Proceedings of the second "international Traveling Workshop on Interactions between Sparse models and Technology" (iTWIST'14)

The implicit objective of the biennial "international - Traveling Workshop on Interactions between Sparse models and Technology" (iTWIST) is to foster collaboration between international scientific teams by disseminating ideas through both specific oral/poster presentations and free discussions. For its second edition, the iTWIST workshop took place in the medieval and picturesque town of Namur in Belgium, from Wednesday August 27th till Friday August 29th, 2014. The workshop was conveniently located in "The Arsenal" building within walking distance of both hotels and town center. iTWIST'14 has gathered about 70 international participants and has featured 9 invited talks, 10 oral presentations, and 14 posters on the following themes, all related to the theory, application and generalization of the "sparsity paradigm": Sparsity-driven data sensing and processing; Union of low dimensional subspaces; Beyond linear and convex inverse problem; Matrix/manifold/graph sensing/processing; Blind inverse problems and dictionary learning; Sparsity and computational neuroscience; Information theory, geometry and randomness; Complexity/accuracy tradeoffs in numerical methods; Sparsity? What's next?; Sparse machine learning and inference.Comment: 69 pages, 24 extended abstracts, iTWIST'14 website: http://sites.google.com/site/itwist1

To be understood: Transitioning to adult life for people with Autism Spectrum Disorder

Introduction: The purpose of this study was to explore the viewpoints of parents of young people with Autism Spectrum Disorder (ASD) in relation to their child's transition to adulthood. Methods: Data were collected during four structured focus groups with 19 parents of young people with ASD with average to high intellectual capacities. Condensed meaning units were identified and checked during focus groups, and were subsequently linked to the International Classification of Functioning, Disability and Health (ICF). Results: Three major themes emerged: to be understood, to understand the world and to succeed. The ICF domains of activity and participation and environmental factors emerged as having the greatest potential to influence transition outcomes. Conclusions: Policies and services should focus on strengths to maximise participation in higher education, employment and independent living amongst young people with ASD. Interventions targeting environmental factors could be effective in improving participation in adult life. Person-centred and individualised approaches could further complement this approach supporting the transition to adulthood for people with ASD, ultimately improving outcomes in adulthood

A comparison between chip fractional and non-fractional sampling for a direct sequence CDMA receiver

This paper examines the effects of chip fractional (CF) and chip nonfractional (CNF) sampling on the performance of a CDMA uplink receiver. The impact of the receiver front end filter, which is sampling rate dependent, is investigated. Models for burst and continuous transmissions are introduced. The discrete-time equivalent channels between the various users and the receiver are assumed to be known. First, the mutual information between the emitted sequences of symbols and the received sequence is investigated. It is analytically shown that the receiver systematically loses information in case of CNF sampling. Second, we have demonstrated that the CF receiver always achieves better performance in terms of minimum mean square error (MMSE) for both linear and decision feedback (DF) structures. A closed-form expression of the gain in performance is provided for the two metrics under consideration. The importance of the gain due to CF sampling is also illustrated by means of computations for multipath channels. For a typical system setup, a gain of 0.1 bits per emitted symbol is observed for the mutual information. Considering the geometrical mean of symbol SINRs in case of linear and DF joint detection (JD) for a roll-off factor equal to 0.3, a gain of 0.4 dB arises for the CF linear detector, and a gain of 0.2 dB arises for the CF DF detector

Low-complexity estimation of CFO and frequency independent I/Q mismatch for OFDM systems

CFO and I/Q mismatch could cause significant performance degradation to OFDM systems. Their estimation and compensation are generally difficult as they are entangled in the received signal. In this paper, we propose some low-complexity estimation and compensation schemes in the receiver, which are robust to various CFO and I/Q mismatch values although the performance is slightly degraded for very small CFO. These schemes consist of three steps: forming a cosine estimator free of I/Q mismatch interference, estimating I/Q mismatch using the estimated cosine value, and forming a sine estimator using samples after I/Q mismatch compensation. These estimators are based on the perception that an estimate of cosine serves much better as the basis for I/Q mismatch estimation than the estimate of CFO derived from the cosine function. Simulation results show that the proposed schemes can improve system performance significantly, and they are robust to CFO and I/Q mismatch

DNA sequence modeling based on context trees

Genomic sequences contain instructions for protein and cell production. Therefore understanding and identification of biologically and functionally meaningful patterns in DNA sequences is of paramount importance. Modeling of DNA sequences in its turn can help to better understand and identify such patterns and dependencies between them. It is well-known that genomic data contains various regions with distinct functionality and thus also statistical properties. In this work we focus on modeling of such individual regions of distinct functionalities. We apply the concept of context trees to model these DNA regions. Based on the Minimum Description Length principle, we use the estimated compression rate of a genomic region, given such models, as a similarity measure. We show that the constructed model can be used to distinguish specific genes within DNA sequences