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Article Citation - WoS: 27Citation - Scopus: 35A Wavelet-Based Feature Set for Recognizing Pulse Repetition Interval Modulation Patterns(Tubitak Scientific & Technological Research Council Turkey, 2016) Gencol, Kenan; At, Nuray; Kara, AliThis 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: 1Citation - Scopus: 2Cannabinoid Receptor Ligands Modulate Fibrosis and Inflammation in Idiopathic Pulmonary Fibrosis: a Preliminary Study(Tubitak Scientific & Technological Research Council Turkey, 2024) Kose, Sevil; Onen, Selin; Gizer, Merve; Boduroglu, Esin; Gonullu, Ugur; Korkusuz, PetekBackground/aim: No specific pharmacological treatment regimen for idiopathic pulmonary fibrosis (IPF) exists. Therefore, new antiinflammatory therapeutic strategies are needed. Cannabinoids (CBs), known for their inflammation-modulating and antifibrotic effects, may be potential medication candidates for treating IPF. We aim to evaluate the inflammation-modulating and antifibrotic effects of CB receptor (CBR) agonists and antagonists in lipopolysaccharide-stimulated normal human lung fibroblast, epithelial cells, IPF fibroblast cells, and monocytes. Materials and methods: We detected CBRs in normal human lung fibroblasts (LL24) and IPF fibroblast cells (LL29), epithelial cells (A549) and monocytes (THP-1) by flow cytometry. We determined TGF-(31, IL-8, and TNF-alpha inflammatory cytokines in the LL24, LL29, A549, and THP-1 cell culture supernatants on days 1 and 5 by ELISA. We evaluated the cell viability in LL24, LL29, and A549 cells on days 1, 3, and 5 spectrophotometrically and detected collagen Type I (ColI) production in the LL24 and LL29 cell culture supernatants on days 1, 3, and 5 by ELISA. Results: LL24, LL29, A549, and THP-1 cells exhibited CB1 (CB1R) and CB2 (CB2R) receptors. CB1R and CB2R agonists WIN55,2122 and JWH015 inhibited fibroblastic and epithelial cell proliferation on day 5. TGF-(31 and TNF-alpha release increased, while IL-8 release decreased in LL24, LL29, A549, and THP-1 cells in response to the administration of WIN55,212-2 and JWH015 at a 10-2 mM concentration. CB1R and CB2R antagonists AM251 and AM630 did not block agonistic responses, suggesting a nonclassical CBRmediated pathway. CB2R agonist JWH015 decreased ColI expression in IPF lung fibroblasts LL29 on day 3. Conclusion: These results suggest that CB signaling regulates the progression of pulmonary inflammation and fibrosis via CBR activation. This may offer a potential pharmacological tool for developing antifibrosis therapies.Article Citation - WoS: 11Citation - Scopus: 12Mutual Correlation of Nist Statistical Randomness Tests and Comparison of Their Sensitivities on Transformed Sequences(Tubitak Scientific & Technological Research Council Turkey, 2017) Doganaksoy, Ali; Sulak, Fatih; Uguz, Muhiddin; Seker, Okan; Akcengiz, ZiyaRandom sequences are widely used in many cryptographic applications and hence their generation is one of the main research areas in cryptography. Statistical randomness tests are introduced to detect the weaknesses or nonrandom characteristics that a sequence under consideration may have. In the literature, there exist various statistical randomness tests and test suites, defined as a collection of tests. An efficient test suite should consist of a number of uncorrelated statistical tests each of which measures randomness from another point of view. `Being uncorrelated' is not a well-defined or well-understood concept in the literature. In this work, we apply Pearson's correlation test to measure the correlation between the tests. In addition, we define five new methods for transforming a sequence. Our motivation is to detect those tests whose results are invariant under a certain transformation. To observe the correlation, we use two methods. One is the direct correlation between the tests and the other is the correlation between the results of a test on the sequence and its transformed form. In light of the observations, we conclude that some of the tests are correlated with each other. Furthermore, we conclude that in designing a reliable and efficient suite we can avoid overpopulating the list of test functions by employing transformations together with a reasonable number of statistical test functions.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 Citation - WoS: 5Citation - Scopus: 10Quality of Service Assessment: a Case Study on Performance Benchmarking of Cellular Network Operators in Turkey(Tubitak Scientific & Technological Research Council Turkey, 2015) Kadioglu, Rana; Dalveren, Yaser; Dalveren, Yaser; Kara, Ali; Kara, Ali; Dalveren, Yaser; Kara, Ali; Department of Electrical & Electronics Engineering; Department of Electrical & Electronics EngineeringThis paper presents findings on performance benchmarking of cellular network operators in Turkey. Benchmarking 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 Neuron Modeling: Estimating the Parameters of a Neuron Model From Neural Spiking Data(Tubitak Scientific & Technological Research Council Turkey, 2018) Doruk, Resat OzgurWe present a modeling study aiming at the estimation of the parameters of a single neuron model from neural spiking data. The model receives a stimulus as input and provides the firing rate of the neuron as output. The neural spiking data will be obtained from point process simulation. The resultant data will be used in parameter estimation based on the inhomogeneous Poisson maximum likelihood method. The model will be stimulated by various forms of stimuli, which are modeled by a Fourier series (FS), exponential functions, and radial basis functions (RBFs). Tabulated results 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 performance appears to be the sample size. In addition, the lowest variance of the estimates is obtained when a Fourier series stimulus is applied in the estimation.Article Citation - WoS: 20Citation - Scopus: 22Electrochemical and Optical Properties of an Azo Dye Based Conducting Copolymer(Tubitak Scientific & Technological Research Council Turkey, 2009) Cihaner, Atilla; Algi, 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 pi-pi* transition at 555 nm.Article Citation - WoS: 3Citation - Scopus: 5Investigation of the Effect of Hyperthyroidism on Endoplasmic Reticulum Stress and Transient Receptor Potential Canonical 1 Channel in the Kidney(Tubitak Scientific & Technological Research Council Turkey, 2021) Aykanat, Nuriye Ezgi Bektur; Şahin, Erhan; Kaçar, Sedat; Bağcı, Rıdvan; Karakaya, Şerife; Dönmez, Dilek Burukoğlu; Şahintürk, VarolBackground/aim: Hyperthyroidism is associated with results in increased glomerular filtration rate as well as increased renin-angiotensin-aldosterone activation. The disturbance of Ca2+ homeostasis in the endoplasmic reticulum (ER) is associated with many diseases, including diabetic nephropathy and hyperthyroidism. Transient receptor potential canonical 1 (TRPC1) channel is the first cloned TRPC family protein. Although it is expressed in many places in the kidney, its function is uncertain. TRPC1 is involved in regulating Ca2+ homeostasis, and its upregulation increases ER Ca2+ level, activates the unfolded protein response, which leads to cellular damage in the kidney. This study investigated the role of TRPC1 in the kidneys of hyperthyroid rats in terms of ER stress markers that are glucose-regulated protein 78 (GRP78), activating transcription factor 6 (ATF6), (protein kinase R (PKR)-like endoplasmic reticulum kinase) (PERK), Inositol-requiring enzyme 1 (IRE1). Materials and methods: Twenty male rats were assigned into control and hyperthyroid groups (n = 10). Hyperthyroidism was induced by adding 12 mg/L thyroxine into the drinking water of rats for 4 weeks. The serum-free T3 and T4 (fT3, fT4), TSH, blood urea nitrogen (BUN), and creatinine levels were measured. The histochemical analysis of kidney sections for morphological changes and also immunohistochemical and western blot analysis of kidney sections were performed for GRP78, ATF6, PERK, IRE1, TRPC1 antibodies. Results: TSH, BUN, and creatinine levels decreased while fT3 and fT4 levels increased in the hyperthyroid rat. The morphologic analysis resulted in the capillary basal membrane thickening in glomeruli and also western blot, and immunohistochemical results showed an increase in TRPC1, GRP78, and ATF6 in the hyperthyroid rat (p < 0.05). Conclusion: In conclusion, in our study, we showed for the first time that the relationship between ER stress and TRPC1, and their increased expression caused renal damage in hyperthyroid rats.Key words: Hyperthyroidism, endoplasmic reticulum (ER) stress, transient receptor potential canonical 1 (TRPC1), kidney, ratArticle ISAR Imaging of Drone Swarms at 77 GHz(Tubitak Scientific & Technological Research Council Turkey, 2025) Coruk, Remziye Busra; Kara, Ali; Aydin, ElifThe proliferation of easily available, internet-purchased drones, coupled with the emergence of coordinated drone swarms, poses a significant security threat for airspace. Detecting these swarms is crucial to prevent potential accidents, criminal misuse, and airspace disruptions. This paper proposes a novel inverse synthetic aperture radar (ISAR) imaging technique for high-resolution reconstruction of drone swarms at 77 GHz millimeter wave (mmWave) frequency, offering a valuable tool for military and defense antidrone systems. The key parameters affecting down-range and cross-range resolution (0.05 m), ultimately enabling the generation of detailed ISAR images are discussed. Here, we create diverse scenarios encompassing various swarm formations, sizes, and payload configurations by employing ANSYS simulations. To enhance image quality, different window functions are evaluated, and the Hamming window is selected due to its highest peak signal-to-noise ratio (PSNR) (16.3645) and structural similarity (SSIM) (0.9067) values, ensuring superior noise reduction and structural preservation. The results demonstrate that the effectiveness of high-resolution ISAR imaging in accurately detecting and characterizing drone swarms pave the way for enhanced airspace security measures.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.
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