Integration of 3D Scanning and Augmented Reality (AR) Technology in East Kalimantan Furniture Products in E-Commerce

The creative furniture industry in East Kalimantan faces the challenge of less effective online marketing in e-commerce. In 2018, there were more than 370 furniture entrepreneurs in the region, but only 37% of their total production managed to reach the market. According to projections from Markets and Markets, the market value of Augmented Reality (AR) in e-commerce is expected to grow by 34% between 2020 and 2025. To overcome this problem, the use of 3D object configuration visual technology and AR presents a better solution. promising solution. This technology can improve product presentation, create a more interactive and realistic shopping experience, and reduce the environmental impact of e-commerce due to the re-shipment of non-conforming products. The main objective of the research is to assess the effectiveness of product communication, the ease of the purchasing process, and the level of consumer trust in the product. This visual method of 3D object configuration combines 3D scanning to produce detailed and realistic 3D images. This research uses a sprint design method based on design thinking, which involves co-creation to refine ideas. Next, a prototype design was developed with a focus on aspects of the user interface and user experience, fostering intelligent interaction between users and their environment, thus contributing to the progress of the Smart City concept in IKN Nusantara

Integrating Natural Language Processing and Interpretive Thematic Analyses to Gain Human-Centered Design Insights on HIV Mobile Health: Proof-of-Concept Analysis

Background: HIV mobile health (mHealth) interventions often incorporate interactive peer-to-peer features. The user-generated content (UGC) created by these features can offer valuable design insights by revealing what topics and life events are most salient for participants, which can serve as targets for subsequent interventions. However, unstructured, textual UGC can be difficult to analyze. Interpretive thematic analyses can preserve rich narratives and latent themes but are labor-intensive and therefore scale poorly. Natural language processing (NLP) methods scale more readily but often produce only coarse descriptive results. Recent calls to advance the field have emphasized the untapped potential of combined NLP and qualitative analyses toward advancing user attunement in next-generation mHealth. Objective: In this proof-of-concept analysis, we gain human-centered design insights by applying hybrid consecutive NLP-qualitative methods to UGC from an HIV mHealth forum. Methods: UGC was extracted from Thrive With Me, a web app intervention for men living with HIV that includes an unstructured peer-to-peer support forum. In Python, topics were modeled by latent Dirichlet allocation. Rule-based sentiment analysis scored interactions by emotional valence. Using a no v el ranking standard, the experientially richest and most emotionally polarized segments of UGC were condensed and then analyzed thematically in Dedoose. Design insights were then distilled from these themes. Results: The refined topic model detected K=3 topics: A: disease coping; B: social adversities; C: salutations and check-ins. Strong intratopic themes included HIV medication adherence, survivorship, and relationship challenges. Negative UGC often involved strong negative reactions to external media events. Positive UGC often focused on gratitude for survival, well-being, and fellow users’ support. Conclusions: With routinization, hybrid NLP-qualitative methods may be viable to rapidly characterize UGC in mHealth environments. Design principles point to ward opportunities to align mHealth intervention features with the organically occurring uses captured in these analyses, for example, by foregrounding inspiring personal narratives and expressions of gratitude, or de-emphasizing anger-inducing media

Designing an Online Intervention for Adults with ADHD

Attention-deficit/hyperactivity disorder(ADHD) affects humans across a life span. However, the available treatment resources are quite limited for adults with ADHD. In this study, a mobile application is designed to help support interaction in-between group therapy sessions. The Companion app is designed to be a part of an intervention targeting emotional issues in adults with ADHD, based on principles from Dialectical behavior therapy (DBT). The methodology applied in this thesis is Research through Design (RtD), and participatory design methods were applied in the design and research process. Hence, this research included participation from clinical experts, adults with ADHD, and UX/HCI experts ensuring that researchers from relevant fields and potential users were involved in the design of the intervention. Previous research finds that users' participation in the design process is important to ensure valuable products. In the context of mental health applications, the involvement of users with lived experience can contribute to a better understanding of user needs and limit the risk of low usability. Furthermore, several features were found to be useful in supporting interaction in-between group therapy sessions. By implementing peer support, homework, journals, and other resources, principles from DBT can be transferred into a digital format. This research resulted in a prototype of the Companion app, including several features based on data from previous research and the design process. The results indicate that ADHD users are positive to the use of online interfaces in the context of therapy. Nevertheless, the Companion app should be tested in the context of a therapy intervention to ensure effectiveness.Masteroppgave i informasjonsvitenskapINFO390MASV-INF

Metodología para integrar la experiencia de usuario en el desarrollo de sistemas web de una entidad pública, Lima 2021

A menudo somo testigos de las dificultades que tienen los usuarios al hacer uso de servicios públicos, ya sea por la calidad de dichos servicios o por la simple inexistencia de estos. Una forma efectiva de garantizar la satisfacción de los usuarios en el uso de un servicio digital es la adopción de la Experiencia de Usuario en las etapas de desarrollo de los sistemas web. Desde hace muchos las entidades públicas han venido desarrollado sistemas web utilizando metodologías tradicionales en cascada, sin embargo, en los últimos años la tendencia es generar entornos de desarrollo ágiles. Esta investigación fue de enfoque cualitativo, el método de investigación se basó en el paradigma interpretativo, el tipo de investigación fue aplicada y se utilizó el diseño de investigación acción. Se empleó como técnicas, la entrevista a profundidad semiestructurada realizada a expertos externos de la entidad, la observación a la unidad de estudio. Se concluye que para integrar la Experiencia de Usuario en el desarrollo de sistemas web se debe considerar los beneficios del uso de las metodologías existentes y aplicarlas en entornos de desarrollo ágiles, aunque se puede integrar a entornos tradicionales en cascada, pero con propensión a encontrar mayores dificultades

Steve, A Framework For Augmenting The Visual Identity Design Process With ML

This research is positioned in the field of graphic design and seeks to investigate the working processes in visual identity projects and their augmentation through Machine Learning (ML). It defines identity as the visual elements that, together, create an atmosphere around a client, involving its values and views of the world and society. Through a deep focus on the creative process, this thesis proposes functional approaches to integrate the designer's perspective on the development of new digital tools. My study reveals fruitful ways to augment identity design through ML rather than replace designers through automation. Since its blooming during the Industrial Revolution, visual identity remains the highest-order project in the discipline of graphic design. The parallel evolution of graphic and information technology has undergone numerous phases in which visual identity structures have become more dynamic, and its impact on society has grown along with the designer’s responsibilities. Increasing integration of automation into graphic design in the twenty-first century, as well as potential future developments in ML, represent new challenges for professionals and researchers. Investigation into the intersection of ML and graphic design has been led mainly by computer scientists, leading to misplaced assumptions of creativity. At the same time, research into graphic creative processes is limited. My research addresses these deficiencies, and the gap in the existing literature on the conjunction between graphic design theory and practice, by involving practitioners in the evaluation and proposal of novel design tools. Moreover, it creates a direct link between software development and the actual needs of graphic designers. The novelty of this research lies in the intersection of design methodology, visual identity and ML. Research on design processes is well established in other areas like architecture, industrial design and software development. An understanding of tools and concepts from these fields helps to investigate the possibilities of integrating ML into the design process. Three main questions are addressed in the research: – Is it possible to find coherent working methods in visual identity projects? – What are the most critical phases for the designers in visual identity projects? – How can these be augmented through ML? To answer these questions, I utilize grounded theory methodology, complemented by literature review, to construct a conceptual framework rooted in the expertise of practitioners. By conducting semi-structured interviews with a sample of twenty graphic design studios, I confirmed that they employ consistent and coherent working methods and that ML has the potential to help augment critical phases in the visual identity process. My findings are further explored via non-participant observation that, in conjunction with the interviews, has led to a primary hypothesis subsequently tested through a within-subject design survey. My findings collectively provide a series of propositions that constitute the basis for a concrete ML implementation proposal. The definition of a replicable conceptual framework that incorporates the shared semantic cognition of design teams into an ML recommendation system constitutes the main contribution to the knowledge offered by my thesis.This research is positioned in the field of graphic design and seeks to investigate the working processes in visual identity projects and their augmentation through Machine Learning (ML). It defines identity as the visual elements that, together, create an atmosphere around a client, involving its values and views of the world and society. Through a deep focus on the creative process, this thesis proposes functional approaches to integrate the designer's perspective on the development of new digital tools. My study reveals fruitful ways to augment identity design through ML rather than replace designers through automation. Since its blooming during the Industrial Revolution, visual identity remains the highest-order project in the discipline of graphic design. The parallel evolution of graphic and information technology has undergone numerous phases in which visual identity structures have become more dynamic, and its impact on society has grown along with the designer’s responsibilities. Increasing integration of automation into graphic design in the twenty-first century, as well as potential future developments in ML, represent new challenges for professionals and researchers. Investigation into the intersection of ML and graphic design has been led mainly by computer scientists, leading to misplaced assumptions of creativity. At the same time, research into graphic creative processes is limited. My research addresses these deficiencies, and the gap in the existing literature on the conjunction between graphic design theory and practice, by involving practitioners in the evaluation and proposal of novel design tools. Moreover, it creates a direct link between software development and the actual needs of graphic designers. The novelty of this research lies in the intersection of design methodology, visual identity and ML. Research on design processes is well established in other areas like architecture, industrial design and software development. An understanding of tools and concepts from these fields helps to investigate the possibilities of integrating ML into the design process. Three main questions are addressed in the research: – Is it possible to find coherent working methods in visual identity projects? – What are the most critical phases for the designers in visual identity projects? – How can these be augmented through ML? To answer these questions, I utilize grounded theory methodology, complemented by literature review, to construct a conceptual framework rooted in the expertise of practitioners. By conducting semi-structured interviews with a sample of twenty graphic design studios, I confirmed that they employ consistent and coherent working methods and that ML has the potential to help augment critical phases in the visual identity process. My findings are further explored via non-participant observation that, in conjunction with the interviews, has led to a primary hypothesis subsequently tested through a within-subject design survey. My findings collectively provide a series of propositions that constitute the basis for a concrete ML implementation proposal. The definition of a replicable conceptual framework that incorporates the shared semantic cognition of design teams into an ML recommendation system constitutes the main contribution to the knowledge offered by my thesis