PRIMARY SCHOOL TEACHERS’ VIEWPOINTS ON READING COMPREHENSION DIFFICULTIES OF 3RD AND 4TH GRADE PRIMARY SCHOOL STUDENTS

The purpose of the present study is to determine the viewpoints of primary school teachers on difficulties experienced by 3rd and 4th grade primary school students in reading comprehension. The study was planned in Phenomenology Design, which is one of the Qualitative Research Methods. The study group consisted of 25 primary school teachers working at 7 primary schools in the city center of Bayburt. The sampling of the study was determined with the Criterion Sampling Method, which is one of the Purposeful Sampling Methods. Semi-structured Interview Forms were used for data collection. The Descriptive Analysis Methods were used in the analysis of the data. As a result of the study, it was concluded that difficulties in reading comprehension appeared in the form of difficulties in answering questions after reading a text; the cause of the difficulty in reading was students’ not focusing on the meaning; and teachers conducted plenty of activities suitable for the levels of students to overcome the difficulties in reading.   Article visualizations

Next-gen traffic surveillance: AI-assisted mobile traffic violation detection system

Road traffic accidents pose a significant global public health concern, leading to injuries, fatalities, and vehicle damage. Approximately 1,3 million people lose their lives daily due to traffic accidents [World Health Organization, 2022]. Addressing this issue requires accurate traffic law violation detection systems to ensure adherence to regulations. The integration of Artificial Intelligence algorithms, leveraging machine learning and computer vision, has facilitated the development of precise traffic rule enforcement. This paper illustrates how computer vision and machine learning enable the creation of robust algorithms for detecting various traffic violations. Our model, capable of identifying six common traffic infractions, detects red light violations, illegal use of breakdown lanes, violations of vehicle following distance, breaches of marked crosswalk laws, illegal parking, and parking on marked crosswalks. Utilizing online traffic footage and a self-mounted on-dash camera, we apply the YOLOv5 algorithm's detection module to identify traffic agents such as cars, pedestrians, and traffic signs, and the strongSORT algorithm for continuous interframe tracking. Six discrete algorithms analyze agents' behavior and trajectory to detect violations. Subsequently, an Identification Module extracts vehicle ID information, such as the license plate, to generate violation notices sent to relevant authorities

PyNanospacing: TEM image processing tool for strain analysis and visualization

The diverse spectrum of material characteristics including band gap, mechanical moduli, color, phonon and electronic density of states, along with catalytic and surface properties are intricately intertwined with the atomic structure and the corresponding interatomic bond-lengths. This interconnection extends to the manifestation of interplanar spacings within a crystalline lattice. Analysis of these interplanar spacings and the comprehension of any deviations, whether it be lattice compression or expansion, commonly referred to as strain, hold paramount significance in unraveling various unknowns within the field. Transmission Electron Microscopy (TEM) is widely used to capture atomic-scale ordering, facilitating direct investigation of interplanar spacings. However, creating critical contour maps for visualizing and interpreting lattice stresses in TEM images remains a challenging task. Here we developed a Python code for TEM image processing that can handle a wide range of materials including nanoparticles, 2D materials, pure crystals and solid solutions. This algorithm converts local differences in interplanar spacings into contour maps allowing for a visual representation of lattice expansion and compression. The tool is very generic and can significantly aid in analyzing material properties using TEM images, allowing for a more in-depth exploration of the underlying science behind strain engineering via strain contour maps at the atomic level.Comment: Preprint, 13 pages, 9 figure

Edge on Wheels With OMNIBUS Networking for 6G Technology

In recent years, both the scientific community and the industry have focused on moving computational resources with remote data centres from the centralized cloud to decentralised computing, making them closer to the source or the so called “edge” of the network. This is due to the fact that the cloud system alone cannot sufficiently support the huge demands of future networks with the massive growth of new, time-critical applications such as self-driving vehicles, Augmented Reality/Virtual Reality techniques, advanced robotics and critical remote control of smart Internet-of-Things applications. While decentralised edge computing will form the backbone of future heterogeneous networks, it still remains at its infancy stage. Currently, there is no comprehensive platform. In this article, we propose a novel decentralised edge architecture, a solution called OMNIBUS, which enables a continuous distribution of computational capacity for end-devices in different localities by exploiting moving vehicles as storage and computation resources. Scalability and adaptability are the main features that differentiate the proposed solution from existing edge computing models. The proposed solution has the potential to scale infinitely, which will lead to a significant increase in network speed. The OMNIBUS solution rests on developing two predictive models: (i) to learn timing and direction of vehicular movements to ascertain computational capacity for a given locale, and (ii) to introduce a theoretical framework for sequential to parallel conversion in learning, optimisation and caching under contingent circumstances due to vehicles in motion

Synthesis, Contact Printing, and Device Characterization of Ni-Catalyzed, Crystalline InAs Nanowires

InAs nanowires have been actively explored as the channel material for high performance transistors owing to their high electron mobility and ease of ohmic metal contact formation. The catalytic growth of non-epitaxial InAs nanowires, however, has often relied on the use of Au colloids which is non-CMOS compatible. Here, we demonstrate the successful synthesis of high yield of crystalline InAs nanowires with high yield and tunable diameters by using Ni nanoparticles as the catalyst material on amorphous SiO2 substrates. The nanowires show superb electrical properties with field-effect electron mobility ~2,700 cm2/Vs and ION/IOFF >103. The uniformity and purity of the grown InAs nanowires are further demonstrated by large-scale assembly of parallel arrays of nanowires on substrates via the contact printing process that enables high performance, printable transistors, capable of delivering 5-10 mA ON currents (~400 nanowires).Comment: 21 pages, 5 figures included, all in .docx format. Nano Research (In Press

Application of two dimensional and high surface area materials in energy conversion and storage devices

The work presented in this thesis aims to emphasize the power of two dimensional (2D) and high surface area material integration into energy harvesting and storage devices by introducing new techniques and devices. The techniques and device architectures are unique and encourage new ways of thinking in experimental condensed matter physics, material growth, and synthesis, while providing new perspectives to science and engineering.This thesis consists of three parts: Part I introduces two dimensional and high surface area materials. Part II focuses on energy harvesting devices and the demonstration of different solar cell architectures with integration of graphene, hexagonal boron nitride (h-BN), and graphene aerogel (GA). In Part III, various energy storage device architectures are introduced for lithium ion batteries (LIBs) and lithium air batteries (Li-air) by incorporating different high surface area materials: boron nitride aerogels (BNAG), boron nitride nanotubes (BNNTs), or graphene aerogels (GA). Additional measurements, supplementary figures, and detailed fabrication methods are discussed in the appendix

Application of two dimensional and high surface area materials in energy conversion and storage devices

The work presented in this thesis aims to emphasize the power of two dimensional (2D) and high surface area material integration into energy harvesting and storage devices by introducing new techniques and devices. The techniques and device architectures are unique and encourage new ways of thinking in experimental condensed matter physics, material growth, and synthesis, while providing new perspectives to science and engineering.This thesis consists of three parts: Part I introduces two dimensional and high surface area materials. Part II focuses on energy harvesting devices and the demonstration of different solar cell architectures with integration of graphene, hexagonal boron nitride (h-BN), and graphene aerogel (GA). In Part III, various energy storage device architectures are introduced for lithium ion batteries (LIBs) and lithium air batteries (Li-air) by incorporating different high surface area materials: boron nitride aerogels (BNAG), boron nitride nanotubes (BNNTs), or graphene aerogels (GA). Additional measurements, supplementary figures, and detailed fabrication methods are discussed in the appendix

Basınç Girdaplı Bir Püskürteçte Damlacık Boyut Dağılımı Ve Hava Çekirdeği Kararsızlığının İncelenmesi

Konferans Bildirisi -- Teorik ve Uygulamalı Mekanik Türk Milli Komitesi, 2015Conference Paper -- Theoretical and Applied Mechanical Turkish National Committee, 2015Basınç girdaplı enjektörler sıvı yakıtlı roket motorlarında yakıt ve oksitleyicinin itki odasına püskürtülmesi için kullanılır. Bu çalışmada basınçlı girdap tipi püskürteç içindeki akış hesaplamalı akışkanlar dinamiği kullanılarak incelenmiştir. Zamana bağlı benzetimler iki fazlı laminer sıkıştırılamaz akış kabulü altında Sıvının Hacmi (VOF) metodu, iki boyutlu girdaplı eksenel simetrik çözüm ağı kullanılarak yapılmıştır. İncelenen geometri için püskürtecin basınç düşüşü 5.3 g/s için 8 bar ve yarım koni açısı 28 derece olarak bulunmuştur. Elde edilen sayısal sonuçlar işlenerek spreyin Sauter ortalama çapı 74 m olarak elde edilmiştir. Girdap odasının duvar sınırlarına yakın bölgelerinde Taylor girdapları oluşmaktadır. Püskürteç içerisinde basınç ve hava çekirdeği çapı çalkantıları gözlenmektedir. Basınç çalkantılarının baskın modu 274 Hz civarında, hava çekirdeği çapı salınımlarının dominant modu ise 47 Hz civarındadır. Bu çalkantılar neticesinde spreyin koni açısı da modüle edilmektedir. Sayısal sonuçlar açık literatürdeki deneysel gözlemler ile uyumludur.Pressure swirl atomizers are used in rocket engines with liquid propellants to spray fuel and oxidizer into the combustion chamber. In this study, flow inside the pressure swirl atomizer is investigated with computational fluid dynamics. Simulations are carried out using Volume of Fluid (VOF) method with axisymmetric boundary condition assuming flow is incompressible in two dimension. Pressure drop and half cone angle of investigated geometry found as 8 bars and 28 degrees for 5.3 g/s flow rate. Sauter Mean Diameter of the atomizer is calculated as 74.6 m. Formation of Taylor vortices are observed near the swirl chamber walls. After flow became fully developed, pressure inside swirl chamber and air core diameter fluctuated over time. Dominant mode of pressure and air core diameter change was found 274 Hz and 47 Hz, respectively. Numerical solutions are consistent with experimental observations in literature