Berechnung der Wirbelstromdichten und-kräfte in der Umgebung großer supraleitender Spulen für den magnetischen Einschluß bei der Kernfusion

Übersicht Um die Betriebssicherheit großer supraleitender Magnetsysteme für die Kernfusionsforschung zu gewährleisten, muß die im Magnetsystem gespeicherte Energie schnell entladen werden können. Durch die veränderlichen großvolumigen Magnetfelder werden in benachbarten leitfähigen Strukturen durch Induktion hohe Wirbelströme hervorgerufen. Durch sie treten dort elektromagnetische Kräfte. auf, die einzelne Komponenten mechanisch überlasten können. Zur Berechnung dieser Kräfte wurde eine einfache numerischanalytische Methode entwickelt, die im folgenden vorgestellt und mit Finite-Elemente-Verfahren verglichen wird.

---

Calculation of eddy current densities and forces around large superconducting coils for nuclear fusion

Contents The reliable operation of the superconducting magnet systems used for the magnetic confinement in nuclear fusion research requires the ability of a fast discharge of the stored magnetic energy. The corresponding magnetic field variation gives rise to high eddy currents by inductive coupling with surrounding conductive components. The eddy current forces can lead to a mechanical overload of some of these components. A simple numerical-analytical method was developed in order to calculate these forces. This method is presented and compared with the Finite Element Method.

     

Swarm Intelligent Compressive Routing in Wireless Sensor Networks

This article proposes a novel algorithm to improve the lifetime of a wireless sensor network. This algorithm employs swarm intelligence algorithms in conjunction with compressive sensing theory to build up the routing trees and to decrease the communication rate. The main contribution of this article is to extend swarm intelligence algorithms to build a routing tree in such a way that it can be utilized to maximize efficiency, thereby rectifying the delay problem of compressive sensing theory and improving the network lifetime. In addition, our approach offers accurate data recovery from small amounts of compressed data. Simulation results show that our approach can effectively extend the network lifetime of a large‐scale wireless sensor network.     

Accelerating Boyer–Moore searches on binary texts

The Boyer and Moore (BM) pattern matching algorithm is considered as one of the best, but its performance is reduced on binary data. Yet, searching in binary texts has important applications, such as compressed matching. The paper shows how, by means of some pre-computed tables, one may implement the BM algorithm also for the binary case without referring to bits, and processing only entire blocks such as bytes or words, thereby significantly reducing the number of comparisons. Empirical comparisons show that the new variant performs better than regular binary BM and even than BDM.     

Adaptive ROC-based ensembles of HMMs applied to anomaly detection

Hidden Markov models (HMMs) have been successfully applied in many intrusion detection applications, including anomaly detection from sequences of operating system calls. In practice, anomaly detection systems (ADSs) based on HMMs typically generate false alarms because they are designed using limited amount of representative training data. Since new data may become available over time, an important feature of an ADS is the ability to accommodate newly acquired data incrementally, after it has originally been trained and deployed for operations. In this paper, a system based on the receiver operating characteristic (ROC) is proposed to efficiently adapt ensembles of HMMs (EoHMMs) in response to new data, according to a learn-and-combine approach. When a new block of training data becomes available, a pool of base HMMs is generated from the data using a different number of HMM states and random initializations. The responses from the newly trained HMMs are then combined to those of the previously trained HMMs in ROC space using a novel incremental Boolean combination (incrBC) technique. Finally, specialized algorithms for model management allow to select a diversified EoHMM from the pool, and adapt Boolean fusion functions and thresholds for improved performance, while it prunes redundant base HMMs. The proposed system is capable of changing the desired operating point during operations, and this point can be adjusted to changes in prior probabilities and costs of errors. Computer simulations conducted on synthetic and real-world host-based intrusion detection data indicate that the proposed system can achieve a significantly higher level of performance than when parameters of a single best HMM are estimated, at each learning stage, using reference batch and incremental learning techniques. It also outperforms the learn-and-combine approaches using static fusion functions (e.g., majority voting). Over time, the proposed ensemble selection algorithms form compact EoHMMs, while maintaining or improving system accuracy. Pruning allows to limit the pool size from increasing indefinitely, thereby reducing the storage space for accommodating HMMs parameters without negatively affecting the overall EoHMM performance. Although applied for HMM-based ADSs, the proposed approach is general and can be employed for a wide range of classifiers and detection applications.     

Thermal Stability Investigation of Synthesized Epoxy-Polyurethane/Silica Nanocomposites

Silicon - In this research, epoxy polyurethane-nano silica nanocomposites have been synthesized using an in-situ method, for which SiO2 nanocomposites had been initially ready in N,...     

Scalable and fault‐tolerant key agreement protocol for dynamic groups

With the widespread use of the Internet, the popularity of group communication‐based applications has grown considerably. Since most communications over the Internet involve the traversal of insecure networks, basic security services are necessary for these collaborative applications. These security services can be facilitated if the authorized group members share a common secret. In such distributed applications, key agreement protocols are preferred to key distribution protocols. In the past two decades, there have been many proposals for key agreement protocols. Most of these protocols are not efficient and limit the size of the underlying group. In this paper, we consider the scalability problem in group key agreement protocols. We propose a novel framework based on extension of the Diffie–Hellman key exchange protocol. The efficiency of our protocol comes from the clustering of the group members, where the common session key is established collaboratively by all participants. We present the auxiliary protocols needed when the membership changes. We show that our protocol is superior in complexity in both communication and computation overheads required to generate the session key. Copyright © 2006 John Wiley & Sons, Ltd.     

Transition from traditional to ICT-enhanced learning environments in undergraduate chemistry courses

This paper describes a three-year study conducted among chemistry instructors (professors and teaching assistants) at a post-secondary institution. The goal was to explore the integration process of information and communication technologies (ICT) into traditional teaching. Four undergraduate chemistry courses incorporated a course website, an electronic forum, computerized visualizations, and Web-based projects, into their curriculum. The learning technologies were integrated to enhance inquiry-based learning, visualizations, and knowledge sharing. The current study investigated chemistry instructors’ perceptions toward ICT and their activities while practicing the newly introduced technologies. The findings showed that integrating new practices is a phase-dependent process that consists of promises as well as complexities. Four transition steps were found to characterize the integration of ICT-learning environments: non-active, support-dependant, partial-independant, and total-independant. Findings indicated that the transition from traditional to ICT-enhanced learning environments involves ambivalent feelings and dichotomy among instructors.     

Review of The dissociative mind.

Reviews the book, The dissociative mind by Elizabeth F. Howell (see record 2005-14945-000). In her book, The Dissociative Mind, Elizabeth Howell presents a complex and thorough overview of what she describes as a "sea change" in psychoanalytic theory. From her vantage point as both psychoanalyst and traumatologist, she demonstrates how, in the last 15-20 years, relational trauma and the resulting impact on the individual mind-namely the splits and fissures that comprise dissociation- have made their way back into psychoanalytic thinking. Howell's elaboration of the overwhelmed, traumatized mind is very useful in clients who present with problems in thinking or who have limited capacity to symbolize. However, detailed clinical material of how an analyst thinking of dissociated self states would work with such a client, what Bromberg termed the "relational bridge," would support her fundamental assertions more effectively. (PsycINFO Database Record (c) 2010 APA, all rights reserved)