Sürdürülebilir Kalkınma Amaçları
Yazarlar
- Yildirim, Ozal(4)
- Demir, Yakup(3)
- Eristi, Belkis(3)
- Eristi, Huseyin(3)
- Akmaz, Duzgun(2)
- Eren, H.(2)
- Erol, Yavuz(2)
- Kaya, M.(2)
- Kaya, Mehmet(2)
- Mamis, Mehmet Salih(2)
- Omaç, Zeki(2)
- Polat, M.(2)
- Yakut, O.(2)
- Ünal, Sencer(2)
- Adali, E(1)
- Arkan, Muslum(1)
- Aslan, Serpil(1)
- Can, Umit(1)
- Celenk, M.(1)
- Gül, Serpil(1)
- Ince, Cemile(1)
- Kaya, Buket(1)
- Kiziloluk, Soner(1)
- Kurum, H.(1)
- Köseoglu, Murat(1)
- Kürüm, H.(1)
- Kürüm, Hasan(1)
- Oksuztepe, E.(1)
- Omac, Z.(1)
- Omaç, Z.(1)
- Ozyildirim, BM(1)
- Polat, Mehmet(1)
- Tagluk, M. Emin(1)
- Talo, Muhammed(1)
- Utku, Anil(1)
- Uyanik, Hakan(1)
- Yildirim, M.(1)
- Yildirim, Merve(1)
- Yildirim, T(1)
- Öksüztepe, E.(1)
Yayınlar
- BildiriYalnız künye2022Machine Learning-Based A Comparative Analysis for Air Quality Prediction
Utku, Anil; Can, Umit
Air pollution affects human life negatively, especially in terms of health, and causes the death of millions of people every year. Today, air pollution in many regions is still above the limits indicated by the World Health Organization. In this study, the prediction of the rate of PM2.5, which is an important air pollutant, in the Beijing region of China is emphasized. For this purpose, weather prediction models were created using Random Forest Algorithm, Support Vector Regression, XGBoost and K-Nearest Neighbor Algorithm, which are popular machine learning algorithms, and the results were compared using various metrics. The best prediction result in all the metrics used was obtained with the Support Vector Regression method.
AtıfWoS2OpenAlex8
İncele - BildiriYalnız künye2020The Effect of Different Noise Levels on The Performance of The Audio Search Algorithm
Köseoglu, Murat; Uyanik, Hakan
Audio fingerprint technique is a method that creates a unique and compact identity for audio data and is also used to distinguish these identities from each other. In this study, an algorithm, based on the methods used in Shazam 's audio fingerprint technique and hash functions, was developed to recognize multimedia audio files by using MATLAB software, and it was tested against noise factor of different levels. Experimental results have shown that the developed algorithm gives successful results against the noise factor. In addition, it has been understood that the preferred hash function technique has revealed satisfying results in comparison with the conventional techniques.
AtıfOpenAlex5İncele - BildiriYalnız künye2019Pneumonia Detection from Radiography Images using Convolutional Neural Networks
Talo, Muhammed
Pneumonia continues to be the leading cause of child mortality in children under the age of five, and 2,400 children, most of whom are babies under 2 years of age, die from pneumonia. In this study, an automated detection system is proposed for the diagnosis of pneumonia with chest radiography images. With the transfer learning technique, ResNet-152 convolutional neural network was customized to recognize pneumonia from radiography images. With this customized architecture, a recognition success of 97.4% was obtained in the detection of pneumonia disease without any preprocessing of raw data or manual feature extraction on radiography images. This model, which was proposed for the detection of pneumonia, found to be more successful when compared with the other successful studies in the literature.
AtıfWoS6OpenAlex16İncele - BildiriYalnız künye2019An Intrusion Detection System Using Apache Log Files
Ince, Cemile; Omaç, Zeki
Today, thousands of systems are exposed to attacks every day. For this reason, many studies have been done in this area. These studies, using data mining (VM) and machine learning techniques, are trying to determine the intrusion detection by examining the log files in different OSI layers. These studies generally use standard data sets and propose hybrid systems to increase the success rate. In this study, an attack detection system (STS) has been developed by using Inonu University web page log files. The log files used as a data set consist of more than 35 million requests and a total of 326 attacks. As a result, the system was trained using artificial neural network (ANN) and attacks were detected with 99.3% success.
- BildiriYalnız künye2018Geometric Methods in Deep Learning
Ünal, Inan; Yildirim, Ozal; Ozyildirim, BM; Yildirim, T
Deep learning algorithms have recently become the most widely used machine learning approaches. Remarkable approaches have emerged in the field of machine learning studies with the use of geometric methods for deep learning. The manifold theory, which is simply regarded as the general state of an Euclidean space, has become applicable in the field of deep learning and this field has been named Geometric Deep Learning. In this study, applications of manifold theory and differential geometry to deep learning is presented.
- BildiriYalnız künye2017Link Prediction Methods in Bipartite Networks
Aslan, Serpil; Kaya, Mehmet; Adali, E
Nowadays, social networks, whose application areas are increasing day by day; Such as data mining, protein-gene interaction networks, online social networks, transport networks, academic information networks, and telecommunications networks. Many real-world complex networks have a naturel bipartite structure. In bipartite networks, which have become the focus of many researchers who have been dealing with social network analysis in recent years, connection estimation methods are the basic methods used to understand the structure of these networks. This study is a survey work that describes the connection in a bipartite network that is suitable for the nature of today's huge data networks. In this study, a bipartite network interface is an introductory guide for researchers who plan to work on this subject by examining the internal links and bipartite network projection methods.
AtıfWoS4İncele - BildiriYalnız künye2016Predicting Links in Weighted Disease Networks
Gül, Serpil; Kaya, Mehmet; Kaya, Buket
This paper proposes a link prediction method to estimate what sort of disease risks may have been carried by the patients via surveying their and similar patients' medical histories. It is possible to make future oriented predictions with link prediction by deriving new data within a network structure. It is attempted to estimate the future structure of the network and the relations which will be created or abandoned by the individuals on the basis of the nodes within the network structure and the relations between these nodes. For this purpose, an undirected weighted disease network is first created by using the data of patients which were subjected to Hemogram test at F. rat University Hospital during 2013. In the disease network, each node represents a disease and the links represent a relationship between diseases. By the developed method, then disease risk prediction is made through a proactive approach by determining what sorts of disease risks were carried by the patients applying with certain complaints. Experimental results demonstrate the applicability of the link prediction in these networks.
AtıfWoS11İncele - BildiriYalnız künye2016An Online Electric Power Quality Disturbance Detection System
Yildirim, Ozal; Eristi, Belkis; Eristi, Huseyin; Ünal, Sencer; Erol, Yavuz; Demir, Yakup
In this study, an FPGA based online monitoring system was developed for detection of power quality disturbances. The developed system has the capability to instantly detect commonly seen PQ disturbances such as voltage sag, voltage swell and interruption occurring on real-time three-phase voltage signals obtained from the electric power system. The data of the detected disturbance events are transferred to the visual software prepared in the computer environment by means of the UDP/IP communication module embedded in the FPGA. This PQ disturbance detection system was tested upon installation at three different measuring points across the campus of Tunceli University. It was seen from the test results examined that the detection system successfully identified the PQ disturbance events.
- BildiriYalnız künye2016A Real-Time Power Quality Disturbance Detection System Based On The Wavelet Transform
Eristi, Belkis; Yildirim, Ozal; Eristi, Huseyin; Demir, Yakup
Disturbances occurring on voltage signals following switching events or faults on power systems are defined as power quality problem. Power quality problems result in significant financial losses in the power systems in addition to faulty operation or breakdown of sensitive loads connected to the power system. Therefore, power quality problems should be swiftly detected and eliminated. This paper proposes a real-time embedded detection system for the purpose of identification of power quality disturbances. The detection system developed has been created using the wavelet transform in the Field Programmable Gate Array (FPGA) media. The general structure of FPGA-based detection system comprises two fundamental parts: hardware and software. Hardware structure comprises signal input card, FPGA and computer components. The software stage includes FPGA and graphical interface software. An experimental setup of the power system has been created in laboratory environment in order to test the FPGA-based detection system, determine accuracy rates and assess its success. Various power quality disturbances have been created over this model in wide parameter intervals. When the results obtained for the real-time power quality disturbance detection system developed under this study are examined, it has been seen that hardware and software designs are quite effective, fast and of high achievement performance.
- BildiriYalnız künye2016Comparison of Physics-Based Optimization Algorithms by Using Benchmark Functions
Kiziloluk, Soner; Özer, Ahmet Bedri
Many of meta-heuristics optimization algorithms which are used to solving optimization problems are inspired from biological evolution, physical, social and chemical processes. Electromagnetism-like Algorithm (EM), Big Bang-Big Crunch Algorithm (BB-BC) and Gravitational Search Algorithm (GSA) are investigated in this study and they are physics-based meta-heuristics techniques. Performances of EM, BB-BC and GSA are compared by using Rastrigin, Rosenbrock and De Jong test functions.
AtıfWoS1İncele - BildiriYalnız künye2015Fault Location on Series Compensated Power Transmission Lines Using Transient Spectrum
Akmaz, Duzgun; Mamis, Mehmet Salih; Arkan, Muslum; Tagluk, M. Emin
Nowadays sustainability and quality of energy have gained more importance. Power outages due to failures particularly cause interruption of production at industrial facilities may lead to loss of manpower and resources. One of the major causes of power outages in the power system is the short-circuit faults occurring in transmission lines. The most important requirement to clear the fault in a short time is to estimate the fault location quickly and accurately. In this study, fault location is determined in series compensated power transmission lines utilizing transient frequency spectrum. It has been shown that the method is suitable for series compensated lines.
AtıfWoS4İncele - BildiriYalnız künye2015Harmonic Analysis in Power Systems With Discrete Fourier Transform
Akmaz, Duzgun; Mamis, Mehmet Salih
Harmonics has become more significant issue due to the increasing of utilization of the non-linear loads and switching elements such as inverter on the power system recently. Harmonics disrupts the shape of the current and voltage signals in power systems and leads to many problems in power systems. It has made harmonic analysis necessary on the power system. Harmonics has become more significant issue due to the increasing of utilization of the non-linear loads and switching elements such as inverter on the power system recently. In this study a method is designed to obtain a basic signal by using Discrete Fourier Transform (DFT) in order to determine harmonics on power systems. The simulation of this method has been implemented by using Matlab/Simulink software package.
AtıfWoS2İncele - BildiriYalnız künye2015An FPGA Based Power Quality Monitoring System
Yildirim, Ozal; Eristi, Belkis; Eristi, Huseyin; Ünal, Sencer; Erol, Yavuz; Demir, Yakup
In this study, a new FPGA based monitoring system has been developed for monitoring the power quality. Designed system performs the calculations of power quality parameters on real-time voltages and currents datas that are obtained from the network. FPGA devices that have recently become more popular in digital signal processing field is used in the structure of monitoring system. Designed power quality monitoring system has been established on electrical distribution panels of Tunceli University Vocational Schools. When the obtained test results are evaluated, it has been observed that the proposed power quality monitoring system is successful.
AtıfWoS1İncele - BildiriYalnız künye2014DESIGNING IN-WHEEL SWITCHED RELUCTANCE MOTOR FOR ELECTRIC VEHICLES
Yildirim, M.; Polat, M.; Öksüztepe, E.; Omaç, Z.; Yakut, O.; Eren, H.; Kaya, M.; Kürüm, H.
Estimation of dimension parameters for an electrical machine has great importance before manufacturing. For this reason, analytical design should be performed in an optimum form. While motor analysis is accomplished by package programs, initial size parameters are intutivily provided and then various trials are examined to get optimum results. In this study, we are trying to find dimensional and electrical parameters generating mathematical equations in analytic approaches for In-Wheel Switched Reluctance Motor (IW-SRM), which will be employed by Electric Vehicle (EV). Therefore, optimum motor parameters for required speed and torque have been estimated by solving generated equations for in-wheel SRM with 18/12 poles via MATLAB. Using the parameters, analysis of in-wheel SRM has been carried out 3D Finite Element Method (FEM) by Ansoft Maxwell 15.0 Package Software. Consequently, the accuracy of the estimated parameters has been validated by the results of Maxwell 3D FEM.
AtıfWoS10İncele - BildiriYalnız künye2014Estimation of Confidence Regions and Severity of Undefined Faults in Driving using Synthetic Disturbance Signals
Yakut, O.; Eren, H.; Kaya, M.; Oksuztepe, E.; Polat, M.; Omac, Z.; Kurum, H.; Celenk, M.
In this study, we aim to determine fault severity in an electric car that may be caused by yawing due to such disturbances as non-uniform road pavements, in-wheel bearing clearance, suspension system, driver under Influence of alcohol (DUI), and tire deformation. The major research contribution herein is to alert drivers about an unforeseen situation on steering wheel whether it refers to a severe fault or contemporary states. In a sense, the undertaken study serves as a state of the art driving assistant system operating under unsteady conditions. We determine the fault severity of the system via classifying it into specified confidence regions by estimating the deviation from a monotonous straight route for any unstable situation. In this way, the proposed system informs driver to gain an insight about the severity level of arising problematic scenario. In order to realize the classification of confidence regions, we initially obtain the overall dynamic model of the system. Then, disturbance functions with different amplitudes and frequencies are characterized and included in the dynamic system specification. Here, the confidence regions have been constructed as to respective fault severity level of the car through the system response. Trajectory of vehicle in dynamic driving conditions considering these perturbations and noises are interrelated through the Kalman filtering to predict deviations from the desired trajectory and the prediction error. In simulation scenarios, Dynamic Time Warping (DTW) is employed to obtain deviation from ground truth under different noise functions, and results are sketched graphically assigning rate of fault severity into specified confidence regions. Initially, we have modeled the proposed system considering an electric car although the idea can readily be generalized for all cars with four tires. Presently, fault severity with classified confidence regions has been investigated under a simple car model.
- BildiriYalnız künye2013EXAMINATION OF RADIAL FORCE WITH FINITE ELEMENT METHOD IN SWITCHED RELUCTANCE MOTOR
Polat, Mehmet; Öksüztepe, Eyyup; Omaç, Zeki; Yildirim, Merve; Kürüm, Hasan
The aim of this study is computation of radial forces shown as one of the main and important reasons of noise in Switched Reluctance Motor (SRM). In this paper, radial forces in saturation and unsaturation regions of a standart submersible pump type 8/6-pole SRM have been calculated and their changes have been obtained. ANSYS 10.0 package program which makes a solution with Finite Element Method (FEM) has been used for computation of radial forces. After geometric shapes are given, radial forces have been calculated from unaligned position of rotor towards aligned position with angle of one degree according to different current values.
- Dergi2015 23RD SIGNAL PROCESSING AND COMMUNICATIONS APPLICATIONS CONFERENCE (SIU)