British Columbia Institute of Technology

About: British Columbia Institute of Technology is a education organization based out in Burnaby, British Columbia, Canada. It is known for research contribution in the topics: Smart grid & Belief revision. The organization has 458 authors who have published 785 publications receiving 16140 citations.

Investigating vulnerabilities in GSM security

Abstract: The telecommunications industry uses a combination of 2G (GSM), 3G (UMTS) and 4G (LTE) systems to access communication worldwide. Concurrent with a recent rise in cyber-attacks, the requirement for a secure infrastructure is increasingly crucial. However, while each new standard offers better protection to the mobile users, currently 84% of households in the UK have access to 3G signal from the four leading providers. Users are expected to be aware of the possible security threats, however auditing of the existing systems is responsibility of administrators. This paper highlights weaknesses and issues in the Global System for Mobile communications (GSM) standard, and presents an informed approach to help audit GSM networks for vulnerabilities.

Effectiveness of UPQC in Mitigating Harmonics Generated by an Induction Furnace

Abstract: Majority of the loads involved in the operation of a steel plant are non-linear. An induction furnace is one distinctive case of a non-linear load, the growth of which has been a boon to the steel ...

Designing Computer Science Competency Statements: A Process and Curriculum Model for the 21st Century

Abstract: The broadly influential document Computing Curricula 2005 (CC2005) is in the process of being updated through a project called Computing Curricula 2020 (CC2020). CC2020 provides a vision for the future of computing education, including a comprehensive report that contrasts curricular guidelines, and contextualizing those guidelines within the broader landscape of computing education. In the process, a framework of competency-based educational principles has been developed which is closely aligned with other skills and qualifications frameworks. This working group report demonstrates one way in which the transition from current learning-outcomes-based practices to the competency-based practices can be approached. Further, the paper discusses the challenges and insights that have emerged as the learning outcomes for various Knowledge Areas in the CS2013 report were re-expressed in terms of competencies.

Design of a dynamic model of genes with multiple autonomous regulatory modules by evolutionary computations

Abstract: A new approach to design a dynamic model of genes with multiple autonomous regulatory modules by evolutionary computations is proposed. The approach is based on Genetic Algorithms (GA), with new crossover operators especially designed for these purposes. The new operators use local homology between parental strings to preserve building blocks found by the algorithm. The approach exploits the subbasin-portal architecture of the fitness functions suitable for this kind of evolutionary modeling. This architecture is significant for Royal Road class fitness functions. Two real-life Systems Biology problems with such fitness functions are implemented here: evolution of the bacterial promoter rrnPl and of the enhancer of the Drosophila even-skipped gene. The effectiveness of the approach compared to standard GA is demonstrated on several benchmark and real-life tasks.

Measuring gene expression noise in early Drosophila embryos: the highly dynamic compartmentalized micro-environment of the blastoderm is one of the main sources of noise

Abstract: Fluorescence imaging has become a widely used technique for quantitatively measuring mRNA or protein expression. The first measurements were on gene expression noise in bacteria and yeast. The relative biological and physicochemical simplicity of these single cells encouraged a number of groups to try similar approaches in multicellular organisms. Such work has been primarily on whole Drosophila embryos, where the genes forming the body plan are very well understood. The numerous sources of noise in complex embryonic tissues are a major challenge for characterizing gene expression noise. Here, we present our approach for first separating experimental from biological noise, followed by distinguishing sources of biological noise. We decompose raw signal into trend and residual noise using Singular Spectrum Analysis. We demonstrate our statistical techniques on the Drosophila Hunchback protein pattern. We show that the ‘texture noise', arising from the pre-cellular compartmentalization of the embryo surface, which is highly dynamic in time, is a major component of total biological noise, and can exceed gene transcription/translation noise.