An approach was evaluated for the retrieval of soil moisture of bare soil surface using bistatic scatterometer data in the angular range of 200 to 700 at VVand HHpolarization. The microwave data was acquired by specially designed X-band (10 GHz) bistatic scatterometer. The linear regression analysis was done between scattering coefficients and soil moisture content to select the suitable incide...

Today Recommendation systems [6] have become indispensable because of the sheer overload of information made available to a user from web-services(Netflix, IMDB, Amazon, Yelp and many others). Recommendation systems are a well studied research area. In the following work, we present our study on the Netflix Challenge [3]. The Netflix Challenge can be summarized in the following way : Given a mo...

This paper presents the application of neuro-fuzzy method for prediction of vehicle fuel consumption prediction. Prediction motor vehicle fuel consumption has become a strategic issue, because it is not only related to the issue of availability of fuel but also the problem of the environmental impact caused. This study used automobile data, i.e. number of cylinders, displacement, horsepower, we...

Eutrophication is an increasing problem in coastal waters of the Baltic Sea. Moreover, algal blooms, which occur every summer in the Gulf of Gdansk can deleteriously impact human health, the aquatic environment, and economically important fisheries, tourism, and recreation industries. Traditional laboratory-based techniques for water monitoring are expensive and time consuming, which usually re...

Image registration is a fundamental enabling technology in computer vision. Developing an accurate image registration algorithm will significantly improve the techniques for computer vision problems such as tracking, fusion, change detection, autonomous navigation. In this paper, our goal is to develop an algorithm that is robust, automatic, can perform multi-modality registration, reduces the ...

Latent Semantic Analysis (LSA) is a statistical technique for extracting semantic information from text corpora. LSA has been used with success to automatically grade student essays (Intelligent Essay Scoring), model human language learning, and model language comprehension. We examine how LSA may help to predict a reader’s interest in a selection of news articles, based on their reported inter...

Learning Factors Analysis (LFA), a form of student modeling, is used to predict whether a student can correctly answer a tutor question. Existing evaluations of LFA rely on metrics like the crossvalidated root mean squared error (RMSE). However, the LFA output can be a binary classification (the student will be correct or not), so we can use classification metrics, such as precision and recall,...

In this paper, we propose deep learning architectures (FNN, CNN and LSTM) to forecast a regression model for time dependent data. These algorithm’s are designed to handle Floating Car Data (FCD) historic speeds to predict road traffic data. For this we aggregate the speeds into the network inputs in an innovative way. We compare the RMSE thus obtained with the results of a simpler physical mode...

The benefits of Free Space Optics (FSO) motivate to use it for future high data rate demanding communication applications. However, widespread growth of the technology has been hampered by reduced availability due to weather influences on the link. The fog has been analyzed as the most detrimental for FSO communication. There are some models that predict fog attenuation in terms of visibility. ...

This paper presents the corpus-driven approach in building the computational model of fundamental frequency, or F0, for Lithuanian language. The model was obtained by training the HMM-based speech synthesis system HTS on six hours of speech coming from multiple speakers. Several gender specific models, using different parameters and different contextual factors, were investigated. The models we...