Computer Engineering / Bilgisayar Mühendisliği

Permanent URI for this collectionhttps://hdl.handle.net/11147/10

Browse

Filters

2001 - 2009172010 - 2019312020 - 20243

Settings

Publisher: search.filters.publisher.Institute of Electrical and Electronics Engineers Inc.Scopus Q: search.filters.scopusQuartile.N/A

Search Results

Now showing 1 - 10 of 51
  • Conference Object
    Citation - Scopus: 1
    Applying Weighted Graph Embeddings To Turkish Metaphor Detection
    (Institute of Electrical and Electronics Engineers Inc., 2024) İnan, Emrah
    Metaphor is a common literary mechanism that allows abstract concepts to be conceptualised using more concrete terminology. Existing methods rely on either end-to-end models or hand-crafted pre-processing steps. Generating well-defined training datasets for supervised models is a time-consuming operation for this type of problem. There is also a lack of pre-processing steps for resource-poor natural languages. In this study, we propose an approach for detecting Turkish metaphorical concepts. Initially, we collect non-literal concepts including their meaning and reference sentences by employing a Turkish dictionary. Secondly, we generate a graph by discovering super-sense relations between sample texts including target metaphorical expressions in Turkish WordNet. We also compute weights for relations based on the path closeness and word occurrences. Finally, we classify the texts by leveraging a weighted graph embedding model. The evaluation setup indicates that the proposed approach reaches the best F1 and Gmean scores of 0.83 and 0.68 for the generated test sets when we use feature vector representations of the Node2Vec model as the input of the logistic regression for detecting metaphors in Turkish texts. © 2024 IEEE.
  • Conference Object
    Citation - WoS: 2
    Citation - Scopus: 3
    Adopting Heterogeneous Computing Modules: Experiences From a Touch Summer Workshop
    (Institute of Electrical and Electronics Engineers Inc., 2022) Bunde, D.P.; Ahmed, K.; Ayloo, S.; Brown-Gaines, T.; Fuentes, J.; Jatala, V.; Yeh, T.Y.
    We present efforts to encourage the adoption of modules for teaching heterogeneous parallel computing through a faculty development workshop. The workshop was held remotely using a novel format to exploit the advantages of a virtual format and mitigate its disadvantages. Adoption at a wide variety of institutions showed module effectiveness and also gathered feedback leading to several module improvements. We also report on the adoptions themselves, which show the importance of supporting adaptation of the modules for diverse settings. © 2022 IEEE.
  • Conference Object
    Citation - WoS: 1
    Citation - Scopus: 2
    Predicting the Soft Error Vulnerability of Gpgpu Applications
    (Institute of Electrical and Electronics Engineers Inc., 2022) Topçu, Burak; Öz, Işıl
    As Graphics Processing Units (GPUs) have evolved to deliver performance increases for general-purpose computations as well as graphics and multimedia applications, soft error reliability becomes an important concern. The soft error vulnerability of the applications is evaluated via fault injection experiments. Since performing fault injection takes impractical times to cover the fault locations in complex GPU hardware structures, prediction-based techniques have been proposed to evaluate the soft error vulnerability of General-Purpose GPU (GPGPU) programs based on the hardware performance characteristics.In this work, we propose ML-based prediction models for the soft error vulnerability evaluation of GPGPU programs. We consider both program characteristics and hardware performance metrics collected from either the simulation or the profiling tools. While we utilize regression models for the prediction of the masked fault rates, we build classification models to specify the vulnerability level of the programs based on their silent data corruption (SDC) and crash rates. Our prediction models achieve maximum prediction accuracy rates of 96.6%, 82.6%, and 87% for masked fault rates, SDCs, and crashes, respectively.
  • Conference Object
    Citation - Scopus: 2
    Telsiz Duyarga Ağlarında Hızlı Hareket Eden Hedefler için Küme Tabanlı Hedef İzleme Algoritması
    (Institute of Electrical and Electronics Engineers Inc., 2009) Alaybeyoğlu, Ayşegül; Dağdeviren, Orhan; Kantarcı, Aylin; Erciyes, Kayhan
    Kablosuz iletişim teknolojilerindeki ilerlemelerle birlikte telsiz duyarga ağları (TDA) birçok sivil ve askeri uygulamalarda özellikle de hareketli hedefin takibi gibi konularda yaygın olarak kullanılmaya başlanmıştır. Bu çalışmada da TDA’da hızlı hareket eden nesneler için küme tabanlı bir hedef izleme algoritması önerilmiştir. Literatürde bulunan mevcut çalışmalarda lider düğüm, hedefin sadece t+1 anında yaklaşacağı konumu tahminleyerek bu konuma en yakın düğümü uyandırır. Hedefin çok hızlı hareket etmesi durumunda ise hedefin kısa süre içerisinde bir grup düğümün yakınlarından algılanmadan geçip gitmesi söz konusudur. Önermiş olduğumuz algoritma ile hedefin hızına bağlı olarak, hedefin tahmini gideceği yöndeki düğümler önceden uyandırılarak, kümeler önceden oluşturulmaktadır. Böylece hedefin ani hızlanması durumunda, önceden oluşturmuş olduğumuz kümeler sayesinde hedefin kaybolma riskini azaltmış bulunmaktayız.
  • Conference Object
    Citation - WoS: 38
    Citation - Scopus: 57
    Application Areas of Community Detection: a Review
    (Institute of Electrical and Electronics Engineers Inc., 2019) Karatas, A.; Sahin, S.
    In the realm of today's real world, information systems are represented by complex networks. Complex networks contain a community structure inherently. Community is a set of members strongly connected within members and loosely connected with the rest of the network. Community detection is the task of revealing inherent community structure. Since the networks can be either static or dynamic, community detection can be done on both static and dynamic networks as well. In this study, we have talked about taxonomy of community detection methods with their shortages. Then we examine and categorize application areas of community detection in the realm of nature of complex networks (i.e., static or dynamic) by including sub areas of criminology such as fraud detection, criminal identification, criminal activity detection and bot detection. This paper provides a hot review and quick start for researchers and developers in community detection area. © 2018 IEEE.
  • Conference Object
    Citation - WoS: 5
    Citation - Scopus: 8
    Lensless Digital In-Line Holographic Microscopy for Space Biotechnology Applications
    (Institute of Electrical and Electronics Engineers Inc., 2019) Delikoyun, Kerem; Çine, Ersin; Anıl İnevi, Müge; Özuysal, Mustafa; Özçivici, Engin; Tekin, Hüseyin Cumhur
    Biomechanical changes at cellular level can dramatically affect living organisms in both aviation and space applications. Weightlessness induces morphological alteration of cells, which leads to tissue loss. Therefore, scientists have been studying the effect of weightlessness using cell culture based biological experiments using conventional microscopes. However, strict requirements regarding cost, weight and functionality limit the use of conventional microscopes in space environment. Lensless digital in-line holographic microscopy enables to use low-weight, low-cost and robust elements, such as a light emitting diode (LED), an aperture and an imaging sensor, instead of bulky, expensive and fragile optical elements, such as lenses, mirrors and filters. This technology offers a high field of view compared to conventional microscopes without affecting the resolution and it is also suitable for remote sensing applications with automated imaging capabilities. Here, we present a portable digital in-line holographic microscopy platform that allows to visualize cells and to analyze their viability in a microfluidic chip. The platform offers microscopic imaging with 1.55 mu m spatial resolution, 21.7 mm(2) field of view and image coloring capability. This platform could potentially play an important role in space biotechnology applications by enabling low-cost, high-resolution and portable monitoring of cells.
  • Conference Object
    Utilizing Modeling Approach Patterns in the Embedded Software Industry
    (Institute of Electrical and Electronics Engineers Inc., 2019) Akdur, Deniz; Demirörs, Onur
    To cope with the growing complexity of software-intensive embedded system development, modeling is a widely used approach. The modeling approaches in the embedded software industry vary depending on many modeling characteristics (e.g., purpose, modeling rigor, medium type used, modeling stakeholder profile, etc.). In the light of our previous studies, we have identified modeling approach patterns of embedded software development projects and constructed a characterization model. This model not only identifies and defines modeling approach patterns of the stakeholder in embedded software development projects, but also gives recommendations for commonsense modeling practices. In this article, one of the application results of this characterization model, which was performed in Defense & Aerospace sector is presented. The model was successfully applied to the case, in which a series of both structured and semi-structured interviews with 17 embedded software professionals were conducted. The results show that identification of individual patterns provide insight for improvement both for individuals as well as larger units of operations such as projects and organizations.
  • Conference Object
    Citation - WoS: 1
    Citation - Scopus: 3
    Context-Aware Operation-Based Access Control for Internet of Things Applications
    (Institute of Electrical and Electronics Engineers Inc., 2019) Genç, Didem; Tomur, Emrah; Erten, Yusuf Murat
    Recently, interest of both the academic and industrial world in Internet of Things (IoT) has been increasing and this trend requires development of new security approaches addressing potential weaknesses in this domain. Despite the presence of many studies directed towards security of IoT applications, they are mostly adoption of current methods to IoT scenarios. Yet, IoT applications are comprised of various kinds of different entities including computers, processes, people and services. Therefore, it is inadequate to detect malicious attempts by using conventional security methods, which apply fixed security policies and do not take interaction of things, that is context information, into account. In this study, by considering new security requirements of next generation IoT applications, we propose a fine-grained, dynamic and easily manageable access control model, which is called context-aware operation-based access control.
  • Conference Object
    Citation - Scopus: 3
    Towards Uniform Modeling and Holistic Testing of Hardware and Software
    (Institute of Electrical and Electronics Engineers Inc., 2019) Kılınççeker, Onur; Belli, Fevzi
    This paper introduces an approach to uniform modeling and testing of hardware and software systems and their faults. As an example, for hardware under consideration, designs at a behavioral level will be used, implemented in Hardware Description Language (HDL). For software, an example will be borrowed from a graphical user interface design. Both examples will be modeled by finite state machines. The mutation of these models leads to lucid hardware and software fault models, respectively. Original models and their mutants will then be used to generate test cases for positive testing and negative testing, respectively, forming a holistic test strategy. A positive test is supposed to validate the system under legal (expected, regular) circumstances, whereas a negative test checks the behavior of the system under illegal (unexpected, irregular) situations. Non-trivial examples are used to validate and analyze the approach with respect to uniform modeling and testing capability. © 2019 IEEE.
  • Conference Object
    Citation - WoS: 2
    Citation - Scopus: 8
    İnsansız Araçlar için Anlamsal Bölütleme ile İmge Tabanlı Konumlandırma
    (Institute of Electrical and Electronics Engineers Inc., 2019) Çınaroğlu, İbrahim; Baştanlar, Yalın
    Bilgisayarlı Görü alanındaki popülerliğini koruyan araştırma konularından birisi insansız araçlarda yer tespiti ve konumlandırmadır. Araçların konumlandırılmasında kullanılan GPS sistemlerinin bazı durumlarda faal olamadığı bilinen bir gerçektir ve bu yetersizlik imge tabanlı konumlandırma çalışmalarına hız vermiştir. Bizim çalışmamızda, araç içinden elde edilmiş Malaga şehir merkezi görüntülerinden oluşan bir veri tabanı kullanılarak imge tabanlı konumlandırma yapılmıştır. İlk olarak, anlamsal (semantik) bölütleme sonucunda elde edilen bir anlamsal betimleyici oluşturulmuş ve yaklaşık en yakın komşuluk araması tekniği de kullanılarak bir konumlandırma yapılmıştır. Ardından bu yöntemin başarısı, literatürde sıkça kullanılan yerel betimleyici tabanlı yöntemin başarısıyla kıyaslanmıştır. Ayrıca, bu iki yöntemin birleştirilmesi ile elde edilen melez bir yöntem önerilmiştir. Önerilen melez imge-tabanlı konumlandırmanın, sadece yerel betimleyici ve sadece anlamsal betimleyici kullanan yöntemden daha başarılı olduğu, dolayısıyla yerel betimleyici tabanlı yöntemlerin anlamsal betimleyiciler ile desteklenmesinin başarıyı artırdığı, deneysel sonuçlarla gösterilmiştir.