Forschungs- und Entwicklungsprojekte Virtuelle Maschinen: zSeries- und S/390-Partitionierung

Der gleichzeitige Betrieb mehrerer Gast-Betriebssysteme auf einem einzigen physischen Rechner unter einem Host-Betriebssystem ist eine leistungsfähige moderne Entwicklung. Bekannte Beispiele sind VMware für die IA32-Architektur sowie das Betriebssystem z/VM und die PR/SM-LPAR Einrichtungen der zSeries-Architektur. Die Nutzung eines Betriebssystems als Gast bedingt einen Leistungsverlust. Die als Partitionierung bezeichnete Zuordnung von Systemressourcen zu den einzelnen Gast-Betriebssysteme ist schwierig, wenn eine dynamische Anpassung an sich ändernde Lastprofile erforderlich ist. Diese Probleme lassen sich mittels Erweiterungen der Hardwarearchitektur adressieren, sowie durch Softwarestrukturen, welche diese Erweiterungen nutzen. Die Erweiterungen der Hardwarearchitektur gehen über das hinaus, was auf heutigen Rechnerarchitekturen wie IA32 oder Mips verfügbar ist. Der vorliegende Beitrag erläutert den optimalen Betrieb von Gast-Betriebssystemen und die begleitenden Partitionierungsmöglichkeiten auf der zSeries-Plattform und beschreibt die zusätzlichen Hardware- und Software-Einrichtungen, welche dies ermöglichen.     

传媒经济学研究的历史、方法与范例

本文主要回顾了传媒经济学在西方的发展历程、研究方法以及不同时期的研究议题。传媒经济学是构建于不同的经济学理论和分析方法之上的应用性学科,它致力于研究经济和金融力量如何影响传媒体系和传媒组织。西方传媒经济学创建于20世纪50年代,至今已发展成为一个活跃的和跨学科研究领域。文章认为,西方传媒经济学的主要研究范例包括理论型、应用型和批评型范例;其研究方法可分为行业市场研究、公司研究和影响力研究。在介绍西方传媒经济学研究的同时,本文还简要回顾了传媒经济学在中国的兴起与发展。     

Lighting the Shroud of Turin for Exhibition in 2015

ABSTRACT

Lighting a cultural heritage artifact requires balancing visual perception with preventive conservation, by providing the best lighting (in terms of spectral distribution and quantity) to enable the viewer to appreciate details and color, while limiting photo-induced degradation. The paper outlines the methodology applied by a multi-disciplinary team while lighting the Shroud of Turin at its last public exhibition in 2015. The methodology considered the special requirements of the Shroud, including exposure to ultraviolet light, while providing appropriate display conditions that would meet audience expectations. The desired appearance (readability of the body image and color) was defined with the help of Shroud researchers and confirmed by subjective tests, while appropriate light levels for preservation were set in agreement with standard requirements and using knowledge of the degradation of linen in visible and UV light. The installation provided a controlled environment and a managed visitor route to the Shroud, assuring excellent perception of both details and color, with the lowest illuminance level about 15?lx.     

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.     

Spanish historic archives’ use of websites as a management transparency vehicle

Against the backdrop of Spain’s Transparency Act, this article discusses the presence or otherwise of a series of document types, proposed as management-related transparency indicators, on 61 (8 national and 53 provincial) historic archive websites. Although examples of good practice were identified, the information provided was found to be scant, in particular as regards lines of action, organisational objectives and yearly reports. The information most commonly provided on the websites included the collection classification chart, service use regulations and citizen charters. The inference drawn was that archives, so intently focused on their role in the application of the Act by the organisations they serve, neglect their own administrative obligations in respect of its provisions. The recommendation is that as government-funded and subsidised public service institutions, historic archives should exercise transparency by furnishing the information stipulated in the Act on their websites.     

Applying LDA Topic Modeling in Communication Research: Toward a Valid and Reliable Methodology

ABSTRACT

Latent Dirichlet allocation (LDA) topic models are increasingly being used in communication research. Yet, questions regarding reliability and validity of the approach have received little attention thus far. In applying LDA to textual data, researchers need to tackle at least four major challenges that affect these criteria: (a) appropriate pre-processing of the text collection; (b) adequate selection of model parameters, including the number of topics to be generated; (c) evaluation of the model’s reliability; and (d) the process of validly interpreting the resulting topics. We review the research literature dealing with these questions and propose a methodology that approaches these challenges. Our overall goal is to make LDA topic modeling more accessible to communication researchers and to ensure compliance with disciplinary standards. Consequently, we develop a brief hands-on user guide for applying LDA topic modeling. We demonstrate the value of our approach with empirical data from an ongoing research project.     

Scaling up Content Analysis

ABSTRACT

Employing a number of different standalone programs is a prevalent approach among communication scholars who use computational methods to analyze media content. For instance, a researcher might use a specific program or a paid service to scrape some content from the Web, then use another program to process the resulting data, and finally conduct statistical analysis or produce some visualizations in yet another program. This makes it hard to build reproducible workflows, and even harder to build on the work of earlier studies. To improve this situation, we propose and discuss four criteria that a framework for automated content analysis should fulfill: scalability, free and open source, adaptability, and accessibility via multiple interfaces. We also describe how to put these considerations into practice, discuss their feasibility, and point toward future developments.     

Placing Facebook

Facebook is challenging professional journalism. These challenges were evident in three incidents from 2016: the allegation that Facebook privileged progressive-leaning news on its trending feature; Facebook’s removal of the Pulitzer Prize-winning “Napalm Girl” photo from the pages of prominent users; and the proliferation of “fake news” during the US presidential election. Using theoretical concepts from the field of boundary work, this paper examines how The Guardian, The New York Times, Columbia Journalism Review and Poynter editorialized Facebook’s role in these three incidents to discursively construct the boundary between the value of professional journalism to democracy and Facebook’s ascendant role in facilitating essential democratic functions. Findings reveal that these publications attempted to define Facebook as a news organization (i.e., include it within the boundaries of journalism) so that they could then criticize the company for not following duties traditionally incumbent upon news organizations (i.e., place it outside the boundaries of journalism). This paper advances scholarship that focuses on both inward and outward conceptions of boundary work, further explores the complex challenge of defining who a journalist is in the face of rapidly changing technological norms, and advances scholarship in the field of media ethics that positions ethical analysis at the institutional level.