Campus commons: The calculus of grief

Lee Burdette Williams shares her firsthand experience of her students' resilience in the face of loss.     

What Is Right About Special Education

Abstract

Promoting self-determination has become an important aspect of the educational programs of students with disabilities. There is now a sufficient literature base to support some syntheses that enable researchers to judge their progress in this area to date and to provide direction for future research and practice. For this study, we conducted a literature review of studies that measured or examined global self-determination.     

Cultivating a sense of belonging in part-time students

This study investigated the sense of belonging of part-time students through interviews with 53 novice or experienced students enrolled in part-time programmes in Hong Kong. It was found that students were more easily able to affiliate with their class groups or teaching staff than with their department or university. Seven methods are suggested for promoting a sense of belonging. Class cohesiveness can be developed through learning activities and maintaining classes as a cohort. Relationships with teaching staff can be developed through encouraging interaction, providing good quality teaching and making a positive initial impression. There was also evidence that a sense of belonging was more likely to develop if enrolment was through departments and part-time students had access to resources and facilities. The data showed that promoting a sense of belonging contributed to better quality learning outcomes and increased the chances of students completing programmes.     

Integrierte Entwicklung von Automotive-Software mit AutoFocus

Zur Beherrschung der komplexen vernetzten und verteilten Funktionen von Automotive-Software ist eine Beschreibung des zu erstellenden Systems auf verschiedenen Abstraktionsebenen und schrittweise überg?nge zwischen diesen Ebenen notwendig. Neben der Definition geeigneter Ebenen werden zur Unterstützung echtzeitkritischer Systemanteile ein einheitliches Berechnungsmodell, ebenenspezifische Beschreibungstechniken, sowie methodische Regeln für diese Abstraktionsebenen eingeführt und in den Werkzeugprototypen AutoFocus integriert.     

The information gulag: Rethinking openness in times of national danger

The founding fathers of the United States recognized that freely available information and an educated citizenry were essential to the functioning of a representative democracy. But almost as soon as the ink dried on the Constitution, political forces moved, and have continued to move, to restrict the flow of information from the government to the public, as well as among members of the public. This article examines whether information availability has become a victim of the war on terrorism – whether the nation has entered a time in which legal and policy initiatives are creating information gulags – secreting government information and restricting communications among members of the public, including the academic community. This article explores how policy is shaping the information relationship among the government, the public, academia, and the media and whether new models may be appropriate and more beneficial to society. In doing so, we examine in depth not only public access to government information but also the emerging and vital issue of government restrictions on scholarly exchange, as most recently presented by the legal dispute between the Institute of Electrical and Electronic Engineers (IEEE) and the Office of Foreign Asset Control (OFAC), Department of Treasury, and subsequently the litigation brought by the Association of American University Presses (AAUP).     

Dimensions of variability in embedded operating systems

Design, implementation, and re-engineering of operating systems are still an ambitious undertaking. Despite, or even because, of the long history of theory and practice in this field, adapting existing systems to environments of different conditions and requirements as originally specified or assumed, in terms of functional and/or non-functional respects, is anything but simple. Especially this is true for the embedded systems domain which, on the one hand, calls for highly specialized and application-aware system abstractions and, on the other hand, cares a great deal for easily reusable implementations of these abstractions. The latter aspect becomes more and more important as embedded systems technology is faced with an innovation cycle decreasing in length. Software for embedded systems needs to be designed for variability, and this is in particular true for the operating systems of this domain. The paper discusses dimensions of variability that need to be considered in the development of embedded operating systems and presents approaches that aid construction and maintenance of evolutionary operating systems. CR subject classification  C.3; D.2.11; D.2.13; D.4.7     

Efficient reverse k-nearest neighbor estimation

The reverse k-nearest neighbor (RkNN) problem, i.e. finding all objects in a data set the k-nearest neighbors of which include a specified query object, has received increasing attention recently. Many industrial and scientific applications call for solutions of the RkNN problem in arbitrary metric spaces where the data objects are not Euclidean and only a metric distance function is given for specifying object similarity. Usually, these applications need a solution for the generalized problem where the value of k is not known in advance and may change from query to query. In addition, many applications require a fast approximate answer of RkNN-queries. For these scenarios, it is important to generate a fast answer with high recall. In this paper, we propose the first approach for efficient approximative RkNN search in arbitrary metric spaces where the value of k is specified at query time. Our approach uses the advantages of existing metric index structures but proposes to use an approximation of the nearest-neighbor-distances in order to prune the search space. We show that our method scales significantly better than existing non-approximative approaches while producing an approximation of the true query result with a high recall.