ﻻ يوجد ملخص باللغة العربية
The aim of this work is to create a new catalog of reliable AGN candidates selected from the AKARI NEP-Deep field. Selection of the AGN candidates was done by applying a fuzzy SVM algorithm, which allows to incorporate measurement uncertainties into the classification process. The training dataset was based on the spectroscopic data available for selected objects in the NEP-Deep and NEP-Wide fields. The generalization sample was based on the AKARI NEP-Deep field data including objects without optical counterparts and making use of the infrared information only. A high quality catalog of previously unclassified 275 AGN candidates was prepared.
Context: It is crucial to develop a method for classifying objects detected in deep surveys at infrared wavelengths. We specifically need a method to separate galaxies from stars using only the infrared information to study the properties of galaxies
In this research, we provide a new, efficient method to select infrared (IR) active galatic nucleus (AGN). In the past, AGN selection in IR had been established by many studies using color-color diagrams. However, those methods have a problem in comm
We have developed an efficient Active Galactic Nucleus (AGN) selection method using 18-band Spectral Energy Distribution (SED) fitting in mid-infrared (mid-IR). AGNs are often obscured by gas and dust, and those obscured AGNs tend to be missed in opt
We present a preliminary analysis of clustering of galaxies luminous in the near- and mid-infrared as seen by seven various ilters of the AKARI IRC instrument from 2 $mu$m to 24 $mu$m in the the AKARI NEP-Deep field. We compare populations of galaxie
Radio-loud active galaxies have been found to exhibit a close connection to galactic mergers and host galaxy star-formation quenching. We present preliminary results of an optical spectroscopic investigation of the AKARI NEP field. We focus on the po