Investigations on The Finite Size Effects of Some Inverse Spinels and Studies on Their Composites Based on Nitrile Rubber

Magnetism and magnetic materials have been an ever-attractive subject area for engineers and scientists alike because of its versatility in finding applications in useful devices. They find applications in a host of devices ranging from rudimentary devices like loud speakers to sophisticated gadgets like waveguides and Magnetic Random Access Memories (MRAM).The one and only material in the realm of magnetism that has been at the centre stage of applications is ferrites and in that spinel ferrites received the lions share as far as practical applications are concerned.It has been the endeavour of scientists and engineers to remove obsolescence and improve upon the existing so as to save energy and integrate in to various other systems. This has been the hallmark of material scientists and this has led to new materials and new technologies.In the field of ferrites too there has been considerable interest to devise new materials based on iron oxides and other compounds. This means synthesising ultra fine particles and tuning its properties to device new materials. There are various preparation techniques ranging from top- down to bottom-up approaches. This includes synthesising at molecular level, self assembling,gas based condensation. Iow temperature eo-precipitation, solgel process and high energy ball milling. Among these methods sol-gel process allows good control of the properties of ceramic materials. The advantage of this method includes processing at low temperature. mixing at the molecular level and fabrication of novel materials for various devices.Composites are materials. which combine the good qualities of one or more components. They can be prepared in situ or by mechanical means by the incorporation of fine particles in appropriate matrixes. The size of the magnetic powders as well as the nature of matrix affect the processability and other physical properties of the final product. These plastic/rubber magnets can in turn be useful for various applications in different devices. In applications involving ferrites at high frequencies, it is essential that the material possesses an appropriate dielectric permittivity and suitable magnetic permeability. This can be achieved by synthesizing rubber ferrite composites (RFC's). RFCs are very useful materials for microwave absorptions. Hence the synthesis of ferrites in the nanoregirne.investigations on their size effects on the structural, magnetic, and electrical properties and the incorporation of these ferrites into polymer matrixes assume significance.In the present study, nano particles of NiFe204, Li(!5Fe2S04 and Col-e-O, are prepared by sol gel method. By appropriate heat treatments, particles of different grain sizes are obtained. The structural, magnetic and electrical measurements are evaluated as a function of grain size and temperature. NiFel04 prepared in the ultrafine regime are then incorporated in nitrile rubber matrix. The incorporation was carried out according to a specific recipe and for various loadings of magnetic fillers. The cure characteristics, magnetic properties, electrical properties and mechanical properties of these elastomer blends are carried out. The electrical permittivity of all the rubber samples in the X - band are also conducted.

Feature Extraction Methods Based on Linear Predictive Coding and Wavelet Packet Decomposition for Recognizing Spoken Words in Malayalam

Speech signals are one of the most important means of communication among the human beings. In this paper, a comparative study of two feature extraction techniques are carried out for recognizing speaker independent spoken isolated words. First one is a hybrid approach with Linear Predictive Coding (LPC) and Artificial Neural Networks (ANN) and the second method uses a combination of Wavelet Packet Decomposition (WPD) and Artificial Neural Networks. Voice signals are sampled directly from the microphone and then they are processed using these two techniques for extracting the features. Words from Malayalam, one of the four major Dravidian languages of southern India are chosen for recognition. Training, testing and pattern recognition are performed using Artificial Neural Networks. Back propagation method is used to train the ANN. The proposed method is implemented for 50 speakers uttering 20 isolated words each. Both the methods produce good recognition accuracy. But Wavelet Packet Decomposition is found to be more suitable for recognizing speech because of its multi-resolution characteristics and efficient time frequency localizations

A Comparative Study of Wavelet Based Feature Extraction Techniques in Recognizing Isolated Spoken Words

Speech is a natural mode of communication for people and speech recognition is an intensive area of research due to its versatile applications. This paper presents a comparative study of various feature extraction methods based on wavelets for recognizing isolated spoken words. Isolated words from Malayalam, one of the four major Dravidian languages of southern India are chosen for recognition. This work includes two speech recognition methods. First one is a hybrid approach with Discrete Wavelet Transforms and Artificial Neural Networks and the second method uses a combination of Wavelet Packet Decomposition and Artificial Neural Networks. Features are extracted by using Discrete Wavelet Transforms (DWT) and Wavelet Packet Decomposition (WPD). Training, testing and pattern recognition are performed using Artificial Neural Networks (ANN). The proposed method is implemented for 50 speakers uttering 20 isolated words each. The experimental results obtained show the efficiency of these techniques in recognizing speech

PERFORMANCE OF DIFFERENT CLASSIFIERS IN SPEECH RECOGNITION

Speech is the most natural means of communication among human beings and speech processing and recognition are intensive areas of research for the last five decades. Since speech recognition is a pattern recognition problem, classification is an important part of any speech recognition system. In this work, a speech recognition system is developed for recognizing speaker independent spoken digits in Malayalam. Voice signals are sampled directly from the microphone. The proposed method is implemented for 1000 speakers uttering 10 digits each. Since the speech signals are affected by background noise, the signals are tuned by removing the noise from it using wavelet denoising method based on Soft Thresholding. Here, the features from the signals are extracted using Discrete Wavelet Transforms (DWT) because they are well suitable for processing non-stationary signals like speech. This is due to their multi- resolutional, multi-scale analysis characteristics. Speech recognition is a multiclass classification problem. So, the feature vector set obtained are classified using three classifiers namely, Artificial Neural Networks (ANN), Support Vector Machines (SVM) and Naive Bayes classifiers which are capable of handling multiclasses. During classification stage, the input feature vector data is trained using information relating to known patterns and then they are tested using the test data set. The performances of all these classifiers are evaluated based on recognition accuracy. All the three methods produced good recognition accuracy. DWT and ANN produced a recognition accuracy of 89%, SVM and DWT combination produced an accuracy of 86.6% and Naive Bayes and DWT combination produced an accuracy of 83.5%. ANN is found to be better among the three methods.

Syntactic Based Machine Translation from English to Malayalam

Due to the emergence of multiple language support on the Internet, machine translation (MT) technologies are indispensable to the communication between speakers using different languages. Recent research works have started to explore tree-based machine translation systems with syntactical and morphological information. This work aims the development of Syntactic Based Machine Translation from English to Malayalam by adding different case information during translation. The system identifies general rules for various sentence patterns in English. These rules are generated using the Parts Of Speech (POS) tag information of the texts. Word Reordering based on the Syntax Tree is used to improve the translation quality of the system. The system used Bilingual English –Malayalam dictionary for translation.

Automated Transcription System for Malayalam Language

Malayalam is one of the 22 scheduled languages in India with more than 130 million speakers. This paper presents a report on the development of a speaker independent, continuous transcription system for Malayalam. The system employs Hidden Markov Model (HMM) for acoustic modeling and Mel Frequency Cepstral Coefficient (MFCC) for feature extraction. It is trained with 21 male and female speakers in the age group ranging from 20 to 40 years. The system obtained a word recognition accuracy of 87.4% and a sentence recognition accuracy of 84%, when tested with a set of continuous speech data.

Development & evaluation of different acoustic models for Malayalam continuous speech recognition

Performance of any continuous speech recognition system is dependent on the accuracy of its acoustic model. Hence, preparation of a robust and accurate acoustic model lead to satisfactory recognition performance for a speech recognizer. In acoustic modeling of phonetic unit, context information is of prime importance as the phonemes are found to vary according to the place of occurrence in a word. In this paper we compare and evaluate the effect of context dependent tied (CD tied) models, context dependent (CD) and context independent (CI) models in the perspective of continuous speech recognition of Malayalam language. The database for the speech recognition system has utterance from 21 speakers including 11 female and 10 males. Our evaluation results show that CD tied models outperforms CI models over 21%.

Malayalam Isolated Digit Recognition using HMM and PLP cepstral coefficient

Development of Malayalam speech recognition system is in its infancy stage; although many works have been done in other Indian languages. In this paper we present the first work on speaker independent Malayalam isolated speech recognizer based on PLP (Perceptual Linear Predictive) Cepstral Coefficient and Hidden Markov Model (HMM). The performance of the developed system has been evaluated with different number of states of HMM (Hidden Markov Model). The system is trained with 21 male and female speakers in the age group ranging from 19 to 41 years. The system obtained an accuracy of 99.5% with the unseen data

Connected digit speech recognition system for Malayalam language

A connected digit speech recognition is important in many applications such as automated banking system, catalogue-dialing, automatic data entry, automated banking system, etc. This paper presents an optimum speaker-independent connected digit recognizer forMalayalam language. The system employs Perceptual Linear Predictive (PLP) cepstral coefficient for speech parameterization and continuous density Hidden Markov Model (HMM) in the recognition process. Viterbi algorithm is used for decoding. The training data base has the utterance of 21 speakers from the age group of 20 to 40 years and the sound is recorded in the normal office environment where each speaker is asked to read 20 set of continuous digits. The system obtained an accuracy of 99.5 % with the unseen data.

Kompetenzraster aus dem schweizerischen Institut Beatenberg - eine Option für berufliche Schulen in Deutschland?

Der Name einer kleinen Internatsschule im Berner Oberland taucht zunehmend in den Diskussionen über die Gestaltung von selbst organisiertem Lernen auf: Institut Beatenberg. Der Direktor des Instituts, Andreas Müller, und seine Mitarbeiter sind gefragte Referenten auf Veranstaltungen über die Einführung einer Lehr-Lernkultur, die den Lernenden und seine Lernprozesse in den Mittelpunkt der pädagogischen Arbeit stellt. Zudem finden ihre Publikationen zunehmendes Interesse im gesamten deutschsprachigen Raum. Ein Schlüsselinstrument wurde dabei zum Schlagwort: Kompetenzraster. Doch die stellen nur eines der Instrumente dar, die den ‚Wirkungskreislauf des Lernerfolgs’ in Beatenberg stützen. Berufliche Schulen in Hessen und Hamburg haben im Rahmen von Modellprojekten mit der Erarbeitung von Kompetenzrastern nach den Vorbildern in Beatenberg begonnen und versprechen sich damit eine neue, auf selbst organisiertem Lernen aufbauende kompetenzorientierte berufliche Bildung. In dem Beitrag werden die Arbeit mit Kompetenzrastern und den dahinter liegenden ‚Lernlandschaften’ sowie der ‚Wirkungskreislauf den Lernerfolgs’ in Beatenberg kompetenzorientiert dargestellt. Die Dimensionen Definition, Beschreibung, Ordnung, Erwerb, Messung und Anerkennung von Kompetenzen werden herausgearbeitet und die Möglichkeiten von Kompetenzrastern in der beruflichen Bildung kritisch gewürdigt. Der Beitrag ist entlang der genannten Dimensionen gegliedert.

Evaluation of Auditory Displays Supporting Aircraft Approach and Landing

Abstract: The paper describes an auditory interface using directional sound as a possible support for pilots during approach in an instrument landing scenario. Several ways of producing directional sounds are illustrated. One using speaker pairs and controlling power distribution between speakers is evaluated experimentally. Results show, that power alone is insufficient for positioning single isolated sound events, although discrimination in the horizontal plane performs better than in the vertical. Additional sound parameters to compensate for this are proposed.

“La simulación al servicio de la academia - reflexiones y aplicaciones de la dinámica de sistemas en Colombia 2011” memorias del 9° Encuentro Colombiano de Dinámica de Sistemas

“La simulación al servicio de la academia - Reflexiones y aplicaciones de la Dinámica de Sistemas en Colombia 2011”, son las memorias del noveno encuentro colombiano de Dinámica de Sistemas celebrado en la Universidad del Rosario los días 14, 15 y 16 de septiembre de 2011, en el cual participaron ponentes de universidades nacionales e internacionales y se contó con la presencia de expertos en el tema quienes acompañaron y lideraron el desarrollo de las exposiciones durante los tres días. Diego Cardona Eng MSc PhD, organizador del evento, recoge la producción de sus participantes y acá se presenta la compilación de los documentos presentados.

Curriculum Innovation Network Conference - 18th & 19th January 2011

Presentations from the Curriculum Innovation Network Conference that took place on 18th & 19th January 2011 at the University of Southampton. The ambition was to bring together a global network of universities who are engaged in institution-wide curriculum innovation. The focus of the network is to share learning and practice in a collaborative way, to identify best practice and to explore practical solutions to the challenges we face. Keynote speakers from across the world and colleagues from leading universities came together to share their experience on approaches to transforming their curricula and the overall learning experience of their students. The challenges of doing this are significant, and there is much that we can learn from each other as we seek to transform the learning environment of our institutions. We hope that all who attend found these two days of great value in starting and enhancing a global dialogue about education transformation. Additional presentations will be uploaded in due course. Please note the copy right of these presentations remains with the author.

Sobre el valor de la verdad: una crítica a Richard Rorty

En el presente texto se sostiene, con Rorty, que la verdad no es una propiedad de hechos –ni mucho menos de objetos–. Sin embargo, contra Rorty, se afirma que asumir esta posición no implica la eliminación del concepto de verdad de nuestros discursos teóricos y filosóficos, esto es, que sigue teniendo sentido hacer una reflexión filosófica sobre la verdad. La estrategia para mostrar esto es abiertamente pragmatista: se inicia con el análisis de las prácticas de los hablantes para mostrar que no adquirimos los mismos compromisos cuando atribuimos verdad y cuando atribuimos justificación (sección 1); posteriormente, se evidencia en qué sentido la distinción filosófica entre verdad y justificación es útil socialmente (sección 2); y para finalizar, se muestra que dicha distinción no entraña ninguna metafísica misteriosa (sección 3).

2015 Exam Report: ‘Open Up’ Digital Democracy Commission’s Report

The Speaker’s Commission on Digital Democracy has published its report ‘Open Up’. The report recommends how Parliament can use digital technology to help it to be more transparent, inclusive, and better able to engage the public with democracy.