Hasil untuk "Architectural drawing and design"

Ben Pfaff, Justin Pettit, T. Koponen et al.

Yuchao Liao, Tosiron Adegbija, Roman Lysecky

Post-quantum cryptography (PQC) is crucial for securing data against emerging quantum threats. However, its algorithms are computationally complex and difficult to implement efficiently on hardware. In this paper, we explore the potential of Large Language Models (LLMs) to accelerate the hardware-software co-design process for PQC, with a focus on the FALCON digital signature scheme. We present a novel framework that leverages LLMs to analyze PQC algorithms, identify performance-critical components, and generate candidate hardware descriptions for FPGA implementation. We present the first quantitative comparison between LLM-driven synthesis and conventional HLS-based approaches for low-level compute-intensive kernels in FALCON, showing that human-in-the-loop LLM-generated accelerators can achieve up to 2.6x speedup in kernel execution time with shorter critical paths, while highlighting trade-offs in resource utilization and power consumption. Our results suggest that LLMs can minimize design effort and development time by automating FPGA accelerator design iterations for PQC algorithms, offering a promising new direction for rapid and adaptive PQC accelerator design on FPGAs.

N. Madathil, F. Dankar, Marton Gergely et al.

Federated learning (FL)–a distributed machine learning that offers collaborative training of global models across multiple clients. FL has been considered for the design and development of many FL systems in various domains. Hence, we present a comprehensive survey and analysis of existing FL systems, drawing insights from more than 250 articles published in 2019-2024. Our review elucidates the functioning of FL systems, particularly in comparison with alternative distributed learning approaches. Considering the healthcare domain as an example, we define the building blocks of a typical FL healthcare system, including system architecture, federation scale, data partitioning, open-source frameworks, ML models, and aggregation algorithms. Furthermore, we identify and discuss key challenges associated with the design and implementation of FL systems within the healthcare sector while outlining the directions of future research. In general, through systematic categorization and analysis of existing FL systems, we offer insights to design efficient, accurate, and privacy-preserving healthcare applications using cutting-edge FL techniques.

Yao WU, Chuan WANG, Yacheng SONG

ObjectiveThe research on carbon neutrality, in an ecological – environmental perspective, is a major mission of the landscape architecture discipline. In the global pursuit of low-carbon urban development, communities play a pivotal role in advancing low-carbon initiatives at the meso – micro scale. Since 2015, China has initiated a series of pilot projects to establish low-carbon communities following the issuance of national guidelines. However, the current policy implementation paths in China are not yet mature, primarily relying on the organization of pilot programs in various regions, which poses certain challenges for the promotion and scaling-up of low-carbon community development. Relevant policies rely predominantly on operational indicators for evaluation, offering inadequate feedback to guide implementation and design. This research aims to explore effective implementation paths for low-carbon community policies to promote sustainable development and broader dissemination of low-carbon communities in China.MethodsThis research employs an analytical framework of “institution – strategy – tool” (IST) to dissect policies related to low-carbon community development. Institutions, strategies, and tools are the three pivotal elements of an implementation pathway mechanism; the collaborative mode that these three elements jointly shape and the operational process thereof constitute the implementation paths discussed in this research. The research begins with a comparative overview of widely-used low-carbon community policies at home and abroad, highlighting their institutional backgrounds, strategic focuses, and implementation tools. Subsequently, the research conducts an in-depth analysis of two representative policies: LEED 4.0 Neighborhood Development (LEED-ND), a market-driven, standardized evaluation system developed by the U.S. Green Building Council (USGBC), and ÉcoQuartier, a government-led, adaptive governance initiative launched by the French Ministry of Ecology. Besides analyzing these two representative policies through the IST framework, the research compares these international models with China’s current practices, identifying gaps and opportunities for improvement in the Chinese context.ResultsThe results demonstrate that different institutional contexts give rise to distinct strategies, which in turn shape corresponding implementation tools and thereby generate divergent implementation paths. The positive synergy among their three core elements — institutions, strategies, and tools — is essential for the effective and efficient implementation of those policies. Strategies and tools are constructed under the foundational institutional conditions. The three elements then continuously influence and iteratively refine each other, progressively evolving into a well-integrated, mutually matched, and enduringly dynamic system for sustainable development. This sustained interaction fosters a long-term, effective process of stakeholder collaboration, enabling the transition of low-carbon community policies into its spatial interpretation. This can trigger a continuously accumulating positive spatial feedback loop.ConclusionBoth the indicator-based, highly quantified standardized evaluation pathways and the guidance-oriented, customized adaptive governance pathways have successfully engaged diverse social stakeholders, providing effective guidance or feedback mechanisms for low-carbon community development and forming a robust foundation for practical implementation and scaling-up. Therefore, to achieve the spatial grounding and positive accumulation of low-carbon development, the three elements — institutions, strategies, and tools — ought to be mutually aligned, forging a long-term, effective collaborative relationship among the stakeholders involved. Based on China’s current low-carbon community development, this research proposes three key optimization directions to enhance implementation effectiveness. This research argues that spatial – ecological landscape design tools that assist carbon reduction should be developed, thereby enhancing the spatial benefits and wider dissemination of China’s low-carbon community policies. First, to implement low-carbon community policies, market-based stakeholders should be incorporated to create a multi-stakeholder governance mechanism. Public funds should be strategically leveraged to attract social capitals, fostering a multi-stakeholder collaborative development mechanism. Unlike international practices, China’s current low-carbon community development relies heavily on direct government investment, resulting in significant financial burdens and limited scalability. To address this, mechanisms such as performance-based rewards and reputation marketing campaigns should be introduced to incentivize developers, businesses, and residents to actively participate in low-carbon projects. By ensuring all stakeholders perceive tangible benefits, broader support can be mobilized to collaboratively create sustainable communities. Second, technical exchanges and process-oriented coaching should be used to intensify design interactions. The fundamental purpose of developing a comprehensive indicator system is to achieve real carbon emission reductions in line with China’s “carbon peaking and carbon neutrality goals”. Technical exchanges and ongoing process support allow proven technical methods from pilot projects to be closely integrated with current project conditions, while progressively aligning low-carbon management practices and spatial design optimization requirements with each project’s renewal objectives. Only in this way can relatively abundant government funds be directed toward the specific and realistic needs of each project. Finally, policies should incorporate design strategies for spatial and ecological landscape optimization and tools tailored specifically to the community level, so as to ensure effective project implementation. International best practices demonstrate that spatial adjustments and optimizations can simultaneously enhance quality of life and reduce resource consumption, achieving low-carbon goals at a lower cost. Integrating spatial design elements into China’s low-carbon community policies, alongside existing technological carbon-reduction measures, can enable a more comprehensive and coordinated implementation of low-carbon strategies at the community level. This approach not only improves resource efficiency but also creates more livable and sustainable environments. This will align with global best practices while addressing the unique challenges and opportunities within China’s institutional and developmental context, ultimately contributing to the China’s broader climate goals.

Spartaco Paris, Vincenzo Gattulli, Roberto Bianchi et al.

Within the framework of technology transfer opportunities promoted by the third mission of research, this paper presents the activities of a Sapienza start-up engaged in a funded project on territorial innovation ecosystems, TECNODIGIT, co-financed by the PNRR. The applied research explores the innovative use of Digital Twins in civil engineering and architecture through two case studies, namely the infrastructure of the Gran Sasso National Laboratories, and the Esedra in the Capitoline Museums, where the equestrian monument of Marcus Aurelius is exhibited. By integrating IoT sensors and BIM models, the project aims to develop advanced methodologies for automated monitoring, maintenance, and inspection of the built environment. Selected by Rome Technopole, the project combines automation, real-time analysis, and machine learning, contributing to the digitalisation of the construction sector.

Alessandro Basso

<p>The concept of an archive has undergone considerable evolution over time, transforming itself from a simple repository of memory into a dynamic and versatile tool capable of actively interacting with society. From a place for storing information organized chronologically or by type, the archive has become an essential cultural, political, and social resource for research and knowledge. This transformation reflects a profound change in the archive, which is now conceived not only as a means of recovering historical memory, but also as an operational basis for contemporary design. <br />In this context, the proposal for a dynamic and interactive archive enhanced by artificial intelligence offers an innovative perspective. Designed as an online portal, these archives offer a fluid and multifaceted exploration experience, accessible through two-dimensional and three-dimensional modes. Users can dynamically navigate within a 3D virtual space, interacting with 20th-century architectural content, presented both in high-resolution digital form (2D) and as three-dimensional models, accessible via virtual reality or desktop. <br />The archive uses complex algorithms and artificial intelligence to adjust the layout of the works within the 3D environment, creating variable configurations based on specific parameters, such as keywords or search areas. With the help of a simple activator, it is possible to switch between 2D and 3D views, revealing further aesthetic and exploratory possibilities. <br />This methodological approach, based on 2.0 interactions, also offers the possibility of integrating new technologies, such as augmented reality or crowdsourcing mechanisms, in the future. In this way, the archive could evolve autonomously, fueled by collective participation and artificial intelligence management, giving rise to a constantly expanding and self-organizing organism.</p><p>DOI: https://doi.org/10.20365/disegnarecon.34.2025.29</p>

Francesca Thiebat, Fiamma Morselli

This contribution highlights the need to reflect on the environmental, cultural, and social value of biogenic construction materials and their role in the roadmap towards climate neutrality. Based on a mapping of European case studies, the essay investigates the diffusion of biogenic materials in architecture, questioning whether their use is limited to experimental cases or if it can be at the base of a decarbonisation strategy. The analysis conducted reveals the urgency of adopting technologies and practices that promote the diffusion and scalability of biogenic materials to respond to energy and environmental regulations, as well as  to contribute effectively and sustainably to the demand for net-positive materials, as alternatives to conventional ones. This contribution highlights the need to reflect on the environmental, cultural, and social value of biogenic construction materials and their role in the roadmap towards climate neutrality. Based on a mapping of European case studies, the essay investigates the diffusion of biogenic materials in architecture, questioning whether their use is limited to experimental cases or if it can be at the base of a decarbonization strategy. The analysis conducted reveals the urgency of adopting technologies and practices that promote the diffusion and scalability of biogenic materials to respond, on the one hand, to energy and environmental regulations and, on the other hand, to contribute effectively and economically sustainably to the demand for net-positive materials, as alternatives to conventional ones.

Sebahat Sevde Sağlam, Nazife Özer, Seden Acun Özgünler

Boron is a rare metalloid found in borate minerals like borax, kernite, colemanite, and ulexite. In the construction sector, it is used to protect wood from fungi, insects, and decay, as well as to enhance fire resistance in building materials. Additionally, it serves as an additive in cement and concrete to improve structural properties. This study investigated the effects of ground colemanite (45 µm and 75 µm) as a partial substitute (0-3%) for natural hydraulic lime (NHL 3.5) in mortar. The 28-day mechanical strength and physical properties of the samples were analyzed. Results showed that colemanite improved compressive strength but had little impact on other characteristics, including water absorption. This indicates that at low concentrations, colemanite does not significantly affect the mortar's water permeability.

Erdem Köymen

This study explores the stylization of architectural elements in 3D animated films, emphasizing their crucial role in visual storytelling. Using qualitative research methods, 10 films were analyzed, showcasing diverse periods, cultural themes, and aesthetic styles. The findings reveal that architectural elements are not just passive backgrounds but active narrative components that shape emotional and visual dynamics. Real-world architectural references are reinterpreted through historical or futuristic stylizations, manipulating form, texture, material, and lighting to create immersive atmospheres. By exaggerating proportions, simplifying structures, or using abstract forms, stylization visually reflects characters’ psychological states and enhances the dramatic flow of the story. The research highlights that stylized architecture enriches the visual experience while reinforcing the narrative structure, drawing viewers more deeply into the animated world. The concept of “hyperreality” helps explain how animated films use stylization to transcend physical realism, unlocking greater creative freedom. This process allows architecture to shape the film’s atmosphere, guide audience perception, and establish a cohesive visual language that amplifies storytelling. Ultimately, the study demonstrates that architectural stylization is not merely an aesthetic choice but a powerful narrative device. The findings propose narrative-driven design as a new approach for creating emotionally resonant spaces in both animation and architectural practice.

Kamil Szczepanik, Jarosław A. Chudziak

Software architecture design is a fundamental part of creating every software system. Despite its importance, producing a C4 software architecture model, the preferred notation for such architecture, remains manual and time-consuming. We introduce an LLM-based multi-agent system that automates this task by simulating a dialogue between role-specific experts who analyze requirements and generate the Context, Container, and Component views of the C4 model. Quality is assessed with a hybrid evaluation framework: deterministic checks for structural and syntactic integrity and C4 rule consistency, plus semantic and qualitative scoring via an LLM-as-a-Judge approach. Tested on five canonical system briefs, the workflow demonstrates fast C4 model creation, sustains high compilation success, and delivers semantic fidelity. A comparison of four state-of-the-art LLMs shows different strengths relevant to architectural design. This study contributes to automated software architecture design and its evaluation methods.

Shuvra S. Bhattacharyya, Marilyn Wolf

System-level design, once the province of board designers, has now become a central concern for chip designers. Because chip design is a less forgiving design medium -- design cycles are longer and mistakes are harder to correct -- system-on-chip designers need a more extensive tool suite than may be used by board designers and a variety of tools and methodologies have been developed for system-level design of systems-on-chips (SoCs). System-level design is less amenable to synthesis than are logic or physical design. As a result, system-level tools concentrate on modeling, simulation, design space exploration, and design verification. The goal of modeling is to correctly capture the system's operational semantics, which helps with both implementation and verification. The study of models of computation provides a framework for the description of digital systems. Not only do we need to understand a particular style of computation, such as dataflow, but we also need to understand how different models of computation can reliably communicate with each other. Design space exploration tools, such as hardware/software co-design, develop candidate designs to understand trade-offs. Simulation can be used not only to verify functional correctness but also to supply performance and power/energy information for design analysis. This chapter employs two applications -- video and neural networks -- as examples. Both are leading-edge applications that illustrate many important aspects of system-level design.

Jiayu Li, Masood Mortazavi, Ning Yan et al.

The goal of inverse design in distributed circuits is to generate near-optimal designs that meet a desirable transfer function specification. Existing design exploration methods use some combination of strategies involving artificial grids, differentiable evaluation procedures, and specific template topologies. However, real-world design practices often require non-differentiable evaluation procedures, varying topologies, and near-continuous placement spaces. In this paper, we propose DCIDA, a design exploration framework that learns a near-optimal design sampling policy for a target transfer function. DCIDA decides all design factors in a compound single-step action by sampling from a set of jointly-trained conditional distributions generated by the policy. Utilizing an injective interdependent ``map", DCIDA transforms raw sampled design ``actions" into uniquely equivalent physical representations, enabling the framework to learn the conditional dependencies among joint ``raw'' design decisions. Our experiments demonstrate DCIDA's Transformer-based policy network achieves significant reductions in design error compared to state-of-the-art approaches, with significantly better fit in cases involving more complex transfer functions.

H. Ishii, Minoru Kobayashi

Luca Collini, Siddharth Garg, Ramesh Karri

High Level Synthesis (HLS) tools offer rapid hardware design from C code, but their compatibility is limited by code constructs. This paper investigates Large Language Models (LLMs) for refactoring C code into HLS-compatible formats. We present several case studies by using an LLM to rewrite C code for NIST 800-22 randomness tests, a QuickSort algorithm and AES-128 into HLS-synthesizable c. The LLM iteratively transforms the C code guided by user prompts, implementing functions like streaming data and hardware-specific signals. This evaluation demonstrates the LLM's potential to assist hardware design refactoring regular C code into HLS synthesizable C code.

Luyao Shi, Michael Kazda, Bradley Sears et al.

Electronic design engineers are challenged to find relevant information efficiently for a myriad of tasks within design construction, verification and technology development. Large language models (LLM) have the potential to help improve productivity by serving as conversational agents that effectively function as subject-matter experts. In this paper we demonstrate Ask-EDA, a chat agent designed to serve as a 24x7 expert available to provide guidance to design engineers. Ask-EDA leverages LLM, hybrid retrieval augmented generation (RAG) and abbreviation de-hallucination (ADH) techniques to deliver more relevant and accurate responses. We curated three evaluation datasets, namely q2a-100, cmds-100 and abbr-100. Each dataset is tailored to assess a distinct aspect: general design question answering, design command handling and abbreviation resolution. We demonstrated that hybrid RAG offers over a 40% improvement in Recall on the q2a-100 dataset and over a 60% improvement on the cmds-100 dataset compared to not using RAG, while ADH yields over a 70% enhancement in Recall on the abbr-100 dataset. The evaluation results show that Ask-EDA can effectively respond to design-related inquiries.

Adriana Marra, Luca Vespasiano

<p>Digital surveying and rapid prototyping techniques are important tools to support processes related to cultural and architectural heritage. Digital surveying can be used to document, analyse, and enjoy the built heritage thanks to point clouds and detailed digital models resulting from the processing of data acquired during field activities. 3D printing, on the other hand, enables the creation of realistic physical replicas of heritage artefacts that can support activities related to analysis, documentation, conservation, valorisation and enjoyment. The use and combination of these techniques to architectural and cultural heritage have brought benefits and advantages since digital and physical replicas can be used in the processes of documenting, analysing, preserving and enhancing historical artefacts by promoting their accessibility on multiple levels.</p><p>The paper discusses the results of research aimed at defining and testing an effective workflow for the development of physical models suitable for the analysis, documentation and communication of architectural heritage. The experimentation was performed considering as a case study a peculiar element of architecture, a historical portal. The paper illustrates the technical challenges faced starting from the photogrammetric survey to the digital reconstruction of the analysed artefact for 3D printing, with a focus on the printing parameter settings used to produce physical replicas with high-quality, but different resolutions and scales, to be used for several purposes, such as analysis and documentation and education and communication.</p><p><span class="TextRun SCXW86936444 BCX8" lang="EN-GB" xml:lang="EN-GB" data-contrast="auto">DOI: https://doi.org/10.20365/disegnarecon.31.2023.</span><span class="TextRun Highlight SCXW86936444 BCX8" lang="EN-GB" xml:lang="EN-GB" data-contrast="auto"><span class="NormalTextRun SCXW86936444 BCX8">1</span><span class="NormalTextRun SCXW86936444 BCX8">8</span></span><span class="EOP SCXW86936444 BCX8" data-ccp-props="{&quot;201341983&quot;:0,&quot;335559739&quot;:0,&quot;335559740&quot;:240}"> </span></p>

Daniel Elkin , Andrea Navarrete , Gerhard Bruyns et al.

The desire to live vicariously, mirroring behavioural conditions external to one’s own home, gives each home multiple lives in a hyper-functional world. Technology’s fusion with the home produces two outcomes. First, the ability to capture comprehensive, three-dimensional records of a home’s physical conditions and traces using light detection and ranging (LiDAR) data, connects functional layout more concretely to behavioural scripts. Second, virtual mirroring converts transferable information about the home from generalities to hyper-specific singularities. A home’s digital twin can contribute to archives of domestic conditions disseminated as assets for access, download, and manipulation in other media. Behavioural simulation and gaming can simulate exact domestic conditions from throughout the world, rather than interpreted approximations. This paper draws on projects developing digital twins of homes in several locations in Hong Kong. Researchers are using 3D scanning technology to record homes in public housing flats and in the stilt house architecture of Tai O Village. The paper discusses technology and workflows employed, theorizing the technological and social impacts of domestic digital twins in data archives. The paper uses graphic precedents to demonstrate archiving protocols and speculate on influences the post-digital turn will have on domestic environments and behaviour.

Sara Pieri, Jose Renato Restom, Samuel Horvath et al.

Federated Learning (FL) is a promising research paradigm that enables the collaborative training of machine learning models among various parties without the need for sensitive information exchange. Nonetheless, retaining data in individual clients introduces fundamental challenges to achieving performance on par with centrally trained models. Our study provides an extensive review of federated learning applied to visual recognition. It underscores the critical role of thoughtful architectural design choices in achieving optimal performance, a factor often neglected in the FL literature. Many existing FL solutions are tested on shallow or simple networks, which may not accurately reflect real-world applications. This practice restricts the transferability of research findings to large-scale visual recognition models. Through an in-depth analysis of diverse cutting-edge architectures such as convolutional neural networks, transformers, and MLP-mixers, we experimentally demonstrate that architectural choices can substantially enhance FL systems' performance, particularly when handling heterogeneous data. We study 19 visual recognition models from five different architectural families on four challenging FL datasets. We also re-investigate the inferior performance of convolution-based architectures in the FL setting and analyze the influence of normalization layers on the FL performance. Our findings emphasize the importance of architectural design for computer vision tasks in practical scenarios, effectively narrowing the performance gap between federated and centralized learning. Our source code is available at https://github.com/sarapieri/fed_het.git.

Gabriela Molina León

Making technology design inclusive requires facing multiple challenges in different dimensions: the populations we work with, who we are, what interaction possibilities we consider, and what context we examine. We reflect on these challenges and propose two main measures to achieve research inclusiveness.

Rebekah Rousi

In an ever more connected world, awareness has grown towards the hazards and vulnerabilities that the networking on sensitive digitized information pose for all parties involved. This vulnerability rests in a number of factors, both human and technical.From an ethical perspective, this means people seeking to maximise their own gain, and accomplish their goals through exploiting information existing in cyber space at the expense of other individuals and parties. One matter that is yet to be fully explored is the eventuality of not only financial information and other sensitive material being globally connected on the information highways, but also the people themselves as physical beings. Humans are natural born cyborgs who have integrated technology into their being throughout history. Issues of cyber security are extended to cybernetic security, which not only has severe ethical implications for how we, policy makers, academics, scientists, designers etc., define ethics in relation to humanity and human rights, but also the security and safety of merged organic and artificial systems and ecosystems.