Computer Science

This paper highlights an effort of incorporating several renewabIes like geothermal power plant (GTP), solar thermal and wind in automatic generation control and analyse its impact along with FACT devices on conventional thermal system. Suitable generation rate constraint for thermal units is considered. Fractional order (FO) Proportional Integral - FO Proportional Derivative (FOPI-FOPD) is used as secondary controller implementing the innovative concept of FO cascade controller. The dynamic performance of FOPI-FOPD controller is compared with the normally used traditional controllers and the controller parameters are optimized by means of the Sine Cosine Algorithm. Superiority of FOPI-FOPD is clearly revealed in the analysis over others. Effect of integrating GTP and other renewables is also highlighted on the thermal system. The performance of interline power flow controller (IPFC) is also evaluated on system dynamics. Observations reflect IPFC in between Linel and Line3 is the op...

400 Commonwealth Drive, Warrendale, PA 15096-0001 USA Tel: (724) 776-4841 Fax: (724) 776-5760 Web: www.sae.org ... Gaurav Anand, Milind Mahajan and Nagendra Jain Adroit Software and Consulting, Inc. ... Balaji Maniam and Todd M. Tumas General Motors Corporation

400 Commonwealth Drive, Warrendale, PA 15096-0001 USA Tel: (724) 776-4841 Fax: (724) 776-5760 Web: www.sae.org ... Gaurav Anand, Milind Mahajan and Nagendra Jain Adroit Software and Consulting, Inc. ... Balaji Maniam and Todd M. Tumas General Motors Corporation

Institutional websites are available for a large amount of data hindering the access of scholars to information relevant to their academic journey. As the university is also a space of opportunities, it is necessary that the student is aware of all the possibilities that can support his professional and human growth, such as, monitoring, projects of scientific initiation, cultural activities, among others. So, considering the massive use of smartphones by students, this paper proposes a mobile application that provides the information of interest to academics in a more simplified way, using the resources of gamification. In order to investigate the most interesting contents of the students of the State University of the North of Parana (UENP), a questionnaire containing questions related to university contents was applied a 220 students. The investigation allowed to verify that the students have a high level of difficulty to access the contents of their interest, pointing out as mai...

This paper presents vector tracking algorithm for tracking the pseudorandom code of satellite navigation signals, which is suitable for degraded signal environment. The benefits of the vector tracking in comparison of scalar tracking are also explained. This vector tracking algorithm is based on the discriminator function. Conventional GPS receivers use scalar tracking methods and signals from each channel are processed independently. On the contrary, vector tracking loops process the signals in aggregate and can provide better tracking in degraded signal environment, since the channels are closely correlated in vector mode. In vector tracking approach the tracking control input is generated by the navigation filter. The vector tracking loops can operate in weak signal conditions and can rapidly reacquire the weak or attenuated signals. In this paper the ability of vector tracking loop to reacquire the signals is explored and is compared with conventional scalar tracking method.

Many experimental studies have been carried out to demonstrate that a multiccmponent complex skill as reading can be described through a series of processing stages (LaBerge & Jay Samuels, 1974). A visual word activates different codes: visual, phonological, semantic and some operations take place within each code. Consequently reading disabilities could be due either to the inability to deal with the different internal codes produced by a word (Posner, 1978; Snowling, 1980) or to the difficulties to operate within each code. While theories differ about the relationship between letter processing and word processing, almost all acknowledge that children must identify and discriminate among letters in order to read fluently (Gibson, 1969). Posner (1978) reviewed some studies to show that separable codes are activated when a visual word is presented. These include the physical (visual) and the phonetic codes found for individual letters. Thus many of the question to which the reading process has been subjected can benefit from studies on matching of letters. To trace the nature of the codes activated and the time course of the efficiency of letter processing could help reading researchers to a better understanding of the early letter processing skills. The general aim of the present study is to define the codes upon which different operations take place and to isolate the stages of visual information processing both with alphanumeric and nonalphanumeric material.

Developmental theories have been dominated by two different views both on the origin of knowledge and on the initial mechanisms that form the basis for cognitive development. On one view, knowledge emerges on the basis of domain-general mechanisms of learning that are sufficient to explain how children learn about specific domains of knowledge such as language, number, space, or faces. Although Piagetian, behaviorist, and more recently connectionist theories fall within this view, Piaget's position, known as “epigenetic ...

Developmental theories have been dominated by two different views both on the origin of knowledge and on the initial mechanisms that form the basis for cognitive development. On one view, knowledge emerges on the basis of domain-general mechanisms of learning that are sufficient to explain how children learn about specific domains of knowledge such as language, number, space, or faces. Although Piagetian, behaviorist, and more recently connectionist theories fall within this view, Piaget's position, known as “epigenetic ...

This paper presents a novel unsupervised and incremental learning technique for data clustering that are polluted by noise using neural network approaches. The proposed approach is based on a self-organizing incremental neural network. The design of two-layer neural network enables this system to represent the topological structure of unsupervised on-line data, reports the reasonable number of clusters and gives typical prototype patterns of every cluster without prior conditions such as a suitable number of nodes. To confirm the efficiency of the proposed learning mechanism, we present a set of experiments with artificial and real world data sets.

This article describes a method for the automatic evaluation of video summaries based on the training of individual predictors for different quality measures from the TRECVid 2008 BBC Rushes Summarization Task. The obtained results demonstrate that, with a large set of evaluation data, it is possible to train fully automatic evaluation systems based on visual features automatically extracted from the summaries. The proposed approach will enable faster and easier estimation of the results of newly developed abstraction algorithms and the study of which summary characteristics influence their perceived quality.

Online-Befragungen stellen mittlerweile ein Standardwerkzeug der empirischen Sozialforschung dar, dessen Potentiale und Grenzen seit langerem diskutiert werden. Im Kontext vieler Internetanwendungen fallen jedoch zusatzliche Daten an, deren Verwendung fur sozialwissenschaftliche und methodische Fragestellungen noch keine vergleichbare Verbreitung gefunden hat. Es handelt sich hierbei um prozessproduzierte Daten, die durch (soziale) Handlungen von Nutzern erzeugt und vom jeweiligen Provider ohne einen ursprunglich wissenschaftlichen Verwendungszweck aufgezeichnet werden. Am Beispiel des Projektes „Prozesse der Partnerwahl auf Online-Kontaktborsen“ wird argumentiert, dass Verhaltensspuren, die durch Such-, Interaktionsund Kommunikationshandlungen in Social-Web-Applikationen generiert und aufgezeichnet werden, gewinnbringend fur die sozialwissenschaftliche Forschung genutzt werden konnen. Neben einem empirischen Anwendungsbeispiel des erganzenden bzw. komplementaren Gebrauchs nichtreak...

Leading wind turbine manufacturers are increasingly looking at the possibilities of sending offshore wind turbines to deep seas. This can be done using a Floating Offshore Wind Turbine (FOWT). Therefore FOWT is an interesting and timely field of study. The aim of the paper is to use System Identification (SI) to make a data-driven-based model for the FOWT system, located in Offshore Wind & Wave Laboratory at Aalborg University. This is achieved by conducting experiments and analyzing the data. SI is used to analyze data from the experiments and obtain different models. These models are then evaluated based on the fit, the frequency response, autocorrelation and crosscorrelation. Eventually, an AutoRegressive Moving Average and Extra input (ARMAX) model is shown to be the most accurate amongst the analyzed models.

In industry the condition monitoring of rotating machinery gear is very important. The defect in gear mesh may cause the failure in machinery and that causes a severe loss in industry. The failure in gear mesh reduces the efficiency and hence decreases the productivity in industrial operation. Therefore the health monitoring of gear mesh is very important. Proper health monitoring of gears can avoid the failure in machinery and can save money in industrial applications. The acoustic emission and vibration are the two widely used measuring parameters which is used for the condition monitoring of gear mesh. In this work the gear fault detection by using the acoustic emission monitoring technique is used. This experimentation is done by using an efficient instrumentation system. The experimental set-up is designed which consists of a gear mesh driving system and a hand-held sound analyzer. To carry out the experiment the measuring signals from the defective and healthy gears are captur...

Electroencephalography (EEG) is used for the diagnosis of brain disorders (like epilepsy, Amyotrophic Lateral Sclerosis (ALS) etc). Artifacts are the unwanted interference in the EEG signal because of eye movements, blinks, muscle activity, heartbeats, power line noise etc. Different techniques were proposed to get artifacts free EEG signal for improving the accuracy while doing feature extraction and data classification. In this paper, conventional methods for noise removal are described and recent techniques are reviewed.