Weighted and filtered mutual information: A Metric for the automated creation of panoramas from views of complex scenes

To contribute a novel approach in the field of image registration and panorama creation, this algorithm foregoes any scene knowledge, requiring only modest scene overlap and an acceptable amount of entropy within each overlapping view. The weighted and filtered mutual information (WFMI) algorithm has been developed for multiple stationary, color, surveillance video camera views and relies on color gradients for feature correspondence. This is a novel extension of well-established maximization of mutual information (MMI) algorithms. Where MMI algorithms are typically applied to high altitude photography and medical imaging (scenes with relatively simple shapes and affine relationships between views), the WFMI algorithm has been designed for scenes with occluded objects and significant parallax variation between non-affine related views. Despite these typically non-affine surveillance scenarios, searching in the affine space for a homography is a practical assumption that provides computational efficiency and accurate results, even with complex scene views. The WFMI algorithm can perfectly register affine views, performs exceptionally well with near-affine related views, and in complex scene views (well beyond affine constraints) the WFMI algorithm provides an accurate estimate of the overlap regions between the views. The WFMI algorithm uses simple calculations (vector field color gradient, Laplacian filtering, and feature histograms) to generate the WFMI metric and provide the optimal affine relationship. This algorithm is unique when compared to typical MMI algorithms and modern registration algorithms because it avoids almost all a priori knowledge and calculations, while still providing an accurate or useful estimate for realistic scenes. With mutual information weighting and the Laplacian filtering operation, the WFMI algorithm overcomes the failures of typical MMI algorithms in scenes where complex or occluded shapes do not provide sufficiently large peaks in the mutual information maps to determine the overlap region. This work has currently been applied to individual video frames and it will be shown that future work could easily extend the algorithm into utilizing motion information or temporal frame registrations to enhance scenes with smaller overlap regions, lower entropy, or even more significant parallax and occlusion variations between views

Adaptive Scheduling Across a Distributed Computation Platform

A programmable Java distributed system, which adapts to available resources, has been developed to minimise the overall processing time of computationally intensive problems. The system exploits the free resources of a heterogeneous set of computers linked together by a network, communicating using SUN Microsystems' Remote Method Invocation and Java sockets. It uses a multi-tiered distributed system model, which in principal allows for a system of unbounded size. The system consists of an n-ary tree of nodes where the internal nodes perform the scheduling and the leaves do the processing. The scheduler nodes communicate in a peer-to-peer manner and the processing nodes operate in a strictly client-server manner with their respective scheduler. The independent schedulers on each tier of the tree dynamically allocate resources between problems based on the constantly changing characteristics of the underlying network. The system has been evaluated over a network of 86 PCs with a bioinformatics application and the travelling salesman optimisation problem

DSEARCH: sensitive database searching using distributed computing

Summary: We present a distributed and fully cross-platform database search program that allows the user to utilise the idle clock cycles of machines to perform large searches using the most sensitive algorithms. For those in an academic or corporate environment with hundreds of idle desktop machines, DSEARCH can deliver a âfreeâ database search supercomputer. Availability: The software is publicly available under the GNU general public licence from http://www.cs.may.ie/distributed Contact: [email protected] Supplementary Information: Full documentation and a user manual is available from http://www.cs.may.ie/distribute

Ranking and Selection of Motor Carrier Safety Performance by Commodity

We use recent safety performance data to rank US motor carrier commodity segments (e.g., Tank segment or Produce segment) in terms of several driver-related, vehicle-related, and crash-related safety measures. Ranking and selection inference techniques are used to determine the best and worst performing commodity segments at the 95% confidence level. The results are mixed, however the Passenger segment is generally best, while the Produce, Intermodal, and Refrigerated segments tend to be worst

Circlator: automated circularization of genome assemblies using long sequencing reads

The assembly of DNA sequence data is undergoing a renaissance thanks to emerging technologies capable of producing reads tens of kilobases long. Assembling complete bacterial and small eukaryotic genomes is now possible, but the final step of circularizing sequences remains unsolved. Here we present Circlator, the first tool to automate assembly circularization and produce accurate linear representations of circular sequences. Using Pacific Biosciences and Oxford Nanopore data, Circlator correctly circularized 26 of 27 circularizable sequences, comprising 11 chromosomes and 12 plasmids from bacteria, the apicoplast and mitochondrion of Plasmodium falciparum and a human mitochondrion. Circlator is available at http://sanger-pathogens.github.io/circlator/

Designing zeolite catalysts for shape-selective reactions: Chemical modification of surfaces for improved selectivity to dimethylamine in synthesis from methanol and ammonia

The relative contributions of external and intracrystalline acidic sites of small pore H-RHO zeolite for the selective synthesis of methylamines from methanol and ammonia have been studied. Nonselective surface reactions which produce predominantly trimethylamine can be eliminated by “capping” the external acidic sites with trimethylphosphite (TMP) and other reagents, thus improving the selectivity toward the formation of dimethylamine. For small pore zeolites, neither the zeolite pore size nor the internal acidic sites is significantly affected by this treatment. In situ infrared and MAS-NMR studies show that TMP reacts irreversibly with the zeolite acidic sites via a modified Arbusov rearrangement to form surface-bound dimethylmethylphosphonate

The gamification of cybersecurity training

Due to the rapidly and continued evolving nature of technology, there is a constant need to update police officers’ training in cyber security to ensure that the UK continues to be a secure place to live and do business. Rather than deliver traditional classroom-based training, our project assesses the effectiveness of the delivery of cyber security through the use of games based learning to simulate cybercrimes and provide training in incident response. The aim of our research is to transform the delivery of first responder training in tackling cybercrime.Through the use of a Game Jam and subsequent prototype development, we have trialed training materials that are based on serious games technology. The game poses a common incident reported to the police, for example the problem of a virtual person receiving offensive messages via Facebook and the training reflects the dialogue with that person and the technical steps to ensure that a copy of the evidence has been preserved for further investigation. Evaluation has been conducted with local police officers. Overall, this approach to the large-scale provision of training (potentially to a whole force) is shown to offer potential

On the use of serious games technology to facilitate large-scale training in cybercrime response

As technology becomes pervasive in everyday life, there are very few crimes that don’t have some ‘cyber’ element to them. The vast majority of crime now has some digital footprint; whether it’s from a CCTV camera, mobile phone or IoT device, there exists a vast range of technological devices with the ability to store digital evidence that could be of use during a criminal investigation. There is a clear requirement to ensure that digital forensic investigators have received up-to-date training on appropriate methods for the seizure, acquisition and analysis of digital devices. However, given the increasing number of crimes now involving a range of technological devices it is increasingly important for those police officers who respond to incidents of crime to have received appropriate training.The aim of our research is to transform the delivery of first responder training in tackling cybercrime.A project trialling the use of computer games technology to train officers in cybercrime response is described. A game simulating typical cybercrime scenes has been developed and its use in training first responders has been evaluated within Police Scotland. Overall, this approach to the large-scale provision of training (potentially to a whole force) is shown to offer potential

Understanding Surprise: Can Less Likely Events Be Less Surprising?

Surprise is often thought of as an experience that is elicited following an unexpected event. However, it may also be the case that surprise stems from an event that is simply difficult to explain. In this paper, we investigate the latter view. Specifically, we question why the provision of an enabling factor can mitigate perceived surprise for an unexpected event despite lowering the overall probability of that event. One possibility is that surprise occurs when a person cannot rationalise an outcome event in the context of the scenario representation. A second possibility is that people can generate plausible explanations for unexpected events but that surprise is experienced when those explanations are uncertain. We explored these hypotheses in an experiment where a first group of participants rated surprise for a number of scenario outcomes and a second group rated surprise after generating a plausible explanation for those outcomes. Finally, a third group of participants rated surprise for the both the original outcomes and the reasons generated for those outcomes by the second group. Our results suggest that people can come up with plausible explanations for unexpected events but that surprise results when these explanations are uncertain