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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]

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]

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]

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.)

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]

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]

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]

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]

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]

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]

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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]

Marcel Breuer began sporadically working as an architect in 1923, although he did not open his professional studio in Berlin until 1928, after leaving his teaching duties at the Bauhaus. In most of the commissions and competitions he undertook, he used scale models as a means of representation his architectural proposals. This article is about the models used in the first 25 years of their professional practice, that is, from 1924 to 1949, a turning point in their trajectory, as from then on, it would experience remarkable development. The primary source of documentation for this writing comes from the Marcel Breuer Digital Archives at Syracuse University. [ABSTRACT FROM AUTHOR]

This study presents the interaction with the human host metabolism of SARS-CoV-2 ORF7b protein (43 aa), using a protein–protein interaction network analysis. After pruning, we selected from BioGRID the 51 most significant proteins among 2753 proven interactions and 1708 interactors specific to ORF7b. We used these proteins as functional seeds, and we obtained a significant network of 551 nodes via STRING. We performed topological analysis and calculated topological distributions by Cytoscape. By following a hub-and-spoke network architectural model, we were able to identify seven proteins that ranked high as hubs and an additional seven as bottlenecks. Through this interaction model, we identified significant GO-processes (5057 terms in 15 categories) induced in human metabolism by ORF7b. We discovered high statistical significance processes of dysregulated molecular cell mechanisms caused by acting ORF7b. We detected disease-related human proteins and their involvement in metabolic roles, how they relate in a distorted way to signaling and/or functional systems, in particular intra- and inter-cellular signaling systems, and the molecular mechanisms that supervise programmed cell death, with mechanisms similar to that of cancer metastasis diffusion. A cluster analysis showed 10 compact and significant functional clusters, where two of them overlap in a Giant Connected Component core of 206 total nodes. These two clusters contain most of the high-rank nodes. ORF7b acts through these two clusters, inducing most of the metabolic dysregulation. We conducted a co-regulation and transcriptional analysis by hub and bottleneck proteins. This analysis allowed us to define the transcription factors and miRNAs that control the high-ranking proteins and the dysregulated processes within the limits of the poor knowledge that these sectors still impose. [ABSTRACT FROM AUTHOR]

The selection of the optimal methodology for the 3D geometric documentation of cultural heritage is a subject of high concern in contemporary scientific research. As a matter of fact, it requires a multi-source data acquisition process and the fusion of datasets from different sensors. This paper aims to demonstrate the workflow for the proper implementation and integration of geodetic, photogrammetric and laser scanning techniques so that high-quality photorealistic 3D models and other documentation products can be generated for a complicated, large-dimensional architectural monument and its surroundings. As a case study, we present the monitoring of the Mehmet Bey Mosque, which is a landmark in the city of Serres and a significant remaining sample of the Ottoman architecture in Greece. The surveying campaign was conducted in the context of the 2022–2023 annual workshop of the Interdepartmental Program of Postgraduate Studies "Protection Conservation and Restoration of Cultural Monuments" of the Aristotle University of Thessaloniki, and it served as a geometric background for interdisciplinary cooperation and decision-making on the monument restoration process. The results of our study encourage the fusion of terrestrial laser scanning and photogrammetric datasets for the 3D modeling of the mosque, as they supplement each other as regards geometry and texture. [ABSTRACT FROM AUTHOR]

When buildings are exposed to erosion from the natural environment, erosion behaviors such as surface damage and structural instability occur, which greatly affect the aesthetic value and service life of the buildings. The study of erosion behaviors and the establishment of a suitable erosion model are constructive references for the protection and restoration of buildings. In order to establish a suitable erosion model for architectural red sandstone, two types of red sandstone specimens were selected in this paper to carry out dry and wet cycle tests. Combining the theoretical analysis and the actual erosion situation, a unidirectional corrosion model is proposed to describe the erosion of buildings by the natural environment. In this model, it is assumed that only the outer surface of the building is in contact with external erosion factors for a long period of time, so this situation can be considered a unidirectional erosion process. The paper uses XRD, SEM, and ultrasonic methods to record changes in the properties of the red sandstone samples. Finally, the rationality of the unidirectional erosion model was verified numerically. The test results show that the red sandstone specimens subjected to erosion by the natural environment will be accompanied by the development of defects, such as cracks, fissures, and holes, as well as the generation of fresh material. The demarcation point of different erosion stages exists in both the in-service red sandstone specimens and the fresh red sandstone specimens, which is consistent with the results of the unidirectional erosion model. In this paper, a calculation model for the demarcation point of different erosion stages is established, and the model estimation shows that the demarcation point of different erosion stages of the in-service red sandstone sample is 1.1528 cm from the erosion surface, and the demarcation point of different erosion stages of the fresh red sandstone sample is 1.67 cm. [ABSTRACT FROM AUTHOR]

Architectural models serve as a bridge between the idea and its realization. Moreover, it is considered one of the main means by which the architect invents and develops his design. The “Architectural Models” course in many architectural schools introduces the basics of implementing architectural models. Students learn how to think of and build architectural models using different materials. While many of these courses overlook how to think about architectural concepts using physical models. The aim of this research is to state and examine strategies for generating architectural ideas using physical models. This paper discusses various strategies for generating architectural ideas using physical models. Furthermore, it illustrates an experiment conducted in the “Architectural Models” course in the Department of Architecture and Environmental Design at the Arab Academy for Science and Technology, Egypt, which was offered in 2021. The experiment was followed by a small questionnaire. The experiment aims to stimulate the creation of innovative architectural forms using physical models. The role of architectural models goes beyond presenting projects. Therefore, the intended learning outcomes of the “Architectural Models” courses in architecture departments should be developed. Strategies for generating ideas using architectural models were adopted and applied. This is the first paper in which such strategies are examined. The final students’ products were very good, and their feedback was very encouraging. [ABSTRACT FROM AUTHOR]

Developing, experimenting, and sharing critical pedagogical approaches is becoming increasingly important in architectural education, which supposedly superposes theory and practice. In this article, the authors reveal and reflect on an enriching pedagogical approach to the traditional architectural design studio. It is acknowledged that students develop comprehensive examination and internalization abilities by developing reflective thinking and self-evaluation abilities that complement each other. Based on the pioneer educational theory of John Dewey, the researchers' selected instructional interventions. Using the action research method, four additional modes conceptualized towards disciplinary literacy -reading, mapping, discussion, and peer assessment-were injected into the traditional studio process during a semester of architectural design course. The pedagogical approach is built on questioning the two basic creativity-based abilities of learners: reflective thinking and self-assessment. The fundamental questions are: How can a reading-discussion setup designed to nurture disciplinary literacy in the design studio be a factor in developing reflective thinking ability? How can the systematic peer assessment exercise be a factor in the students' self-assessment and reflective thinking skills as a learning outcome? The results argue for the effects on students' intangible skills. The model studio setup exhibited two remarkable findings, showing that (i) the reading-discussion mode is more effective in generating reflective thinking and (ii) the systematic peer review exercise is more effective in gaining self-assessment ability. The aim is to contribute to the theory of education by making the model application in the field of architectural design studio accessible and reflective for other educators. [ABSTRACT FROM AUTHOR]

The discrepancy between competence and real work in engineering graduates can be resolved with cooperation by the construction industry. Therefore, it is necessary to determine the appropriate and required architectural engineering competencies with the current demands and conditions of the construction industry. So, this study aims to analyze the determinants of competence and test the competency development model for architectural engineering graduates according to the needs of the construction industry. The research sample method is non-probability sampling using purposive sampling. The research sample consisted of 240 practitioners and trainers from 40 construction industry companies. The PLS-SEM technique was used to test the measurement and structural models (3 dimensions, 8 elements, 47 constructs/indicators, and 9 hypotheses). The competence of architecture graduates is determined by the dominant factor, namely Utilities and Building Construction (UBC1 & UBC2, = 89.90%), and Building Estimation and Costing (BEC7, = 73.30%) is the lowest factor. The ability of the structural model to explain architectural competency measurements is 36.20% in the moderate category. The predictive relevance value (Q2) explains 47.5% to 56.0% of the phenomena predicted in the field and explains the level of strength of the observed value in the structural model. Furthermore, 9 hypotheses from 8 dimensions have a positive and significant effect. The results of this study can be a recommendation for schools in the competency implementation model, and efforts to improve graduates' abilities and skills so that they can be absorbed by the construction industry and reduce unemployment. [ABSTRACT FROM AUTHOR]

Describing the architecture of microservices systems allows for the illustration of various aspects of design and implementation with information tailored to different stakeholders. On the one hand, the microservices architecture provides flexibility, scalability, faster deployment times, and the potential to design solutions incorporating multiple technologies. An architecture-centered, scenario-driven, iterative development method, on the other hand, is used to explain the system from the perspective of many stakeholders, such as project managers, system architects, developers, and end users. To complement this point of view, this paper proposes an architectural view model that highlights numerous viewpoints and disciplines in microservices-based software development. Such methods are typically well suited for developing and implementing microservices-based software processes to satisfy stakeholders' demands and expectations. [ABSTRACT FROM AUTHOR]

Public health experts are deeply concerned about cardiovascular diseases, including numerous heart-related ailments that can prove fatal. Distinguishing between Myocarditis and myocardial infarction (MI) is difficult due to comparable symptoms and diagnostic complications. While endomyocardial biopsy (EMB), cardiac troponin indicators, electrocardiography (ECG), and echocardiography are useful in making preliminary diagnoses, their effectiveness is limited. The EMIDEC challenge initiative stands out as an important development in this context. It demonstrates how clinical physiological parameters, combined with delayed enhancement magnetic resonance imaging (DE-MRI), can significantly enhance classification reliability. The aim of this research is to provide a thorough assessment of the present state of the art in EMIDEC-related research. Subsequently, our intention is to establish a new database that will serve as the framework for comprehensive testing and evaluation of the architectural models drawn from the literature. We established a constructive collaboration with the Military Hospital of Tunis, which was crucial for patient data collection and access to a diverse group of patients diagnosed with Myocarditis and MI. We proceeded to select the appropriate architectural models for our study. We chose the DOC-NET and DOC-NET+ models based on prior research that demonstrated their effectiveness in similar classification contexts. DOC-NET and DOC-NET+ demonstrated accuracy rates of 95% and 100% in previous studies with the EMIDEC dataset. When these models were applied to our newly produced custom dataset, DOC-NET maintained its impressive performance with an accuracy score of 97%, while DOC-NET+ had an accuracy score of 98%. However, as we increased both the number of patients and the complexity of scenarios in our new dataset, the accuracy of DOC-NET+ dropped significantly to 91%. The CMR with AI combination allows for more customized and efficient evaluation, ultimately increasing patient outcomes and altering the cardiovascular healthcare environment. However, problems connected to the algorithm's generalizability to complicated data continue to be a crucial concern in further refining these improvements. [ABSTRACT FROM AUTHOR]

Networks serve as a metaphor for understanding various phenomena in humanities, encompassing the circulation of ideas, people, and artifacts. This research employs network analysis, drawing from H. C. White's concept of netdom, to capture social and language patterns within Ljubljana's Arhitektura magazine from 1931 to 1934. Its objective was to map the socio-semantic network of the magazine, assisting in discerning relationship and expression patterns within Yugoslavian architecture discourse of the 1930s, aligned with the principles of "new architecture". Methodologically, the research has entailed text analysis using natural language processing techniques and quantitative network analysis, revealing three types of networks: a bimodal network of authors and issues, individual semantic networks of authors, and a socio-semantic network. This has resulted in 18 networks. Despite a simplified text processing model and trivial architectural concepts, common language among contributors is detected, pointing to mutual connections in architectural expressions and actors' social ties. Arhitektura was not the sole platform for discourse creation; however, the conducted network analysis has confirmed that the nature of the magazine embodies the concept of netdom switching, where identities are formed and altered through transitions between netdoms, shaping and changing those identities over time. Furthermore, this research illustrates how network analysis can offer actionable insight into historical phenomena, as well as its applicability in understanding social and cultural dynamics. [ABSTRACT FROM AUTHOR]

Unmanned platforms are becoming more and more widely used in both civilian and military applications. The flight safety of such aircraft is crucial. Therefore, it becomes necessary to formally model and rigorously test their software. Commencement of an unmanned air vehicle's (UAV) operation requires it undergoing a certification process, which further heightens the quality requirements. The validation process of the designed system is presented on the example of verifying the correctness of the operational scenario involving the transfer of control over a UAV between two ground control stations (GCSs). The paper introduces the method of designing unmanned aerial vehicles and testing their functionality based on finite-state machines. The architecture description of the system encompasses the use cases view and logical view of the 1+5 architectural views model. The paper concentrates on system requirements and their transformation into unified modeling language (UML) state machine diagrams. The authors present a method of mapping requirements to functions related to flight safety and system dynamics models expressed as communicating extended finite-state machines (CEFSMs). Moreover, the paper shows the rules for testing the correctness of state machine models using methods based on determining flows in directed graphs. It should be emphasized that the paper considers the certification of UAV software components from the system safety viewpoint, which directly affects the airworthiness of the air platform. [ABSTRACT FROM AUTHOR]

The Dunhuang murals, a significant part of Chinese heritage, have suffered deterioration primarily due to environmental and chemical factors, notably salt damage. This study proposes a sophisticated method that synergizes Fractional Order Differentiation (FOD) and Partial Least Squares Regression (PLSR) to accurately invert the phosphate content in the Mural Plaster of the Dunhuang paintings. The focal points of the research include: 1) To address the issue of information loss and reduced modeling precision caused by integer order differentiation algorithms, the FOD method is employed for preprocessing hyperspectral data. This approach ensures the fine spectral differences in the phosphate content of the Mural Plaster are precisely captured, 2) Utilizing PLSR, the study models the spectral bands identified at a significance level of 0.01 with measured conductivity values, thereby enabling the precise prediction of the phosphate content in the murals. The research outcomes reveal: 1) The FOD method can elucidate the nonlinear characteristics and variation patterns of the mural samples in the hyperspectral curve.As the order increases from zero to two, the number of spectral bands meeting the 0.01 significance test initially decreases and then increases. The highest absolute value of the positive correlation coefficient is observed at 1.9 orders, corresponding to the 2077 nm band, 2) For predicting the phosphate content in the murals, the model at 1.9 orders is most suitable for inversion. This model, after cross-validation, achieves a maximum R2 value of 0.783. This study created an efficient FOD-based model for estimating phosphate in mural plasters. [ABSTRACT FROM AUTHOR]

In order to solve the most difficult problem of the architectural model established by CNN in solving specific problems, which results in parameter overflow and inefficient training, an optimization algorithm for nonlinear convolutional neural networks based on improved chameleon swarm algorithm is proposed. This article mainly introduces the use of Chameleon Swarm Optimization (PSO) algorithm to research the parameters of CNN architecture, solve them, and achieve the optimization of the optimization model.Although the number of parameters that need to be set up in CNN is very large, this method can find better testing space for Alexnet samples with 5 different images. In order to improve the performance of the improved pruning algorithms, two candidate pruning algorithms are also proposed. The experimental results show that compared with the traditional Alexnet model, the improved pruning method improves the image recognition ability of the Caffe primary parameter set from 1.3% to 5.7%. Conclusion: This method has wide applicability and can be applied to most neural networks which do not require any special functional modules of the Alexnet network model. [ABSTRACT FROM AUTHOR]

In an agricultural nation like Indonesia, where villages are one of the key regions for economic growth, Jatisura Village in the Cikedung district of Indramayu has the potential to grow into a smart village. This is because Rosalia Food MSMEs (Micro, Small, and Medium Enterprises) that have sold their products to the Asian level and reputable communities like Situ Bolang as a tourist attraction both have potential in Jatisura village. Realizing smart village development is a program that requires cooperation from all parties since it is in line with the government's priority program, which is to construct Indonesia from the periphery to minimize the inequity between cities and rural areas. Therefore, a model of architecture that aligns with information technology architecture is required to implement the construction of smart villages. This study intended to build an architecture that aligns with information technology to facilitate the implementation of smart villages based on information and communication technology in Jatisura village, Indonesia's Indramayu regency. To promote digital inclusion and more excellent employment prospects, this study focuses on smart village architecture and methods leveraging ICT initiatives. The TOGAF framework was the foundation architectural concept used. The framework generated business and organizational architecture models, information system and technological architectures, and migration, implementation, and change management architectures. All these architectural models help carry out the process of constructing a smart village, enabling it to do so in a way that effectively carries out the vision and mission of the regency. [ABSTRACT FROM AUTHOR]

In the domain of architectural heritage conservation, the recent advancements in 3D modeling have significantly improved the reconstruction fidelity of historical edifices, particularly medieval castles of the Rhine region. The existing traditional 3D modeling methodologies, though precise, are laborious and exceedingly time-consuming, requiring a detailed focus on intricate architectural nuances. Advancements in Building Information Modeling (BIM) technology have played a key role in simplifying this process, offering an adaptable and parametric approach to architectural modeling. Nonetheless, the domain of Historic Building Information Modeling (HBIM) faces the distinctive challenge of scarce parametric object libraries that are suitably representative of historical heritage, compounded by the architectural heterogeneity inherent in these ancient structures.This paper presents a novel methodology utilizing the Blender software suite, with an emphasis on exploiting "Geometry Nodes" and "Modifiers" for parametric modeling. We introduce a technique that significantly enhances the efficiency of modeling Rhine castles. This method supports rapid alterations and precise customization, catering to the specific analytical needs of archaeologists and heritage researchers. The proposed approach aims to bridge the gap in HBIM by providing a flexible, dynamic toolset for the accurate digital preservation of historical architecture. [ABSTRACT FROM AUTHOR]

The perspective study of one of the panels from the cycle of San Bernardino attributed to Perugino has revealed a contracted space in depth, represented three-dimensionally by the objective model. In contrast, the ideal model eliminates the contraction and maintains the proportions dictated by the architectural interpretation. The contribution presents an advancement in the perspective study aimed at developing an augmented reality (AR) application. It is designed to be experienced at the museum housing the artwork, serving as an in-depth exploration that explains to visitors the nature of the perspective space and the architectural space represented. The case study of the painting by Perugino becomes an opportunity to define and experiment with a workflow aimed at creating AR applications focused on the visualisation of architectural models derived from the perspective restitution of pictorial works. The description of the adopted method focuses on the following aspects: the use of the pictorial image as an AR marker and the relationship between the perspective picture plane and the 3D model; the optimisation of 3D models for AR visualisation purposes; the issue of the landscape; scene lighting; and the user interface for multilayer interaction. [ABSTRACT FROM AUTHOR]

Fog computing is a promising solution for latency-sensitive applications in the Internet of Things (IoT) era. This research thoroughly investigates the performance characteristics of fog computing systems, specifically focusing on the impact of architectural heterogeneity. The study explores how architectural diversity, deadline constraints, and the count of Mobile Data Centers (MDCs) influence key performance metrics. Through experimental simulations, the research assesses success ratio, rejection ratio, and resource utilization across various architectural models. The findings emphasize the significance of adopting heterogeneous architectures and wider deadline ranges, leading to improved success ratio and reduced job rejection. Moreover, increasing the number of MDCs positively affects resource utilization and overall system performance. This research offers valuable insights for optimizing fog computing systems, enabling the development of efficient solutions for real-world applications. [ABSTRACT FROM AUTHOR]

Information integration and sharing in a standardized manner is crucial to enable visibility, coordination and synchronization of supply chain activities, i.e., traceability within and across several companies. Product traceability is an essential tool fully integrated in supply chain management which should not only allow identifying, tracing and tracking but also ensuring product safety and quality. It helps to utilize the resources optimally and makes reliable the information and physical flows, accelerates the transmission of information on these flows, allows accessing a detailed knowledge of the product movements, and leads to the more effective management of the supply chain. However, several difficulties hinder product traceability implementation and make it a challenging task, including diversity of stakeholders, semantic differences between the involved actors, and lack of a shared language leading to confusion and misunderstandings, which make information exchange difficult. Highly expressive systems and techniques are therefore required. The latter must be characterized by the ability to exchange relevant data between stakeholders in a timely, meaningful and coherent manner. In this paper, we propose the development of an Ontology-based traceability system. The ontology is based on an architectural model for the physical Internet using computing resources such as Cloud computing, Fog computing and Internet of Things (IoT). The proposed system provides a shared and common language which improves information exchanges among all stakeholders in supply chains. To evaluate its consistency and efficiency, we carry out several queries dealing with different scenarios of product traceability. The validation results indicate that the developed ontology has the expressivity needed to represent all the knowledge related to the product traceability domain, enabling interoperability among different actors. [ABSTRACT FROM AUTHOR]

Digital twins are considered the next step in IoT-based cyber–physical systems; they allow for the real-time monitoring of assets, and they provide a comprehensive understanding of a system behavior, allowing for data-driven insights and informed choices. However, no comprehensive framework exists for the development of IoT-based digital twins. Moreover, the existing frameworks do not consider the aspects introduced by the Industry 5.0 paradigm, such as sustainability, human-centricity, and resilience. This paper proposes a framework based on the one defined as the outcome of a project funded by the European Union between 2010 and 2013 called the IoT Architectural Reference Model (IoT-A or IoT-ARM), with the aim of the development and implementation of a standard IoT framework that includes digital twins. This framework establishes and implements a standardized collection of architectural instruments for modeling IoT systems in the 5.0 era, serving as a benchmark for the design and implementation of an IoT architecture focused on digital twins and enabling the sustainability, resilience, and human-centricity of the information system. Furthermore, a proof of concept of a monitoring digital twin for a vertical farming system has been developed to test the validity of the framework, and a discussion of applications in the manufacturing and service sectors is presented. [ABSTRACT FROM AUTHOR]