Big data: a normal accident waiting to happen?

Widespread commercial use of the internet has significantly increased the volume and scope of data being collected by organisations. ‘Big data’ has emerged as a term to encapsulate both the technical and commercial aspects of this growing data collection activity. To date, much of the discussion of big data has centred upon its transformational potential for innovation and efficiency, yet there has been less reflection on its wider implications beyond commercial value creation. This paper builds upon normal accident theory (NAT) to analyse the broader ethical implications of big data. It argues that the strategies behind big data require organisational systems that leave them vulnerable to normal accidents, that is to say some form of accident or disaster that is both unanticipated and inevitable. Whilst NAT has previously focused on the consequences of physical accidents, this paper suggests a new form of system accident that we label data accidents. These have distinct, less tangible and more complex characteristics and raise significant questions over the role of individual privacy in a ‘data society’. The paper concludes by considering the ways in which the risks of such data accidents might be managed or mitigated.

Big social data and political sentiment: the tweet stream during the UK General Election 2015 campaign

The General Election for the 56th United Kingdom Parliament was held on 7 May 2015. Tweets related to UK politics, not only those with the specific hashtag ”#GE2015”, have been collected in the period between March 1 and May 31, 2015. The resulting dataset contains over 28 million tweets for a total of 118 GB in uncompressed format or 15 GB in compressed format. This study describes the method that was used to collect the tweets and presents some analysis, including a political sentiment index, and outlines interesting research directions on Big Social Data based on Twitter microblogging.

Scalable and fault tolerant failure detection and consensus

Future extreme-scale high-performance computing systems will be required to work under frequent component failures. The MPI Forum's User Level Failure Mitigation proposal has introduced an operation, MPI_Comm_shrink, to synchronize the alive processes on the list of failed processes, so that applications can continue to execute even in the presence of failures by adopting algorithm-based fault tolerance techniques. This MPI_Comm_shrink operation requires a fault tolerant failure detection and consensus algorithm. This paper presents and compares two novel failure detection and consensus algorithms. The proposed algorithms are based on Gossip protocols and are inherently fault-tolerant and scalable. The proposed algorithms were implemented and tested using the Extreme-scale Simulator. The results show that in both algorithms the number of Gossip cycles to achieve global consensus scales logarithmically with system size. The second algorithm also shows better scalability in terms of memory and network bandwidth usage and a perfect synchronization in achieving global consensus.

An LDA and probability-based classifier for the diagnosis of Alzheimer's Disease from structural MRI

In this paper a custom classification algorithm based on linear discriminant analysis and probability-based weights is implemented and applied to the hippocampus measurements of structural magnetic resonance images from healthy subjects and Alzheimer’s Disease sufferers; and then attempts to diagnose them as accurately as possible. The classifier works by classifying each measurement of a hippocampal volume as healthy controlsized or Alzheimer’s Disease-sized, these new features are then weighted and used to classify the subject as a healthy control or suffering from Alzheimer’s Disease. The preliminary results obtained reach an accuracy of 85.8% and this is a similar accuracy to state-of-the-art methods such as a Naive Bayes classifier and a Support Vector Machine. An advantage of the method proposed in this paper over the aforementioned state of the art classifiers is the descriptive ability of the classifications it produces. The descriptive model can be of great help to aid a doctor in the diagnosis of Alzheimer’s Disease, or even further the understand of how Alzheimer’s Disease affects the hippocampus.

Connectivity recovery in epidemic membership protocols

Epidemic protocols are a bio-inspired communication and computation paradigm for extreme-scale network system based on randomized communication. The protocols rely on a membership service to build decentralized and random overlay topologies. In a weakly connected overlay topology, a naive mechanism of membership protocols can break the connectivity, thus impairing the accuracy of the application. This work investigates the factors in membership protocols that cause the loss of global connectivity and introduces the first topology connectivity recovery mechanism. The mechanism is integrated into the Expander Membership Protocol, which is then evaluated against other membership protocols. The analysis shows that the proposed connectivity recovery mechanism is effective in preserving topology connectivity and also helps to improve the application performance in terms of convergence speed.

A Genetic Algorithm for the selection of structural MRI features for classification of Mild Cognitive Impairment and Alzheimer's Disease

This work investigates the problem of feature selection in neuroimaging features from structural MRI brain images for the classification of subjects as healthy controls, suffering from Mild Cognitive Impairment or Alzheimer’s Disease. A Genetic Algorithm wrapper method for feature selection is adopted in conjunction with a Support Vector Machine classifier. In very large feature sets, feature selection is found to be redundant as the accuracy is often worsened when compared to an Support Vector Machine with no feature selection. However, when just the hippocampal subfields are used, feature selection shows a significant improvement of the classification accuracy. Three-class Support Vector Machines and two-class Support Vector Machines combined with weighted voting are also compared with the former and found more useful. The highest accuracy achieved at classifying the test data was 65.5% using a genetic algorithm for feature selection with a three-class Support Vector Machine classifier.

Towards expressive rule induction on IP network event streams

In order to gain insights into events and issues that may cause errors and outages in parts of IP networks, intelligent methods that capture and express causal relationships online (in real-time) are needed. Whereas generalised rule induction has been explored for non-streaming data applications, its application and adaptation on streaming data is mostly undeveloped or based on periodic and ad-hoc training with batch algorithms. Some association rule mining approaches for streaming data do exist, however, they can only express binary causal relationships. This paper presents the ongoing work on Online Generalised Rule Induction (OGRI) in order to create expressive and adaptive rule sets real-time that can be applied to a broad range of applications, including network telemetry data streams.

Enhanced Templating in the Crystallisation of Poly(E-caprolactone) Using 1,3:2,4-di(4-Chlorobenzylidene) Sorbitol

We show that small quantities of 1,3:2,4-di(4-chlorobenzylidene) sorbitol dispersed in poly(epsilon-caprolactone) provide a very effective self-assembling nanoscale framework which, with a flow field, yields extremely high levels of polymer crystal orientation. During modest shear flow of the polymer melt, the additive forms highly extended nano-particles which adopt a preferred alignment with respect to the flow field. On cooling, polymer crystallisation is directed by these particles. This chloro substituted dibenzylidene sorbitol is considerably more effective at directing the crystal growth of poly(epsilon-caprolactone) than the unsubstituted compound.

Dicopper(II) complexes of a new di-para-xylyldioxatetraazamacrocycle and cascade species with dicarboxylate anions: thermodynamics and structural properties

The new dioxatetraazamacrocycle (L-1) was synthesized by a 2 + 2 condensation and characterized. Stability constants of its copper(II) complexes were determined by spectrophotometry in DMSO at 298.2 K in 0. 10 mol dm(-3) KClO4. Mainly dinuclear complexes are formed and the presence of mononuclear species is dependent on the counterion (Cl- or ClO4-). The association constants of the dinuclear copper(II) complexes with dicarboxylate anions [oxalate (oxa(2-)), malonate (mal(2-)), succinate (suc(2-)), and glutarate (glu(2-))] were also determined by spectrophotometry at 298.2 K in DMSO, and it was found that values decrease with an increase of the alkyl chain between the carboxylate groups. X-Band EPR spectra of the dicopper(II) complexes and of their cascade species in frozen DMSO exhibit dipole-dipole coupling, and their simulation, together with their UV-vis spectra, showed that the copper centres of the complexes in solution had square pyramidal geometries though with different distortions. From the experimental data, it was also possible to predict the Cu...Cu distances, the minimum being found at 6.4 angstrom for the (Cu2LCl4)-Cl-1 complex and then successively this distance slightly increases when the chloride anions are replaced by dicarboxylate anions, from 6.6 angstrom for oxa(2-) to 7.8 for glu(2-). The crystal structures of the dinuclear copper cascade species with oxa(2-) and suc(2-) were determined and showed one anion bridging both copper centres and Cu...Cu distances of 5.485(7) angstrom and 6.442(8) angstrom, respectively.

Anion directed templated synthesis of mono- and di-Schiff base complexes of Ni(II)

Two sets of Schiff base ligands, set-1 and set-2 have been prepared by mixing the respective diamine (1,2-propanediamine or 1,3-propanediamine) and carbonyl compounds (2-acetylpyridine or pyridine-2-carboxaldehyde) in 1:1 and 1:2 ratios, respectively and employed for the synthesis of complexes with Ni(II) perchlorate and Ni(II) thiocyanate. Ni(II) perchlorate yields the complexes having general formula [NiL2](ClO4)(2) (L = L-1 [N-1-(1-pyridin-2-yl-ethylidine)-propane-1,3-diamine] for complex 1, L-2 [N-1-pyridine-2-ylmethylene-propane1,3-diamine] for complex 2 or L-3 [N-1-(1-pyridine-2-yl-ethylidine)-propane-1,2-diamine] for complex 3) in which the Schiff bases are mono-condensed terdentate whereas Ni(II) thiocyanate results in the formation of tetradentate Schiff base complexes, [NiL](SCN)(2) (L=L-4 [N,N'-bis-(1-pyridine-2-yl-ethylidine)-propane-1,3-diamine] for complex 4, L-5 [NN'-bis(pyridine-2-ylmethyline)-propane-1, 3-diamine] for complex 5 or L-6 [NN'-bis-(1-pyridine-2-yl-ethylidine)-propane- 1, 2-diamine] for complex 6) irrespective of the sets of ligands used. Formation of the complexes has been explained by anion modulation of cation templating effect. All the complexes have been characterized by elemental analyses, spectral and electrochemical results. Single crystal X-ray diffraction studies confirm the structures of four representative members, 1, 3, 4 and 5; all of them have distorted octahedral geometry around Ni(II). The bis-complexes of terdentate ligands, I and 3 are the mer isomers and the complexes of tetradentate ligands, 4 and 5 possess trans geometry. (c) 2007 Elsevier Ltd. All rights reserved.

Structural variations in Ni(II) complexes of salen type di-Schiff base ligands

Three di-Schiff-base ligands, N,N'-bis(salicylidene)-1,3-propanediamine (H(2)Salpn), N,N'-bis(salicylidene)-1,3-pentanedianiine (H(2)Salpen) and N,N'-bis(salicylidine)-ethylenediamine (H(2)Salen) react with Ni(SCN)(2). 4H(2)O in 2:3 molar ratios to form the complexes; mononuclear [Ni(HSalpn)(NCS)(H2O)]center dot H2O (1a), trinuclear [{Ni(Salpen)}(2)Ni(NCS)(2)] (2b) and trinuclear [{Ni(Salen)}(2)Ni(NCS)(2)] (3) respectively. All the complexes have been characterized by elemental analyses, IR and UV-VIS spectra, and room temperature magnetic susceptibility measurements. The structures of la and 2b have been confirmed by X-ray single crystal analysis. In complex la, the Ni(II) atom is coordinated equatorially by the tetradentate, mononegative Schiff-base, HSalpn. Axial coordination of isothiocyanate group and a water molecule completes its octahedral geometry. The hydrogen atom attached to one of the oxygen atoms of the Schiff base is involved in a very strong hydrogen bond with a neighboring unit to form a centrosymmetric dimer. In 2b, two square planar [Ni(Salpen)] units act as bide mate oxygen donor ligands to a central Ni(II) which is also coordinated by two mutually cis N-bonded thiocyanate ligands to complete its distorted octahedral geometry. Complex 3 possesses a similar structure to that of 2b. A dehydrated form of la and a hydrated form of 2b have been obtained and characterized. The importance of electronic and steric factors in the variation of the structures is discussed. (c) 2007 Elsevier Ltd. All rights reserved.