Introduction: In the last 10 years The incidence of diabetes has doubled worldwide with annual increasing rate of about 6%. More than 2 million people in Iran are now affected by this disease.The present research deals with the relation between the observed complications of type 2 diabetic patients and some related features like Blood Glucose Level, Blood Pressure, Age, and Family History. The main purpose was to predict the patients’ complications based on the observed signs.Methods: The research data were gathered from 856 patient records related to the 2009’s cases in the Diabetes Center of Golestan province. A new model based on the standard methodology CRISP was developed. In the modeling section, two well-known data mining techniques called C5.0 decision tree and Neural Network were used. Celementine 12.0 software was implemented For data analysis.Results: The results of data mining showed that the variables of high blood pressure, age, and family history had the most impact on the observed complications. Based on the created decision tree, some rules have been extracted which can be used as a pattern to predict the probability of occurring these complications in the patients. The accuracy of the C5.0 model on the data was shown to be 89.74% and on the Artificial Neural Network was 51.28%.Conclusion: As the highest accuracy was shown to be achieved using C5.0 algorithm, according to the created rules, it can be predicted which complication (s) any diabetic patient with new specified features may probably suffer from.

Despite increasing requirements of rural and tribal communities to use new technologies, the adoption of this technology in rural areas is very low. Surveys show that, the reason of this rejection is the incompatibility of technology with the rural environment. Scientists believe that, to accept the new technologies, it should be referred to indigenous knowledge. In this field study, the indigenous knowledge of the use of oak tree components in Rustam tribe from Mamasani tribe of Fars has been evaluated. Some regions of the territories of Rustam tribe were selected and among those regions, villages that have rich indigenous knowledge in the use of oak were selected. The subjects of the study were selected by snowball sampling method. In this study the techniques of participant observation, free observation and semi-structured interviews were used, and in some cases, documents were also used inevitably. It was found that, in the study area according to the modernization theory based on the compatibility of indigenous knowledge and development, indigenous knowledge has not only been incompatible and an obstacle at the times it was governed, but also it was sustainable in development. The example of this, is the use of oak products by people in their lives and living with this tree for many years. But the arrival of modernization program, caused fundamental changes in the structures of the studied population, and with the lifestyle changes in this area, the utilization of indigenous knowledge has been weakened.

The modern technology has not been well welcomed in the villages. The research findings show that this refusal is due to not matching with the local conditions. The experts in the rural development believe that in order to welcome modern technology more the native knowledge should be applied too. In this research it has been trieel to survey the native knowledge in Mamasani Town. The oak tree and its products have various usages among the villagers. Its products are used in constructing houses, vehicles. Refining, herbal medicine, tannery, dyeing etc. Hence the perts in the rural development should base their developmental planning on applying this native knowledge along with using modern technology.

Introduction: The knowledge tree facilitates the monitoring of research and generated knowledge to ensure the growth and sustatainability of knowledge-based activities. This study aims to present a model for developing the knowledge tree research centers affiliated to medical universities. Methods: This applied study employed a quantitative, descriptive-analytical approach. The statistical population included purposefully selected university research staff, research center managers, and experts in health and knowledge management, aimimg for maximum diversity. Content validity was assessed using an eight-member expert panel and the Content Validity Index (CVI). Results: The five steps for developing a knowledge tree for research centers include: 1) identifying knowledge areas (reviewing strategic and upstream documents, identifying knowledge domains, knowledge types, and knowledge structures), 2) drawing the knowledge tree (identifying knowledge assets, stakeholders and knowledge users; analyzing knowledge needs and current status; establishing a knowledge tree working group), 3) defining the knowledge tree framework (determining the scope, type, and development approach for the knowledge tree), 4) collecting and analyzing knowledge keywords (designing acquisition tools, extracting representative keywords, preparing individual knowledge worksheets, categorizing and integrating keywords), and 5) designing and validating (structuring the tree, drawing relationships, visualization, validation, completion, and updating). Conclusion: In research centers, knowledge representation is achieved by visualizing the knowledge tree, describing its features and relationships, and constructing the knowledge tree. This process improves the efficiency and quality of generated knowledge and enhances judgment by establishing connections between different knowledge areas.

With the rise of the role of knowledge in various fields, it is important to pay attention to the governance knowledge of the education system for policy making and its correct management as a platform for the growth and progress of societies in various fields. The knowledge tree of education system governance of the province is one of the appropriate solutions for macro-policy and correct management in the selection of education managers of that region. The drawing of collaborative knowledge for the management of the province's education system will be a new paradigm and a systematic approach in the governance of the province's education system, and a new perspective can be applied in its management. The main goal of this research is to extract and group the main branches of knowledge needed by governance for the management of education and education in the province through a meta-composite qualitative method. The population and statistical sample of this research is all the library documents related to the governance of the education system in the period from 1988 to 2022. All documents indexed in Google Scholar were identified using Publish or Perish software, and finally 27 indexed documents out of 680 scientific documents were analyzed as well as coding of 221 specific keywords from the documents with MAXQDA Analytics Pro 2020 software. The result is that the governance knowledge tree for managing the education system of the province with the iMindQ software based on the analysis of valid scientific documents in three main levels of knowledge of institutionalization of education thought-making elements, knowledge of education policy, knowledge of architecture of the governance components of the education system of the province and each to several levels. Another subsection was categorized and drawn.