http://hdl.handle.net/10453/35199 2026-06-26T10:03:53Z http://hdl.handle.net/10453/195458 Title: Spatial Association between Near-Misses and Accident Blackspots in Sydney, Australia: A Getis-Ord Gi∗Analysis Authors: Grigorev, A; Lillo-Trynes, D; Mihǎiţǎ, AS Abstract: Conventional road safety management is inherently reactive, relying on analysis of sparse and lagged historical crash data to identify hazardous locations, or crash blackspots. The proliferation of vehicle telematics presents an opportunity for a paradigm shift towards proactive safety, using highfrequency, high-resolution near-miss data as a leading indicator of crash risk. This paper presents a spatial-statistical framework to systematically analyze the concordance and discordance between official crash records and near-miss events within urban environment. A Getis-Ord statistic is first applied to both reported crashes and near-miss events to identify statistically significant local clusters of each type. Subsequently, Bivariate Local Moran's I assesses spatial relationships between crash counts and High-G event counts, classifying grid cells into distinct profiles: High-High (coincident risk), High-Low and Low-High. Our analysis reveals significant amount of LowCrash, High-Near-Miss clusters representing high-risk areas that remain unobservable when relying solely on historical crash data. Feature importance analysis is performed using contextual Point of Interest data to identify the different infrastructure factors that characterize difference between spatial clusters. The results provide a data-driven methodology for transport authorities to transition from a reactive to a proactive safety management strategy, allowing targeted interventions before severe crashes occur. 2025-01-01T00:00:00Z http://hdl.handle.net/10453/195432 Title: On the Quantum Time Complexity of Divide and Conquer Authors: Allcock, J; Bao, J; Belovs, A; Lee, T; Santha, M Abstract: In this work, we initiate a systematic study of the time complexity of quantum divide and conquer (QD&C) algorithms for classical problems, and propose a general framework for their analysis. We establish generic conditions under which search and minimization problems with classical divide and conquer algorithms are amenable to quantum speedup, and apply these theorems to various problems involving strings, integers, and geometric objects. These include Longest Distinct Substring, Klee’s Coverage, several optimization problems on stock transactions, and k-Increasing Subsequence. For most of these problems our quantum time upper bounds match the quantum query lower bounds, up to polylogarithmic factors. We give a structured framework for describing and classifying a wide variety of QD&C algorithms so that quantum speedups can be more easily identified and applied, and prove general statements on QD&C time complexity covering a range of cases, accounting for the time required for all operations. In particular, we explicitly account for memory access operations in the commonly used QRAM (read-only) and QRAG (read-write) models, which are assumed to take unit time in the query model, and which require careful analysis when involved in recursion. Our generic QD&C theorems have several nice features. 1. To apply them, it suffices to come up with a classical divide and conquer algorithm satisfying the conditions of the theorem. The quantization of the algorithm is then completely handled by the theorem. This can make it easier to find applications which admit a quantum speedup, and contrast with dynamic programming algorithms which can be difficult to quantize due to their highly sequential nature. 2. As these theorems give bounds on time complexity, they can be applied to a greater range of problems than those based on query complexity, e.g., where the best-known quantum algorithms require super-linear time. 3. It can handle minimization problems as well as boolean functions, which allows us to improve on the query complexity result of Childs et al. [13] for k-Increasing Subsequence by a logarithmic factor. 2025-06-30T00:00:00Z http://hdl.handle.net/10453/195416 Title: Environmental and economic impact assessment of single-use laboratory plastic waste: A case study Authors: Tan, YH; Ong, HC; Raja Ali, RA; Gew, LT Abstract: Research labs rely on disposable plastics for sterility, safety, and affordability, but their environmental and economic impact has been largely overlooked. While the impact of single-use plastics is well-known, laboratory waste poses an additional challenge due to necessary treatment processes. Hence, this study investigated both the environmental and economic impact associated with single-use plastic waste management in a university laboratory, serving as a case study for Southeast Asia. A retrospective analysis was conducted on laboratory plastic waste management between 2014 and 2023 at a Malaysian university. Three waste management methods, i.e. incineration, landfilling with microwave pre-treatment, and landfilling with ozone pre-treatment, were implemented at consecutive intervals. Environmental impact was assessed by quantifying the GHG emissions in terms of carbon dioxide equivalent (CO₂eq) emissions, while economic assessment was evaluated based on invoiced costs. A total of 29,180.11 kg of single-use plastic waste resulted in 46,420.08 kg CO₂eq emissions and a cumulative disposal cost of RM 84,890.49. Among the three methods, landfilling with ozone pre-treatment demonstrated the lowest environmental impact (1.55 kg CO₂eq/kg) and cost (RM 2.79/kg). Direct emission from the end-of-life stage was the main source of GHG emissions, while disposal fees represented the largest portion of total costs. In light of these findings, it is crucial for universities and research institutions to recognise the environmental and economic impact of laboratory single-use plastics. This case study will serve as a foundation for advancing pre-treatment technologies and future end-of-life solutions. 2025-12-01T00:00:00Z http://hdl.handle.net/10453/195403 Title: An Overview of Principles, Enablers, Metrics and Emerging Technologies for Resilient Networks Authors: Chemalamarri, VD; Abdollahi, M; Bryant, A; Abolhasan, M; Owen, R Abstract: There are approximately 5.78 billion users relying on mobile networks to access a wide range of digital services. Hence, the resilience of these communication networks is of the highest importance. In this paper, we define network resilience and outline key architectural design principles and their enabling technologies. We further describe relevant metrics for assessing network performance and examine emerging technologies, such as the integration of terrestrial and non-terrestrial networks, artificial intelligence-enabled network management and optimization, as well as innovative concepts like core network disaggregation and non-IP-based architectures. We identify current challenges and highlight critical research directions for the advancement of resilient mobile networks. 2026-01-01T00:00:00Z