Scopus İndeksli Yayınlar Koleksiyonu / Scopus Indexed Publications Collection
Permanent URI for this collectionhttps://hdl.handle.net/11147/7148
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Article Citation - WoS: 3Citation - Scopus: 3Determining the Complexity of Multi-Component Conformal Systems: a Platoon-Based Approach(Elsevier Ltd., 2017) Koşun, Çağlar; Özdemir, SerhanMany systems in nature and engineering are composed of subsystems. These subsystems may be formed in a linear, planar or spatial array. A typical example of these formations is a chain of vehicles known as platoon formation in traffic flow. Platoon formation of vehicles is a linear or planar formation of vehicles where a certain and a constant headway, and sideway if applicable, is provided in between every and each one of them. It is argued in this paper that a well-automated platoon formation of vehicles is an extreme case of conformity. During this transformation from a many degrees of freedom formation to a solid object, Tsallis q value is computed to be ranging from one extreme case of q=3 to the other where q=1, when classified in terms of inverse temperatures of clearance fluctuations. At one extreme of q=3, one observes unbounded fluctuations in clearance fluctuations so that inverse temperature distributions approach a Dirac delta at the origin. At the other extreme of q=1, fluctuations in clearance tend to zero asymptotically, where a solid structure of agents (vehicles) emerges. The transition from q=3 to q=1 is investigated through synthetic and experimental clearance fluctuations between the cars. The results show that during the transition from q=3 to q=1, the platoon loses its many degrees of freedom (dof) of motion until a solid single object emerges. Authors assert that the Tsallis q value of a platoon of vehicles is limited to 3>q<1.Article Citation - WoS: 14Citation - Scopus: 15A Superstatistical Model of Vehicular Traffic Flow(Elsevier Ltd., 2016) Koşun, Çağlar; Özdemir, SerhanIn the analysis of vehicular traffic flow, a myriad of techniques have been implemented. In this study, superstatistics is used in modeling the traffic flow on a highway segment. Traffic variables such as vehicular speeds, volume, and headway were collected for three days. For the superstatistical approach, at least two distinct time scales must exist, so that a superposition of nonequilibrium systems assumption could hold. When the slow dynamics of the vehicle speeds exhibit a Gaussian distribution in between the fluctuations of the system at large, one speaks of a relaxation to a local equilibrium. These Gaussian distributions are found with corresponding standard deviations 1/β. This translates into a series of fluctuating beta values, hence the statistics of statistics, superstatistics. The traffic flow model has generated an inverse temperature parameter (beta) distribution as well as the speed distribution. This beta distribution has shown that the fluctuations in beta are distributed with respect to a chi-square distribution. It must be mentioned that two distinct Tsallis q values are specified: one is time-dependent and the other is independent. A ramification of these q values is that the highway segment and the traffic flow generate separate characteristics. This highway segment in question is not only nonadditive in nature, but a nonequilibrium driven system, with frequent relaxations to a Gaussian.Article Citation - Scopus: 1Cost Effective Localization in Distributed Sensory Networks(Elsevier Ltd., 2011) Coşkun, Anıl; Sevil, Hakkı Erhan; Özdemir, SerhanThe most important mechanism to occur in biological distributed sensory networks (DSNs) is called lateral inhibition, (LI). LI relies on one simple principle. Each sensor strives to suppress its neighbors in proportion to its own excitation. In this study, LI mechanism is exploited to localize the unknown position of a light source that illuminated the photosensitive sensory network containing high and low quality sensors. Each photosensitive sensor was then calibrated to accurately read the distance to the light source. A series of experiments were conducted employing both quality sensors. Low quality array was allowed to take advantage of LI, whereas the high quality one was not. Results showed that the lateral inhibition mechanism increased the sensitivity of inferior quality sensors, giving the ability to make the localization as sensitive as high quality sensors do. This suggests that the networks with multitude of sensors could be made cost-effective, were these sensory networks equipped with LI.Article Citation - WoS: 6Citation - Scopus: 7Classification of Manipulators of the Same Origin by Virtue of Compactness and Complexity(Elsevier Ltd., 2011) Gezgin, Erkin; Özdemir, SerhanThis work deals with a classification method that employs concepts such as complexity and compactness. The idea is to classify manipulators, or any other mechanism for that matter, of the same origin, based on the geometry of the joints, the tasks performed by the joints, the efficiency and the manufacturing cost to generate the specified efficiency. It is known that successive units on a single branch create individual uncertainties that affect the eventual quality of the performed operation [1]. An entropic expression quantifies this uncertainty in terms of the number of links and the unit effectiveness. The concepts of compactness and complexity have been formulated, and these concepts are explained through serial and parallel manipulators with varying parameters. Eventually, a cost function is created which is a function of complexity, uncertainty and the manufacturing cost. A worked example on M = 6 Stewart-Gough platform is given how this cost function could be taken advantage of when deciding an initial manipulator. A genetic algorithm is used for the optimization of the cost function, where the results are tabulated.Article Citation - WoS: 2Citation - Scopus: 2Trait-based heterogeneous populations plus (TbHP+) genetic algorithm(Elsevier Ltd., 2009) Tayfur, Gökmen; Sevil, Hakkı Erhan; Gezgin, Erkin; Özdemir, SerhanThis study developed a variant of genetic algorithm (GA) model called the trait-based heterogeneous populations plus (TbHP+). The developed TbHP+ model employs a memory concept in the form of immunity and instinct to provide the populations with a more efficient guidance. Also, it has an ability to vary the number of individuals during the search process, thus allowing an automatic determination of the size of the population based on the individual qualities such as character fitness and credit for immunity. The algorithm was tested against the classical GA model in convergence and minimum error performance. For this purpose, 5 different mathematical functions from the literature were employed. The selected functions have different topological characteristics, ranging from simple convex curves with 2 variables to complex trigonometric ones having several hilly shapes with more than 2 variables. The developed model and the classical GA model were applied to finding the global minima of the functions. The comparison of the results revealed that the developed TbHP+ model outperformed the classical GA in faster convergence and minimum errors, which may be explained by the adaptive nature of the new paradigm.Article Citation - WoS: 8Citation - Scopus: 8Measures of Uncertainty in Power Split Systems(Elsevier Ltd., 2007) Özdemir, SerhanThis paper discusses the overlooked uncertainty inherent in every transmission. The uncertainty aspect has been often, for the sake of clarity, ignored. Instead, mechanical transmissions have been characterized traditionally by their transmission efficacies. It is known that transmission localities are sources of power loss, depending on many factors, hence sources of uncertainty. Thus each transmission of power should not only be designated by a constant of efficiency but also by an expression of uncertainty, reflecting the probability of transmission. Furthermore, Shannon's and Renyi's expressions of entropy have been used to quantify this so-called transmission uncertainty. The entropy of a transmitting unit is given in these two forms and then compared. Practical formulations for flow optimization are given.Article Citation - WoS: 6Citation - Scopus: 6Intelligence Modeling of the Transient Asperity Temperatures in Meshing Spur Gears(Elsevier Ltd., 2005) Atan, Ebubekir; Özdemir, SerhanTemperature rise in the contact zone of meshing gears is a serious problem in gear design. The temperature rise on lubricated surfaces may result in the significant decrease on the material strength and lubricant viscosity which reduces the film thickness, causing solid to solid contact. The equations and the evaluations of the rise in temperature were given in [Proc. VDI Berichte 2 (1665) (2002) 615-626] and reiterated in this paper briefly. The data from [Proc. VDI Berichte 2 (1665) (2002) 615-626] are used to establish an artificial intelligence model where a multi layer feedforward neural network has been employed. The model accepts surface roughness, gear ratio, horsepower and the number of teeth as input variables, and outputs calculated pinion surface asperity temperatures. The aim of the present work is to provide a straightforward and simple way to compute the asperity temperature rise for a given set of variables, R-square value for the computed temperature values proves the method satisfactory.Article Citation - WoS: 121Citation - Scopus: 136Quantification of Caco3-Caso3·0.5h 2o-Caso4·2h2o Mixtures by Ftir Analysis and Its Ann Model(Elsevier Ltd., 2004) Böke, Hasan; Akkurt, Sedat; Özdemir, Serhan; Göktürk, E. Hale; Caner Saltık, Emine N.A new quantitative analysis method for mixtures of calcium carbonate (CaCO3), calcium sulphite hemihydrate (CaSO 3·1/2H2O) and gypsum (CaSO 4·2H2O) by FTIR spectroscopy is developed. The method involves the FTIR analysis of powder mixtures of several compositions on KBr disc specimens. Intensities of the resulting absorbance peaks for CaCO 3, CaSO3·1/2H2O and CaSO 4·2H2O at 1453, 980, 1146 cm-1 were used as input data for an artificial neural network (ANN) model, the output being the weight percent compositions of the mixtures. The training and testing data were randomly separated from the complete original data set. Testing of the model was done with successfully low-average error levels. The utility of the model is in the potential ability to use FTIR spectrum to predict the proportions of the three substances in unknown mixtures.Article Citation - WoS: 135Citation - Scopus: 157The Use of Ga-Anns in the Modelling of Compressive Strength of Cement Mortar(Elsevier Ltd., 2003) Akkurt, Sedat; Özdemir, Serhan; Tayfur, Gökmen; Akyol, BurakIn this paper, results of a project aimed at modelling the compressive strength of cement mortar under standard curing conditions are reported. Plant data were collected for 6 months for the chemical and physical properties of the cement that were used in model construction and testing. The training and testing data were separated from the complete original data set by the use of genetic algorithms (GAs). A GA-artificial neural network (ANN) model based on the training data of the cement strength was created. Testing of the model was also done within low average error levels (2.24%). The model was subjected to sensitivity analysis to predict the response of the system to different values of the factors affecting the strength. The plots obtained after sensitivity analysis indicated that increasing the amount of C3S, SO3 and surface area led to increased strength within the limits of the model. C2S decreased the strength whereas C3A decreased or increased the strength depending on the SO3 level. Because of the limited data range used for training, the prediction results were good only within the same range. The utility of the model is in the potential ability to control processing parameters to yield the desired strength levels and in providing information regarding the most favourable experimental conditions to obtain maximum compressive strength.Article Citation - WoS: 68Citation - Scopus: 86Fuzzy Logic Algorithm for Runoff-Induced Sediment Transport From Bare Soil Surfaces(Elsevier Ltd., 2003) Tayfur, Gökmen; Özdemir, Serhan; Singh, Vijay P.Utilizing the rainfall intensity, and slope data, a fuzzy logic algorithm was developed to estimate sediment loads from bare soil surfaces. Considering slope and rainfall as input variables, the variables were fuzzified into fuzzy subsets. The fuzzy subsets of the variables were considered to have triangular membership functions. The relations among rainfall intensity, slope, and sediment transport were represented by a set of fuzzy rules. The fuzzy rules relating input variables to the output variable of sediment discharge were laid out in the IF-THEN format. The commonly used weighted average method was employed for the defuzzification procedure. The sediment load predicted by the fuzzy model was in satisfactory agreement with the measured sediment load data. Predicting the mean sediment loads from experimental runs, the performance of the fuzzy model was compared with that of the artificial neural networks (ANNs) and the physics-based models. The results of showed revealed that the fuzzy model performed better under very high rainfall intensities over different slopes and over very steep slopes under different rainfall intensities. This is closely related to the selection of the shape and frequency of the fuzzy membership functions in the fuzzy model.