Browsing by Author "Aydin S."
Now showing 1 - 14 of 14
Results Per Page
Sort Options
Item Vibrations of a beam-mass systems using artificial neural networks(Elsevier Ltd, 1998) Karlik B.; Özkaya E.; Aydin S.; Pakdemirli M.The nonlinear vibrations of an Euler-Bernoulli beam with a concentrated mass attached to it are investigated. Five different sets of boundary conditions are considered. The transcendental equations yielding the exact values of natural frequencies are presented. Using the Newton-Raphson method, natural frequencies are calculated for different boundary conditions, mass ratios and mass locations. The corresponding nonlinear correction coefficients are also calculated for the fundamental mode. The calculated natural frequencies and nonlinear corrections are used in training a multi-layer, feed-forward, backpropagation artificial neural network (ANN) algorithm. The algorithm produces results within 0.5 and 1.5% error limits for linear and nonlinear cases, respectively. By employing the ANN algorithm, computational time is drastically reduced compared with the conventional numerical techniques. © 1998 Published by Elsevier Science Ltd. All rights reserved.Item Improved approach to the solution of inverse kinematics problems for robot manipulators(Elsevier Science Ltd, 2000) Karlik B.; Aydin S.A structured artificial neural-network (ANN) approach has been proposed here to control the motion of a robot manipulator. Many neural-network models use threshold units with sigmoid transfer functions and gradient descent-type learning rules. The learning equations used are those of the backpropagation algorithm. In this work, the solution of the kinematics of a six-degrees-of-freedom robot manipulator is implemented by using ANN. Work has been undertaken to find the best ANN configurations for this problem. Both the placement and orientation angles of a robot manipulator are used to fin the inverse kinematics solutions.Item Identification of oxalotrophic bacteria by neural network analysis of numerical phenetic data(2006) Sahin N.; Aydin S.A new approach with artificial neural network (ANN) was applied to numerical taxonomy of bacteria using the oxalate as carbon and energy source. For this aim the characters effective in differentiating separate groups were selected from morphological, physiological and biochemical test results. Fourteen aerobic, Gram-negative, oxalate-utilizing isolates and four oxalate-utilizing reference strains (Ralstonia eutropha DSM 428, Methylobacterium extorquens DSM 1337T, Ralstonia oxalatica DSM 1105T, Oxalicibacterium flavum DSM 15506T) were included in the study. ANN program used here was developed in Borland C++ language. Iterations were performed on an IBM compatible PC computer. ANN architecture having feed-forward backpropagation algorithm was used for teaching generalized δ rule. The results show that ANN can have a large potential in solving the taxonomic problems of oxalate-utilizing bacteria.Item Nesfatin-1 and ghrelin levels in serum and saliva of epileptic patients: Hormonal changes can have a major effect on seizure disorders(2009) Aydin S.; Dag E.; Ozkan Y.; Erman F.; Dagli A.F.; Kilic N.; Sahin I.; Karatas F.; Yoldas T.; Barim A.O.; Kendir Y.Nesfatin-1 and ghrelin are the two recently discovered peptide hormones involved in the control of appetite. Besides its main appetite-control function, ghrelin also has anticonvulsant effects, while nesfatin-1 causes depolarization in the paraventricular nucleus (PVN). The aims of this study, therefore, were to investigate: (i) whether there are differences in the concentrations of nesfatin-1 and ghrelin in saliva and serum samples between eplilepsy patients and normal controls and (ii) whether salivary glands produce nesfatin-1. The study included a total of 73 subjects: 8 patients who were newly diagnosed with primary generalized seizures and had recently started antiepileptic drug therapy; 21 who had primary generalized seizures and were continuing with established antiepileptic drug therapy; 24 who had partial seizures (simple: n = 12 or complex: n = 12) and were continuing with established antiepileptic drug therapy; and 20 controls. Salivary gland tissue samples were analyzed for nesfatin-1 expression by immunochemistry and ELISA. Saliva and serum ghrelin levels were measured by ELISA and RIA, and nesfatin-1 levels by ELISA. Nesfatin-1 immunoreactivity was detected in the striated and interlobular parts of the salivary glands and the ducts. The nesfatin-1 level in the brain was around 12 times higher than in the salivary gland. Before antiepileptic treatment, both saliva and serum nesfatin-1 levels were around 160-fold higher in patients who are newly diagnosed with primary generalized epilepsy (PGE) than in controls; these levels decreased with treatment but remained about 10 times higher than the control values. Saliva and serum nesfatin-1 levels from patients with PGE and partial epilepsies who were continuing antiepileptic drugs were also 10-fold higher than control values. Serum and saliva ghrelin levels were significantly (twofold) lower in epileptic patients before treatment than in controls; they recovered somewhat with treatment but remained below the control values. These results suggest that the low ghrelin and especially the dramatically elevated nesfatin-1 levels might contribute to the pathophyisology of epilepsy. Therefore, serum and saliva ghrelin and especially the remarkably increased nesfatin-1 might be candidate biomarkers for the diagnosis of epilepsy and for monitoring the response to anti-epileptic treatment. © Springer Science+Business Media, LLC. 2009.Item Effect of salt in irrigation water on some physical and chemical properties of lettuce plant and soil(Chemical Publishing Co., 2010) Yagmur B.; Aydin S.; Okur B.; Coskun A.Knowledge of salt tolerance in vegetable plants is necessary to increase productivity and profitability of crop irrigated with saline waters. This research was carried out in Celal Bayar University, Alasehir vocational school glasshouse which is in Manisa, Alasehir located in the west part of Agean region. The purpose of the experiment is to determine salinity effects on some chemical and physical properties of lettuce plant and soil and some vegetative growth parameter of plant which is irrigated with water having different concentrations of salt (NaCl). The experiment was established in a randomized block design with four replications. Salinity levels are in five levels as 0-4-8-12-16 dSm -1 EC. Depending on increasing salt concentration m irrigation water, from the soil saturation extract values, especially Na + from cations and Cl - from anions which are dominant compared to others (K +, Mg 2+, SO 4 2-, HCC 3 -) and also increase of total soluble salt values have caused some negativeness in plant production. Different EC levels in irrigation water showed an important effect on K + and Na + content of soil and only Na + content of plant. Highest values were generally obtained at 4 dSm -1 EC for lettuce plant vegetative growing parameters such as dry and fresh head weight, head length and leaf number per plant. However, the increase in salt content of water (> 4 dSm -1 EC) affected negatively these vegetative growing parameters.Item A fuzzy clustering neural networks for motion equations of synchro-drive robot(Elsevier Ltd, 2010) Aydin S.Motion equations for synchro-drive robot Nomad 200 are solved by using fuzzy clustering neural networks. The trajectories of the Nomad 200 are assumed to be composed of line segments and curves. The structure of the curves is determined by only two parameters (turn angle and translational velocity in the curve). The curves of the trajectories are found by using artificial neural networks (ANN) and fuzzy C-means clustered (FCM) ANN. In this study a clustering method is used in order to improve the learning and the test performance of the ANN. The FCM algorithm is successfully used in clustering ANN datasets. Thus, the best of training dataset of ANN is achieved and minimum error values are obtained. It is seen that, FCM-ANN models are better than the classic ANN models. © 2010 Elsevier Ltd. All rights reserved.Item Fat-free milk as a therapeutic approach for constipation and the effect on serum motilin and ghrelin levels(2010) Aydin S.; Donder E.; Akin O.K.; Sahpaz F.; Kendir Y.; Alnema M.M.Objective: This study explores the effects of fat-free milk supplementation on individuals with chronic constipation with regard to levels of motilin and acylated and des-acylated ghrelin (which affect intestinal motility) and compares them with data from control subjects given whole milk supplementation. Methods: The investigation was designed according to the constipation severity test of individuals whose ages and body mass indexes were comparable. Individuals with mild constipation (n=10) were supplemented with 400. mL of fat-free milk daily; moderate constipation cases (n=10) were supplemented with 600 mL, and severe constipation cases (n=10) were supplemented with 800 mL of fat-free milk daily. Healthy control subjects were administered 400 mL of fat-free milk (group 1), which was followed a month later by administration of 400 mL of whole milk for 3 days (group 2). Blood samples were collected from the subjects before and after milk supplementation for hormone analyses. Motilin and acylated and des-acylated ghrelin were quantified with ELISA assay. Results: Supplementation of fat-free milk significantly increased levels of circulating motilin and ghrelin in all groups, including the control subjects, but whole milk supplementation led to a decrease in these hormone levels in the control subjects. Conclusion: Drinking fat-free milk might be a new way of solving constipation. © 2010 Elsevier Inc.Item Using Linde Buzo Gray Clustering Neural Networks for Solving the Motion Equations of a Mobile Robot(Springer Verlag, 2011) Aydin S.; Kilic I.; Temeltas H.In this paper, motion equations for the synchro-drive robot Nomad 200 are solved by using Linde Buzo Gray (LBG) clustering neural networks. The trajectories of the Nomad 200 are assumed to be composed of straight line segments and curves. The structure of the curves is determined by only two parameters, turn angle and translational velocity in the curve. The curves of the trajectories are found by using artificial neural networks (ANN) and the LBG clustered ANN. In this study a clustering method is used to improve the learning and test the performance of the ANN. In general, the LBG algorithm is used in image processing as a quantizer. This is the first publication where the LBG algorithm is successfully used in clustering ANN data sets. Thus, the best training data set of the ANN is achieved and minimum error values are obtained. It is shown that LBG-ANN models are better than the classic ANN models. © 2011 King Fahd University of Petroleum and Minerals.Item A proposed artificial neural network model for PEM fuel cells(IEEE Computer Society, 2013) Sari A.; Balikci A.; Taskin S.; Aydin S.Fuel cells convert the chemical energy directly to the electrical energy and hence they are a very favorable alternative energy source. In the literature, there are many studies related to the modeling of fuel cells. Artificial neural networks (ANNs) is one of the promising techniques for modelling nonlinear systems such as fuel cells. The proposed model in this study doesn't require many parameters like other studies. Firstly, training and testing data was obtained the dynamic model of a PEM fuel-cell. Then, proposed ANN model outputs are compared with dynamic model ouputs Simulation results shows that the proposed ANN model can be used very efficiently for PEM fuel-cells without using many parameters. © 2013 The Chamber of Turkish Electrical Engineers-Bursa.Item Quality parameters of vineyard irrigation water in a semi-arid region: The Plain of Alasehir, Turkey(Parlar Scientific Publications, 2014) Yagmur B.; Aydin S.; Okur B.; Coban H.; Simsek H.Production of seedless raisins is extremely important in Aegean Region in Turkey. The Plain of Alasehir in province of Manisa in Aegean Region is extremely important for seedless raisin production since 25% of the seedless raisin has been grown in this area. The irrigation water samples were collected from 13 different water distribution locations in the Plain of Alasehir. Results showed that pH and EC (electrical conductivity) values were in a reasonable range except EC levels from two locations were slightly high. The vineyard irrigation water in the region was classified as type of C3S1. It was suggested that, the salt content might be monitored continuously since salinity might increase in the soil through the end of the irrigation season. The most common cations were Ca++ and Mg++, and anion was HCO3\ Trace elements and heavy metals were under the risk limits except Mn was high in three locations. Boron was high in nine sampling locations. Overall, irrigation waters in the Plain of Alasehir were suitable for vineyard irrigation as long as the contents of boron and salinity were continuously monitored. © by PSP.Item The nutritional conditions and some heavy metal contents of the vineyards in a semi-arid area(Parlar Scientific Publications, 2015) Aydin S.; Yagmur B.; Coban H.; Simsek H.Turkey is one of the most important seedless raisin producers in the world market. Approximately, 82% of the seedless raisin has been produced in the western part of Turkey since the climate (semi-arid) of this region is very appropriate to grow seedless grape. More specifically, the Plain of Alasehir, located in the Gediz Basin in Aegean Region has been known its high quality seedless raisin production. About 25% of the seedless raisin of the entire Aegean Region is produced in the Plain of Alasehir. Therefore, the Plain of Alasehir region was selected to determine some heavy metal contents (Cd, Co, Cr, and Pb) and certain macro and micro element contents (N, P, K, Ca, Mg, Fe, Zn, Mn, and Cu) of the leaf samples obtained from the vineyards in the area. The plant samples from 13 vineyards were analyzed by collecting the samples across the first plant bunch during the veraison period. In terms of nutrition profile, N deficiency was detected in 15% of vineyards while P deficiency was determined in 38.5 % of the vineyards. Similarly, Fe deficiency was detected in the 30.8 % of the vineyards. The contents of Zn, Mn, Cu, K, Ca, and Mg were sufficient in all of the vineyards. Some heavy metal contents of the leaf samples were analyzed and it was found that there was no pollution for the Cd, Co, and Pb in all the vineyards. Cr pollution was not detected in 93.2% of the samples.Item Harmonic estimation based support vector machine for typical power systems(Institute of Computer Science, 2016) Özdemir S.; Demirtaş M.; Aydin S.The power quality in electrical energy systems is very important and harmonic is the vital criterion. Traditionally Fast Fourier Transform (FFT) and Discrete Fourier Transform (DFT) have been used for the harmonic distortion analysis and in the literature harmonic estimations have been made using di erent methods. As an alternative method, this paper suggested using Support Vector Machine (SVM) for harmonic estimation. The real power energy distribution system has been examined and the estimation results have been compared with measured real data. The proposed solution approach was comparatively evaluated with the ANN and LR estimation methods. Comparison results show that THD estimation values that were obtained by the SVM method are close to the THD estimation values obtained from ANN (Artificial Neural Network) and LR (Linear regression) methods. The numerical results clearly showed that the SVM method is valid for THD estimation in the power system. © 2016 CTU FTS.Item Examining beliefs of preservice teachers about self-competency and lifelong learning competency via canonical correlation analysis(Birlesik Dunya Yenilik Arastirma ve Yayıncilik Merkezi, 2018) Selcuk G.; Aydin S.; Cakmak A.This study investigates the canonical correlation between preservice teachers’ lifelong learning beliefs and self-competency beliefs. Canonical correlation analysis is a sophisticated tool which has the capacity to explain the relationships between two sets of variables. For this aim, lifelong learning and self-competency beliefs of 1,242 preservice teachers in Turkey from four different departments, i.e., i) Turkish education, ii) social sciences education, iii) primary education and iv) science education were determined. The data were analyzed using the SPSS 22 program. The findings of the study demonstrated that there is a significant canonical correlation between self-competency beliefs and lifelong learning competency beliefs with an effect size of 44%. In conclusion, self-competency beliefs predict lifelong learning competency beliefs. All dimensions of self-competency beliefs are powerful predictors of lifelong learning competency beliefs. © 2018 SciencePark Research, Organization & Counseling. All rights reserved.Item Preparation and characterization of novel boron containing nanocomposites with neutron radiation shielding properties(John Wiley and Sons Inc, 2023) Saltan F.; Şirin K.; Aydin S.; Yildirim Y.PVA/PEO/PVP-B4C and PVA/PEO/PVP-BN polymer nanocomposites were prepared using boron nitrite (BN), boron carbide (B4C), polyvinyl alcohol (PVA), polyvinylpyrrolidone (PVP), and polyethylene oxide (PEO). B4C and BN nanopowders were added to the mixture at three different percentages: 5%, 10%, and 20%. Thermal characterization was performed by differential scanning calorimetry, differential thermal analysis and thermogravimetry. Scanning electron microscopy, X-ray photoelectron spectroscopy, and X-ray diffraction were used for surface analysis and crystal structure characterization. The atomic distribution was determined by elemental analysis. Neutron shielding properties were performed at three different gamma peak areas, 1293.56 keV, 1097.33 keV, 416.86 keV, and calculated total macroscopic cross-section ∑T and half-value layer. The ∑T values were found to be in the range of 7.99–14.37 for all synthesized composites. B4C-doped composites show higher protection efficiency against slow thermal neutrons than BN-doped samples. Highlights: Poly(vinyl alcohol)/poly(ethylene oxide)/polyvinylpyrrolidone composites containing boron nanoparticles are flexible and workable. Nanocomposites were prepared with a simple, cheap, and fast method. Prepared boron nanocomposites exhibit slow thermal neutron stopping even at 3 mm thickness. PVA90/PEO5/PVP5-BN and PVA90/PEO5/PVP5-B4C composites are good candidates for demanding military applications such as vehicle and body armor. © 2023 Society of Plastics Engineers.