Conceptual Phase Research Articles

Formalizing Sustainable Urban Mobility Management: An Innovative Approach with Digital Twin and Integrated Modeling

Background: Urban mobility management faces growing challenges that require the analysis and optimization of sustainable solutions. Digital twins (DTs) have emerged as innovative tools for this assessment, but their implementation requires standardized procedures and languages; Methods: As part of a broader methodology for continuous DT validation, this study focuses on the conceptual validation phase, presenting a conceptualization approach through formalization using Specification and Description Language (SDL), agnostic to simulation tools. The conceptual validation was achieved through stakeholder engagement in the Bolzano context, producing 41 SDL diagrams that define both elements common to different urban realities and specific local data collection procedures; Results: The feasibility of implementing this stakeholder-validated conceptualization was demonstrated using Simulation of Urban MObility (SUMO) for traffic simulation and optimization criteria calculation, and its framework SUMO Activity GenerAtion (SAGA) for generating an Activity-Based Modeling (ABM) mobility demand that can be improved through real sensor data; Conclusions: The SDL approach, through its graphical representation (SDL/GR), enables conceptual validation by enhancing stakeholder communication while defining a framework that, while adapting to the monitoring specificities of different urban realities, maintains a common and rigorous structure, independent of the chosen implementation tools and programming languages.

Crafting Kuweni’s Legacy: Folklore-Inspired Responsible Dyeing Techniques and Textile Developments

Folklore, originating from the past, holds immense social and cultural significance, forging profound connections with communities’ roots. This study examines into the folklore of Kuweni in Sri Lanka, revealing its historical and geographical significance intertwined with myth. The story of Kuweni, a young native woman from diverse local communities, has spawned various place legends, with Thambappanni being particularly noteworthy in this folklore. The aim of this research is to explore the translation of folklore elements into a localized fashion products that honour the narrative, and connect past and present. By adopting a thematic approach to analyse folk literature and the folklore of Kuweni, this study takes a practice-led approach to fashion product development. In the conceptualization phase, it highlights the unique aspects of the place legend, Thambappanni, famous for its copper-coloured soil and Kuweni’s tale of spinning cotton for handloom weaving in this region. This led to experiments in handloom weaving using yarn dyed with a specific technique derived from Thambappanni soil, resulting in a distinct textile product deeply rooted in folklore and to ideas of fashion localism. The significance of these findings lies in the conceptual framework developed for transforming folklore into fashion products, bridging the preservation of socio-cultural values from folklore to contemporary society through fashion that speaks to the significance of place and story.

Practicality of syntax soft skill-based learning (Ss-BL): a new model in web-based entrepreneurship learning

The soft skills-based learning (Ss-BL) learning the methodology was proposed as an innovative approach to facilitate experiential learning in authentic real-world contexts. This was created to address the shortcomings of the Experiential Learning (EL) approach in enhancing student communication proficiency. Thus, this study's goal is to evaluate the viability of the Ss-BL learning paradigm. In this work, confirmatory factor analysis (CFA) and the Mile and Huberman methodology were employed in an exploratory sequential mixed methods approach. The paradigm for Ss-BL learning is created by conceptualization, theorization, hypothesization, and finalization phases. The research data was acquired via the process of document analysis and conducting a Focus Group Discussion (FGD). A focus group discussion (FGD) was carried out with a sample of 5 experts for research purposes. A non-test was the tool used in the FGD. The Ss-BL model consists of the Motivation, Observation, Real Experience, Implementation, Evaluation, Reflection phases. For all phases, a CFA value of 0.000 was obtained, that is, if the number is less than 2, it means that the Ss-BL model meets the goodness-of-fit model criterion. Among the innovative learning models suggested for entrepreneurial courses in vocational education, the Ss-BL model stands out as both a contribution to the advancement of knowledge and a viable option

ARTIFICIAL INTELLIGENCE TOOLS IN ARCHITECTURE

Lately, architects have begun to favour a more result-oriented way of working based on artificial intelligence (AI) and its use for automation and software applications operation that support work with design data. The research aims to identify and systematise data on computer tools using artificial intelligence algorithms and the prospects for its development in architectural activities. The use of AI algorithms in architectural design is characteristic of all its stages, from the conceptual phase and basic design levels to detailing, development of design documentation, and future implementation, which is why various computer tools are available. The scientific paper describes three groups of AI software products. The first group includes software for architectural activities with AI-based functionality. The second group involves additional plug-ins with AI algorithms, i.e., independently compiled software modules installed and connected to the main programme, expanding its capabilities. The third group comprises online AI platforms, many of which are already available on the Internet and continue to grow in number. These services are usually not associated with professional software but can be used to perform specific architectural design tasks. The reviewed software products suggest that artificial intelligence technologies can transform traditional approaches to architecture and construction, offering architects powerful tools to increase efficiency and creativity. However, it is necessary to note significant doubts in the professional architectural community about whether to implement artificial intelligence fully. It is due to uncertainty about the impact of AI on traditional roles in the architectural industry, displacement from jobs, and the reliability and ethical implications of decision-making based on these particular algorithms. We should also note that the first group of software is the most promising for the future development of the architectural profession, as it provides full-fledged programmes with a comprehensive approach to architectural activities. Keywords: artificial intelligence, software, plugin, architecture.

Deciphering climate change impacts on resource extraction supply chain: a systematic review

AbstractMining is becoming increasingly vulnerable to the effects of climate change (CC). The vulnerability stems from changing weather patterns, leading to extreme weather events that can cause damage to equipment, infrastructure, and mining facilities and disrupt operations. The new demand from governments and international agreements has placed additional pressure on mining industries to update their policies in order to reduce greenhouse gas emissions and adapt to CC. This includes implementing carbon pricing systems, utilizing renewable energy, and focusing on sustainable development. Most mining and exploration industries prioritize reducing mining’s impact on climate change rather than adapting to extreme weather events. Therefore, it is important to study and investigate the impacts of climate change on the mining sector. This paper aims to investigate the challenges and strategies for adapting to and mitigating the impacts of climate change on mining through a systematic literature review. The results indicate that the majority of proposed models and strategies in the mining field are still in the conceptual phase, with fewer practical implementations. It has been identified that there is a requirement for long-term planning, improved risk management plans, and increased awareness and education within the industry. Practical strategies such as integrating renewable energy, enhancing operational safety, and improving water and tailings management have been recognized as crucial for effective climate change adaptation and mitigation.

Conceptual Framework for the Psychosocial Management of Depression in Adolescents in the North West Province, South Africa

Background A conceptual framework is imperative in the understanding of the psychosocial management of depression in adolescents, owing to the ability to effectively present and demonstrate the linking of concepts for an in-depth understanding of the phenomenon. Objectives This study aims To develop and validate a conceptual framework for the psychosocial management of depression in adolescents in the North West Province, South Africa. Methods A qualitative, exploratory, descriptive, contextual research design was followed in two phases: the empirical phase (phase 1) and the development of a conceptual framework phase (phase 2). Phase 1 consisted of two steps: firstly, a systematic review (referred to as step 1), followed by qualitative, exploratory, descriptive, and contextual research (referred to as step 2). The outcomes from the empirical phase served as the foundation for developing a conceptual framework for the psychosocial management of depression in adolescents, North West Province, South Africa. In Phase 2, the development of this conceptual framework was guided by addressing the six crucial questions introduced by Dickoff et al. (1968) regarding Practical Orientation and validated by Chinn and Kramer’s five criteria questions. Results The conceptual framework focused on mental health practitioners, immediate and extended family members of adolescents, social workers, psychologists and peer groups of adolescents, adolescents diagnosed with depression, mental health institutions, homes of adolescents, schools, religious institutions, and communities. Conclusion The conceptual framework for the psychosocial management of depression in adolescents provides comprehensive insights capable of enhancing the recovery process for adolescents dealing with depression. Implementing this conceptual framework has the potential to enhance professional practice, elevate the quality of care provided, and contribute to expanding the body of knowledge within the field of mental health.

Empirical insights into AI-assisted game development: A case study on the integration of generative AI tools in creative pipelines

<p>This study conducts an empirical exploration of generative Artificial Intelligence (AI) tools across the game development pipeline, from concept art creation to 3D model integration in a game engine. Employing AI generators like Leonardo AI, Scenario AI, Alpha 3D, and Luma AI, the research investigates their application in generating game assets. The process, documented in a diary-like format, ranges from producing concept art using fantasy game prompts to optimizing 3D models in Blender and applying them in Unreal Engine 5. The findings highlight the potential of AI to enhance the conceptualization phase and identify challenges in producing optimized, high-quality 3D models suitable for game development. This study reveals the current limitations and ethical considerations of AI in game design, suggesting that while generative AI tools hold significant promise for transforming game development, their full integration depends on overcoming these hurdles and gaining broader industry acceptance.<strong></strong></p>

Short-term Load Forecasting and Regime Switching Detection Based on Normalized Causal Entropy Boosting

Abstract This paper introduces a method based on normalized causal entropy boosting (NCEBoosting) to identify regime switches in load patterns and improve the adaptability of prediction models. Load time-series exhibit multidimensional, nonlinear changes influenced by factors such as human behavior and meteorological environments. To detect regime switches, we calculate the sparsified causal entropy matrix using a small batch of load flow data, which corrects the original prediction model. Subsequently, the corrected model is employed to predict the load requirements after the switch. By comparing the causal entropy across different time periods, we effectively detect conceptual drift, phase changes, and unexpected events in the data, enabling the determination of load mode switches. Given that load timing data is typically generated in batches, calculating the causal entropy of successive data batches provides a robust metric. In this paper, we determine the load mode change by calculating the integrated causal entropy of the batch data streams and calibrating the prediction model accordingly. Extensive computational experiments on real building load datasets are conducted to validate the proposed method. The results demonstrate that the normalized causal entropy boosting effectively detects load mode switches compared to traditional approaches. Furthermore, the method demonstrates efficient adaptive learning based on online data streams, resulting in improved adaptability and prediction accuracy.

Implementation of suitable information technology governance frameworks for Moroccan higher education institutions

This article aims to present formal governance practices of information technology adapted to the general context of Moroccan universities. The study consists of two main phases: the conceptualization phase and the operationalization phase. During the conceptualization phase, the authors reviewed relevant literature on best practices and their associated frameworks in higher education institutions (HEIs). The results revealed that universities had varying levels of maturity in terms of good practices and often used multiple information system frameworks, which can cause organizational and technical problems. In order to find a solution to this situation, the authors conducted in-depth interviews with chief information officers (CIOs) and university officials from four Moroccan universities during the operationalization phase. These interviews enabled them to propose an effective baseline of best practices and an algorithmic approach to assist managers in choosing between two combinations of frameworks that cover all the mechanisms of the baseline. This solution would enable optimal, agile, and easy-to-implement information technology governance in Moroccan universities while avoiding the multiplicity of frameworks.

Developing a cost estimation model for efficient road improvement planning: A case study in Aceh Jaya regency

Abstract Estimation is a method used to predict financial requirements by analyzing, calculating, and engineering based on field conditions and bidding documents. To enhance efficiency, there is a pressing need for a simple, swift, accurate cost estimation model. Therefore, this study aimed to establish cost estimation model at the initial planning phase of construction work and to assess its accuracy in estimating cost for road improvement using cost significant model (CSM) compared to actual expenses. The fundamental objective was to facilitate the execution of construction work, ensuring the successful completion. Data collection occurred at the (PUPR) in Aceh Jaya Regency, consisting of 25 contracts for road improvement work spanning from 2018 to 2022. The data included the execution year, road area, total variable cost (y), and the categorization of work item as independent variables (xn). Subsequently, the work data was transformed into data per square meter (m2) for each work item by dividing each independent variable by the area of road improvement work. This showed the cost/m2 for each work item (xn) and the total cost (y)/m2. Annual inflation data was obtained from (BPS) of Aceh province used for calculation projection year. The identification of cost-significant item variables occurred after organizing the data according to work item, adjusting the work cost for the execution year and the work-year cost while considering inflation factor. Additionally, it was observed that 3 most expensive work items represented 80% work item had a substantial impact on the total cost. Classic assumption tests were conducted to confirm the suitability of data for further analysis. The analysis was conducted using multiple linear regression, resulting in a model with y = 69850.515 + 0.879(x4) + 1.085(x5) + 1.221(x7). When cost significant model estimates were compared to the actual total cost of road improvement in Aceh Jaya, the accuracy ranged from +17.46% to -19.30%, which was consistent with Class 3 classification of (AACE) International standards.This classification was suitable for semi-detailed cost estimation in the conceptual phase.

Artificial intelligence based data curation: enabling a patient-centric European health data space.

The emerging European Health Data Space (EHDS) Regulation opens new prospects for large-scale sharing and re-use of health data. Yet, the proposed regulation suffers from two important limitations: it is designed to benefit the whole population with limited consideration for individuals, and the generation of secondary datasets from heterogeneous, unlinked patient data will remain burdensome. AIDAVA, a Horizon Europe project that started in September 2022, proposes to address both shortcomings by providing patients with an AI-based virtual assistant that maximises automation in the integration and transformation of their health data into an interoperable, longitudinal health record. This personal record can then be used to inform patient-related decisions at the point of care, whether this is the usual point of care or a possible cross-border point of care. The personal record can also be used to generate population datasets for research and policymaking. The proposed solution will enable a much-needed paradigm shift in health data management, implementing a 'curate once at patient level, use many times' approach, primarily for the benefit of patients and their care providers, but also for more efficient generation of high-quality secondary datasets. After 15 months, the project shows promising preliminary results in achieving automation in the integration and transformation of heterogeneous data of each individual patient, once the content of the data sources managed by the data holders has been formally described. Additionally, the conceptualization phase of the project identified a set of recommendations for the development of a patient-centric EHDS, significantly facilitating the generation of data for secondary use.

An instructional model text mapping with poetry text description

The Indonesian language learning method at Junior High School (SMP) Negeri Padangpanjang was generally boring and traditional. A solution is required to create products that are successful, efficient and enjoyable to use in classroom learning activities. A solution is required to make goods that are effective, efficient and entertaining to use in classroom learning activities. The product trial took place at SMP Negeri 3 Padangpanjang. The 4-D development phase was done in this study. During the conceptualization and development phases of this study, junior high school teachers and students were involved. In addition, experts participate in the process of evaluating products. A variety of methods are used including tests, questionnaires, observations and interviews. The main syntax of OMEMPAT is created by the descriptive text mapping learning model with the help of poetry text such as (1) orientation (2) reading and listening to poetry (3) mapping the contents of the descriptive text (4) presenting the results of the descriptive text mapping and (5) reflecting on the learning process. The three criteria of validity, practicability and efficacy were used to assess the quality of the learning model. The descriptive text mapping learning model which is supported by poetry texts needs to be put into practice. Teachers must create learning models that enable students to engage in educational activities while enjoying.

Product Re-Design Towards Sustainability: a Case Study of a Mass-Production Device

Sustainability issues are nowadays embedded in society and organizations cannot avoid tackling them. Product design represents the phase in which 80% of the overall emissions are determined, thus the one on which changes should be realized. In some industrial sectors the environmental impact has never been accounted systematically during the conceptualization phase. The resulting products are consequently characterized by poor environmental performances, that have a deep negative effect if realized on a mass production scale. A sustainable re-design and process innovation approach is therefore required. This is the objective of this research, that uses Rold Washing Machine Doorlock as a case study example. After the realization of a cradle-to-gate Life Cycle Assessment (LCA) of the component under exam, design and process modifications are identified. The assessment is not limited to the proposal of environmentally improved versions of the product. A barrier towards sustainability adoption is represented by the common perception of its unaffordability. It is important for the identified solutions leading to improved ecological performances, but they should be sustainable for the company also in financial terms. At this purpose, for each proposed change, a technical assessment of the operational steps required is performed, together with an economic analysis. The resulting re-engineered product passes all the desired conditions, and the methodology applied can be extended to every other sector facing the same issue.

Contingency Theory in Management: Conceptual Phases and Strategic Link with Performance Measurement Systems

This literature review delves into the dynamic evolution of contingency theory in management, with a specific focus on the relationship between organizational strategy and Performance Measurement Systems (PMS). Employing a systematic literature review methodology, the conceptual phases of contingency theory are examined, spanning from the technological approach to the configurational approach. The analysis underscores the crucial importance of aligning PMS with the overall organizational strategy, as advocated by Kaplan and Norton. Empirical studies by Chenhall, Kaplan and Norton, and Hoque lend support to this correlation, emphasizing its impact on organizational performance. Thus, this review underscores the need for a strategic approach in designing PMS, providing practical implications for managers and prompting avenues for future research.

Design: Episteme and Doxa. Co-design as an Opportunity to Share Choices

This paper delves into the concept of co-design, a collaborative approach involving stakeholders in the conceptualization and design phases to understand diverse perspectives and jointly define project directions. Examining the relationships between co-design, Design Thinking, and user-centred design, the paper emphasises distinctions in their goals and methods. It addresses potential biases in co-design processes, providing strategies to mitigate analogical relations, cognitive effort minimization, and emotional influences. Epistemological reflections highlight the efficacy of participatory methods in generating theoretical hypotheses while underscoring the need for evidence-based validation. The article explores co-design’s applications in speculative design and ludo-didactics (game design). In speculative design, co-design aids in framing problems and generating plausible contextualizations, while in game design, participatory processes, particularly playtesting, enhance the exploratory and refinement phases. The paper suggests avenues for further research, emphasising the strategic placement of Co-design processes in project phases, considering potential biases, and exploring its application in disruptive innovation contexts.

ParaStell: parametric modeling and neutronics support for stellarator fusion power plants

The three-dimensional variation inherent to stellarator geometries and fusion sources motivates three-dimensional modeling to obtain accurate results from computational modeling in support of design and analysis of first wall, blanket, and shield (FWBS) systems. Manually constructing stellarator fusion power plant geometries in computer-aided design (CAD) and defining the corresponding fusion source can be cumbersome and challenging. The open-source parametric modeling toolset ParaStell has been developed to automate construction of such geometries in low-fidelity. Low-fidelity modeling is useful during the conceptual phase of engineering design as a means of rapidly exploring the design space of a given device. The modeling capability of ParaStell includes in-vessel components and magnets, for any given stellarator configuration, using a parametric definition and plasma equilibrium data. Furthermore, the toolset automates the generation of detailed, tetrahedral neutron source definitions and DAGMC geometries for use in neutronics modeling. ParaStell assists rapid design iteration, parametric study, and design optimization of stellarator fusion cores. As a demonstration of the design iteration capability, the effect of the three-dimensional parameter space on tritium breeding and magnet shielding is investigated, using the WISTELL-D configuration as a design basis. Blanket and shield thicknesses are varied in three dimensions, using the space available between the plasma edge and magnet coils as a constraint. The corresponding effects on tritium breeding ratio and magnet heating are tallied using the open-source Monte Carlo particle transport code OpenMC. The inclusion of additional and higher-fidelity modeling capabilities is planned for ParaStell’s future, as well as its implementation in machine-driven optimization.

Perspective of Using Apple Processing Waste for the Production of Edible Oil with Health-Promoting Properties

(1) Background: The effective management of waste and by-products generated in the food industry helps development and implementation of ranges of health-promoting products. The manufacturing of apple juice and cider results in the generation of large quantities of apple pomace. (2) Methods: This paper outlines the concept of a technological process for industrial-scale production of edible oil with a health-promoting fatty acids profile using dried apple pomace as a raw material. (3) Results: Described approach allows for innovative and profitable industrial-scale utilization of the pomace generated from apple juice production. This paper presents a new technological line for apple seed separation intended for oil pressing. (4) Conclusions: The new technological approach could increase the production of apple seed oil. Because of the growing needs in managing post-production waste and by-products, apple seed oil produced from apple pomace on an industrial scale may become a new, attractive product in the functional food market. The fatty acids profile of apple seed oil is high in polyunsaturated fatty acids and can beneficially influence health. The technology outlined here is in the conceptual phase and requires further research.

The Designers’ Perspective on Autonomous Mining Systems and Sociotechnology

Digitalization and automation technology offer new possibilities to increase productivity and obtain higher levels of autonomy in mining operations. Introducing autonomous systems into mining is not only a technical problem in terms of effectiveness and efficiency, nor a problem of safety in human-automation interactions. The systems also need to be designed and developed so that they foster healthy and attractive working environments. The design and development phase of new mining technology has not been extensively studied previously. To fill this knowledge gap, we investigated technology developers’ basic assumptions about humans and their interactions with the technology they develop. We conducted five semi-structured workshops within an EU funded project concerned with developing digitalization and automation solutions for the mining industry. The data suggests that many critical functions will still be under human control in future mining systems. The results also indicate increased complexity in the interaction between autonomous systems and humans as the technology becomes more advanced. As a result, we suggest that a human perspective, based on sociotechnical principles, should not only be considered in implementing the technology at mines but also in the early conceptual phases of developing and designing the technology. This will ensure healthy and attractive work environments in the future mining industry.

Supervised multilabel classification techniques for categorising customer requirements during the conceptual phase in the new product development

Abstract The research aims to provide the decision-maker with a framework for determining customer requirements during product development. The proposed framework is based on sentiment analysis and supervised multilabel classification techniques. Therefore, the proposed technique can categorise customer reviews based on the “product design criteria” label and the “sentiment of the review” label. To achieve the research goal, the research presented in this article uses the existing product development framework presented in the literature. The modification is conducted especially in the conceptual stage of product development, in which the voice of the customer or a customer review is obtained from the scraping, and a multilabel classification technique is performed to categorise customer reviews. The proposed framework is tested by using the set data on women’s clothing reviews from an e-commerce site downloaded from www.kaggle.com based on data by Agarap (2018). The result shows that the proposed framework can categorise customer reviews. The research presented in this paper has contributed by proposing a technique based on sentiment analysis and multilabel classification that can be used to categorise customers during product development. The research presented in this paper answers one of the concerns in the categorisation of needs raised by Shabestari et al. (2019), namely, the unclear rules or main attributes of a requirement that make these needs fall into certain categories. Categorising customer requirements allows decision-makers to determine the direction of product development to meet customer needs.

Investigation of Workload Control Methods for Shops with Re-Entrant Flows

Abstract The re-entrant flow with an unpredictable nature of arrival would apparently harm production plans and schedules in flow type of shops. The re-entrant flow with varied arrival frequencies in rotor blade manufacturing is quite complicated and results in disproportionate workloads. Hence, an attempt has been made to study the significant influence of disproportionate workloads and research on an innovative order release method to enhance performance. The manufacturing process was observed thoroughly to incorporate the uncertain events that cause disturbance in the production. A simulation model was developed on a discrete event simulation platform by analysing problem phenomena right from the conceptualization phase. The model has been verified and validated to ensure the accuracy. The model was subjected to 288 experiments representing different scenarios that a flow shop undergoes in reality. The factors considered in the experimentation were re-entrant frequency, re-entrant proportions, order release methods and priority dispatching rules. A refined load release policy for disproportionate loads has been proposed to judge its effectiveness in terms of profit computation by comparing it with other relevant policies. Results of the experiment revealed that the order release methods contribute 95.93% to throughput performance, in addition, the use of the new re-entrant method policy in the above scenario was productive in improving the overall shop performance.