The OpenPMU Platform for Open Source Phasor Measurements

OpenPMU is an open platform for the development of phasor measurement unit (PMU) technology. A need has been identified for an open-source alternative to commercial PMU devices tailored to the needs of the university researcher and for enabling the development of new synchrophasor instruments from this foundation. OpenPMU achieves this through open-source hardware design specifications and software source code, allowing duplicates of the OpenPMU to be fabricated under open-source licenses. This paper presents the OpenPMU device based on the Labview development environment. The device is performance tested according to the IEEE C37.118.1 standard. Compatibility with the IEEE C37.118.2 messaging format is achieved through middleware which is readily adaptable to other PMU projects or applications. Improvements have been made to the original design to increase its flexibility. A new modularized architecture for the OpenPMU is presented using an open messaging format which the authors propose is adopted as a platform for PMU research.

Open Source Telecommunications Framework for Time-Series Data from Smart Grid Sensors.

This paper presents a framework for a telecommunications interface which allows data from sensors embedded in Smart Grid applications to reliably archive data in an appropriate time-series database. The challenge in doing so is two-fold, firstly the various formats in which sensor data is represented, secondly the problems of telecoms reliability. A prototype of the authors' framework is detailed which showcases the main features of the framework in a case study featuring Phasor Measurement Units (PMU) as the application. Useful analysis of PMU data is achieved whenever data from multiple locations can be compared on a common time axis. The prototype developed highlights its reliability, extensibility and adoptability; features which are largely deferred from industry standards for data representation to proprietary database solutions. The open source framework presented provides link reliability for any type of Smart Grid sensor and is interoperable with existing proprietary database systems, and open database systems. The features of the authors' framework allow for researchers and developers to focus on the core of their real-time or historical analysis applications, rather than having to spend time interfacing with complex protocols.

cudaMap: a GPU accelerated program for gene expression connectivity mapping

Background: Modern cancer research often involves large datasets and the use of sophisticated statistical techniques. Together these add a heavy computational load to the analysis, which is often coupled with issues surrounding data accessibility. Connectivity mapping is an advanced bioinformatic and computational technique dedicated to therapeutics discovery and drug re-purposing around differential gene expression analysis. On a normal desktop PC, it is common for the connectivity mapping task with a single gene signature to take >2h to complete using sscMap, a popular Java application that runs on standard CPUs (Central Processing Units). Here, we describe new software, cudaMap, which has been implemented using CUDA C/C++ to harness the computational power of NVIDIA GPUs (Graphics Processing Units) to greatly reduce processing times for connectivity mapping.

Results: cudaMap can identify candidate therapeutics from the same signature in just over thirty seconds when using an NVIDIA Tesla C2050 GPU. Results from the analysis of multiple gene signatures, which would previously have taken several days, can now be obtained in as little as 10 minutes, greatly facilitating candidate therapeutics discovery with high throughput. We are able to demonstrate dramatic speed differentials between GPU assisted performance and CPU executions as the computational load increases for high accuracy evaluation of statistical significance.

Conclusion: Emerging 'omics' technologies are constantly increasing the volume of data and information to be processed in all areas of biomedical research. Embracing the multicore functionality of GPUs represents a major avenue of local accelerated computing. cudaMap will make a strong contribution in the discovery of candidate therapeutics by enabling speedy execution of heavy duty connectivity mapping tasks, which are increasingly required in modern cancer research. cudaMap is open source and can be freely downloaded from http://purl.oclc.org/NET/cudaMap.

PLUMED 2: New feathers for an old bird

Enhancing sampling and analyzing simulations are central issues in molecular simulation. Recently, we introduced PLUMED, an open-source plug-in that provides some of the most popular molecular dynamics (MD) codes with implementations of a variety of different enhanced sampling algorithms and collective variables (CVs). The rapid changes in this field, in particular new directions in enhanced sampling and dimensionality reduction together with new hardware, require a code that is more flexible and more efficient. We therefore present PLUMED 2 here a,complete rewrite of the code in an object-oriented programming language (C++). This new version introduces greater flexibility and greater modularity, which both extends its core capabilities and makes it far easier to add new methods and CVs. It also has a simpler interface with the MD engines and provides a single software library containing both tools and core facilities. Ultimately, the new code better serves the ever-growing community of users and contributors in coping with the new challenges arising in the field.

Program summary

Program title: PLUMED 2

Catalogue identifier: AEEE_v2_0

Program summary URL: http://cpc.cs.qub.ac.uk/summaries/AEEE_v2_0.html

Program obtainable from: CPC Program Library, Queen's University, Belfast, N. Ireland

Licensing provisions: Yes

No. of lines in distributed program, including test data, etc.: 700646

No. of bytes in distributed program, including test data, etc.: 6618136

Distribution format: tar.gz

Programming language: ANSI-C++.

Computer: Any computer capable of running an executable produced by a C++ compiler.

Operating system: Linux operating system, Unix OSs.

Has the code been vectorized or parallelized?: Yes, parallelized using MPI.

RAM: Depends on the number of atoms, the method chosen and the collective variables used.

Classification: 3, 7.7, 23. Catalogue identifier of previous version: AEEE_v1_0.

Journal reference of previous version: Comput. Phys. Comm. 180 (2009) 1961.

External routines: GNU libmatheval, Lapack, Bias, MPI. (C) 2013 Elsevier B.V. All rights reserved.

Automated detection and measurement of isolated retinal arterioles by a combination of edge enhancement and cost analysis

Pressure myography studies have played a crucial role in our understanding of vascular physiology and pathophysiology. Such studies depend upon the reliable measurement of changes in the diameter of isolated vessel segments over time. Although several software packages are available to carry out such measurements on small arteries and veins, no such software exists to study smaller vessels (<50 µm in diameter). We provide here a new, freely available open-source algorithm, MyoTracker, to measure and track changes in the diameter of small isolated retinal arterioles. The program has been developed as an ImageJ plug-in and uses a combination of cost analysis and edge enhancement to detect the vessel walls. In tests performed on a dataset of 102 images, automatic measurements were found to be comparable to those of manual ones. The program was also able to track both fast and slow constrictions and dilations during intraluminal pressure changes and following application of several drugs. Variability in automated measurements during analysis of videos and processing times were also investigated and are reported. MyoTracker is a new software to assist during pressure myography experiments on small isolated retinal arterioles. It provides fast and accurate measurements with low levels of noise and works with both individual images and videos. Although the program was developed to work with small arterioles, it is also capable of tracking the walls of other types of microvessels, including venules and capillaries. It also works well with larger arteries, and therefore may provide an alternative to other packages developed for larger vessels when its features are considered advantageous.

Design and deployment of secure, robust, and resilient SDN Controllers

The scale of the Software-Defined Network (SDN) Controller design problem has become apparent with the expansion of SDN deployments. Initial SDN deployments were small-scale, single controller environments for research and usecase testing. Today, enterprise deployments requiring multiple controllers are gathering momentum e.g. Google’s backbone network, Microsoft’s public cloud, and NTT’s edge gateway. Third-party applications are also becoming available e.g. HP SDN App Store. The increase in components and interfaces for the evolved SDN implementation increases the security challenges of the SDN controller design. In this work, the requirements of a secure, robust, and resilient SDN controller are identified, stateof-the-art open-source SDN controllers are analyzed with respect to the security of their design, and recommendations for security improvements are provided. This contribution highlights the gap between the potential security solutions for SDN controllers and the actual security level of current controller designs.

Machine learning classification of surgical pathology reports and chunk recognition for information extraction noise reduction

Background and aims: Machine learning techniques for the text mining of cancer-related clinical documents have not been sufficiently explored. Here some techniques are presented for the pre-processing of free-text breast cancer pathology reports, with the aim of facilitating the extraction of information relevant to cancer staging.

Materials and methods: The first technique was implemented using the freely available software RapidMiner to classify the reports according to their general layout: ‘semi-structured’ and ‘unstructured’. The second technique was developed using the open source language engineering framework GATE and aimed at the prediction of chunks of the report text containing information pertaining to the cancer morphology, the tumour size, its hormone receptor status and the number of positive nodes. The classifiers were trained and tested respectively on sets of 635 and 163 manually classified or annotated reports, from the Northern Ireland Cancer Registry.

Results: The best result of 99.4% accuracy – which included only one semi-structured report predicted as unstructured – was produced by the layout classifier with the k nearest algorithm, using the binary term occurrence word vector type with stopword filter and pruning. For chunk recognition, the best results were found using the PAUM algorithm with the same parameters for all cases, except for the prediction of chunks containing cancer morphology. For semi-structured reports the performance ranged from 0.97 to 0.94 and from 0.92 to 0.83 in precision and recall, while for unstructured reports performance ranged from 0.91 to 0.64 and from 0.68 to 0.41 in precision and recall. Poor results were found when the classifier was trained on semi-structured reports but tested on unstructured.

Conclusions: These results show that it is possible and beneficial to predict the layout of reports and that the accuracy of prediction of which segments of a report may contain certain information is sensitive to the report layout and the type of information sought.

Is the General Public Licence a Rational Choice?

Open source projects are networks of developers, distributors and end-users of non-proprietary created knowledge goods. It has been argued that this form of organization has some advantages over the firm or market coordination. I show that for sufficiently convex and modular projects proprietary licences are not able to sustain sequential knowledge production which, however, can be carried out if the project is run on the open source basis.

Density Matrix Renormalization Group for Dummies

We describe the Density Matrix Renormalization Group algorithms for time dependent and time independent Hamiltonians. This paper is a brief but comprehensive introduction to the subject for anyone willing to enter in the field or write the program source code from scratch. An open source version of the code can be found at: http://www.dmrg.it.

Phenomenology and system engineering of micro- and nano-antenna FPA sensors for detection of concealed weapons and improvised explosive devices

The ability of millimetre wave and terahertz systems to penetrate clothing is well known. The fact that the transmission of clothing and the reflectivity of the body vary as a function of frequency is less so. Several instruments have now been developed to exploit this capability. The choice of operating frequency, however, has often been associated with the maturity and the cost of the enabling technology rather than a sound systems engineering approach. Top level user and systems requirements have been derived to inform the development of design concepts. Emerging micro and nano technology concepts have been reviewed and we have demonstrated how these can be evaluated against these requirements by simulation using OpenFx. Openfx is an open source suite of 3D tools for modeling, animation and visualization which has been modified for use at millimeter waves. © 2012 SPIE.