Makale Koleksiyonu

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Genetik algoritmalar kullanılarak metinlerde otomatik özet çıkarma
(IEEE, 2020-01-07) Karcıoğlu, Abdullah Ammar; Yaşa, Ahmet Cahit; Yaşa, Ahmet Cahit; Fakülteler > Mühendislik Ve Doğa Bilimleri Fakültesi > Bilgisayar Mühendisliği Bölümü
Automatic text summarization is one of the applications of natural language processing that has been studied for a long time. The increase in the amount of information in web resources has increased the need for automatic text summarization methods. It is difficult to design a system to produce abstracts created by human hands. For this reason, many researchers have focused on extracting sentences or paragraphs, which is a kind of summary. In this study, we introduce a method that was created using genetic algorithms to generate such summaries. After the texts are preprocessed, vocabulary is created and given as input to the proposed method. The sentence selection based on Genetic Algorithm is used to summarize and after that the summary is created, it is evaluated using the fitness function. In our first model, the fitness function is based on the frequency of each word and the word pair frequencies. The results of the applied model are discussed using the same dataset in another method based on tf-idf, with precision, recall, fscore and Rouge metrics.
OPPCAT: Ontology population from tabular data
(SAGE Publications Ltd., 2019-02) Öztürk, Övünç; Öztürk, Övünç; Fakülteler > Mühendislik Ve Doğa Bilimleri Fakültesi > Bilgisayar Mühendisliği Bölümü
In order to present large amount of information on the Web to both users and machines, it is urgently needed to structure Web data. E-commerce is one of the areas where increasing data bottlenecks on the Web inhibit data access. Ontological display of the product information enables better product comparison and search applications using the semantics of the product specifications and their corresponding values. In this article, we present a framework called OPPCAT, which is used for semi-automatic ontology population from tabular data in e-commerce stores and product catalogues. As a result, OPPCAT allows tabular data to be used for mass production of ontology content. First, we present the common patterns in tabular data which obstruct semi-automatic production of ontologies. Then, we suggest solutions which automatically fix these errors. Finally, we define an algorithm to build ontology content semi-automatically.
Onyx: A new Canvas-based tool for visualizing biomedical and health ontologies
(Wiley, 2019-02) Öztürk, Övünç; Açıkgöz, Hasan Gökhan; Öztürk, Övünç; Fakülteler > Mühendislik Ve Doğa Bilimleri Fakültesi > Bilgisayar Mühendisliği Bölümü
Ontologies provide formal, machine-readable, and human-interpretable representations of domain knowledge. Therefore, ontologies have come into question with the development of Semantic Web technologies. People who want to use ontologies need an understanding of the ontology, but this understanding is very difficult to attain if the ontology user lacks the background knowledge necessary to comprehend the ontology or if the ontology is very large. Thus, software tools that facilitate the understanding of ontologies are needed. Ontology visualization is an important research area because visualization can help in the development, exploration, verification, and comprehension of ontologies. This paper introduces the design of a new ontology visualization tool, which differs from traditional visualization tools by providing important metrics and analytics about ontology concepts and warning the ontology developer about potential ontology design errors. The tool, called Onyx, also has advantages in terms of speed and readability. Thus, Onyx offers a suitable environment for the representation of large ontologies, especially those used in biomedical and health information systems and those that contain many terms. It is clear that these additional functionalities will increase the value of traditional ontology visualization tools during ontology exploration and evaluation.
An approach for online weight update using particle swarm optimization in dynamic fuzzy cognitive maps
(Institute of Electrical and Electronics Engineers Inc., 2018-09-20) Altundoğan, Turan Göktuğ; Karaköse, Mehmet; Altundoğan, Turan Göktuğ; Fakülteler > Mühendislik Ve Doğa Bilimleri Fakültesi > Bilgisayar Mühendisliği Bölümü
Fuzzy cognitive maps (FCM) is a method to update a given initial vector to obtain the most stable state of a system, using a neighborhood of weights between these vectors and updating it over a series of iterations. FCMs are modeled with graphs. Neighbor weights between nodes are between -1 and 1. Nowadays it is used in business management, information technology, communication, health and medical decision making, engineering and computer vision. In this study, a dynamic FCM structure based on Particle Swarm Optimization (PSO) is given for determining node weights and online updating for modeling of dynamic systems with FCMs. Neighborhood weights in dynamic FCMs can be updated instantly and the system feedback is used for this update. In this work, updating the weights of the dynamic FCM is a PSO based approach that takes advantage of system feedback. In previous literature suggestions, dynamic FCM structure performs the weight updating process by using rule-based methods such as Hebbian. Metaheuristic methods are less complex and more efficient than rule-based methods in such optimization problems. In the developed PSO approach, the initialize vector state of the system, the weights between the vector nodes, and the desired steady state vector are taken into consideration. As a fitness function, the system has benefited from the convergence state to the desired steady state vector. As a stopping criterion for PSO, 100 * n number of iteration limits have been applied for the initial vector with n nodes. The proposed method has been tested for five different scenarios with different node counts.
Performance analysis of EEG signal processing based device control applications
(Institute of Electrical and Electronics Engineers Inc., 2018-09) Altundoğan, Turan Göktuğ; Karaköse, Mehmet; Altundoğan, Turan Göktuğ; Fakülteler > Mühendislik Ve Doğa Bilimleri Fakültesi > Bilgisayar Mühendisliği Bölümü
Nowadays, many types of devices are controlled by electroselenography (EEG) signals. In the literature and in daily life, related studies with EEG controlled devices are increasing day by day. EEG based control applications are applied on many devices such as robot arm, robot, vehicle and unmanned aerial vehicle (UAV). EEG based control procedures usually involve taking, pre-processing, classifying EEG signals, and applying the resulting command to the controlled device. In this study, a performance analysis was carried out by examining the control application studies using EEG signals in the literature. In this analysis study, firstly all studies related to the subject in the literature are examined and the devices, methods, signal processing techniques and classification algorithms used in these studies are handled separately. Appropriate electrode selection for the type of device used in device control applications using EEG signals and type of interaction for command extraction from EEG signal appears to be an important step. In this respect, performance correlations between the types of EEG devices used in the literature studies and the electrode choices used in these studies were compared. Since there are a variety of preprocessing steps for EEG signals, this study provides comparisons based on EEG signal preprocessing techniques. Artificial neural networks (ANN), support vector machines (SVM) and K nearest neighbours (Knn) are used to classify the works in the literature. In this study, comparative studies based on classification methods used in literature studies are also included. As a result, in this study, the studies in the literature for the device control using the EEG signal are examined, compared, interpreted and evaluated, and the points to be considered in the designs to be performed in this area are given.
Using classification algorithms for Turkish Music Makam recognition
(Selçuk Üniversitesi, 2018-09) Abidin, Didem; Özacar Öztürk, Tuğba; Öztürk, Övünç; Abidin, Didem; Özacar Öztürk, Tuğba; Öztürk, Övünç; Fakülteler > Mühendislik Ve Doğa Bilimleri Fakültesi > Bilgisayar Mühendisliği Bölümü
Turkish Music pieces are used in various studies including makam recognition in computational music domain. Turkish Music pieces offer a rich content to the researchers because of their different makam properties. SymbTr is one of the most referred Turkish Music data sets in this area. In this study, the pieces from SymbTr data set belonging to 13 makams are used to execute 10 different machine learning algorithms for makam recognition and the performances of these algorithms are evaluated. These algorithms were executed on WEKA application environment and the performances in makam recognition were obtained with F-measure and recall metrics. The machine learning algorithms performed between 82% and 88%.
The extension-based inference algorithm for pD
(Elsevier, 2012-02) Öztürk, Övünç; Özacar Öztürk, Tuğba; Ünalır, Murat Osman; Öztürk, Övünç; Özacar Öztürk, Tuğba; Fakülteler > Mühendislik Ve Doğa Bilimleri Fakültesi > Bilgisayar Mühendisliği Bölümü
In this work, we present a scalable rule-based reasoning algorithm for the OWL pD* language. This algorithm uses partial materialization and a syntactic ontology transformation (the extension-based knowledge model) to provide a fast inference. Because the materialized part of the ontology does not contain assertional data, the time consumed by the process, and the number of inferred triples, remain fixed with varying amounts of assertional data. The algorithm uses database reasoning and a query rewriting technique to handle the remaining inference. The extension-based knowledge model and the database reasoning prevent the expected decreases in query performances, which are the natural result of online reasoning during query time. This work also evaluates the efficiency of the proposed method by conducting experiments using LUBM and UOBM benchmarks.
A new method for computer-assisted detection, definition and differentiation of the urinary calculi
(Taylor & Francis, 2014-09) Yıldırım, Düzgün; Öztürk, Övünç; Tutar, Onur; Nurili, Fuad; Bozkurt, İbrahim Halil; Kayadibi, Hüseyin; Karaarslan, Ercan; Öztürk, Övünç; Fakülteler > Mühendislik Ve Doğa Bilimleri Fakültesi > Bilgisayar Mühendisliği Bölümü
Purpose: Urinary stones are common and can be diagnosed with computed tomography (CT) easily. In this study, we aimed to specify the opacity characteristics of various types of calcified foci that develop through the urinary system by using an image analysis program. With this method, we try to differentiate the calculi from the non-calculous opacities and also we aimed to present how to identify the characteristic features of renal and ureteral calcules. Materials and methods: We obtained the CT studies of the subjects (n = 48, mean age = 41 years) by using a dual source CT imaging system. We grouped the calculi detected in the dual-energy CT sections as renal (n = 40) or ureteric (n = 45) based on their locations. Other radio-opaque structures that were identified outside but within close proximity of the urinary tract were recorded as calculi "mimickers". We used ImageJ program for morphological analysis. All the acquired data were analyzed statistically. Results: According to thorough morphological parameters, there were statistically significant differences in the angle and Feret angle values between calculi and mimickers (p < 0.001). Multivariate logistical regression analysis showed that Minor Axis and Feret angle parameters can be used to distinguish between ureteric (p = 0.003) and kidney (p = 0.001) stones. Conclusions: Computer-based morphologic parameters can be used simply to differentiate between calcular and noncalcular densities on CT and also between renal and ureteric stones.
KORAL: Türk müziği için makam tabanlı öneri motoru tasarımı
(Institute of Electrical and Electronics Engineers Inc., 2018-09) Öztürk, Övünç; Özacar Öztürk, Tuğba; Abidin, Didem; Öztürk, Övünç; Özacar Öztürk, Tuğba; Abidin, Didem; Fakülteler > Mühendislik Ve Doğa Bilimleri Fakültesi > Bilgisayar Mühendisliği Bölümü
Bu çalışmada, tek bir Türk Sanat Müziği eserinden yola çıkarak makam ve usul yönünden benzer eserleri bulan ve fasıl niteliğinde bir çalma listesi oluşturabilen bir uygulama tasarımı anlatılmaktadır. Çalışmada kullanılan eserler bir çizgede tutulacak ve bu çizge bağlı veri olarak yayınlanacaktır. Bu bağlamda ilk defa Türk Sanat Müziği eserlerine yönelik bağlı veri standartlarında bir bilgi tabanı oluşturulmuş olacaktır.
Buz pateni öğrenenler için hareket algılama tabanlı bir sistem tasarımı
(Institute of Electrical and Electronics Engineers Inc., 2018-05) Öztürk, Övünç; Kahramanlı, Murat Mecit; Öztürk, Övünç; Fakülteler > Mühendislik Ve Doğa Bilimleri Fakültesi > Bilgisayar Mühendisliği Bölümü
Bu bildiride buz patenini yeni öğrenmeye başlayanlar için hareket algılama tabanlı, ergonomik, kurulumu basit ve taşınabilir bir sistem tasarımı sunulmaktadır. Sistem kullanıcıların temel kayma tekniklerini doğru bir şekilde uygulamasına destek olacaktır. Sistem tasarlanırken, geliştirmeye açık, esnek ve modüler olmasına dikkat edilmiştir. Böylece, daha ileri seviye tekniklerin kontrolünün sağlanması veya sistemin vücut koordinasyonu gerektiren diğer sporlar için adaptasyonu daha kolay bir şekilde gerçekleştirilebilecektir. Sistemin temel destek elemanları ataletsel ölçüm birimleridir. Sistemdeki ataletsel ölçüm birimi bile¸senleri bedenin her bir uzvunun yön vektörünü belirlemektedir. Bu sensörlerden gelen veriler aracılığıyla belirlenmiş olan yönler, sistemde kullanıcıyı doğru bir şekilde yönlendirmek için altyapı oluşturmaktadır. Kullanıcı kulaklıkları ve sensör modüllerini taktıktan sonra sensörlerden gelen veriler kullanılarak kullanıcıya sesli olarak açıkça anlaşılır, motive edici ve kısa komutlar verilecektir.
TSMONT ontolojisi: Türk Sanat Müziği makamlarının anlamsal olarak modellenmesi
(Dicle Üniversitesi, 2018) Öztürk, Övünç; Abidin, Didem; Özacar Öztürk, Tuğba; Öztürk, Övünç; Abidin, Didem; Özacar Öztürk, Tuğba; Fakülteler > Mühendislik Ve Doğa Bilimleri Fakültesi > Bilgisayar Mühendisliği Bölümü
Anlamsal web teknolojileri, yalnızca insanlar tarafından değil makineler tarafında da anlaşılabilir bir veri ağı oluşturulmasını hedefler. Bu veri ağında birbirleriyle ilişkilendirilmiş ontolojiler aracılığıyla veri anlamı ile bağlanır. Ontoloji belirli bir alandaki (örneğin bu çalışmada müzik alanı) ilgili olan bir dizi kavram ve ilişkinin biçimsel belirtimidir. Bu makalede, Türk Sanat Müziği teorisinde yer alan kavramların anlamsal olarak modellenmesine yönelik TSMONT ontolojisi geliştirilmiştir. Bu ontoloji ile Türk Sanat Müziği’nde kullanılan makamlar, diziler, çeşniler, perdeler; bu kavramlar arasındaki ilişkiler ve kavram ve ilişkilere ait örnekler modellenmektedir. Böylelikle müzik alanındaki heterojen veri kaynaklarındaki bilgiden dağıtık ve birlikte çalışabilir bir bilgi tabanı oluşturulabilir.Ayrıca, TSMONT ontolojisi, en çok kullanılan ontoloji değerlendirme araçlarından olan OntoQA metrikleri çerçevesinde değerlendirilmiştir. Yapılan değerlendirme sonucunda TSMONT ontolojisi, derin bir taksonomiye sahip, zengin ilişkilerin olduğu, kavramların kapsamlı bir biçimde modellendiği, yeterli sınıf örneğine sahip ve kavramların birbirine yakın öneme sahip olduğu bir ontoloji olarak değerlendirilmiştir.
A semantic web case study: representing the ephesus museum collection using erlangen CRM ontology
(Springer Verlag, 2017-11) Özacar Öztürk, Tuğba; Öztürk, Övünç; Yüksel, Fulya; Lobaba, Salloutah; Abdülbaki, Baraa; Bilici, Elif; Özacar Öztürk, Tuğba; Öztürk, Övünç; Fakülteler > Mühendislik Ve Doğa Bilimleri Fakültesi > Bilgisayar Mühendisliği Bölümü
Cultural heritage has recently become an important application area for Semantic Web technologies. Semantic Web technologies and ontologies provide a solution for intelligent integration of heterogeneous data about the cultural heritage. The objective of this paper is the construction of an ontology for the cultural heritage related to Selçuk region in Western Turkey. We use a subset of the Erlangen CRM as our ontology schema, then we populate the ontology with 814 objects in the Ephesus Museum. One of the objectives of this work is to integrate the ontology with other projects which use Erlangen CRM as ontology schema. Therefore, we present an integration case study that aggregates content from Ephesus Museum and British Museum.
IRIS: A Prot´eg´e plug-in to extract and serialize product attribute name-value pairs
(2014) Özacar Öztürk, Tuğba; Özacar Öztürk, Tuğba; Fakülteler > Mühendislik Ve Doğa Bilimleri Fakültesi > Bilgisayar Mühendisliği Bölümü
This article introduces IRIS wrapper, which is developed as a Prot´eg´e plug-in, to solve an increasingly important problem: extracting information from the product descriptions provided by online sources and structuring this information so that is sharable among business entities, software agents and search engines. Extracted product information is presented in a GoodRelations-compliant ontology. IRIS also automatically marks up your products using RDFa or Microdata. Creating GoodRelations snippets in RDFa or Microdata using the product information extracted from Web is a business value, especially when you consider most of the popular search engines recommend the use of these standards to provide rich site data for their index.
A tool for producing structured interoperable datafrom product features on the web
(Pergamnon, 2015) Özacar Öztürk, Tuğba; Özacar Öztürk, Tuğba; Fakülteler > Mühendislik Ve Doğa Bilimleri Fakültesi > Bilgisayar Mühendisliği Bölümü
This paper introduces a tool that produces structured interoperable data from product features, i.e., attribute name-value pairs, on the web. The tool extracts the product features using a web site specific template created by the user. The value of the extracted data is maximized by using GoodRelations, which is the standard vocabulary for modeling product types and their features. The final output of the tool is GoodRelations snippets, which contain product features encoded in RDFa or Microdata. These snippets can be embedded into existing static and dynamic web pages in a way accessible to major search engines like Google and Yahoo, mobile applications, and browser extensions. This increases the visibility of your products and services in the latest generation of search engines, recommender systems, and other novel applications.
A perceptual quality metric for dynamic triangle meshes
(Springer International Publishing, 2017) Çipiloğlu Yıldız, Zeynep; Capin, Tolga; Çipiloğlu Yıldız, Zeynep; Fakülteler > Mühendislik Ve Doğa Bilimleri Fakültesi > Bilgisayar Mühendisliği Bölümü
A measure for assessing the quality of a 3D mesh is necessary in order to determine whether an operation on the mesh, such as watermarking or compression, affects the perceived quality. The studies on this field are limited when compared to the studies for 2D. In this work, we aim a full-reference perceptual quality metric for animated meshes to predict the visibility of local distortions on the mesh surface. The proposed visual quality metric is independent of connectivity and material attributes. Thus, it is not associated to a specific application and can be used for evaluating the effect of an arbitrary mesh processing method. We use a bottom-up approach incorporating both the spatial and temporal sensitivity of the human visual system. In this approach, the mesh sequences go through a pipeline which models the contrast sensitivity and channel decomposition mechanisms of the HVS. As the output of the method, a 3D probability map representing the visibility of distortions is generated. We have validated our method by a formal user experiment and obtained a promising correlation between the user responses and the proposed metric. Finally, we provide a dataset consisting of subjective user evaluation of the quality of public animation datasets.
Electrical analogue of arterial blood pressure signals
(Gümüşhane Üniversitesi, 2018) Emek, Sevcan; Evren, Vedat; Bora, Şebnem; Emek, Sevcan; Fakülteler > Mühendislik Ve Doğa Bilimleri Fakültesi > Bilgisayar Mühendisliği Bölümü
In this study, we propose an electrical circuit model that will be useful for understanding of the mechanisms and dynamics of the human cardiovascular system, which is considered as a complex system in the field of physiology. The electrical circuit model, defined as the Windkessel model, plays an important role in the observation of the characteristic effect of the blood pressure on the arterial system. An electrical circuit model, which we have connected to the input terminals of the Windkessel model, ensures that the mean arterial blood pressure signals are observed within the expected range of values. The Windkessel circuit model that we have tried to develop in this study was constructed in a laboratory environment and the results were observed. It is thought that this study will contribute to the literature in terms of the development of the Windkessel model by increasing the number of parameters involved in the models of heart and arterial system.
Simulation of glucose regulating mechanism with an agent-based software engineering tool
(Balikesir University, 2019) Emek, Sevcan; Evren, Vedat; Bora, Şebnem; Emek, Sevcan; Fakülteler > Mühendislik Ve Doğa Bilimleri Fakültesi > Bilgisayar Mühendisliği Bölümü
This study provides a detailed explanation of a regulating mechanism of the blood glucose levels by an agent-based software engineering tool. Repast Simphony which is used in implementation of this study is an agent-based software engineering tool based on the object-oriented programming using Java language. Agent-based modeling and simulation is a computational methodology for simulating and exploring phenomena that includes a large set of active components represented by agents. The agents are main components situated in space and time of agent-based simulation environment. In this study, we present hormonal regulation of blood glucose levels by our improved agent-based control mechanism. Hormonal regulation of blood glucose levels is an important process to maintain homeostasis inside the human body. We offer a negative feedback control mechanism with agent-based modeling approach to regulate the secretion of insulin hormone which is responsible for increasing the blood glucose levels. The negative feedback control mechanism run by three main agents that interact with each other to perform their local actions in the simulation environment. The result of this study shows the local behavior of the agents in the negative feedback loop and illustrates how to balance the blood glucose levels. Finally, this study which is thought a potential implementation of agent-based modeling and simulation may contribute to the exploration of other homeostatic control systems inside the human body.
WALRUS: A retro communication gadget based on internet of things technologies
(2018) Öztürk, Övünç; Küçük, Yunus Emre; Yalnız, Ahmet; Öztürk, Övünç; Fakülteler > Mühendislik Ve Doğa Bilimleri Fakültesi > Bilgisayar Mühendisliği Bölümü
In this work, a new system depending on a device that can encode and decode push-button signals, modulated using Morse code conventions, were developed to build a low-cost communication medium based on Internet of Things (IoT). The proposed system consists of two parts: a base station and handheld terminals. The base station is a single board computer with a web application based on Node.js. Handheld terminals are small battery powered devices, developed using MCU's, that can communicate with the base station over the wireless network. They can encode and decode Morse code, and convert to text or speech depending on the configuration of the terminal, which can be extended by using different add-ons, such as an OLED screen or a text to speech module. Communication between terminals is orchestrated by the base station using IoT Technologies like MQTT. The handheld terminals can be used by disabled people as a mean for private conversation, or a gadget for entertainment purposes. The system is an uncomplicated and low-cost communication medium and implemented to find alternative use cases for the IoT technologies.
A framework for applying the principles of depth perception to information visualization
(ACM, 2010) Çipiloğlu Yıldız, Zeynep; Bülbül, Abdullah; Capin, Tolga; Çipiloğlu Yıldız, Zeynep; Fakülteler > Mühendislik Ve Doğa Bilimleri Fakültesi > Bilgisayar Mühendisliği Bölümü
During the visualization of 3D content, using the depth cues selectively to support the design goals and enabling a user to perceive the spatial relationships between the objects are important concerns. In this novel solution, we automate this process by proposing a framework that determines important depth cues for the input scene and the rendering methods to provide these cues. While determining the importance of the cues, we consider the user’s tasks and the scene’s spatial layout. The importance of each depth cue is calculated using a fuzzy logic–based decision system. Then, suitable rendering methods that provide the important cues are selected by performing a cost-proﬁt analysis on the rendering costs of the methods and their contribution to depth perception. Possible cue conﬂicts are considered and handled in the system. We also provide formal experimental studies designed for several visualization tasks. A statistical analysis of the experiments veriﬁes the success of our framework.
A machine learning framework for full-reference 3D shape quality assessment
(Springer Berlin Heidelberg, 2018) Çipiloğlu Yıldız, Zeynep; Öztireli, A. Cengiz; Capin, Tolga; Çipiloğlu Yıldız, Zeynep; Fakülteler > Mühendislik Ve Doğa Bilimleri Fakültesi > Bilgisayar Mühendisliği Bölümü
To decide whether the perceived quality of a mesh is inﬂuenced by a certain modiﬁcation such as compressionors impliﬁcation, a metric for estimating the visual quality of 3D meshes is required. Today, machine learning and deep learning techniques are getting increasingly popular since they present efﬁcient solutions to many complex problems. However, these techniques are not much utilized in the ﬁeld of 3D shape perception. We propose a novel machine learning-based approach for evaluating the visual quality of 3D static meshes. The novelty of our study lies in incorporating crowdsourcing in a machine learning framework for visual quality evaluation. We deliberate that this is an elegant way since modeling human visual system processes is a tedious task and requires tuning many parameters. We employ crowdsourcing methodology for collecting data of quality evaluations and metric learning for drawing the best parameters that well correlate with the human perception. Experimental validation of the proposed metric reveals a promising correlation between the metric output and human perception. Results of our crowdsourcing experiments are publicly available for the community.

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