Architectural Space Research Articles

ALTERNATYWNE PRZESTRZENIE WYSTAWIENNICZE. ANALIZA KOMPARYTYSTYCZNA

The aim of this article is to make a multi-criteria analysis of various exhibition spaces of an originally non-exhibition character and to determine how these spaces affect the selection of works and the exhibition concept. The analysis is based on the exhibitions of art objects at collective exhibitions in unconventional architectural spaces: commercial, post-industrial and in the historic interior. The multi-criteria comparative analysis shows a variety of features of the studied spaces as well as the relationship between architecture and art and their mutual interaction, and the participatory role of the non-exhibition space in the process of creating an exhibition and selecting works has been proven.

HARMONY OF ARCHITECTURE AND MONUMENTAL PAINTING IN THE ART OF UZBEKISTAN

This study explores the harmony between architecture and monumental painting in the art of Uzbekistan. It investigates how architectural forms and decorative elements are integrated with painting techniques to create a cohesive visual language. Through an analysis of historical and contemporary examples, the research elucidates the cultural significance and aesthetic principles underlying this symbiotic relationship. By examining the interplay between architectural space and pictorial composition, this study offers insights into the unique artistic traditions of Uzbekistan and their enduring influence on architectural design and decorative arts.

Adaptability and Interconnectedness in Latin American Innerburbs: An Assessment of the Public/Private Interface in Informal Settlements

An “Innerburb” is an urban structure that emerged between the 1950s and 1980s, settled in rural areas, and is considered the first periphery of the Latin American city. This structure results from socio-spatial and territorial evolutionary processes, constituting the pinnacle of informal evolution. However, despite offering a comprehensive perspective on the informal problem, innerburbs have been scarcely reviewed in the literature. This article explores the Latin American innerburb by adopting as a method a comparative study of the public/private interface in the cases of San Cosme in Lima, Villa Rodolfo Ricciardelli in Buenos Aires and Vila Heliopolis in São Paulo, evaluating their adaptation and interconnection with the city through morphological indicators, using morphological mapping through satellite images as an analytical tool, and using Space Syntax as a topological approach in the analysis of connectivity and visibility indicators. The objective of the research is the detection of morphological patterns that alter the functioning of the public/private interface in innerburbs. The results show that the existence of impermeable facades, the lack of public spaces and the illegal appropriation in the development of informal practices are transgressive adaptability patterns at the micro-scale that affect the interface, drastically limiting the interconnection between the innerburb and the formal fabric, restricting its morphological openness and affecting the development of socioeconomic activities. As a discussion and conclusion, corrective measures for progressive improvement in innerburbs are established, focusing on the adaptability of housing and road space as a means of interconnection between the innerburb and the city.

From restoration to social media: exploring the nexus of architecture, social media and information sharing behaviours

PurposeThis study aims to explore the impact of architecture on digital communication mediums, focusing on how social media shapes the public perception and discussion of architectural spaces. It specifically examines the case of the Basilica Cistern/Istanbul, analysing social media interactions post-restoration.Design/methodology/approachUsing newspaper archive scanning and survey technique, this study observed public content on Instagram focusing on the post-restoration period of the Basilica Cistern. 406 (283 valid) people who visited the Cistern and shared their experiences on Instagram between August 2022 and January 2023 participated in a survey. The analysis utilized Python for advanced correlation studies, enabling an in-depth exploration of the interplay between architectural features and social media sharing behaviours.FindingsThe analysis revealed that historical significance, lighting elements, role as a photographic backdrop significantly influenced sharing behaviours. Correlations were found between specific spatial features of the cistern and various sharing motivations, such as communication with people, personal gain, and popularity. The study highlights a diverse spectrum of motivations among users, emphasizing the relationship between these motivations and spatial features.Research limitations/implicationsThis study underscores the necessity for further inquiry into the intricate dynamics among digital communication, architectural spaces, and user motivations. Limitations include potential challenges in gathering data from social media due to concerns of cyber fraud and the misuse of hashtags.Originality/valueThis research offers novel insights into the interplay between digital communication and architecture. It underscores the potential of digital platforms as valuable data sources for architectural theorizing and practice, particularly in understanding how restorations and architectural changes are perceived and discussed in the digital space.

Decoupled differentiable graph neural architecture search

The differentiable graph neural architecture search (GNAS) effectively designs graph neural networks (GNNs) efficiently and automatically with excellent performance based on different graph data distributions. Given a GNN search space containing multiple GNN component operation candidates, the differentiable GNAS method builds a mixed supernet using learnable architecture parameters multiplied by the GNN component operation candidates. When the mixed supernet completes optimization, the mixed supernet is pruned based on the best architecture parameters to efficiently identify the optimal GNN architecture in the GNN search space. However, the multiplicative relationship between the architecture parameters and the GNN component operation candidates introduces a coupled optimization bias into the weight optimization process of the mixed supernet GNN component operation candidates. This bias results in differentiable GNAS performance degradation. To solve the problem of coupled optimization bias in the previous differentiable GNAS method, we propose the Decoupled Differentiable Graph Neural Architecture Search (D2GNAS). It utilizes the Gumbel distribution as a bridge to decouple the weights optimization of supernet GNN component candidate operation and architecture parameters for constructing the decoupled differentiable GNN architecture sampler. The sampler is capable of selecting promising GNN architectures based on architecture parameters treated as sampling probabilities, and it is further optimized through the validation gradients derived from the sampled GNN architectures. Simultaneously, D2GNAS builds a single-path supernet with a pruning strategy to compress the supernet progressively to improve search efficiency further. We conduct extensive experiments on multiple benchmark graphs. The experimental findings demonstrate that D2GNAS outperforms all established baseline methods, both manual GNN and GNAS methods, in terms of performance. Additionally, D2GNAS has a lower time complexity than previous differentiable GNAS methods. Based on the fair GNN search space, it achieves an average 5x efficiency improvement. Codes are available at https://github.com/AutoMachine0/D2GNAS.

Understanding visitor flow and behaviour in developing tourism-service-oriented villages by space syntax methodologies: a case study of Tabian Rural Section of Qingshan Village, Hangzhou

ABSTRACT In the built environment (BE) of tourism-service-oriented villages, understanding visitor flow volumes and behaviours is crucial for guiding space revitalization and tourism management. This research uncovers quantitative relationships between visitor flow volume, spatial visual exposure, and visitors’ behaviour at 12 sites in the Tabian Rural Section of Qingshan Village, a typical tourism service-oriented village in Hangzhou. The methodologies employed in this study are based on two space syntax algorithms: 3-D isovist analysis and agent-based models (ABMs). Visual Exposure Rates (VERs) in 3-D isovists along visitors’ routes were calculated using parametric programming, and visitor flow simulation was conducted using two ABMs. Real-world visitor volumes (RWFVs) and visitors’ behaviors were also recorded during an in-situ survey. A comprehensive correlation analysis revealed multiple associations. The results demonstrated that combined simulations from ABM I, and VERs explained 50.5% of the overall variability in RWFVs. Notably, VERs were found to be associated with visitors’ behaviours of photography and seating, while the outputs from ABM I showed a moderate correlation with RWFVs. This study innovatively combines space syntax models for extended application in the research of rural BEs, providing guidance for optimizing strategies to improve spatial configuration in homogeneous villages.

Absolute Zero – Revealing the Void

Which comes first, the walls or the space? The discussion in this paper explores the significance of the void in the development of innovative architectural space. It challenges the traditional perception that only ‘positive’ elements, such as walls, generate meaningful form; the void being diminished in the role of resultant ‘negative’ space. If our design process concentrates on the object as the generator of interior space, then, as is proposed in the paper, our ability to develop and communicate our ideas is limited by the inherent meaning of that object. If, however, we come to accept the symbolic language of materiality, then, as interior architects, we will invert this process and explore the subject meaning of our ideas before defining their form. This proposal is illustrated with reference to Daniel Libeskind, Coop Himmmelb[l]au, Michaelangelo, the vanishing point, the blank page, and the absent North Pole. Oppositional relationships are noted as existing within the symbiotic framework of the void; a place where we strip away preconceived meaning in order to find the zero- point of our ideas. In so doing, the negative is inverted and the void becomes a meaningful generator of architectural form, in a design process that enables us to define our intentions beyond the inherent influence of the tangible object.

An automated multi-layer perceptron discriminative neural network based on Bayesian optimization achieves high-precision one-source single-snapshot direction-of-arrival estimation

This paper proposes an innovative global solution which is a pioneering work applying automated machine learning algorithms to remarkable precision sparse underwater direction-of-arrival (DOA) estimation that views the subaquatic sparse-sampling DOA estimation problem as a classification prediction task. The proposed solution, termed automated multi-layer perceptron discriminative neural network (AutoMPDNN), is built upon a Bayesian optimization framework. AutoMPDNN transforms sparsely sampled time-domain signals into the complex domain, preserving essential components in a one-source single-snapshot scenario. Leveraging Bayesian optimization principles, the algorithm embeds necessary hyperparameters into the loss function, effectively defining it as a maximum likelihood problem using the upper confidence bound function and incorporating sparse signal features. We also explore the model space architecture and introduce variants of AutoMPDNN, denoted as AutoMPDNNs_ln (n = 2,3,4). Through a series of plane wave simulation experiments, it is demonstrated that AutoMPDNN achieves the highest prediction performance for one-source single-snapshot scenarios compared to classical DOA estimation algorithms that incorporate sparse representation approaches, as well as contemporary deep learning DOA methods under varying conditions.

Creative Movement and Anti-Gentrification: Learning from Los Tjihapit Market's Coffee in Bandung

The phenomenon of gentrification, driven by the presence of the creative class, is a consequence of the global implementation of the Creative City concept. Bandung has adopted this concept, and one of the areas developed by the creative class is the Cihapit Market area. This article examines how the "creative" community, specifically Kopi Pasar Los Tjihapit, sustains its business amidst gentrification through a placekeeping strategy. Participatory qualitative descriptive research methods were employed to explore the role of architectural space as part of the placekeeping strategy. Five strategies were identified: 1) zoning to support maintenance, 2) collaboration spaces for various partnerships, 3) space flexibility through collective decision-making, 4) collaborative spaces to encourage community involvement, and 5) coordination of all aspects to preserve the public market character. In conclusion, the success of creative placekeeping strategies in architectural spaces combines non-technical aspects such as community enthusiasm with technical aspects such as the arrangement of physical architectural elements.

Exploring Ecological Relationality Through Architectural Practice

This practice-led research article explores how post-humanist and eco-feminist perspectives of entanglement and relationality challenge human exceptionalism as a basis for making architecture in the process of the Alusta research pavilion. Multisensory spatial experience, material circulation and more-than-human temporalities are explored through building a temporary pavilion for multispecies encounters in an urban museum setting. Reflecting on the project, an architectural space is understood as a continuous process of becoming enacted by various human and nonhuman forces instead of as a stable object with a sole human author. Architecture is reimagined as part of the web of care sustaining all life.

Racist dogs and classist rats?

In cities across the world, animals reflect, reproduce and transform urban inequalities – yet their role in mediating social hierarchies remains undertheorized. Urban scholars have begun to highlight the importance of infrastructures and technologies in configuring access to essential goods and services. While this research provides key insights into how non-human entities mediate unequal relations, it has largely overlooked how certain animals – „political animals“ – also co-produce inequalities. This article focuses on two critical urban domains, security and public health, that are often characterized by stark inequalities, and takes the role of key animals within these domains – dogs and rats, respectively – as a new analytical entry-point. Security dogs are socialized to identify threatening individuals on the basis of classed and raced markers. Rats thrive in upscale neighborhoods with historical architecture and abundant green space – yet the public health risks and the stigma associated with these rodents may disproportionately affect low-income residents. Drawing on research on security dogs in Kingston, Jamaica and rats in Amsterdam, this talk discusses the role of animals in the formation of sociospatial boundaries, and the distribution of resources and risks across urban spaces and populations. Focusing on the interactions these two types of „political animals“ have with both humans and infrastructure, it sets out a research agenda for studying how animals’ everyday encounters with their cultural and material environments combine to result in (in-)equitable social outcomes.

The Impact of Spatial Configuration on Perceived Accessibility of Urban Parks Based on Space Syntax and Users' Responses

The Impact of Spatial Configuration on Perceived Accessibility of Urban Parks Based on Space Syntax and Users' Responses

DNA Family: Boosting Weight-Sharing NAS With Block-Wise Supervisions.

Neural Architecture Search (NAS), aiming at automatically designing neural architectures by machines, has been considered a key step toward automatic machine learning. One notable NAS branch is the weight-sharing NAS, which significantly improves search efficiency and allows NAS algorithms to run on ordinary computers. Despite receiving high expectations, this category of methods suffers from low search effectiveness. By employing a generalization boundedness tool, we demonstrate that the devil behind this drawback is the untrustworthy architecture rating with the oversized search space of the possible architectures. Addressing this problem, we modularize a large search space into blocks with small search spaces and develop a family of models with the distilling neural architecture (DNA) techniques. These proposed models, namely a DNA family, are capable of resolving multiple dilemmas of the weight-sharing NAS, such as scalability, efficiency, and multi-modal compatibility. Our proposed DNA models can rate all architecture candidates, as opposed to previous works that can only access a sub- search space using heuristic algorithms. Moreover, under a certain computational complexity constraint, our method can seek architectures with different depths and widths. Extensive experimental evaluations show that our models achieve state-of-the-art top-1 accuracy of 78.9% and 83.6% on ImageNet for a mobile convolutional network and a small vision transformer, respectively. Additionally, we provide in-depth empirical analysis and insights into neural architecture ratings.

Optimization for bilevel spatial configuration of underground space surrounding high-speed railway station in China from the perspective of urban morphology

The rapid growth of high-speed railways has led to the development of underground spaces surrounding high-speed railway stations (USSHRSs). The evolution of USSHRS has enhanced the space utilization efficiency. As USSHRSs expand, the layout of the underground connectivity network becomes increasingly intricate. Additionally, pedestrian behavior in USSHRSs transitions from mere passing to longer stays, and its spatial configuration becomes more difficult to evaluate. To date, studies have mostly focused on the structural analysis or inner underground space relationship of USSHRSs. A research gap exists in the field of USSHRS spatial configuration from the perspective of urban development. To fill this research gap, this study focused on the spatial configuration of the USSHRS from the perspective of urban morphology and established a quantitative analysis method for USSHRSs at both global and local levels. At the global level, we devised a method for measuring the USSHRS spatial configuration using pedestrian composite accessibility based on a complex network. At the local level, we used space syntax to study the inner spatial configuration problems of USSHRSs. Finally, we used the Shanghai Hongqiao Station (Shanghai, China) as a case study. The results revealed that the spatial configuration optimization of the USSHRS must improve the connectivity efficiency of the USSHRS, and the corresponding functional layout should also be optimized towards a centralized layout. This study aims to provide decision-making support for the planning and layout of complicated USSHRS and to highlight the role of USSHRS in urban sustainable development.

Enhancing Architectural Space through AI-Driven Ideation: A Case Study of Future Iranian-Traditional City

Artificial intelligence is an evolving technology that has drawn huge economic and social, educational benefits for the future. The revolutionary potential of this technology is boundless, as it can transform how humans live, work, learn, discover, and interact with each other. This research aims to investigate the theoretical foundations of environmental psychology, identify the characteristics of the appropriate architectural space, and then investigate the effect of using artificial intelligence in creating the appropriate architectural space from a formal aspect. The research method is descriptive-analytical and of a qualitative type, which was done by studying library sources and then logically analyzing the data. The research tool is artificial intelligence Midjourny and Dall.e3, which has been introduced for some time in creating artistic images from input words, and prompts. It has been the focus of various artists and architects. It can be said that with architectural conceptual plans, the future will become a reality differently, and they can positively influence the creativity of architects and create futures that most people will not think of today. The use of these images in creating accessible spaces is only one example of the use of artificial intelligence in the architectural design process and it can inspire architectural researchers in various fields.

Enhancing spatial accessibility of tourist spots in Al Kharj city through space syntax analysis

The tourism industry plays a pivotal role in the economic growth and cultural enrichment of cities. Urban regeneration has been considered as a key focus of urban tourism development. This study investigates the application of space syntax as an analytical and design tool in urban regeneration efforts, specifically focusing on Al Kharj City, Saudi Arabia, as a burgeoning tourist destination. The research aims to enhance the spatial accessibility of tourist spots in Al Kharj through space syntax analysis, addressing existing gaps in understanding and optimizing accessibility within the city. By integrating space syntax analysis into urban planning processes, this study seeks to inform stakeholders about the importance of spatial accessibility in enhancing the visitors’ experience and fostering sustainable urban development. Through a multi-scale approach and advanced analytical techniques, the study provides insights into the complex relationships between spatial structures, economic activities, and functional distributions, offering recommendations for improving accessibility and optimizing the spatial distribution of tourist services in Al Kharj. Integrating spatial analysis into urban planning, enhancing connectivity and integration, promoting community involvement, addressing spatial disparities, and implementing evidence-based interventions could result in a more accessible and inclusive urban environment for the enhancement of urban tourism.

The Flag as a Symbol and Vision of Peace, Democracy, and Nation-Building

The design of the flag of Bosnia and Herzegovina (B&H) illustrates both the objectives and limitations of intentional design’s role in national healing and state building following violent conflict. The architecture and design of public buildings, spaces, and symbols can facilitate sociability or reinforce segregation and hostility. This analysis contends that design, especially of public symbols intended to evoke emotions and unity, can facilitate healing. Yet in this case, the flag's design ignores the conflict, assumes a utopia, thus failing to move society to reconciliation.

Exploring Urban Service Location Suitability: Mapping Social Behavior Dynamics with Space Syntax Theory

Assessing urban service locations is a key issue within city planning, integral to promoting the well-being of citizens, and ensuring effective urban development. However, many current approaches emphasize spatial analysis focused solely on physical attributes, neglecting the equally vital social dimensions essential for enhancing inhabitants’ comfort and quality of life. When social factors are considered, they tend to operate at smaller scales. This paper addresses this gap by prioritizing integrating social factors alongside spatial analysis at the community level. By employing space syntax theory, this study investigates urban service suitability in Hajjah, a Palestinian urban community, presenting a novel approach in the literature. The research identifies good spots for essential governmental facilities like health clinics and fire stations using axial map analysis. It also suggests reallocation for some schools. Additionally, it shows ways to improve the placement of community amenities, finding ideal park locations but suboptimal mosque placements. Commercial services also exhibit areas for enhancement including gas stations and shops. The insights from this research can offer policymakers and planners insights to create more efficient, equitable, and accessible cities. The research approach incorporates social behavior dynamics into spatial analysis, promoting inclusive urban planning.

Residential urban heritage space identification, delimitation, and potential assessment model based on space syntax

In the era of post-modernization, profound transformations in urban spaces have led to significant shifts in the spatial composition paradigms of contemporary urban heritage. Research on this process is crucial for elucidating the spatial pathways and compositional changes in the modernization transformation of urban heritage. This study aims to establish identification indicators and assessment systems for the spatial structure of urban residential environments exhibiting historical characteristics and heritage potential through a comparative analysis of residential urban heritage spatial paradigms in historic cities in China and Japan. First, grounded in space syntax theory, this study selected residential urban heritage in Suzhou’s Pingjiang Historic District and Uji’s Nakauji District as research cases. Utilizing road network data, this study analyzed the Life Integration (Int.VR1000) and Global Integration (Int.VR5000) of urban heritage spaces, thereby constructing a spatial topology system for heritage spaces. Second, the study employed urban spatial entropy indicators, such as architectural density entropy, spatial morphology entropy, and function mixing entropy, to quantitatively describe the spatial structure, consequently establishing a heritage space morphological structure indicator system. Finally, spatial clustering methods are used to integrate the spatial topology system with the morphological structure indicator system, resulting in a feature model for residential urban heritage spaces. The research results indicate that the transformation path of residential space paradigms is mainly influenced by spatial topology, affecting the structure of residential heritage spaces in three aspects: functional layout, building density, and spatial form. This phenomenon, in turn, impacts population distribution and the migration of living spaces. However, at the same time, the “resistance effect” of street and lane spaces and the limitations of architectural forms on spatial functions have protected the integrity and authenticity of the internal space.

Mapping semantic space: Exploring the higher-order structure of word meaning

Multiple representation theories posit that concepts are represented via a combination of properties derived from sensorimotor, affective, and linguistic experiences. Recently, it has been proposed that information derived from social experience, or socialness, represents another key aspect of conceptual representation. How these various dimensions interact to form a coherent conceptual space has yet to be fully explored. To address this, we capitalized on openly available word property norms for 6339 words and conducted a large-scale investigation into the relationships between 18 dimensions. An exploratory factor analysis reduced the dimensions to six higher-order factors: sub-lexical, distributional, visuotactile, body action, affective and social interaction. All these factors explained unique variance in performance on lexical and semantic tasks, demonstrating that they make important contributions to the representation of word meaning. An important and novel finding was that the socialness dimension clustered with the auditory modality and with mouth and head actions. We suggest this reflects experiential learning from verbal interpersonal interactions. Moreover, formally modelling the network structure of semantic space revealed pairwise partial correlations between most dimensions and highlighted the centrality of the interoception dimension. Altogether, these findings provide new insights into the architecture of conceptual space, including the importance of inner and social experience, and highlight promising avenues for future research.