionary algorithms provides us with the ability of solving complicated models. Wavelet neural network has been used and the resulted pricing policy has been compared with other demand models that are widely used. The results show that the suggested model match up well under different scenarios and presents a better pricing policy than other suggested models.

Credit risk consists of probability of non-return, which may be in the form of bankruptcy or a decrease in financial and credit situation of the lessee. The variables are extracted from the Central Bank. In this study the independent variables are measured with six factors that are called external factors. The external factors are size of leasing, ownership interest rate, foreign exchange, inflation, and Gross Domestic Product (GDP). The present study uses related observations from 31 leasing companies from 2008 to 2013 to find out the determinants of the credit risk. The combined evidences suggest that internal factors such as upfront prepayment, credit insurance contract, security deposits, time and period contract, collateral and guarantees, contract amount, as well as external factors such as interest rate, inflation, foreign exchange, Gross Domestic Product infrastructure, and credit risk are determinants in the policy-making process involving the industrial leasing. Furthermore, the empirical results indicate the size of leasing and ownership are not the significant determinants of credit risk. The results of this dissertation provide several implications for policy-makers in the leasing industry. Policy-makers will be better off employing different procedures for leasing activities in the leasing industry.

Failure analyses require more and more reliable and robust approaches to structural response prediction. This represents a quite complex task to be accomplished especially when dealing with historical or ancient constructions in seismic geographic areas. The paper is aimed at providing approaches to the analysis of buildings alternative to simplified methods usually adopted in professional practice, which do typically involve drastic simplifications of the fabric. The approach allows developing full holonomic non-linear analyses for forecasting the behavior of structural panels present in the structural system, and it results in higher reliability and flexibility than ordinary procedures that are generally adopted in commercial software and are typically based on gross simplifications of the real structure. The presented method allows taking into account the real geometry of the masonry building under analysis, also including a number of elements such as architraves, tendons or reinforcements possibly incorporated into the walls. Besides the consistent improved reliability in performing structural analyses under quasi-static loads, the main potential of the approach is related to the possibility of developing its extension for performing dynamic analyses quite easily.

Manufacturing organizations are under the pressure to give quality products at least cost within the possible minimum delivery time, even during unpredictable economic conditions. Due to competition like improved customer service and cost reduction, organizations are looking for innovative ways for creating competitive advantage. One such way is the effective information sharing among all the members of supply chain. To understand information sharing, we have to know the benefits of information sharing within the supply chain. In this study, on the basis of the relevant available literature and the suggestions of an expert team composed of managerial and technical experts of the manufacturing organization and academicians, eleven information sharing benefits have been diagnosed. An ISM-based model has been formed to study the understanding of the information sharing benefits in adopting the right information sharing within a manufacturing industry. We propose the ISM model, and a MICMAC investigation is applied. Its practical significance is to make use of the decision makers’ knowledge to give a fundamental understanding of a complicated situation, followed by a course of actions for problem-solving.

This article studies the impact of working capital management (WCM) on firm profitability (FP) in Vietnam. The study uses the Generalized Least Squares (GLS) regression method using a sample of 5,295 firms (observations) listed on stock market in Vietnam from 2009 to 2018. First, the study found that inventory turnover, average receivables (AR), average payment (AP), cash conversion cycle (CCC) had negative impacts on the firm profitability (FP). However, when we continued using quadratic function, we found that INV, AR, AP and CCC had a non-linear relationship (the U-curve) with FP. These research results contribute managerial contributions for firms in efficiently using capital when considering its investment policy.

Powder mixed electro discharge machining (PMEDM) is a hybrid machining process where electrically conductive powder is suspended into a dielectric medium, for enhancing the material removal as well as the surface finish. In this investigation, electro discharge machining (EDM) has been performed for the machining of AISI 304 stainless steel by using the tungsten carbide electrode, when silicon carbide (SiC) powder is suspended into kerosene dielectric medium. Peak current, pulse on time, gap voltage, duty cycle and powder concentration are considered as process parameter while the surface roughness (Ra) is the only response. The effect of significant process parameters on the response has been studied. A regression analysis has been performed to describe the correlation of data between the machining parameter, and the response. Microstructural analysis has been done for the PMEDMed surface. The result shows that peak current is the most influential parameter for surface roughness. Surface roughness decreases with the increase of powder concentration.

This paper presents a numerical investigation on the flexural performance of a novel cementitious reinforced GEM-TECH material using finite element method. A discrete nonlinear FE model using the commercial software ANSYS was employed to model a steel-reinforced GEM-TECH beam. Element SOLID65 was used to model the cementitious material while LINK180 element was used to model the reinforcing bars and stirrups. For model validation, FEA results and crack plots were compared to those obtained from the experimental results of five reinforced GEM-TECH beams: three beams designed with target density of 1810 kg/m3 and two beams with target density of 1600 kg/m3. Both load-deflection plots and the failure mode crack plots predicted by the FE model were in good agreement with the experimental results.

This study aims to analyze the factors affecting the role of women in the economic development of rural household families in Vietnam. 210 survey samples collected in Trieu Son district, Thanh Hoa province were used as data in the study. The study finds a number of important factors influencing the role of women in rural household economic development. Since then, some meaningful solutions to promote the role of women in the economic development of rural household families in Trieu Son district are proposed in the study.

Nowadays efficiency measurement is considered as one of the most important methods for performance assessment of the organizations. Assessment of academic education and research system is a vital factor for education and research promotion and also is a panoramic mirror for education and research activities. The aim of this research is to assess the efficiency measurement of Shiraz university colleges over the period 2009 – 2014. Data Envelopment Analysis (DEA) as one of the most important methods of efficiency measurement has two limitations: First, it calculates cross-sectional efficiency values and second, it may consider many units as an efficient unit. Window Data Envelopment Analysis (WDEA) is used for eliminating the first limitation and similarly double frontier analysis is used to overcome the second limitation. The results show that proposed WDEA method with double frontier in comparison with traditional analysis, provides more accurate results.