Structure from motion (SFM) photogrammetry vs terrestrial laser scanning

Structure from Motion (SfM) has its roots in the well-established spatial measurement method of photogrammetry, but is becoming increasingly recognised as a means to capture dense 3D data to represent real-world objects, both natural and man- made. This capability has conventionally been the domain of the terrestrial laser scanner (TLS), a mature and easy to understand method used to generate millions of 3D point coordinates in a form known as a “point cloud”. Each technique is described and noted for its strengths and weaknesses

The state of green technologies in South Africa

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Vector boson fusion searches for dark matter at the LHC

The vector boson fusion (VBF) event topology at the Large Hadron Collider (LHC) allows efficient suppression of dijet backgrounds and is therefore a promising target for new physics searches. We consider dark matter models which interact with the Standard Model through the electroweak sector: either through new scalar and pseudoscalar mediators which can be embedded into the Higgs sector, or via effective operators suppressed by some higher scale, and therefore have significant VBF production cross-sections. Using realistic simulations of the ATLAS and CMS analysis chain, including estimates of major error sources, we project the discovery and exclusion potential of the LHC for these models over the next decade.Comment: 16 pages, 2 tables, 12 figure

Chemokine receptors in the rheumatoid synovium: upregulation of CXCR5

In patients with rheumatoid arthritis (RA), chemokine and chemokine receptor interactions play a central role in the recruitment of leukocytes into inflamed joints. This study was undertaken to characterize the expression of chemokine receptors in the synovial tissue of RA and non-RA patients. RA synovia (n = 8) were obtained from knee joint replacement operations and control non-RA synovia (n = 9) were obtained from arthroscopic knee biopsies sampled from patients with recent meniscal or articular cartilage damage or degeneration. The mRNA expression of chemokine receptors and their ligands was determined using gene microarrays and PCR. The protein expression of these genes was demonstrated by single-label and double-label immunohistochemistry. Microarray analysis showed the mRNA for CXCR5 to be more abundant in RA than non-RA synovial tissue, and of the chemokine receptors studied CXCR5 showed the greatest upregulation. PCR experiments confirmed the differential expression of CXCR5. By immunohistochemistry we were able to detect CXCR5 in all RA and non-RA samples. In the RA samples the presence of CXCR5 was observed on B cells and T cells in the infiltrates but also on macrophages and endothelial cells. In the non-RA samples the presence of CXCR5 was limited to macrophages and endothelial cells. CXCR5 expression in synovial fluid macrophages and peripheral blood monocytes from RA patients was confirmed by PCR. The present study shows that CXCR5 is upregulated in RA synovial tissue and is expressed in a variety of cell types. This receptor may be involved in the recruitment and positioning of B cells, T cells and monocytes/macrophages in the RA synovium. More importantly, the increased level of CXCR5, a homeostatic chemokine receptor, in the RA synovium suggests that non-inflammatory receptor–ligand pairs might play an important role in the pathogenesis of RA

Using a Nearest-Neighbour, BERT-Based Approach for Scalable Clone Detection

Code clones can detrimentally impact software maintenance and manually detecting them in very large codebases is impractical. Additionally, automated approaches find detection of Type 3 and Type 4 (inexact) clones very challenging. While the most recent artificial deep neural networks (for example BERT-based artificial neural networks) seem to be highly effective in detecting such clones, their pairwise comparison of every code pair in the target system(s) is inefficient and scales poorly on large codebases. We therefore introduce SSCD, a BERT-based clone detection approach that targets high recall of Type 3 and Type 4 clones at scale (in line with our industrial partner's requirements). It does so by computing a representative embedding for each code fragment and finding similar fragments using a nearest neighbour search. SSCD thus avoids the pairwise-comparison bottleneck of other Neural Network approaches while also using parallel, GPU-accelerated search to tackle scalability. This paper details the approach and an empirical assessment towards configuring and evaluating that approach in industrial setting. The configuration analysis suggests that shorter input lengths and text-only based neural network models demonstrate better efficiency in SSCD, while only slightly decreasing effectiveness. The evaluation results suggest that SSCD is more effective than state-of-the-art approaches like SAGA and SourcererCC. It is also highly efficient: in its optimal setting, SSCD effectively locates clones in the entire 320 million LOC BigCloneBench (a standard clone detection benchmark) in just under three hours.Comment: 10 pages, 2 figures, 38th IEEE International Conference on Software Maintenance and Evolutio

Ariel - Volume 6 Number 4

Editors Mark Dembert J.D. Kanofsky Frank Chervenak John Lammie Curt Cummings Entertainment Robert Breckenridge Joe Conti Gary Kaskey Photographer Larry Glazerman Overseas Editor Mike Sinason Humorist Jim McCann Staff Ken Jaffe Bob Sklaroff Halley Faust Jim Burk

Towards a Taxonomy of Software Evolution

Previous taxonomies of software evolution have focused on the purpose of the change rather than the underlying mechanisms. This paper proposes a taxonomy of software evolution based on the characterizing mechanisms of change and the factors that influence these mechanisms. The taxonomy is organized into the following logical groupings: temporal properties, objects of change, system properties, and change support. The ultimate goal of this taxonomy is to provide a framework that positions concrete tools, formalisms and methods within the domain of software evolution. Such a framework would considerably ease comparison between these tools, formalisms and methods. It would also allow practitioners to evaluate their potential use in particular change scenarios. As an initial step towards this taxonomy, the paper presents a framework that can be used to characterize software change support tools and to identify the factors that impact on the use of these tools. The framework is evaluated by applying it to three different change support tools and by comparing these tools based on this analysis