Augmented Reality Applied to Identify Aromatic Herbs Using Mobile Devices

On average, annual building maintenance and repair cost 1–5% of the initial building cost, which, accumulated over the building life, could even exceed the initial construction cost. New advancements in architecture, engineering, construction, and operation (AECO) are transforming the current practice of building maintenance operations using visualization and sensing technologies. This chapter will describe a use case for the application of augmented reality (AR) visualization in building maintenance and repair. AR enhances user’s perception of the surroundings by overlaying virtual objects on real-world views and can lead to new forms of user interaction. For instance, AR visualization embedded in the building maintenance instruction manual (BMIM) can be used to guide facility managers and repair personnel. We present the design and evaluation of an AR-integrated BMIM to improve the quality of building operation and maintenance. We adopt the design science research (DSR) methodology to carry out a systematic literature review, characterization of AR features that can be applied to BMIM, development of AR artifacts for incorporating into BMIM, and assessment of user performance through experiments with measurements taken with the NASA TLX protocol. Results are implemented in two applications, namely, Living Augmented Reality (LAR) and Manual Augmented Reality (MAR), with different visualization scales. Analysis of users’ workload data indicates that a majority agree that BMIM can be effectively enhanced with a high degree of acceptability using AR on mobile devices. It is also found that this integration will be helpful to future evolution of the BMIM and integration with the Internet of Things paradigm.KeywordsFacility managementAugmented realityBuilding maintenance instruction manualUser performanceMobile device

Enhancing medical radiation science education through a design science research methodology

This study presents the development and evaluation of ARTechGuide, an Augmented Reality (AR)-based application designed for technical training of operators in an automotive industrial environment. The research was conducted using the Design Science Research (DSR) methodology, with application and validation in a real factory setting. The system uses mobile devices and visual recognition to provide audiovisual instructions in five critical operational scenarios. Compared to traditional methods, a 57 % reduction in setup time, a 25 % increase in execution accuracy, and a 75 % decrease in requests for help were observed. The system achieved an average of 9.25 on the User Experience (UX) scale and 4.5 on nine technical indicators evaluated by experts. Unlike commercial AR platforms, the solution adopts a local architecture, independent of constant connectivity, facilitating its adoption in environments with operational constraints. These benefits are aligned with the Industry 5.0 proposal, which values customization according to human needs.

Natural science research is the most common and widely used research methodology. Various fields such as physics, biology, social and behavioral apply this research methodology. However, not all research is suitable for using the natural science research methodology in computer fields such as information technology, computer science, and information systems. Research that aims to solve problems by developing an artefact is more suitable for using the design science research methodology. Unfortunately, there are still many researchers who do not understand or even do not know this methodology. In this paper, we discuss the design science research methodology framework to reintroduce this methodology. The discussion starts with the theory of design science research, which explains five stages, from the explicated problem to the evaluation stage. Furthermore, an example of the application of this methodology is presented for the timetabling problem. This application example shows how the design process was and what the results were. This paper is expected to provide knowledge to researchers, especially for researchers who should use this methodology.

We propose a methodological framework based on design science research for the design and development of data and information artifacts in data analysis projects, particularly managerial performance analysis. Design science research methodology is an artifact-centric creation and evaluation approach. Artifacts are used to solve real-life business problems. These are key elements of the proposed approach. Starting from the main current approaches of design science research, we propose a framework that contains artifact engineering aspects for a class of problems, namely data analysis using machine learning techniques. Several classification algorithms were applied to previously labelled datasets through clustering. The datasets contain values for eight competencies that define a manager’s profile. These values were obtained through a 360 feedback evaluation. A set of metrics for evaluating the performance of the classifiers was introduced, and a general algorithm was described. Our initiative has a predominant practical relevance but also ensures a theoretical contribution to the domain of study. The proposed framework can be applied to any problem involving data analysis using machine learning techniques.

The emerging impact of cloud computing in businesses has become a great driving force for business success and cannot be understated. The lack of a tailored functional application software, even though a framework exists, poses a significant challenge to SMEs. Without a digital corresponding software solution, SMES struggle to conduct a practical assessment since the framework offers only theoretical guidance. A well-developed cloud implementation assessment tool is essential for SMEs to thrive. The main aim of the study was to develop a robust cloud implementation assessment system for SMEs to evaluate their cloud implementation readiness. Design Science Research Methodology (DSRM), is a kind of research methodology which aims at developing and evaluating innovative artefacts, in the form of models, frameworks, designs, or prototypes, to solve complex and practical problems. Framework Usability Validation used. On the Clarity of the framework, none of the respondents strongly disagreed, representing 0%. 8 respondents, representing 15.4% disagreed, and 3 respondents, representing 5.8% were unsure. The system was developed using the Django Python web framework. Out of 43 respondents, 18 participants (42%) found the Learn Cloud Phase helpful, 3 participants (7%) found the Assessment and Cloud Choice Phase helpful, and 15 participants (35%) found the Migration Phase helpful. Additionally, 4 participants (9%) reported that all phases were helpful, 2 participants (5%) indicated that none of the phases were helpful, and 1 participant (2%) was uncertain about the helpfulness of any phase. In this paper, the design science Research (DSR) method was utilised to develop and evaluate the cloud implementation assessment system for SMEs. Key features of the developed system include learn cloud, assessment, cloud choice and migration phase. The developed system was said to be very useful and suitable, solidifying its value as a helpful resource for small businesses aiming to utilise cloud technology. A cloud assessment system was developed to aid in assessing SMEs' cloud readiness and implementation. Generally, SMEs responded positively to the cloud computing implementation framework.

PurposeThe main goal of this research work is the optimization of the purchasing business process in the Moroccan public sector in terms of transparency and budgetary optimization. The authors have worked on the public university as an implementation field.Design/methodology/approachThe design of the research work followed the design science research (DSR) methodology for information systems. DSR is a research paradigm wherein a designer answers questions relevant to human problems through the creation of innovative artifacts, thereby contributing new knowledge to the body of scientific evidence. The authors have adopted a techno-functional approach. The technical part consists of the development of an intelligent recommendation system that supports the choice of optimal information technology (IT) equipment for decision-makers. This intelligent recommendation system relies on a set of functional and business concepts, namely the Moroccan normative laws and Control Objectives for Information and Related Technology's (COBIT) guidelines in information system governance.FindingsThe modeling of business processes in public universities is established using business process model and notation (BPMN) in accordance with official regulations. The set of BPMN models constitute a powerful repository not only for business process execution but also for further optimization. Governance generally aims to reduce budgetary wastes, and the authors' recommendation system demonstrates a technical and methodological approach enabling this feature. Implementation of artificial intelligence techniques can bring great value in terms of transparency and fluidity in purchasing business process execution.Research limitations/implicationsBusiness limitations: First, the proposed system was modeled to handle one type products, which are computer-related equipment. Hence, the authors intend to extend the model to other types of products in future works. Conversely, the system proposes optimal purchasing order and assumes that decision makers will rely on this optimal purchasing order to choose between offers. In fact, as a perspective, the authors plan to work on a complete automation of the workflow to also include vendor selection and offer validation. Technical limitations: Natural language processing (NLP) is a widely used sentiment analysis (SA) technique that enabled the authors to validate the proposed system. Even working on samples of datasets, the authors noticed NLP dependency on huge computing power. The authors intend to experiment with learning and knowledge-based SA and assess the' computing power consumption and accuracy of the analysis compared to NLP. Another technical limitation is related to the web scraping technique; in fact, the users' reviews are crucial for the authors' system. To guarantee timeliness and reliable reviews, the system has to look automatically in websites, which confront the authors with the limitations of the web scraping like the permanent changing of website structure and scraping restrictions.Practical implicationsThe modeling of business processes in public universities is established using BPMN in accordance with official regulations. The set of BPMN models constitute a powerful repository not only for business process execution but also for further optimization. Governance generally aims to reduce budgetary wastes, and the authors' recommendation system demonstrates a technical and methodological approach enabling this feature.Originality/valueThe adopted techno-functional approach enabled the authors to bring information system governance from a highly abstract level to a practical implementation where the theoretical best practices and guidelines are transformed to a tangible application.

Based on reviewing foremost literature, this paper discusses various design science research methodologies and related to them case studies. I have identified common activities that may create an outline of a reference model for design science. The model will apply to a design step activity in any design science methodology. I also present my assumptions, based on structured interviews, that the current abstract level of design science methodologies may cause poor quality of content of its artefacts. As for the measurement of quality, I discuss representational information quality dimensions. The contribution of the paper is to relate design sciences theories with research activities by providing a design science process oriented framework. My observations indicate that it will help improve the quality of design science artefacts.KeywordsDesign Science MethodologySystematic FrameworkDesign Science Literature ReviewInformation Quality Dimensions

Knowledge-intensive business services (KIBS) such as consulting and research and development services are important factors of performance and innovation in industrialized economies. However, current modeling techniques aimed at supporting service design do not account for their core characteristics such as the relational nature of exchanges among providers, clients, and other actors. Using data from a case of academic research and development service as a type of KIBS, we present a modeling technique that can support the design of successful service engagements in this domain. This work is guided by the understanding of service as a process of collaborative value creation, or value cocreation. Beyond the contribution of the modeling technique to KIBS design, our work shows the strength of using a Design Science Research methodology in creating design artifacts that are strongly aligned with the problem domain for which they are developed.

Course and instructor evaluations (CIE) are essential tools for assessing educational quality in higher education. However, traditional CIE systems often suffer from inconsistencies between structured responses and open-ended feedback, leading to unreliable insights and increased administrative workload. This study suggests a modular system to address these challenges, leveraging sentiment analysis and inconsistency detection to enhance the reliability and efficiency of CIE processes.BackgroundImproving the reliability of CIE data is crucial for informed decision-making in higher education. Existing methods fail to address discrepancies between numerical scores and textual feedback, resulting in misleading evaluations. This study proposes a system to identify and exclude inconsistent data, providing more reliable insights.MethodsUsing the Design Science Research Methodology (DSRM), a system architecture was developed with five modules: data collection, preprocessing, sentiment analysis, inconsistency detection, and reporting. A dataset of 13,651 anonymized Turkish CIE records was used to train and evaluate machine learning algorithms, including support vector machines, naive Bayes, random forest, decision trees, K-nearest neighbors, and OpenAI’s GPT-4 Turbo Preview model. Sentiment analysis results from open-ended responses were compared with structured responses to identify inconsistencies.ResultsThe GPT-4 Turbo Preview model outperformed traditional algorithms, achieving 85% accuracy, 88% precision, and 95% recall. Analysis of a prototype system applied to 431 CIEs identified a 37% inconsistency rate. By excluding inconsistent data, the system generated reliable reports with actionable insights for course and instructor performance. The purpose of this study is to design and evaluate a new system using the Design Science Research (DSR) approach to enhance the accuracy and reliability of course evaluation processes employed in higher education institutions. The modular system effectively addresses inconsistencies in CIE processes, offering a scalable and adaptable solution for higher education institutions. By integrating advanced machine learning techniques, the system enhances the accuracy and reliability of evaluation reports, supporting data-driven decision-making. Future work will focus on refining sentiment analysis for neutral comments and broadening the system’s applicability to diverse educational contexts. This innovative approach represents a significant advancement in leveraging technology to improve educational quality.

Extended-Reality Technologies: An Overview of Emerging Applications in Medical Education and Clinical Care.

Food safety, quality and preservation are some latest issues concerned with food industries today. During recent years, the application of nanotechnology in the food sector has gained much popularity worldwide and is jumping at a rapid rate in this direction. Subsequently, attention towards the utility of essential oil nanoemulsions as a natural food preservative is increasing day by day. In spite of a lot of benefits offered by essential oils, there are some problems (high volatile nature, low water solubility and strong odour) associated with their use in various formulations. However, distinctive properties like more surface area, small size and constancy towards physical and chemical changes, make nanoemulsions a valuable formulation for targeted delivery of essential oils. These act as effective delivery systems for essential oils as bioavailability and stability of the encapsulated bioactive compounds get enhanced. Antimicrobial activity of the emulsions is influenced by many factors like kinds of essential oils and emulsifiers, ripening inhibitor and method of fabrication used for nanoemulsions preparation. The application of nanoemulsions for human use is safe except in situations in which a very high concentration of surfactants and emulsifiers are used. High-energy and low-energy methods are most commonly employed techniques for their formulation. The present discussion opens a new perspective for use of essential oil nanoemulsions in a wide range of products and will be helpful in satisfying the consumer needs of safe and wholesome foods.

Since 2001, a link has been established between the Last Planner® System (LPS) and Linguistic Action Perspective (LAP). However, to date, it has not been studied in sufficient depth. This research developed a system of indicators to measure and control the management of commitments, through the Design Science Research (DSR) methodology, and thus contribute to the development of the social dimension of sustainability that is often neglected in construction management research. The main contributions of this paper are a proposal of five main activities to apply the DSR method, a checklist to analyze the engagement of meeting participants, a notebook for last planners, delve into the variations that can occur to the basic movements of LAP, and the creation of a system of indicators hence updating the Percent Plan Complete (PPC) with a reliability indicator. The main limitation of this research is that the system was only validated in two South American countries that implemented LPS. In future studies, we propose to apply case studies in weekly planning meetings in other industries worldwide and to determine the recommended values to improve communication and achieve the proper implementation of LAP with LPS and without LPS.

This study uses the Design Science Research Methodology (DSRM) approach in creating an artifact on the perspective of the Information System. Design Science as a valuable tool for creating a new artifact or developing an existing artifact through research. The DSRM Framework described in this study discusses the implementation of each stage, namely, Explicated Problem, Define Requirement, Design and Development, Demonstration, and Evaluation and is complemented by the implementation of case studies of artifact creation in DSRM stages. The Digital Maturity Measurement in question is a service to measure digital maturity in various dimensions. Each DSRM stage is mapped to a case study of that service. Canvas visualization is presented to describe a complete picture of how the artifacts of Digital maturity services are built with the DSRM approach. This research also provides guidance on the principles, procedures, and characteristics needed to build effective research.

This research conceptualises and validates a design theory for developing Community Collaboration Support Systems (CCSS) to enhance supply chain (SC) resilience during crises. We constructed a knowledge base to derive kernel theories, following the Design Science Research (DSR) methodology. Utilising exploratory and confirmatory focus groups as the primary data collection methods, we refined and validated the proposed CCSS design theory, ensuring its robustness, applicability, and validity. This study not only contributes to the field of information collaborative systems through the theoretical conceptualisation of CCSS theory but also provides practical insights for researchers and practitioners, fostering advancements in crisis management and community collaboration support systems.