A reactive soil moisture sensor network: Design and field evaluation

Wireless sensor network technology has the potential to reveal finegrained, dynamic changes in monitored variables of an outdoor landscape. But there are significant problems to be overcome in order to realize this vision in working systems. This paper describes the design and implementation of a reactive, event driven network for environmental monitoring of soil moisture and evaluates its effectiveness. A novel feature of our solution is its reactivity to the environment: when rain falls and soil moisture is changing rapidly, measurements are collected frequently, whereas during dry periods, between rainfall, measurements are collected less often. Field trials demonstrating the reactivity, robustness, and longevity of the network are presented and evaluated, and future improvements proposed

A test generation framework for quiescent real-time systems

We present an extension of Tretmans theory and algorithm for test generation for input-output transition systems to real-time systems. Our treatment is based on an operational interpretation of the notion of quiescence in the context of real-time behaviour. This gives rise to a family of implementation relations parameterized by observation durations for quiescence. We define a nondeterministic (parameterized) test generation algorithm that generates test cases that are sound with respect to the corresponding implementation relation. Also, the test generation is exhaustive in the sense that for each non-conforming implementation a test case can be generated that detects the non-conformance

Managing plagiarism in programming assignments with blended assessment and randomisation.

Plagiarism is a common concern for coursework in many situations, particularly where electronic solutions can be provided e.g. computer programs, and leads to unreliability of assessment. Written exams are often used to try to deal with this, and to increase reliability, but at the expense of validity. One solution, outlined in this paper, is to randomise the work that is set for students so that it is very unlikely that any two students will be working on exactly the same problem set. This also helps to address the issue of students trying to outsource their work by paying external people to complete their assignments for them. We examine the effectiveness of this approach and others (including blended assessment) by analysing the spread of similarity scores across four different introductory programming assignments to find the natural similarity i.e. the level of similarity that could reasonably occur without plagiarism. The results of the study indicate that divergent assessment (having more than one possible solution) as opposed to convergent assessment (only one solution) is the dominant factor in natural similarity. A key area for further work is to apply the analysis to a larger sample of programming assignments to better understand the impact of different features of the assignment design on natural similarity and hence the detection of plagiarism

Testing real-time systems using TINA

The paper presents a technique for model-based black-box conformance testing of real-time systems using the Time Petri Net Analyzer TINA. Such test suites are derived from a prioritized time Petri net composed of two concurrent sub-nets specifying respectively the expected behaviour of the system under test and its environment.We describe how the toolbox TINA has been extended to support automatic generation of time-optimal test suites. The result is optimal in the sense that the set of test cases in the test suite have the shortest possible accumulated time to be executed. Input/output conformance serves as the notion of implementation correctness, essentially timed trace inclusion taking environment assumptions into account. Test cases selection is based either on using manually formulated test purposes or automatically from various coverage criteria specifying structural criteria of the model to be fulfilled by the test suite. We discuss how test purposes and coverage criterion are specified in the linear temporal logic SE-LTL, derive test sequences, and assign verdicts

Testing timed systems modeled by stream X-machines

Stream X-machines have been used to specify real systems where complex data structures. They are a variety of extended finite state machine where a shared memory is used to represent communications between the components of systems. In this paper we introduce an extension of the Stream X-machines formalism in order to specify systems that present temporal requirements. We add time in two different ways. First, we consider that (output) actions take time to be performed. Second, our formalism allows to specify timeouts. Timeouts represent the time a system can wait for the environment to react without changing its internal state. Since timeous affect the set of available actions of the system, a relation focusing on the functional behavior of systems, that is, the actions that they can perform, must explicitly take into account the possible timeouts. In this paper we also propose a formal testing methodology allowing to systematically test a system with respect to a specification. Finally, we introduce a test derivation algorithm. Given a specification, the derived test suite is sound and complete, that is, a system under test successfully passes the test suite if and only if this system conforms to the specification

Guidelines for the use of flow cytometry and cell sorting in immunological studies (second edition)

These guidelines are a consensus work of a considerable number of members of the immunology and flow cytometry community. They provide the theory and key practical aspects of flow cytometry enabling immunologists to avoid the common errors that often undermine immunological data. Notably, there are comprehensive sections of all major immune cell types with helpful Tables detailing phenotypes in murine and human cells. The latest flow cytometry techniques and applications are also described, featuring examples of the data that can be generated and, importantly, how the data can be analysed. Furthermore, there are sections detailing tips, tricks and pitfalls to avoid, all written and peer-reviewed by leading experts in the field, making this an essential research companion

An interactive web-based toolset for knowledge discovery from short text log data

© Springer International Publishing AG 2017. Many companies maintain human-written logs to capture data on events such as workplace incidents and equipment failures. However, the sheer volume and unstructured nature of this data prevent it from being utilised for knowledge acquisition. Our web-based prototype software system provides a cohesive computational methodology for analysing and visualising log data that requires minimal human involvement. It features an interface to support customisable, modularised log data processing and knowledge discovery. This enables owners of event-based datasets containing short textual descriptions, such as occupational health & safety officers and machine operators, to identify latent knowledge not previously acquirable without significant time and effort. The software system comprises five distinct stages, corresponding to standard data mining milestones: exploratory analysis, data warehousing, association rule mining, entity clustering, and predictive analysis. To the best of our knowledge, it is the first dedicated system to computationally analyse short text log data and provides a powerful interface that visualises the analytical results and supports human interaction

Designing sensor networks for leak detection in water pipeline systems

Undetected leaks in water distribution networks are a significant problem both economically and environmentally. Across Australia 12% of water is estimated to be lost through leaks and the annual cost to water utilities worldwide is US$14 billion. A sensor network that measures water flow in the pipes can be used to predict the location and size of leaks. Recent advances in sensor technology and lower costs mean that large scale sensor networks may soon be an economic choice for solving the leak detection problem. This paper presents a sensor network design method that generates human-readable rules for leak detection. Additionally, for a given network and range of operating scenarios, it discovers the best locations for flow sensors. The method is demonstrated to make acceptably accurate predictions under real-world conditions of uncertain measurements. It also allows trade-offs to be made between minimising the costs of installing and maintaining sensors and maximising prediction accuracy. For example, in some cases sufficiently accurate predictions can be made using sensors on only half the pipes.Rachel Cardell-Oliver, Verity Scott, Tom Chapman, Jon Morgan, Angus Simpso