This research applied EXPERTise retrieval model for finding EXPERT authors, and used evaluation methods of information retrieval systems for measuring the performance of those models. Current research is an experimental one. Besides, a variety of methods including survey method has been used in the research process. Various models were developed for finding EXPERT authors, all built on a known EXPERTise retrieval model, called document-centered model. Voting models were used within these models, too. All models were implemented and evaluated on the test collection developed specially for this research. Results showed that citation-centered models outperformed authorshipcentered models in term of EXPERT author finding task. In addition, there was no significant difference among retrieval performance of voting models. Individuals name occur in academic papers in two ways: either as author of paper or cited in the paper. Measuring retrieval performance of ER model considering kind of occurrence is our contribution in this research.

A good Legal system with the appropriate function is one of the most significant element for de-veloping social justice and today's improvement. And this factor exes the number of judical cases and a judge without any helps cant consider them. the capacity of Iranians judical system in the last decade go to the world wild standards. but now we need some improvements. one of the cases that was not considered was the culture of using EXPERTs in different fields that in many developed countries like England France even some countries like Turkey understood them and they try to use them in their courts. Also in our country for a long time these procedure was mentioned but because of different challenges in our judical system they couldn't use these potential very well. In this article the author tried to mention their importance of EXPERTs in judical system and he's going to talk about the gaps and opposites between formal and informal EXPERTs, and at last by analyzing the priority of using these EXPERTs instead of a local intelligence and their functions, suggest some no codes for reducing the extension of judical procedure.

Introduction: Micropropagation is important for both multiplication and preservation of a wide range of nursery plants, including many fruit crops. A number of studies exist on optimization of growth in in vitro condition for one or two cultivars, but often these results cannot be used for the other genotypes because individual cultivars may differ greatly in their requirements. Therefore, genotype-specific medium are usually empirically developed for many plants including pear. Pear cultivars and species are often recalcitrant to tissue culture manipulations and Murashige and Skoog (23) (MS) basal nutrient medium at full or half strength or with slight modifications is the most media were used. The QL, DKW, and WPM media are also used and they differ mostly in types or amounts of calcium and nitrogen in compared with MS. Developing growth media for specific and unique cultivars is complex and time-consuming. Currently, improved experimental design and using statistical softwares allow much more efficient approaches to be utilized for the improvement of micropropagation media and conditions. Improving of growth medium for in vitro propagation of plants depends on type and quantities of mineral nutrients and plant growth regulators as important ones. The existence of statistical softwares to manage effective factors is very needed to access an optimized growth medium for in vitro propagation of plants. Design EXPERT is used as auxiliary software to identify essential factors in in vitro culture. Since the in vitro proliferation parameters of Pyrus communis cv. ʽ Shekariʼ need to optimize for growth better, we were designed and performed a multifactor surface response experiment by Design EXPERT software to following two goals. First, to find optimized amount of some elements in medium and second, to show the response surface method can be useful for improving in vitro culture. Materials and Methods: One experiment was designed by Design EXPERT software and was performed to improve in vitro proliferated shoots of Pyrus communis cv. ʽ Shekariʼ . Shoots were grown in a modified MS medium (supplement with 1 mg l-1 of N6-benzyladenine) were used for this experiment. The experiment was included 20 model points randomly based on three nutritional factors: NH4NO3 (0. 5-1. 5×), Fe (0. 5-1. 5×) and micro nutrients (1-2×) in different concentration of their MS amounts. Media enriched with sucrose (30 g l-1) and agar (8 g l-1) after pH adjustment at 5. 7. Cultures were grown at 25° C under a 16-h photoperiod with 70– 90 μ M m-2 s-1 irradiance provided by a combination of cool-and warm-white fluorescent bulbs and were transferred to new medium every 3 weeks. Several responses were recorded after two months: Proliferated shoot number, proliferated shoot length (cm), total leaf number, leaf chlorophyll a (mg g-1), leaf carotenoids (mg g-1), and vegetative growth (cm). Responses for each point were the mean of 5 replicates. Experimental design, model evaluation, and analysis were done by Design-EXPERT® 8 (2010) software and the highest-order polynomial model that was significant for each response was used for ANOVA. Results and Discussion: Factors statistically were significant for responses according to ANOVA in linear, 2FI and quadratic models. Reduced NH4NO3 (×0. 5) and enhanced Fe (×1. 5) induced the higher number of proliferated shoots up to 4. 43 folds of control according a quadratic model. NH4NO3 and Fe×Micro had negative liner relationships with shoot length, while leaf number negatively was affected by micros. Fe and NH4NO3 were effective factors on leaf chlorophyll a and carotenoids contents. Increasing Fe (×1. 5) and decreasing NH4NO3 (×0. 5) led to 2 folds higher production of chlorophyll a and carotenoids. Vegetative growth of Pyrus communis cv. ʽ Shekariʼ in a quadratic-order method (negatively controlled by NH4NO3 and micros) increased by high values of proliferated shoot number and shoot length induced by reduced NH4NO3 (×0. 5). Optimized amount of three studied factors based on two important responses, maximum amount of proliferated shoot number and length, were 0. 9, 1 and 0. 5× for Fe, micro and NH4NO3 in MS medium, respectively. Conclusions: Design EXPERT software and response surface method were used successfully for in vitro optimizing of Pyrus communis cv. ʽ Shekariʼ regenerated shoots. Fe, Micro and NH4NO3, were the effective factors for shoot regeneration responses in linear, 2FI and quadratic models. The multifactor investigation in surface response design will enable us to predict an optimal medium for several effective factors and estimate suitable responses. Outputs of these types of experiments provide a suitable background to increase optimization accuracy for future experiments.

Community Question Answering has a crucial role in almost all societies nowadays. It is important for the owners of a community to be able to make it better and more reliable. One way to achieve this, is to find the users who have more knowledge, EXPERTise, experience and skill and can well share their knowledge with others (which we call EXPERTs and aim to encourage them to be more active in the website). One method to use is to identify EXPERT users, and whenever a new question is asked, we suggest this question to them to check and answer if its in their area of EXPERTise. One way to encourage users to post replies, is to use gameplay techniques such as assigning points and badges to users. But as we will discuss, this method does not always detect EXPERT users well, because some users will try to have small and insignificant but numerous activities that will make them gain a lot of points, however they are not EXPERTs. In this study, we examine the methods by which EXPERTs in a question-and-answer system can be found, and try to evaluate and compare these methods, use their ideas and positive points, and add our own new ideas to a new way of finding them. We used some ideas such as profile making for users, categorize users’,EXPERTise, A-Priori algorithm and showed that neural networks method results the best for the purpose of EXPERT detection.