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With advancements in digital technology, the field of architectural design has increasingly embraced data and algorithms to enhance design efficiency and quality. Recent advancements in text-to-image (T2I) generation models have enabled the creation of images that correspond to textual descriptions. However, textual descriptions struggle to capture essential style characteristics in style images. In this study, we proposed a method for architectural facade design based on the stable diffusion model (SDM) that combined stylistic images or keywords as input with the structural conditions of content images to generate images with both stylistic and architectural features. By employing the constrastive language-image pre-training (CLIP) image encoder to convert the style image into its initial image embedding and feature extraction from multilayer cross-attention and training optimization to obtain a pretrained image embedding, the proposed method extracts stylistic features from style images and converts them into corresponding embeddings. This process enables the generated images to embody stylistic features and artistic semantic information. Furthermore, the T2I adapter model is employed to use the architectural structure of content images as conditional guidance, thereby ensuring that the generated images exhibit the corresponding structural features. By leveraging these two aspects, the proposed method can decorate architecture with stylistic features from stylistic images while preserving the architectural structure features of content images, resulting in images that reflect the content images after style transformation. Our method is mainly used in architectural design applications. It was capable of generating facade images from flat design drawings, three-dimensional (3D) architectural models, and hand-drawn sketches and has achieved commendable results. [ABSTRACT FROM AUTHOR]

Managing the level-of-detail (LOD) in architectural models is crucial yet challenging, particularly for effective representation and visualization of buildings. Traditional approaches often fail to deliver controllable detail alongside semantic consistency, especially when dealing with noisy and inconsistent inputs. We address these limitations with Co-LOD, a new approach specifically designed for effective LOD management in architectural modeling. Co-LOD employs shape co-analysis to standardize geometric structures across multiple buildings, facilitating the progressive and consistent generation of LODs. This method allows for precise detailing in both individual models and model collections, ensuring semantic integrity. Extensive experiments demonstrate that Co-LOD effectively applies accurate LOD across a variety of architectural inputs, consistently delivering superior detail and quality in LOD representations. [ABSTRACT FROM AUTHOR]

A Viral Infection Risk Indoor Simulator (VIRIS) has been developed to quickly assess and compare mitigations for airborne disease spread. This agent-based simulator combines people movement in an indoor space, viral transmission modelling and detailed architectural design, and it is powered by topologicpy, an open-source Python library. VIRIS generates very fast predictions of the viral concentration and the spatiotemporal infection risk for individuals as they move through a given space. The simulator is validated with data from a courtroom superspreader event. A sensitivity study for unknown parameter values is also performed. We compare several non-pharmaceutical interventions (NPIs) issued in UK government guidance, for two indoor settings: a care home and a supermarket. Additionally, we have developed the user-friendly VIRIS web app that allows quick exploration of diverse scenarios of interest and visualisation, allowing policymakers, architects and space managers to easily design or assess infection risk in an indoor space. [ABSTRACT FROM AUTHOR]

Façade elements, such as windows, doors, balconies, sculptures, and totems, in architectural heritage images with incomplete structures should be automatically reconstructed for applications in 3D analysis, 3D modeling, virtual tourism, city planning, and the protection and reconstruction of architectural heritage. This study segments façade elements of architectural heritage semantically using YOLOv9. A parameterized expression for the semantic façade model is designed. In addition, the façade layer graph (FLG) and element layer graph (ELG) algorithms are developed based on topological, geometric, and structural constraints to automatically reconstruct the semantic façade model for architectural heritages. The results showed that the average precision (AP) and mean intersection over union (MIoU) achieved using YOLOv9 + FLG-ELG are 86.91% and 85.63%, respectively, on the dataset concerning façade elements of architectural heritages. The AP values obtained from the proposed method are 98.5% on the ECP2011 dataset and 95.3% on the Graz2012 dataset. The YOLOv9 + FLG-ELG method automatically reconstructs regular, irregular, and complex façade layouts with high accuracy and robustness. [ABSTRACT FROM AUTHOR]

Technological progress has driven the integration of new technologies in the field of industrial automation, but a structured framework is often lacking to efficiently guide the transition from traditional industries. This article presents the implementation of advanced technologies on FESTO's (MPS-500) modular production system, using the reference architectural model for Industry 4.0 (RAMI 4.0) as a guide for scaling. It highlights the importance of the synergy between information technologies (ITs), which enables the development of a multi-level processing system. This system performs concurrent tasks, thus managing execution and manufacturing through an MES based on requests from the cloud. On the other hand, at a lower level, a fog computing system was integrated, which relieves the processing load by distributing processes locally. In addition, matrix mapping was performed to map the integrated technologies within the context of a reference model, allowing a clear alignment between the different levels of the system. The results show a significant reduction in waiting times between batches and operations, which directly improves productivity and offers greater flexibility, that is crucial for SMEs during their growth and scaling process towards Industry 4.0. [ABSTRACT FROM AUTHOR]

This study describes the process of digitally reconstructing the ancient Korean city of Suwon Hwaseong in 3D utilizing Historic Building Information Modeling (HBIM) resources to accurately represent its wooden architectural heritage. Previous 3D reconstructions of cultural heritage have often prioritized appearance or remained partially disassembled. However, our reconstruction method offers a comprehensive representation of the appearance and the internal structure of wooden architectural heritage, which can be suitable for restoration maintenance. To ensure accuracy in digital restoration, we collected and utilized administrative records and historical materials, including the geography, fortress walls, folk houses, and Haenggung (the temporary palace of the Joseon Dynasty)—drawing from the archive of the Korean Cultural Heritage Service's management records and the 1796 manuscript "Uigwe: Royal Protocols of the Hwaseong Fortress" which documents the construction of the ancient city of Suwon Hwaseong. Extensive architectural records were used to generate HBIM data, which digitized historical records, documents, and drawings to accurately represent the complex layout of the wooden architectural heritage. For the folk houses that lacked design records and the fortress walls that retained their original shape, we performed a digital restoration-based façade modeling. These elements of the ancient city of Suwon Hwaseong were assembled into a 3D model using Unreal Engine (version 5.1.1) to digitally reconstruct the city and enhance its visual representation. The digital restoration content, which utilizes visual effects and precise rendering from a game engine, can be used for the restoration, repair, and maintenance of both appearance and internal structures. [ABSTRACT FROM AUTHOR]

Foundation model has brought unprecedented opportunities and challenges to the military field due to its powerful capabilities in natural language understanding, logical reasoning, and text generation. This paper reviews related technologies of large language models, including architectural and modeling, adaption and fine-tuning, and prompting and learning, as well as the current status of the development of typical multimodal foundation models. It conducts a deep analysis of the characteristics of mainstream domestic and international military application platforms that utilize foundation models, and designs typical task scenarios and capability requirements for military applications of large models. Then, challenges of military foundation models are discussed. Finally, the key common technologies in military applications are summarized. Hopefully, our work can be beneficial for the design of significant military applications based on foundation model technologies and researches of actual combat. [ABSTRACT FROM AUTHOR]

Copyright of South Architecture / Nanfang Jianzhu is the property of South Architecture Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

The purpose of this study is to develop a new architectural model that responds to environmental pollution. The subject of this study is infrastructure buildings related to automobiles, which cause environmental pollution. Parking facilities accommodate several vehicles, necessitating the design of large-scale parking infrastructure. In this study, the parametric design of an energy-independent building was developed targeting the facade of a large-scale parking facility. As basic research for the development of the parametric design, a parking building was planned toward the optimization of parking space. Based on this basic research, a kinetic photovoltaic facade was developed to achieve optimal renewable energy generation from the perspective of eco-friendly architectural design. Energy simulation using building information modeling (BIM) on the kinetic photovoltaic system developed in this study over a period of one year resulted in the generation of a total of 692,386 kWh·year−1. The novelty of this study is the development of a kinetic photovoltaic facade that is oriented according to the optimal tilt angle every month, focusing on the infrastructure. The significance of the kinetic photovoltaic system lies in the fact that it not only maximizes the efficiency of renewable energy generation but also presents a new architectural design model. [ABSTRACT FROM AUTHOR]

The development of precise analytical methodologies, together with the systematic use of verifiable data, aims to raise standards for treatment, risk management, and maintenance programs. This endeavor aims to diminish the frequency of subsequent restoration cycles, thereby positively impacting public spending and fostering the preservation of the authentic characteristics of historical buildings, particularly by mitigating the effects of decay. The Damage Map through Heritage Building Information Modeling (HBIM) project, funded by the National Council for Scientific and Technological Development (CNPq) and Minas Gerais Research Support Foundation (FAPEMIG), both Brazil, aims to establish protocols for risk management in historical buildings, with a focus on decorative stone elements integrated into the construction. For this reason, the stone relief on the façade of the church of St Francis of Assisi in Ouro Preto, Brazil, was chosen as a case study. This paper outlines the data collection methodology applied to study the stone. This approach encompasses historical examinations of restoration cycles, along with preliminary findings derived from extensive fieldwork, conducted by a multidisciplinary team in 2023. It elucidates the data collection stage, employing photography and aerial photogrammetry, ultraviolet fluorescence photography, mobile laser scanning, and thermography. Subsequently, all collected data will be used to construct a diagnostic model within the HBIM. [ABSTRACT FROM AUTHOR]

Cilia are slender, micrometer‐long organelles present on the surface of eukaryotic cells. They function in signaling and locomotion and are constructed by intraflagellar transport (IFT). The assembly of IFT complexes into so‐called IFT trains to initiate ciliary entry at the base of the cilium remains a matter of debate. Here, we use structural modeling to provide an architectural framework for how RabL2 is anchored at the ciliary base via CEP19 before being handed over to IFT trains for ciliary entry. Our models suggest that the N‐terminal domain of CEP43 forms a homo‐dimer to anchor at the subdistal appendages of cilia through a direct interaction with CEP350. A long linker region separates the N‐terminal domain of CEP43 from the C‐terminal domain, which captures CEP19 above the subdistal appendages and close to the distal appendages. Furthermore, we present a structural model for how RabL2‐CEP19 associates with the IFT‐B complex, providing insight into how RabL2 is handed over from CEP19 to the IFT complex. Interestingly, RabL2 association with the IFT‐B complex appears to induce a significant conformational change in the IFT complex via a kink in the coiled‐coils of the IFT81/74 proteins, which may prime the IFT machinery for entry into cilia. [ABSTRACT FROM AUTHOR]

Public participation in architectural heritage protection is a crucial part of promoting the development of heritage conservation. However, even in the same country, different regions protect heritage at different levels. This study, taking national wooden arch corridor bridges as the research object, analyzes the public participation level in wooden arch corridor bridge protection in the last 5 years, studying the factors that influence public participation and the change in rules of public participation caused by geography, providing a theoretical reference for the sustainable development of the protection of wooden arch corridor bridges. The results indicate (1) public participation in the protection of wooden arch corridor bridges has been increasing annually under government guidance; (2) there is a positive correlation between the concentration of wooden arch corridor bridges and the level of public participation; (3) the better the planning is regarding wooden arch corridor bridges and their surrounding areas, the higher the level of public participation, while the lower the level of residents' participation and willing; (4) the higher the development and better the transportation in the areas where wooden arch corridor bridges are located, the higher the level of public participation; and (5) increasing the popularity of wooden arch corridor bridges, as well as the areas they are located in, can enhance public participation. These conclusions and research methods also provide methodological guidance and theoretical support for other public participation in the study of architectural heritage. [ABSTRACT FROM AUTHOR]

Ransomware attacks are becoming increasingly sophisticated, and defensive solutions must necessarily evolve. Unfortunately, automated backup management through validation—critical for data recovery after an attack—and strengthening file server protection are not sufficiently addressed in current protection strategies. To focus on this area, an architectural model has been developed that complements traditional central data storage with an additional high-level file server protection solution. However, in addition to the functional adequacy of file server protection solutions, the measurability of operational performance is also important. In order to validate and evaluate the developed ransomware-proof file server protection, a dynamic performance metric is introduced for comparability, by which the performance results measured on the tested client–server architectures are presented, together with the methodology and results of the measurements. Our results show that the investigated model does not cause any performance degradation when moving sensitive data files and their backups during operation and even shows performance improvements in some frequently used configurations. The result proves that the developed real-time approach provides a solution to this critical problem in terms of the time required to restore key data from backups and to ensure file availability and continuity of accessibility. Based on a review of the literature and available solutions, it is concluded that there is no integrated solution for implementing a similar concept in practice, and therefore, the developed model is a gap-filling in this priority area. [ABSTRACT FROM AUTHOR]

The digital economy, as a key driver of China's economic development and industrial structure transformation, provides a strong impetus for the integrated development of the marine industry. Building on relevant research both domestically and internationally, this study employs programmatic grounded theory coding to analyze the effective case data published on authoritative official websites. We construct a theoretical model and architectural design for the integration of digital economy and marine industry, elucidating the crucial roles of digital infrastructure, digital collaborative service platforms, and digital application scenarios in this integration. We propose the following four integration pathways: digital resource collaborative optimization based on the 'sea–ship–shore–breeding–tourism–management' framework, industry chain optimization led by the seed industry, industrial cluster format optimization based on ecosystems, and land–sea linkage layout optimization driven by application scenarios. These pathways provide scientific theoretical guidance and practical recommendations for the integrated development of China's marine industry in the digital economy era. [ABSTRACT FROM AUTHOR]

This study investigates the geometric modelling of architectural heritage digital twins constructed based on multi-source point cloud data and its effectiveness in structural reinforcement assessment. Particular emphasis has been placed on the use of static stiffness rules to identify areas of structural weakness in the geometric models of digital twins and the need for their reinforcement, in order to prevent potential structural problems and to ensure the long-term preservation of the built heritage. Taking Yingxian wooden pagoda as a study case, based on the collection of multi-source point cloud data, the digital twin geometric model is constructed through fine modelling, decoupling of digital models, and geometric transformation. This enhances the true reflection of the column-architrave structure morphology, providing a more accurate model for structural stress analysis. Based on verifying the accuracy of the digital twin geometric model, the instability conditions are identified through static stiffness rules and the deformation values at multiple points are analyzed, enabling precise identification of weak areas in the column-architrave structure. Two types of reinforcement measures are designed and simulated for the structural weak areas identified through the geometric modelling, and the optimal reinforcement scheme is obtained after detailed analysis, according to which specific adjustments and optimization strategies are proposed to enhance the overall stability and durability of the structure. The results showed that the maximum deformation value of 4.65 mm existed in column M2W23, which required reinforcement. Aluminum reinforcement reduced the deformation to 3.5 mm (24.7% reduction), while CFRP fabric reinforcement was more effective, reducing the deformation to 2.8 mm (39.7% reduction), showing high stability. The research results demonstrate the potential application of digital twin technology in architectural heritage preservation and restoration, providing methodological and empirical guidance for heritage preservation research. [ABSTRACT FROM AUTHOR]

Recent advancements in AI research, particularly in spatial layout generation, highlight its capacity to enhance human creativity by swiftly providing architects with numerous alternatives during the pre-design phase. The complexity of architectural design data, characterized by multifaceted elements and varying representations, presents significant challenges in creating uniform and robust datasets. This study addresses this challenge by developing a robust training dataset specifically tailored for AI-driven spatial layout generation in architecture. An algorithm capable of extracting spatial relationship diagrams from raster-based floor plan images and converting them into vector-based data was introduced. Through extensive web crawling, a dataset comprising 10,000 data rows, categorized into 21 classes and three spatial relationship categories, was collected. When tested with the You-Only-Look-Once (YOLO) model, the detection rate was 99%, the mean average precision was 85%, and the MIoU was 74.2%. The development of this robust training dataset holds significant potential to advance knowledge-based artificial intelligence design automation studies, paving the way for further innovation in architectural design. [ABSTRACT FROM AUTHOR]

Digital Twins (DT) play a key role in Industry 4.0 applications, and the technology is in the process of being mature. Since its conceptualisation, it has been heavily contextualised and often misinterpreted as being merely a virtual model. Thus, it is crucial to define it clearly and have a deeper understanding of its architecture, workflow, and implementation scales. This paper reviews the notion of a Digital Twin represented in the literature and analyses different kinds of descriptions, including several definitions and architectural models. A new fit-for-all definition is proposed which describes the underlying technology without being context-specific and also overcomes the pitfalls of the existing generalised definitions. In addition, the existing three-dimensional and five-dimensional models of the DT architecture and their characteristic features are analysed. A new simplified two-branched model of DT is introduced, which retains a clear separation between the real and virtual spaces and outlines the latter based on the two key modelling approaches. This model is then extended for condition monitoring of electronic components and systems, and a hybrid approach to Prognostics and Health Management (PHM) is further elaborated on. The proposed framework, enabled by the two-branched Digital Twin model, combines the physics-of-degradation and data-driven approaches and empowers the next generation of reliability assessment methods. Finally, the benefits, challenges, and outlook of the proposed approach are also discussed. [ABSTRACT FROM AUTHOR]

A shared commitment to standardising the process of hypothetically reconstructing lost buildings from the past has characterised academic research in recent years and can manifest at various stages of the reconstructive process and with different perspectives. This research specifically aims to establish a user-independent and traceable procedure that can be applied at the end of the reconstructive process to quantify the average level of uncertainty of 3D digital architectural models. The procedure consists of applying a set of mathematical formulas based on numerical values retrievable from a given scale of uncertainty and developed to simplify reuse and improve transparency in reconstructive 3D models. This effort to assess uncertainty in the most user-independent way possible will contribute to producing 3D models that are more comparable to each other and more transparent for academic researchers, professionals, and laypersons who wish to reuse them. Being able to calculate a univocal numerical value that gives information on the global average uncertainty of a certain reconstructive model is an additional synthetic way, together with the more visual false-colour scale of uncertainty, to help disseminate the work in a clear and transmissible way. However, since the hypothetical reconstructive process is a process based on personal interpretation, which inevitably requires a certain level of subjectivity, it is crucial to define a methodology to assess and communicate this subjectivity in a user-independent and reproducible way. [ABSTRACT FROM AUTHOR]

Copyright of Magazine General Union of Arab Archaeologists is the property of General Union of Arab Archaeologists and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Automatic Question Generation (AQG) from text is difficult, especially in Indonesia, where research is scarce. Current research focuses on factual questions, leaving room for improvement. Previous studies used sequence-to-sequence models, which are effective for rule-based and cloze testing but rely on pre-existing rules. This article evaluates state-of-the-art pre-trained models such as IndoBERT, IndoGPT, and IndoBART as well as classical models such as BiGRU, BiLSTM, and Transformer to fill this gap. This paper tests model question generation using SQuAD-ID, IDK-MRC, and TyDi-QA, three popular question-and-answer datasets. This study uses BLEU and ROUGE-L to evaluate each model's ability to generate meaningful queries from the provided settings. This research aims to understand AQG in Indonesian and evaluate model performance. Discusses the background of AQG research, model limitations, as well as research topics and hypotheses. The paper also analyzes the expected contributions, such as the effectiveness of the trained model and the architectural effects on the AQG process. This research improves natural language processing and question generation systems, especially for Indonesian. [ABSTRACT FROM AUTHOR]

Building information modelling (BIM) is an appreciated technology in the field of architecture and construction management. Collaboration of information in BIM has not been fully utilized in the structural engineering stream as many engineers keep on working with previous prevailing design approaches. Failure to adequately facilitate automation in design could lead to structural defects, construction rework, or even structural clashes, with major financial implications. Given the inherent complexity of large-scale construction projects, the 'manual design and detailing' of structure is a challenging task and prone to human errors. Against this backdrop, this study developed a 4D building information management approach to facilitate automated structural models for professionals designing all the elements required in reinforced concrete (RC) structures like slabs, beams, and columns. The main contribution of this study is to obtain structural models directly from architecture models automatically, which reduces effort and possible errors in the previous prevailing approaches. The framework enables execution of all the model design works automatically through coding. This is achieved by executing a script which is beneficial for integrated project delivery (IPD). The 3D structural model in BIM software presented in this study extracts and transfers the geometrical data and links these data in Industry Foundation Classes (IFC) files using integration facilitated by Python 3.6 and IFCopenshell. The developed automated programme framework offers a cost-effective and accurate methodology to address the limitations and inefficiencies of traditional methods of structural modelling, which had been carried out manually. The authors have developed a novel tool to extract structural models from architectural models without proprietary software, greatly benefiting BIM managers by enhancing 3D BIM models. This advancement toward Open BIM, crucial for the architecture, engineering, and construction (AEC) industry's future, is accessible to educators and beginners and highlights BIM's effectiveness in improving structural analysis and productivity. The core finding of this study is to generate a structural model from an architecture model by automating the script with Python integration of IFC and IFCopenshell. The merits of the developed framework are reduced clashes, more economical structural modelling, and fully automated smart work as functions of the IPD. [ABSTRACT FROM AUTHOR]

Designing the floodlighting of objects in the context of improving the night image of the city is a very complex task, requiring not only a time commitment but also precise analysis and innovative solutions. In particular, designers must consider the principles of aesthetics and adapt the lighting to the architectural style and details of the facilities while ensuring energy efficiency and minimising the impact on the natural environment. For single objects, the task is relatively simple. The problem arises when the task is to develop a lighting concept for a large ensemble. Computer applications strictly dedicated to lighting analysis cannot capture a 3D model rich in architectural detail. The article presents a case study that focuses on a comprehensive approach to designing the floodlighting of a complex of architectural objects. The steps for designing the floodlighting of objects are presented. Based on a computer simulation, a visual lighting concept and a detailed analysis of the luminance distribution and floodlighting efficiency were presented. The obtained average luminance levels are consistent with recommendations and standards, and the project is characterised by a high lighting efficiency of 56%. This approach enables an understanding of how light affects architectural structures and the surroundings, which is crucial to achieving harmony between the technical side of the project and its aesthetics. The project presented in the article is an inspiring example of how a comprehensive approach to illumination can contribute to creating an attractive night landscape of the city, taking into account the aspects of sustainable development. This is very important nowadays, when the floodlighting of architectural objects is often considered an element of the landscape that can be omitted. [ABSTRACT FROM AUTHOR]

The first ideas generation of the architectural project has traditionally been carried out through sketches. Even though in recent decades models have also gained importance, their use is still restricted due to the time required to make them and their difficulty of realization when it comes to complex forms. This research argues that the use of concept models mediated by two disruptive technologies such as Immersive Virtual Reality and 3D Printing can foster the cognitive process of the ideation and configuration of the first architectural ideas. To demonstrate the hypothesis, a pilot study was conducted with 32 architecture students; 17 students created models manually and 15 used IVR and 3DP. Two observation sheets were used to collect information. The results show that in the process of generating ideas, the group that used the two technologies developed three of the four characteristics of the cognitive process better, being an undecided and slow process, then fast and continuous, and finally perceptual for reinterpretation. Also, both technologies complemented each other and favored the development of an intense, tactile, and phenomenological experience. Finally, regarding the model as a product, a better result was found in 3D-printed models in terms of two of the three characteristics, three-dimensionality complexity and materiality. It is concluded that these two technologies ideally complement each other as mediating tools for three-dimensional architectural thinking, making it possible to use the conceptual models as the first generators of the architectural idea. [ABSTRACT FROM AUTHOR]

Copyright of Journal of Geomechanics is the property of Journal of Geomechanics Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

By aligning Saudi Vision 2030 with the UN's SDGs, this study highlights the significant role of integrating sustainable environmental design knowledge into architectural education in Saudi Arabia. Viewing this integration as a moral obligation, it emphasizes equipping future architects with the skills to create environmentally responsible and resource-efficient buildings, fostering a sustainable and resilient built environment. This paper aims to examine the degree of integration of sustainability knowledge and assess the structural models incorporated into the architectural programs of six Saudi Arabian universities. Adopting a quantitative approach with qualitative insights, this research focuses on universities certified by the National Architectural Accrediting Board (NAAB) or accredited by recognized national and international bodies. This study is limited to the meso-level (curricular management) and includes structural models, course descriptions, learning outcomes, course sequences, and alignment with program visions and missions. A comprehensive review was conducted on all courses related to sustainability, collecting data from program websites. The main variables analyzed included sustainable environmental knowledge, total contact hours dedicated to sustainability courses, distribution across various course types, and patterns over a 5-year period. The units of analysis encompass program plans, vision and mission statements, learning outcomes, course syllabi, and descriptions. The findings reveal significant disparities in sustainability emphasis among programs, with Imam Abdul Rahman Al-Faisal University dedicating 42% of contact hours to sustainability, compared to 25 to 11% at other universities. This study highlights the need for integrating sustainability across design studio levels to provide students with practical skills across disciplines. Most programs use a "linear/parallel" or "partially integrated" model, requiring sustainability principles in graduation projects. However, elective sustainability courses are unpopular and do not adequately address curriculum gaps. This study highlights the necessity of further investigating the effectiveness of incorporating sustainability knowledge in architectural programs. Exploring specific areas for future research to enhance the integration of sustainability in architectural education is also recommended. [ABSTRACT FROM AUTHOR]

After 1830, the French presence in Algiers brought significant changes to the architectural landscape of the city. The dominant feature of this transformation was the construction of European houses. The first models were constructed mainly within the Ottoman city, especially in its lower part. This paper attempts to explain certain aspects of this type of housing. To do so, it relies on three tools necessary to the study of minor architecture, namely the plot of land, the template, and the scheduling. And how the colonial cultural heritage shaped perceptions and references. This resulted in the dismantling of the original architectural model in city of Algiers represented by the "old" city el-Casbah with its time-established functional, artistic and social divisions and new political-social divisions that respond to the needs of the colonizer rather than the needs of the indigenous population, in addition to technical and value distortions in the general architectural fabric. [ABSTRACT FROM AUTHOR]

The identification of safflower filament targets and the precise localization of picking points are fundamental prerequisites for achieving automated filament retrieval. In light of challenges such as severe occlusion of targets, low recognition accuracy, and the considerable size of models in unstructured environments, this paper introduces a novel lightweight YOLO-SaFi model. The architectural design of this model features a Backbone layer incorporating the StarNet network; a Neck layer introducing a novel ELC convolution module to refine the C2f module; and a Head layer implementing a new lightweight shared convolution detection head, Detect_EL. Furthermore, the loss function is enhanced by upgrading CIoU to PIoUv2. These enhancements significantly augment the model's capability to perceive spatial information and facilitate multi-feature fusion, consequently enhancing detection performance and rendering the model more lightweight. Performance evaluations conducted via comparative experiments with the baseline model reveal that YOLO-SaFi achieved a reduction of parameters, computational load, and weight files by 50.0%, 40.7%, and 48.2%, respectively, compared to the YOLOv8 baseline model. Moreover, YOLO-SaFi demonstrated improvements in recall, mean average precision, and detection speed by 1.9%, 0.3%, and 88.4 frames per second, respectively. Finally, the deployment of the YOLO-SaFi model on the Jetson Orin Nano device corroborates the superior performance of the enhanced model, thereby establishing a robust visual detection framework for the advancement of intelligent safflower filament retrieval robots in unstructured environments. [ABSTRACT FROM AUTHOR]

Interest in cloud computing is steadily increasing and the range of offerings is evolving due to continuous technological innovation. Hence, cloud-native has been established as a term for building applications in a way that maximally exploits benefits of modern cloud computing concepts. However, cloud-native as a topic is broad and the variety in cloud computing technologies is large. Thus, we identify a need in supporting developers and software architects who want to benefit from cloud-native concepts. We provide this support in the form of a quality model for cloud-native software architectures that explains how architectural characteristics impact different quality aspects. Our focus is on the design time and the aim is that architectural models of applications can be evaluated according to cloud-native characteristics and corresponding quality aspects. In this work we present our approach for formulating and validating the quality model for cloud-native software architectures as well as its current state. This presentation is based on previous work, especially a recently conducted validation survey that focused on the impacts of architectural characteristics on quality aspects. The new contribution of this work is the integrated presentation of our approach in a larger context of conceptual and methodological considerations. Further, revision of the quality model based on a repeated literature search for architectural measures is presented. We provide a more detailed look on the quality model, explaining exemplary product factors and their relevance within the topic of cloud-native. Our results provide a qualitative overview of characteristics associated with cloud native software architectures and lay the foundation for quantitative quality evaluations based on architectural models of applications. [ABSTRACT FROM AUTHOR]

In Ying Xian Fogong Si Shijia Ta 應縣佛宮寺釋迦塔 (Sakyamuni Pagoda of Fogong Temple in Ying County), Shanxi, there are statues set on each floor, and 26 exist in total, with six murals painted on the first floor. The pagoda was designed as a vertically rising Buddhist temple, and the interior space of each floor was customized for the statues. Based on previous research and through surveying and mapping of the architecture and statuary (including the murals on the first floor) combined with geometric design analysis, this paper proposes the following: First, there exists a clear geometric proportion among the interior space and statues on each floor of the pagoda. Second, clear proportional relationships also exist among the statues on each floor, and each of the 26 statues has 'classical' proportion rules. Third, the height of the giant Buddha statue on the first floor is the module for not only the height of the statues on each floor but also the construction of the whole pagoda such that the height of the statue on the first floor is 1/6 of the total height of the pagoda (excluding the base). And the ratio of the pagoda's total height to the first floor's diameter, the ratio of the total height to the top-story height under the column capital, and all the other geometric proportions are closely related to the architectural modeling. And finally, in the construction of the pagoda, statues, and murals, the scale is deduced to be 1 chi 尺 (Chinese foot) = 29.5 cm. These values give clear scale logics not only to the construction but also to the details of the statues. Accordingly, the most frequently used proportions in the architectural space, statues, and murals of the Pagoda of Fogong Temple are 2 , 3:2, 5:3 (or 8:5), and 9:5, which are imbued with cultural messages, like Zhou Bi Suan Jing 周髀算經 (The Mathematical classic of the Zhou shadow-gauging instrument), Ying Zao Fa Shi 營造法式 (Treatise on Architectural Methods or State Building Standards), the ancient Chinese world view—tian yuan di fang 天圜地方 (the dome-shaped heaven and the flat, square earth) reflected from " yuan fang tu 圓方圖 (rounded-square map)" and "fang yuan tu 方圓圖 (squared-circle map)", ancient Chinese ideas that "san tian liang di er yi shu 參天兩地而倚數 ('three' is the number of the heaven and 'two' is the number of the earth, and all numbers are based on them)" and "jiu wu zhi zun 九五之尊 (nine and five are the numbers of the honorable central position)", and most probably related to the "mandala" of Esoteric Buddhism and to the Western "Golden Ratio", which all need further research in depth. [ABSTRACT FROM AUTHOR]

The vastly overscaled elements, lineaments and sculptures of a seemingly infinite house form the backdrop of Susanna Clarke's 2020 novel Piranesi. Head of Teaching and Learning at the Architectural Association, Mark Morris draws on his research into architectural models, paracosms and the representation of buildings in fiction, filtering this through the lens of an encyclopaedic knowledge of architectural history to investigate the book's narrative arc, its ghostly visitations and its beautiful if not overbearing architectural mise en scène. [ABSTRACT FROM AUTHOR]

A rchitectural documentation not only plays a critical role in the conservation of historical structures, but also enables their detailed comprehension of the structure. This study aims to assess the most effective methods for drawing and modeling architectural structures and present their advantages and disadvantages. Measurements play a significant role in this context, and today's technology offers the potential to accelerate this process and enhance accuracy. However, the application of these technologies can impose additional burdens such as elevated expenses, the requisite for specialized personnel, and the management of substantial data volumes. Therefore, determining the appropriate measurement method in line with the quality of architectural documentation is essential. For this study, the Mosque of Kurşunlu Complex in Eskişehir was selected for its historical and topographical attributes which enabled all methods to be examined. The data produced via terrestrial laser scanning, aerial photogrammetry and terrestrial photogrammetry methods were examined in terms of the production of drawings and models for different analysis methods such as structure, daylight and building acoustics, as well as survey drawings required for the architectural documentation processes of the building. The study concluded that no single method could produce holistic data on its own, and the best results for comprehensive documentation were achieved by integrating terrestrial laser scanning and aerial photogrammetry. Furthermore, for products that do not require comprehensive data, photogrammetric methods were more efficient. [ABSTRACT FROM AUTHOR]

Conventional methods of teaching architectural design have flaws like fuzzy information exchange, limitations of thought dispersion, and disconnection of theory and practice because of the different cognitive levels of teachers and students. This paper explores the interactive and collaborative "human-machine-human" mode of utilizing Stable Diffusion image generation technology to teach architectural design and achieve artificial intelligence. To enhance the quality and effectiveness of instruction, the model uses artificial intelligence for image generation, optimization, and presentation in accordance with the three stages of architectural design teaching that are developed in this paper. Mainly using the Northeastern University youth hostel design course as an example, this paper compares the new "human-machine-human" mode with the traditional "human-human" mode, assesses the necessity and viability of the AI intervention, and offers examples for future architectural course teaching reform and the comprehensive integration of AI and architecture. In the interim, it offers resources and recommendations for the deep integration of AI and architecture, as well as recommendations for future teaching reform of architecture courses. [ABSTRACT FROM AUTHOR]

A Clinical Data Repository (CDR) is a dynamic database capable of real-time updates with patients' data, organized to facilitate rapid and easy retrieval. CDRs offer numerous benefits, ranging from preserving patients' medical records for follow-up care and prescriptions to enabling the development of intelligent models that can predict, and potentially mitigate serious health conditions. While several research works have attempted to provide state-of-the-art reviews on CDR design and implementation, reviews from 2013 to 2023 cover CDR regulations, guidelines, standards, and challenges in CDR implementation without providing a holistic overview of CDRs. Additionally, these reviews need to adequately address critical aspects of CDR; development and utilization, CDR architecture and metadata, CDR management tools, CDR security, use cases, and artificial intelligence (AI) in CDR design and implementation. The collective knowledge gaps in these works underscore the imperative for a comprehensive overview of the diverse spectrum of CDR as presented in the current study. Existing reviews conducted over the past decade, from 2013 to 2023 have yet to comprehensively cover the critical aspects of CDR development, which are essential for uncovering trends and potential future research directions in Africa and beyond. These aspects include architecture and metadata, security and privacy concerns, tools employed, and more. To bridge this gap, in particular, this study conducts a comprehensive systematic review of CDR, considering critical facets such as architecture and metadata, security and privacy issues, regulations guiding development, practical use cases, tools employed, the role of AI and machine learning (ML) in CDR development, existing CDRs, and challenges faced during CDR development and deployment in Africa and beyond. Specifically, the study extracts valuable discussions and analyses of the different aspects of CDR. Key findings revealed that most architectural models for CDR are still in the theoretical phase, with low awareness and adoption of CDR in healthcare environments, susceptibility to several security threats, and the need to integrate federated learning in CDR systems. Overall, this paper would serve as a valuable reference for designing and implementing cutting-edge clinical data repositories in Africa and beyond. [ABSTRACT FROM AUTHOR]

Automated Foreign Object Debris (FOD) detection offers significant benefit to the aviation industry by reducing human error and enabling continuous surveillance. This paper focuses on addressing the intricacies of FOD detection, with a specific emphasis on treating FODs as "small" objects, a facet which has received limited attention in prior research. This study provides a pioneering evaluation of state-of-the-art object detectors, including both anchor-based models including SSD, YOLOv5m, Scaled YOLOv4 and anchorless models CenterNet and YOLOv8m, applied to a multiclass FOD dataset, "FOD in Airports (FOD-A)", as well as meticulously curated subset of FOD-A featuring small FODs. The findings reveal that the anchorless object detector YOLOv8m gives the best time accuracy trade off outperforming all compared anchor-based and anchorless approaches. To address the challenge of detecting small FODs, this study optimizes YOLOv8m model by making architectural modifications and incorporating a dedicated, shallow detection head that is purpose-built for the precise identification of small objects. The proposed model, termed as "Improved YOLOv8", outperforms YOLOv8m by a margin of 1.02 in Average Precision for small objects (APs), achieving a mean average precision (mAP) of 93.8%. Notably, Improved YOLOv8 also has better mAP than all the considered anchor-based and anchorless object detectors examined, as well as those featured in prior FOD-A dataset research. [ABSTRACT FROM AUTHOR]

Introduction: Gene regulatory networks (GRNs) are characterized by their dynamism, meaning that the regulatory interactions which constitute these networks evolve with time. Identifying when changes in the GRN architecture occur can inform our understanding of fundamental biological processes, such as disease manifestation, development, and evolution. However, it is usually not possible to know a priori when a change in the network architecture will occur. Furthermore, an architectural shift may alter the underlying noise characteristics, such as the process noise covariance. Methods: We develop a fully Bayesian hierarchical model to address the following: a) sudden changes in the network architecture; b) unknown process noise covariance which may change along with the network structure; and c) unknown measurement noise covariance. We exploit the use of conjugate priors to develop an analytically tractable inference scheme using Bayesian sequential Monte Carlo (SMC) with a local Gibbs sampler. Results: Our Bayesian learning algorithm effectively estimates time-varying gene expression levels and architectural model indicators under varying noise conditions. It accurately captures sudden changes in network architecture and accounts for time-evolving process and measurement noise characteristics. Our algorithm performs well even under high noise conditions. By incorporating conjugate priors, we achieve analytical tractability, enabling robust inference despite the inherent complexities of the system. Furthermore, our method outperforms the standard particle filter in all test scenarios. Discussion: The results underscore our method's efficacy in capturing architectural changes in GRNs. Its ability to adapt to a range of time-evolving noise conditions emphasizes its practical relevance for real-world biological data, where noise presents a significant challenge. Overall, our method provides a powerful tool for studying the dynamics of GRNs and has the potential to advance our understanding of fundamental biological processes. [ABSTRACT FROM AUTHOR]

In this paper we present an analysis contract approach that takes advantage of efficient domain-specific analysis algorithms, enable incremental analysis of architectural model refinements, and implement assume- guarantee reasoning in symbolic domains in SMT. [ABSTRACT FROM AUTHOR]

Neural radiance fields have emerged as a dominant paradigm for creating complex 3D environments incorporating synthetic novel views. However, 3D object removal applications utilizing neural radiance fields have lagged behind in effectiveness, particularly when open set queries are necessary for determining the relevant objects. One such application area is in architectural heritage preservation, where the automatic removal of non-architectural objects from 3D environments is necessary for many downstream tasks. Furthermore, when modeling occupied buildings, it is crucial for modeling techniques to be privacy preserving by default; this also motivates the removal of non-architectural elements. In this paper, we propose a pipeline for the automatic creation of cleaned, architectural structure only point clouds utilizing a language embedded radiance field (LERF) with a specific application toward generating suitable point clouds for the structural integrity assessment of occupied buildings. We then validated the efficacy of our approach on the rooms of the historic Sion hospital, a national historic monument in Valais, Switzerland. By using our automatic removal pipeline on the point clouds of rooms filled with furniture, we decreased the average earth mover's distance (EMD) to the ground truth point clouds of the physically emptied rooms by 31 percent. The success of our research points the way toward new paradigms in architectural modeling and cultural preservation. [ABSTRACT FROM AUTHOR]

Current supply chain management (SCM) requires the control of physical and information flows in order to satisfy the customer, i.e. deliver the right product to the customer at the right place, at the right time, at the right price and at the lowest cost. SCM is inseparable from traceability which makes reliable the said flows, accelerates the transmission of information on these flows, allows to access a detailed knowledge of the movements, and makes the flows visible. In order to streamline and monitor, if possible, in real time and permanently these logistical processes, we propose the design and implementation of an Ontology-based traceability system based on an architectural model for the physical Internet using computing resources such as Cloud computing, Fog computing and Internet of Things (IoT) to achieve efficiency and sustainability goals. To evaluate our system, we were able to carry out all the queries that the user can express whether he is a customer, a supplier or a manager. [ABSTRACT FROM AUTHOR]

Coffee bean production can encounter challenges due to fluctuations in global coffee prices, impacting the economic stability of some countries that heavily depend on coffee production. The primary objective is to evaluate how effectively various pre-trained models can predict coffee types using advanced deep learning techniques. The selection of an optimal pre-trained model is crucial, given the growing popularity of specialty coffee and the necessity for precise classification. We conducted a comprehensive comparison of several pre-trained models, including AlexNet, LeNet, HRNet, Google Net, Mobile V2 Net, ResNet (50), VGG, Efficient, Darknet, and DenseNet, utilizing a coffee-type dataset. By leveraging transfer learning and fine-tuning, we assess the generalization capabilities of the models for the coffee classification task. Our findings emphasize the substantial impact of the pre-trained model choice on the model's performance, with certain models demonstrating higher accuracy and faster convergence than conventional alternatives. This study offers a thorough evaluation of pre-trained architectural models regarding their effectiveness in coffee classification. Through the evaluation of result metrics, including sensitivity (1.0000), specificity (0.9917), precision (0.9924), negative predictive value (1.0000), accuracy (1.0000), and F1 score (0.9962), our analysis provides nuanced insights into the intricate landscape of pre-trained models. [ABSTRACT FROM AUTHOR]

Integrating deep generative models into urban form generation is an innovative and promising approach to support the urban design process. However, most deep generative urban form models are based on image representations that do not explicitly consider topological relationships among urban form elements. Toward developing an urban form generation framework aided by deep generative models and considering topological information, this paper reviews urban form generation, deep generative models/deep graph generation, and the state of the art of deep generative models in architectural and urban form generation. Based on the literature review, a topology-based urban form generation framework aided by deep generative models is proposed. The hypotheses of street network generation by deep generative models for graph generation and plot/building configuration generation by deep generative models/space syntax and the feasibility of the proposed framework require validation in future research. [ABSTRACT FROM AUTHOR]

Copyright of Journal of Beijing University of Civil Engineering & Architecture is the property of Journal of Beijing University of Civil Engineering & Architecture Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

To date, BIM has been primarily utilized in cost and schedule management, an interference check between architectural and structural models and systems based on geometric data in the process of the construction life cycle. However, there is a lack of research that utilizes the information contained in the BIM model to review whether the proposed architectural model is appropriately designed in accordance with each country's building regulations or building codes or that proposes a model optimized for laws and standards. 'Building code checking' is the step of reviewing whether a building designed based on the building codes is suitable for being constructed as a building. However, this process consumes significant time and money and leads to human errors due to the manual review process. This study included implementation of an algorithm based on the Korean building code. In this study, there was the process of selection of codes when architects interpret building codes in common and implementation based on the codes selected. Next, modeling based on DXF files from NGII (National Geographic Information Institute) was applied to the algorithm developed in this study. Last, it includes case studies that compare the outputs of the algorithm with the real buildings, which had received real code checking, to make sure the algorithm in this paper is working properly. The implementation of such an automated system has the potential to significantly improve the efficiency and effectiveness of the building design and construction process. It can help architects to quickly and accurately identify potential legal issues and provide alternative solutions that meet regulatory requirements. This, in turn, can lead to reduced project costs, improved quality of designs, and faster project delivery times. [ABSTRACT FROM AUTHOR]

The article discusses the history and significance of architectural models in Victorian London and Britain, focusing on the roles of architects and modelmakers. It highlights the importance of models in architectural representation and communication, as well as the evolving relationship between architects and modelmakers over the centuries. The authors, Matthew Wells and David Lund, provide comprehensive insights into the expertise and contributions of modelmakers, challenging traditional hierarchies and shedding light on the often overlooked role of modelmakers in shaping the built environment. The works are praised for their exhaustive research, innovative approaches, and visual presentation, making them valuable resources for those interested in architecture and design. [Extracted from the article]

Copyright of Journal of Threatened Taxa is the property of Wildlife Information Liaison Development and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Optimizing the energy structure to effectively enhance the integration level of renewable energy is an important pathway for achieving dual carbon goals. This study utilizes an improved multi-objective particle swarm optimization algorithm based on load fluctuation rates to optimize the architecture and unit capacity of hydrogen production systems. It investigates the optimal configuration methods for the architectural model of new energy hydrogen production systems in Xining City, Qinghai Province, as well as the internal storage battery, ALK hydrogen production equipment, and PEM hydrogen production equipment, aiming at various scenarios of power sources such as wind, solar, wind–solar complementary, and wind–solar–storage complementary, as well as intermittent hydrogen production scenarios such as hydrogen stations, hydrogen metallurgy, and continuous hydrogen production scenarios such as hydrogen methanol production. The results indicate that the fluctuation of hydrogen load scenarios has a significant impact on the installed capacity and initial investment of the system. Compared with the single-channel photovoltaic hydrogen production scheme, the dual-channel hydrogen production scheme still reduces equipment capacity by 6.04% and initial investment by 6.16% in the chemical hydrogen scenario with the least load fluctuation. [ABSTRACT FROM AUTHOR]