Generalized Operations in Soft Set Theory via Relaxed Conditions on Parameters

[EN] Soft set theory has been evolved as a very useful mathematical tool to handle uncertainty and ambiguity associated with the real world data based structures. Parameters with certain conditions have been used to classify the data with the help of suitable functions. The aim of this paper is to relax conditions on parameters which lead us to propose some new concepts that consequently generalize existing comparable notions. We introduce the concepts of generalized finite soft equality (gf-soft equality), generalized finite soft union (gf-soft union) and generalized finite soft intersection (gf-soft intersection) of two soft sets. We prove results involving operations introduced herein. Moreover, with the help of examples, it is shown that these operations are proper generalizations of existing comparable operations.Abbas, M.; Ali, MI.; Romaguera Bonilla, S. (2017). Generalized Operations in Soft Set Theory via Relaxed Conditions on Parameters. Filomat. 31(19):5955-5964. doi:10.2298/FIL1719955AS59555964311

Ship target recognition based on superstructure matching

The Automatic Target Recognition(ATR) of ship targets based on Inverse Synthetic Aperture Radar(ISAR) images plays a significant role in naval warfare.To address the issue that existing superstructure-based recognition methods do not fully use superstructure shape information,we propose a novel automatic ship recognition method based on superstructure matching using the Dynamic Time Warping (DTW) algorithm.Firstly,the superstructures of each class are extracted from ISAR images after preprocessing and preliminary calibration,then the DTW algorithm is used to create the superstructure templates, and eventually the target's class is determined by the DTW distance from the templates.The proposed method is robust to ship deformation from changing aspect angles and requires few training samples per class.The experimental results of applying the technique on real ISAR data demonstrate the effectiveness of the proposed method

Remarks on Fixed Point Theory in Soft Metric Type Spaces

[EN] The aim of this paper is to discuss the recent developement regarding fixed point theory in soft metric type spaces such as soft G-metric spaces, soft cone metric spaces, dislocated soft metric spaces and soft b-metric spaces. We show that soft versions of fixed point results proved in such metric type spaces can be directly deduced from the comparable existing results in the literature.Abbas, M.; Murtaza, G.; Romaguera Bonilla, S. (2019). Remarks on Fixed Point Theory in Soft Metric Type Spaces. Filomat (Online). 33(17):5531-5541. https://doi.org/10.2298/FIL1917531AS55315541331

Scattering Removal for Finger-Vein Image Restoration

Finger-vein recognition has received increased attention recently. However, the finger-vein images are always captured in poor quality. This certainly makes finger-vein feature representation unreliable, and further impairs the accuracy of finger-vein recognition. In this paper, we first give an analysis of the intrinsic factors causing finger-vein image degradation, and then propose a simple but effective image restoration method based on scattering removal. To give a proper description of finger-vein image degradation, a biological optical model (BOM) specific to finger-vein imaging is proposed according to the principle of light propagation in biological tissues. Based on BOM, the light scattering component is sensibly estimated and properly removed for finger-vein image restoration. Finally, experimental results demonstrate that the proposed method is powerful in enhancing the finger-vein image contrast and in improving the finger-vein image matching accuracy

WAVELET-BASED AUDIO FEATURES OF DC MOTOR SOUND

The usage of wavelets is widespread in many fields nowadays, especially in signal processing. Their nature provides some advantages in comparison to the Fourier transform, and therefore many applications rely on wavelets rather than on other methods. The decomposition of wavelets into detail and approximation coefficients is one of the methods to extract representative audio features. They can be used in signal analysis and further classification. This paper investigates the usage of various wavelet families in the wavelet decomposition to extract audio features of direct current (DC) motor sounds recorded in the production environment. The purpose of feature representation and analysis is the detection of DC motor failures in motor production. The effects of applying different wavelet families and parameters in the decomposition process are studied using sounds of more than 60 motors. Time and frequency analysis is also done for the tested DC motor sounds

On generalized soft equality and soft lattice structure

Molodtsov introduced soft sets as a mathematical tool to handle uncertainty associated with real world data based problems. In this paper we propose some new concepts which generalize existing comparable notions. We introduce the concept of generalized soft equality (denoted as g-soft equality) of two soft sets and prove that the so called lower and upper soft equality of two soft sets imply g-soft equality but the converse does not hold. Moreover we give tolerance or dependence relation on the collection of soft sets and soft lattice structures. Examples are provided to illustrate the concepts and results obtained herein.http://www.pmf.ni.ac.rs/filomathb201