Editorial zum Themenheft ,,Automotive Software Engineering”

Ohne Zusammenfassung     

Editorial zum Themenheft: ?‘Software-Reengineering“’

Ohne Zusammenfassung     

Modellierung und kartographische Visualisierung von Geodaten mit XML-basierten Sprachen

Zusammenfassung Mit den XML-basierten Sprachen GML, XSLT und SVG lassen sich Geodaten nicht nur anwendungsorientiert modellieren, sondern auch karten?hnlich visualisieren. In dieser Fallstudie zeigen wir das, indem wir realistische Geodatenbest?nde der Landesvermessungs?mter zun?chst mit der Geography Markup Language (GML) nachmodellieren. So mit GML strukturierte Daten werden dann mit der Extensible Stylesheet Language for Transformation (XSLT) auf Elemente der Sprache Scalable Vector Graphics (SVG) abgebildet. Dabei wird der Prozess der kartografischen Visualisierung durch XSLT-Konstrukte modelliert und auch gleichzeitig implementiert. Als Ergebnis erhalten wir Grafiken, die den entsprechenden Karten der Landes?mter zumindest nicht un?hnlich sind.

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Using the XML-based languages GML, XSLT and SVG, we modeled German geo data and also visualized it in map-like graphics. This case study shows the feasibility of that approach, by modelling the data with the Geography Markup Language (GML). Then, the GML-structured data is mapped with the Extensible Stylesheet Language for Transformation (XSLT) to elements of the language Scalable Vector Graphics (SVG). The process of cartographical visualization is thus modelled through XSLT-constructs and at same time also implemented. The results are graphics, which share close ressemblance to the corresponding maps of the official offices.

CR Subject Classification I.3.3,I.3.5,I.6.5,I.7.2,J.2     

Staff development planning in an academic health sciences library.

OBJECTIVE: A staff development committee (SDC) was convened to implement staff development opportunities for an academic health sciences library system comprised of three separate facilities. The charge for the SDC was to: (1) develop programs to enhance workplace skills and personal growth, (2) communicate the availability of existing programs at the university and medical center, and (3) encourage the staff to participate in these opportunities. PROGRAM: The committee created goals and objectives and developed a survey designed to give staff the opportunity to provide input for this initiative. With an 80% response rate, the survey results were used to plan 15 events based on staff needs and preferences. First-year attendance for SDC-sponsored events was 459. Committee members served as liaisons for each event. Two forms were developed to facilitate event planning. A monthly announcement sheet, email reminders, and the library's local area network are used to communicate upcoming SDC events and encourage attendance. CONCLUSION: This approach can serve as a useful model for similar program planning in any organization.     

Institutional policy process improvement: using structurating activity theory to inform practice

Organizational communication scholars are increasingly called upon to use theoretical knowledge to address problematic processes in public institutions. This article reports a process improvement project focused on a university conflict of interest (COI) policy as an example of how scholars can engage theory to improve ongoing policy processes. The project team included communication scholars and research administration staff who designed, implemented, and evaluated the mixed-methods project guided by structurating activity theory. Baseline survey results were used to design the process improvement project. Results of the follow-up survey indicate that researchers who participated in some aspect of the process improvement project (i.e. attending a policy café, using the redesigned website, or reading the new Quick Reference Guide) reported higher levels of policy communication and knowledge and more positive attitudes toward the COI policy than researchers who had not engaged with process improvement efforts. We offer theoretical and practical implications of results for organizational communication scholars and practitioners.     

Russian Science Citation Index: Areas for Development Identified by Active Users

The current state of the Russian Science Citation Index is analyzed. Several areas for its further development identified by long-standing active users, such as data searching, refinement, and storage; current user alerts; data input with the Science Index license; patent information; and the application programming interface (API) are investigated.     

The Effects of Darkness and Lightness Cues in the Visual Depiction of Political Actors Involved in Scandals: An Experimental Study

Reports about political scandals have increased lately. Yet the general impact of news visuals and the specific role of lightness and darkness cues in images of scandalized politicians remain unclear. With the help of an experiment, the present pilot study examined the influence of candidate images and the effects of particular image backgrounds (light versus dark). While the foreground of the image depicting a politician involved in a scandal remained unchanged, the background was systematically altered. The results revealed that a light background had a positive effect on recipients’ attitudes toward the politician. In contrast, participants exposed to a dark image background demanded a more severe punishment for the politician.     

Alexa,Siri, Cortana,and More: An Introduction to Voice Assistants

Voice assistants are software agents that can interpret human speech and respond via synthesized voices. Apple’s Siri, Amazon’s Alexa, Microsoft’s Cortana, and Google’s Assistant are the most popular voice assistants and are embedded in smartphones or dedicated home speakers. Users can ask their assistants questions, control home automation devices and media playback via voice, and manage other basic tasks such as email, to-do lists, and calendars with verbal commands. This column will explore the basic workings and common features of today’s voice assistants. It will also discuss some of the privacy and security issues inherent to voice assistants and some potential future uses for these devices. As voice assistants become more widely used, librarians will want to be familiar with their operation and perhaps consider them as a means to deliver library services and materials.     

Retrieving and classifying instances of source code plagiarism

Automatic detection of source code plagiarism is an important research field for both the commercial software industry and within the research community. Existing methods of plagiarism detection primarily involve exhaustive pairwise document comparison, which does not scale well for large software collections. To achieve scalability, we approach the problem from an information retrieval (IR) perspective. We retrieve a ranked list of candidate documents in response to a pseudo-query representation constructed from each source code document in the collection. The challenge in source code document retrieval is that the standard bag-of-words (BoW) representation model for such documents is likely to result in many false positives being retrieved, because of the use of identical programming language specific constructs and keywords. To address this problem, we make use of an abstract syntax tree (AST) representation of the source code documents. While the IR approach is efficient, it is essentially unsupervised in nature. To further improve its effectiveness, we apply a supervised classifier (pre-trained with features extracted from sample plagiarized source code pairs) on the top ranked retrieved documents. We report experiments on the SOCO-2014 dataset comprising 12K Java source files with almost 1M lines of code. Our experiments confirm that the AST based approach produces significantly better retrieval effectiveness than a standard BoW representation, i.e., the AST based approach is able to identify a higher number of plagiarized source code documents at top ranks in response to a query source code document. The supervised classifier, trained on features extracted from sample plagiarized source code pairs, is shown to effectively filter and thus further improve the ranked list of retrieved candidate plagiarized documents.