Bilgisayar Mühendisliği Bölümü Yayın Koleksiyonu

Permanent URI for this collectionhttps://hdl.handle.net/20.500.12416/253

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An Experimental Study on Decomposition: Process First or Structure First?
(2019) Çetinkaya, Anıl; Suloğlu, Selma; Kaya, M. Çağrı; Karamanlıoğlu, Alper; Tokdemir, Gül; Doğru, Ali H.
This article explores the answer to the question of considering the process or the structure dimensions earlier, in software development where decomposition is a preferred technique for top-down model construction. In this research, an experimental study was conducted to observe which software modeling practice is more convenient: process or structural modeling, for the beginning. The study was conducted in different courses that include software modeling where students work within groups to model a system with predefined requirements. The students used Business Process Modeling Notation and Component-Oriented Software Engineering Modeling Language modeling tools. Observations based on the results are analyzed and discussed. The results seem to prioritize the process dimension.
Analysing Iraqi Railways Network by Applying Specific Criteria Using the Gis Techniques
(Coll Science Women, Univ Baghdad, 2019) Naji, Hayder Fans; Maras, H. Hakan
The railways network is one of the huge infrastructure projects. Therefore, dealing with these projects such as analyzing and developing should be done using appropriate tools, i.e. GIS tools. Because, traditional methods will consume resources, time, money and the results maybe not accurate. In this research, the train stations in all of Iraq's provinces were studied and analyzed using network analysis, which is one of the most powerful techniques within GIS. A free trial copy of ArcGIS (R) 10.2 software was used in this research in order to achieve the aim of this study. The analysis of current train stations has been done depending on the road network, because people used roads to reach those train stations. The data layers for this study were collected and prepared to meet the requirements of network analyses within GIS. In this study, the current train stations in Iraq were analyzed and studied depending on accessibility value for those stations. Also, to know the numbers of people who can reach those stations within a walking time of 20 minutes. So, this study aims to analyze the current train stations according to multiple criteria by using network analysis in order to find the serviced areas around those stations. Results will be presented as digital maps layers with their attribute tables that show the beneficiaries from those train stations and serviced areas around those stations depending on specific criteria, with a view to determine the size of this problem and to support the decision makers in case of locating new train stations within the best locations for it.
Citation - Scopus: 4
Analysis of B2c Mobile Application Characteristics and Quality Factors Based on Iso 25010 Quality Model
(Springer Verlag, 2014) Tokdemir, G.; Cagiltay, N.E.; Erturan, Y.N.; Yildiz, E.; Bilgen, S.
The number of mobile applications in mobile market has rapidly increased as new technology and new devices are emerging at remarkable speed which shows mobile applications have an important role in every field of our life. Among those, even some of the mobile applications have a long time life as end-users use those effectively, some of them fail to do so that prevents the companies to reach from their aim. The main reason of that problem results from the quality of the mobile applications. Although there are some methods and metrics to analyze the quality of mobile applications, they have lack of criteria since they are mostly based on ISO 9126 quality model factors which are invalid anymore. This study aims to analyze both mobile commerce applications' characteristics and quality factors and sub-factors based on ISO 25010 product quality model. Accordingly a quality model is proposed by analysis performed by a group of experts from the mobile software development area. The results of this study aims to help developing more qualified and effective mobile applications from developer perspective. © 2014 Springer International Publishing.
Citation - Scopus: 4
Applications and Design for a Cloud of Virtual Sensors
(Institute of Advanced Engineering and Science, 2016) Hussein, A.J.; Riadh, A.; Alsultan, M.; Tareq, A.A.-R.
The use of sensors in our daily lives is a growing demand with the large number of electronic devices around us. These sensors will be included in our daily life requirements soon and they will affect our lives in both positive and negative ways. In this paper, we discuss the manner, applications and design issues for a cloud of virtual sensors, and we introduce a distributed system design to deal with physical sensors that reside in diverse locations and operate in different environments. This design operates in a cloud computing vision and can make virtual sensors in upper of physical one available from anywhere using ICT structure. Then, we negotiated the future of this technology, i.e., the Internet of Things (IoT). Additionally, we go over the strengths and weaknesses of using this technology. Our test lab shows high performance and good total cost of ownership and effective response time. © 2016 Institute of Advanced Engineering and Science. All rights reserved.
Citation - WoS: 3
Citation - Scopus: 4
Automatic Coastline Detection Using Image Enhancement and Segmentation Algorithms
(Hard, 2016) Caniberk, Mustafa; Maras, Hadi Hakan; Maras, Erdem Emin
Coastlines 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.
Citation - Scopus: 2
Automatic Detection of Spina Bifida Occulta With Deep Learning Methods From Plain Pelvic Radiographs
(Springer Science and Business Media Deutschland GmbH, 2023) Üreten, K.; Maraş, Y.; Maraş, H.H.; Gök, K.; Atalar, E.; Çayhan, V.; Duran, S.
Purpose: Spina bifida occulta (SBO), which is the most common congenital spinal deformity, is often seen in the lower lumbar spine and sacrum. In this study, it is aimed to develop a computer-aided diagnosis method that will help clinicians in the diagnosis of spina bifida occulta from plain pelvic radiographs with deep learning methods and transfer learning method. Materials and methods: The You Only Look Once (YOLO) algorithm was used for object detection, and classification was made by applying transfer learning with a pre-trained VGG-19, ResNet-101, MobileNetV2, and GoogLeNet networks. Our dataset consisted of 206 normal lumbosacral radiographs and 160 SBO lumbosacral radiographs. The performance of the models was evaluated by metrics such as accuracy, sensitivity, specificity, precision, F1 score, and area under the ROC curve (AUC) results. Results: In the detection of SBO, 85.5%, 80.8%, 89.7%, 87.5%, 84%, and 0.92 accuracy, sensitivity, specificity, precision, F1 score, and AUC results were obtained with the pre-trained VGG-19 model, respectively. The pre-trained VGG-19 model performed better than the others. Conclusion: Successful results were obtained in this study performed to the diagnosis of SBO with deep learning methods. A model that will assist physicians in the diagnosis of SBO can be developed with new studies to be conducted with a large number of spinal radiographs. © 2023, The Author(s), under exclusive licence to The Brazilian Society of Biomedical Engineering.
Citation - WoS: 17
Citation - Scopus: 18
Boron Doped Graphene Nanostructures
(Wiley-v C H verlag Gmbh, 2008) Ozdogan, Cem; Kunstmann, Jens; Fehske, Holger; Quandt, Alexander
We present results from an ab initio study of metallized semiconducting graphene nanostructures. Our model system consists of an alternating chain of quasi-planar B-7 clusters embedded into a semiconducting arm-chair nanoribbon. We observe the appearance of overlapping bands around the Fermi-level, with crystal momenta pointing into the direction of these boron chains. This observation could be a vantage point for the development of graphene nanodevices and integrated nanocircuits, based on existing technologies. (C) 2008 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim
Classification of Linked Data Sources Using Semantic Scoring
(Ieice-inst Electronics information Communication Engineers, 2018) Dogdu, Erdogan; Kodaz, Halife; Yumusak, Semih
Linked 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.
Covariance Features for Trajectory Analysis
(Kaunas Univ Technology, 2018) Karadeniz, Talha; Maraş, Hadi Hakan
In 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.
Citation - Scopus: 6
Design Effort Estimation Using Complexity Metrics
(2004) Salman, N.; Salman, Nael; Doǧru, A.; Bilgisayar Mühendisliği
Component-oriented software development is a new trend and is becoming very popular these days. In addition to requiring a different development approach, the new orientation also requires a different metrics approach. A set of metrics for Component Oriented Software Engineering was first introduced in previous research. These metrics set were used to measure the quality of component-oriented software designs. The impact of these metrics on design effort is investigated in this paper. A statistical model is developed based on nine projects that carried out component-oriented software development. Design effort is expressed as a junction of a subset of the complexity metrics.
Citation - WoS: 10
Citation - Scopus: 12
The Diagnosis of Developmental Dysplasia of the Hip From Hip Ultrasonography Images With Deep Learning Methods
(Lippincott Williams & Wilkins, 2023) Ureten, Kemal; Tokdemir, Gul; Tolunay, Tolga; Ciceklidag, Murat; Atik, Osman Sahap; Atalar, Hakan
Background:Hip ultrasonography is very important in the early diagnosis of developmental dysplasia of the hip. The application of deep learning-based medical image analysis to computer-aided diagnosis has the potential to provide decision-making support to clinicians and improve the accuracy and efficiency of various diagnostic and treatment processes. This has encouraged new research and development efforts in computer-aided diagnosis. The aim of this study was to evaluate hip sonograms using computer-assisted deep-learning methods. Methods:The study included 376 sonograms evaluated as normal according to the Graf method, 541 images with dysplasia and 365 images with incorrect probe position. To classify the developmental hip dysplasia ultrasound images, transfer learning was applied with pretrained VGG-16, ResNet-101, MobileNetV2 and GoogLeNet networks. The performances of the networks were evaluated with the performance parameters of accuracy, sensitivity, specificity, precision, F1 score, and AUC (area under the ROC curve). Results:The accuracy, sensitivity, specificity, precision, F1 score, and AUC results obtained by testing the VGG-16, ResNet-101, MobileNetV2, and GoogLeNet models showed performance >80%. With the pretrained VGG-19 model, 93%, 93.5%, 96.7%, 92.3%, 92.6%, and 0.99 accuracy, sensitivity, specificity, precision, F1 score, and AUC results were obtained, respectively. Conclusion:In this study, in addition to the ultrasonography images of dysplastic and healthy hips, images were also included of probe malpositioning, and these images were able to be successfully evaluated with deep learning methods. On the sonograms, which provided criteria appropriate for evaluation, successful differentiation could be made of healthy hips and dysplastic hips.
Citation - WoS: 23
Citation - Scopus: 29
Effective Social Productivity Measurements During Software Development: an Empirical Study
(World Scientific Publ Co Pte Ltd, 2016) O'Connor, Rory V.; Clarke, Paul; Yilmaz, Murat
Much 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.
Citation - WoS: 8
Citation - Scopus: 9
Effects of Hydrogen Hosting on Cage Structures of Boron Clusters: Density Functional Study of Bmhn (m=5-10 and N ≤ M) Complexes
(Iop Publishing Ltd, 2008) Ozdogan, C.; Guvenc, Z. B.; Boyukata, M.
The structural stability of hydrogen bonded boron microclusters has been studied by using the density functional theory. Effects of the increasing number of hydrogen atoms on the cage geometries of B-5-B-10 clusters, and the distortion of the cage configurations of the boranes are assessed. The possible stable structures of BmHn(m = 5-10 and n <= m) boron hydrides, their binding energies, HOMO-LUMO energy gaps and the total atomic charges of the B-m in the complexes are determined. For the series of B5Hn, B7Hn, and B9Hn major structural changes are observed.
Citation - WoS: 1
Citation - Scopus: 2
Evaluation of Semantic Relatedness Measures for Turkish Language
(Springer international Publishing Ag, 2018) Sopaoglu, Ugur; Ercan, Gonenc
The problem of quantifying semantic relatedness level of two words is a fundamental sub-task for many natural language processing systems. While there is a large body of research on measuring semantic relatedness in the English language, the literature lacks detailed analysis for these methods in agglutinative languages. In this research, two new evaluation resources for the Turkish language are constructed. An extensive set of experiments involving multiple tasks: word association, semantic categorization, and automatic WordNet relationship discovery are performed to evaluate different semantic relatedness measures in the Turkish language. As Turkish is an agglutinative language, the morphological processing component is important for distributional similarity algorithms. For languages with rich morphological variations and productivity, methods ranging from simple stemming strategies to morphological disambiguation exists. In our experiments, different morphological processing methods for the Turkish language are investigated.
Citation - WoS: 2
Citation - Scopus: 1
An Experimental Study on Decomposition: Process First or Structure First
(Springer international Publishing Ag, 2019) Suloglu, Selma; Kaya, M. Cagri; Karamanlioglu, Alper; Tokdemir, Gul; Dogru, Ali H.; Cetinkaya, Anil
This article explores the answer to the question of considering the process or the structure dimensions earlier, in software development where decomposition is a preferred technique for top-down model construction. In this research, an experimental study was conducted to observe which software modeling practice is more convenient: process or structural modeling, for the beginning. The study was conducted in different courses that include software modeling where students work within groups to model a system with predefined requirements. The students used Business Process Modeling Notation and Component-Oriented Software Engineering Modeling Language modeling tools. Observations based on the results are analyzed and discussed. The results seem to prioritize the process dimension.
Citation - Scopus: 3
Experimental Study on the Sensitivity of Autocalibration To Projective Camera Model Parameters
(Spie-soc Photo-optical instrumentation Engineers, 2006) Atalay, Volkan; Hassanpour, Reza
Existing 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.
Citation - WoS: 7
Citation - Scopus: 8
Fragmentation of Water Clusters: Molecular-Dynamics Simulation Study
(Springer-verlag, 2001) Erkoç, S; Kökten, H; Güvenç, Z
The fragmentation of water clusters, [(H2O)(n): n = 2-8], have been investigated by using molecular-dynamics simulation method. In the simulations a polarizable-dissociable potential energy function for water has been used. Particular attention has been paid to investigate the effect of structural properties and cluster size of the fragmentation.
Citation - WoS: 43
Citation - Scopus: 53
Gamification as a Disruptive Factor in Software Process Improvement Initiatives
(Graz Univ Technolgoy, inst information Systems Computer Media-iicm, 2014) Herranz, Eduardo; Yılmaz, Murat; Colomo-Palacios, Ricardo; de Amescua Seco, Antonio; Yilmaz, Murat; Yazılım Mühendisliği
For any Software Process Improvement (SPI) initiative to succeed human factors, in particular, motivation and commitment of the people involved should be kept in mind. In fact, Organizational Change Management (OCM) has been identified as an essential knowledge area for any SPI initiative. However, enough attention is still not given to the human factors and therefore, the high degree of failures in the SPI initiatives is directly linked to a lack of commitment and motivation. Gamification discipline allows us to define mechanisms that drive people's motivation and commitment towards the development of tasks in order to encourage and accelerate the acceptance of an SPI initiative. In this paper, a gamification framework oriented to both organization needs and software practitioners groups involved in an SPI initiative is defined. This framework tries to take advantage of the transverse nature of gamification in order to apply its Critical Success Factors (CSF) to the organizational change management of an SPI. Gamification framework guidelines have been validated by some qualitative methods. Results show some limitations that threaten the reliability of this validation. These require further empirical validation of a software organization.
Citation - WoS: 49
Citation - Scopus: 49
Global Minima of Aln, Aun and Ptn, N≤80, Clusters Described by the Voter-Chen Version of Embedded-Atom Potentials
(Iop Publishing Ltd, 2005) Sebetci, A; Güvenç, ZB
We report the global minima for aluminium, gold and platinum metal clusters modelled by the Voter-Chen version of the embedded-atom model potential containing up to 80 atoms using the basin-hopping Monte Carlo minimization approach. The results show that the global minima of the Al, Au and Pt clusters have structures based on either octahedral, decahedral, icosahedral or a mixture of decahedral and icosahedral packing. The 54-atom icosahedron without a central atom is found to be more stable than the 55-atom complete icosahedron for all of the elements considered in this work. Most of the Al global minima are identified as face-centred cubic structures and many of the An global minima are found to be low symmetric structures, both of which are in agreement with the previous theoretical and experimental Studies. Although many of the Pt global minima are identical with the global minima of the corresponding Au clusters, the most stable sizes of the Pt clusters correspond to the same sizes of the Al clusters.
Guis With Haptic Interfaces
(Springer Verlag, 2015) Ozcelik, E.; Tuner, E.; Sahin, H.; Tokdemir, G.; Arda Aydin, M.; Cagiltay, N.E.
While there are many studies regarding utilization of Haptic feedback to enhance desktop GUIs and utilizing Haptic devices as additional interfaces to improve performance in current interaction techniques, there are not many studies that uses Haptic device as a primary input device. In this study, we present an experimentation conducted with 30 students, comparing performance of a Haptic device with mouse to use a GUI elements commonly used with mouse gestures. This study is inspired by a system that utilizes both mouse and a Haptic device, thus also taking task switching into consideration. We conclude that it is possible to achieve an acceptable performance with a Haptic device in a desktop-like GUI but further study and experimentation is necessary. © Springer International Publishing Switzerland 2015.

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