IMPACTS in natural language generation NLG between technology and applications : workshop at Schloss Dagstuhl, Germany July 26-28, 2000

Instructional text, because it is a useful and relatively constrained sub-Ianguage, has been a popular target for research-oriented generation systems. This work has demonstrated that existing technology is adequate for generating draft instructions; the problem, as is typical of generation work in general, has been with the acquisition of domain and lexicogrammatical knowledge. This acquisition task is a formidable barrier to the practical use of generation technology. The Isolde project attempts to address this problem by extracting parts of the required knowledge from existing models and by building tools to tailor what is extracted into a form suitable for generation

FPGA in-the-loop implementation of direct torque control for induction motor

In this study, the hysteresis based direct torque control (DTC) of a three-phase induction motor was carried out experimentally. The DTC algorithm was also modelled in the hardware environment by using FPGA’s in-the-loop feature. The dSPACE DS1103 controller board was used in the experimental study and Altera DE2-115 model development board was used in the hardware modelling. Both applications had the same sample time and all of the DTC algorithm was tested within the FPGA. The hardware simulation study conducted in FPGA environment was carried out in MATLAB/Simulink environment. The experimental results were compared with the hardware simulation results obtained from FPGA. As a result of the comparison, it was shown that DTC algorithm could be realized easily in FPGA environment without experimental installation, and the obtained current, voltage and velocity graphs were similar

Improvement of structural dynamic finite elements responses by using super elements and structuring

Bu çalışmada yapısal dinamik problemlerin analizlerinde sonlu elemanlar yöntemi ile elde edilen cevaplarının süper elemanlar ile iyileştirilmesi incelenmiştir. Geliştirilen yeni model derecesi düşürme (MDD) yaklaşımları ile olumlu sonuçlar elde edilmiştir. Bu yeni yaklaşımlar sistem zaman cevaplarının eşitliğini sağlayacak serbestlik derecelerinin aktif serbestlik dereceleri olarak MDD uygulanmış sistemin içine taşınması temeline dayanmaktadır. Hazırlanan Matlab kodları ile geliştirilen model derecesi düşürme yöntemi örnek yapılara uygulanmış ve alınan zaman cevabı sonuçları, orijinal modelin sonuçları ile karşılaştırılmıştır. Tüm bu karşılaştırmalarda Rayleigh sönüm modeline uygun farklı katılık orantılı sönüm matrisi durumları dikkate alınmış ve farklı model dereceleri için hesaplama zamanları açısından sonuçlar değerlendirilmiştir. Ayrıca farklı MDD teknikleri ile elde edilen sistem toplam enerji miktarı orijinal modelin toplam enerjisi ile karşılaştırılmıştır. Çalışmada alt yapılara bölme (AYB)-“Substructuring” yöntemi de incelenmiştir. Geliştirilen Matlab kodu ile plak sistemleri üzerinde AYB uygulamları yapılmış, sonuçlar orijinal model cevabı ile karşılaştırılmıştır. Oluşturulan süper elemanların kullanılması ile de hesaplama zamanları önemli ölçüde düşürülmüştür. Ancak süper eleman oluşturmaya harcanan zamanın yüksek olduğu ve AYB yönteminin geliştirilen MDD yönteminden daha kötü performans gösterdiği görülmüştür. Yapılan tüm karşılaştırmalar sonucunda çalışmada incelenen yöntemlerin çok düşük olan sönüm durumları dışında, orijinal model ile uyumlu zaman ve frekans cevapları verdiği, MDD uygulanmış sistemin orijinal model ile aynı enerji seviyelerinde bulunduğu ve karşılaştırılan diğer MDD yöntemlerinden çok daha az hesaplama zamanına ihtiyaç duyulduğu görülmüştür.  Anahtar Kelimeler: Sonlu elemanlar yöntemi, model derecesi düşürme, alt yapılara bölme, süper eleman.In this study, the responses obtained by the Finite Element Analyses of structural dynamic problems are studied. With the developed model order reduction approach, some improvements have been gained. The developed model order reduction method is essentially based on the equality of the total energies of both original and reduced systems and therefore it is named as “Equality of the total energies”. In the new approach, respecting the degrees of freedoms (DOF)s that give responses conforming with original system is assumed as the main criteria for selection of active DOFs. In this study, the main significant step is the selection of the active DOFs according to their influence to the system time response. The groups of active are application points of the external loadings and the DOFs having high stress or deflection values maximum because they are very important to reveal the right system response. For better accuracy, DOFs close to loading application points are also transferred into reduced system. Heuristic method had been also used for the selection of the active DOFs by some trials and errors to get better consistency between the original system response and reduced system response. Developed model order reduction method was applied to a sample 2D truss system and cantilever plate by some Matlab codes, and the results of the reduction analyses are compared with the original system responses in response to various loadings, eg. İmpulse, step and sinusoidal inputs. In the same Matlab codes, time responses of some other model order reduction methods –Forward differences, Newmark integration and impulse response invariant (IRI)- are also implemented to the same original model. Various Rayleigh damping models for the sample system are taken into account in all these comparisons and the results of analyses for different model orders are evaluated in terms of calculation time and accuracy. Frequency domain responses of the original and the reduced systems by different approaches are also compared with each other based on Bode diagrams by considering the stiffness proportional damping. In parallel, the total energy levels of the reduced systems are also compared with the original system energy level. While auditing of the system responses and Bode diagrams, it is noted that the compatibility of both the original and the reduced systems increases in parallel with the stiffness proportional damping value. In evaluation of the results, it could be expressed that the change in stiffness proportional damping value does not affect the calculation time. While comparing the total energies of original and reduced systems, it is observed that their consistency is good enough to state that both systems have the same system characteristic. Bode diagrams which reflect frequency response of a system, are assumed to be the main criteria to evaluate the performance of the reduced system for both high and low frequencies. It is concluded in general that when the number of an element type used in the analyses decreases, the amount of the DOFs which could be omitted from the original system increases and also the order of the reduced system decreases by keeping the same expected accuracy. As a result of observation, the limit of the model order reduction depends on the selected elemen type. Another conclusion is that general behavior of the damped or undamped systems do not affect the selected element numbers for the reduced system. In the study, substructing method is also taken into considerations. By using Matlab codes, substructuring is implemented into a plate system and the results are compared with the original system. It is observed that the calculation time is extremely reduced by using super elements Nevertheless, since the time for calculation of super elements is long, it is seen that substructuring exhibits worse performance than developed model order reduction method. After all comparisons, it is noted that the developed method gives compatible time and frequency responses with the original model except too low stiffness proportional dampings. It is also observed that the energy level of the reduced system obtained by this new model order reduction method is almost the same with the energy level of the original model. Finally, the most advantageous feature of equality of the total energies method was determined on the calculation time and it needs less calculation time than the other compared model order reduction methods during all examples carried out in the study. Keywords: Finite element method, model order reduction, substructuring, super element

PRECURSORS OF EARTHQUAKES: VLF SIGNALSIONOSPHERE IONOSPHERE RELATION

lot of people have died because of earthquakes every year. Therefore It is crucial to predict the time of the earthquakes reasonable time before it had happed. This paper presents recent information published in the literature about precursors of earthquakes. The relationships between earthquakes and ionosphere are targeted to guide new researches in order to study further to find novel prediction methods

Power Quality Event Detection Using a Fast Extreme Learning Machine

Monitoring Power Quality Events (PQE) is a crucial task for sustainable and resilient smart grid. This paper proposes a fast and accurate algorithm for monitoring PQEs from a pattern recognition perspective. The proposed method consists of two stages: feature extraction (FE) and decision-making. In the first phase, this paper focuses on utilizing a histogram based method that can detect the majority of PQE classes while combining it with a Discrete Wavelet Transform (DWT) based technique that uses a multi-resolution analysis to boost its performance. In the decision stage, Extreme Learning Machine (ELM) classifies the PQE dataset, resulting in high detection performance. A real-world like PQE database is used for a thorough test performance analysis. Results of the study show that the proposed intelligent pattern recognition system makes the classification task accurately. For validation and comparison purposes, a classic neural network based classifier is applied

Bundle Extreme Learning Machine for Power Quality Analysis in Transmission Networks

This paper presents a novel method for online power quality data analysis in transmission networks using a machine learning-based classifier. The proposed classifier has a bundle structure based on the enhanced version of the Extreme Learning Machine (ELM). Due to its fast response and easy-to-build architecture, the ELM is an appropriate machine learning model for power quality analysis. The sparse Bayesian ELM and weighted ELM have been embedded into the proposed bundle learning machine. The case study includes real field signals obtained from the Turkish electricity transmission system. Most actual events like voltage sag, voltage swell, interruption, and harmonics have been detected using the proposed algorithm. For validation purposes, the ELM algorithm is compared with state-of-the-art methods such as artificial neural network and least squares support vector machine

Bundle Extreme Learning Machine for Power Quality Analysis in Transmission Networks

This paper presents a novel method for online power quality data analysis in transmission networks using a machine learning-based classifier. The proposed classifier has a bundle structure based on the enhanced version of the Extreme Learning Machine (ELM). Due to its fast response and easy-to-build architecture, the ELM is an appropriate machine learning model for power quality analysis. The sparse Bayesian ELM and weighted ELM have been embedded into the proposed bundle learning machine. The case study includes real field signals obtained from the Turkish electricity transmission system. Most actual events like voltage sag, voltage swell, interruption, and harmonics have been detected using the proposed algorithm. For validation purposes, the ELM algorithm is compared with state-of-the-art methods such as artificial neural network and least squares support vector machine

Mass mortality in endangered fan mussels Pinna nobilis (Linnaeus 1758) caused by co-infection of Haplosporidium pinnae and multiple Vibrio infection in canakkale Strait, Turkey

Purpos