National Taipei University

This teaching case examines AquaTech’s critical decision to overcome the ‘black box’ dilemma of open-ocean aquaculture – a traditional industry reliant on veteran farmers’ tacit knowledge for feed management in highly volatile environments. This subjectivity created severe financial and environmental risks, including costly resource waste and crippling downstream supply chain inefficiencies due to low inventory accuracy. The case details the implementation of an innovative AI system that fuses computer vision, sonar, and IoT sensors to provide real-time, empirical data on fish satiety and biomass. The AI pilot demonstrated decisive operational superiority, leading to a substantial increase in Feed Conversion Ratio (FCR) efficiency, which simultaneously drove down feed costs, significantly increased harvest yield, and reduced environmental impact. This digital transformation illustrates the profound potential for traditional industries to solve persistent challenges by adopting new technology.

Spatiotemporal Characteristics of Precipitation and Drought Variability in Taiwan Using Multi-dimensional Complementary Ensemble Empirical Mode Decomposition AbstractMost time series observed in natural systems are nonlinear and nonstationary, particularly under the influence of climate change. Taiwan has experienced increasingly frequent drought events in recent decades. Droughts are characterized by their gradual development, cumulative impacts, and lack of clear early warning signals, which makes their detection and analysis challenging. To address these issues, this study applies Multi-dimensional Complementary Ensemble Empirical Mode Decomposition (MCEEMD) to analyze long-term temperature and precipitation data in Taiwan from 1960 to 2023. MCEEMD is an effective time–frequency analysis method designed for nonlinear and nonstationary time series. It enables the decomposition of multi-dimensional signals into a set of Intrinsic Mode Functions (IMFs), allowing both spatial and temporal characteristics of climate variables to be examined. Through these IMFs, meaningful instantaneous frequencies and long-term trends in the signals can be identified. This study considers both stochastic and deterministic influences by reconstructing the IMFs into two components based on their autocorrelation coefficients. The relationships between temperature, precipitation variability, and drought-related characteristics are then examined, providing insights into the spatiotemporal behavior of drought events in Taiwan. Key word: Multi-dimensional Complementary Ensemble Empirical Mode Decomposition(MCEEMD ),Intrinsic Mode Functions (IMFs)

As global urbanization accelerates, the United Nations projects that nearly 68% of the world’s population will live in cities by 2050, increasing pressure on urban livability under climate change, pollution, and urban heat islands. Conventional comfort research often relies on single indicators (e.g., temperature) and misses how people experience outdoor spaces. This study proposes a multi-domain framework integrating thermal, visual, acoustic, and air-quality factors to evaluate community-scale outdoor comfort. Fieldwork was conducted in a dense, mixed-use traditional neighborhood in the Daxue community during an Intensive Observation Period (IOP). The researcher walked a predefined route with multiple checkpoints at scheduled times to represent daily outdoor activities. A mobile sensing device continuously recorded air temperature, humidity, wind speed, illumination, sound level, and air-quality indicators, while structured qualitative rating scales documented in-situ perceptions of comfort across domains.To bridge the gap between monitoring evidence and community perceptions, the study convened a participatory mapping workshop with residents and other stakeholders. Monitoring results were shared as prompts, and participants collaboratively identified perceived environmental hotspots and discussed the contextual drivers behind them. Beyond jointly proposing improvement strategies and practical solutions, the workshop also helped residents and stakeholders better understand local environmental issues and strengthen environmental awareness. By combining objective monitoring, qualitative perception records, and participatory mapping, this approach links environmental science with community-informed decision-making and provides actionable evidence for community-scale planning and design. Future work will extend the framework across seasons and diverse urban typologies to refine and generalize the proposed model.

The representation of deep moist convection and organized convective systems in numerical modeling of the atmosphere is pivotal to model fidelity. Although kilometer-scale global models better capture large-scale oscillations and convection features that traditional general circulation models struggle to represent, past studies have reported notable differences in their simulations of convective organization, especially over the tropics. However, untangling the controlling factors of convective organization remains challenging, since physical processes associated with deep moist convection are intrinsically multiscale and deeply intertwined. To address this challenge, this study develops a cumulus parameterization tailored for kilometer-scale models, aiming to enable the modulation and systematic testing of multiscale interactions associated with deep moist convection.The cumulus parameterization developed in this study employs Arakawa's unified parameterization to represent the interactions of unresolved deep moist convection with its environmental flow, including the explicitly simulated convection. The underlying parameterizability of unresolved deep moist convection follows the notion of convective quasi-equilibrium, while a complementary closure is employed to predict the fractional area covered by cumulus updrafts and adjust the local vertical eddy transports accordingly. A representation of stochasticity and convection memory is introduced by coupling our parameterization with a cellular automaton. Empirical values and physical assumptions are used to establish our parameterization as a prototype subject to designing systematic experiments of specific process representation in the future.Idealized experiments of tropical maritime deep convection at a horizontal grid spacing of 3 km demonstrate that employing our parameterization in convection-permitting simulations modulates deep convective system features while generally retaining the profile of total vertical energy transport associated with deep convection. Unresolved deep convection dominates the vertical energy transport in the early stages of deep convective systems, and its contribution gradually weakens as systems develop. Meanwhile, detrainment from unresolved deep convection leads to the early occurrence of cumulus congestus and cumulonimbus. In comparison with the ordinary convection-permitting simulation, our parameterization exhibits a pronounced congestus mode in the vertical velocity profile of mature convective systems, partially due to the enhanced dry static stability. Overall, simulations with our parameterization exhibit fewer and larger short-lived convective systems. Further investigation into the source of the uncertainty in convective organization is warranted.

Most international student mobility research emphasizes class reproduction and credential competition rather than how valuation actually occurs. This study examines Taiwanese education agents and their role in shaping the valuation of U.S. college admissions applicants. Data from interviews, observations, and archives are used to explain how agents help students reorganize life stories, fine-tune language, and insert symbolic cues in an effort to increase perceptions of authenticity and admissibility. Essays and recommendation documents are central to the task of making authenticity look natural, with a major requirement of not appearing fabricated. This study uses Karpik’s (2010) economy of singularities theory to analyze these practices, to show how such merit is actively produced rather than simply measured, and to discuss uneven access to production tools. In doing so, the paper contributes a clearer account of how admissibility making operates as a valuation mechanism that reshapes opportunity pathways in global higher education, and reveals the paradox of produced authenticity through which commercial intermediaries remake global admissions ideals.

Anthropogenic greenhouse gas emissions continue to drive global climate change, highlighting the importance of terrestrial ecosystems in regulating atmospheric carbon. While vegetation acts as a major carbon sink through photosynthetic uptake and biomass accumulation, carbon sequestration research has predominantly focused on forest ecosystems. In contrast, agricultural systems—especially perennial crops—remain comparatively underrepresented despite their extensive land coverage and long-term management.Tea plantations (Camellia sinensis) are perennial agroecosystems composed of long-lived woody shrubs with repeated harvest cycles and sustained biomass, suggesting a potentially significant but poorly constrained role in terrestrial carbon cycling. In Taiwan, tea is a major commercial crop occupying extensive agricultural land, yet quantitative assessments of plant–soil carbon exchange processes in tea systems remain limited. To better understand carbon exchange processes in tea plantations, this study applies a dual-approach integrating plant- and soil-level greenhouse gas measurements in a managed tea garden in Taiwan.Field measurements were conducted from January to April 2026. Branch-level photosynthesis and respiration were monitored using branch cuvettes, and gas exchange rates were extrapolated to the plant level using allometric relationships. Concurrently, soil carbon dioxide (CO2) fluxes were measured using static chamber techniques to characterize soil–atmosphere carbon exchange, with fluxes further extrapolated to the garden scale. Measurements were repeated monthly under fair-weather conditions and supported by laboratory gas chromatography analysis. Ancillary environmental variables and management activities were recorded to support flux interpretation.Overall, this study provides an integrated, field-based assessment of carbon exchange dynamics in a managed tea plantation by explicitly linking plant- and soil-level gas fluxes with seasonal progression and agricultural practices. By aligning greenhouse gas measurements with farming activities, the results offer insight into how management and phenological stages jointly regulate carbon exchange in perennial agroecosystems. The findings contribute to reducing current uncertainties surrounding the role of tea plantations in terrestrial carbon cycling and provide a scientific basis for future evaluations of carbon management and climate mitigation potential in perennial agricultural systems.