Abstract Objective: Among geographical regions, cities are increasingly becoming champions. Their competition to establish their reputation as the best choice for visitors, investors, and businesses is intensifying. Some cities possess unique features creating a distinct image in people’s minds. The present paper is aimed at identifying the most influential architectural components in city branding of Yazd and subsequently comparing and prioritizing them based on their impact. Method: The research is conducted through using a questionnaire prepared for two groups: 1) a group of 35 specialists and 2) a group of 110 ordinary individuals. The snowball sampling method was used to select the sample for group 1, and random sampling method was employed for group 2. Findings: This applied research is qualitative based on the nature of the data. All components were examined in both statistical populations using the SPSS test, revealing a significant impact on the city branding of Yazd. In terms of prioritization, the components’ degree of influence on the city branding of Yazd city differed between architects and urban planners as well as between ordinary people in two statistical populations. Conclusion: Among ordinary individuals, the architectural texture had the greatest impact on the city branding of Yazd, whereas, among specialists, symbols and landmarks such as elements like windcatchers and awning had the most significant impact on this city’s branding.

Abstract Description: City as a text and urban design as the language of text creation, the constructive dimensions of the city are categorized into two levels: superstructure and deep structure. The superstructure of the city is the result of mental and internal deep constructions. Superstructure has no meaning without regard to deep structure.
Purpose: The current research aims to extract the components that influence the language of the city pattern, and seeks to find out what are the deep structural components of the language of the urban design pattern?
Method: The research has been done by descriptive analytical method and library studies.
Findings: The superstructure patterns identified in the research are mass-space pattern, usage and function pattern, and view pattern. Also, the identified dimensions of deep structures were studied in this research and the independent variables of each dimension that affect the superstructure patterns were identified. In total, 24 independent variables were discovered from urban deep structures and 45 dependent variables were discovered from the set of superstructures.
Conclusion: The most important dimension shaping the settlement is the cultural dimension, followed by the environmental dimension. Also, some superstructure patterns are affected by several deep structure dimensions. The independent variables found in this research were presented in the form of a diagram as influencing components on the language of the urban design pattern. As a strategy, it is recommended that the components found in this research be given special attention as a framework for the final design as a guide for the steps from cognitive studies to the presentation of the plan.

Abstract Problem: This article unfolds a collective educational journey that while initially faced by serious doubts, ultimately received positive feedback from the students in an online urban design workshop. During a rampant global pandemic, one of the two instructors communicating from overseas, who is experienced in teaching face-to-face courses, raised initial pedagogical concerns.
Aims: To remedy these, the two instructors dedicated the first part of the workshop to theorizing urban complexity. Exposure to theory, while less common if not uncommon in design studios, removed the students’ initial misgivings. Gaining student confidence boosted their spirit in crafting idiosyncratic interpretations based on personal memories, and paved the way toward assuming agency, and subsequently integrative learning.
Methods: This technique enabled students to connect discrete structural learning domains to produce more complicated outcomes, and by doing so experienced three states of mind. Melting away initial doubts coincided with thematic arrangement. Boosting confidence through conceptual connectivity and self-discovery, then, resulted in ebullience in designing through purposeful action.
Result: This article contributes to the scanty literature on coping mechanisms in the face of looming uncertainties both for students and instructors in teaching studios.

Abstract Problem: Justice in urban health means the absence of systematic differences in one or more aspects of the health status of citizens or population groups in terms of social, economic and physical environment. In the present study, the city of Urmia has been investigated and analyzed as a focus of studies on the level of realization of the right to health approach to the city and the distribution of health-therapeutic services and functions.
Aims: In terms of its purpose, the current research is in the category of semi-basic, semi-applied research, which is carried out with descriptive and analytical method.
Methods: The methods of collecting information are based on documentary-library methods, observation and field verification (Swara and Cocoso tests).
Findings: Based on the results, the city of Urmia has not acted in a fair manner in terms of the distribution of health-treatment functions and services in accordance with the approach of the right to the city, in spatial planning and allocation.
Conclusion: Regions 4 in the central context and the commercial pole of the city and 2 in the peripheral part of Urmia city have respectively the most favorable and unfavorable environmental conditions and conditions in the matter of enjoying the right to health policies of the city. In the end, based on the findings and the identification of the strengths and weaknesses of the study area in the field of urban development, some targeted and sustainable proposals and actions have been taken to improve the environmental conditions.

Abstract Problem: In a two-way relationship with the surrounding environment, human affects the environment on the one hand and is also under the influence of the environment on the other hand. The quality of the physical environment affects the mental health of individuals, and decreases or increases depression, stress, liveliness, vitality, and other states of individuals.
Objective: This study aims to explain and evaluate the effectiveness of physical factors of open space of residential complexes on the mental health of elderlies.
Method: The method of this study is quantitative, and is among descriptive-analytical studies with correlation type in terms of objective.
Results: Findings indicate a direct and significant relationship between physical components: place desirability, appropriateness with cognitive-perceptual abilities, permeability, geometry, location, and mental health of elderlies. Moreover, all components identified in this study could affect the liveliness, vitality, and mental health of elderlies although the effect levels are different between various studied buildings.

Abstract Goals: The emergence of new issues in various economic, social and political fields, physical and environmental issues in cities, forces urban management to respond effectively and actively. Extensive developments in the Tehran metropolis have led to more attention to urban green space as green infrastructure , and planning for managing the development and protection of urban green areas has been put on the agenda. Therefore, the development policy of this field or use in the future has been in the focus of attention. Therefore, with the aim of identifying the driving forces affecting the future of Tehran's green spaces, this research tries to take an effective step in this direction by using the intellectual base of future research and foresight.
Methods: This study is analytical and exploratory in nature and uses the environmental scanning method based on the STEEP model, document study, holding brainstorming sessions and distributing questionnaires among experts and elites.
Findings: In this research, 32driving forces affecting the future of Tehran's green space in 6 categories, including 3 driving forces in the technological field, 6 driving forces in the demographic and social field, 8 driving forces in the environmental field, 6 driving forces in the economic field, 4driving forces in the political-institutional field and 5 drivers were identified in the field of physical and urban development.
Conclusion: The results of this research show that the environmental, economic and demographic and social axes have a more effective role in the future of the green space of Tehran.

Abstract Aims: Today, the use of artificial intelligence has grown significantly, and is developing as a new field. The main goal of this research is to know the capabilities of artificial intelligence in advancing the design and implementation process in the artificial environment. The practical goal of research is the development and application of the most important achievements of machine learning in the field of design.
Methods: The main research method is "meta-analysis" research in the paradigm of "free research" with a critical approach and basic design, which examines the general knowledge field of this field using broad techniques. Then, to consolidate the literature on the topic, through searching three reliable knowledge bases of this field, we collected articles related to machine learning in the fields of unsupervised learning methods, semi-supervised learning, and reinforcement learning; The most important capacities and shortcomings, and strengths and weaknesses are reviewed.
Findings: Quantitative findings from the combined data indicate that supervised machine learning and directed deep learning can be the best option to recommend in the future of design. While the learning process in deep learning is gradual and slower, supervised machine learning works faster in the testing phase.
Conclusion: The research emphasizes that supervised machine learning is the best option for predicting answers in the design process. But if, in addition to prediction, the issue of creativity in design is desired, deep learning is more efficient.