A Relational Model of Workplace Victimization: Social Roles and Patterns of Victimization in Dyadic Relationships.

This article proposes a model of the ways in which dyadic interactions between employees who occupy 1 of 4 archetypal social roles in organizations can lead to either episodic or institutionalized patterns of victimization. The model shows how the occurrence of victimization involving these 4 role types is influenced by organizational variables such as power differences, culture, and access to social capital. The model integrates behavioral and social structural antecedents of victimization to develop a relational perspective on the dynamics of harmful behavior in the workplace. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

„Patriot“

Ohne Zusammenfassung     

OC-48、OC-192芯片和系统设计师面临挑战

当今，从事OC-48、OC-192技术的设计师在设计基于因特网协议(IP协议)的下一代系统时，因系统含有诸如ASIC、网络处理器(NP)、高速跟踪器等元件，以及分组SONET物理层(PoS-PHY)接口规范等的演变，而一直面临挑战。抖动和扭斜失真等现象的存在给诸如系统分组接口第4层(SPI-4)和通用交换接口(CSIX)等总线结构本已拥挤的时序容限，以及四元数据率静态RAM传送表访问时间带来极大混乱。再加上诸如低压差分信号(LVDS)、高速收发逻辑和短线串行终端逻辑等超低电压峰-峰信号技术的引入，使数据出错的可能性变得异常之高。而利用仿真技…     

Meßtechnik zur Charakterisierung von Gas/Flüssigkeits-Reaktoren

Measuring techniques for characterizing gas/liquid reactors . The article considers measuring techniques for the characterization of the phases in gas/liquid reactors. These include the velocity profile and turbulence in the continuous phase as well as holdup, size, and velocity of the dispersed phase. Also, methods for the determination of the specific interfacial area and the volumetric mass transfer coefficients are discussed. Measuring methods have made enormous advances in recent years. In spite of this, there is a lack of reliable methods, especially for use during reactions without disturbing the state of the reactor. It is suspected that probe technique will gradually fall into disuse and more and more attention will be focussed on contractless methods. This calls for further development of ultrasonic methods and methods relying on emission of light.     

Comparison of Markov model and fault tree approach in determining initiating event frequency for systems with two train configurations

This study explores the use of Markov models in some areas of systems analysis in which time evolution of the system may be a significant factor in influencing the system reliability or availability. Comparisons are made between the Markov models and the time-averaged fault tree models for determining support system failure initiating event frequency in a nuclear power plant, for both power and shutdown conditions. Factors affecting consistency between the fault tree approach and the Markov model approach are studied for systems with common two train configurations. A correlation is developed to estimate the ratio between initiator frequencies through both approaches for a two parallel component system. Insights are developed as to when time averaged and simplified fault tree models support a good approximation to the more rigorous time-dependent Markov models.     

Object-extending class transformations

Reorganisation and evolution of class hierarchies is important for object-oriented system development and has received considerable attention in the literature. The contributions of this paper are: (1) a formal study of a set of extension relations and transformations on class hierarchies; (2) a presentation of a small set of primitive transformations which form a minimal and complete basis for the extension relations; and (3) an analysis of the impact of these transformations at the object level.The study leads to a better understanding of evolution and reuse of object-oriented software and class hierarchies. It also provides a terminology and a means of classification for design reuse. The theory presented in this paper is based on the Demeter data model, which gives a concise mathematical foundation for classes and their inheritance and part-of relationships. Parts of the theory have been implemented in the Demeter System ^TM C++, a CASE tool for object-oriented design and programming.     

Prognose von 15 Zeitreihen der DGOR mit Neuronalen Netzen

In 1982, the working group “Forecasting Methods” of the Deutsche Gesellschaft für Operations Research (DGOR) carried out a forecasting comparison between 12 various models which were applied to 15 time series. The results of this study can be considered as a good benchmark for further prediction techniques. This paper reports upon the prediction of these 15 time series by using a Neural Network which was developed by the Backpropagation algorithm. The four highest autocorrelated lag-variables were used as the input variables of the Neural Network. The results show that the Neural Network delivered worse predictions than the other methods including the naive prediction by forecasting non-stationary time series. Stationary time series could be predicted better than the naive prediction, but in comparison to the other techniques the results were only average. After regarding the problem of non-stationarity by using the Dickey-Fuller-Test, first differences were chosen as the input-variables of the Neural Network. In this case, there was a considerable improvement, but the best method (Box-Jenkins' ARIMA technique) could not be surpassed.