Existing project selection models do not consider the Complexity of projects as a selection criterion, while their Complexity may prolong the project duration and even result in its failure. In addition, existing models cannot formulate the aggregate Complexity of the selected projects. The aggregated Complexity is not always equal to summation of Complexity of projects because of possible synergies or conflicts between them may increase or decrease the total Complexity. In this paper, a model is proposed for measuring the aggregate Complexity in the selection of project portfolios. A case study is presented to show the usefulness of the model and its applicability in practice. Moreover, several large-sized numerical examples have been tested showing the capability of the model to solve such problems in logical computational time.

Background and Aim: this study aimed to explore the impact of Objective Complexity and Product of work task on user's interactive information searching behavior.Method: The research population consisted of MSc students of Ferdowsi university of Mashhad enrolled in 2012-13 academic year. In 3 stages of sampling (random stratified, quota, and voluntary sampling), 30 cases were selected. Each of these cases searched 6 different types of simulated work tasks. Students’ Interactive Information searching behavior was measured by “loud thinking reports” and “log files”. Also, reliable questionnaire (Cronbach's alpha=0.88) was applied to measure subjective Complexity. Validity of tools was verified through Faculties of KIS at Ferdowsi university of Mashhad.Results: By increasing level of Objective Complexity, users view more databases, search engines and web OPACs. Also they use more queries and select resources, visit and analyze more results and spend more time during search process. Totally, they feel less satisfaction and success. It was also found that most participants spend more time to search IR systems related to tasks including intellectual product. Also, they iterate queries, use more search facilities, view, analyze and select more search results and resources. At the end, in spite of more interaction, satisfaction and perception of search success were reported not favorable.Conclusion: It is necessary to pay attention to work task characteristics in designing interactive and personalized IR systems. So, recommendations raised from this study are appropriate to improve and develop Interactive IR systems.

Purpose: Aims to identify the role of document readability level and the Objective Complexity of the work task on students' relevance judgment and document ranking.Methods: Quantitative content analysis was utilized to determine the readability level of texts. The statistical population of the research included 2825 graduate students of Shiraz University of Humanities. To determine the sample size, due to time-consuming process of relevance judgment, students’ time constraint, and sample size of similar studies, a non-probability sampling method of voluntary type was used. Two work tasks were designed based on Borland's (2000) Repository of Assigned Search Tasks and experts' opinions. After confirming the validity of the work tasks by the experts, searching through the Persian article databases, including SID, Magiran, and Noormags, four relevant, four partially relevant, and two irrelevant articles were selected by five experts The articles were divided into difficult and very difficult levels by determining their readability levels using Flash-Diani readability formula. In the next step, ten articles related to two work tasks were scored by users in a six-level spectrum (from entirely irrelevant to entirely relevant) then ranked based on the relevance degree (from 1 to 10). Data was analyzed using social science statistical software version 23 (SPSS), and T-tests and Mann-Whitney U tests were conducted.Findings: The results showed significant difference between students' relevance judgment with different readability levels. Students rated documents with difficult readability levels more relevant than documents with very difficult readability levels. In addition, considering the role of readability level on the ranking, there was a significant difference between the rankings of relevance in the documents with different readability levels according to the students. Documents with difficult readability levels were ranked lower in terms of relevance. Therefore, students performed finer on rating documents with difficult readability levels.  Findings about the role of Complexity level of work showed that Objective Complexity of the work task affected the students' relevance judgment. The retrieved documents related to the simple work task were found to be more relevant than the complex work task. Regarding the role of Complexity level of work tasks on ranking, findings  revealed that the level of Objective Complexity of the work task affected the ranking of documents, and the simple work task ranked lower in terms of relevance ranking. Therefore, students performed finer on the simple work task than on the complex work task regarding relevance rating.Conclusion: The role of level of readability of documents and Objective Complexity of the task affected relevance, judgment, and ranking. Further research on the effect of these indicators on relevance judgment  can improve the design of information retrieval systems and increase the quality of the relevance and ranking algorithms.

A B S T R A C T Green city is one of the approaches to sustainable development. “green city” is an environmentally friendly city compatible with the concept of sustainable development and can be used for the welfare and security of its inhabitants. Based on the concept of a “green city,” urban managers try to have the least destructive effect on the ecosystems upon which cities rely. Green city is one of the sustainable development approaches that reduce the environmental footprint of cities. The purpose of this study is to evaluate the situation of Mashhad metropolis in terms of the Objective characteristics of the green city. In this study, 14 indicators of electricity consumption per capita, green space per capita, population density, water availability, sewage availability, superior public transportation network, urban mass transportation, traffic reduction, annual production waste per capita, carbon monoxide, concentration nitrogen dioxide, sulfur dioxide concentration, particulate matter concentration, and air quality were exerted. To determine the importance of research indicators, the Shannon entropy method, and the status of Mashhad city areas in terms of green city indicators, the VIKOR multi-criteria decision-making method has been applied. The results showed that most areas of Mashhad are average and below average in terms of green city characteristics, and only District 9 is in very good condition (0.636). Also, based on the results of this part of the research, District 5, with the value of VIKOR index of 0.969, is in the last rank in terms of Objective characteristics of the green city Extended Abstract Introduction Green city is one of the approaches to sustainable development. A “Green city” is an environmentally friendly city compatible with the concept of sustainable development and can be used for the welfare and security of its inhabitants. Based on the concept of a “green city,” urban managers try to have the least destructive effect on the ecosystems upon which cities rely. Green cities constantly try to manage their environmental effects by reducing waste, increasing recycling, reducing air pollution, increasing population density, developing open urban spaces, and encouraging the development of sustainable local businesses. Green cities were first used to evaluate 30 European cities by the Economist Intelligence Unit (EIU) in 2009 with the financial support of Siemens and the aim of reducing the environmental effects of human activities in cities. In that study, eight indices of carbon dioxide, energy, construction, transportation, water, recycling and land use, air quality, and environmental governance were used. Later, the Economist Intelligence Unit, with the financial support of Siemens, evaluated the status of the green city index in 17 Latin American cities, 15 African cities, 22 major Asian cities, and 27 cities in United States, Canada, Australia, and New Zealand. In recent years, even some Western Islamic scholars have, in various publications, shown that Islam is an ecological religion. In Iran, the issue of protecting the environment has not received much attention regardless of its rich cultural and religious background and its confirmation in Article 50 of the Constitution of the Islamic Republic of Iran. Mashhad is the second metropolis of Iran, located in North-East of Iran, and is one of the counties of Khorasan Razavi Province. According to the 2016 Iranian Population and Housing Census, its population was 3057679 people (The Vice-Presidency of Planning and Development of Mashhad Municipality). In Mashhad, due to several reasons including the presence of Imam Reza Shrine (PBUH) and arrival of millions of pilgrims per year, population growth, increased garbage production (production of 896534 tons of garbage in 2016 (The Vice-Presidency of Planning and Development of Mashhad Municipality), air pollution (increased number of unhealthy days from 46 days per year in 2015 to 88 days in 2016 for sensitive groups and 4 days of unhealthy air for all groups in 2016 (Center for Monitoring Environmental Pollutants of Mashhad Municipality) the 2025 vision of the city has paid attention to the environment in the form of five general Objectives; however, just like the national level, no specific pattern for environmentally-compatible urban development, such as green city, is determined. Analysis of the green city index in Mashhad metropolis can considerably contribute to urban managers and planners in addition to providing a pattern for evaluating the present situation in other cities of Iran and improving the quality of life regardless of the current status of the urban environment in Iranian cities; we can preserve these environments as parts of the natural environment for future generations.   Methodology In terms of its goal, the present study is an applied one; in the study, drawing upon other studies and library sources and considering the conditions of Iran and the metropolis of Mashhad in terms of green city, 14 quantitative indices were exerted. To this end, the required data for the quantitative indices was gathered by library research from the relevant institutions. Next, the weights of quantitative indices were determined using Shannon's entropy. Then, using the VIKOR method of multi-criteria decision-making, the status of various districts of the metropolis of Mashhad in terms of quantitative indices of green city was determined. Finally, the map of the spatial distribution of quantitative indices was drawn using the ARC GIS software package.   Results and discussion In this study, to analyze the status of the metropolis of Mashhad in terms of green city features, 14 quantitative indices were used. Considering the value of the VIKOR index ranges from 0 to 1, various districts of Mashhad can be classified into five categories; very satisfactory, satisfactory, average, unsatisfactory, and very unsatisfactory in terms of quantitative indices of green city. The results of the current situation of Mashhad showed that in terms of Objective indicators of the green city, District 9 of Mashhad metropolis with a value of VIKOR index of 0.056 is in first place, and the seventh region with a value of VIKOR index of 0.433 is in second place. Also, based on the results of this part of the research, District 5, with the value of VIKOR index of 0.969, is in the last rank in terms of Objective characteristics of the green city.   Conclusion Similarly, the results of studies by Afshar (2011) and Shabani et al. (2017) on Tehran metropolis are indicative of the unsatisfactory situation of Tehran (the biggest metropolis of Iran) in terms of green city features. Comparing the results of the studies by Afshar (2011) and Shabani et al. (2017) with the present study on Mashhad (the second biggest metropolis of Iran) reveals the necessity for a comprehensive plan toward achieving green cities. It should be mentioned that, due to the specific conditions of Mashhad metropolis and availability or unavailability of the required data, the indices used in the present study are somewhat different from the ones used by Afshar (2011) and Shabani et al. (2017).   Funding There is no funding support.   Authors’ Contribution All of the authors approved the content of the manuscript and agreed on all aspects of the work.     Conflict of Interest Authors declared no conflict of interest.   Acknowledgments We are grateful to all the scientific

The two terms "Objective" and "subjective" nowadays mean, respectively, "external" and "mental". But these terms in their primary usage in Middle Ages (from Dunes Scotos) have had exactly the opposite of today"s meaning: "Objective" has meant "mental;""" and "subjective" has meant "external". These old (and nowadays completely strange) meanings have been current in philosophical literature, especially in Descartes and his contemporaries, e. g. Spinoza and Berkley. This paper tends to argument that the word "Objective" must be taken as meaning "mental" in Descartes" philosophy (and other philosophers" up to 19th century), and not to confused with its modern meaning (i. e. "external").

Rapid environmental changes and rapid technological advancements, along with wider communication and large volumes of information, have made organizations more complex than ever, and their management has become much more difficult. The purpose of this paper was to identify the most important types of organizational Complexity in the first stage and, secondly, to determine the ranking of organizations based on the Complexity of the three types of service, agriculture, and industry organiztions. The present study in terms of research methodology is quantitative and to analyze data the hierarchical analysis process (AHP) method has been used. The statistical population consists of 16 academic experts that also work at industry, service, or agriculture field. The results showed that the most important complexities in order of importance include: Environmental Complexity (491/0), Structural Complexity (201/0), Technological Complexity (169/0) and information Complexity (140/0). Also, the results showed that the most complex organizations are as follows: industrial organizations (421/0), service organizations (348/0) and agricultural organizations (231/0).