Hasil untuk "Mechanical drawing. Engineering graphics"

Annalisa Di Roma, Piera Losciale, Anna Christiana Maiorano et al.

The research project 7.5 “Cultural Value Chain: From Local Traditional Production Districts to a New Country of Origin Effect,” developed under Spoke 7 of the national program, explores design strategies for the cultural enhancement and sustainability of local production chains. Focusing on one of the key assets of Made in Italy - upholstered furniture - the project proposes an integrated model in which territorial identity, technological innovation and production memory converge in a new competitive vision. Through the analysis of the supply chain and the case study of Natuzzi S.p.A., the research led to the definition of a taxonomy of Italian upholstered products, composed of about one hundred icons, structured in a dynamic and searchable database, designed as a design tool and active archive. The digital infrastructure was subsequently translated into a field-tested business archival platform. From these results, the project also proposes an original upholstered product concept that incorporates the design guidelines that emerged, demonstrating the applicability of the model. The work contributes to outlining a regenerative approach to design, capable of strengthening local supply chains and redefining the Country-of-Origin Effect from a cultural and sustainable perspective. 

giuseppe lotti, Ami Licaj, irene fiesoli et al.

The Made in Italy label has historically been associated with excellence rooted in the virtuous integration of design culture, manufacturing craftsmanship, and aesthetic quality. However, in the current context of digital transition, there is an emerging risk of communicative simplification, which tends to obscure the intangible values underlying this identity—particularly those related to sustainability and innovation. The EMOTIONAL project aims to address this critical issue through a design-oriented approach that integrates disruptive technologies—such as Extended Reality (XR) and DV (DV)—to restore narrative depth and accessibility to these complex contents. This contribution presents two complementary approaches developed within the project: an immersive virtual reality experience, centered on an embodied and affective narrative from the perspective of the crafted object, and an interactive semantic atlas mapping the evolution of key concepts related to circularity and sustainability in the context of Made in Italy. Through a methodological and critical reflection on these two tools, the article highlights how communication design can serve as a strategic mediator between systemic complexity and emotional engagement, helping to make visible—and shareable—the intangible values that lie at the heart of a circular and sustainable Made in Italy identity and its transformative potential.

Roland Preuss, Udo von Toussaint

The modelling of plasma–wall interactions (PWIs) depends on distributions describing the angle and energy distribution of particles scattered at the first wall of fusion devices. Most PWI codes rely on extensive tables based on data from reflection simulations, employing a Monte Carlo method. At first glance, the uncertainty distribution of the data should be assumed Gaussian. However, in order to obtain the resulting particle distribution, the reflected ions are counted within angle sections of the upper hemisphere, which hints to a Poisson uncertainty distribution. In this paper, we let Bayesian model comparison decide which uncertainty model should be taken.

Suchada Kuntaros, Kitirochna Rattanakasamsuk, Uravis Tangkijviwat et al.

The research aimed to compare how different styles of instant lemongrass drink package imagery influence consumer interest and behavior using eye-tracking technology. A total of 30 participants, aged 19 to 65, evaluated three packaging styles: style 1 Images of instant lemongrass drinks served in a cup, style 2 images of instant lemongrass drinks served in a cup with steam and style 3 images of instant lemongrass drinks being poured into a cup. To determine visual areas of interest (AOIs), we examined eye-tracking variables including number of fixations, duration of fixations, and heatmaps. To mitigate positional bias, we displayed each style at a randomly assigned screen position each time. Participants also filled out a survey to determine which style they would most likely purchase. A one-way ANOVA and Tukey HSD post-hoc testing revealed significant variations in fixation metrics among the styles. The result demonstrates style. Two images of instant lemongrass drinks served in a cup with steam had the longest average duration of fixations and were the most popular style that affected customer choice. This is due to the warm sensation they experience when they gaze at it, which is associated with their preference for hot tea over cold tea, as well as the sensation of being close to a product as if it were in front of them. The findings highlight the necessity of using dynamic emotional packaging imagery and resonant visual features in packaging. This study makes actionable ideas for packaging designers and marketers to increase customer engagement and product awareness in competitive markets.

Gulden Othman, Robert H. Hadfield, Katharina-Sophie Isleif et al.

Superconducting Transition Edge Sensors (TESs) are a promising technology for fundamental physics applications due to their low dark count rates, excellent energy resolution, and high detection efficiency. On the DESY campus, we have been developing a program to characterize cryogenic quantum sensors for fundamental physics applications, particularly focused on TESs. We currently have two fully equipped dilution refrigerators that enable simultaneous TES characterization and fundamental physics searches. In this paper, we summarize the current status of our TES characterization, including recent calibration efforts and efficiency measurements, as well as simulations to better understand TES behavior and its backgrounds. Additionally, we summarize some physics applications that we are already exploring or planning to explore. We will give preliminary projections on a direct dark matter search with our TES, where exploiting low-threshold electron scattering in superconducting materials allows us to search for sub-MeV-scale dark matter. We are also working toward performing a measurement of the even-number photon distribution (beyond one pair) of a quantum-squeezed light source. Finally, if it proves to meet the requirements, our TES detector may be used as a second, independent detection system to search for an axion signal at the ALPS II experiment.

Nathan D. Schiele, Olga Gadyatskaya

Threat modeling (TM) is an important aspect of risk analysis and secure software engineering. Graphical threat models are a recommended tool to analyze and communicate threat information. However, the comparison of different graphical threat models, and the acceptability of these threat models for an audience with a limited technical background, is not well understood, despite these users making up a sizable portion of the cybersecurity industry. We seek to compare the acceptability of three general, graphical threat models, Attack-Defense Trees (ADTs), Attack Graphs (AGs), and CORAS, for users with a limited technical background. We conducted a laboratory study with 38 bachelor students who completed tasks with the three threat models across three different scenarios assigned using a Latin square design. Threat model submissions were qualitatively analyzed, and participants filled out a perception questionnaire based on the Method Evaluation Model (MEM). We find that both ADTs and CORAS are broadly acceptable for a wide range of scenarios, and both could be applied successfully by users with a limited technical background; further, we also find that the lack of a specific tool for AGs may have impacted the perceived usefulness of AGs. We can recommend that users with a limited technical background use ADTs or CORAS as a general graphical TM method. Further research on the acceptability of AGs to such an audience and the effect of a dedicated TM tool support is needed.

Johan Cederbladh, Loek Cleophas, Eduard Kamburjan et al.

With the current trend in Model-Based Systems Engineering towards Digital Engineering and early Validation & Verification, experiments are increasingly used to estimate system parameters and explore design decisions. Managing such experimental configuration metadata and results is of utmost importance in accelerating overall design effort. In particular, we observe it is important to 'intelligent-ly' reuse experiment-related data to save time and effort by not performing potentially superfluous, time-consuming, and resource-intensive experiments. In this work, we present a framework for managing experiments on digital and/or physical assets with a focus on case-based reasoning with domain knowledge to reuse experimental data efficiently by deciding whether an already-performed experiment (or associated answer) can be reused to answer a new (potentially different) question from the engineer/user without having to set up and perform a new experiment. We provide the general architecture for such an experiment manager and validate our approach using an industrial vehicular energy system-design case study.

Sara Laura Wilson

Identity-Centered Design facilitates the creation of products and services that align with users’ personal and social identities, enhancing user engagement and product longevity. To successfully design for longevity, designers require user research methodologies that accurately forecast the needs of future users. This case study examines the development and application of two specific tools for user research within Identity-Centered Design for Sustainable Behavior, emphasising the importance of understanding the future self and integrating insights from behavioural psychology into sustainable design practices. The first tool, the Eco-Identity Indicator, utilises principles from behavioural psychology to assess dimensions of identity and pro-environmental behaviours. This tool aids in predicting future behaviours and developing products that cater to future user needs. The second tool, a Virtual Reality Time Machine, allows users to visualise and interactively modify projected future scenarios. This approach leverages immersive technology to identify design opportunities to address discrepancies between the projected and ideal future.

بهرام ابراهیمی, سیروان محمدی آذر

در این مطالعه یک کامپوزیت مغناطیسی کربن فعال (Activated carbon (AC)) با استفاده از روش ترموشیمیایی و هم‌رسوبی ذرات آهن تهیه گردید(AC/Fe3O4) . از پوست سخت میوه بنه بومی منطقه اورامان استان کردستان به عنوان ماده خام استفاده شد. خصوصیات ساختمانی جاذب تهیه شده با استفاده از آنالیزهای SEM، FT-IR، EDAX، BET و VSM مورد بررسی قرار گرفت. تصاویر SEM به وضوح شکل گیری یک جاذب متخلخل با تخلخل در گستره میکرو و مزو حفرات را نشان داد. نتایج آنالیزهای FT-IR و EDAX حضور آهن در ساختمان جاذب را اثبات نمود. با استفاده از تخلخل‌سنجی BET، سطح ویژه جاذب تولید شده قبل و بعد از ترسیب ذرات آهن به ترتیب 229.6 و 179.37 متر مربع بر گرم تعیین گردید. در شرایط بهینه میزان حذف رنگ‌های مورد مطالعه از محلول‌های مدل 91.2 و 98.6 درصد به ترتیب برای اسید بلو 113 و اسید اورانژ 10 حاصل شد. داده‌های سینیتیکی پیروی فرایند‌ حذف را از مدل شبه درجه دوم نشان داد. همچنین مدل فروندلیچ بهترین مدل برای توصیف فرایند‌ جذب سطحی بود.

Muhammad Adamu, Makuochi Nkwo

The Authors attempt to show how the proliferation of AI-led initiatives across Africa denotes a potential rebirth of modern forms of imperialism. Building on the concept of digital colonialism, we point to how the “for good” rhetoric in the AI arena might have provided the invisible platform for the appropriation of social life for cultural dominance and control. By exploring the subtle power relations underpinning the design and adoption of AI systems in Africa, this note amplifies Kate Crawford’s claim that AI is “neither artificial nor intelligent” as widely presumed — one needs to identify the human social values behind and inside the machine.

Everton Cavalcante, Thais Batista, Flavio Oquendo

Modern systems are increasingly connected and more integrated with other existing systems, giving rise to \textit{systems-of-systems} (SoS). An SoS consists of a set of independent, heterogeneous systems that interact to provide new functionalities and accomplish global missions through emergent behavior manifested at runtime. The distinctive characteristics of SoS, when contrasted to traditional systems, pose significant research challenges within Software Engineering. These challenges motivate the need for a paradigm shift and the exploration of novel approaches for designing, developing, deploying, and evolving these systems. The \textit{International Workshop on Software Engineering for Systems-of-Systems} (SESoS) series started in 2013 to fill a gap in scientific forums addressing SoS from the Software Engineering perspective, becoming the first venue for this purpose. This article presents a study aimed at outlining the evolution and future trajectory of Software Engineering for SoS based on the examination of 57 papers spanning the 11 editions of the SESoS workshop (2013-2023). The study combined scoping review and scientometric analysis methods to categorize and analyze the research contributions concerning temporal and geographic distribution, topics of interest, research methodologies employed, application domains, and research impact. Based on such a comprehensive overview, this article discusses current and future directions in Software Engineering for SoS.

Siddhant Dutta, Iago Leal de Freitas, Pedro Maciel Xavier et al.

Federated Learning (FL) is a decentralized machine learning approach that has gained attention for its potential to enable collaborative model training across clients while protecting data privacy, making it an attractive solution for the chemical industry. This work aims to provide the chemical engineering community with an accessible introduction to the discipline. Supported by a hands-on tutorial and a comprehensive collection of examples, it explores the application of FL in tasks such as manufacturing optimization, multimodal data integration, and drug discovery while addressing the unique challenges of protecting proprietary information and managing distributed datasets. The tutorial was built using key frameworks such as $\texttt{Flower}$ and $\texttt{TensorFlow Federated}$ and was designed to provide chemical engineers with the right tools to adopt FL in their specific needs. We compare the performance of FL against centralized learning across three different datasets relevant to chemical engineering applications, demonstrating that FL will often maintain or improve classification performance, particularly for complex and heterogeneous data. We conclude with an outlook on the open challenges in federated learning to be tackled and current approaches designed to remediate and improve this framework.

Mohammed B. Al-Fadhli

Large inconsistencies in the outcome of precise measurements of Newtonian gravitational ‘constant’ were identified throughout more than three hundred experiments conducted up to date. This paper illustrates the dependency of the Newtonian gravitational parameter on the curvature of the background and the associated field strength of vacuum energy. Additionally, the derived interaction field equations show that boundary interactions and spin-spin correlations of vacuum and conventional energy densities contribute to the emergence of mass. Experimental conditions are recommended to achieve consistent outcomes of the parameter precision measurements, which can directly falsify or provide confirmations to the presented field equations.

Đorđe Vujčić, Sandra Dedijer, Mladen Stančić et al.

It is known that gloss has a significant impact on colour measurement. The UV varnish used for surface finishing, spot effects, as well as special effects, such as 3D effects and formation of Braille, has a pronounced gloss effect. In this work, a comparison of the spectrophotometer measurement geometry influence on the colour measurement of an unprinted PVC sample covered with UV varnish was done. UV varnish was applied successively in layers, and patches with different number of varnish layers, from 1 to 12, were formed. Two spectrophotometers with different measurement geometries were used for the measurement: Konica Minolta CM-2600d with d/8 measurement geometry, with spectral reflection included and excluded, and different measurement aperture 3 and 8 mm, and X-Rite eXact with 45/0 measurement geometry. By comparing the measurements, it was established that there is a significant difference in the measured values between different measuring device geometries on the given samples, and that the number of UV varnish layers has a significant influence on this difference.

Fabio Calefato, Luigi Quaranta, Filippo Lanubile et al.

Background. Due to the widespread adoption of Artificial Intelligence (AI) and Machine Learning (ML) for building software applications, companies are struggling to recruit employees with a deep understanding of such technologies. In this scenario, AutoML is soaring as a promising solution to fill the AI/ML skills gap since it promises to automate the building of end-to-end AI/ML pipelines that would normally be engineered by specialized team members. Aims. Despite the growing interest and high expectations, there is a dearth of information about the extent to which AutoML is currently adopted by teams developing AI/ML-enabled systems and how it is perceived by practitioners and researchers. Method. To fill these gaps, in this paper, we present a mixed-method study comprising a benchmark of 12 end-to-end AutoML tools on two SE datasets and a user survey with follow-up interviews to further our understanding of AutoML adoption and perception. Results. We found that AutoML solutions can generate models that outperform those trained and optimized by researchers to perform classification tasks in the SE domain. Also, our findings show that the currently available AutoML solutions do not live up to their names as they do not equally support automation across the stages of the ML development workflow and for all the team members. Conclusions. We derive insights to inform the SE research community on how AutoML can facilitate their activities and tool builders on how to design the next generation of AutoML technologies.

Gabriel C. Ullmann, Yann-Gaël Guéhéneuc, Fabio Petrillo et al.

Game engines support video game development by providing functionalities such as graphics rendering or input/output device management. However, their architectures are often overlooked, which hinders their integration and extension. In this paper, we use an approach for architecture recovery to create architectural models for 10 open-source game engines. We use these models to answer the following questions: Which subsystems more often couple with one another? Do game engines share subsystem coupling patterns? We observe that the Low-Level Renderer, Platform Independence Layer and Resource Manager are frequently coupled to the game engine Core. By identifying the most frequent coupling patterns, we describe an emergent game engine architecture and discuss how it can be used by practitioners to improve system understanding and maintainability.

Towaki Takikawa, Thomas Müller, Merlin Nimier-David et al.

Neural graphics primitives are faster and achieve higher quality when their neural networks are augmented by spatial data structures that hold trainable features arranged in a grid. However, existing feature grids either come with a large memory footprint (dense or factorized grids, trees, and hash tables) or slow performance (index learning and vector quantization). In this paper, we show that a hash table with learned probes has neither disadvantage, resulting in a favorable combination of size and speed. Inference is faster than unprobed hash tables at equal quality while training is only 1.2-2.6x slower, significantly outperforming prior index learning approaches. We arrive at this formulation by casting all feature grids into a common framework: they each correspond to a lookup function that indexes into a table of feature vectors. In this framework, the lookup functions of existing data structures can be combined by simple arithmetic combinations of their indices, resulting in Pareto optimal compression and speed.

Sean McGuire, Erin Shultz, Bimpe Ayoola et al.

Background: Sustainable software engineering (SSE) means creating software in a way that meets present needs without undermining our collective capacity to meet our future needs. It is typically conceptualized as several intersecting dimensions or ``pillars'' -- environmental, social, economic, technical and individual. However; these pillars are theoretically underdeveloped and require refinement. Objectives: The objective of this paper is to generate a better theory of SSE. Method: First, a scoping review was conducted to understand the state of research on SSE and identify existing models thereof. Next, a meta-synthesis of qualitative research on SSE was conducted to critique and improve the existing models identified. Results: 961 potentially relevant articles were extracted from five article databases. These articles were de-duplicated and then screened independently by two screeners, leaving 243 articles to examine. Of these, 109 were non-empirical, the most common empirical method was systematic review, and no randomized controlled experiments were found. Most papers focus on ecological sustainability (158) and the sustainability of software products (148) rather than processes. A meta-synthesis of 36 qualitative studies produced several key propositions, most notably, that sustainability is stratified (has different meanings at different levels of abstraction) and multisystemic (emerges from interactions among multiple social, technical, and sociotechnical systems). Conclusion: The academic literature on SSE is surprisingly non-empirical. More empirical evaluations of specific sustainability interventions are needed. The sustainability of software development products and processes should be conceptualized as multisystemic and stratified, and assessed accordingly.

Carlo Emilio Standoli

This paper aims to investigate the current role of design in healthcare and reflect on its mandate in defining products, services, strategies, and policies, proposing perspectives toward a person-centred healthcare. Today, design research in healthcare reflects on scenarios and challenges affecting innovation and change, considering the potentially disruptive effect of technological innovation on personal care and social, economic, ethical, and political aspects. Through a literature review and case studies analysis, the paper focuses on the current criticalities of the healthcare system, exacerbated by the pandemic situation, and presents a first taxonomy of the trajectories for design-led intervention. It reflects on top-down actions proposed by the government, activities of co-design and the cross-fertilisation between design and other disciplines, and bottom-up actions of social innovation, to present near future perspectives for design-led actions in healthcare.