Auditability is a key requirement for providing scalability and availability to distributed systems. Auditability allows us to identify latent concurrency bugs, dependencies among events, and performance bottlenecks. Our work focuses on providing auditability by combining two key concepts: time and causality. In particular, we prescribe hybrid logical clocks (HLC) which offer the functionality ...

Auditability is an important property in nancial systems and architectures Here we de ne the primitive of blind auditable mem bership proof BAMP which combines public auditability with privacy i e user anonymity In particular one can use it as an auditable alter native to a blind signature component in unconditionally anonymous payment systems and in other systems requiring anonymity We show th...

Presently, the process of extraction and dissemination of data subsets for research from clinical data warehouses is cumbersome and error prone. Furthermore, large-scale research projects often involve multiple users of the same data extract; each of these users may be authorized to access different data elements and specific subsets of the data extract. Once initial data extraction has been do...

Without adequate audit mechanisms, electronic health record (EHR) systems remain vulnerable to undetected misuse. Users could modify or delete protected health information without these actions being traceable. The objective of this paper is to assess electronic health record audit mechanisms to determine the current degree of auditing for non-repudiation and to assess whether general audit gui...

bearing capacity prediction of axially loaded piles is one of the most important problems in geotechnical engineering practices, with a wide variety range of methods which have been introduced to forecast it accurately. machine learning methods have been reported by many contemporary researches with some degree of success in modeling geotechnical phenomena. in this study, a fairly new machine l...

Businesses are increasingly interested in how big data, artificial intelligence, machine learning, and predictive analytics can be used to increase revenue, lower costs, and improve their business processes. In this paper, we describe how we have developed a data-driven machine learning method to optimize the collection process for a debt collection agency. Precisely speaking, we create a frame...