Browsing by Subject "Curve fitting"
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Item Open Access Analyzing impact of experience curve on ROI in the software product line adoption process(Elsevier BV, 2015) Tüzün, E.; Tekinerdogan, B.Context Experience curve is a well-known concept in management and education science, which explains the phenomenon of increased worker efficiency with repetitive production of a good or service. Objective We aim to analyze the impact of the experience curve effect on the Return on Investment (ROI) in the software product line engineering (SPLE) process. Method We first present the results of a systematic literature review (SLR) to explicitly depict the studies that have considered the impact of experience curve effect on software development in general. Subsequently, based on the results of the SLR, the experience curve effect models in the literature, and the SPLE cost models, we define an approach for extending the cost models with the experience curve effect. Finally, we discuss the application of the refined cost models in a real industrial context. Results The SLR resulted in 15 primary studies which confirm the impact of experience curve effect on software development in general but the experience curve effect in the adoption of SPLE got less attention. The analytical discussion of the cost models and the application of the refined SPLE cost models in the industrial context showed a clear impact of the experience curve effect on the time-to-market, cost of development and ROI in the SPLE adoption process. Conclusions The proposed analysis with the newly defined cost models for SPLE adoption provides a more precise analysis tool for the management, and as such helps to support a better decision making.Item Open Access Combined filtering and key-frame reduction of motion capture data with application to 3DTV(WSCG, 2006-01-02) Önder, Onur; Erdem, Ç.; Erdem, T.; Güdükbay, Uğur; Özgüç, BülentA new method for combined filtering and key-frame reduction of motion capture data is proposed. Filtering of motion capture data is necessary to eliminate any jitter introduced by a motion capture system. Key-frame reduction, on the other hand, allows animators to easily edit motion data by representing animation curves with a significantly smaller number of key frames. The proposed technique achieves key frame reduction and jitter removal simultaneously by fitting a Hermite curve to motion capture data using dynamic programming. Copyright © UNION Agency - Science Press.Item Open Access Efficient evaluation of spatial-domain MoM matrix entries in the analysis of planar stratified geometries(IEEE, 2000) Kinayman, N.; Aksun, M. IAn efficient hybrid method for evaluation of spatial-domain method-of-moments (MoM) matrix entries is presented in this paper. It has already been demonstrated that the introduction of the closed-form Green's functions into the MoM formulation results in a significant computational improvement in filling up MoM matrices and, consequently, in the analysis of planar geometries. To achieve further improvement in the computational efficiency of the MoM matrix entries, a hybrid method is proposed in this paper and, through some examples, it is demonstrated that it provides significant acceleration in filling up MoM matrices while preserving the accuracy of the results.Item Open Access Employing active contours and artificial neural networks in representing ultrasonic range data(IEEE, 2008-08) Altun, Kerem; Barshan, BillurActive snake contours and Kohonen's self-organizing feature maps (SOM) are considered for efficient representation and evaluation of the maps of an environment obtained with different ultrasonic arc map (UAM) processing techniques. The mapping results are compared with a reference map acquired with a very accurate laser system. Both approaches are convenient ways of representing and comparing the map points obtained with different techniques among themselves, as well as with an absolute reference. Snake curve fitting results in more accurate maps than SOM since it is more robust to outliers. The two methods are sufficiently general that they can be applied to discrete point maps acquired with other mapping techniques and other sensing modalities as well. copyright by EURASIP.Item Open Access Enhancements to linear least squares localization through reference selection and ML estimation(IEEE, 2008-03-04) Güvenç, İsmail; Gezici, Sinan; Watanabe F.; Inamura, H.Linear least squares (LLS) estimation is a low complexity but sub-optimum method for estimating the location of a mobile terminal (MT) from some distance measurements. It requires selecting one of the fixed terminals (FTs) as a reference FT for obtaining a linear set of expressions. However, selection of the reference FT is commonly performed arbitrarily in the literature. In this paper, a method for selection of the reference FT is proposed, which improves the location accuracy compared to a fixed selection of the reference FT. Moreover, a covariancematrix based LLS estimator is proposed in line of sight (LOS) and non-LOS (NLOS) environments which further improves accuracy since the correlations between the observations are exploited. Simulation results prove the effectiveness of the proposed techniques. © 2008 IEEE.Item Open Access Estimation of object location and radius of curvature using ultrasonic sonar(Elsevier, 2001-07) Sekmen, A. Ş.; Barshan, B.Acoustic sensors are very popular in time-of-flight (TOF) ranging systems since they are inexpensive and convenient to use. One of the major limitations of these sensors is their low angular resolution which makes object localization difficult. In this paper, an adaptive multisensor configuration consisting of three transmitter/receiver ultrasonic transducers is introduced to compensate for the low angular resolution of sonar sensors and improve the localization accuracy. With this configuration, the radius of curvature and location of cylindrical objects are estimated. Two methods of TOF estimation are considered: thresholding and curve-fitting. The bias-variance combinations of these estimators are compared. Theory and simulations are verified by experimental data from a real sonar system. Extended Kalman filtering is used to smooth the data. It is shown that curve-fitting method, compared to thresholding method, provides about 30% improvement in the absence of noise and 50% improvement in the presence of noise. Moreover. the adaptive configuration improves the estimation accuracy by 35-40%. (C) 2001 Elsevier Science Ltd. All rights reserved.Item Open Access Fast processing techniques for accurate ultrasonic range measurements(Institute of Physics Publishing, 2000) Barshan, B.Four methods of range measurement for airborne ultrasonic systems - namely simple thresholding, curve-fitting, sliding-window, and correlation detection - are compared on the basis of bias error, standard deviation, total error, robustness to noise, and the difficulty/complexity of implementation. Whereas correlation detection is theoretically optimal, the other three methods can offer acceptable performance at much lower cost. Performances of all methods have been investigated as a function of target range, azimuth, and signal-to-noise ratio. Curve fitting, sliding window, and thresholding follow correlation detection in the order of decreasing complexity. Apart from correlation detection, minimum bias and total error is most consistently obtained with the curve-fitting method. On the other hand, the sliding-window method is always better than the thresholding and curve-fitting methods in terms of minimizing the standard deviation. The experimental results are in close agreement with the corresponding simulation results. Overall, the three simple and fast processing methods provide a variety of attractive compromises between measurement accuracy and system complexity. Although this paper concentrates on ultrasonic range measurement in air, the techniques described may also find application in underwater acoustics.Item Open Access Human activity recognition using tag-based localization(IEEE, 2012-04) Yurtman, Aras; Barshan, BarshanThis paper provides a comparative study on the different techniques of classifying human activities using a tag-based radio-frequency (RF) localization system. Non-uniformly-sampled data containing position measurements of the tags on the body is first converted to a uniformly-sampled one using different curve-fitting algorithms. Then, the data is partitioned into segments. Finally, various classification techniques are applied to classify human activities. Curve-fitting, segmentation, and classification methods are compared using different cross-validation techniques and the combination resulting in the best performance is presented. The results indicate that the system demonstrates acceptable performance despite the fact that tag-based RF localization is not very accurate.Item Open Access Human activity recognition using tag-based radio frequency localization(Taylor and Francis Inc., 2016) Yurtman, A.; Barshan, B.This article provides a comparative study on the different techniques of classifying human activities using tag-based radio-frequency (RF) localization. A publicly available dataset is used where the position data of multiple RF tags worn on different parts of the human body are acquired asynchronously and nonuniformly. In this study, curves fitted to the data are resampled uniformly and then segmented. We investigate the effect on system accuracy of varying the relevant system parameters. We compare various curve-fitting, segmentation, and classification techniques and present the combination resulting in the best performance. The classifiers are validated using 5-fold and subject-based leave-one-out cross validation, and for the complete classification problem with 11 classes, the proposed system demonstrates an average classification error of 8.67% and 21.30%, respectively. When the number of classes is reduced to five by omitting the transition classes, these errors become 1.12% and 6.52%, respectively. The results indicate that the system demonstrates acceptable classification performance despite that tag-based RF localization does not provide very accurate position measurements.Item Open Access A hybrid approach for line segmentation in handwritten documents(2012) Adıgüzel, Hande; Şahin, Emre; Duygulu, PınarThis paper presents an approach for text line segmentation which combines connected component based and projection based information to take advantage of aspects of both methods. The proposed system finds baselines of each connected component. Lines are detected by grouping baselines of connected components belonging to each line by projection information. Components are assigned to lines according to different distance metrics with respect to their size. This study is one of the rare studies that apply line segmentation to Ottoman documents. Further, it proposes a new method, Fourier curve fitting, to detect the peaks in a projection profile. The algorithm is demonstrated on different printed and handwritten Ottoman datasets. Results show that the method manages to segment lines both from printed and handwritten documents under different writing conditions at least with 92% accuracy.Item Open Access Keyframe reduction techniques for motion capture data(IEEE, 2008-05) Önder, Onur; Güdükbay, Uğur; Özgüç, Bülent; Erdem, T.; Erdem, Ç.; Özkan, M.Two methods for keyframe reduction of motion capture data are presented. Keyframe reduction of motion capture data enables animators to easily edit motion data with smaller number of keyframes. One of the approaches achieves keyframe reduction and noise removal simultaneously by fitting a curve to the motion information using dynamic programming. The other approach uses curve simplification algorithms on the motion capture data until a predefined threshold of number of keyframes is reached. Although the error rate varies with different motions, the results show that curve fitting with dynamic programming performs as good as curve simplification methods. ©2008 IEEE.Item Open Access A large-signal behavioural modeling approach of GaN HEMTs for power amplifier design(Institute of Electrical and Electronics Engineers Inc., 2021-01-10) Yegin, Mustafa Oğuz; Gurdal, Armagan; Ozipek, Ulas; Özbay, EkmelA new method to simulate the large-signal behaviour of GaN HEMTs is presented along with the two 15W X-band MMIC Class AB power amplifier (PA) designs using the same methodology. Proposed modeling approach is based on curve-fitting transistor performance parameters in the load impedance plane, while transistor’s behaviour in the source impedance space is calculated using a virtual source-pull technique. Good agreement with the results of two fabricated GaN PA MMICs demonstrate the accuracy of the method in simulating Pout , Gt and PAE of the amplifiers at any given compression level. This approach is distinguished from conventional modeling methods with its minimal measurement requirements, ease of model development, and generic nature while accurately predicting the large-signal response, thus is suitable to use for PA design, under the lack of a more comprehensive transistor model.Item Open Access A new effective side length expression obtained using a modified tabu search algorithm for the resonant frequency of a triangular microstrip antenna(John Wiley & Sons, 1998) Karaboğa, D.; Güney, K.; Kaplan, A.; Akdağli, A.A new, very simple curve-fitting expression for the effective side length is presented for the resonant frequency of triangular microstrip antennas. It is obtained using a modified tabu search algorithm, and is useful for the computer-aided design (CAD) of microstrip antennas. The theoretical resonant frequency results obtained using this new effective side length expression are in very good agreement with the experimental results available in the literature.Item Open Access On reduced order modeling of flexible structures from frequency response data(IEEE, 2014) Demir, Okan; Özbay, HitayIn order to identify the dominant flexible modes of a flexible structure with an input/output delay, a numerical method is proposed. The method uses a frequency domain approach (frequency response data) to estimate the resonating frequencies and damping coefficients of the flexible modes, as well as the amount of the time delay. A sequential NLLS (Non-Linear Least Squares) curve fitting procedure is adopted. It is illustrated that such a Newtonian optimization method has the capability of finding the parameters of a reduced order transfer function by minimizing a cost function involving nonlinearities such as exponential and fractional terms.