Self-driven lattice-model Monte Carlo simulations of alloy thermodynamic

Monte Carlo (MC) simulations of lattice models are a widely used way to compute thermodynamic properties of substitutional alloys. A limitation to their more widespread use is the difficulty of driving a MC simulation in order to obtain the desired quantities. To address this problem, we have devised a variety of high-level algorithms that serve as an interface between the user and a traditional MC code. The user specifies the goals sought in a high-level form that our algorithms convert into elementary tasks to be performed by a standard MC code. For instance, our algorithms permit the determination of the free energy of an alloy phase over its entire region of stability within a specified accuracy, without requiring any user intervention during the calculations. Our algorithms also enable the direct determination of composition-temperature phase boundaries without requiring the calculation of the whole free energy surface of the alloy system

Use of nonintrusive sensor-based information and communication technology for real-world evidence for clinical trials in dementia

Cognitive function is an important end point of treatments in dementia clinical trials. Measuring cognitive function by standardized tests, however, is biased toward highly constrained environments (such as hospitals) in selected samples. Patient-powered real-world evidence using information and communication technology devices, including environmental and wearable sensors, may help to overcome these limitations. This position paper describes current and novel information and communication technology devices and algorithms to monitor behavior and function in people with prodromal and manifest stages of dementia continuously, and discusses clinical, technological, ethical, regulatory, and user-centered requirements for collecting real-world evidence in future randomized controlled trials. Challenges of data safety, quality, and privacy and regulatory requirements need to be addressed by future smart sensor technologies. When these requirements are satisfied, these technologies will provide access to truly user relevant outcomes and broader cohorts of participants than currently sampled in clinical trials

Building a Socio-technical Perspective of Community Resilience with a Semiotic Approach

Situated in the diversity and adversity of real-life contexts facing crisis situations, this research aims at boosting the resilience process within communities supported by digital and social technology. In this paper, eight community leaders in different parts of the world are invited to express their issues and wishes regarding the support of technology to face social challenges. Methods and artefacts based on the Organisational Semiotics (OS) and the Socially-Aware computing have been applied to analyse and consolidate this data. By providing both a systemic view of the problem and also leading to the identification of requirements, the analysis evidences some benefits of the OS-based approach to consolidate perspectives from different real-life scenarios towards building a socio-technical solution

JWalk: a tool for lazy, systematic testing of java classes by design introspection and user interaction

Popular software testing tools, such as JUnit, allow frequent retesting of modified code; yet the manually created test scripts are often seriously incomplete. A unit-testing tool called JWalk has therefore been developed to address the need for systematic unit testing within the context of agile methods. The tool operates directly on the compiled code for Java classes and uses a new lazy method for inducing the changing design of a class on the fly. This is achieved partly through introspection, using Java’s reflection capability, and partly through interaction with the user, constructing and saving test oracles on the fly. Predictive rules reduce the number of oracle values that must be confirmed by the tester. Without human intervention, JWalk performs bounded exhaustive exploration of the class’s method protocols and may be directed to explore the space of algebraic constructions, or the intended design state-space of the tested class. With some human interaction, JWalk performs up to the equivalent of fully automated state-based testing, from a specification that was acquired incrementally

An approach to safety analysis of clinical workflows

A clinical workflow considers the information and processes that are involved in providing a clinical service. They are safety critical since even minor faults have the potential to propagate and consequently cause harm to a patient, or even for a patient's life to be lost. Experiencing these kinds of failures has a destructive impact on all the involved parties. Due to the large number of processes and tasks included in the delivery of a clinical service, it can be difficult to determine the individuals or the processes that are responsible for adverse events, since such an analysis is typically complex and slow to do manually. Using automated tools to carry out an analysis can help in determining the root causes of potential adverse events and consequently help in avoiding preventable errors through either the alteration of existing workflows, or the design of a new workflow. This paper describes a technical approach to safety analysis of clinical workflows, utilising a safety analysis tool (Hierarchically-Performed Hazard Origin and Propagation Studies (HiP-HOPS)) that is already in use in the field of mechanical systems. The paper then demonstrates the applicability of the approach to clinical workflows by applying it to analyse the workflow in a radiology department. We conclude that the approach is applicable to this area of healthcare and provides a mechanism both for the systematic identification of adverse events and for the introduction of possible safeguards in clinical workflows

Detecting compact binary coalescences with seedless clustering

Compact binary coalescences are a promising source of gravitational waves for second-generation interferometric gravitational-wave detectors. Although matched filtering is the optimal search method for well-modeled systems, alternative detection strategies can be used to guard against theoretical errors (e.g., involving new physics and/or assumptions about spin/eccentricity) while providing a measure of redundancy. In previous work, we showed how "seedless clustering" can be used to detect long-lived gravitational-wave transients in both targeted and all-sky searches. In this paper, we apply seedless clustering to the problem of low-mass ($M_\text{total}\leq10M_\odot$) compact binary coalescences for both spinning and eccentric systems. We show that seedless clustering provides a robust and computationally efficient method for detecting low-mass compact binaries

Some Findings Concerning Requirements in Agile Methodologies

gile methods have appeared as an attractive alternative to conventional methodologies. These methods try to reduce the time to market and, indirectly, the cost of the product through flexible development and deep customer involvement. The processes related to requirements have been extensively studied in literature, in most cases in the frame of conventional methods. However, conclusions of conventional methodologies could not be necessarily valid for Agile; in some issues, conventional and Agile processes are radically different. As recent surveys report, inadequate project requirements is one of the most conflictive issues in agile approaches and better understanding about this is needed. This paper describes some findings concerning requirements activities in a project developed under an agile methodology. The project intended to evolve an existing product and, therefore, some background information was available. The major difficulties encountered were related to non-functional needs and management of requirements dependencies