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Özmen, Atilla
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Özmen, Atilla
A.,Özmen
A. Özmen
Atilla, Özmen
Ozmen, Atilla
A.,Ozmen
A. Ozmen
Atilla, Ozmen
Özmen, A.
Ozmen, A.
Özmen, Atilla
A.,Özmen
A. Özmen
Atilla, Özmen
Ozmen, Atilla
A.,Ozmen
A. Ozmen
Atilla, Ozmen
Özmen, A.
Ozmen, A.
Özmen, Atilla
Job Title
Dr. Öğr. Üyesi
Email Address
Main Affiliation
Electrical-Electronics Engineering
Electrical-Electronics Engineering
05. Faculty of Engineering and Natural Sciences
01. Kadir Has University
Electrical-Electronics Engineering
05. Faculty of Engineering and Natural Sciences
01. Kadir Has University
Status
Former Staff
Website
ORCID ID
Scopus Author ID
Turkish CoHE Profile ID
Google Scholar ID
WoS Researcher ID
Sustainable Development Goals
3
GOOD HEALTH AND WELL-BEING
3
Research Products
7
AFFORDABLE AND CLEAN ENERGY
1
Research Products
11
SUSTAINABLE CITIES AND COMMUNITIES
2
Research Products
13
CLIMATE ACTION
1
Research Products
17
PARTNERSHIPS FOR THE GOALS
1
Research Products
This researcher does not have a Scopus ID.
This researcher does not have a WoS ID.
Scholarly Output
46
Articles
13
Views / Downloads
266/4789
Supervised MSc Theses
8
Supervised PhD Theses
1
WoS Citation Count
140
Scopus Citation Count
202
WoS h-index
5
Scopus h-index
6
Patents
0
Projects
0
WoS Citations per Publication
3.04
Scopus Citations per Publication
4.39
Open Access Source
22
Supervised Theses
9
Google Analytics Visitor Traffic
| Journal | Count |
|---|---|
| 2012 International Symposium on Innovations in Intelligent Systems and Applications | 2 |
| 2007 IEEE 15th Signal Processing and Communications Applications, SIU | 1 |
| 2011 IEEE 19th Signal Processing and Communications Applications Conference, SIU 2011 | 1 |
| 2015 9th International Conference on Electrical and Electronics Engineering (ELECO) | 1 |
| 2018 26th Signal Processing and Communications Applications Conference (SIU) | 1 |
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Scholarly Output Search Results
Now showing 1 - 10 of 46
Article Citation - WoS: 6Citation - Scopus: 6Correlation of Ternary Liquid- Equilibrium Data Using Neural Network-Based Activity Coefficient Model(Springer, 2014) Özmen, AtillaLiquid--liquid equilibrium (LLE) data are important in chemical industry for the design of separation equipments and it is troublesome to determine experimentally. In this paper a new method for correlation of ternary LLE data is presented. The method is implemented by using a combined structure that uses genetic algorithm (GA)--trained neural network (NN). NN coefficients that satisfy the criterion of equilibrium were obtained by using GA. At the training phase experimental concentration data and corresponding activity coefficients were used as input and output respectively. At the test phase trained NN was used to correlate the whole experimental data by giving only one initial value. Calculated results were compared with the experimental data and very low root-mean-square deviation error values are obtained between experimental and calculated data. By using this model tie-line and solubility curve data of LLE can be obtained with only a few experimental data.Conference Object Genetic Algorithm Based Broadband Equalizer Design With Ripple Level Control(IEEE, 2012) Şengül, Metin Y.; Özmen, AtillaIn this paper broadband equalizer design with ripple control via genetic algorithm has been studied. The equalizer is defined as a lossless two-port terminated by load impedance and the coefficients of its describing scattering polynomials have been optimized via genetic algorithm. During the optimization process ripple level of the transducer power gain has been controlled. An example has been given to illustrate the utilization of the proposed approach. © 2012 IEEE.Conference Object Citation - WoS: 1Design and Implementation of a Cellular Neural Network Based Oscillator Circuit(World Scientific and Engineering Acad and Soc, 2009) Tander, Baran; Özmen, Atilla; Özçelep, YasinIn this paper, a novel inductorless oscillator circuit with negative feedbacks, based on a simple version of a "Cellular Neural Network" (CNN) called "CNN with an Opposite Sign Template" (CNN-OST) is designed and implemented. The system is capable of generating quasi-sine oscillations with tuneable amplitude and frequency which can't be provided at the same time in the conventional oscillator circuits.Article Citation - WoS: 4Citation - Scopus: 6Channel Estimation for Realistic Indoor Optical Wireless Communication in Aco-Ofdm Systems(Springer, 2018) Özmen, Atilla; Şenol, HabibIn this paper channel estimation problem in a visible light communication system is considered. The information data is transmitted using asymmetrical clipped optical orthogonal frequency division multiplexing. Channel estimation and symbol detection are performed by the Maximum Likelihood and the Linear Minimum Mean Square Error detection techniques respectively. The system performance is investigated in realistic environment that is simulated using an indoor channel model. Two different channels are produced using the indoor channel model. Symbol error rate (SER) performance of the system with estimated channels is presented for QPSK and 16-QAM digital modulation types and compared with the perfect channel state information. As a mean square error (MSE) performance benchmark for the channel estimator Cramer-Rao lower bound is also derived. MSE and SER performances of the simulation results are presented.Article Citation - WoS: 1Citation - Scopus: 1Bayesian Estimation of Discrete-Time Cellular Neural Network Coefficients(TUBITAK Scientific & Technical Research Council Turkey, 2017) Özer, Hakan Metin; Özmen, Atilla; Şenol, HabibA new method for finding the network coefficients of a discrete-time cellular neural network (DTCNN) is proposed. This new method uses a probabilistic approach that itself uses Bayesian learning to estimate the network coefficients. A posterior probability density function (PDF) is composed using the likelihood and prior PDFs derived from the system model and prior information respectively. This posterior PDF is used to draw samples with the help of the Metropolis algorithm a special case of the Metropolis--Hastings algorithm where the proposal distribution function is symmetric and resulting samples are then averaged to find the minimum mean square error (MMSE) estimate of the network coefficients. A couple of image processing applications are performed using these estimated parameters and the results are compared with those of some well-known methods.Article Citation - WoS: 3Citation - Scopus: 3Deep Learning Based Combining Rule for the Estimation of Vapor-Liquid Equilibrium(Springer Heidelberg, 2023) Bekri, Sezin; Ozmen, Dilek; Ozmen, AtillaVapor-liquid equilibrium (VLE) data plays a vital role in the design, modeling and control of process equipment. In this study, to estimate the VLE data of binary systems, a deep neural network (DNN)-based combining rule was proposed based on the cross-term parameter (a(ij)) in the two-parameter Peng-Robinson cubic equation of state (PR-EoS) combined with the one-parameter classical van der Waals mixing and combining rule (1PVDW). Experimental VLE data of alternative binary refrigerant systems selected from the literature were calculated using both the PR + 1PVDW and the DNN-based model. Vapor phase mole fractions (y(i)) and equilibrium pressures (P) obtained from the proposed DNN-based and PR + 1PVDW models were compared in the terms of average percent deviations. For the DNN-based model, the vapor phase mole fractions give at least as good results as the models in the literature, and also it has been shown that a much better estimate of the equilibrium pressure (P) is obtained when compared with that of the literature. Results obtained using the proposed DNN-based model are presented with tables and graphs. For the equilibrium pressure, while the average percent deviation errors (Delta P/P%) calculated in the literature are less than 7.739, the errors obtained with the proposed DNN-based model are smaller than 3.455. And also, for vapor phase mole fractions, while the maximum error (Delta(y1)/(y1) %) in the literature is obtained as 6.142, the largest error calculated with DNN-based model is 3.545. It has been seen that the proposed DNN-based model makes more practical and less error-prone estimations than the methods in the literature.Conference Object Citation - Scopus: 2Analytical approaches for the amplitude and frequency computations in the astable cellular neural networks with opposite sign templates(2007) Tander, B.; Özmen, A.In this paper, by using surface fitting methods, analytical approaches for amplitudes and frequencies of the x1,2(t) "States" in a simple dynamical neural network called "Cellular Neural Network with Opposite Sign Templates" which was proposed by Zou and Nossek [1], are obtained under oscillation conditions. The mentioned explicit expressions are employed in a cellular neural network based, amplitude and frequency tuneable oscillator design.Master Thesis Caching Algorithm Implementation for Edge Computing in Iot Network(Kadir Has Üniversitesi, 2020) Abduljabbar, Mohammed; Özmen, Atilla; Öğrenci, Arif SelçukThe developing IoT concept brings new challenges to the service providers. The architecture of the networks changes to satisfy the needs arising by the large number of connected devices. Edge computing is the new architectural solution that will be used in the IoT networks. This architecture is more dynamic than the cloud computing network where the data can be quickly processed in the different layers of the network without going to the cloud. This will remove the problems faced by cloud computing: increase in data traffic and increase in latency of provided services. Research on edge computing in IoT networks encompass information-centric networks, use of 5G, and improving the hardware devices however a suitable solution for all the IoT use cases is not available yet. In this thesis, use of caching among IoT nodes is proposed as a solution to increase the efficiency of edge computing. Caching is an old but effective solution for dealing with data because it improves the real-time response of the system and can be used in IoT use cases. It will also not cause an extra hardware cost. In this research, two commonly used caching algorithms, LRU (Least Recently Used) and FIFO (First in First Out), are investigated and compared for their performance in sample IoT scenarios. Reductions in data processing time are observed where CPU and RAM utilizations are enhanced.Article Citation - WoS: 11Citation - Scopus: 12Application of Deep Neural Network (dnn) for Experimental Liquid-Liquid Equilibrium Data of Water + Butyric Acid + 5-Methyl Ternary Systems(Elsevier B.V., 2021) Bekri, Sezin; Dilek, Özmen; Aykut, Türkmenoğlu; Atilla, ÖzmenLLE data are important for simulation and design of extraction equipment. In this study, deep neural network (DNN) structure was proposed for modelling of the ternary liquid-liquid equilibrium (LLE). LLE data of (water + butyric acid + 5-methyl-2-hexanone) ternaries defined at three different temperatures of 298.2, 308.2, and 318.2 K and P = 101.3 kPa, were obtained experimentally and then correlated with nonrandom two-liquid (NRTL) and universal quasi-chemical (UNIQUAC) models. The performance of the proposed DNN model was compared with that of NRTL and UNIQUAC in terms of the root mean square errors (RMSE). RMSE values were obtained between 0.02-0.06 for NRTL and UNIQUAC, respectively. For DNN, the error values were obtained between 0.00005-0.01 for all temperatures. According to the calculated RMSE values, it was shown that proposed DNN structure can be better choice for the modelling of LLE system. Othmer-Tobias and Hand correlations were also used for the experimental tie-lines. Distribution coefficient and separation factors were calculated from the experimental data.Conference Object Unifac Application To Water-1 Alcohol and N-Amyl Acetate Ternaries(2006) Özmen, Atilla; Çehreli, SüheylaLiquid-liquid equilibrium (LLE) data for water-1-propanol-n-amyl alcohol and water-1-propanol-n-amyl acetate ternaries were measured at T=298.2 K. The UNIFAC model was used to correlate the experimental data. A comparison of the extracting capabilities of the solvents was made with respect to distribution coefficients and separation factors.
