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Article
Publication date: 1 December 2017

Khaled Mohamed Himair Swhli, Srdjan Jovic, Nebojša Arsic and Petar Spalevic

This paper aims to explore detection of heating load of building by machine learning. Detection of heating load of building is very important in design of buildings due to…

Abstract

Purpose

This paper aims to explore detection of heating load of building by machine learning. Detection of heating load of building is very important in design of buildings due to efficient energy consumption.

Design/methodology/approach

In this study, detection of heating load of building based on effects of dry-bulb temperature, dew-point temperature, radiation, diffuse radiation and wind speed was analyzed. Machine learning approach was implemented for such a purpose.

Findings

The obtained results could be useful for future planning of heating load of buildings. Because the heating load of building is a very nonlinear phenomenon, it is suitable to use machine learning approach to avoid the nonlinearity of the system.

Originality/value

The obtained results could be used effectively in detection of heating load of buildings.

Details

Sensor Review, vol. 38 no. 1
Type: Research Article
ISSN: 0260-2288

Keywords

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Article
Publication date: 25 July 2018

Vladan Borovic, Petar Spalevic, Srdjan Jovic, Damir Jerkovic, Vida Drasute and Dejan Rancic

This paper aims to show the implementation in the terrestrial trunked radio (TETRA)-based sensor network. The publicly available data show that, in Serbia, the annual…

Abstract

Purpose

This paper aims to show the implementation in the terrestrial trunked radio (TETRA)-based sensor network. The publicly available data show that, in Serbia, the annual damage caused by hailstorms in the past seven years has been estimated almost at an average level of 40m of euros. As the amount of hail was not changed, the hail suppression system of the Republic of Serbia has to be improved, both technically and organizationally, to get better efficiency and protection and to reduce the damage.

Design/methodology/approach

In this paper, the authors show the implementation and improvements in the modern terrestrial trunked radio (TETRA)-based sensor network, and they propose the scientific use of sensors for remote control of automatic hail suppression rocket stations.

Findings

The authors’ idea is that TETRA should be used as an operational and official telecommunicating system for hail suppression activities units. A number of sensors, connected in a network, are used to maintain a high-quality functioning of this digital radio system, managed remotely and controlled either by operators or automatically.

Originality/value

The presented study with a real example attempts to explain as to how the system functions and how it can improve hail suppression activities.

Details

Sensor Review, vol. 39 no. 2
Type: Research Article
ISSN: 0260-2288

Keywords

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Article
Publication date: 28 February 2019

Gabrijela Dimic, Dejan Rancic, Nemanja Macek, Petar Spalevic and Vida Drasute

This paper aims to deal with the previously unknown prediction accuracy of students’ activity pattern in a blended learning environment.

Abstract

Purpose

This paper aims to deal with the previously unknown prediction accuracy of students’ activity pattern in a blended learning environment.

Design/methodology/approach

To extract the most relevant activity feature subset, different feature-selection methods were applied. For different cardinality subsets, classification models were used in the comparison.

Findings

Experimental evaluation oppose the hypothesis that feature vector dimensionality reduction leads to prediction accuracy increasing.

Research limitations/implications

Improving prediction accuracy in a described learning environment was based on applying synthetic minority oversampling technique, which had affected results on correlation-based feature-selection method.

Originality/value

The major contribution of the research is the proposed methodology for selecting the optimal low-cardinal subset of students’ activities and significant prediction accuracy improvement in a blended learning environment.

Details

Information Discovery and Delivery, vol. 47 no. 2
Type: Research Article
ISSN: 2398-6247

Keywords

Content available
Article
Publication date: 6 June 2019

Xu Du, Jui-Long Hung and Chih-Hsiung Tu

Abstract

Details

Information Discovery and Delivery, vol. 47 no. 2
Type: Research Article
ISSN: 2398-6247

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