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This article is addressed to show the results of hybrid dynamical modeling in the form of PWA (piecewise-affine) and equivalent MLD (mixed-logical dynamical) model for multi-restricted areas avoidance of an autonomous system. It is a problem of determining the optimal moving trajectory from plant’s initial position to some desired position while avoiding some restricted areas…

Tactile displays are widely used in the rehabilitation and education of blind persons, as it is one of the media of communication amongst them. Tactile display performance is measured in terms of accuracy in presenting pattern, accuracy in identification, recognition and reading time of presented pattern. However, it has had meager attention from researchers. This…

This paper is proposed to build a model by applying two methods, namely support vector machine and nonnegative matrix factorization in the process of predicting stock market movement using twitter and historical data. The stock exchange is based on the LQ 45 stock with period from August 2018 – January 2019. The features consist of…

To date, software development is vital since software is a critical element in information technology. Requirements gathering, planning, estimation, estimation, development, collaboration, testing, and deployment. The problem is when it is delivered, so it reduces the risk of the problem which could happen is important. Threat prediction should be made. It will be aimed at…

Convolutional LSTMs are widely used for spatiotemporal prediction. We study the effect of using different activation functions for two types of units within convolutional LSTM modules, namely gate units and non-gate units. The research provides guidance for choosing the best activation function to use in convolutional LSTMs for video prediction. Moreover, this paper studies the…

Climatic changes have a significant impact on many real life processes. Climacteric position of Albania makes precipitations and water inflows in HPP the main variables influencing the amount of electric energy produced in the country. Taking into account their volatility it has considerably increased the need of using hybrid models to improve the quality of…

Robotic catching of thrown objects is one of the common robotic tasks, which is explored in a number of papers. This task includes subtask of tracking and forecasting the trajectory of the thrown object. Here we propose an algorithm for estimating future trajectory based on video signal from two cameras. Most of existing implementations use…

This paper investigates the methods of optimal design construction for step-stress accelerated life testing (ALT) when a Cox’s hazards model is adopted with either a linear or a quadratic baseline hazard function. We discuss multiple step-stress plans for time-censored ALT experiments. The maximum likelihood method is utilized for estimating the model parameters. The information matrices…

Almost every cells in human’s body contain the same number of genes so what makes them different is which genes are expressed at any time. Measuring gene expression can be done by measuring the amount of mRNA molecules. However, it is a very expensive and time consuming task. Using computational methods can help biologists to…

Advances in technology have enabled the installation of an increasing number of sensors in various mechanical systems allowing for more detailed equipment health monitoring capabilities. It is hoped the sensor data will enable development of predictive tools to prevent system failures. This work describes continued analysis of sensor data surrounding a seizure of a turbocharger…

Predicting the impact of suicide on incidental witnesses at an early stage helps to avert the possible side effect. When suicide is committed in public, incidental observers are left to grapple with it. In many cases, these incidental witnesses tend to experience the emotional side effect with time. In this study, we employed a Machine…

Intelligent Transportation Systems (ITS) applications can take big advantage of Context Awareness approaches. Parameters such as user mobility, passengers comfort reaction and pollution emission levels (CO2) can enrich such applications during the decision making phase. Moreover, the expanding in ITS services offers great opportunities for travelers to find the best route to reach their destinations…

A 500 KVA Uninterruptible power supply (UPS) using Fuel Cells (FC) and super-capacitors (SCs) was studied with the worst case of 10 minutes and eight hours of interruption per day. A power management system was established to control the FC and the SCs in order to extract the hybridization benefits with a comparison between a…

Hereby in this paper, we are going to refer image classification. The main issue in image classification is features extraction and image vector representation. We expose the Bag of Features method used to find image representation. Class prediction accuracy of varying classifiers algorithms is measured on Caltech 101 images. For feature extraction functions we evaluate…

Over the years, wind loading codes has been a crucial tool in determining design wind loads on buildings. Due to the limitations of these codes especially in height, wind tunnel testing is recommended as the best approach in predicting wind flow around buildings but carrying out wind tunnel testing in the preliminary as well as…

Cognitive Radio (CR) encompasses a number of technologies which enable adaptive self-programing of systems at different levels to provide more effective use of the increasingly congested radio spectrum. CRs have potential to use spectrum allocated to TV services, which is not used by the primary user (TV), without causing disruptive interference to licensed users by…

The era of big data has witnessed the explosion of tensor datasets, and large scale Probabilistic Tensor Factorization (PTF) analysis is important to accommodate such increasing trend of data. Sparsity, and Cold-Start are some of the inherent problems of recommender systems in the era of big data. This paper proposes a novel Sentiment-Based Probabilistic Tensor…

With the rapid growth of financial markets, analyzers are paying more attention on predictions. Stock data are time series data, with huge amounts. Feasible solution for handling the increasing amount of data is to use a cluster for parallel processing, and Hadoop parallel computing platform is a typical representative. There are various statistical models for…

Conformal Prediction is a recently developed framework for reliable confident predictions. In this work we discuss its possible application to big data coming from different, possibly heterogeneous data sources. On example of anomaly detection problem, we study the question of saving validity of Conformal Prediction in this case. We show that the straight forward averaging…

Modeling of direct expansion (DX) air conditioning and heat pump systems can be necessary in developing energy saving methods required to reduce energy consumption in buildings. The artificial neural networks (ANN) can be simple and reliable as compared to traditional methods. A properly trained artificial neural network can provide accurate results, while being relatively straightforward…