Problems and Solutions
Proposing Indonesian Comic Ecosystem-making through Systemic Design: A Social Innovation through Artist-led Co-design View Digital Media
Paper Presentation in a Themed Session Gideon Hutapea
After many unsuccessful national plans, steps towards systemic thinking and new leadership to improve the Indonesian comic ecosystem have emerged. The research investigates comic artists' leadership capability in improving the ecosystem by understanding it as a systemic problem. Artists are regarded as creative agents capable of designing ("designers") their own ecosystems in addition to excelling in their material culture. The research shifts away from government reliance and put artists who were previously unrecognized to lead the effort. It reveals artists' inventive skills and to become theoretical prototypes of artist leadership interacting with the system's inhabitants. The effort is driven through systemic design methodology, operating through participatory design in social innovation to empower all inhabitants as "designers" in defining and achieving goals and devising enabling systems. By applying multimethod research, the first step is a holistic diagnosis analyses the Indonesian comic complexities. The result is a Giga map, which allows comic artists to focus groups on identifying system challenges in the next step. Focus groups then offer a mental model as a reference point to inform the artist-led co-design process. Co-design convenes system inhabitants as "designers," providing diverse skills, insights, and ways of thinking. The output is a white paper outlining recommended actions. The research is limited in size and scope and acknowledges the risks of unforeseen disruption caused by power shifts and government (dis)empowerment. In conclusion, this new understanding presents political and ethical power shifts, the intriguing possibility of artist-led system transformation, and creative methodologies.
Questions on Redesigning the Plastic Condition View Digital Media
Paper Presentation in a Themed Session Joel Gn
Synthetic polymers, otherwise known as plastic is often regarded as cheap, fake and toxic. Since its commercialisation in the 20th century, plastic has not only become more indispensable for human activity, but is associated with irreversible pollution and ecotoxicity. Yet, accepting the use and consequent waste of plastic as simply an intrusion of human contrivance is to externalise a toxicity that proves to be more peculiar in its origins and culture. To espouse plastic’s sheer artificiality is to overlook its foundations in organic matter, and the proposition that its ‘life’ is – to draw from the narrative in Mary Shelley’s Frankenstein – a reanimation at the expense of the remains of the non-living. It is through this transformation that the operation of plastic’s cultural significance and semantic intersection with cancer becomes evident, insofar as the latter is a deviant cell synthesised by the body’s own mutations and stressors, and in time acquires a plasticity that grows and resides as a toxic entity within the organs. Exploring the parallels between cancer and plastic open the space for oncology to question the plastic condition, and show the production and consumption of the material intrinsically entwined with our humanity. To completely forgo plastic would therefore involve a radical redesigning or even undoing of the human condition, as plastic’s raison d'être lies not in the objects derived from it, but in the quality and potentials of plasticity.
Low-Cost Digitalization for Sustainable Energy Management: A Hybrid Approach for Predicting Occupant Energy Consumption in Different Indoor Layout Configurations View Digital Media
Paper Presentation in a Themed Session Mohammad Nyme Uddin, Xue Cui, Xuange Zhang, Minhyun Lee
Accurately predicting occupant energy consumption is crucial for optimizing energy management and promoting sustainability in buildings. However, the availability of reliable stochastic data on occupant energy consumption poses significant challenges including cost and privacy considerations. This research proposes a low-cost digitalization approach that integrates Agent-Based Modeling (ABM), System Dynamics (SD), Building Information Modeling (BIM), and Machine Learning (ML) techniques to predict energy consumption in various indoor layout configurations, while prioritizing affordability, privacy, and sustainability. To investigate the effectiveness of the approach, three different geometric shapes representing indoor layouts (rectangular, square, and compound) were selected from a residential building in Chittagong, Bangladesh. An ABM-SD-BIM model was constructed, incorporating occupant data, layout information, and environmental data. The model-generated energy consumption data was calibrated using three months of real data collected from customized sensors installed within the indoor layouts. The calibrated model accurately generated data for the entire summer month period from April to September, which was used to develop the ML prediction model for each layout. Results indicate that Layout 3 (Compound) exhibits consistent and favorable performance across the models, suggesting its suitability for accurate energy consumption prediction. The proposed approach prioritizes affordability, privacy, and sustainability, making it accessible and applicable to various building design, operation, and policy-making scenarios. This research contributes to the broader field of low-cost digitalization, emphasizing the importance of accurate energy prediction for optimizing energy management and promoting sustainable practices.
