Filling the gaps of development logs and bug issue data

It has been suggested that the data from bug repositories is not always in sync or complete compared to the logs detailing the actions of developers on source code. In this paper, we trace two sources of information relative to software bugs: the change logs of the actions of developers and the issues reported as bugs. The aim is to identify and quantify the discrepancies between the two sources in recording and storing the developer logs relative to bugs. Focussing on the databases produced by two mining software repository tools, CVSAnalY and Bicho, we use part of the SZZ algorithm to identify bugs and to compare how the"defects-fixing changes" are recorded in the two databases. We use a working example to show how to do so. The results indicate that there is a significant amount of information, not in sync when tracing bugs in the two databases. We, therefore, propose an automatic approach to re-align the two databases, so that the collected information is mirrored and in sync.Dr. Felipe Orteg

Trust and Experience in Online Auctions

This paper aims to shed light on the complexities and difficulties in predicting the effects of trust and the experience of online auction participants on bid levels in online auctions. To provide some insights into learning by bidders, a field study was conducted first to examine auction and bidder characteristics from eBay auctions of rare coins. We proposed that such learning is partly because of institutional-based trust. Data were then gathered from 453 participants in an online experiment and survey, and a structural equation model was used to analyze the results. This paper reveals that experience has a nonmonotonic effect on the levels of online auction bids. Contrary to previous research on traditional auctions, as online auction bidders gain more experience, their level of institutional-based trust increases and leads to higher bid levels. Data also show that both a bidder’s selling and bidding experiences increase bid levels, with the selling experience having a somewhat stronger effect. This paper offers an in-depth study that examines the effects of experience and learning and bid levels in online auctions. We postulate this learning is because of institutional-based trust. Although personal trust in sellers has received a significant amount of research attention, this paper addresses an important gap in the literature by focusing on institutional-based trust

The imperial war museum’s social interpretation project

This report represents the output from research undertaken by University of Salford and MTM London as part of the joint Digital R&D Fund for Arts and Culture, operated by Nesta, Arts Council England and the AHRC. University of Salford and MTM London received funding from the programme to act as researchers on the Social Interpretation (SI) project, which was led by the Imperial War Museum (IWM) and their technical partners, The Centre for Digital Humanities, University College London, Knowledge Integration, and Gooii. The project was carried out between October 2011 and October 2012

Process transparency on construction sites : examples from construction companies in Brazil

Process transparency is the core concept in Visual Management (VM), which is one of the founding blocks of the Toyota Production System. This paper presents the preliminary results of a collaborative research conducted between Brazil and the UK, as part of a research effort focused on the application of Visual Management in construction. How process transparency is realized on construction sites is the main research question of the paper. The use of this concept and the implementation of the transparency theory were investigated through multiple case studies, carried out in nine different construction companies. The findings are explained through six theoretical transparency increasing approaches. The affecting parameters in the application of, the management’s perception of and several methods in process transparency in construction were identified. Further work, especially exploring the functions of process transparency on construction sites and reflecting the worker perception of the issue, is necessary to elaborate the process transparency concept

Fiber Orientation Estimation Guided by a Deep Network

Diffusion magnetic resonance imaging (dMRI) is currently the only tool for noninvasively imaging the brain's white matter tracts. The fiber orientation (FO) is a key feature computed from dMRI for fiber tract reconstruction. Because the number of FOs in a voxel is usually small, dictionary-based sparse reconstruction has been used to estimate FOs with a relatively small number of diffusion gradients. However, accurate FO estimation in regions with complex FO configurations in the presence of noise can still be challenging. In this work we explore the use of a deep network for FO estimation in a dictionary-based framework and propose an algorithm named Fiber Orientation Reconstruction guided by a Deep Network (FORDN). FORDN consists of two steps. First, we use a smaller dictionary encoding coarse basis FOs to represent the diffusion signals. To estimate the mixture fractions of the dictionary atoms (and thus coarse FOs), a deep network is designed specifically for solving the sparse reconstruction problem. Here, the smaller dictionary is used to reduce the computational cost of training. Second, the coarse FOs inform the final FO estimation, where a larger dictionary encoding dense basis FOs is used and a weighted l1-norm regularized least squares problem is solved to encourage FOs that are consistent with the network output. FORDN was evaluated and compared with state-of-the-art algorithms that estimate FOs using sparse reconstruction on simulated and real dMRI data, and the results demonstrate the benefit of using a deep network for FO estimation.Comment: A shorter version is accepted by MICCAI 201

Soc4425G: Concussion Legacy Foundation Media Creation

Concussion Legacy Foundation Center (CLFC) aims to educated youth in Ontario about concussion awareness and prevention. Our Community Engaged Learning task was to create social media content that would engage and educate youth about concussion in a fun and relevant way. Through the use of a popular social media platform, research, and personal testimonies from youth on their knowledge and interests our group was able to create several videos that inform youths ages 9-14 years old about concussions in a brief, engaging, humorous and fun way