Reasoning about dynamic systems with a fine-grained temporal and numeric resolution presents significant challenges for logic-based approaches like Answer Set Programming (ASP). To address this, we introduce and elaborate upon a novel temporal and constraint-based extension of the logic of Here-and-There and its nonmonotonic equilibrium extension, representing, to the best of our knowledge, the first approach to nonmonotonic temporal reasoning with constraints specifically tailored for ASP. This expressive system is achieved by a synergistic combination of two foundational ASP extensions: the linear-time logic of Here-and-There, providing robust nonmonotonic temporal reasoning capabilities, and the logic of Here-and-There with constraints, enabling the direct integration and manipulation of numeric constraints, among others. This work establishes the foundational logical framework for tackling complex dynamic systems with high resolution within the ASP paradigm.

In this paper, we explore the relationship between divergent thinking and stakeholder identification on 15 student engineering design teams. We examine the relationship between fluency, originality, flexibility, and elaboration on the Alternate Uses Task (AUT), a common measure of divergent thinking, and in stakeholder identification. We find fluency and originality to be positively and statistically significantly correlated between the AUT and stakeholder identification task. Flexibility was positively correlated and elaboration was negatively correlated; both lacked statistical significance. Our results suggest that divergent thinking and stakeholder identification may be correlated, and leveraging exercises to improve divergent thinking may also help improve stakeholder identification. Future work can continue to explore this relationship with larger sample sizes and additional tasks.

Engineering systems are represented in a variety of physical, graphical, and virtual ways, supporting decision making about the systems and their operation. As part of a larger research endeavor exploring influences of representation modality, the presented work examines how product identification impacts subsystem clustering behavior. This is achieved through a study using pictorial and functional representations of common household products. Participants were tasked with grouping elements into non-overlapping clusters. Results suggest that correctly identifying a product does not affect clustering behavior regardless of representation modality. This implies that other aspects of the representations are impacting partition convergence. These factors, along with connections to prior work are explored as discussion points and areas of future research.

The possibility of automatic evaluation in online exams offers the advantage of automatic evaluation compared to paper-based exams with manual assessment. Nevertheless, teachers and students have major concerns about digital exams e.g. students are afraid of getting worse grades due to reduced inputs and determined evaluation steps. To analyze these concerns for Engineering Design Education this paper investigates to what extent can be found differences in the results between digital and paper-based examination formats when assessing the same learning outcomes with the same tasks about dimensioning machine elements. The paper contains the transformation of existing paper-based exam tasks into digital automatic evaluable tasks and the data from students participating in a digital exam are compared with data from students with a paper-based exam.

In 1926, Roberto Bartoccini excavated a late-antique tomb at Sirte, Libya. Fifty-three inscriptions in Latin, Greek and Latino-Punic have been recorded and used as evidence of a thriving Christian community. This article reassesses these inscriptions, paying particular attention to the Latino-Punic texts, and discusses the persistence of a Punic identity that can be placed in the context of the wider archaeological landscape.

Design research is highly interdisciplinary, connecting to significant research problems such as the scientificity of design research and blurring boundaries of design disciplines. This paper adopts the perspective of philosophy of technology, regarding design as technical artifact-making activities. It endeavors to identify potential design research approaches based on the evolution of the philosophy of technology, and explain how these approaches have emerged, developed, and evolved. These include: analytic philosophy approach, pragmatism approach, and phenomenology approach. These three research approaches can represent the differentiation rules of design research in both independent and interrelated manners. The clarification can make the philosophical stances of technical artifact-making activities clearer, and provide philosophical references for future design meta-research.

Topology optimization combined with additive manufacturing enables the creation of complex, high-performance products. However, industrial applications often involve numerous and complex requirements, making it challenging to align the design and manufacturing process to meet all demands. A particular challenge is to determine which requirements should be included in the optimization problem statement. This paper presents a procedure model to integrate requirements and feasibility constraints into the design and manufacturing process. It includes two major steps: organizing requirements and constraints in the process and identifying the problem statement. The procedure is applied to the requirements of an engine bracket of AUDI AG, demonstrating its ability to handle numerous requirements and to specify the problem statement.

Recent ice cores from the Allan Hills, a blue ice area in Antarctica, are nearly 3 million years old. These cores extend ice core chronologies, enabling new insight into key climate periods such as the Mid-Pleistocene Transition. The interpretation of these climate records is complex because of the disturbed stratigraphy in this ice. Here, we present a new three-dimensional multitrack electrical conductivity measurement method (3D ECM) to resolve layer structure. We demonstrate this technique on a cumulative 60 m of two large-diameter (241 mm) ice cores, ALHIC2201 and ALHIC2302. Measurements were taken on the upper section of both cores due to better ice core quality in this shallow ice. We find well-defined and dipping layering in both cores, averaging 29° in ALHIC2201 and 69° in ALHIC2302 from horizontal. We observe a slight decrease in dip with depth in both cores, although it only achieves statistical significance in ALHIC2302. We discuss how this new method can be applied to enable accurate, high-resolution multi-proxy record development even in ice cores with steeply dipping layers. 3D ECM improves interpretation of blue ice area cores by providing accurate, non-destructive constraints on stratigraphy.

This study proposed a framework to visualize research trends and create methods to forecast future directions in the design research methodology field from 2018 to 2022. A case study is conducted using a dataset of abstracts from conference proceedings included in the American Society of Mechanical Engineers (ASME) International Design Theory and Methodology Conference track from 2018 to 2022. The proposed method involves extracting keywords from research articles, transforming them into vectors, determining the similarity between keyword pairs to form a keyword network, and constructing a Sankey diagram to show the topic evolution pathways. The resulting Sankey diagrams provide insight into relationships between research topics.

Artificial Intelligence (AI) techniques are increasingly explored to support design activities within the manufacturing context mainly driven by the development of AI technologies. However, few studies were conducted in practice from industrial perspectives. This research aims to understand the opportunities and challenges of AI in design in the real world. A workshop involving twenty-five participants from more than ten manufacturing firms is organised to collect relevant information. The opportunities and challenges identified are categorised by adopting a readily available data-driven design framework. Seven research directions are proposed accordingly to address the industry challenges and opportunities. This research serves as a guide for ensuring future AI in design research and applications are grounded in practice to bridge the gap between academic research and industry practice.

Due to climate change, sustainability has become a crucial topic in product development, while addressing it is associated with many challenges. Based on a literature review, those challenges are collected and clustered into nine categories and sub-categories defined for this purpose. Additionally, a research project is analysed. The exhibited challenges such as data availability versus influenceability, a lack of unified sustainability criteria, and decision-making trade-offs underscore the need for refined methodologies and collaboration in sustainability-oriented design. The differently sourced challenges are compared and the new challenges arising from the research project are sorted into the categories. Finally, possible reasons are discussed for why within the project only challenges from four out of nine categories are encountered.

Volunteer corn is a problem weed in sorghum fields rotated with corn. The commercial availability of imazamox-resistant (igrowth®) and quizalofop-resistant (Double Team™) sorghum allows the use of imazamox and quizalofop, respectively, for controlling grass weeds; however, information is not available regarding their efficacy for control of volunteer corn. The objective of this study was to evaluate the efficacy of imazamox and quizalofop for control, density and biomass reduction of glufosinate/glyphosate-resistant corn volunteers in imazamox- and quizalofop-resistant sorghum. Two separate field experiments were conducted near Clay Center, NE, in 2023 and 2024. Imazamox applied early postemergence (E-POST) and late postemergence (L-POST) (53 and 79 g ai ha–1) controlled up to 98% and 89% of corn volunteers 28 d after application (DAA) in 2023 and 2024, respectively, in igrowth® sorghum. Similarly, quizalofop applied E-POST and L-POST (58 and 73 g ai ha–1) provided 98% and 99% control of volunteer corn in 2023 and 2024, respectively, in Double Team™ sorghum. Quizalofop reduced volunteer corn density (0 to 0.2 plants m–1) and biomass (0 to 13 g m–2) compared to nontreated control in both years. The results suggest that imazamox and quizalofop could be used as POST herbicides for control of glufosinate/glyphosate-resistant corn volunteers in imazamox- and quizalofop-resistant sorghum, respectively.

Advances in information and communication technology (ICT) foster smart systems. Seamless data flows between stakeholders are crucial for their functioning. Designing communication systems to manage data exchange in distributed multi-stakeholder networks is challenged by the complexity of diverse stakeholders with varying interests and data needs. This requires a comprehensive understanding of data flows and communication dynamics. This paper investigates methods for modeling and analyzing data-related links between stakeholders in complex systems. After defining requirements and reviewing available methods, an approach combining dependency and structure modeling (DSM) and systems modeling language (SysML) is identified as most suitable. This is applied to a case study of autonomous buses in public transport, demonstrating its applicability and providing a foundation for further work.

This paper explores the influence of layer variations within Artificial Neural Network (ANN) crowds on their collective behavior and prediction accuracy. While prior research has demonstrated the effectiveness of ANN crowds, understanding how architectural variations impact performance is limited. A coding scheme is used to categorize architectures into distinct behavioral profiles (Normality, Centrality, Width). These profiles provide insights into how individual architecture contributes to the overall behavior and performance of the crowd. The research uses two prediction models. Analysis of behavior distributions across layers reveals minimal fluctuations in both models, suggesting consistent behavior across varying layer configurations. Future work will explore the relationship between layer variations and error metrics to understand their impact on performance.

Gracia de Luna conducted experiments with an HMD virtual environment in which human subjects were presented with surprise distractions. His collected data for head, dominant hand, and non-dominant hand included 6 DOF human subject trajectories. This paper examines this data from 57 human subject responses to those surprise virtual environment distractions using statistical trajectory clustering algorithms. The data is organized and processed with a Dynamic Time Warping (DTW) algorithm and then analyzed using the Density Based Spatial Clustering (DBSCAN) algorithm. The K-means method was used to determine the appropriate number of clusters. Chi Squared goodness of fit was used to determine statistical significance. For five of the data sets, a p value of less than 0.05 was found. These five data sets were found to have a limited relationship to the measured variables.

In this research a study environment is presented that enables iterative design in large engineering lectures and show possibilities for investigations at two example lectures from German universities. The initial results show that it is possible for large lecture-hall-based courses to engage in in-depth tasks of engineering design. Design researchers can use the generated data to measure infuences, e.g. the applied methods on specifc design tasks. Two key insights include the potential for large courses to serve as large-scale research environments for design research and the observed effects of infuences on students’ decision-making processes. This approach offers a promising method to further explore the complexities of decision infuences and design optimization in educational settings.

The domination and exploitation inherent to colonialism entailed casting Africans as violators of European standards, expectations, and even aspirations. This article identifies messaging which permeated the everyday experiences of African wage earners by locating the ways in which employers embedded their understanding of Africans as potential violators into the employment relationship. It examines the records of the Tribunal de Première Instance in Dakar, Senegal, during the decades of high colonialism to reveal the nature of that dynamic, exploring implicit expectations among employers regarding their employees, particularly related to allegations of theft or abandonment of work brought against workers. Analysis of such cases particularly highlights domestic workers, who were overwhelmingly male. The interactions and claims in the justice records reveal clear constructions of violation within the attitudes and actions of non-African employers in colonial Dakar and present the court as a venue for perpetuating that rhetoric.

Regenerative Responsibility (RR) emerges as a transformative framework for design education, addressing the urgent need for sustainability and ethical practices in the field. By integrating principles of ethics, regeneration, and pedagogy, RR redefines the role of designers as agents of systemic change. It incorporates methodologies such as project-based learning, systems thinking, and ethical reflection to align design practices with social, environmental, and economic considerations. Regeneration thinking empowers future designers to adopt innovative and responsible approaches, positioning design education as a catalyst for addressing global challenges and fostering regenerative practices across disciplines.

Topology optimization is a powerful tool for the development of light and strong structures. Due to the preliminary nature of the resulting design proposals, a geometry reconstruction process is required. This primarily serves the purpose to create a functional design. In doing so, parameterization of the geometry and the option to modify are demanded in product development as well as automation. A specific medial axis based reconstruction method not only facilitates the automation, but also the intervention with several possibilities for modification of an optimized design proposal. In this paper, we examine at an examplary use case, how this practice could reduce design iteration cycles, although intermediate new design requirements emerge. We discuss the advantages and limitations of this approach.

This paper introduces a novel methodology for analyzing customer preferences within product ecosystems by leveraging video reviews from social media platforms. The approach includes three stages: collecting and preprocessing video reviews, extracting product features using Latent Dirichlet Allocation (LDA), and analyzing sentiment with the VADER package. By utilizing video reviews, this study captures a more detailed and structured understanding of customer experiences compared to traditional textual reviews, offering actionable guidance for product interoperability and user sentiment analysis. The research highlights the importance of understanding the relationships between products and their accessories, providing specific design insights for creating cohesive product ecosystems that resonate with users on both functional and emotional levels.