m. rabbani

The growth of communication technologies, the expansion of the use of electronic devices and the widespread use of the Internet have affected various aspects of human life. Education, teaching and learning, which are an important aspect of people's lives and an unobtrusive discussion at various social levels, has been greatly influenced by these developments and has grown with the growth of technology. Despite extensive research on the benefits and potentials of Cooperative Learning, its implementation has remained challenging. In line with this research gap at the international and national levels, it seems that identifying solutions to implement this approach in the online environment is a basic necessity. This research gap led the researchers to study the challenges and strategies for implementing the Cooperative Learning approach in Iran with an emphasis on the field of educational management with a small sample. Therefore, the present study aimed to identify the challenges and strategies of Cooperative Learning in the online environment.

This research was based on a qualitative approach and was carried out using a descriptive phenomenology method. The field of research is the Faculty of Psychology and Educational Sciences of Tehran University and the participants were faculty members working in three groups related to the fields of educational sciences. Sampling method was purposeful and criteria-oriented by determining three criteria: 1. they have participated in cooperative research workshops or are familiar with this approach, 2. they have used this approach in their classroom in a practical way, however little and incompletely, 3. they have taught in both face-to-face and online environments. The sample consisted of 22 people. The data analysis was done with the Colaizzi’s method and the use of Atlas-ti qualitative analysis software. In order to further validate the findings of the research, five visiting professors of the university were also interviewed.

The data analysis was categorized in two dimensions: challenges and solutions to facilitate the cooperative learning process in the online environment. As for the challenges, four themes of facilities, environment, implementation and achievements and 22 sub-themes were identified and categorized; in the challenges related to the limitation of facilities, there were themes including the structural complexities of the electronic space, internet disorders, the online environment and the lack of a proper educational platform; in the challenges related to environmental restrictions, there were themes including the reduction of opportunities for face-to-face interaction, the impossibility of continuous monitoring; in the challenges related to implementation limitations, there were cases including insufficient technical skills, low media literacy, inability to enrich life skills training opportunities, limitation of opportunities for creativity, negative attitude towards the electronic space; Also there were issues related to collaborative group including different schedule of group members, misunderstanding in communication, participation, work report, lack of agreement among members regarding means of communication and difficulty in group decision-making; and in the challenges related to achievement limitations, some themes were identified including encouraging superficial learning, creating the background for the occurrence of physical problems, especially eye problems, and reducing enthusiasm in the classroom. With regard to the solutions to facilitate the cooperative learning process in the online environment, 8 themes including solutions related to the online class (including 7 sub-themes of quick response, inability to teach life skills, attendance and absence, establishing face-to-face communication, creating an atmosphere based on honesty weekly group and individual report and expression of feelings), strengthening internet and broadband infrastructure, easy access of professors and students to the internet, holding online classes in times of low network traffic, using various platforms for learning, teaching how to use technical tools to professors and students, using teaching assistant, use of new technologies for learning were identified and classified.

The results indicated that this approach in classrooms, especially in online classrooms, is not only incompletely and very little implemented, but its implementation is facing a wide range of challenges. Considering the strong theoretical support of cooperative learning, its limited implementation in Iran and the identified challenges are thought-provoking and worthy of further investigation. It is clear that most of the identified challenges are not related to the nature and capacities of electronic platforms and are mainly caused by reasons such as incomplete implementation and the inability to act effectively in online environments. It is suggested that in curriculum planning, a special position should be given to wide culturalization regarding the benefits and advantages, disadvantages and threats of cooperative learning in general and online cooperative learning in particular at the level of schools and universities and among managers and students, and especially, teachers and professors.

Line balancing is a fundamental concept for continuous production systems. Assembly lines are present in different industrial environments and usually have a great economic impact because of their high manpower levels. A simplied view of the assembly line balancing problem (ALBP) is dened as the grouping of the tasks required to assemble the nal product to the workstations conforming to the assembly line, which species the permissible orderings of the tasks. The main goal of the assembly line balancing problem is to assign the tasks to workstations such that the precedence relations are satis ed and some performance measure is optimized. The ALBPs are classied into two groups: simple assembly line balancing problems (SALBPs), which bear numerous simplifying assumptions, and general assembly line balancing problems (GALBPs), which are closer to reality due to the consideration of one or more realistic conditions, like sequence-dependent setups.
In this paper, we consider the problem of optimizing simultaneously the objectives of minimizing cycle time and minimizing the overall setups in a general assembly line balancing environment with the consideration of sequence-dependent setup times between tasks. The rst objective, which is referred to as the type II problem, generally occurs when the organization wants to produce the optimum number of items using a xed number of workstations without adding new machines. The minimization of the overall setup times is important mostly for the cases when setups impose maintenance costs on tools and the prolongation of setup times would increase maintenance costs and also bring more exhaustion to workers.
This paper is intended to introduce the objective of minimizing overall setups in the class of assembly line balancing problems and solve the problem of concurrently minimizing cycle time and the overall setups. The exact method was not ecient enough to solve the innovative problem with type II problem assumptions; thus, a Pareto simulated annealing (PSA) algorithm is developed to solve such an Np-hard problem and several quantitative metrics are dened for evaluating the proposed algorithm. Computational results veried the considerable eciency of the PSA algorithm.

The bullwhip effect is one of the most important problems in the supply chain management. It can cause large inefficiency in supply chain. Although there are many researches about bullwhip effect, few studies have investigated this phenomenon caused by product price fluctuation. In this paper we consider a two-period supply chain consisting of one supplier, one wholesaler and one retailer. The wholesale price may increase greatly in the beginning of second period. If this happens, a large number of end customers will go to purchase the product from retailer. For managing the end customers’ demands in the second period, we consider two ordering strategies available to the retailer including optimal order quantity strategy and hedging strategy with call option. For each strategy, we calculate the bullwhip effect ratio for two periods and compare the results. We found that the lower exercise price in hedging strategy compared with the wholesale price in the optimal order quantity strategy must not contribute to extra product purchase. The research provides new insights into how hedging strategy can reduce bullwhip effect.

Cryptocurrencies, which the Bitcoin is the most remarkable one, have allured substantial awareness up to now, and they have encountered enormous instability in their price. While some studies utilize conventional statistical and econometric ways to uncover the driving variables of Bitcoin's prices, experimentation on the advancement of predicting models to be used as decision support tools in investment techniques is rare. There are many different predicting cryptocurrencies' price methods that cover various purposes, such as forecasting a one-step approach that can be done through time series analysis, neural networks, and machine learning algorithms. Sometimes realizing the trend of a coin in a long run period is needed. In this paper, some machine learning algorithms are applied to find the best ones that can forecast Bitcoin price based on three other famous coins. Second, a new methodology is developed to predict Bitcoin's worth, this is also done by considering different cryptocurrencies prices (Ethereum, Zcash, and Litecoin). The results demonstrated that Zcash has the best performance in forecasting Bitcoin's price without any data on Bitcoin's fluctuations price among these three cryptocurrencies.

Medical data mining is considered as a new solution to analyze medical data and discover knowledge . Medical data mining has a high potential for discovering hidden patterns in medical data. In the present era, some studies have been conducted on the relationship between environmental quality and diseases , which have clearly indicated the impact of environmental quality indicators, such as environmental pollutants, on diseases. In this study, environmental conditions in diabetes were investigated based on medical data mining technique. Diabetes is considered as a global threat affecting human health. An ensemble classifier based on genetic algorithm(ECGA) method was designed to study the environmental conditions in diabetes. In the designed ensemble classifier, the decision tree, random forest, k-nearest neighbor, and naive bayes were used. It was found that ECGA was more accurate than the base classifier algorithms. In addition, three datasets were collected from different regions of Iran with different climatic conditions. It was found that environmental conditions can affect diabetes disease.

Data envelopment analysis (DEA), is a non-parametric mathematical programming technique to evaluate the efficiency of a set of homogeneous decision-making units (DMUs), so that DMUs are evaluated into two groups, efficient and inefficient. According to the staggering costs in order to managing DMUs or organizations, maintaining some loss-making organizations are not cost-effective. Therefore, one of the concerns of managers in the discussion related to the financial problems of organizations is the maintenance or merger or elimination of inefficient organizations (inefficient DMUs). However, this article focuses on the performance of inefficient units. Therefore, we measure the productivity of inefficient DMUs using the revised Malmquist productivity index (MPI) to make a decision based on the maintenance or merger or elimination of these DMUs by decision makers (DMs).

In the current situation,taking into consideration the environmental and social issues are related with the production and distribution of products in supplychain systems,due tothe global concerns related with emitting lots of greenhouse gaseswithin the manufacturing process and overlooking the major needs of publicThis paper proposes a newmultiobjectivemodel in the area ofclosed loop supplychainproblem integrated with lot sizing by considering lean,agility and sustainability factors simultaneously.In this regard,responsiveness, environmental,social and economic aspects are regarded in the model besides the capacity and service level constraints.Inaddition,strategic and operational backup decisions are developed to increase the resiliency of the system against disruption of the facilities and routs simultaneously.Next,a robust possibilistic programming approach is applied to handle the uncertainty of the model.To increase the responsiveness of the system,a fuzzyc-means clusteringmethod isapplied to select the potential locations based on the proximity to local customers.In the following, a new hybrid metaheuristic algorithm comprised of a PMOPSO algorithm and aMOSEO is developed to deal with large size problems efficiency and to assess the impact of using a single-based initial solution as the income for the second phase of the proposed hybrid algorithm.To ensure about the effectiveness of the proposed hybrid algorithm,the results of this algorithm arecompared with a NSGA-II.

Data Envelopment Analysis (DEA) is one of the non-parametric methods for evaluating each unit's efficiency. Limited resources in the healthcare system are the main reason for measuring the efficiency of hospitals. Because Operating Rooms (OR) are the most vital part of any hospital, we determine the factors affecting operating rooms' efficiency and evaluate the performance and ranking of operating rooms in 10 of Tehran's largest hospitals. This model's inputs include accuracy in scheduling surgeries, average turnover time, number of successful surgeries and live patients, number of canceled surgeries, number of surgical errors, and number of emergency surgery. Also, outputs consist of the number of operating rooms and equipment, the average number of beds, the number of employees, and the patient satisfaction rate. First, we determine the weight of inputs and outputs by Group Analytic Hierarchy Process (GAHP) with considering experts' ideas in 10 hospitals; then, we utilize three types of DEA model which are input-oriented CCR (CCR-I), output-oriented CCR (CCR-O), input-output oriented CCR (CCR_IO) and AP models to estimate the efficiency of ORs and rank them.

Given that disasters are unavoidable, and many people are suffering from them each year, we should manage the emergencies and plan for them well to reduce mortality and financial losses. One of the measures that organizations must take after the disaster is the assessment of the conditions and needs of the people. We consider some characteristics for sites and roads and two teams for assessment as well as the uncertain assessment time to modeling. A multi-objective model is proposed in this study. The first objective function maximizes the gain from the assessment of areas and roads. The second and third objective functions maximize total coverage at damaged areas and roads. We use the LP-metric technique to solve small size problems in the GAMS software and the Grasshopper Optimization Algorithm (GOA) as a Meta-heuristic algorithm to solve a case study.  Numerical results are presented to prove the credibility and efficiency of our model.

Due to high competition, companies tend to improve their market share by applying different selling mechanisms such as online to offline commerce as an efficient selling mechanism in which the companies sells their products via both online and real stores. This study deals with a selling problem for two complementary supply chains including a supplier and a shopping center where the commodities are sold by a virtual and a traditional shopping center who present items as complementary shopping centers. It is assumed that market demand depends on price and service level so that they can purchase the item via both shopping centers based on their priorities. Also to analyze the reactions of the chain’s partners, different games such as Nash and Stackelberg game are deemed. The aim is to obtain the closed-form solutions of the decision variables of the networks’ members in order to maximize their profits where the prices of different selling periods at each echelon of the chains are the decision variables of the model. The closed-form solutions are derived and the solutions are examined by a numeric example. In following, several sensitivity analyses on key factors are performed to determine efficient ones on the variables and profits.

Manufacturing strategies will let the factories be a market winner in some of the manufacturing outputs of cost, quality, delivery, exibility, and innovation by adjusting their manufacturing levers and production systems. The factors of driving supply chain, relating to these manufacturing outputs, are too many to control, and managing them is essential for world-class manufacturing. That is why this study applied the Supply Chain Operations Reference (SCOR) metrics and Delphi method to categorize the eective factors on manufacturing outputs in procurement, production, and sale levels, known as internal supply chain. As these manufacturing outputs and their hierarchy were inter-connected, this study was conducted to distinguish critical factors, metrics, and levers in uencing most prominently on them. To cope with this inter-relationship, group decision making techniques, Decision Making Trail and Evaluation Laboratory (DEMATEL), and hierarchical weighing approach, with MATLAB programming, were used by the view of 35 Iranian Industrial experts and mangers in the supply chain. The conclusion selects the driving variables which give and receive the most in uences among manufacturing outputs of cost, quality, delivery, exibility, and innovation in procurement, production, and sale units, which are adhered to internal supply chain. The results at the rst level of hierarchy show that Iranian supply chain managers prefers cost and quality rather than exibility and innovation, which prove that they are still in primary level of growth in life cycle. Then, the lowestlevel priority claries the necessity of Iranian managers to receive training of information systems and communication technologies which can connect supplier and customer factories with manufacturing factories, such as on-line purchase and sale, to decrease bullwhip eect. Rather, this selection procedure can reduce the number of aective factors and be used as a pre-assumption for dynamic system modeling of supply chain for choosing their environment, which is usually confusing due to lots of interacting variables.

The Demospongiae was used in Kish Island of Persian Gulf as the biologic absorptive with nano fovea for removing magnesium action and the effect of density, contact time and the size of the absorptive particle was studied in absorption capacity. The absorption capacity of magnesium ion in 10, 30, 50 and 300 mg /l was tested on shaker and the capacities of 0.7, 3, 6.6, 80.3 mg/g were obtained respectively which showed that the absorption capacity increases with density. In addition, the absorption of magnesium ion in the densities of 10, 30 and 50 mg/l, in contact time of 1 hour without shaker, were 1.2, 4.2, 11 and in 3 hours, 0.2, 4.6 and 14.5 mg/g, which showed that the absorption capacity does not increase with contact time. The absorption capacity in absorbent size of 70 meshes and 120 meshes were 80.3, 64.6 and 74.2 mg/g respectively, which showed that the absorption capacity is more when used in pieces. The results of the present research showed that the absorption capacity of magnesium ion by Persian Gulf sponge is 80.3 mg/g and the reported ratio is higher compared to other natural absorbents and is now the highest capacity.

The objective of this study is to determine oil pollutants (PAHs) and investigate PAH source in the sediments of Anzali Lagoon (in Mahrozeh & Selke stations) that can be of high importance from monitoring. Therefore, sampling is made in two wet and dry seasons at Mahrozeh & Selke stations. Finally, making use of GC, the related analyses were performed to determine PAHs. The results showed that mean PAHs in sediments of Mahrozeh were 34.839 in dry season and 61.439 ng/g dw in wet season, and in Selke were 80.432 in dry season and 45.439 ng/g dw in wet season. The amounts of PAHs in Mahrozeh & Selke stations were lower than PAHs in sediments of the Persian Gulf countries, (except of UAE and Oman sediments).and also PAHs in Mahrozeh & Selke stations were lower than sediments of Caspian Sea. The source of PAHs in Mahrozeh & Selke sediments were both pyrogenic and petrogenic.Statistical examinations didn’t show significant differences between PAHs in sampling seasons.

Anzali Lagoon is an international lagoon in North of Iran. It has specific ecosystem characteristics and is a suitable environment for aquatic animals and molluscs, therefore environmental monitoring is very important in this lagoon. On the other hands in recent year'sattention to heavy metals increased. Entry of industrial sewage into aquatic environments and with consideration to bioaccumulation of heavy metals in food chain, the utilization of the polluted aquatic animals by human can bring about irrevocable hazards. The present research aimed to assess Ni, V levels, as oil pollution index, in surface sediments and bivalves (Anodonta cygnea) in 2 stations (Mahrozeh and Selkeh). Samples were collected during 2 different periods of the year, dry and rain seasons, (June & September 2009). Heavy metal (Ni, V) concentrations were determined by Atomic Absorption in Anodonta cygnea and the sediments in Anzali Lagoon. The vanadium concentration in bivalve and sediment was ND (not detected)- 0.3243 µg/g and 2.1796 -306.9603 µg/g respectively. Nickel concentration in bivalve and sediment was 0.0231-1.3351 µg/g, 0.4949-19.5326 µg/g respectively. These amounts in Anzali Lagoon were lower than those of Ni and V in aquatic ecosystems in other countries, and are not in the effect range low (ERL). Besides, the average Vanadium amount is much lower than the sediments in the similar spots, and since ERL and effect range medium (ERM) are not defined for Vanadium, there is no room for judgment. Bioaccumulation sediment factor (BASF) was low for Ni, V (

Possible effects of antioxidant Butyl Hydroxy Anisole (BHA) and sodium polyphosphate on the shelf-life of frozen Astacus leptodactylus of the Caspian Sea was studied. Samples of the crayfish were dipped in 0.02 and 0.2% BHA and 0.04 and 0.4% sodium polyphosphate for 30 and 60 minutes. The control samples were packed without immersion in the mixture of BHA and sodium polyphosphate. The Peroxide Value (PV), Total Volatile Nitrogen (TVN), total bacteria count and organoleptic tests were carried out on the samples using a time schedule. The results showed that the minimum increase in PV for the samples which were soaked in a mixture of 0.2% BHA and 0.4% sodium polyphosphate for 1 hour were from 0.59 to 0.88 meq/1000g, as compared to the control samples with an increase in the range 0.59 to 3.53 meq/1000 g after four months. The PV Value after four month started to be decrease and reached 1.4 meq/1000 grams after sixth months. The results showed that the minimum increase of TVN for the samples which were soaked in a mixture of 0.2% BHA and 0.4% sodium polyphosphate for 1 hour were from 12.88 to 17.8 mg/100 grams and for the control samples, the increase was from 12.88 to 19.8 mg/100 grams after sixth month. The results also demonstrated that the minimum increase in Total Bacteria Count of for the samples soaked in a mixture of 0.2% BHA and 0.4% sodium polyphosphate for 1 hour were from 9×103 to 2×101 per gram and for the control samples, the count was from 9×103 to 7×102 per gram after sixth months. Kruskal-Wallis, chi-square and Duncan tests were conducted on five samples for each specific shelf-life time. Using the results, we conclude that immersing the samples into a mixture of 0.2% BHA and 0.4% sodium polyphosphate for one hour gives the best results in terms of shelf-life and organoleptic tests.