Structural and energy properties of interstitial molecular hydrogen in single-crystal silicon

The structural and energy characteristics of interstitial molecular hydrogen in single-crystal silicon are theoretically studied. The dependence of the potential energy of the system on the position and orientation of the interstitial defect is investigated, and the mechanism of interaction of a hydrogen molecule with a silicon crystal is considered. A three-dimensional model is employed to calculate the energy spectrum of H2 in Si, and the obtained dispersion law is analyzed

Assessing the Phenylketonuria Screening Program in Newborns, Iran 2015-2016

Phenylketonuria is one of the most important congenital disorders and an autosomal recessive metabolic disease that can cause irreversible brain damages, mental retardation, and cognitive disorders if left untreated. In order to reduce the genetic abnormalities caused by this metabolic disease, screening programs are implemented. The quality of the program must be properly assessed to achieve the objectives of this program if promoting children's health is of concern. The descriptive-analytic method is adopted here to assess the phenylketonuria screening program in practice in Chaharmahal and Bakhtiari province since 2012 and analyze the incidence and program coverage. The quality of the screening program is assessed through analyzing the time of diagnosis, beginning of the treatment and the healthcare centers' facilities with checklists. The parental and the staff awareness is assessed through knowledge measuring questionnaires. Cumulative incidence of phenylketonuria in Chaharmahal and Bakhtiari province from 2012 to 2015, is 1 in every 6662 live births. The program coverage across the region is 100%. The recorded on-time sampling index before 5 days of age, indicate 84.6 % in 2015 from 80% in 2012. The treatment begun before the newborn 4 weeks was over in all cases. Program sensitivity was 100 %, and its specificity was 99.9%. Staff awareness is fair with no impact on parental awareness. General quality of the screening program is appropriate, and as to sensitivity and on-time curing specificity, higher staff and parental awareness supervision are recommended as well

Using multiple criteria decision making models for ranking customers of bank network based on loyalty properties in weighted RFM model

One of the most basic requirements of financial institutes, governmental and private banks in the present age is to have a good understanding on customers' behaviors of bank network. It helps banks determine customer loyalty, which yields profit making for bank. On the other hand, it is important to know about credit risk of customers with the goal of decreasing loss and better allocation of bank resources to applicants of receiving loan. According to nature of customer loyalty discussion and credit risk, these two issues are separately studied. The present article deals with studying customer loyalty and prioritizing based one private bank in Kurdistan province. The proposed model of this paper studies customer loyalty by using Recency Frequency Monetary (RFM) factor for prioritizing customer based on loyalty properties and Technique for Order Preference by Similarity to Ideal Solution (TOPSIS). In addition, in order to calculate the relative importance coefficient or weight of loyalty properties in RFM method, the pair wise comparison matrix based on analytical hierarchy process (AHP) is used. Results show that in the present study, necessarily customers having higher average monetary value during a specified time period does not have much higher priority compared with other customers

Modeling Multi-Objective, Multi-Product and Multi-Period Supplier Selection Problem Considering Stochastic Demand

In this paper, a multi-objective, multi-period and multi-product mixed integer programming model ‎for the supplier selection and quota allocation problem under an all-unit quantity discount policy, ‎constrained storage space and stochastic demand is considered. Also, due to the stochastic status of ‎the demand, we use the Chance Constrained Programming (CCP) in order to transform the inventory ‎balance equation to a stochastic position. Since the discount policy encourages the buyer to buy more while the storage capacity restricts, we require to consider both in the supplier selection and quota allocation problem; furthermore, different priorities for the objectives should be considered. We use the LP-metric method, goal programming and the novel solution technique ‎called multi-choice goal programming in order to model the multi-objective problem. Furthermore, a numerical ‎example using three modeling approaches, considering the different scenarios are solved. The differences ‎in the scenarios are the importance of the objective function in terms of the decision maker. Results ‎show if an objective function is prioritized, that objective will be closer to its optimal value. Introduction: The evaluation and selection of suppliers is one of the interesting topics for many researchers. Esfandiari and Seifbarghy (2013) classified the research in the field of evaluation and supplier selection as follows: The first class: mathematical programming models considering the cost objective function The second class: mathematical programming programming considering two objective functions including minimizing cost and maximizing utility function. The third class: mathematical programming considering at least three objective functions including  minimizing cost, return items and delay in delivering products. The forth class: phase models that deal with phase and vague data input such as demand and capacity. The fifth class: models that consider different types of discount The sixth class: models that considering the uncertainties of demand, capacity and ... . The contributions of this paper are as follows: Considering multi-period and multi-objective programming model for supplier selection and quota allocation problem under an all-unit quantity discount policy, ‎constrained storage space and stochastic demand Considering different multi-objective modeling techniques in the field of supplier selection Using the Chance Constrained Programming (CCP) in order to transform the inventory ‎balance equation to a stochastic position.   Materials and Methods: In this paper, a multi-objective, multi-period and multi-product mixed integer programming model ‎for the supplier selection and quota allocation problem under an all-unit quantity discount policy, ‎constrained storage space and stochastic demand is proposed. The Chance Constrained Programming (CCP) in order to transform the inventory ‎balance equation to a stochastic position is used. The assumptions of this paper are as follows: the demand for each product has a normal distribution with specific mean and variance. Inventory holding and shortage costs of each unit product are independent of the price. The number of planning periods is distinct and limited. Suppliers offer all-unit quantity discount policy. The initial inventory level is zero. The remaining inventory of each period is transferable to subsequent periods. The load unit of each product is considered to be 1. The mathematical model of this paper is as follows: (1)   (2)   (3)   (4)   (5)   (6)   (7)   (8)   (9)   (10)   The objective function (1) minimizes costs. The first sentence is buying cost, the second sentence is ordering cost, the third sentence is holding cost and the forth sentence is shortage cost. The objective function (2) minimizes the average amount of returned products. The objective function (3) minimizes the average late delivery of products. Constraint (4) shows the warehouse capacity. Constraint (5), (6) and (7) are related to all-unit discount. Constraint (8) shows inventory balance equilibrium and constraint (9) and (10) show the variables of the model. In this paper, three techniques including LP- metric, goal programming and multi-choice goal programming for modeling are used.   Results and Discussion: To solve numerical example using LP- metric, goal programming and multi-choice goal programming, different scenarios are considered. The difference in scenarios was determined in the importance of objective functions from decision makers’ point of view. The results showed that the LP-metric method is not an appropriate method for solving multi-objective problems. Also, the results showed that if the importance of an objective function is increased from decision maker point of view, that objective function is improved and other function get worse.   Conclusion: In this paper, a multi-objective, multi-period and multi-product mixed integer programming model ‎for the supplier selection and quota allocation problem under an all-unit quantity discount policy, ‎constrained storage space and stochastic demand were considered.  The objective of this model is to minimize the costs, the returns and the delays. Also, due to the stochastic status of ‎the demand, the Chance Constrained Programming (CCP) was used in order to transform the inventory ‎balance equation to a stochastic position. Also, the three methods of LP-metric, goal programming and multi-choice goal programming were used. The results showed that if the importance of an objective function is increased from the decision maker’s point of view, that objective function improves and other functions get worse.   References Seifbarghy, M., & Esfandiari, N. (2011). “Modeling and solving a multi-objective supplier quota allocation problem considering transaction costs”. Journal of Intelligent Manufacturing, 24(1), 201-209. Esfandiari, N., &Seifbarghy, M. (2013). “Modeling a stochastic multi-objective supplier quota allocation problem with price dependent ordering”. Applied Mathematical Modelling, 37(8), 5790-580. Razmi, J., & Maghool, E. (2009). “Multi-item supplier selection and lot-sizing planning under multiple price discounts using augmented -constrained and Tchebycheff method”. International Journal of Advanced Manufacturing Technology, 49(1-4), 379-392

Prediction of New Service Adoption among Mobile Phone Users

Development of ICT services specially those presented by mobile phone operators and increasing competition forces operators to offer new and various services. Operators try to motivate users to apply their innovations by presenting appropriate quality and price. Regarding to the importance of this issue, we survey the effect of service quality and users’ satisfaction on innovation adoption by mobile phone users and predict innovation adoption. The relationship between service quality, customer satisfaction, and innovation adoption will be evaluated and compared using Structural Equation Modelling technique. Also, after extracting the appropriate factors, the probability of acceptance of new services will be calculated using logistic regression method. The results showed that customer orientation and flexibility in services have a major effect on innovation adoption by users. Furthermore, the first mobile operator can attract a lot of users.by offering new services and focusing on these factors

Pricing and inventory control decisions in the stochastic hybrid production systems with multiple recovery options

Although pricing and inventory control are crucial decisions in each production system, these decisions are usually investigated separately. This paper considers pricing and inventory control decisions simultaneously in a hybrid production system. The hybrid production system has two recovery options, remanufacturing and refurbishing sites. The demand follows Poisson distribution, which depends on the sale price of each product. Returned products arrive according to a Poisson process. Each returned product can be remanufactured, refurbished, or disposed. The time to manufacturing, refurbishing, and remanufacturing a product also follows an exponential distribution. By modeling the system as a Markov chain, the long-run expected profit function is obtained in terms of the dispose-down-to level of returned products and the order-up-to level and the sale price of serviceable products. A three-dimensional state space of the Markov Chain dependent to the sale price is developed considering pricing and inventory control decisions simultaneously with remanufacturing and refurbishing returned products. Since the model is a mixed integer nonlinear programming and known as complex models, the Artificial Bee Colony (ABC) algorithm, simulation and complete search method are used to solve the problem. The results show that by increasing the purchase price of the returned products, the amount of returned products will increase. If the refurbishing cost of the returned products is high or the disposal cost is low, less inventory should be kept in the system with a high price of serviceable products. If the lost sale cost is high, the more inventory should be maintained. Moreover, by decreasing the price elasticity of demand, the customer’s demand increases, and then more inventory should be maintained in the system