Architectural Representation Research Articles

Exploring Islamic Vision on the Environmental Architecture of Traditional Javanese Landscape: Study of Thematic Tafseer Perspective

This article examines and explores Islamic visions of environmental architecture and traditional Javanese houses (joglo) from the Qur'anic perspective. This qualitative research with a descriptive method seeks to analyse the values and Islamic vision of the Joglo house architecture by exploring several data sources, both field data and literature data. The results of this study indicate that the architectural elements of the joglo house contain philosophical ideas that are relevant to the Islamic visions in the Qur'an, such as; pendapa (containing the philosophical meaning of the openness principle), pringgitan (principle of equality), dalem (principle of privacy), senthong (principle of respect), gandok (principle of food security), and pawon (use of firewood) as for the suitability of philosophical ideas with the Islamic vision in the architectural elements of the environment, namely sawo (containing the philosophical meaning of the goodness principle), jambu dersono (the principle of sharing), belimbing lingsir (the principle of remembering God), papaya (the principle of self-introspection), and beringin (the principle of knowing the origin). In short, the joglo house building reflects a house that can adapt to the environment and nature. Therefore, joglo is a representation of house architecture that can combine natural elements that are outward and inward, thus creating a comprehensive and balanced religious value.

VALORIZING CULTURAL HERITAGE BY EMPLOYING DIGITAL TECHNOLOGIES FOR SURVEY AND COMMUNICATION: THE CHURCH OF SAN VINCENZO FERRERI

Abstract. This paper proposes a reflection on the role of digital technologies as a tool to know and enhance architectural and artistic heritage through non-invasive modalities and technologies. The article is part of the broader research work on the closed churches of Naples’s historic center, with the Church of S. Vincenzo Ferreri as the case study of this experimentation. The church still has an extremely rich decorative apparatus deriving from various stratifications. However, it is seldom open to the public only when exhibitions and events are hosted. The paper will comply with the foundational concepts of survey and digital architectural representation in the interpretation processes of the architectural heritage to evaluate the validity of alternative fruition techniques aimed at expanding the knowledge of this heritage to the community.

COMPOSITIONAL MODELS FOR THE INTERNET OF THINGS

AbstractThe modularity of components has enhanced the ability to create IoT systems by composing them from off the shelf. However, the breadth of technological choices and capabilities of component devices has made designing these systems harder to select, compose, implement and test, especially for dynamic systems. In this paper, we adopt formal tools from category theory (CT), a branch of mathematics whose central tenet is compositionality, to generate models for IoT systems. More specifically, we introduce a port-graph operad to represent the architectural designs of IoT systems. We use presheaf categories to construct generic IoT schemas to support modularity. Given this information, we briefly describe its relationship to control strategies of dynamical systems that model the interaction of components. Our approach balances genericity and specificity, providing interlinked schematic representations of system architecture and component representation.

Artistic Craftsmanship and Architectural Representation of Newar Rituals in the Heritages: Study of Krishna Mandir and Adinatha

Artistic-architectural craftsmanship in and around the Krishna Mandir in Patan and Adinath Temple in Chovar Kirtipur are based on myth making of the factual and fictional world representation of the history of art and artistic development. Arts, performances and activities of the god-goddesses carved in the statues and portraits reflected there in different positions are researchable. Erotic activities carved in the statues, tudals and roofs expose then activities of gods-goddesses that reflect the history of our ancestor’s and the present ritual groups worship there on the statue with certain expectations as they believe that the honor of gods-goddesses is to fulfill their dreams and desires with their blessings. The objective of this article is to show the importance of historical arts and architectural craftsmanship-based activities that create the relationship among nature, religion and human-non human activities. To achieve the research goal, this study centers in ritual activities and artistic representation on the historical places of Adinath Temple in Kirtipur and Krishna Mandir at Patan in Nepal. This researcher applies Cultural and Environmental study methods through field visit applying interview-based technique. Finding of this paper is that the carving nature and carved portraits in and around Krishna Mandir and Adinath Temple are reflections of the socio-cultural activities connected with cultural history.

Between the Retina and the Celestial Dome: Challenging the scaffolding of spatial imagination

Taking as a starting point French artist Marcel Duchamp’s preoccupation with a poetic portrayal of stereoscopic vision and the red and blue expansion of depth in the technique of the anaglyph, Between the Retina and the Celestial Dome playfully challenges the disciplinary constraints and conventions of spatial thinking. The text takes the form of shorter or lengthier annotations on a twin ‘essayist drawing’ that exists in two versions: a hand-drawn gilding on parchment and a digital film. It proposes that our understanding of visual perception in combination with the perceived immediate environment and its expansion in the cosmos creates an underlying matrix that shapes our scientific and philosophical thinking and projects itself onto built form: an intellectual ‘scaffolding’ on which spatial thought is erected. This scaffolding is not one or constant, but shape-shifts historically, geographically and sociopolitically, affecting not only how we see but also how we conceive, design and construct spatial structures. Since the invention of perspective during the Renaissance, orthographic projection became a potent and often unquestioned scaffolding for architectural thought and representation. Between the Retina and the Celestial Dome uses the drawing’s playful character, which does not follow the rules of normative architectural representation, to question the forgotten, implicit or taken-for-granted aspects of orthographic projection: the curvilinear image created on each retina; stereopsis, how depth is formed by the combination of images on two eyes; and the existence of the flat picture plane. In search of an alternative scaffolding of architectural representation, the collection of drawn figures on the parchment and the digital film refers to the physiology of vision and stereoscopy; the picturing of the celestial dome in religion and popular astronomy; and specific instances of domed structures in architectural history.

Intelliot: a smart IoT environment

This paper examines classic cloud-based IoT systems, typically centered on a centralized IoT platform where data is uploaded for further processing. Next-generation IoT applications are shown, incorporating technologies such as artificial intelligence, augmented reality and distributed registry to implement semi-autonomous vehicle behavior, user management and machine-to-machine interaction in a trusted manner. It is emphasized that such applications require more dynamic IoT environments that can run locally without the need to connect to the cloud. The article describes three use cases for next-generation IoT applications — in agriculture (autonomous management of fleets of agricultural machines), healthcare (IoT for remote patient monitoring) and industry (autonomous interaction between production machines). The authors identified five key component groups of a high-level representation of the IntellIoT logic architecture, which includes the five necessary components to address the identified challenges and enable the development of next-generation IoT applications. Three key concepts (Collaborative IoT, Human-in-the-loop, and Trustworthiness) that occupy an important place in the IntellIoT architecture were taken as benchmarks. The authors present current research on key factors for implementing the next generation IoT concept (the IntellIoT approach) and highlight relevant research challenges for future research on distributed, self-managed, semi-autonomous IoT applications in HITL. The paper outlines prospects for future work to improve the efficiency and reliability of computing and communication infrastructure.

Neural Architecture Search via Proxy Validation.

This paper searches for the optimal neural architecture by minimizing a proxy of validation loss. Existing neural architecture search (NAS) methods used to discover the optimal neural architecture that best fits the validation examples given the up-to-date network weights. These intermediate validation results are invaluable but have not been fully explored. We propose to approximate the validation loss landscape by learning a mapping from neural architectures to their corresponding validate losses. The optimal neural architecture thus can be easily identified as the minimum of this proxy validation loss landscape. To improve the efficiency, a novel architecture sampling strategy is developed for the approximation of the proxy validation loss landscape. We also propose an operation importance weight (OIW) to balance the randomness and certainty of architecture sampling. The representation of neural architecture is learned through a graph autoencoder (GAE) over both architectures sampled during search and randomly generated architectures. We provide theoretical analyses on the validation loss estimator learned with our sampling strategy. Experimental results demonstrate that the proposed proxy validation loss landscape can be effective in both the differentiable NAS and the evolutionary-algorithm-based (EA-based) NAS.

Representing the photobiological dimension of light in northern architecture

Daylight can enhance the quality and inhabitability of architecture through a better relationship with the exterior environment, especially by its intensity, chromaticity and ability to synchronize the human circadian clock. Daylight integration in architecture remains a challenge in Nunavik (Quebec, Canada) due to its subarctic climate, photoperiod and solar geometry. The objective of this research is to implement photobiological metrics of light in architectural representations by isolating the photopic (daytime vision) and melanopic (circadian clock) portions of the electromagnetic spectrum, and to spatialize daylight and artificial light in relation to landscapes and indoor architectural spaces. An automated and low-cost capture tool based on Raspberry Pi microcomputers and Camera Modules (RPiCM) captures high dynamic range images, which accurately measure luminance to render human perception. Absolute photopic luminance maps (cd/m2) are supplemented with false colour displays of photopic/melanopic contents of light regarding building surface materials. The research develops photometric captures of absolute photopic and melanopic illuminance (lux, EML). Photobiological metrics of light are integrated into a set of physical properties of lighting patterns to perform light assessments and are ultimately represented as a graphical display to help designers and researchers to evaluate architectural interior–exterior relationships through daylight qualities.

An architecture decomposition method of pneumatic catapult system based on OPM and DSM

The architecture strategy of the Unmanned Aerial Vehicle (UAV) pneumatic launch system should continue to evolve to adapt to complex and variable operating environments. Architecture representation, decomposition perspective, and cluster analysis play a vital role in the early phase of system architecture development. In order for the system to emerge anticipated and desirable intrinsic functional properties, an architecture decomposition method based on the Object-Process Methodology (OPM) and Design Structure Matrix (DSM) is put forward in this paper. The OPM is proposed to model the UAV launch process formally, and the matrix representation of the architecture of the pneumatic launch system is established. After the extension of the definition and operations of DSM, with the Idicula-Gutierrez-Thebeau Algorithm plus (IGTA + ) clustering algorithm, the transformation of the pneumatic launch system architecture from process decomposition to function decomposition is demonstrated in this paper. The analysis shows that the architecture decomposition of the pneumatic launch system meets the functional requirements of stakeholders.

Augmented reality experience in an architectural design studio.

Thanks to the developing technology, different methods and tools are used in architectural representation, and architects contribute to developing these tools. Architects can easily model their designs with computer technologies and even make them visible in the environment with augmented reality technologies. Also, it is thought that these technologies will become widespread in basic architectural education over time. This study conducted a practice at the undergraduate architecture level using augmented reality technology.Within the scope of the study, the predisposition of students who experience augmented reality technologies to new representation, gender, course period, familiarity with playing computer games, the effect of computer programs that they can use in their previous augmented reality experience and designs if any, and the correlation between them has been tried to be revealed with this study. In this context, a study was carried out with thirteen students in the architectural design studio. Students were expected to parametrically design indoor exhibition elements using Rhinoceros 3D software and the Grasshopper plugin in the study. Then, an experimental augmented reality study was conducted with the Fologram, in which the students transferred these virtual exhibition elements they designed to the real indoors and reshaped them according to the space. Afterwards, a questionnaire consisting of five independent and ten dependent variables was applied to the students. The survey results were analysed with the IBM SPSS Statistics program. According to the results obtained, significant results were determined between 4 independent variables and one dependent variable.

MONITORING DATA AGGREGATION OF DYNAMIC SYSTEMS USING INFORMATION TECHNOLOGIES

The subject matter of the article is models, methods and information technologies of monitoring data aggregation. The goal of the article is to determine the best deep learning model for reducing the dimensionality of dynamic systems monitoring data. The following tasks were solved: analysis of existing dimensionality reduction approaches, description of the general architecture of vanilla and variational autoencoders, development of their architecture, development of software for training and testing of autoencoders, conducting research on the performance quality of autoencoders for the problem of dimensionality reduction. The following models and methods were used: data processing and preparation, data dimensionality reduction. The software was developed using the Python language. Scikit-learn, Pandas, PyTorch, NumPy, argparse and others were used as auxiliary libraries. Obtained results: the work presents a classification of models and methods for dimensionality reduction, general reviews of vanilla and variational autoencoders, which include a description of the models, their properties, loss functions and their application to the problem of dimensionality reduction. Custom autoencoder architectures were also created, including visual representations of the autoencoder architecture and descriptions of each component. The software for training and testing autoencoders was developed, the dynamic system monitoring data set, and the steps for pre-training the data set were described. The metric for evaluating the quality of models is also described; the configuration of autoencoders and their training are considered. Conclusions: The vanilla autoencoder recovers the data much better than the variational one. Looking at the fact that the architectures of the autoencoders are the same, except for the peculiarities of the autoencoders, it can be noted that a vanilla autoencoder compresses data better by keeping more useful variables for later recovery from the bottleneck. Additionally, by training on different bottleneck sizes, you can determine the size at which the data is recovered best, which means that the most important variables are preserved. Looking at the results in general, the autoencoders work effectively for the dimensionality reduction task and the data recovery quality metric shows that they recover the data well with an error of 3–4 digits after 0. In conclusion, the vanilla autoencoder is the best deep learning model for aggregating monitoring data of dynamic systems.

Auto-STGCN: Autonomous Spatial-Temporal Graph Convolutional Network Search

In recent years, many spatial-temporal graph convolutional network (STGCN) models are proposed to deal with the spatial-temporal network data forecasting problem. These STGCN models have their own advantages, i.e., each of them puts forward many effective operations and achieves good prediction results in the real applications. If users can effectively utilize and combine these excellent operations integrating the advantages of existing models, then they may obtain more effective STGCN models thus create greater value using existing work. However, they fail to do so due to the lack of domain knowledge, and there is lack of automated system to help users to achieve this goal. In this article, we fill this gap and propose Auto-STGCN algorithm, which makes use of existing models to automatically explore high-performance STGCN model for specific scenarios. Specifically, we design Unified-STGCN framework, which summarizes the operations of existing architectures, and use parameters to control the usage and characteristic attributes of each operation, so as to realize the parameterized representation of the STGCN architecture and the reorganization and fusion of advantages. Then, we present Auto-STGCN, an optimization method based on reinforcement learning, to quickly search the parameter search space provided by Unified-STGCN, and generate optimal STGCN models automatically. Extensive experiments on real-world benchmark datasets show that our Auto-STGCN can find STGCN models superior to existing STGCN models used for search space construction, which demonstrates the effectiveness of our proposed method.

Network Architecture of Verticality Processing in the Human Thalamus.

Thalamic dysfunction in lesions or neurodegeneration may alter verticality perception and lead to postural imbalance and falls. The aim of the current study was to delineate the structural and functional connectivity network architecture of the vestibular representations in the thalamus by multimodal magnetic resonance imaging. Seventy-four patients with acute unilateral isolated thalamic infarcts were studied prospectively with emphasis on the perception of verticality (tilts of the subjective visual vertical [SVV]). We used multivariate lesion-symptom mapping based on support-vector regression to determine the thalamic nuclei associated with ipsiversive and contraversive tilts of the SVV. The lesion maps were used to evaluate the white matter disconnection and whole brain functional connectivity in healthy subjects. Contraversive SVV tilts were associated with lesions of the ventral posterior lateral/medial, ventral lateral, medial pulvinar, and medial central/parafascicular nuclei. Clusters associated with ipsiversive tilts were located inferiorly (ventral posterior inferior nucleus) and laterally (ventral lateral, ventral posterior lateral, and reticular nucleus) to these areas. Distinct ascending vestibular brainstem pathways terminated in the subnuclei for ipsi- or contraversive verticality processing. The functional connectivity analysis showed specific patterns of cortical connections with the somatomotor network for lesions with contraversive tilts, and with the core multisensory vestibular representations (areas Ri, OP2-3, Ig, 3av, 2v) for lesions with ipsiversive tilts. The functional specialization may allow both a stable representation of verticality for sensorimotor integration and flexible adaption to sudden changes in the environment. A targeted modulation of this circuitry could be a novel therapeutic strategy for higher level balance disorders of thalamocortical origin. ANN NEUROL 2023.

Knowledge Graph Aided Network Representation and Routing Algorithm for LEO Satellite Networks

The compelling applications of Low earth orbit (LEO) satellite networks in our daily lives have been witnessed in recent years, ranging from weather forecasts to military monitoring. LEO satellite networks have grown in importance as a complement to terrestrial networks aiming at delivering global, ubiquitous communication. However, due to the LEO network topology keeps changing dynamically, the development of efficient routing algorithms becomes one of the challenges in the LEO network. Traditional routing policies hardly solve the rerouting problem caused by link switchover and the high calculation cost caused by large-scale irregular satellite topology. In this paper, we propose a knowledge graph-aided representation of satellite network topologies and routing architecture to optimize path selection and calculation cost for lower packet loss ratio and average delay. Moreover, we generate a routing policy by predicting potential relations between data packets and nodes to select the best relay nodes with the maximum probability of forwarding relations. Finally, extensive simulations are performed to evaluate the performance and availability of our proposed algorithm.

Inhabitation, difference, performance: Architectural linearity in three movements

This article questions the temporal and material limitations of architectural representation, as they emerge through the problematic relationship between architectural drawing, considered as a static object of fixed convention and space as an inherently kinetic domain. It reflects on the large-scale drawing Weaving Lines/Looming Narratives (WL/LN, 2013), to propose a way of bringing together the kinetic dimensions of architectural space and architectural drawing. The city is a territorial condition that, since modernity, has come to define a kinetic field of spatial and temporal complexity. The challenges that this complexity entails for architectural drawing are used here to question the fixity of drawing conventions, and expand architecture’s range of concerns to the transitory conditions of space that emerge between the stabilizing effects of order(s) and the spontaneity of events. The question of kinetic space places under new light the discrepancies between the real and the representational by underlining the mobility of both viewer and environment; spectacle and spectator. This article interrogates architectural linearity to propose ways of transversally representing the web of movements that form the contemporary city as well as the making of architectural drawing. Following the deconstructive approaches to the production of meaning of the late twentieth century, and drawing form Catherine Ingraham’s study of architectural linearity, the article frames drawing as a performative practice rather than a systematic language, and a representational field of action rather than order.

A Method for Decoding and Representing Time in Fourdimensional Spaces via Digital Game Environment

The search for novel representation method is one of the critical components of the creative design process. Discoveries in science, such as four-dimensional (4D) spacetime, influenced artists and architects. However, existing representation techniques constrained in two-dimensional (2D) sheets for 4D spacetime for representation is evaluated as a limitation of architecture discipline. Currently, digital game environments are the potential mediums of 4D architectural representation. This study aims to decode and represent time as an entity of 4D spaces. Digital game environment provides the needed flexibility for experimenting in 4D space. Therefore, unity game engine and C# programming are used together with computer aided design (CAD) tools to generate 4D representations. 4D representations are based on two different impressions of time dimension as (1) time dilation and (2) distortion of spacetime. While time dilation is represented via motion blur (mB) script, distortion of spacetime is represented via motion trail (mT) script. As preliminary results, metrics of the time dimension in 4D spatio-temporal representations are introduced. Experimental 4D representations produced via Unity game engine and C# programming are presented to discuss the potential of game environments to be the medium of architectural representation.

The impact of system representation choices on architecting insights

AbstractSystems engineers regularly rely on analysis of early design artifacts like system architecture representations to predict system performance, lifecycle costs, and development schedules, and to support design decision‐making. Recent recognition of challenges in this type of measurement has led to a heightened focus on developing better metrics. Less attention has been paid to the system representations upon which all subsequent analysis is performed. With this study, we demonstrate that choices about how to represent the system can explain variation in measurement, even holding metrics constant. This is important because most of these representation choices remain unarticulated in current practice. To do this, we conduct a controlled experiment where we experimentally manipulated the Design Structure Matrix (DSM) architecture representation of nine crowdsourced robotic arm designs and compared the value and relative ranks of their modularity and complexity. We found statistically significant changes in both value and rank, attributable to differences in choices in the system representation. The direction and magnitude of these changes also differed across modularity and complexity. In addition, some underlying designs seemed to be more robust to representation changes. This suggests an interaction between representation, design, and lifecycle properties. These results emphasize the importance of developing standard guidelines for how to represent system architectures and better documenting their use.

Cami mimarisinde modern ve geleneksel temsil: Üç caminin analitik karşılaştırması Ankara, Türkiye

This article examines three "modern" mosques in Ankara, the capital city of Turkey. Specifically, it researches examples of innovative and authentic mosque architecture, which considerably varies from "Ottoman-type" mosques that heavily dominate the inventory of mosques in Turkey. The Republican period after the Ottoman Empire in Turkey witnessed an ongoing discussion and competition between modern and traditional examples of mosque architecture. Although this problem has been considered in different dimensions, it has generally been discussed by classifying the mosques as "modern" or "traditional" in the academy. It is thought that this classification should be based on the different physical characteristics of mosques, which form the repertoire of tradition in mosque architecture. In this study, the exemplary mosques selected for the inquiry were examined according to 18 different factors that were grouped under six categories considering the physical and interior features of the mosques: namely, mass and facade design, spatial organization, interior forms, architectural program, material selection and ornament details. The research aims to contribute to discussing modern and traditional representation in mosque architecture and clarify ambiguity in understanding and distinguishing between "tradition," "traditional," and "modern," which are essential meanings in mosque architecture.

Learning Reliable Neural Networks with Distributed Architecture Representations

Neural architecture search (NAS) has shown the strong performance of learning neural models automatically in recent years. But most NAS systems are unreliable due to the architecture gap brought by discrete representations of atomic architectures. In this article, we improve the performance and robustness of NAS via narrowing the gap between architecture representations. More specifically, we apply a general contraction mapping to model neural networks with distributed representations (Neural Architecture Search with Distributed Architecture Representations (ArchDAR)). Moreover, for a better search result, we present a joint learning approach to integrating distributed representations with advanced architecture search methods. We implement our ArchDAR in a differentiable architecture search model and test learned architectures on the language modeling task. On the Penn Treebank data, it outperforms a strong baseline significantly by 1.8 perplexity scores. Also, the search process with distributed representations is more stable, which yields a faster structural convergence when it works with the differentiable architecture search model.

Earthly Matters, Earthy Visions: National Architecture Narratives and the Unexpected Culture of Norwegian Rammed Earth Houses

Abstract: This research paper shares the neglected story of rammed earth houses in Norway, with a focus on the past conditions that enabled its craft and emergence. Architectural representations in the country have been inexorably tied to craft traditions and localisms, framed as a marriage of natural materials and the built form; however, wood and stone occupy center stage of this material-oriented ethos. Very little attention is given to old rammed earth building techniques. Beyond tectonic considerations, the paper's aim is to document the value-tinged discourse around the making of rammed earth houses, or jordhus, built at the end of the nineteenth century, between 1920 and 1930, and during the post–World War II building boom. I examine and document the social circumstances and ideologies that caused Norwegian individuals to turn to—and away from—such a material. Based on Asbjørn Klepp's seminal "Jordhus i Norge," as well as Akershus Museum's little-known surveys, building projects in Østland, Vestland, and Sørland are the focus of this study of the social, cultural and technological histories embedded in rammed earth free-standing walls. Notions of sustainability and craft, of vernacular knowledge and home aesthetics are then utilized to qualify and weigh the significance of jordhus for present-day building narratives of Norway, thus shedding new light on established methods for the writing and telling of the country's architectural narratives: in the concluding section, I briefly comment on rammed earth's resurgence in the face of current climate concerns and describe a contemporary case study (Raab Jordhus, 2019) that shows the material's significance for future Norwegian architectural cultures.