WoS İndeksli Yayınlar Koleksiyonu

Permanent URI for this collectionhttps://hdl.handle.net/20.500.12573/394

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Phase-Synchronized Fluidic Oscillator Pair
(AMER INST AERONAUTICS ASTRONAUTICS, 1801 ALEXANDER BELL DRIVE, STE 500, RESTON, VA 22091-4344 USA, 2019) Tomac, Mehmet N; Gregory, James W.
The relative phase of oscillating jets from a pair of fluidic oscillators was synchronized in this work. The means for this synchronization was mutual interaction through a shared feedback channel between the two oscillators. Flow visualization and hot-wire measurements indicated a strong correlation and phase synchronization between the two oscillators. A numerical analysis offered better understanding of the internal flow physics that led to the synchronization phenomenon. A portion of the output jet from one fluidic oscillator was redirected and crossed over into the adjacent oscillator, leading to momentum transfer between the two oscillators. A portion of this cross-oscillator flow was directed into the shared feedback channel and constituted the main feedback flow. In this process, one of the shared feedback channel outlets was blocked by a vortex, allowing only one oscillator to receive feedback flow. The primary mechanism for in-phase synchronization was the cross-oscillator flow, which was divided into phase-modulated momentum injection to the primary jet and modulated flow input to the shared channel feedback channel.
A rational utilization of reinforcement material for flexural design of 3D-printed composite beams
(SAGE PUBLICATIONS LTD, 1 OLIVERS YARD, 55 CITY ROAD, LONDON EC1Y 1SP, ENGLAND, 2019) Ciftci, Cihan; Sas, Hatice S.
Recent developments in composite industry address the adaptation of 3D printing technology to overcome the design and manufacturing challenges of the traditional composite processing techniques. This adaptation can be performed with the development of design methodologies corresponding to the type of structural load-carrying members in a structure. Considering the frequently use of beams in structures, the development of the design methodology of beams is essential for the adaptation of the additive manufacturing. Therefore, in this paper, the flexural loading concept is analytically formulated to derive moment capacity for the flexural behavior of 3D-printed composite beams. Then, the formulation is adapted to develop a design methodology of 3D-printed laminates under flexural loading. Additionally, the analytical solutions developed for the design methodology presented in this paper were verified with a good agreement with experimental studies.
TURKEY
(ROUTLEDGE2 PARK SQ, MILTON PARK, ABINGDON OX14 4RN, OXFORD, ENGLAND, 2017) Salman, Yildiz; Polat, Ebru Omay; Yoney, Nilufer Baturayoglu
TURKEY
Structure Health Monitoring Using Wireless Sensor Networks on Structural Elements (vol 82, pg 68, 2019)
(ELSEVIER, RADARWEG 29, 1043 NX AMSTERDAM, NETHERLANDS, 2020) Ayyildiz, Cem; Erdem, H. Emre; Dirikgil, Tamer; Dugenci, Oguz; Kocak, Taskin; Altun, Fatih; Gungor, V. Cagri
This paper presents a system that monitors the health of structural elements in Reinforced Concrete (RC), concrete elements and/or masonry buildings and warn the authorities in case of physical damage formation. Such rapid and reliable detection of impairments enables the development of better risk management strategies to prevent casualties in case of earthquake and floods. Piezoelectric (PZT) sensors with lead zirconate titanate material are the preferred sensor type for fracture detection. The developed sensor mote hardware triggers the PZT sensors and collects the responses they gather from the structural elements. It also sends the collected data to a data center for further processing and analysis in an energy-efficient manner utilizing low-power wireless communication technologies. The access and the analysis of the collected data can be remotely performed via a web interface. Performance results show that the fractures serious enough to cause structural problems can be successfully detected with the developed system.
QOS-AWARE DOWNLINK SCHEDULING ALGORITHM FOR LTE NETWORKS: A CASE STUDY ON EDGE USERS
(Abdullah Gül Üniversitesi, 2016) UYAN, OSMAN GÖKHAN
4G/LTE (Long Term Evolution) is the state of the art wireless mobile broadband technology. It allows users to take advantage of high internet speeds. It makes use of the OFDM technology to offer high speed, which supplies the system resources both in time and frequency domain. The allocation of these resources is operated by a scheduling algorithm running on the base station. In this thesis, we investigate the performance of existing downlink scheduling algorithms in two ways. First we look at the performance of the algorithms in terms of throughput and fairness metrics. Second, we suggest a new fairness criterion, QoS-aware fairness which accepts that the system is fair if it can supply the users with the packet delays that they demand, and we evaluate the performance of the algorithms according to this metric. We also propose a new algorithm according to these two metrics, which especially increase the throughput gained by the edge users, the QoS-fairness, and classical fairness of the system without causing a big degradation in cell throughput when compared to other schedulers.
Human identification using palm print images based on deep learning methods and gray wolf optimization algorithm
(SPRINGER, 2024) Alshakree, Firas; Akbas, Ayhan; Rahebi, Javad
Palm print identification is a biometric technique that relies on the distinctive characteristics of a person’s palm print to distinguish and authenticate their identity. The unique pattern of ridges, lines, and other features present on the palm allows for the identification of an individual. The ridges and lines on the palm are formed during embryonic development and remain relatively unchanged throughout a person’s lifetime, making palm prints an ideal candidate for biometric identification. Using deep learning networks, such as GoogLeNet, SqueezeNet, and AlexNet combined with gray wolf optimization, we achieved to extract and analyze the unique features of a person’s palm print to create a digital representation that can be used for identification purposes with a high degree of accuracy. To this end, two well-known datasets, the Hong Kong Polytechnic University dataset and the Tongji Contactless dataset, were used for testing and evaluation. The recognition rate of the proposed method was compared with other existing methods such as principal component analysis, including local binary pattern and Laplacian of Gaussian-Gabor transform. The results demonstrate that the proposed method outperforms other methods with a recognition rate of 96.72%. These findings show that the combination of deep learning and gray wolf optimization can effectively improve the accuracy of human identification using palm print images.
Effect of Bilinear Interpolation on the Texture Analysis of Colonoscopy Images
(IEEE345 E 47TH ST, NEW YORK, NY 10017 USA, 2017) Kacmaz, Rukiye Nur; Yilmaz, Bulent
Interpolation is a method that is used to obtain unknown intensities with the help of known intensities on an image. This method is frequently used in the literature to eliminate light reflection on colonoscopy images. Texture features are the most important characteristics used to describe the region or objects of interest in the image. They are the measures of intensity variation of a surface that determine properties such as smoothness, roughness, and regularity. The aim of this study is to find out the how bilinear interpolation applied on colonoscopy images with reflection impact texture features obtained from the same images. A research carried out to make reasonable comparison between a texture feature from an image with no reflection and the same feature obtained from the same image with synthetically added reflections with various percentages. Using the approaches like gray level co-occurence matrix (GLCM), gray level run length matrix (GLRLM), neighborhood gray tone difference matrix (NGTDM) 126 features were extracted from each 32x32 sub-images coming from 610 colonoscopy images. Several of the features extracted from sub-images with no reflection and reflection were not statistically significantly different, while majority of them were affected from the reflections.

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