From text to codings: intercoder reliability assessment in qualitative content analysis

BACKGROUND: High intercoder reliability (ICR) is required in qualitative content analysis for assuring quality when more than one coder is involved in data analysis. The literature is short of standardized procedures for ICR procedures in qualitative content analysis. OBJECTIVE: To illustrate how ICR assessment can be used to improve codings in qualitative content analysis. METHODS: Key steps of the procedure are presented, drawing on data from a qualitative study on patients' perspectives on low back pain. RESULTS: First, a coding scheme was developed using a comprehensive inductive and deductive approach. Second, 10 transcripts were coded independently by two researchers, and ICR was calculated. A resulting kappa value of .67 can be regarded as satisfactory to solid. Moreover, varying agreement rates helped to identify problems in the coding scheme. Low agreement rates, for instance, indicated that respective codes were defined too broadly and would need clarification. In a third step, the results of the analysis were used to improve the coding scheme, leading to consistent and high-quality results. DISCUSSION: The quantitative approach of ICR assessment is a viable instrument for quality assurance in qualitative content analysis. Kappa values and close inspection of agreement rates help to estimate and increase quality of codings. This approach facilitates good practice in coding and enhances credibility of analysis, especially when large samples are interviewed, different coders are involved, and quantitative results are presented.

A 45nm CMOS DESIGN OF NEUROMORPHIC SYSTEM

Neuromorphic computing has become an emerging field in wide range of applications. Its challenge lies in developing a brain-inspired architecture that can emulate human brain and can work for real time applications. In this report a flexible neural architecture is presented which consists of 128 X 128 SRAM crossbar memory and 128 spiking neurons. For Neuron, digital integrate and fire model is used. All components are designed in 45nm technology node. The core can be configured for certain Neuron parameters, Axon types and synapses states and are fully digitally implemented. Learning for this architecture is done offline. To train this circuit a well-known algorithm Restricted Boltzmann Machine (RBM) is used and linear classifiers are trained at the output of RBM. Finally, circuit was tested for handwritten digit recognition application. Future prospects for this architecture are also discussed.

Materialien zum Zivilgesetzbuch. Die Erläuterungen von Eugen Huber / Text des Vorentwurfs von 1900

Das Werk eröffnet eine Serie von Bänden, die sich die Publikation der wichtigsten Materialien zum Schweizerischen Zivilgesetzbuch zum Ziel gesetzt hat. Sie sollen den Berner Kommentar zum Schweizerischen Privatrecht um eine kodifikationshistorische Dimension ergänzen und den Ausgangspunkt für die Erläuterungen zum geltenden Recht bilden. Der erste Band ist eigens auf die Centenarfeier des ZGB am 10. Dezember 2007 hin fertig gestellt worden. Er enthält mit den Erläuterungen zum Vorentwurf des Eidg. Justiz- und Polizeidepartements von 1900 das vielleicht schönste und anregendste, sicher aber das monumentalste Werk der Materialien. Es zeugt vom magistralen Überblick Eugen Hubers über den zivilrechtlichen Rechtsstoff und einer Weitsicht, die noch heute Vorbild jeder Gesetzgebungsarbeit sein sollte. Erstmals seit Jahrzehnten wird es wieder einem breiteren Publikum in originalgetreuer Form zugänglich gemacht. Zwecks prägnanter Zitierbarkeit sind Randnoten hinzugefügt worden. Ein Stichwortverzeichnis garantiert die schnelle Auffindbarkeit der Textstellen.