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The purpose of this paper is to analyze topics as alternative features for sentiment analysis in Indonesian tweets.

Given Indonesian tweets, the processes of sentiment analysis start by extracting features from the tweets. The features are words or topics. The authors use non-negative matrix factorization to extract the topics and apply a support vector machine to classify the tweets into its sentiment class.

The authors analyze the accuracy using the two-class and three-class sentiment analysis data sets. Both data sets are about sentiments of candidates for Indonesian presidential election. The experiments show that the standard word features give better accuracies than the topics features for the two-class sentiment analysis. Moreover, the topic features can slightly improve the accuracy of the standard word features. The topic features can also improve the accuracy of the standard word features for the three-class sentiment analysis.

The standard textual data representation for sentiment analysis using machine learning is bag of word and its extensions mainly created by natural language processing. This paper applies topics as novel features for the machine learning-based sentiment analysis in Indonesian tweets.

On July 3, 1974, Dr Herbert Grunewald succeeded Professor Dr Kurt Hansen as chairman of the Board of Management of Bayer AG, Leverkusen. Professor Hansen was appointed chairman of the Supervisory Board in succession to Professor Dr Otto Bayer, now honorary chairman of this Board.

This paper reports the results of the information retrieval project PADOK‐II. This project, which began in November 1987, is being carried out by the Linguistic Information Science Group of the University of Regensburg (LIR) in cooperation with the German Patent Office (GPO) and is sponsored by the German Ministry for Research and Technology. The long‐term aim is to integrate artificial intelligence into information retrieval research without neglecting traditional information retrieval methodology. In PADOK‐II an information retrieval system is considered which indexes documents rather shallowly using free‐text or morphological components. A large‐scale retrieval test has been carried out, based on the German Patent Information System. Answers have been obtained to some 400 queries made by 10 users in simulated real‐life situations. These results have been used to attempt to answer the question: ‘How do the linguistically‐based functions of an indexing system contribute to its performance?’ As a spinoff of this test, the influence of document size and structure was studied with a view to identifying the most reasonable basic content for a German Patent Information System.

During oral exams at the German distance learning university, we noticed that students fear that they will be faced with questions that they have not anticipated. In our opinion, this is mainly because students have no chance to train and thereby gather positive experiences with exam situations as they are distributed all over Germany and thus it is difficult for them to meet each other. In this paper, we present a design space of 23 learning gadgets, i.e. tools that support collaborative learning, to allow collaborative exam preparation in peer‐based distributed student groups. We discuss this design space according to eight dimensions of the concept of FLOW (Csikszentmihalyi, 1991) that constitutes enjoyable situations. Two of the learning gadgets were implemented and integrated in the CURE environment, a web‐based collaborative learning platform that was developed to support different collaborative learning scenarios, e.g. collaborative exercises or virtual seminars. We discuss these learning gadgets in more detail and show how they promise an enjoyable collaborative exam preparation.

4 Heat exchanger experiments To study the performance of the ferritic 18 Cr‐2 Mo steel under actual heat exchanger conditions, large scale model heat exchangers were fabricated. After experiments to fabricate heat exchanger plates under standard stretch‐forming conditions, our investigations were confined to heat exchangers of the tubular type.

An explanation is given of the physical factors which govern the influence of the speed of sound on the drag, of an aeroplane, and on its performance. Observing the processes at the point of stagnation, the criterion for the compressibility influence is the Machs number, the introduction of which is also explained.

Developing professional identities as both researchers and teachers is core to doctoral students’ growth. Given the primacy of research for the university career, this study aimed at answering the following questions: how much do doctoral students identify with the teacher compared to the researcher role? Can the teacher role identity be purposely activated?

In an experimental study with 167 psychology PhD students, trait role identification was measured using a questionnaire. Afterward, participants were randomly assigned to one of three conditions differing in the picture material (research vs teaching pictures vs a mixture of both) provided for creating a collage reflecting their roles. Subsequently, answers to open questions were coded and quantified as indicators of state role identity.

As a trait, doctoral students identified more strongly with their researcher role than with their teacher role. Teacher role identity as a state was successfully activated when doctoral students engaged with teaching pictures compared to the other conditions.

As the researcher role seems to be the default setting for PhD students, activation of the teacher role has the potential to benefit work satisfaction of PhD students and the quality of their teaching.

Taking both long- and short-term identification processes in PhD students into account is a promising new approach. Besides, quantitative data are added to the field of qualitative insights on PhD students’ professional roles.

The purpose of this paper is to develop a fast and accurate analytic model function for the single-valued H-B curve of ferromagnetic materials, where hysteresis can be disregarded (normal magnetization curve). Nonlinear magnetoquasistatic simulations demand smooth monotone material models to ensure physical correctness and good convergence in Newton's method.

The Brauer model has these beneficial properties, but is not sufficiently accurate for low and high fields in the normal magnetization curve. The paper extends the Brauer model to better fit material behavior in the Rayleigh region (low fields) and in full saturation. Procedures for obtaining optimal parameters from given measurement points are proposed and tested for two technical materials. The approach is compared with cubic spline and monotonicity preserving spline interpolation with respect to error and computational effort.

The extended Brauer model is more accurate and even maintains the computational advantages of the classical Brauer model. The methods for obtaining optimal parameters yield good results if the measurement points have a distinctive Rayleigh region.

The model function for ferromagnetic materials enhances the precision of the classical Brauer model without notable additional simulation cost.