In the current work, beach sand (BS) and beach sand coated with polyaniline (BS/Pani) were used as an efficient green adsorbent for dye removal from aqueous solutions. Methylene blue (MB) was chosen as a test probe for the evaluation of the selected adsorbents for dye removal efficiency. The adsorption experiments were carried out in batch system and the effect of some important empirical parameters affecting adsorption processes were then investigated. The experimental data were also analyzed by Langmuir and Freundlich adsorption models. Based on the correlation coefficient values obtained (R2), it was found that equilibrium data for both adsorbents fitted well with both models. Adsorption data were also examined by pseudo-first-order and pseudo-second-order models and their respective rate constants were estimated. It was found that sorption of MB dye onto BS/Pani is fitted very well with pseudo-second-order kinetic model. Using the equilibrium concentration constants obtained at different temperatures, important thermodynamic parameters of the sorption process were calculated. It was found that the chemically modified beach sand is an effective and low cost adsorbent for dye removal from aqueous solutions.

This paper presents an empirical investigation to measure the performance of a mining firm in province of Semnan, Iran based on fuzzy fuzzy Decision Making Trial and Evaluation Laboratory (DEMATEL) technique. The proposed study of this paper uses strength, weakness, opportunity and threat (SWOT) technique to analyze the firm and using DEMATEL rank various items based on their relative importance. Based on the results of our survey, cost reduction and increase investment in mining sector are the most important components of this survey. The study also compares the results with similar study, which has recently been accomplished and we believe the proposed model is capable of detecting possible threats and helping us provide possible actions.

The objective of this study is to measure the performance improvement of supply chain (SC) stages through implementing the national standardization system (NSS) in an innovative way. There are many studies on the positive effects of standardization system on supply chain performance (SCP), but very few studies have measured and prioritized the impact of this system on SCP. This paper introduces a new approach to the performance improvement of each stage of SC through implementing the NSS. First, we use fuzzy analytical hierarchical process method to measure the relative importance of each stage and determine the characteristics of SC. Then, the amount of SC stages improvement after implementing the NSS is determined. Finally, using a combination of results, the stages of SC are ranked according to the effectiveness of NSS implementation. In order to validate the proposed approach, the case analysis of Iran NSS is carried out on broiler SC. The stages of SC are ranked according to the performance improvement through implementing standardization system, subsequently. This approach can be generalized to other standardization systems and SCs.

There is an ongoing change on customers’ needs on selecting customers’ needs, which may influence requirements on designing products and services as well as export sale and company’s market shares in domestic and international market. In the present study, through descriptive approach with qualitative method and case study, we investigate important key factors influencing on new product development and products’ successive factors at overseas nutritional market. In addition by presenting a new model in accordance with the present condition of the organization we explore the closest product development model and affective factors influencing them. The study investigates 36 factors and extracts six important ones, which influence product development including intelligent information, process research and development, strategy introduced, participation strategy, market survey and differentiation strategy.

Ranking industry normally helps find hot sectors and attract potential investors to invest in appropriate plans. Ranking various industries is also a multiple criteria decision making problem. In this paper, we present an empirical investigation to rank different industries using the art of data envelopment analysis (DEA). The inputs of our proposed DEA model include capital, employment and importance coefficient and outputs are exports, ecological effects and added value. In addition, exports, value added and environmental investment are used as outputs of DEA method. Since the results of DEA may consider more than one efficient unit, so we implement Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) technique to rank efficient units. In our case study, there were 15 different sectors from various industries and the implementation of DEA technique recommends 8 efficient units. The implementation of TOPSIS among these efficient units has suggested that Chemical industry could be considered as the most attracting industry for investment.

Contractor selection plays essential role on development of business industries and any selection strategy is normally involved with various factors. This paper presents an empirical investigation to determine important factors influencing contractor selection to increase profitability. The proposed model of this paper is implemented for an Iranian constructor firm named Kayson Company located in city of Tehran, Iran. The study has been accomplished among top managers who worked for this firm. Using structural equation modeling, the study determines that five factors including performance, believes, flexibility, quality, price and services influence on profitability when a contractor is to be chosen.

Considering the importance and extensive range of decision-making, scientists from various fields have had many discussions on this issue. Various models have been proposed to facilitate decision-making and have had much utilization. In many site selection problems, multiple objectives must be obtained, simultaneously. This study uses a mathematical model to select a suitable location for the refinery in the multi attribute environment. The proposed model uses a large amount of qualitative and quantitative information in the frame of multi objective functions for the first time in the refinery site selection and is flexible enough to use decision makers’ opinions in order to achieve goals. For this reason, after a brief overview of the selected area characteristics, using analytic hierarchy process (AHP) for weighting the criteria, a mathematical operation research model is proposed to determine the best alternatives.

In this paper, we have provided hands-on experience in systematic design, implementation and flight test of an atmospheric data acquisition flying vehicle as a standard CanSat telemetry mission. This system is designed for launching from a rocket at a separation altitude about 1000-meter. During its flight, the reusable flying vehicle collects environmental data and transmits it directly to the ground station. The ground station, which is implemented at a pre-defined radio frequency band receives data and plots the respective graphs. The design performs based on a systematic approach, in which the first step is set aside to mission and objectives definition. In the next step, the system requirements are identified and the required main subsystems and elements with their technical requirements will be extracted. The structure analyses were also performed by ABAQUS software to obtain the natural frequency and the mode shape. The wireless communications, onboard microcontroller programming, sensor interfacing and analog to digital conversion describe the basic technologies employed in the system implementation. This flying vehicle in comparison with the other similar ones is more lightweight, has few interface circuits and high precision sensors. According to the flight test outputs, low power consumption, high transmit line up to 2Km despite of limitation in TX power and up to 10g normal acceleration withstanding are important specific characteristics of the implemented flying system.

This paper presents a study to investigate the effects of open innovation factors on supply chain behavior in Iranian gas industry. The study uses two questionnaires, one to measure the effects of open innovation factors developed by Chesbrough (2003) [Chesbrough, H. W. (2003). Open innovation: The new imperative for creating and profiting from technology. Harvard Business Press.] and the other to measure the effects of supply chain behavior. Using Pearson correlation ratio as well as Stepwise regression model, the study has determined a positive and meaningful relationship between open innovation and supply chain behavior. In our survey, while intellectual property management and networking had no impact on supply chain behavior, three variables of research and development, cooperation and entrepreneurship influence positively on supply chain behavior.

Nowadays, the advance and enhance in competitive area, convert the supply chain management into one of the most important issues for industries, organization, and firms. Increasing the quality of products, decreasing the costs, and representing the satisfying service are the primary objectives of organization and managers. Apart from that, the amount of CNGs (such as CO2) has been raised by industrial activities. Therefore, the concern of air pollution motivates managers and researchers to consider this issue in the process. This paper represents a multi objective supply chain network fuzzy programming, which is multi product, multi period, multi-layer, and has reverse product network. Operational risks are considered as deficiency in suppliers’ units and production center. The model’s duty is to choose the optimal suppliers based on different factors such as selling price, the average of deficiency and transportation costs. In order to solve the model, the Jimenez and TH approach are used and for large-scale problems, the paper uses the NSGA-II algorithm.