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Article Quality of Service Assessment: a Case Study on Performance Benchmarking of Cellular Network Operators in Turkey(2015) Kadıoğlu, Rana; Dalveren, Yaser; Kara, AliAbstract: This paper presents findings on performance benchmarking of cellular network operators in Turkey. Bench- marking is based on measurements of standard key performance indicators (KPIs) in one of the metropolitan cities of Turkey, Ankara. Performance benchmarking is formulated by incorporating customer perception by conducting surveys on how important KPIs are from the user s point of view. KPIs are measured, with standard test equipment, by drive test method on specified routes. According to the performance benchmarking results, the GSM and UMTS network operators achieving the best performance were determined in Ankara. Speech qualities of network operators, as the most popular service, were also evaluated by several statistical methods including pdf/cdf analysis and chi-square and Fisher s exact tests. The network operator providing the highest speech quality in Ankara was determined with the methods applied. Overall, the results and approaches on benchmarking of cellular networks in Turkey are reported for the first time in this paper. The approaches proposed in this paper could be adapted to wide-scale benchmarking of services in cellular networks.Article Citation - WoS: 7Citation - Scopus: 9Ann-Assisted Forecasting of Adsorption Efficiency To Remove Heavy Metals(Tubitak Scientific & Technological Research Council Turkey, 2019) Buaısha, Magdi; Balku, Şaziye; Yaman, Şeniz ÖzalpIn wastewater treatment, scientific and practical models utilizing numerical computational techniques suchas artificial neural networks (ANNs) can significantly help to improve the process as a whole through adsorption systems.In the modeling of the adsorption efficiency for heavy metals from wastewater, some kinetic models have been used such as pseudo first-order and second-order. The present work develops an ANN model to forecast the adsorption efficiency of heavy metals such as zinc, nickel, and copper by extracting experimental data from three case studies. To do this, we apply trial-and-error to find the most ideal ANN settings, the efficiency of which is determined by mean square error (MSE) and coefficient of determination (R2). According to the results, the model can forecast adsorption efficiency percent (AE%) with a tangent sigmoid transfer function (tansig) in the hidden layer with 10 neurons and a linear transferfunction (purelin) in the output layer. Furthermore, the Levenberg–Marquardt algorithm is seen to be most ideal for training the algorithm for the case studies, with the lowest MSE and high R2 . In addition, the experimental results and the results predicted by the model with the ANN were found to be highly compatible with each other.Article A Wavelet-Based Feature Set for Recognizing Pulse Repetition Interval Modulation Patterns(2016) Gençol, Kenan; At, Nuray; Kara, AlıThis paper presents a new feature set for the problem of recognizing pulse repetition interval (PRI) modulation patterns. The recognition is based upon the features extracted from the multiresolution decomposition of different types of PRI modulated sequences. Special emphasis is placed on the recognition of jittered and stagger type PRI sequences due to the fact that these types of PRI sequences appear predominantly in modern electronic warfare environments for some specific mission requirements and recognition of them is heavily based on histogram features. We test our method with a broad range of PRI modulation parameters. Simulation results show that the proposed feature set is highly robust and separates jittered, stagger, and other modulation patterns very well. Especially for the stagger type of PRI sequences, wavelet-based features outperform conventional histogram-based features. Advantages of the proposed feature set along with its robustness criteria are analyzed in detail.Article Citation - WoS: 12Citation - Scopus: 12A Polarity Calculation Approach for Lexicon-Based Turkish Sentiment Analysis(Tubitak Scientific & Technological Research Council Turkey, 2019) Yurtalan, Gökhan; Koyuncu, Murat; Turhan, ÇiğdemSentiment analysis attempts to resolve the senses or emotions that a writer or speaker intends to send across tothe people about an object or event. It generally uses natural language processing and/or artificial intelligence techniquesfor processing electronic documents and mining the opinion specified in the content. In recent years, researchers haveconducted many successful sentiment analysis studies for the English language which consider many words and wordgroups that set emotion polarities arising from the English grammar structure, and then use datasets to test theirperformance. However, there are only a limited number of studies for the Turkish language, and these studies have lowerperformance results compared to those studies for English. The reasons for this can be incorrect translation of datasetsfrom English into Turkish and ignoring the special grammar structures in the latter. In this study, special Turkish wordsand linguistic constructs which affect the polarity of a sentence are determined with the aid of a Turkish linguist, and anappropriate lexicon-based polarity determination and calculation approach is introduced for this language. The proposedmethodology is tested using different datasets collected from Twitter, and the test results show that the proposed systemachieves better accuracy than the previously developed lexical-based sentiment analysis systems for Turkish. The authorsconclude that especially analysis of word groups increases the overall performance of the system significantly.Article Synthesis, Properties, and Electrochemistry of a Photochromic Compound Based on Dithienylethene and Prodot(2015) Algı, Melek Pamuk; Cihaner, Atilla; Algı, FatihAbstract: The synthesis, photochromic features, and electrochemistry of a novel material based on dithienylethene (DTE) and 3,3-didecyl-3,4-dihydro-2H-thieno[3,4-b][1,4]dioxepine (didecyl-ProDOT) units are described. It is noteworthy that 1,2-bis(5-(3,3-didecyl-3,4-dihydro-2H-thieno[3,4-b][1,4]dioxepin-6-yl)-2-methylthiophen-3-yl)cyclopent-1-ene can be efficiently switched between open and closed states by light in both solution and in the solid poly(methyl metacrylate) (PMMA) matrix. It is also found that the emission of this novel compound can be switched on and off upon irradiation.Article Electrochemical and Optical Properties of an Azo Dye Based Conducting Copolymer(2009) Cihaner, Atilla; Algı, FatihThe electrochemical and optical properties of a novel conducting copolymer called poly(2,5' -dimethyl-[4- (2,5-di-thiophen-2-yl-pyrrol-1-yl)-phenyl]azobenzene-co-(3,4-ethylenedioxythiophene)) (poly(1-co-EDOT)) are reported. Electrochemically synthesized poly(1-co-EDOT) based on the azo dye has a well-defined and reversible redox couple (0.37 V vs. Ag/AgCl) with good cycle stability. The copolymer film exhibits high conductivity (13 S/cm) as well as electrochromic behavior (magenta when neutralized and transmissive sky blue when oxidized). Furthermore, electro-optically active copolymer film has a low band gap of 1.79 eV with a π − π* transition at 555 nm.Article Fitting a Recurrent Dynamical Neural Network To Neural Spiking Data: Tackling the Sigmoidal Gain Function Issues(Tubitak Scientific & Technological Research Council Turkey, 2019) Doruk, Reşat ÖzgürThis is a continuation of a recent study (Doruk RO, Zhang K. Fitting of dynamic recurrent neural networkmodels to sensory stimulus-response data. J Biol Phys 2018; 44: 449-469), where a continuous time dynamical recurrentneural network is fitted to neural spiking data. In this research, we address the issues arising from the inclusion ofsigmoidal gain function parameters to the estimation algorithm. The neural spiking data will be obtained from the samemodel as that of Doruk and Zhang, but we propose a different model for identification. This will also be a continuoustime recurrent neural network, but with generic sigmoidal gains. The simulation framework and estimation algorithmsare kept similar to that of Doruk and Zhang so that we can have a solid base to compare the results. We evaluatethe estimation performance in two different ways. First, we compare the firing rate responses of the original and theestimated model. We find that responses of both models to the same stimuli are similar. Secondly, we evaluate variationsof the standard deviations of the estimates against a number of samples and stimulus parameters. They show a similarpattern to that of Doruk and Zhang. We thus conclude that our model serves as a reasonable alternative provided thatfiring rate is the response of interest (to any stimulus).Article The Synthesis, Characterization and Energy Transfer Efficiency of a Dithienylpyrrole and Bodipy Based Donor-Acceptor System(2009) Atalar, Taner; Cihaner, Atilla; Algı, FatihA dithienylpyrrole-BODIPY based donor-acceptor system with 1,4-phenylene spacer as a model system for energy transfer was designed and synthesized. Absorption and emission spectra have revealed an efficient resonance energy transfer from dithienylpyrrole as donor to BODIPY as acceptor.Article Neuron Modeling: Estimating the Parameters of a Neuron Model From Neural Spiking Data(2018) Doruk, Reşat ÖzgürWe present a modeling study aiming at the estimation of the parameters of a single neuron model from neuralspiking data. The model receives a stimulus as input and provides the firing rate of the neuron as output. The neuralspiking data will be obtained from point process simulation. The resultant data will be used in parameter estimationbased on the inhomogeneous Poisson maximum likelihood method. The model will be stimulated by various forms ofstimuli, which are modeled by a Fourier series (FS), exponential functions, and radial basis functions (RBFs). Tabulatedresults presenting cases with different sample sizes (# of repeated trials), stimulus component sizes (FS and RBF),amplitudes, and frequency ranges (FS) will be presented to validate the approach and provide a means of comparison.The results showed that regardless of the stimulus type, the most effective parameter on the estimation performanceappears to be the sample size. In addition, the lowest variance of the estimates is obtained when a Fourier series stimulusis applied in the estimation.Article Experimental and Theoretical Investigation of the Reaction Between Co2andcarbon Dioxide Binding Organic Liquids(2016) Tankal, Hilal; Orhan, Özge Yüksel; Alper, Erdoğan; Özdoğan, Telhat; Kayı, HakanThe reaction kinetics of CO2absorption into new carbon dioxide binding organic liquids (CO2BOLs) was com-prehensively studied to evaluate their potential for CO2removal. A stopped- ow apparatus with conductivity detectionwas used to determine the CO2absorption kinetics of novel CO2BOLs composed of DBN (1,5-diazabicyclo[4.3.0]non-5-ene)/1-propanol and TBD (1,5,7-triazabicyclo[4.4.0]dec-5-ene)/1-butanol. A modi ed termolecular reaction mechanismfor the reaction of CO2with CO2BOLs was used to calculate the observed pseudo- rst{order rate constant k0(s1)and second-order reaction rate constant k2(m3/kmol.s). Experiments were performed by varying organic base (DBN orTBD) weight percentage in alcohol medium for a temperature range of 288{308 K. It was found that k0increased withincreasing amine concentration and temperature. By comparing using two different CO2BOL systems, it was observedthat the TBD/1-butanol system has faster reaction kinetics than the DBN/1-propanol system. Finally, experimentaland theoretical activation energies of these CO2BOL systems were obtained and compared. Quantum chemical calcula-tions using spin restricted B3LYP and MP2 methods were utilized to reveal the structural and energetic details of thesingle-step termolecular reaction mechanism.
