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Abstract

Marine mammal identification and classification for passive acoustic monitoring remain a challenging task. Mainly the interspecific and intraspecific variations in calls within species and among different individuals of single species make it more challenging. Varieties of species along with geographical diversity induce more complications towards an accurate analysis of marine mammal classification using acoustic signatures. Prior methods for classification focused on spectral features which result in increasing bias for contour base classifiers in automatic detection algorithms. In this study, acoustic marine mammal classification is performed through the fusion of 1D Local Binary Pattern (1D-LBP) and Mel Frequency Cepstral Coefficient (MFCC) based features. Multi-class Support Vector Machines (SVM) classifier is employed to identify different classes of mammal sounds. Classification of six species named Tursiops truncatus, Delphinus delphis, Peponocephala electra, Grampus griseus, Stenella longirostris, and Stenella attenuate are targeted in this research. The proposed model achieved 90.4% accuracy on 70–30% training testing and 89.6% on 5-fold cross-validation experiments.

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Authors and Affiliations

Maheen Nadir
Syed Muhammad Adnan
Sumair Aziz
Muhammad Umar Khan
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Abstract

Nowadays the demand for renewable energy sources is constantly growing. There are several reasons of such state, including requirements for energy-efficient new buildings and reduction of greenhouse gas emissions. An exemplary solution that may help to reduce “traditional” primary energy consumption is local energy source utilization. The article presents a simplified feasibility study of hybrid energy system under Polish law and economic conditions for a self-government unit, that is legally obliged to apply means of energy efficiency improvement. The aim of this paper is to provide a simple algorithm to find optimal hybrid PV and wind power source sizing for a prosumer. Resource data used in analyses are imported from Photovoltaic Geographical Information System and cover a period of one year. The paper includes two different methodologies applied to solve the problem of optimal hybrid energy system sizing. The first approach is heuristic and based on monthly energy balancing while the second is iterative and takes into account hourly energy balance. The results from both methods are compared and verified by HomerPro software, that shows significant differences between two algorithms. At the end economic assessment based on Net Present Value method is performed.

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Authors and Affiliations

M. Bartecka
P. Terlikowski
M. Kłos
Ł. Michalski

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