Modeling and optimum design for wire electrical discharge machining of γ titanium aluminide alloy

ÖMER FARUK BÜYÜKYAVUZ

Wire electrical discharge machining (WEDM) of γ titanium aluminide is the subject of the current research. Due to the large number of process variables and sophisticated stochastic process mechanisms, selecting the best machining parameter combinations for increased cutting efficiency and accuracy is a difficult task in WEDM. In general, there is no perfect combination that can produce the fastest cutting speed and the finest surface finish quality at the same time. For this purpose, the data were selected from a literature study. This study describes an attempt to devise a suitable machining ...Daha fazlası

7th International Students Science Congress: Proceedings, 12-13 May 2023 = 7. Uluslararası Öğrenciler Fen Bilimleri Kongresi: Tam Metin Bildiriler Kitabı, 12-13 Mayıs 2023

Değerli Katılımcılar, Meslektaşlarım ve Uluslararası Öğrenciler, 7. Uluslararası Öğrenciler Fen Bilimleri Kongresi Tam Metin Kitabını etkinliğin yazarlarına ve katılımcılarına sunmak bizler için büyük bir onur ve ayrıcalıktır. Bunu yararlı, heyecan ve ilham verici bulacağınızı umuyoruz. Son altı yıldır çeşitli bilim dallarında çalışan genç uluslararası araştırmacıları bir araya getirmek amacıyla kongrelerimizi düzenledik ve bu hepimizi gerçekten motive etti. Geçen yıl olduğu gibi bu yıl da kongremizi hibrid bir şekilde düzenledik. Kongrenin ilk günü olan 12 Mayıs’ta, 200'den fazla katılımcının ...Daha fazlası

A Face Authentication System Using Landmark Detection

Velican ERCAN | M. Erdal ÖZBEK

Biometric data is the key for many security applications. Authentication relies on the individual’s measurable biometric properties collected as features. In this study, a face authentication system is built to be used in opening the entrance door accessing to the apartments and housing estates. The proposed system consists of three stages. In the first stage, landmarks on the face are captured using a deep neural network. Then six selected features from the landmarks are extracted and traditional machine learning algorithms are used to authenticate users. In the last stage, a user interface i ...Daha fazlası

Estimation of Scattering Parameters of U-Slotted Rectangular RFID Patch Antenna with Machine Learning Models

İsmail AKDAĞ

Abstract In this study, machine learning-based models have been used to estimate the return loss parameters of the operational resonant frequency of the U-slotted UHF RFID antenna. The data set utilized, consisting of 544 instances, has been collected from the simulation software as a consequence of the parametric evaluation of the antenna design parameters. Distinct machine learning methods have been used on two different types of output data, complex and linear scattering parameters, and the models' prediction performance has been evaluated. In the single-output regression models, a mean-squ ...Daha fazlası

Fabric Defect Classification Using Combination of Deep Learning and Machine Learning

Fatma Günseli YAŞAR ÇIKLAÇANDIR

Automatic systems can be used in many areas, such as the production stage in factories, country defense, and traffic control. They provide the opportunity to reach results faster with higher success rates thanks to human-computer vision cooperation. In this study, it is aimed to develop an intelligent system that automatically detects and classifies defects in fabrics. Thanks to the developed system, the cause of the malfunction is eliminated, and the recurrence of the malfunction is prevented. Using deep learning methods in fabric defect classification studies has a disadvantage compared to o ...Daha fazlası

Electron Beam Welding (EBW) of Aerospace Alloy (Inconel 825): Optimization and Modeling of Weld Bead Area

LEVENT AYDIN

This study investigates the optimum weld area on a popular aerospace alloy (i.e., Inconel 825) made by the electron beam welding technique. Welding speed (S), beam current (I), accelerating voltage (V), and beam oscillation (O) are considered as process parameters to study the weld bead area (WA) of the weldments. An instructive study on multiple non-linear neural regression analyses has been done as a basic introduction to neuro regression modeling with artificial neural network (ANN) philosophy. To do this, the experimental prediction has been modeled with 14 predictive functional structures ...Daha fazlası

Optimization of Process Parameters for Green Composites in Abrasive Water Jet Machining Process Using Neuro-Regression Analysis

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