1,483 research outputs found
M. Kittner, M. Kôrner-Damman et A. Schunk, Labour under the Apartheid Régime Practical Problems and Légal Framework of Labour in South Africa
No full textM. Kittner, M. Kôrner-Damman et A. Schunk, Labour under the Apartheid Régime Practical Problems and Légal Framework of Labour in South Africa. In: Revue internationale de droit comparé. Vol. 43 N°1, Janvier-mars 1991. p. 271
M. Kittner, M. Kôrner-Damman et A. Schunk, Labour under the Apartheid Régime Practical Problems and Légal Framework of Labour in South Africa
No full textM. Kittner, M. Kôrner-Damman et A. Schunk, Labour under the Apartheid Régime Practical Problems and Légal Framework of Labour in South Africa. In: Revue internationale de droit comparé. Vol. 43 N°1, Janvier-mars 1991. p. 271
Aus alten Tagebuechern und Erinnerungen der Familien Hirsch, Strupp, Eisenberg /
No full textAnecdotal account of the Hirsch and Worms families. Hyam Worms of Karlsruhe, great-grandfather of the author, was the first Jew to obtain civil rights in Paris in 1794; his son Alphonse was tax comptroller of Paris under Louis XVI, but had to leave Paris during the Napoleonic Wars. Alphonse then founded an export/import business in Karlsruhe. The grandmother of Betty Schunk was a witness in the trial of the outlaw Schinderhannes (1783-1803.)Brief summary in Max Kreutzberger: "Leo Baeck Institute New York, Bibliothek und Archiv; Katalog": C 16
Relevance determination in learning vector quantization
No full textBojer T, Hammer B, Schunk D, Tluk von Toschanowitz K. Relevance determination in learning vector quantization. In: Verleysen M, ed. ESANN'2001. D-facto publications; 2001: 271-276
A Markov Chain Monte Carlo Multiple Imputation Procedure for Dealing with Item Nonresponse in the German SAVE Survey
No full textImportant empirical information on household behavior is obtained from surveys. However, various interdependent factors that can only be controlled to a limited extent lead to unit and item nonresponse, and missing data on certain items is a frequent source of difficulties in statistical practice. This paper presents the theoretical underpinnings of a Markov Chain Monte Carlo multiple imputation procedure and applies this procedure to a socio-economic survey of German households, the SAVE survey. I discuss convergence properties and results of the iterative multiple imputation method and I compare them briefly with other imputation approaches. Concerning missing data in the SAVE survey, the results suggest that item nonresponse is not occurring randomly but is related to the included covariates. The analysis further indicates that there might be differences in the character of nonresponse across asset types. Concerning the methodology of imputation, the paper underlines that it would be of particular interest to apply different imputation methods to the same dataset and to compare the findings.
Modeling the Use of Nonrenewable Resources Using a Genetic Algorithm
No full textThis paper shows, how a genetic algorithm (GA) can be used to model an economic process: the interaction of profit-maximizing oil-exploration firms that compete with each other for a limited amount of oil. After a brief introduction to the concept of multi-agent-modeling in economics, a GA-based resource-economic model is developed. Several model runs based on different economic policy assumptions are presented and discussed in order to show how the GA-model can be used to gain insight into the dynamic properties of economic systems. The remainder outlines deficiencies of GA-based multi-agent approaches and sketches how the present model can be improved.
A Markov Chain Monte Carlo Multiple Imputation Procedure for Dealing with Item Nonresponse in the German SAVE Survey
No full textImportant empirical information on household behavior is obtained from surveys. However, various interdependent factors that can only be controlled to a limited extent lead to unit and item nonresponse, and missing data on certain items is a frequent source of difficulties in statistical practice. This paper presents the theoretical underpinnings of a Markov Chain Monte Carlo multiple imputation procedure and applies this procedure to a socio-economic survey of German households, the SAVE survey. I discuss convergence properties and results of the iterative multiple imputation method and I compare them briefly with other imputation approaches. Concerning missing data in the SAVE survey, the results suggest that item nonresponse is not occurring randomly but is related to the included covariates. The analysis further indicates that there might be differences in the character of nonresponse across asset types. Concerning the methodology of imputation, the paper underlines that it would be of particular interest to apply different imputation methods to the same dataset and to compare the findings.
The Pennsylvania Reemployment Bonus Experiments: How a survival model helps in the analysis of the data
No full textSurvival models for life-time data and other time-to-event data are widely used in many fields, including medicine, the environmental sciences, engineering etc. They have also found recognition in the analysis of economic duration data. This paper provides a reanalysis of the Pennsylvania Reemployment Bonus Experiments, which were conducted in 1988-89 to examine the effect of different types of reemployment bonus offers on the unemployment spell. A Cox-proportional-hazards survival-model is fitted to the data and the results are compared to the results of a linear regression approach and to the results of a quantile regression approach. The Cox-proportional-hazards model provides for a remarkable goodness of fit and yields less effective treatment responses, therefore lower expectations concerning the overall implications of the Pennsylvania experiment. An influence analysis is proposed for obtaining qualitative information on the influence of the covariates at different quantiles. The results of the quantile regression and of the influence analysis show that both the linear regression and the Cox-model still impose stringent restrictions on the way covariates influence the duration distribution, however, due to its flexibility, the Cox-proportional hazards model is more appropriate for analysing the data.
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Abschlussbericht zum BMBF-Forschungsvorhaben - Beitrag der Firma Schunk Kohlenstofftechnik GmbH, Gießen
No full textIm Rahmen des Förderprojektes SoLiS war die Schunk Kohlenstofftechnik GmbH in Arbeitspaket 1.1 daran beteiligt, ein Kohlenstoff-Schwefel-Komposit herzustellen und zu charakterisieren, welches als Kathodenmaterial in Lithium-Schwefel-Feststoffbatterien eingesetzt werden kann. Das technische Ziel dabei war es, den gesamten Schwefel im Komposit durch einen kommerziell erhältlichen und ggf. modifizierten Kohlenstoff für den optimalen Kompromiss aus Leistungs- und Energiedichte elektrisch zu kontaktieren. Auf dem Weg zur Erreichung dieser Zielsetzung sind insgesamt 103 Proben aus unterschiedlichen Materialien
sowie Kombinationen auf unterschiedlichen Prozessrouten entstanden, von denen 34 Muster an die Projektpartner zur elektrochemischen Charakterisierung versandt wurden.
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Spatial Dynamic Modeling and Urban Land Use Transformation:
No full textAssessing the economic impacts of urban land use transformation has become complex and acrimonious. Although community planners are beginning to comprehend the economic trade-offs inherent in transforming the urban fringe, they find it increasingly difficult to analyze and assess the trade-offs expediently and in ways that can influence local decisionmaking. New and sophisticated spatial modeling techniques are now being applied to urban systems that can quickly assess the probable spatial outcomes of given communal policies. Applying an economic impact assessment to the probable spatial patterns can provide to planners the tools needed to quickly assess scenarios for policy formation that will ultimately help inform decision makers. This paper focuses on the theoretical underpinnings and practical application of an economic impact analysis submodel developed within the Land use Evolution and Impact Assessment Modeling (LEAM) environment. The conceptual framework of LEAM is described, followed by an application of the model to the assessment of the cost of urban sprawl in Kane County, Illinois. The results show the effectiveness of spatially explicit modeling from a theoretical and a practical point of view. The agent-based approach of spatial dynamic modeling with a high spatial resolution allows for discerning the macro-level implications of micro-level behaviors. These phenomena are highlighted in the economic submodel in the discussion of the implications of land use change decisions on individual and communal costs; low-density development patterns favoring individual behaviors at the expense of the broader community.
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