In order to cope with the turbulent environments in digital age, an enterprise should response to the changes quickly. Therefore, an enterprise must improve her ability of real-time decision-making. One way to increase the competence of real-time decision-making is to use Real-Time Decision Support Systems (RTDSS). A key feature for a Decision Support Systems (DSS) to successfully support real-time decision-making is to help decision-makers selecting the best models within deadline. This study focuses on developing methods to support the mechanism of model selection in DSS. There are five results in this study. Firstly, we have developed a time-based framework to evaluate models. This framework can help decision-makers to evaluate the quality and cost of model solutions. Secondly, based on the framework of models evaluation, we also developed three models selection strategies. These strategies can help decision-makers to select the best model within deadline. Thirdly, according the definitions of parameter value precision and model solution precision in this study, we conduct a simulation analysis to understand the impacts of the precision of parameter values to the precision of a model solution. Fourthly, in order to understand the interaction among the model selection variables, we also simulate the application of model selection strategies. The results of simulation indicate our study can support models selection well. Finally, we developed a structure-based model retrieval method to help decision-makers find alternative models from model base efficiently and effectively. In conclusion, the results of this research have drawn a basic skeleton for the development of models selection. This research also reveals much insight into the development of real-time decision support systems.

Backup diesel generator (DG) systems continue to be a heavily polluting and costly solution for institutions with unreliable grid connections. These systems slow economic growth and accelerate climate change. Photovoltaic (PV), energy storage (ES), grid connected, DG – Hybrid Energy Systems (HESs) or, PV-HESs, can alleviate overwhelming costs and harmful emissions incurred from traditional back-up DG systems and improve the reliability of power supply. However, from project conception to end of lifetime, PV-HESs face significant barriers of uncertainty and variable operating conditions. The fit-and-forget solution previously applied to backup DG systems should not be adopted for PV-HESs. To maximize cost and emission reductions, PV-HESs must be adapted to their boundary conditions for example, irradiance, temperature, and demand. These conditions can be defined and monitored using measurement equipment. From this, an opportunity for performance optimization can be established. The method demonstrated in this study is a techno-economic and environmental approach to improving the performance of PV-HESs. The method has been applied to a case study of an existing PV-HES in Kenya. A combination of both analytical and numerical analyses has been conducted. The analytical analysis has been carried out in Microsoft Excel with the intent of being easily repeatable and practical in a business environment. Simulation analysis has been conducted in improved Hybrid Optimization by Genetic Algorithms (iHOGA), which is a commercially available software for simulating HESs. Using six months of measurement data, the method presented identifies performance inefficiencies and explores corrective interventions. The proposed interventions are evaluated, by simulation analyses, using a set of techno-economic and environment key performance indicators, namely: Net Present Cost (NPC), generator runtime, fuel consumption, total system emissions, and renewable fraction. Five corrective interventions are proposed, and predictions indicate that if these are implemented fuel consumption can be reduced by 70 % and battery lifetime can be extended by 28 %, net present cost can be reduced by 30 % and emissions fall by 42 %. This method has only been applied to a single PV-HES; however, the impact this method could have on sub-Saharan Africa as well as similar regions with unreliable grid connections is found to be significant. In the future, in sub-Saharan Africa alone, over $500 million dollars (USD) and 1.7 billion kgCO2 emissions could be saved annually if only 25 % of the fuel savings identified in this study were realized. The method proposed here could be improved with additional measurement data and refined simulation models. Furthermore, this method could potentially be fully automated, which could allow it to be implemented more frequently and at lower cost.

<p dir="ltr">The study investigated an innovative design and modeling approach for a compliant four-bar mechanism incorporating a variable stiffness link (VSL), which enabled multiple end-effector trajectories without requiring structural modifications. Conventional four-bar mechanisms have limited adaptability due to fixed configurations, constraining their applications in environments demanding flexible motion paths. The integrated VSL, serving as the output link, permitted trajectory versatility under consistent load conditions by allowing stiffness adjustments. The research involved analyzing both single-beam and multi-sectional configurations of the VSL, utilizing a large deflection model (LDM) and a pseudo-rigid-body model (PRBM) to simulate compliant behavior accurately. Comprehensive validation of the theoretical model included numerical simulations, finite element analysis (FEA), and physical testing with a 3D-printed prototype. Findings demonstrated that VSL significantly broadened the application potential of four-bar mechanisms, offering enhanced adaptability, efficient performance, and resilience across dynamic environments. The study contributed to the advancement of compliant mechanism design, providing valuable insights for applications in robotics, automotive systems, and biomedical devices where adaptable trajectories improve functionality and durability.</p>

<p dir="ltr">At airports, aircraft taxi time may have effect on congestion, engine pollutants, and aircraft fuel consumption. An End-Around Taxiway (EAT) improves airport runway efficiencies and safety by providing a path for aircraft to move from one side of the runway to the other side without crossing that runway (FAA, 2022). The EAT has been implemented in four airports in the U.S.: Dallas/Fort Worth International Airport (KDFW), Hartsfield-Jackson International Airport (KATL), Detroit Metro Airport (KDTW), and Miami International Airport (KMIA) (Le, 2014). Currently, all the EATs are implemented at parallel runways. Previous research have shown that EAT on parallel runways has the potential to improve airport capacity and reduce fuel consumption (Fala et al., 2014; Feng & Johnson, 2021). There was no published application or research found about implementing EAT on crossing runways. This research is an explanatory study that focuses on analyzing the effect of EATs on airports with crossing runways. This research uses dynamic discrete event stochastic simulation software to build simulation models to analyze the effects of implementing EAT at crossing runways. Using a fictional airport loosely based on existing commercial service airports, the effect of EATs on a crossing runway airport was studied. The research has three experiments to measure the effects of the EAT in terms of taxi-in time, taxi-out time, and number of operations completed.</p><p dir="ltr">The major findings of the research are: 1) using EAT for taxi-in operations significantly reduces the taxi-in time and taxi-out time at the fictional airport with crossing runways; 2) using EAT for taxi-out operation significantly increases taxi-in time at the fictional airport with crossing runways; 3) using EAT for taxi-out operations significantly reduces taxi-out times at the fictional airport with crossing runways; 4) there is no statistical significance found when implementing EAT at the fictional airport with crossing runways in terms of number of operations completed per day. The configuration of the airport, the number of operations, the weather, and other factors may affect the transfer of these results to other airports with crossing runways.</p><p dir="ltr">Current EATs are only implemented and proposed at parallel runway airports. As aviation demand grows, this research may provide insights about a novel usage and operation strategy of EATs. The simulation model in this research is subject to assumptions and limitations. Future research is needed to improve the simulation model and further explore the effect of EATs on crossing runways.</p>

生態都市以永續概念為基礎，強調自我調節與最小能源消耗，使人類與動植物能與自然環境永遠共存。過去於都市計畫領域中，土地使用分區管制工具及都市設計元素，對於生態都市環境之影響似乎尚未完全釐清。此外從環境使用者（包含人類與動植物）面向探討生態都市規劃時，不同環境使用者取向為主之綠色空間規劃相異，又各種綠色空間規劃之適用標的為何過去鮮少提及。為釐清上述研究缺口，本研究之研究目的為建立不同生態都市使用者之生態都市規劃原則，並判別促進生態都市的重要土地使用工具與設計元素，以提供生態都市規劃上之政策建議。 在研究方法方面，首先以ArcGIS建立一模擬都市，並設計出各種規劃元素及其變化情境；接著在模擬都市中模擬所有情境之市綠色空間配置；最後計算個情境之生態指標，並運用彈性系數分析各規劃元素改變對於生態都市改善程度差異。研究結果認為若都市已高度開發、無殘存原始棲地時，規劃應偏向提供人類良好足夠之綠色空間、提升植物生長空間，已達到降低汙染並提升環境品質之生態目標；若生態都市內具部分原始棲地時，綠色空間規劃則可增加綠色網路品質，以提供動物更具生態性之環境。又在所有土地使用工具與設計元素中，縮減式退縮、偏低的建蔽率、鄰棟距離容積向上移轉、前後院距離容積向上移轉為較佳之規劃元素；高度比、街角退縮等元素整體表現普通；此外ㄨ字型建物及十字型建物之退縮對於環境改善程度最大。 / Eco-city is based on the concept of sustainability, emphasizing self-regulation and of energy consumption minimization. In urban planning, the relationship of zoning and urban design elements with eco-city built environment is not totally clarified. Besides, the planning strategy of green space will be different because of different participators living in the city. The city includes people (which can be divided into residents and pedestrians), animals and plants. It’s rarely discussed how green space strategies apply to different types of city in the past. To clarify them, two purposes on this study are established. One is to set up eco-city planning principles which designed for different environment users. The other is to find out good land use tools and urban design elements which can make built environment more ecological. The research methods of this study can be done by the following ways . First, use ArcGIS to establish a simulated urban environment. Secondly, integrate all land use tools and design elements as input, and then simulate each input’s green space configuration. Finally, calculate eco-city index and then analyze with elasticity to evaluate the efficiency of land use tools and design elements for improving environmental quality. The result of study suggests that, if highly developed city lacks habitats, the planning strategy should emphasize on offering sufficient and high quality of greenspace in order to satisfy residents’ leisure needs and plants’ growth spaces. By this way, the goal of pollution-reducing and environment-quality-improving could be reached. If the habitat exists in the city, planning strategy should tend to increase the quality of green network system in order to provide a more ecological environment for animals. Simultaneously, the study finding that among all the inputs, SBU, lower BCR, SDU, and RDU are better for eco-city planning. Besides, HDB, HDR, and HDFAR perform ordinarily. Moreover, TP7 is the most efficient input for improving environment quality, followed by TP6.