Design Knowledge Research Articles

Reference architecture design and evaluation for digitalization of underground mining

Digitalization of underground mining operations requires interaction and interoperability between multiple stakeholders and their technical systems. A reference architecture (RA) facilitating design of multi-stakeholder digital solutions for underground mining would be valuable design knowledge for mining industry digitalization activities and would facilitate the design of concrete architectures to the underground mining context. The main contribution of this work is RA design, which is missing in the current research literature. The RA has empirical foundation on the implementation architectures of two prototypes, which were demonstrated and evaluated in an underground mining environment. The prototypes were evaluated based on several design science research evaluation criteria (feasibility, efficiency, robustness, operability) for fulfilling architectural concerns of related stakeholders. Digital Twin-based modeling, MQTT-based messaging, high accuracy location monitoring of vehicles with Lidars, reliable communication with 5G SA network, and utilization of safety zones and safety messaging for enabling emergency stops were identified as important aspects for RA design. Digital Twin (DT)-based data models focusing on the modeling of mining site, moving vehicles, communication data, and related equipment for the underground mining context may be considered as an additional contribution of our study.

Enhanced agency and the visual thinking of design

Abstract Visual thinking is a systematic way to produce knowledge in design by means of mental imagery, spatial reasoning, and the use of an array of visual representations. Pictorial representations such as sketches are crucial for the activity of designing at the early stage of the creative process. Designers see more information in sketches than was actually drawn. The ability to see more information than is sketched out can be seen as an enhanced visual capacity of human agency. Enhanced agency is the prosthetic incorporation of artifacts to improve the original agentive capacities. The incorporation of artifacts to draw raises some fundamental questions: Is the pencil an extension of the mind? Can we think with our hands? What agentive capacities are increased with the use of the pencil? What is the representational status of sketching? The chapter is structured around these key questions to suggest some answers inspired by the work of Göran Sonesson. Using the notion of enhanced agency and the layered model of agency, I explore the way in which the pencil improves the visual thinking of design. In doing so I found that it is important to maintain the principle of asymmetry in cognitive systems to reconsider relational ontology in favor of ecological relationships.

The Importance of Large-Scale Genomic Studies to Unravel Genetic Risk Factors for Autism.

Autism spectrum disorder (ASD) is a common and highly heritable neurodevelopmental disorder. During the last 15 years, advances in genomic technologies and the availability of increasingly large patient cohorts have greatly expanded our knowledge of the genetic architecture of ASD and its neurobiological mechanisms. Over two hundred risk regions and genes carrying rare de novo and transmitted high-impact variants have been identified. Additionally, common variants with small individual effect size are also important, and a number of loci are now being uncovered. At the same time, these new insights have highlighted ongoing challenges. In this perspective article, we summarize developments in ASD genetic research and address the enormous impact of large-scale genomic initiatives on ASD gene discovery.

Pythagorean Music Theory and Its Application in Renaissance Architectural Design

This article concerns Alberti's approach to architectural design integrates Pythagorean consonance ratios from music theory, not by direct application but as a conceptual guide for aesthetic ratios in buildings. He expands spatial dimensions using methods derived from past artisans, adhering to and building upon the foundational consonance ratios. While applying these two-number proportions to width and length poses no problem, calculating height in a three-dimensional space requires a three-number proportion. Alberti resolves this issue by adopting the mean value strategy from music theory, where the mean is typically the middle value in an octave ratio, to determine the height in the spatial configuration. Alberti advocates for architects to leverage the insights of skilled artisans. However, his own architectural work demonstrates deviations from his theoretical principles. This study highlights Alberti's application of musical intervals such as the major and minor thirds, sixths, and sevenths, which were not traditionally emphasized in the musical science of the quadrivium, focused primarily on octaves, fifths, and fourths. These choices reflect the broader evolution of music during the 15th century, marking a shift towards "practical music" and signaling music's departure from the liberal arts to become a significant element of the fine arts, showcasing the influence of Pythagorean consonance in European music and arts through the 16th century. Thus, this article reflects the interactions between music and architecture of knowledge received from ancient Greek civilization in the Renaissance. The art of music in this period is founded on the philosophy and knowledge of Pythagoras.

An automatic completion method for design domain knowledge graph using surrogate model, for rapid performance evaluation

The data and information generated during the design process, such as part parameters, affect the efficiency and quality of product design. Knowledge graph (KG) is often used to express and reuse the above knowledge. However, due to the decentralised and complex nature of the KG, it lacks the quantitative knowledge required for part selection, e.g. the relationship between part type and performance. To complete the knowledge and meet the requirements for rapid and accurate performance evaluation, this paper proposes an automatic KGC method based on a surrogate model. Firstly, the schema layer is established based on the design knowledge ontology. For the sampling process, the query statement is applied to extract knowledge such as design parameters, which define the range of sample points. Secondly, the design of experiments (DOE) method can obtain the data set of the target performance through simulation. Surrogate models are built based on multiple machine learning algorithms. Meanwhile, the hyperparameter optimisation method can further improve the prediction accuracy of the model. Finally, the performance of the design scheme is predicted, and the results are used to complete the KG through knowledge extraction. The method is validated by the selection and evaluation of bogie parts.

A closed-loop human-computer interactive design method based on sequential human intention prediction and knowledge recommendation

Designers working on large-scale complex engineering projects may encounter design errors due to limited experience and expertise. Therefore, during the design process, accurately identifying the designer’s design intention and recommending relevant design knowledge can enhance design efficiency and reduce errors. In this paper, we propose a closed-loop human–computer interactive design method based on sequential human intention prediction and knowledge recommendation. This method leverages the Function-Behaviour-Structure (FBS) model to reduce the dimensionality of design action sequences, so as to facilitate the analysis of potential design patterns. The processed action sequences are used to train Transformer to predict design intentions. In different input sequences, Transformer achieved a highest prediction accuracy of 92.09%. We construct a Design Knowledge Recommendation Framework (DKRF) and its corresponding design knowledge matching algorithm. This framework accurately recommends design knowledge to designers, solving design stagnation and improving design efficiency. Finally, a case study of four types of mechanical model design is conducted to demonstrate the feasibility and wide applicability of the proposed closed-loop human–computer interactive design method.

Advancing surgical VQA with scene graph knowledge

PurposeThe modern operating room is becoming increasingly complex, requiring innovative intra-operative support systems. While the focus of surgical data science has largely been on video analysis, integrating surgical computer vision with natural language capabilities is emerging as a necessity. Our work aims to advance visual question answering (VQA) in the surgical context with scene graph knowledge, addressing two main challenges in the current surgical VQA systems: removing question–condition bias in the surgical VQA dataset and incorporating scene-aware reasoning in the surgical VQA model design.MethodsFirst, we propose a surgical scene graph-based dataset, SSG-VQA, generated by employing segmentation and detection models on publicly available datasets. We build surgical scene graphs using spatial and action information of instruments and anatomies. These graphs are fed into a question engine, generating diverse QA pairs. We then propose SSG-VQA-Net, a novel surgical VQA model incorporating a lightweight Scene-embedded Interaction Module, which integrates geometric scene knowledge in the VQA model design by employing cross-attention between the textual and the scene features.ResultsOur comprehensive analysis shows that our SSG-VQA dataset provides a more complex, diverse, geometrically grounded, unbiased and surgical action-oriented dataset compared to existing surgical VQA datasets and SSG-VQA-Net outperforms existing methods across different question types and complexities. We highlight that the primary limitation in the current surgical VQA systems is the lack of scene knowledge to answer complex queries.ConclusionWe present a novel surgical VQA dataset and model and show that results can be significantly improved by incorporating geometric scene features in the VQA model design. We point out that the bottleneck of the current surgical visual question–answer model lies in learning the encoded representation rather than decoding the sequence. Our SSG-VQA dataset provides a diagnostic benchmark to test the scene understanding and reasoning capabilities of the model. The source code and the dataset will be made publicly available at: https://github.com/CAMMA-public/SSG-VQA.

The Revelations of New Quality Productive Forces on the Work of University Counselors

In the contemporary milieu, characterized by the dynamic interplay of technological prowess and interdisciplinary synthesis inherent in new quality productive forces, myriad spheres stand profoundly impacted. Among these, the job of university counselor finds itself amidst fresh horizons of opportunity and challenge under its transformative influence. This discourse endeavors to delve into the reverberations of new quality productive forces on the endeavors of university counselors, embarking on a comprehensive analysis spanning dimensions such as knowledge architecture, working patterns, student cultivation, and the pedagogical resource landscape, with the aim of furnishing insights and paradigms for pedagogical innovation. Central to this exposition is the elucidation of the novel imperatives precipitated by new quality productive forces, including the imperative for counselors to engage in continual scholarship, harness contemporary technological modalities, foster student capacities, and advocate for the equitable dissemination of educational resources. It is hoped that counselors can adapt to emergent paradigms, assume pivotal roles, and contribute to the cultivation of astute talents poised to navigate the exigencies of future societal evolution. Through theoretical discourse, this treatise endeavors to illumine fresh vistas on the pedagogical endeavor, fostering its progression and maturation.

Nature-Based Design in Stroke Rehabilitation Environments: A Scoping Review.

To identify, examine, and map the characteristics of knowledge of nature-based design in stroke rehabilitation facilities, examine how research in this field has been conducted and identify gaps in knowledge. Many stroke survivors have wide ranging impacts, resulting in long hospital stays to undertake rehabilitation. The physical environment can influence brain recovery; however, there is limited evidence to support the design of effective rehabilitation environments. Conversely, the health benefits available from connection with nature are well established. A nature-based design approach may have benefits and implications for the physical environment of inpatient stroke rehabilitation facilities; however, it is unclear what evidence exists in this field. This scoping review followed the JBI methodological guidance for the conduct of scoping reviews, with systematic searches of six databases. Twenty-eight studies were included in the review. Aims and research methods varied widely. Investigations in 19 studies related to gardens and other designed outdoor nature-based environments. Other studies explored natural analogues, nature inside, inside/outside connections, and the natural environment. Findings from the studies were spread across the fields of design, use, exposure to, and engagement in nature-based environments. The characteristics of knowledge underpinning nature-based design in stroke rehabilitation environments are highly diverse, and significant gaps exist in the evidence base. A framework developed during this review for mapping knowledge on the intentions and impacts for spaces and services in this field assisted to identify these gaps and may be applied to other areas of healthcare design research.

Evaluation of cooling energy saving and ventilation renovations in office buildings by combining bioclimatic design strategies with CFD-BEM coupled simulation

Bioclimatic design knowledge and measures, including passive techniques and natural ventilation cooling, are urgently for building renovation to mitigate global warming. The performance of indoor airflow, energy, economic, and environmental aspects has been researched separately. However, developing a comprehensive framework to investigate bioclimatic strategies under the impact of climate change is challenging. This study aims to integrate bioclimatic design strategies with a coupled simulation approach using Fluent and EnergyPlus to evaluate retrofitting techniques for a single-room office in a university building in a hot summer and cold winter climate. A bioclimatic analysis was conducted to recommend cost-effective passive cooling strategies, including natural ventilation and window shading systems. Two passive measures, changing window types and furniture layouts, were included in renovation packages. Results indicated that the empty model is not valid compared to the fully furnished model when calculating room air change per hour (ACH). Natural ventilation was the most cost-effective strategy to mitigate climate change, with a net present value (NPV) ranging from USD 135.09 to 402.81 over 30 years. However, a higher ACH did not ensure a longer natural ventilation period. By changing the top-hung window to a vertical sash and implementing a movable furniture layout, can achieve better ventilation efficiency. The installation of window vertical shadings had the highest annual emission savings by 2080, while it performed negative economic viability in both the present and the 2050 climates. This research demonstrated how combining bioclimatic measures with a co-simulation approach can offer a thorough evaluation of building energy retrofitting. The results could support architectural and engineering design by integrating bioclimate measures to identify the most effective strategies.

Improving emergency and disaster response management through bidirectional communication between citizens and decision-makers – A field test on the coordination of spontaneous volunteers

Cooperation between different stakeholders plays an important role in managing crises and disasters. The software tools used must also support cooperation and the mutual exchange of information. The bidirectional exchange of information between the population and official agencies poses a particular challenge. In this paper, we present a software demonstrator for the coordination of spontaneous volunteers and its evaluation as part of an overarching research project to gain design knowledge for the development of interconnected systems in disaster management. We describe how the system demonstrator was instantiated on the basis of our existing design knowledge from technical requirements and reference architecture and show the respective interfaces for the stakeholders involved. As the main contribution of the paper, we describe the implementation of a field test to evaluate the demonstrator and present the results in terms of usability and perceived usefulness, which we obtained using a methodologically sound questionnaire.

Interactive Batik & HR Incubation for Art-Technopreneurship: Mantraman Village Pilot Project

The implementation of this activity presents an innovative approach to promote the sustainability of the Javanese batik industry by developing interactive batik designs and fostering human resources in the arts and technopreneurship fields. The research project undertaken in Mantraman Village, Pagelaran, aims to brand Mantraman Village as a unique destination embodying Javanese Cultural Village characteristics. The cutting-edge approach combines age-old batik techniques with the latest in digital augmented reality technology. By doing so, it aims to boost visitor engagement and offer a hands-on experience in the batik design process. This implementation also focuses on fostering human resources in the arts and technopreneurship fields. These educational activities are designed to impart both theoretical knowledge and practical skills, empowering individuals to venture into or further develop their own art-technopreneurial pursuits. Training programs and workshops are conducted to develop participants’ skills and knowledge in batik design, business management, marketing, and related technological aspects. This implementation methodology involves conducting participatory surveys, observations, and interviews with relevant stakeholders, as well as testing and evaluating prototypes of interactive batik design systems. The data collected will be analyzed qualitatively and quantitatively to measure the project’s impact on increasing public interest, improving the quality of batik products, and developing human resources in the arts and technopreneurship fields. The results of the implementation of this activity made a positive contribution through an inventory of interactive batik motif designs with augmented reality technology, contributing to the development of the batik industry in Mantraman Village, Pagelaran Village as an iconic tourism village branding. Through these efforts, the project contributes positively to the sustainable growth of the batik industry and cultural branding of the village. Keywords: interactive, pattern, batik, mantraman village, pagelaran

Cross-domain heterogeneous metasurface inverse design based on a transfer learning method.

In this Letter, a transfer learning method is proposed to complete design tasks on heterogeneous metasurface datasets with distinct functionalities. Through fine-tuning the inverse design network and freezing the parameters of hidden layers, we successfully transfer the metasurface inverse design knowledge from the electromagnetic-induced transparency (EIT) domain to the three target domains of EIT (different design), absorption, and phase-controlled metasurface. Remarkably, in comparison to the source domain dataset, a minimum of only 700 target domain samples is required to complete the training process. This work presents a significant solution to lower the data threshold for the inverse design process and provides the possibility of knowledge transfer between different domain metasurface datasets.

Intelligent design of reconfigurable flexible assembly fixture for aircraft panels based on smart composite jig model and knowledge graph

The current demand for aircraft panel assembly fixtures necessitates agile manufacturing solutions. Traditional welding fixtures struggle to meet diverse panel types, high quantities, and short manufacturing cycles. Conversely, reconfigurable flexible assembly fixtures offer universality, efficiency and ease of maintenance but heavily rely on designers' experience, hindering knowledge reuse. Existing research on computer-aided fixture design (CAFD) primarily addresses specialized fixtures, neglecting reconfigurable flexible ones, lacking fixture design knowledge systems. Aiming at the above problems, the study proposes an intelligent design method for the reconfigurable flexible assembly fixture for aircraft panels based on the smart composite jig model (SCJM) and knowledge graph (KG). Firstly, based on the SCJM of the aircraft panel type assembly fixture (PSCJM), a configuration design method is proposed to carry out the multi-level design of reconfigurable assembly fixture to instantiate PSCJM containing fixture configuration rules and a module library based on model definition (MBD). Then, a knowledge retrieval method is proposed to search the suitable fixture design knowledge based on KG, assisting designers in achieving the flexible design of aircraft panel reconfigurable assembly fixtures. Finally, practical engineering design validation confirms the method's feasibility and effectiveness in obtaining the reconfigurable flexible assembly fixture design scheme for aircraft panels.

The SICO Color Naming Project

How can interior design educators develop closer ties to industry? How do we develop mutually beneficial relationships, which respect the integrity of academic intellectual freedom and contribute to the development of disciplinary knowledge while providing useful services to industries competing in a market-driven economy? The SICO Color Naming Project was a successful university-industry collaboration that used design knowledge and methods as the basis for an innovative, result-driven process. It explains how an industry need led to the development of a new way to name colours, and how colour affectivity played a key role in the project, providing a catalyst for the naming process. During this process, a multidisciplinary team worked together to develop a novel framework for designing coherent, structured, and emotionally resonant links between colours and names. This paper describes the phenomenologically grounded strategy used to manage the design process and guide the team through the naming of 2400 colours in two languages.

Reading room/ Writing roam

This paper discusses a final year course in which students were invited to?discuss design through reading, writing and making. The course had two? main goals - research and critical reflection. During the course students studied 'closely associated' words to determine meaning in order to parallel their use in other discipline s. The chosen words focussed on the notion/act of adding-to, embellishing, or inserting into/onto existing conditions. Since the words were researched through disciplines other than interior and architecture, new meanings or interpretations helped formulate architectural propositions about space, surface, form, etc., thus extending our knowledge and understanding of design.

A Comprehensive Study on Net Zero Energy Buildings and Sustainable Construction Materials with Low Carbon Contents

One-third of the world's greenhouse gas emissions come from the building industry, with embodied carbon from the manufacture of building materials accounting for a sizable portion of these emissions. Prior research has mostly focused on examining the carbon emissions of low-rise structures, but it has failed to consider the significant influence that high-rise buildings have on a city's overall carbon emissions. Net-zero energy buildings (NZEBs) combine intelligent energy management strategies with conventional design knowledge to facilitate a sustainable and eco-friendly transition. The NZEB building revolution has the potential to become a long-term structural pillar for structures to come. The purpose of this study is to assess how various design factors and the embodied carbon in high-rise structures relate to one another. Additionally, the goal of this research is to keep annual consumer energy comfort in a home NZEB at its highest level without using any electricity from the electrical grid. In order to achieve long-term climate goals, our work emphasises the socio-economic advantages of adopting NZE buildings and further empowers consumer participation to minimise energy waste and carbon emissions. The findings provide a foundation for constructing high-rise structures in a more ecologically conscious manner to lower the structure's carbon emissions. The evaluation and comparison of the embedded carbon values takes into account the carbon emissions from the transportation and material manufacturing processes.

Fostering innovation through bio-inspired projects in engineering design education

AbstractThis paper discusses the C-K theory approach and developing templates for student's use in design courses, specifically for the conceptual design phase. Examples of C-K templates are reviewed to demonstrate the process leading to a design solution. Analysis of student's work using these templates are presented and discussed with respect to design learning attributes and design innovation during the conceptual design. Student reflections from their final design reports indicated that students did develop knowledge and skills in bio-inspired design, collaboration, and interdisciplinary mindsets.

Local perturbation-based black-box federated learning attack for time series classification

The widespread adoption of intelligent machines and sensors has generated vast amounts of time series data, leading to the increasing use of neural networks in time series classification. Federated learning has emerged as a promising machine learning paradigm that reduces the risk of user privacy leakage. However, federated learning is vulnerable to backdoor attacks, which pose significant security threats. Furthermore, existing unrealistic white-box methods for attacking time series result in insufficient adaptation and inferior stealthiness. To overcome these limitations, this paper proposes a gradient-free black-box method called local perturbation-based backdoor Federated Learning Attack for Time Series classification (FLATS). The attack is formulated as a constrained optimization problem and is solved using a differential evolution algorithm, without requiring any knowledge of the internal architecture of the target model. In addition, the proposed method considers the time series shapelet interval as a local perturbation range and adopts a soft target poisoning approach to minimize the difference between the attacker model and the benign model. Experimental results demonstrate that our proposed method can effectively attack federated learning time series classification models with potential security issues while generating imperceptible poisoned samples that can evade various defence methods.

An agent architecture for expressive spatial knowledge and reasoning in land use modeling and simulations

This paper presents a new cognitive agent design approach integrating spatial knowledge representation and reasoning in agent-based modeling dedicated to land use simulations. A deep motivation for our agent-centric contribution is the ever-increasing development of spatially explicit agent simulation platforms. We build on this technological evolution and topology theory to endow the agent with human’s spatial representation and reasoning following a Belief–Desire–Intention architecture. A pilot implementation of the methodology with simulation experiments on a hunting model was carried out in GAMA platform to assess agent performances. Simulations display a consistent trend of animal population dynamics and also confirm a high model sensitivity to the integration of spatial knowledge and reasoning in agent-based models of human actor. These results demonstrate a successful implementation and the importance of spatial dimension in the expressive power and the validity of agent-based models. Future research efforts should therefore emphasize on designing human knowledge representation and incorporating learning abilities to improve models efficiency.