Scopus İndeksli Yayınlar Koleksiyonu / Scopus Indexed Publications Collection

Permanent URI for this collectionhttps://hdl.handle.net/11147/7148

Browse

Search Results

Now showing 1 - 10 of 29
  • Conference Object
    Yazilim Yapisal Kapsama Analizinde Testlerin Önceliklendirilmesi
    (CEUR-WS, 2015) Ayav,T.
    [No abstract available]
  • Conference Object
    Sayisal Devrelerin Model Kontrol Tabanli Testi
    (CEUR-WS, 2015) Takan,S.
    [No abstract available]
  • Conference Object
    Citation - Scopus: 2
    Outage Probability Analysis of Triple-Hybrid Rf/Fso Communication System
    (Ieee, 2024) Bakirci, Emre Berker; Ahrazoglu, Evla Safahan; Altunbas, Ibrahim; Erdogan, Eylem
    Terahertz (THz) and free space optical (FSO) transmission techniques are considered as alternatives for radio frequency (RF) transmission to meet the requirements for the sixth generation and beyond wireless communication systems. However, these transmission techniques may experience high level of deterioration under different weather conditions. In this study, triple-hybrid RF/FSO/THz system is proposed to enhance the system performance. The results have shown that the proposed system has improved outage probability performance under wide range weather conditions compared to only RF, only FSO, and only THz systems as well as dual-hybrid systems (RF/FSO, RF/THz, and FSO/THz). Theoretical results are validated via computer simulations.
  • Conference Object
    Improvements on a Multi-Task Bert Model
    (Ieee, 2024) Agrali, Mahmut; Tekir, Selma
    Pre-trained language models have introduced significant performance boosts in natural language processing. Fine-tuning of these models using downstream tasks' supervised data further improves the acquired results. In the fine-tuning process, combining the learning of tasks is an effective approach. This paper proposes a multi-task learning framework based on BERT. To accomplish the tasks of sentiment analysis, paraphrase detection, and semantic text similarity, we include linear layers, a Siamese network with cosine similarity, and convolutional layers to the appropriate places in the architecture. We conducted an ablation study using Stanford Sentiment Treebank (SST), Quora, and SemEval STS datasets for each task to test the framework and its components' effectiveness. The results demonstrate that the proposed multi-task framework improves the performance of BERT. The best results obtained for sentiment analysis, paraphrase detection, and semantic text similarity are accuracies of 0.534 and 0.697 and a Pearson correlation coefficient of 0.345.
  • Conference Object
    Citation - WoS: 1
    Konteyner Görüntülerini Kullanarak Hasar Tespiti ve Sınıflandırması
    (IEEE, 2020) Imamoglu, Zeynep Ekici; Tuglular, Tugkan; Bastanlar, Yalin
    In the logistics sector, digital transformation is of great importance in terms of competition. In the present case, container warehouse entry / exit operations are carried out manually by the logistics personnel including container damage detection. During container warehouse entry / exit process, the process of detecting damaged containers is carried out by the personnel and several minutes are required to upload to the IT system. The aim of our work is to automate the detection of damaged containers. This way, the mistakes made by the personnel will be eliminated and the process will be accelerated. In this work, we propose to use a convolutional neural network (CNN) that takes the container images and classify them as damaged or undamaged. We modeled the problem as a binary classification and employed different CNN models. The result we obtained shows that there is no single best method for the classification. It is shown how the dataset was created and how the parameters used in the layered structures affect the models employed in this study.
  • Conference Object
    Citation - WoS: 1
    An Origami-Inspired Low-Cost Waveguide Design, Fabrication and Measurements for X-Band Satellite Communication Systems
    (IEEE, 2023) Karatay, Anıl; Ataç, Enes; Yaman, Fatih
    In many applications such as satellite communication, transmission lines are required and waveguides are widely used in these applications. This passive component, which is an indispensable element of microwave systems, is generally not suitable for practical and low-cost applications due to being produced from costly and heavy metals. Therefore, nowadays, the tendency to use low-cost, light and practical components has increased. In this study, origami-inspired waveguide design for X-band satellite communication systems is aimed. This component, which is formed by folding a paper into a three-dimensional structure and covering it with a conductive material, is both practical and fast to produce, portable and adjustable. The obtained simulation results match well with the experimental results, and it has been proven that the paper-based waveguide performs as well as the conventional aluminum waveguide. This makes the proposed method an innovative and cost-effective solution for waveguide fabrication.
  • Conference Object
    Citation - WoS: 2
    Citation - Scopus: 3
    Long Term Wind Speed Prediction With Polynomial Autoregressive Model
    (Institute of Electrical and Electronics Engineers Inc., 2015) Karakuş, Oktay; Kuruoğlu, Ercan E.; Altınkaya, Mustafa Aziz
    Wind energy is one of the preferred energy generation methods because wind is an important renewable energy source. Prediction of wind speed in a time period, is important due to the one-to-one relationship between wind speed and wind power. Due to the nonlinear character of the wind speed data, nonlinear methods are known to produce better results compared to linear time series methods like Autoregressive (AR), Autoregressive Moving Average (ARMA) in predicting in a period longer than 12 hours. A method is proposed to apply a 48-hour ahead wind speed prediction by using the past wind speed measurements of the (Cesme Peninsula. We proposed to model wind speed data with a Polynomial AR (PAR) model. Coefficients of the models are estimated via linear Least Squares (LS) method and up to 48 hours ahead wind speed prediction is calculated for different models. In conclusion, a better performance is observed for higher than 12-hour ahead wind speed predictions of wind speed data which is modelled with PAR model, than AR and ARMA models.
  • Conference Object
    Citation - WoS: 1
    Citation - Scopus: 2
    Scene text localization using keypoints
    (Institute of Electrical and Electronics Engineers Inc., 2015) Erdoğmuş, Nesli; Özuysal, Mustafa
    Scene text localization and recognition (also known as text localization and recognition in real-world images, nature scene OCR or text-in-the-wild problem) is an open problem, attracting increasing interest from researchers. In this paper, we address the localization issue and leave the recognition part out of its scope. For the purpose of scene text localization, Scale-Invariant Feature Transform (SIFT) keypoints are extracted from the images and classified as text and non-text. Subsequently, the text keypoints are utilized to compute the bounding boxes around text regions. The proposed technique is tested on the database of ICDAR 2013 Robust Reading Competition-Challenge 2 and the experimental results are reported in detail. Although the idea introduced here is still at its infancy, it is observed to achieve remarkable results and due to the fact that there is a large room for improvement, it is found to be promising.
  • Conference Object
    A Detailed Analysis of Mser and Fast Repeatibility
    (Institute of Electrical and Electronics Engineers Inc., 2015) Uzyıldırım, Furkan Eren; Köksal, Ali; Özuysal, Mustafa
    This paper investigates the relationship between the MSER and FAST repeatability and changes in various camera parameters. By employing a realistic view synthesis methodology, it is possible to observe the effect of small parameter changes on the repeatability. Furthermore, for the analysis of MSER repeatability, a convex hull approach is proposed instead of fitting ellipses to the MSER region. This yields a better approximation to the MSER region without significantly increasing computation time.
  • Conference Object
    Citation - Scopus: 1
    Modelling Twin Rotor System With Artificial Neural Networks
    (Institute of Electrical and Electronics Engineers Inc., 2015) Deniz, Meryem; Bıdıklı, Barış; Bayrak, Alper; Özdemirel, Barbaros; Tatlıcıoğlu, Enver
    In this study, the input output relation of the twin rotor system which was constructed in our laboratory is obtained by using ANNs. When compared with the existing literature, main advantage of this modelling approach is that multi input multi output ANN structure is used preferred. As a result of this approach, the cross coupling effects, between the rotors and also between the outputs, are taken into consideration. Thus, we sincerely believe that the obtained input output model demonstrates a close behavior to the real system.