In this paper, we study The estimation of The spatially sparse radio emitter locations via The proposed Quad-tree variational Bayesian expectation maximization (QVBEM) algorithm. Firstly, we assume that The emitters are approximately lie on a uniform grid points in The region under surveillance. The VBEM algorithm is applied and The points exceeding The threshold level are considered as potential targets. Then, The grids are refined around The potential targets via The Quad-tree algorithm and The process is iterated. It allows us to find The location of sparse emitters with much less computational complexity due to The use of fewer grid points. Simulation results show The superiority of The QVBEM to existing methods. The impact of threshold value on The performance of QVBEM is also studied.

The purpose of this study was to identify The language consistency between indexers, authors and taggers in The ERIC and Mendeley databases. This survey was conducted using content analysis methods and techniques to evaluate The language consistency between indexers, authors and taggers in The ERIC and Mendeley databases and also to determine common keywords. The sample for this study was comprised of top twenty journals in The field of Educational Research based on The Journal Citation Reports (JCR) of Web of Science, indexed in The ERIC database in 2014. Finally 499 articles published in The above-mentioned journals in 2014 were chosen as The sample base for The dataset. Note that only articles with author-supported keywords, indexed in The ERIC database and also tagged in The Mendeley database from January 2014 to August 2016 were eligible to be assessed. Descriptors assigned to The articles on The ERIC database and tags associated to The articles on The Mendeley database for The period from January 2014 to August 2016 were extracted. Also authorassigned keywords assigned to all 499 articles were collected. Finally we created a software based on object-oriented programming (OOP) in C++ to analyze The search results. Descriptive statistics and measures, and Thesaural term comparison show that There are important differences in The context of keywords from The three groups. This study demonstrated that There were differences between The tagger, author and professional indexer views of The words used as tags, descriptors, or author-assigned keywords. The results showed that The consistency between The author-supported keywords and user tags of The 499 articles in The Mendeley was 15 percent; while The consistency between descriptors designated to The articles in The ERIC database and user tags associated to The articles on The Mendeley were three percent. On The oTher hand, The consistency between descriptors assigned to The articles in The ERIC database and The author-assigned keywords were 4 percent. Finally, The language consistency between The three above-mentioned groups was 1. 1 percent. Also note that The presence of descriptors in The ERIC Thesaurus was 34 percent, which were more than The author-supported keywords and tags. The findings showed that The consistency between The keywords used by authors and taggers were more than The keywords chosen by indexers and authors, and by indexers and taggers. This means that three sides of The information representation triangle, i. e., indexer, author and tagger are unfamiliar with each oTher’ s language. It is worth noting that tags are useful supplements to controlled vocabularies, since The former provide a means for social organization of knowledge outside The framework of The latter. The low consistency between tags and descriptors in this research indicates that Mendeley users do not use The same terminology as subject specialists who maintain descriptors in The ERIC Thesaurus. FurTher research involving semantic analysis of Mendeley tags may reveal an emerging vocabulary suitable for inclusion in The ERIC Thesaurus as a controlled vocabulary.

Due to The role of The process of maintenance in The production of competitive products by reducing The stop of machines and create a field for most employees, partnership in The guidance and steering this process is essential. It seems that this process, from The perspective of users, can identify The strength points to improve and to upgrade The planning in manufacturing systems, monitoring and measurement. Currently, industries use some time based indexes that is not sufficient for monitoring this process. With regard to The importance of this issue, identify and provide indicators which can monitor The process of maintenance are very important. This paper has attempted to provide indicators to assess The quality of maintenance services with emphasize on time and cost factors as control measures. Using historical studies and research and interviews with industry experts, indicators as The control criteria are introduced to assess The level of quality of service maintenance provision. In this research, The proposed indicators affect The quality of The maintenance process are divided into three sections including: customer demands, maintenance of process and output indicators. The result of its use in The maintenance process of Pars Khodro Co. showed that The performance of this method to assess The level of quality of maintenance process is effective and useful.

Leadership has always been a basic need in human societies and organizations. The purpose of this study was to identify and analyze The factors that cause poisonous leadership in The Disciplinary Command Center of Mazandaran Province. This research was applied in terms of purpose and in terms of implementation method, it was descriptive-survey and correlational. In The qualitative stage, The statistical population consisted of ten university experts who were selected by purposeful and snowball method. In The quantitative stage, all employees of The police command center of Mazandaran province were 480 people. Simple random sampling method was used. The Delphi method was used to identify The factors and The structural equation method with SmartPLS3 software was used to analyze The relationships of The variables. The results showed that The factors that create poisonous leadership in The police command center of Mazandaran province include 47 components in The form of six dimensions (psychological characteristics of The leader, narcissism, authoritarian leadership, offensive supervision, unpredictable behaviors, ambition). The results of structural equations also showed The psychological characteristics of The leader (0. 390), narcissism (0. 362), authoritarian leadership (0. 401), offensive leadership (0. 337), unpredictable behaviors (0. 315) and ambition ( 0. 418) has a positive and significant effect on The creation of poisonous leadership. Finally, it is suggested that through meritocracy, reforming The incentive and punishment system, and monitoring and removing ambiguity from jobs, efforts be made so that if The management shows a desire for poisonous leadership, it will not have a chance to fulfill its demands.

Background: Today, in most hospitals in Iran, There is an extensive database of patient characteristics that includes a large amount of information related to medical, family and medical records. Finding a knowledge model of this information can help to predict The performance of The medical system and improve educational processes. Methods: Data mining techniques are analytical tools that are used to extract meaningful knowledge from a large data set. In this study, The information of 500 people referred to Shahid Bolandian Health Center in Qazvin has been used. In this research, a predicted model has been performed using decision tree data mining methods and neural network and Bayesian network. Results: The decision tree model has The highest accuracy and The Bayesian network has The lowest accuracy in diagnosing diabetic patients, and consequently The decision tree has The least error and The Bayesian network has The highest error. The decision tree model with 95. 68% had The highest accuracy in prediction. Conclusion: Fat has The greatest effect in predicting diabetes and gender has The least effect in predicting diabetes. Based on The decision tree analysis, The rules obtained among The stated characteristics of age and sugar variables have The greatest effect in predicting The occurrence of diabetes (according to software analysis) and by creating a proper diet can prevent this disease Prevented.

Aim and background: Saffron as a strategic commodity and competitive advantage in The development of trade in our beloved country has always been considered by experts and executives. However, There are problems in many parts of The supply chain of this valuable product, The main purpose of this study was to identify and rank The challenges facing The saffron supply chain and provide proposed solutions Method: This research is descriptive and in terms of applied purpose and its nature is correlational. The study population is experts and elites in The production and sale of saffron. The samples were 100 people and The sampling method was purposeful and available. The data collection tool was a questionnaire. Its validity was confirmed by professors and experts. Cronbach's alpha was used to evaluate The reliability of The questionnaires, which was 0. 911 for The whole questionnaire. Research data are analyzed with SPSS and PLS software Findings: Analyzes show that saffron supply chain challenges include final customer challenges, producer challenges and distributor challenges. These challenges are due to pricing, innovation, packaging, quality of raw materials, marketing, competitors, etc., respectively. Conclusion: The results show that according to The path coefficient, it can be said that The most important challenge of The saffron supply chain is The challenges of distributors, followed by The challenges of producers and The challenges of The final customer.

The purpose of this qualitative research is to identify and explain The topics in financial literacy training in Iran using an exploratory approach. For this purpose, 20 semi-structured interviews with experts were conducted in The first stage to identify The topics of financial literacy training, and 36 primary categories were identified in The open coding stage using qualitative content analysis. The identified sub-categories were linked in The axial coding stage and categorized into nine axial categories. In The next step, namely selective coding, The identified central categories were systematically categorized into three general chapters. In The second stage, The fuzzy Delphi technique in two phases was used to achieve group consensus between experts and screening The findings of The first stage. At this stage, The most consensus between The experts was reached in 32 topics. Based on The results, all areas of personal finance are covered under three general topics, including income and savings management, risk management, and cost management. The topics extracted in this study can be utilized to design, codify, and implemented financial literacy training programs in Iran.