Refine
Document Type
- Article (20)
- Conference Object (14)
- Report (13)
- Part of a Book (7)
- Working Paper (6)
- Book (2)
- Contribution to a Periodical (2)
- Doctoral Thesis (1)
Year of publication
Language
- English (34)
- German (26)
- Multiple languages (5)
Keywords
- Hochschule (2)
- Internationales Marketing (2)
- Online-Marketing (2)
- Produktionstheorie (2)
- Studierende (2)
- Website (2)
- Agile production (1)
- Arbeitsethik (1)
- Arbeitsverhalten (1)
- Chaos (1)
Despite the small number of applications to date, neural networks are likely to be able to contribute to decision support in selected fields of R&D management. We identify the potential of neural networks in the application domain and compare it to 'classical' applications, such as the recognition of hand-written characters. Typical neural network architectures for R&D management tend to be simple, having low complexity, and only a small number of training samples are generally available. As an example, we carry out experiments for a typical R&D management application where neural networks have to estimate the final cost of a new product under development. It turns out that neural networks based on the standard backpropagation learning algorithm perform reasonably well when the ratio between highest and lowest cost is small, even for relatively small training set sizes. Otherwise the learning algorithm tends to undervalue low cost levels, so that deviations between estimated cost and real cost are intolerably high. Future research will have to investigate a modification of the error definition of the backpropagation algorithm. Finally, a number of general statements are derived from our experience, and examples are provided where neural networks are appropriate or inappropriate in the domain of R&D management.
Usually, knowledge to be learned by neural networks is represented implicitly in the training samples. The ability to insert knowledge apart from the implicit representations in training samples (“background knowledge”) gives rise to the hope that the learning and operation behavior of neural networks can be improved. In this paper, we develop a method to accomplish the insertion of expert knowledge into the error function during training.
Continued growth in international experiences for U.S. co++6llege students is a favorable trend. However, the most substantial increase has occurred with of short-term study abroad programs. Many of these programs include extensive travel instead of involving a single site. There is great danger that if not properly managed, these types of international educational experience will default into little more than an organized group tour.
In these types of programs it is challenging to induce student participants to engage meaningfully with local residents as the traveling group tends to form into its own portable society. In addition, the current state of wireless communications means that students participating in these types of programs can easily stay plugged into their home social networks which further reduces meaningful interactions in the cultures being visited.
Incorporating well designed research projects into short-term study abroad programs holds the potential to offset some of the inherent limitations of such programs. Research projects can serve both to prepare the students for the trip and promote meaningful cross-cultural interaction while the program is underway.
In this paper, the authors provide suggestions based on their experiences with short-term travel abroad programs which incorporated student research. Several potential problems are identified and suggestions are given for project design.
Die Internetpräsenz einer Hochschule ist für ausländische Studierende häufig die erste Informationsquelle auf der Suche nach einem geeigneten Studienstandort. Um die Website für die Nutzer besonders verständlich zu gestalten, sollten neben den grundlegenden Regeln des Webdesigns einige elementare Gestaltungshinweise beachtet werden. Der Leitfaden gibt dazu Anregungen und wertvolle Tipps.
A framework of decision‐support systems in advanced manufacturing enterprises ‐ a systems view
(1997)
Analyses the environment and characteristics of an advanced manufacturing system (AMS). It is an open system with a multi‐layer structure and a self‐organizing ability capable of responding to a continuous changing and unpredictable environment in this information age. Based on the analysis, summarizes the requirements of decision processes in a typical AMS, and presents a framework of a decision‐support system (DSS) in an advanced manufacturing enterprise. Outlines the conceptual modelling of the system, explains the work carried out by an inter‐disciplinary team composed of researchers from the 863/CIMS/I‐MADIS, a national hi‐tech R&D programme in China and a joint research programme in computer integrated manufacturing management between the City University of Hong Kong and Tsinghua University, Beijing. 863/CIMS is one of the subject themes under the auspices of automation technology of the National High Technology Research and Development Programme of China launched by the government in March 1986.
Wissen vermitteln, Binnendifferenzierung realisieren, individuelle Besorgnis zeigen, Interesse wecken, Praxisbezug herstellen, optimale Lernatmosphäre schaffen, digitale Instrumente einbinden, Interdisziplinarität zeigen, das Gefühl vermitteln, etwas gelernt zu haben – und nicht zuletzt curricular verankerte Lernziele erreichen und ein angemessenes Evaluationsergebnis erreichen: Das Aufgabenspektrum von Hochschullehrenden ist groß. Den klassischen „Vorlesenden“, der Lehrbuchinhalte minimalst visualisiert vorträgt, gibt es bei Weitem weniger als früher, allerdings ist zu fragen, wohin sich dieses Rollenverständnis im Hinblick auf Kompetenzen und Fähigkeiten entwickelt hat. Dieser Beitrag soll die Anforderungen aus der praktischen Lehre mit Forschungsergebnissen verknüpfen und anhand eines konkreten Lehrprojekts zeigen, mit welchen Methoden die Änderung des Rollenverständnisses zielorientiert gelingen kann.
