Cilt:62 Sayı:01 (2020)
Permanent URI for this collection
Browse
Browsing Cilt:62 Sayı:01 (2020) by Title
Now showing 1 - 9 of 9
Results Per Page
Sort Options
Item A Study On The Search Potentıal of Doubly Charged Leptons At The Sppc Based Ep Colliders(Ankara Üniversitesi Fen Fakültesi, 2020-06-30) Ozansoy, Aysuhan; Albayrak, Oğuzhan; Fizik; Fen FakültesiWe consider the single production of doubly charged leptons which take part in the extended weak isospin models and have exotic electric charges such as at the SppC based electron-proton (ep) colliders. We introduce the effective lagrangians describing the doubly charged lepton gauge interactions with SM leptons. We calculate the decay widths and production cross sections as a function of doubly charged lepton mass. We deal with the process and plot the kinematical distributions for the final state electron both for the signal and corresponding background. We perform a cut-based analysis to obtain the mass limits and couplings of doubly charged leptons at the SppC based ep colliders with the center-of-mass energies of TeV and TeV.Item An Artifact Reduction Method for Block-Based Video Coding(Ankara Üniversitesi Fen Fakültesi, 2020-06-30) Ilgın, Hakki Alparslan; Akbulut, Ahmet; Elektrik-Elektronik Mühendisliği; Fen FakültesiMost of the image/video coding standards are based on discrete cosine transform which is a block-based coding scheme with a disadvantage of blocking effects at low bit rates. In this paper, we propose a hybrid method which consists of downsampling/upsampling, significance map coding and local cosine transform to reduce the disadvantage of lossy compression and is also compatible with current standards. Experimental results show that performance of the proposed method is better than the conventional approaches.Item Band Reduction for Target Detection in Hyperspectral Images(Ankara Üniversitesi Fen Fakültesi, 2020-06-30) Şimşek, Murat; Ilgın, Hakkı Alparslan; Elektrik-Elektronik Mühendisliği; Mühendislik FakültesiDue to the high spectral resolution, hyperspectral images need large data storage and processing time. Indeed, its high dimensional structure requires high computational complexity, especially for target detection. In order to overcome these problems, band reduction methods have been proposed. In this paper, we compare PCA and SNR-based band reduction methods to improve target detection performance in hyperspectral images. Experimental results show that band reduction methods not only reduce processing time, but also increase accuracy rate.Item Evaluatıon Of Ms-Dıal And Mzmıne2 Softwares For Clınıcal Lıpıdomıcs Analysıs(Ankara Üniversitesi Fen Fakültesi, 2020-06-30) Koçak, Engin; Other; OtherLipidomics covers analysis of all lipid species in an organism. Lipid metabolism is one of the key factors to understand cellular processes at molecular level. Lipidomics has been used to find diagnostic and prognostic biomarkers in clinical sample (plasma, serum, urine, tissue). Today mass spectroscopy based approach dominates lipidomics and several computational platforms have been developed to process raw mass spectra data. However, there is no routine procedure for data processing in lipidomics. In present work, two different bioinformatics platforms, which are MS-DIAL and MZmine2, was compared for lipidomics analysis of plasma sample. Peak detection, identification and quantification parameters were investigated to understand advantages and disadvantages. In peak detection process, it was observed that MZmine2 detected more peak than MS-DIAL at same threshold level. In identification process, Lipidmaps database was used for identification. MZmine2 identifies more lipid than MS-DIAL. Semi-quantification is very important to find differentially expressed lipid species and biomarkers in clinical studies. MS-DIAL and MZmine2 calculated normalized peak intensities and results were compared to understand reproducibility. Average relative standard deviation of all peaks was calculated and results showed that MS-DIAL gives more reproducible results than MZmine2. In conclusion, MZmine2 and MS-DIAL could be used in clinical lipidomics studies.Item Generatıng Turkısh Lyrıcs Wıth Long Short Term Memory(Ankara Üniversitesi Fen Fakültesi, 2020-06-30) Güzel, Mehmet; Erten, Hakan; Bostancı, Erkan; Bilgisayar Mühendisliği; Mühendislik FakültesiLong Short Term Memory (LSTM) has gained a serious achievement on sequential data which have been used generally videos, text and time-series. In this paper, we aim for generating lyrics with newly created “Turkish Lyrics” dataset. By this time, there have been studies for creating Turkish Lyrics with character-level. Unlike previous studies, we propose to Turkish Lyrics generator working with word-level instead on character-level. Also, for employing LSTM, we can’t send the words as string and words must be vectorized. To vectorize, we tried two ways for encoding the words that are used in dataset and compared them. Firstly, we sample for generating one-hot encoding and then, secondly word-embedding way (Word2Vec). Observational results show us that word- level generation with word-embedding way gives more meaningful and realistic lyrics. Actually, there have not been good results enough to be used for a song because of Turkish Grammar. But, this study encourages authors to work on this field and we do believe that this study will initialize research on this area and lead researchers to contribute to this as well.Item Learning Dense Contextual Features For Semantic Segmentation(Ankara Üniversitesi Fen Fakültesi, 2020-06-30) Keleş, Hacer Yalim; Lim, Long Ang; Bilgisayar Mühendisliği; Mühendislik FakültesiSemantic segmentation, which is one of the key problems in computer vision, has been applied in various application domains such as autonomous driving, robot navigation, or medical imagery, to name a few. Recently, deep learning, especially deep neural networks, have shown significant performance improvement over conventional semantic segmentation methods. In this paper, we present a novel encoder-decoder type deep neural network-based method, namely XSeNet, that can be trained end-to-end in a supervised manner. We adapt ResNet-50 layers as the encoder and design a cascaded decoder that composes of the stack of the X-Modules, which enables the network to learning dense contextual information and having wider field-of-view. We evaluate our method using CamVid dataset, and experimental results reveal that our method can segment most part of the scene accurately and even outperforms previous state-of-the art methods.Item RF Antenna Desıgn For Button-Type Beam Posıtıon Monıtors Usıng Bıo-Inspıred Optımızatıon Methods(Ankara Üniversitesi Fen Fakültesi, 2020-06-30) Aydın, Ayhan; Bostancı, Gazi Erhan; Bilgisayar Mühendisliği; Mühendislik FakültesiAccelerator based facilities are in a leading position for crafting many scientific and technical innovations for a wide range of application from aviation to medicine. Beam Position Monitors (BPMs) are critical diagnostics tools for such facilities. This study presents bio-inspired methods known as Particle Swarm Optimization and Evolutionary Algorithms in order to design RF antennas for button-type BPMs. Our results show that the antenna parameters obtained using this multiple objective approaches present suitable SNR and linearity values for signal processing. It is found that using an antenna radius of 5.5 mm and beam-pipe radius of 17.5 mm, we can obtain SNR values around 40 dB which can be electronically processed.Item Study Of Transportatıon Problem Of Iron And Steel Industry In Turkey Based On Lınear Programmıng, Vam And Modı Methods(Ankara Üniversitesi Fen Fakültesi, 2020-06-30) Askerbeyli, Rehile; Other; OtherThe subject of this study is the investigation of the minimization of the total transportation costs for finished product produced by Alter Iron and Steel Industry Company in its own production facilities in Karabuk. Firstly, the current situation in the Iron and Steel Industry in the world and Turkey are briefly discussed. In the second stage, the distribution to the demand point from the factory operating in the Iron and Steel Sector is considered as the basic problem. The demand points were determined as geographical regions. We have two targets: the total cost to be minimized and the total amount of goods to be sent from supply center to the demand centers to be equal to the total demand or supply amount. The optimum solution of the transportation model were solved both the traditional transportation model methods such as Vogels Approximation Method (VAM), Modified Distribution (MODI) method and the linear programming method. The optimal solution for last model was found using the R /SIMPLEX package program. Obtained results by different approachs are discussed. Critical aspect of this problem is to use the single source transportation model, where all demand amounts are met from a single production center.Item The Design of Standalone pv System Using P&O Algorithm For Maximum Power Point Tracking(Ankara Üniversitesi Fen Fakültesi, 2020-06-30) Özel, Kenan; Karaaslan, Ahmet; Enerji Mühendisliği; OtherThis paper presents the simulation of output power control of photovoltaic panel using Maximum Power Point Tracking (MPPT) controller of boost converter. Due to the stochastic behavior of temperature and irradiation condition, integrating a MPPT algorithm to DC-DC converter is important for extracting the maximum power from photovoltaic system. The Perturb and Observe (P&O) algorithm has been preferred due to its lower complexity and easy implementation. The main aim of this study is to track the maximum operation point of photovoltaic system and to control the output power with respect to the changing irradiation and temperature. The simulation results demonstrate that MPPT controller prevents the power deviation and provide to extract maximum possible power from solar array.