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。     

Analysis of Statistical Question Classification for Fact-Based Questions

Question classification systems play an important role in question answering systems and can be used in a wide range of other domains. The goal of question classification is to accurately assign labels to questions based on expected answer type. Most approaches in the past have relied on matching questions against hand-crafted rules. However, rules require laborious effort to create and often suffer from being too specific. Statistical question classification methods overcome these issues by employing machine learning techniques. We empirically show that a statistical approach is robust and achieves good performance on three diverse data sets with little or no hand tuning. Furthermore, we examine the role different syntactic and semantic features have on performance. We find that semantic features tend to increase performance more than purely syntactic features. Finally, we analyze common causes of misclassification error and provide insight into ways they may be overcome.     

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.     

Concept Relationships in Knowledge Organization Systems: Elements for Analysis and Common Research Among Fields

Knowledge organization systems have been studied in several fields and for different and complementary aspects. Among the aspects that concentrate common interests, in this article we highlight those related to the terminological and conceptual relationships among the components of any knowledge organization system. This research aims to contribute to the critical analysis of knowledge organization systems, especially ontologies, thesauri, and classification systems, by the comprehension of its similarities and differences when dealing with concepts and their ways of relating to each other as well as to the conceptual design that is adopted.     

Some Aspects of the Development of the All-Russian Institute for Scientific and Technical Information

Although the USSR and the United States had a comparable number of employees in the field of scientific information, there was a substantial difference in funding, which resulted in a lack of information support for Soviet scientists. While 90% of the publications in the United States were available almost immediately after their release, in the USSR they were delayed by 1.5 to 2 years. Since the publication of the Abstracts Journal by VINITI (AJ), its content was consistently expanding and reached its peak in 1990 (1.5 million documents per year). The next quarter of a century was characterized by a decline in both the composition of the AJ and the time required for its document coverage. The steps for restructuring VINITI activities are discussed. The focus is made on improving the limited coverage of the Russian-language part of the global flow of scientific information by Western information systems.     

Scientometric Instruments of Research Funding

The issues related to funding of public research organizations are explored. The history of scientometric information systems is outlined. The advantages and disadvantages of a bibliometric approach to financing of research organizations are analyzed. The link between the assessment of the scientific and technological potential of an institution and the optimal allocation of funds is investigated. Recommendations on how to improve the efficiency of public resources allocated for scientific research are presented.