Computer Engineering / Bilgisayar Mühendisliği
Permanent URI for this collectionhttps://hdl.handle.net/11147/10
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Conference Object Citation - WoS: 2Word2vec Kullanarak Eş Anlamlılık Temelinde Anahtar Kelime Çıkarımı(IEEE, 2019) Oğul, İskender Ülgen; Özcan, Caner; Hakdağlı, ÖzlemNowadays, the data revealed by the online individuals are increasing exponentially. The raw information that increasing data holds, transformed into meaningful outputs using machine learning and deep learning methods. Generally, supervised learning methods are used for information extraction and classification. Supervised learning is based on the training set that classification algorithms are trained. In the proposed approach, keyword extraction solution is proposed to classify text data more convenient. The developed solution is based on the Word2Vec algorithm, which works by taking into consideration the semantic meaning of the words unlike general approaches that based on word frequency. A new approach, word embedding algorithm named Word2Vec, works by calculating the word weights, semantic relationship, and the final weights of vectors. The obtained keywords are trained with Name Bayes and Decision Trees methods and the performance of the proposed method is shown by classification example.Conference Object Citation - WoS: 2Citation - Scopus: 3Impact of Variations in Synthetic Training Data on Fingerprint Classification(IEEE, 2019) İrtem, Pelin; İrtem, Emre; Erdoğmuş, NesliCreating and labeling data can be extremely time consuming and labor intensive. For this reason, lack of sufficiently large datasets for training deep structures is often noted as a major obstacle and instead, synthetic data generation is proposed. With their high acquisition and labeling complexity, this also applies to fingerprints. In the literature, a number of synthetic fingerprint generation systems have been proposed, but mostly for algorithm evaluation purposes. In this paper, we aim to analyze the use of synthetic fingerprint data with different levels of degradation for training deep neural networks. Fingerprint classification problem is selected as a case-study and the experiments are conducted on a public domain database, NIST SD4. A positive correlation between the synthetic data variation and the classification rate is observed while achieving state-of-the-art results.Conference Object Duyarga Ağları için Bir Γ Eşuyumcusu Tasarım ve Uygulaması(IEEE, 2008) Özsoyeller, Deniz; Erciyeş, Kayhan; Dağdeviren, OrhanImplementation of synchronous algorithms in distributed systems in general is less troublesome than the implementation of asynchronous algorithms. Synchronizers provide synchronous execution of an asynchronous algorithm in distributed systems. In this study, we propose a gamma synchronizer for Wireless Sensor Networks (WSNs). This synchronizer consists of a and beta synchronizers. In our work, the WSN is first divided into clusters and then these clusters are connected using a ring protocol. Synchronization is provided using the beta synchronizer in the cluster and a synchronizer among the clusters. We describe the clustering algorithm and the ring formation algorithm for the WSNs and give the results obtained so far.Conference Object Citation - Scopus: 15Gezgin Tasarsız Ağlar için Taşırma Tabanlı Yönlendirme Yordamı(IEEE, 2008) Çokuslu, Deniz; Erciyeş, KayhanMobile Ad Hoc Networks (MANETs) are videly in use in rescue, military operations, scientific and business areas. Many studies are addressed in MANETs because of their need to long lasting liveness, fault tolerance, dynamic addressing, collusion prevention, mobility management and security. Especially, self clustering, backbone construction and routing are the most interesting academic and industrial research areas in MANETs. A wide range of studies addressed the routing problem in MANETs. Many previous studies address the clustering and routing problems as seperate subjects. However, rowing approaches which are specific to the clustering methodologies may have many advantages in terms of efficiency and availability. In this study, a flooding based routing algorithm is proposed. First, a detailed description of the algorithm is explained, then the analysis and test results using the ns2 simulator are given which show that the designed algorithm is scalable and has favorable performance.Conference Object Zamanda ortalaması alınmış ikili önplan imgeleri kullanarak taşıt sınıflandırması(IEEE, 2015) Karaimer, Hakkı Can; Baştanlar, YalınWe describe a shape-based method for classification of vehicles from omnidirectional videos. Different from similar approaches, the binary images of vehicles obtained by background subtraction in a sequence of frames are averaged over time. We show with experiments that using the average shape of the object results in a more accurate classification than using a single frame. The vehicle types we classify are motorcycle, car and van. We created an omnidirectional video dataset and repeated experiments with shuffled train-test sets to ensure randomization.Conference Object Citation - WoS: 3Citation - Scopus: 11Towards Modeling Patterns for Embedded Software Industry: Feedback From the Field(IEEE, 2018) Akdur, Deniz; Demirörs, Onur; Say, BilgeThe analysis, design, implementation and testing of software for embedded systems are not trivial. Software modeling is a commonly used approach in the embedded software industry to manage complexity of these phases. The modeling approaches vary since the characteristics of modeling such as its purpose, the medium type used, the lifecycle phase used, differ among systems and industrial sectors. Our previous research identified and defined the modeling approach patterns in embedded software development projects based on quantitative data. In this paper, to validate and improve the pre-investigated pattern set, we present a series of semi-structured interviews over eight months with 53 embedded software professionals across a variety of target industrial sectors and roles. With the help of these interviews, the different modeling approach patterns in embedded software development were better understood and the hidden patterns not evident in the previous study were identified along with a documentation of personalized modeling experiences.Conference Object Syllogistic Knowledge Bases With Description Logic Reasoners(IEEE, 2018) Çine, ErsinReasoning is a core topic both for natural intelligence and for artificial intelligence. While syllogistic logics (SLs) are often studied by cognitive scientists for understanding human reasoning, description logics (DLs) are usually studied by computer scientists for performing automated reasoning. Although the studies on both of these logics are extensive, their literatures are interestingly isolated from each other. Firstly, we formally define a practical family of SLs with different levels of expressivity, including a logic which has recently been introduced for automated reasoning. Then, we reveal their theoretical properties either by defining direct algorithms for deductive reasoning or by translation rules for them into relevant DLs. These algorithms and rules prove that (i) two of our SLs (namely PolSyl and NegSyl) are tractable fragments of DLs, and (ii) other two SLs (namely ComSyl and ComSyl+) are categorical fragments of DL AEC and DL AEC:0 with general TBoxes, respectively. These findings bridge the gap between (ancient) SLs and (modern) DLs. An immediate result is that it is possible to combine powerful features of both logics, for example, intuitional user interface of an SL and efficient reasoning algorithms for a DL. Finally, we propose a framework for knowledge representation in SLs and link it to sound and complete DL reasoners for automated deduction.Conference Object Citation - WoS: 3Citation - Scopus: 6Spl-At Gherkin: a Gherkin Extension for Feature Oriented Testing of Software Product Lines(IEEE, 2019) Tuğlular, Tuğkan; Şensülün, SecanAs cloud platforms turn into software product lines (SPLs), testing products composed of customer selected features becomes more and more important. In this paper, we propose a feature-oriented testing approach for platform-based SPLs through a novel extension to Gherkin called SPL-AT Gherkin and a novel automatic test method generation technique, which utilizes TestNG framework. We demonstrate the applicability of the proposed approach by a case study.Conference Object Citation - WoS: 5Citation - Scopus: 5Featured Event Sequence Graphs for Model-Based Incremental Testing of Software Product Lines(IEEE, 2019) Tuğlular, Tuğkan; Beyazıt, Mutlu; Öztürk, DilekThe goal of software product lines (SPLs) is rapid development of high-quality software products in a specific domain with cost minimization. To assure quality of software products from SPLs, products need to be tested systematically. However, testing every product variant in isolation is generally not feasible for large number of product variants. An approach to deal with this issue is to use incremental testing, where test artifacts that are developed for one product are reused for another product which can be obtained by incrementally adding features to the prior product. We propose a novel model-based test generation approach for products developed using SPL that follows incremental testing paradigm. First, we introduce Featured Event Sequence Graphs (FESGs), an extension of ESGs, that provide necessary definitions and operations to support commonalities and variabilities in SPLs with respect to test models. Then we propose a test generation technique for the product variants of an SPL, which starts from any product. The proposed technique with FESGs avoids redundant test generation for each product from SPL. We compare our technique with in-isolation testing approach by a case study.Conference Object Citation - WoS: 15Citation - Scopus: 20Measureability of Functional Size in Agile Software Projects: Multiple Case Studies With Cosmic Fsm(IEEE, 2019) Hacaloğlu, Tuna; Demirörs, OnurFunctional size measurement (FSM) has been used in software engineering for decades as a main driver for estimation and significant input for other various project management activities throughout the project life span. To apply FSM accurately at the early stages of software development process, especially for estimation purposes, functional user requirements need to be available in detail as required by the adopted FSM method. However, in agile software development, requirement specifications, in general, are kept minimal. For this reason, the adjustment of the requirements to the necessary granularity level has been articulated as one of the barriers preventing the diffusion of FSM practices among agile teams. In this paper, we take a closer look at this problem in order to investigate the usability of FSM and to reveal FSM related challenges empirically through case studies on real agile projects from different software organizations. This study also provides a snapshot of agile organizations in terms of requirement specification and estimation related practices. © 2019 IEEE.