Bilgisayar Mühendisliği Bölümü Yayın Koleksiyonu
Permanent URI for this collectionhttps://hdl.handle.net/20.500.12416/253
Browse
9 results
Search Results
Article Citation - WoS: 23Citation - Scopus: 29Effective Social Productivity Measurements During Software Development: an Empirical Study(World Scientific Publ Co Pte Ltd, 2016) O'Connor, Rory V.; Clarke, Paul; Yilmaz, MuratMuch of contemporary scientific discussion regarding factors that influence software development productivity is undertaken in various domains where there is an insuflcient empirical basis for exploring socio-technical factors of productivity that are specific to a software development organization. The purpose of the study is to characterize the multidimensional nature of software development productivity and its social aspects as a set of latent constructs (i.e. variables that are not directly observed) for a medium-sized software company. To this end, we designed an exploratory in-depthfield study based on the hypothesized productivity constructs, which were modeled by a set of factors identified from literature reviews, and later refined by industrial focus groups. In order to demonstrate the applicability of our approach, we conducted confirmatory factor analysis with the data attained from a questionnaire with 216 participants. To investigate factors of influence further, we analyzed the impact of selected team-based variables over the latent constructs of productivity. Taken together, our findings confirm that such an approach can be used to explore the quantifiable influence of socio-technical factors that would affect productivity of a particular software development organization. Ultimately, the resulting model provides guidance to explore the comparative importance of a set of firm-specific factors that may help to improve the productivity of the organization.Article Citation - WoS: 2Citation - Scopus: 2Improvement of Dwt-Svd With Curve Fitting and Robust Regression: an Application To Astronomy Images(Kaunas Univ Technology, 2016) Elbasi, Ersin; Karadeniz, TalhaDWT-SVD is a frequency domain based eigenanalysis watermarking technique. In this work, we improve this method by exploring the relationship between the cover image's DWT singular values and those of the watermark. We show that, via the usage of curve fitting and robust regression, it is possible to achieve accurate results. We also demonstrate that the improved scheme is suitable for the watermarking of astronomy images. In addition to encoding and decoding examples, statistical results on stealth and robustness are deduced from the experiments so that the clear advance can be observed. Quality of the watermark is measured by testing against various attack types.Article Citation - WoS: 1Unbalanced Multiple Description Wavelet Coding for Scalable Video Transmission(Spie-soc Photo-optical instrumentation Engineers, 2012) Choupani, Roya; Wong, Stephan; Tolun, MehmetScalable video coding and multiple description coding are the two different adaptation schemes for video transmission over heterogeneous and best-effort networks such as the Internet. We propose a new method to encode video for unreliable networks with rate adaptation capability. Our proposed method groups three dimensional discrete wavelet transform coefficients in different descriptions and applies a modified embedded zero tree data for rate adaptation. The proposed method optimizes the bit-rates of the descriptions with respect to the channel bit rates and the maximum acceptable distortion. The experimental results in the presence of one description loss indicate that on average the videos at the rate of 1000 Kbit/s are reconstructed with Y-component of peak signal to noise ratio (Y-PSNR) value of 36.2 dB. The dynamic allocation of descriptions to the network channels is optimized for rate distortion minimization. The improvement in term of Y-PSNR achieved by rate distortion optimization has been between 0.7 and 5.3 dB in different bit rates. (c) 2012 SPIE and IS&T. [DOI: 10.1117/1.JEI.21.4.043006]Article Citation - WoS: 3Citation - Scopus: 4Automatic Coastline Detection Using Image Enhancement and Segmentation Algorithms(Hard, 2016) Caniberk, Mustafa; Maras, Hadi Hakan; Maras, Erdem EminCoastlines have hosted numerous civilizations since the earliest times of mankind due to the advantages they offer such as natural resources, transportation, arable areas, seafood, trade, and biodiversity. Coastal regions should be monitored vigilantly by planners and control mechanisms, and any changes in these regions should be detected with its human or natural origin, and future plans and possible interventions should be formed in these aspects to maintain ecological balance, sustainable development, and planned urbanization. Integrated coastal zone management (ICZM) provides an important tool to reach that goal. One of the important elements of ICZM is the detection of coastlines. While there are several methods to detect coastlines, remote sensing methods provide the fastest and the most efficient solutions. In this study, color infrared, grayscale, RGB, and fake infrared images were processed with the median filtering and segmentation software developed within the study, and coastal lines were detected by the edge detection method. The results show that segmentation with fake infrared images derived from RGB images give the best results.Article Citation - WoS: 2Citation - Scopus: 3Investigating the Relationship Between Sloc and Logical Database Measures To Improve the Early Estimation of Software Cost(World Scientific Publ Co Pte Ltd, 2019) Cagiltay, Nergiz Ercil; Tokdemir, GulProject planning is a critical activity in the software development life cycle. At the early stages of a project, the managers need to estimate required time, effort and cost to plan, track and then to deliver the project successfully. Many studies have attempted to provide methods for precise software cost estimation. The current software cost estimation methods are mainly based on software size estimation and functional system requirements. The main assumption of this study is that, as the primary source of complexity in today's software is the interaction between the database and the user, database measures may provide inputs allowing current software estimation methods to achieve more accurate results. Accordingly, this study attempts to gain insights from objective measures, collected through the logical database model of software systems, for better prediction of the software's effort and hence cost through software lines of code (SLOC) measure. For this purpose, more than 2.5 million lines of code developed by four different companies, for 79 different software packages with their related database design measures, are analyzed. The results of this study show that there is a close correlation between the software size and database design measure, namely, the number of tables which can be collected at the logical database design stage. By adapting this result, the current estimation models could be improved significantly.Conference Object Classification of Linked Data Sources Using Semantic Scoring(Ieice-inst Electronics information Communication Engineers, 2018) Dogdu, Erdogan; Kodaz, Halife; Yumusak, SemihLinked data sets are created using semantic Web technologies and they are usually big and the number of such datasets is growing. The query execution is therefore costly, and knowing the content of data in such datasets should help in targeted querying. Our aim in this paper is to classify linked data sets by their knowledge content. Earlier projects such as LOD Cloud, LODStats, and SPARQLES analyze linked data sources in terms of content, availability and infrastructure. In these projects, linked data sets are classified and tagged principally using VoID vocabulary and analyzed according to their content, availability and infrastructure. Although all linked data sources listed in these projects appear to be classified or tagged, there are a limited number of studies on automated tagging and classification of newly arriving linked data sets. Here, we focus on automated classification of linked data sets using semantic scoring methods. We have collected the SPARQL endpoints of 1,328 unique linked datasets from Datahub, LOD Cloud, LODStats, SPARQLES, and SpEnD projects. We have then queried textual descriptions of resources in these data sets using their rdfs: comment and rdfs: label property values. We analyzed these texts in a similar manner with document analysis techniques by assuming every SPARQL endpoint as a separate document. In this regard, we have used WordNet semantic relations library combined with an adapted term frequency-inverted document frequency (tfidf) analysis on the words and their semantic neighbours. In WordNet database, we have extracted information about comment/label objects in linked data sources by using hypernym, hyponym, homonym, meronym, region, topic and usage semantic relations. We obtained some significant results on hypernym and topic semantic relations; we can find words that identify data sets and this can be used in automatic classification and tagging of linked data sources. By using these words, we experimented different classifiers with different scoring methods, which results in better classification accuracy results.Article Covariance Features for Trajectory Analysis(Kaunas Univ Technology, 2018) Karadeniz, Talha; Maraş, Hadi HakanIn this work, it is demonstrated that covariance estimator methods can be used for trajectory classification. It is shown that, features obtained via shrunk covariance estimation are suitable for describing trajectories. Compared to Dynamic Time Warping, application of explained technique is faster and yields more accurate results. An improvement of Dynamic Time Warping based on counting statistical comparison of base distance measures is also achieved. Results on Australian Sign Language and Character Trajectories datasets are reported. Experiment realizations imply feasibility through covariance attributes on time series.Article Citation - Scopus: 3Experimental Study on the Sensitivity of Autocalibration To Projective Camera Model Parameters(Spie-soc Photo-optical instrumentation Engineers, 2006) Atalay, Volkan; Hassanpour, RezaExisting methods of 3-D object modeling and recovering 3-D data from uncalibrated 2-D images are subject to errors introduced by assumptions about camera parameters and mismatches in finding point pairs in the images. In this study, we experimentally evaluate the effect of each of these assumptions together with the inaccuracy in the measurements in the images. Sensitivity of reconstruction errors to inaccuracies in the estimation of camera parameters and mismatches due to noise in input data is measured using a linear and two nonlinear autocalibration methods for a projective camera. Our experimental results show that some assumptions such as a vanishing skew can be safely made; however, other parameters such as principal point location are quite sensitive to wrong assumptions. (c) 2006 Society of Photo-Optical Instrumentation Engineers.Article Citation - WoS: 1Citation - Scopus: 1Relative Consistency of Projective Reconstructions Obtained From the Same Image Pair(World Scientific Publ Co Pte Ltd, 2006) Atalay, M. Volkan; Hassanpour, Reza; Otlu, Burcak; Volkan Atalay, M.This study obtains projective reconstructions of an object or a scene from its image pair and measures relative consistency of these projective reconstructions. 3D points are estimated from an image pair using projective and epipolar geometry. Two measures are presented for verification of projective reconstructions with each other. These measures are based on the equality of ratios between the x-, y- and z-coordinates of 3D reconstructed points which are obtained from the same corresponding points. This information is used for measuring the relative consistency of projective reconstructions obtained from the same image pair.