5,079 research outputs found
Punctuated Equilibrium in Software Evolution
The approach based on paradigm of self-organized criticality proposed for
experimental investigation and theoretical modelling of software evolution. The
dynamics of modifications studied for three free, open source programs Mozilla,
Free-BSD and Emacs using the data from version control systems. Scaling laws
typical for the self-organization criticality found. The model of software
evolution presenting the natural selection principle is proposed. The results
of numerical and analytical investigation of the model are presented. They are
in a good agreement with the data collected for the real-world software.Comment: 4 pages, LaTeX, 2 Postscript figure
YouTube Video Project: A Cool Way to Learn Communication Ethics
The millennial generation embraces new technologies as a natural way of accessing and exchanging information, staying connected, and having fun. YouTube, a video-sharing site that allows users to upload, view, and share video clips, is among the latest “cool” technologies for enjoying quick laughs, employing a wide variety of corporate activities, and also communicating relevant, engaging instructional content for today’s students. This article describes a YouTube video class project that is a natural fit with today’s students because it involves cutting-edge social media while addressing a critical component of professional development—communication ethics. This project encourages critical thinking, creativity, and applied learning in a team environment using a “cool” new media tool
Empirical Studies of Evolving Systems
This paper describes the results of the working group investigating the issues of empirical studies for
evolving systems. The groups found that there were many issues that were central to successful evolution and this
concluded that this is a very important area within software engineering. Finally nine main areas were selected for consideration. For each of these areas the central issues were identified as well as success factors. In some cases success stories were also described and the critical factors accounting for the success analysed. In some cases it was later found that a number of areas were so tightly coupled that it was important to discuss them together
Face recognition system using fringe projection and moiré: characterization with fractal parameters
We show a new method for face recognition which combines the projection of structures with different characteristics (fringes, bars or grids, dots or speckle) over the face. These projections will then allow the creation of a computer-generated moiré pattern over which different kinds of fractal and complex geometry parameters are then measured. Such parameters will then be used as inputs for a neuro-symbolic hybrid system. Here, we analyze the incidence of some parameters on the efficience for the face recognition method
The Case for Learned Index Structures
Indexes are models: a B-Tree-Index can be seen as a model to map a key to the
position of a record within a sorted array, a Hash-Index as a model to map a
key to a position of a record within an unsorted array, and a BitMap-Index as a
model to indicate if a data record exists or not. In this exploratory research
paper, we start from this premise and posit that all existing index structures
can be replaced with other types of models, including deep-learning models,
which we term learned indexes. The key idea is that a model can learn the sort
order or structure of lookup keys and use this signal to effectively predict
the position or existence of records. We theoretically analyze under which
conditions learned indexes outperform traditional index structures and describe
the main challenges in designing learned index structures. Our initial results
show, that by using neural nets we are able to outperform cache-optimized
B-Trees by up to 70% in speed while saving an order-of-magnitude in memory over
several real-world data sets. More importantly though, we believe that the idea
of replacing core components of a data management system through learned models
has far reaching implications for future systems designs and that this work
just provides a glimpse of what might be possible
Human phosphodiesterase 4D7 (PDE4D7) expression is increased in TMPRSS2-ERG positive primary prostate cancer and independently adds to a reduced risk of post-surgical disease progression
background: There is an acute need to uncover biomarkers that reflect the molecular pathologies, underpinning prostate cancer progression and poor patient outcome. We have previously demonstrated that in prostate cancer cell lines PDE4D7 is downregulated in advanced cases of the disease. To investigate further the prognostic power of PDE4D7 expression during prostate cancer progression and assess how downregulation of this PDE isoform may affect disease outcome, we have examined PDE4D7 expression in physiologically relevant primary human samples.
methods: About 1405 patient samples across 8 publically available qPCR, Affymetrix Exon 1.0 ST arrays and RNA sequencing data sets were screened for PDE4D7 expression. The TMPRSS2-ERG gene rearrangement status of patient samples was determined by transformation of the exon array and RNA seq expression data to robust z-scores followed by the application of a threshold >3 to define a positive TMPRSS2-ERG gene fusion event in a tumour sample.
results: We demonstrate that PDE4D7 expression positively correlates with primary tumour development. We also show a positive association with the highly prostate cancer-specific gene rearrangement between TMPRSS2 and the ETS transcription factor family member ERG. In addition, we find that in primary TMPRSS2-ERG-positive tumours PDE4D7 expression is significantly positively correlated with low-grade disease and a reduced likelihood of progression after primary treatment. Conversely, PDE4D7 transcript levels become significantly decreased in castration resistant prostate cancer (CRPC).
conclusions: We further characterise and add physiological relevance to PDE4D7 as a novel marker that is associated with the development and progression of prostate tumours. We propose that the assessment of PDE4D7 levels may provide a novel, independent predictor of post-surgical disease progression
Novelty Search in Competitive Coevolution
One of the main motivations for the use of competitive coevolution systems is
their ability to capitalise on arms races between competing species to evolve
increasingly sophisticated solutions. Such arms races can, however, be hard to
sustain, and it has been shown that the competing species often converge
prematurely to certain classes of behaviours. In this paper, we investigate if
and how novelty search, an evolutionary technique driven by behavioural
novelty, can overcome convergence in coevolution. We propose three methods for
applying novelty search to coevolutionary systems with two species: (i) score
both populations according to behavioural novelty; (ii) score one population
according to novelty, and the other according to fitness; and (iii) score both
populations with a combination of novelty and fitness. We evaluate the methods
in a predator-prey pursuit task. Our results show that novelty-based approaches
can evolve a significantly more diverse set of solutions, when compared to
traditional fitness-based coevolution.Comment: To appear in 13th International Conference on Parallel Problem
Solving from Nature (PPSN 2014
A biophysical model of prokaryotic diversity in geothermal hot springs
Recent field investigations of photosynthetic bacteria living in geothermal
hot spring environments have revealed surprisingly complex ecosystems, with an
unexpected level of genetic diversity. One case of particular interest involves
the distribution along hot spring thermal gradients of genetically distinct
bacterial strains that differ in their preferred temperatures for reproduction
and photosynthesis. In such systems, a single variable, temperature, defines
the relevant environmental variation. In spite of this, each region along the
thermal gradient exhibits multiple strains of photosynthetic bacteria adapted
to several distinct thermal optima, rather than the expected single thermal
strain adapted to the local environmental temperature. Here we analyze
microbiology data from several ecological studies to show that the thermal
distribution field data exhibit several universal features independent of
location and specific bacterial strain. These include the distribution of
optimal temperatures of different thermal strains and the functional dependence
of the net population density on temperature. Further, we present a simple
population dynamics model of these systems that is highly constrained by
biophysical data and by physical features of the environment. This model can
explain in detail the observed diversity of different strains of the
photosynthetic bacteria. It also reproduces the observed thermal population
distributions, as well as certain features of population dynamics observed in
laboratory studies of the same organisms
The Wild Turkey in South Dakota
This bulletin provides an extensive look at the wild turkey in South Dakota
- …