The Graduate School of Syiah Kuala University consists of five main buildings, one of which is Building B. Building B serves as a space for educational activities at the master's (S2) and doctoral (S3) levels. Based on observations, Building B features windows (openings) of very large dimensions, with the building and window orientations facing west and east. This condition results in excessive and glaring natural lighting, causing thermal discomfort. Consequently, the rooms are often used with curtains, artificial lighting such as lamps, and tinted glass windows, specifically ray-band glass. This study aims to evaluate the natural lighting levels in lecture rooms based on the Indonesian National Standard (SNI No. 6197-2020). Data collection was conducted using a quantitative method, obtained through direct visual observations and field measurements, including openings, building dimensions, and illumination levels measured with a Lux Meter. The measured illumination values were then analyzed based on the SNI No. 6197-2020 standard and the observational results, enabling the identification of factors affecting natural lighting intensity. The findings indicate that the natural lighting levels within the building do not meet the SNI 6197-2020 standard for classrooms, which is 350 Lux. The average illumination value measured using the Lux Meter was 109.69 Lux.
Technology, Architectural engineering. Structural engineering of buildings
ABSTRACT This paper proposes a control method for a semi‐active controlled tuned mass damper (TMD) adaptable to the period fluctuation of the target structure. It is based on the idea of maximizing the TMD's absorbing energy. First, previous control methods are reviewed from the aspects of performance and applicability. Next, the concept and algorithm of the proposed control method are described, and the relationship between its response control performance and absorbing energy is investigated. Finally, earthquake response analyses are performed that compare the proposed control method with other types of TMD.
Architecture, Architectural engineering. Structural engineering of buildings
The adoption of large language models (LLMs) and autonomous agents in software engineering marks an enduring paradigm shift. These systems create new opportunities for tool design, workflow orchestration, and empirical observation, while fundamentally reshaping the roles of developers and the artifacts they produce. Although traditional empirical methods remain central to software engineering research, the rapid evolution of AI introduces new data modalities, alters causal assumptions, and challenges foundational constructs such as "developer", "artifact", and "interaction". As humans and AI agents increasingly co-create, the boundaries between social and technical actors blur, and the reproducibility of findings becomes contingent on model updates and prompt contexts. This vision paper examines how the integration of LLMs into software engineering disrupts established research paradigms. We discuss how it transforms the phenomena we study, the methods and theories we rely on, the data we analyze, and the threats to validity that arise in dynamic AI-mediated environments. Our aim is to help the empirical software engineering community adapt its questions, instruments, and validation standards to a future in which AI systems are not merely tools, but active collaborators shaping software engineering and its study.
Joshua Owotogbe, Indika Kumara, Dario Di Nucci
et al.
Chaos engineering aims to improve the resilience of software systems by intentionally injecting faults to identify and address system weaknesses that cause outages in production environments. Although many tools for chaos engineering exist, their practical adoption is not yet explored. This study examines 971 GitHub repositories that incorporate 10 popular chaos engineering tools to identify patterns and trends in their use. The analysis reveals that Toxiproxy and Chaos Mesh are the most frequently used, showing consistent growth since 2016 and reflecting increasing adoption in cloud-native development. The release of new chaos engineering tools peaked in 2018, followed by a shift toward refinement and integration, with Chaos Mesh and LitmusChaos leading in ongoing development activity. Software development is the most frequent application (58.0%), followed by unclassified purposes (16.2%), teaching (10.3%), learning (9.9%), and research (5.7%). Development-focused repositories tend to have higher activity, particularly for Toxiproxy and Chaos Mesh, highlighting their industrial relevance. Fault injection scenarios mainly address network disruptions (40.9%) and instance termination (32.7%), while application-level faults remain underrepresented (3.0%), highlighting for future exploration.
This paper introduces ModeliHub, a Web-based, federated analytics platform designed specifically for model-based systems engineering with Modelica. ModeliHub's key innovation lies in its Modelica-centric, hub-and-spoke federation architecture that provides systems engineers with a Modelica-based, unified system model of repositories containing heterogeneous engineering artifacts. From this unified system model, ModeliHub's Virtual Twin engine provides a real-time, interactive simulation environment for deploying Modelica simulation models that represent digital twins of the virtual prototype of the system under development at a particular iteration of the iterative systems engineering life cycle. The implementation of ModeliHub is centered around its extensible, Modelica compiler frontend developed in Isomorphic TypeScript that can run seamlessly across browser, desktop and server environments. This architecture aims to strike a balance between rigor and agility, enabling seamless integration and analysis across various engineering domains.
Vincenzo De Martino, Mohammad Amin Zadenoori, Xavier Franch
et al.
Language Models are increasingly applied in software engineering, yet their inference raises growing environmental concerns. Prior work has examined hardware choices and prompt length, but little attention has been paid to linguistic complexity as a sustainability factor. This paper introduces Green Prompt Engineering, framing linguistic complexity as a design dimension that can influence energy consumption and performance. We conduct an empirical study on requirement classification using open-source Small Language Models, varying the readability of prompts. Our results reveal that readability affects environmental sustainability and performance, exposing trade-offs between them. For practitioners, simpler prompts can reduce energy costs without a significant F1-score loss; for researchers, it opens a path toward guidelines and studies on sustainable prompt design within the Green AI agenda.
Abstract This study provides an understanding of the needs for signs identifying rooms shown in group homes for the elderly with dementia (residents' room signs) and reveals the elements for planning. The purpose of staff displaying residents' room signs is to support residents with dementia returning to their own rooms by themselves. It is appropriate for the display contents shown on the residents' room signs to be displayed with the name of the resident approximately 30 to 50 mm. The appropriate display location is near the door handle at a height of approximately 1200 to 1400 mm.
Architecture, Architectural engineering. Structural engineering of buildings
Adrian Mihai GOANTA, Diana Gina MUSCA, Aurora Maria POTIRNICHE
et al.
The paper presents some aspects of the evolution made by computer-aided design and the presentation of some common commands used in Inventor 2024. In addition, both the Any CAD import method and the transfer methods offered by the Autodesk Inventor Professional 2024 version are presented. At the end of the work, some results obtained using the educational versions downloaded for university users at the level of diploma or dissertation work are presented.
Architectural engineering. Structural engineering of buildings, Engineering design
This work introduces an innovative program for training the next generation of software engineers within university settings, addressing the limitations of traditional software engineering courses. Initial program costs were significant, totaling $551,420 in direct expenditures to pay for program staff salaries and benefits over two years. We present a strategy for reducing overall costs and establishing sustainable funding sources to perpetuate the program, which has yielded educational, research, professional, and societal benefits.
Larissa Barbosa, Sávio Freire, Rita S. P. Maciel
et al.
[Context and Motivation] Several studies have investigated attributes of great software practitioners. However, the investigation of such attributes is still missing in Requirements Engineering (RE). The current knowledge on attributes of great software practitioners might not be easily translated to the context of RE because its activities are, usually, less technical and more human-centered than other software engineering activities. [Question/Problem] This work aims to investigate which are the attributes of great requirements engineers, the relationship between them, and strategies that can be employed to obtain these attributes. We follow a method composed of a survey with 18 practitioners and follow up interviews with 11 of them. [Principal Ideas/Results] Investigative ability in talking to stakeholders, judicious, and understand the business are the most commonly mentioned attributes amongst the set of 22 attributes identified, which were grouped into four categories. We also found 38 strategies to improve RE skills. Examples are training, talking to all stakeholders, and acquiring domain knowledge. [Contribution] The attributes, their categories, and relationships are organized into a map. The relations between attributes and strategies are represented in a Sankey diagram. Software practitioners can use our findings to improve their understanding about the role and responsibilities of requirements engineers.
The development of cities in Indonesia must be connected to the role of the Dutch colonial government. Cities were built from an indigenous village by creating a grid pattern to divide the village into residential blocks with the traditional market as the center. The Chinese, as immigrants, had no choice of work other than being traders. Currently, in Pasar Baru, the first commercial area in Bandung, Chinese-style shophouses are still recognizable, and some have been designated cultural heritage buildings. Unfortunately, some more are no longer intact, split into several units, or transformed into other shophouses. This study aims to show how Chinese society has continued to trade as tradition and how the shophouse as a legacy has adapted. The method used in this research is descriptive qualitative using several case studies. From survey observations, it can be seen that the transformation of shophouses begins with the division of shophouses in a transverse direction so that each unit still has road access to continue the trading tradition. The success of the descendant's continued tradition has made Pasar Baru the most prominent trading center in Bandung and serves other cities around Bandung.
Architecture, Architectural engineering. Structural engineering of buildings
Vinay Kumar Singh, Pramod Kumar Gupta, S M Ali Jawaid
The axial load-carrying capacity for a wide range of short concrete-filled steel tubular (CFST) members having different section profiles is evaluated in the presented work. A numerical study has been carried out through Finite-Element based demonstration and it has been accomplished in the ABAQUS package for relevancy of analytically predicted axial load carrying capacity by unified formula as suggested by Yu M. et al. (2010). To validate the results from the unified formula and the experimentally available literature, finite element-based models for hollow and solid sections of CFST columns with circular, octagonal, and square section profiles have been generated. A total of 31 hollow and 24 solid circular columns, 9 hollow, and 9 solid octagonal columns, and in the last 9 hollows and 38 solid square CFST columns are examined for the persistence of the results. After evaluation of obtained results from the modeling existing results are validated, and it is found that the proposed unified formula predicts satisfactory results when compared with the result of established models. Further, it is concluded that displacement in the direction of applied load is not uniform throughout the length of CFST columns thereby using the ring confinement technique for the region of applied force may be reasonable.
Architectural engineering. Structural engineering of buildings, Structural engineering (General)
Aleksandar Dimov, Simeon Emanuilov, Boyan Bontchev
et al.
Orientation of modern software systems towards data-intensive processing raises new difficulties in software engineering on how to build and maintain such systems. Some of the important challenges concern the design of software architecture. In this article, we survey the fundamental challenges when designing data-intensive computing systems and present some of the most popular software architectural styles together with their potential to tackle these challenges.
Background: Risk-taking is prevalent in a host of activities performed by software engineers on a daily basis, yet there is scant research on it. Aims and Method: We study if software engineers' risk-taking is affected by framing effects and by software engineers' personality. To this end, we perform a survey experiment with 124 software engineers. Results: We find that framing substantially affects their risk-taking. None of the "Big Five" personality traits are related to risk-taking in software engineers after correcting for multiple testing. Conclusions: Software engineers and their managers must be aware of framing effects and account for them properly.
In this paper, the adoption patterns of Generative Artificial Intelligence (AI) tools within software engineering are investigated. Influencing factors at the individual, technological, and societal levels are analyzed using a mixed-methods approach for an extensive comprehension of AI adoption. An initial structured interview was conducted with 100 software engineers, employing the Technology Acceptance Model (TAM), the Diffusion of Innovations theory (DOI), and the Social Cognitive Theory (SCT) as guiding theories. A theoretical model named the Human-AI Collaboration and Adaptation Framework (HACAF) was deduced using the Gioia Methodology, characterizing AI adoption in software engineering. This model's validity was subsequently tested through Partial Least Squares - Structural Equation Modeling (PLS-SEM), using data collected from 183 software professionals. The results indicate that the adoption of AI tools in these early integration stages is primarily driven by their compatibility with existing development workflows. This finding counters the traditional theories of technology acceptance. Contrary to expectations, the influence of perceived usefulness, social aspects, and personal innovativeness on adoption appeared to be less significant. This paper yields significant insights for the design of future AI tools and supplies a structure for devising effective strategies for organizational implementation.
Anh Nguyen-Duc, Beatriz Cabrero-Daniel, Adam Przybylek
et al.
Generative Artificial Intelligence (GenAI) tools have become increasingly prevalent in software development, offering assistance to various managerial and technical project activities. Notable examples of these tools include OpenAIs ChatGPT, GitHub Copilot, and Amazon CodeWhisperer. Although many recent publications have explored and evaluated the application of GenAI, a comprehensive understanding of the current development, applications, limitations, and open challenges remains unclear to many. Particularly, we do not have an overall picture of the current state of GenAI technology in practical software engineering usage scenarios. We conducted a literature review and focus groups for a duration of five months to develop a research agenda on GenAI for Software Engineering. We identified 78 open Research Questions (RQs) in 11 areas of Software Engineering. Our results show that it is possible to explore the adoption of GenAI in partial automation and support decision-making in all software development activities. While the current literature is skewed toward software implementation, quality assurance and software maintenance, other areas, such as requirements engineering, software design, and software engineering education, would need further research attention. Common considerations when implementing GenAI include industry-level assessment, dependability and accuracy, data accessibility, transparency, and sustainability aspects associated with the technology. GenAI is bringing significant changes to the field of software engineering. Nevertheless, the state of research on the topic still remains immature. We believe that this research agenda holds significance and practical value for informing both researchers and practitioners about current applications and guiding future research.