Automated Vehicles Have Arrived: What\u27s a Transit Agency to Do?

Ongoing innovations in automated and connected road vehicles create a path of radical transformation of personal mobility, the automotive industry, trucking, public transit, the taxi industry, urban planning, transportation infrastructure, jobs, vehicle ownership, and other physical and social aspects of our built world and daily lives. In considering automated vehicle (AV) deployments and their cost, as well as the changes in traffic volume, congestion, rights of way, and the complexities of mixed fleets with both automated and non-automated vehicles, the time frame of impacts can only be surmised. Still, it is worth considering a framework for understanding and managing the forthcoming process of change covered in this perspective

Revisiting h measured on UK LIS and IR academics

A brief communication appearing in this journal ranked UK LIS and (some) IR academics by their h-index using data derived from Web of Science. In this brief communication, the same academics were re-ranked, using other popular citation databases. It was found that for academics who publish more in computer science forums, their h was significantly different due to highly cited papers missed by Web of Science; consequently their rank changed substantially. The study was widened to a broader set of UK LIS and IR academics where results showed similar statistically significant differences. A variant of h, hmx, was introduced that allowed a ranking of the academics using all citation databases together

Adaptive text mining: Inferring structure from sequences

Text mining is about inferring structure from sequences representing natural language text, and may be defined as the process of analyzing text to extract information that is useful for particular purposes. Although hand-crafted heuristics are a common practical approach for extracting information from text, a general, and generalizable, approach requires adaptive techniques. This paper studies the way in which the adaptive techniques used in text compression can be applied to text mining. It develops several examples: extraction of hierarchical phrase structures from text, identification of keyphrases in documents, locating proper names and quantities of interest in a piece of text, text categorization, word segmentation, acronym extraction, and structure recognition. We conclude that compression forms a sound unifying principle that allows many text mining problems to be tacked adaptively

Analysing Scientific Collaborations of New Zealand Institutions using Scopus Bibliometric Data

Scientific collaborations are among the main enablers of development in small national science systems. Although analysing scientific collaborations is a well-established subject in scientometrics, evaluations of scientific collaborations within a country remain speculative with studies based on a limited number of fields or using data too inadequate to be representative of collaborations at a national level. This study represents a unique view on the collaborative aspect of scientific activities in New Zealand. We perform a quantitative study based on all Scopus publications in all subjects for more than 1500 New Zealand institutions over a period of 6 years to generate an extensive mapping of scientific collaboration at a national level. The comparative results reveal the level of collaboration between New Zealand institutions and business enterprises, government institutions, higher education providers, and private not for profit organisations in 2010-2015. Constructing a collaboration network of institutions, we observe a power-law distribution indicating that a small number of New Zealand institutions account for a large proportion of national collaborations. Network centrality concepts are deployed to identify the most central institutions of the country in terms of collaboration. We also provide comparative results on 15 universities and Crown research institutes based on 27 subject classifications.Comment: 10 pages, 15 figures, accepted author copy with link to research data, Analysing Scientific Collaborations of New Zealand Institutions using Scopus Bibliometric Data. In Proceedings of ACSW 2018: Australasian Computer Science Week 2018, January 29-February 2, 2018, Brisbane, QLD, Australi

Improving Transportation Construction Project Performance: Development of a Model to Support the Decision-Making Process for Incentive/Disincentive Construction Projects, MTI Report 09-07

This research presents a project time and cost performance simulation model to assist project planners and managers by providing a complete picture during the Incentive/Disincentive (I/D) contracting decision-making process of possible performance outcomes with probabilities based on historical data. This study was performed by collecting transportation construction project data. The collected project data from the Florida Department of Transportation were evaluated using time and cost performance indices and then statistical data analysis was performed to identify important factors that influence construction project time performance. Using Monte Carlo simulation procedures, this study demonstrated a methodology for developing an I/D project time and cost performance prediction model. User-friendly visual interfaces were developed to perform the simulation and report results using Visual Basic Application programming. The developed model was validated using additional cases of transportation construction projects. Based on statistical analysis, this research found that several project factors influence I/D contracting performance. The important factors that had significant impacts on project performance were the effects of contract type, project type, district, project size, project length, maximum incentive amount, and daily I/D amount. In conclusion, the developed model applied to I/D contracting projects will be a useful tool to assist the project planners and managers during the decision-making process and will promote the efficient use of I/D contracting, which will benefit the traveling public by saving their travel time from construction delays. With additional project data, the developed model can be updated easily and the more data used for the model, the better the accuracy of prediction that can be expected

Social Media Attention Increases Article Visits: An Investigation on Article-Level Referral Data of PeerJ

In order to better understand the effect of social media in the dissemination of scholarly articles, employing the daily updated referral data of 110 PeerJ articles collected over a period of 345 days, we analyze the relationship between social media attention and article visitors directed by social media. Our results show that social media presence of PeerJ articles is high. About 68.18% of the papers receive at least one tweet from Twitter accounts other than @PeerJ, the official account of the journal. Social media attention increases the dissemination of scholarly articles. Altmetrics could not only act as the complement of traditional citation measures but also play an important role in increasing the article downloads and promoting the impacts of scholarly articles. There also exists a significant correlation among the online attention from different social media platforms. Articles with more Facebook shares tend to get more tweets. The temporal trends show that social attention comes immediately following publication but does not last long, so do the social media directed article views

Software Engineers' Information Seeking Behavior in Change Impact Analysis - An Interview Study

Software engineers working in large projects must navigate complex information landscapes. Change Impact Analysis (CIA) is a task that relies on engineers' successful information seeking in databases storing, e.g., source code, requirements, design descriptions, and test case specifications. Several previous approaches to support information seeking are task-specific, thus understanding engineers' seeking behavior in specific tasks is fundamental. We present an industrial case study on how engineers seek information in CIA, with a particular focus on traceability and development artifacts that are not source code. We show that engineers have different information seeking behavior, and that some do not consider traceability particularly useful when conducting CIA. Furthermore, we observe a tendency for engineers to prefer less rigid types of support rather than formal approaches, i.e., engineers value support that allows flexibility in how to practically conduct CIA. Finally, due to diverse information seeking behavior, we argue that future CIA support should embrace individual preferences to identify change impact by empowering several seeking alternatives, including searching, browsing, and tracing.Comment: Accepted for publication in the proceedings of the 25th International Conference on Program Comprehensio

Task-related models for teaching and assessing iteration learning in high school

A number of studies report about students’ difficulties with basic flow-control constructs, and specifically with iteration. Although such issues are less explored in the context of pre-tertiary education, this seems to be especially the case for high-school programming learning, where the difficulties concern both the “mechanical” features of the notional machine as well as the logical aspects connected with the constructs, ranging from the implications of loop conditions to a more abstract grasp of the underlying algorithms. For these reasons, the aim of this work is to: i) identifying methodological tools to enhance a comprehensive understanding of the iteration constructs, ii) suggest strategies to teach iterations. We interviewed 20 experienced upper secondary teachers of introductory programming in different kinds of schools. The interviews were mainly aimed at ascertaining teachers’ beliefs about major sources of issues for basic programming concepts and their approach to the teaching and learning of iteration constructs. Once teachers’ perception of students’ difficulties have been identified, we have submitted, to a sample of 164 students, a survey which included both questions on their subjective perception of difficulty and simple tasks probing their understanding of iteration. Data collected from teachers and students confirm that iteration is a central programming concept and indicate that the treatment of conditions and nested constructs are major sources of students’ difficulties with iteration. The interviews allowed us to identify a list of problems that are typically presented by teachers to explain the iterations. Hence, a catalogue of significant program examples has been built to support students’ learning, tasks with characteristics different from those typically presented in class. Based on the outcome of previous steps, a survey to collect related information and good practices from a larger sample of teachers has been designed. Data collected have been analysed distinguishing an orientation towards more conceptual objectives, and one towards more practical objectives. Furthermore, regarding evaluation, a orientation focused on process-based assessment and another on product-based assessment. Finally, based on the outcome of previous students’ survey and drawing from the proposed examples catalogue, we have designed and submitted a new students’ survey, composed of a set of small tasks, or tasklets, to investigate in more depth on high-school students’ understanding of iteration in terms of code reading abilities. The chosen tasklets covered the different topics: technical program feature, correlation between tracing effort and abstraction, the role of flow-charts, students’ perception of self-confidence concerning high-level thinking skills.A number of studies report about students’ difficulties with basic flow-control constructs, and specifically with iteration. Although such issues are less explored in the context of pre-tertiary education, this seems to be especially the case for high-school programming learning, where the difficulties concern both the “mechanical” features of the notional machine as well as the logical aspects connected with the constructs, ranging from the implications of loop conditions to a more abstract grasp of the underlying algorithms. For these reasons, the aim of this work is to: i) identifying methodological tools to enhance a comprehensive understanding of the iteration constructs, ii) suggest strategies to teach iterations. We interviewed 20 experienced upper secondary teachers of introductory programming in different kinds of schools. The interviews were mainly aimed at ascertaining teachers’ beliefs about major sources of issues for basic programming concepts and their approach to the teaching and learning of iteration constructs. Once teachers’ perception of students’ difficulties have been identified, we have submitted, to a sample of 164 students, a survey which included both questions on their subjective perception of difficulty and simple tasks probing their understanding of iteration. Data collected from teachers and students confirm that iteration is a central programming concept and indicate that the treatment of conditions and nested constructs are major sources of students’ difficulties with iteration. The interviews allowed us to identify a list of problems that are typically presented by teachers to explain the iterations. Hence, a catalogue of significant program examples has been built to support students’ learning, tasks with characteristics different from those typically presented in class. Based on the outcome of previous steps, a survey to collect related information and good practices from a larger sample of teachers has been designed. Data collected have been analysed distinguishing an orientation towards more conceptual objectives, and one towards more practical objectives. Furthermore, regarding evaluation, a orientation focused on process-based assessment and another on product-based assessment. Finally, based on the outcome of previous students’ survey and drawing from the proposed examples catalogue, we have designed and submitted a new students’ survey, composed of a set of small tasks, or tasklets, to investigate in more depth on high-school students’ understanding of iteration in terms of code reading abilities. The chosen tasklets covered the different topics: technical program feature, correlation between tracing effort and abstraction, the role of flow-charts, students’ perception of self-confidence concerning high-level thinking skills