Coordination and control in project-based work: digital objects and infrastructures for delivery

A major infrastructure project is used to investigate the role of digital objects in the coordination of engineering design work. From a practice-based perspective, research emphasizes objects as important in enabling cooperative knowledge work and knowledge sharing. The term ‘boundary object’ has become used in the analysis of mutual and reciprocal knowledge sharing around physical and digital objects. The aim is to extend this work by analysing the introduction of an extranet into the public–private partnership project used to construct a new motorway. Multiple categories of digital objects are mobilized in coordination across heterogeneous, cross-organizational groups. The main findings are that digital objects provide mechanisms for accountability and control, as well as for mutual and reciprocal knowledge sharing; and that different types of objects are nested, forming a digital infrastructure for project delivery. Reconceptualizing boundary objects as a digital infrastructure for delivery has practical implications for management practices on large projects and for the use of digital tools, such as building information models, in construction. It provides a starting point for future research into the changing nature of digitally enabled coordination in project-based work

Advancing Healthcare Security: A Cutting-Edge Zero-Trust Blockchain Solution for Protecting Electronic Health Records

The effective management of electronic health records (EHRs) is vital in healthcare. However, traditional systems often need help handling data inconsistently, providing limited access, and coordinating poorly across facilities. This study aims to tackle these issues using blockchain technology to improve EHR systems' data security, privacy, and interoperability. By thoroughly analyzing blockchain's applications in healthcare, we propose an innovative solution that leverages blockchain's decentralized and immutable nature, combined with advanced encryption techniques such as the Advanced Encryption Standard and Zero Knowledge Proof Protocol, to fortify EHR systems. Our research demonstrates that blockchain can effectively overcome significant EHR challenges, including fragmented data and interoperability problems, by facilitating secure and transparent data exchange, leading to enhanced coordination, care quality, and cost-efficiency across healthcare facilities. This study offers practical guidelines for implementing blockchain technology in healthcare, emphasizing a balanced approach to interoperability, privacy, and security. It represents a significant advancement over traditional EHR systems, boosting security and affording patients greater control over their health records. Doi: 10.28991/HIJ-2023-04-03-012 Full Text: PD

Runtime Enforcement of Hyperproperties

An enforcement mechanism monitors a reactive system for undesired behavior at runtime and corrects the system’s output in case it violates the given specification. In this paper, we study the enforcement problem for hyperproperties, i.e., properties that relate multiple computation traces to each other. We elaborate the notion of sound and transparent enforcement mechanisms for hyperproperties in two trace input models: 1) the parallel trace input model, where the number of traces is known a-priori and all traces are produced and processed in parallel and 2) the sequential trace input model, where traces are processed sequentially and no a-priori bound on the number of traces is known. For both models, we study enforcement algorithms for specifications given as formulas in universally quantified HyperLTL, a temporal logic for hyperproperties. For the parallel model, we describe an enforcement mechanism based on parity games. For the sequential model, we show that enforcement is in general undecidable and present algorithms for reasonable simplifications of the problem (partial guarantees or the restriction to safety properties). Furthermore, we report on experimental results of our prototype implementation for the parallel model

A study of image quality for radar image processing

Methods developed for image quality metrics are reviewed with focus on basic interpretation or recognition elements including: tone or color; shape; pattern; size; shadow; texture; site; association or context; and resolution. Seven metrics are believed to show promise as a way of characterizing the quality of an image: (1) the dynamic range of intensities in the displayed image; (2) the system signal-to-noise ratio; (3) the system spatial bandwidth or bandpass; (4) the system resolution or acutance; (5) the normalized-mean-square-error as a measure of geometric fidelity; (6) the perceptual mean square error; and (7) the radar threshold quality factor. Selective levels of degradation are being applied to simulated synthetic radar images to test the validity of these metrics