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Mark Fox

Publications and source records attributed to Mark Fox.

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Housing Potential Common Data Model and City Digital Twin

The evaluation of housing potential requires consideration of a location from multiple perspectives, ranging from zoning and land use to population characteristics and access to services. This research introduces the Housing Potential Common Data Model (HPCDM) to overcome existing data silos, serving as a standard to support integration and interoperability across the diverse range of datasets that are required for housing potential analysis. This report details the evaluation of the model along with the creation of a City Digital Twin for housing and a pilot dashboard application to demonstrate a practical implementation. Beyond the technical framework, this work identifies critical barriers to adoption and provides actionable mitigation strategies for urban planners and stakeholders.

cs.AI

33 Gbit/s source-device-independent quantum random number generator based on heterodyne detection with real-time FPGA-integrated extraction

We present a high-speed continuous-variable quantum random number generator (QRNG) based on heterodyne detection of vacuum fluctuations. The scheme follows a source-device-independent (SDI) security model in which the entropy originates from quantum measurement uncertainty and no model of the source is required; security depends only on the trusted measurement device and the calibrated discretization, and thus remains valid even under adversarial state preparation. The optical field is split by a 90$^\circ$ optical hybrid and measured by two balanced photodiodes to obtain both quadratures of the vacuum state simultaneously. The analog outputs are digitized using a dual-channel 12-bit analog-to-digital converter operating at a sampling rate of 3.2 GS/s per channel, and processed in real time by an FPGA implementing Toeplitz hashing for randomness extraction. The quantum-to-classical noise ratio was verified through calibrated power spectral density measurements and cross-checked in the time domain, confirming vacuum-noise dominance within the 1.6 GHz detection bandwidth. After extraction, the system achieves a sustained generation rate of $R_{\rm net}= 33.92~\mathrm{Gbit/s}$ of uniformly distributed random bits, which pass all NIST and Dieharder statistical tests. The demonstrated platform provides a compact, FPGA-based realization of a practical heterodyne continuous-variable source-independent QRNG suitable for high-rate quantum communication and secure key distribution systems.

quant-ph

Semantic Computing for Organizational Effectiveness: From Organization Theory to Practice through Semantics-Based Modelling

A critical function of an organization is to foster the level of integration (coordination and cooperation) necessary to achieve its objectives. The need to coordinate and motivation to cooperate emerges from the myriad dependencies between an organization's members and their work. Therefore, to reason about solutions to coordination and cooperation problems requires a robust representation that includes the underlying dependencies. We find that such a representation remains missing from formal organizational models, and we leverage semantics to bridge this gap. Drawing on well-established organizational research and our extensive fieldwork with one of North America's largest municipalities, (1) we introduce an ontology, formalized in first-order logic, that operationalizes concepts like outcome, reward, and epistemic dependence, and their links to potential integration risks; and (2) present real-world applications of this ontology to analyze and support integration in complex government infrastructure projects. Our ontology is implemented and validated in both Z3 and OWL. Key features of our model include inferable dependencies, explainable coordination and cooperation risks, and actionable insights on how dependency structures within an organization can be altered to mitigate the risks. Conceptualizing real-world challenges like incentive misalignment, free-riding, and subgoal optimization in terms of dependency structures, our semantics-based approach represents a novel method for modelling and enhancing coordination and cooperation. Integrated within a decision-support system, our model may serve as an impactful aid for organizational design and effectiveness. More broadly, our approach underscores the transformative potential of semantics in deriving tangible, real-world value from existing organization theory.

cs.AI