Search results for: Aysun Eksioglu

Authors: Rabia Genc, Aysun Eksioglu, Emine Serap Sarican, Sibel Icke

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Today the habit of cigarette smoking is among one of the most important public health concerns because of the health problems it leads to. The most important and hazardous group to use tobacco and tobacco products is adolescents and teenagers. And one of the most effective ways to prevent them from starting to smoke is education. This research is a kind of educational intervention study which was carried out in order to evaluate the effect of peer education on the teenagers' knowledge about smoking. The research was carried out between October 15, 2013 and September 9, 2015 at Ege University Ataturk Vocational Health School. The population of the research comprised of the students that have been studying at Ege University Atatürk Vocational Health School, Midwifery Department (N=390). The peer educator group that would give training on smoking consisted of 10 people, and the peer groups that would be trained were divided into two groups via simple randomization as experimental group (n=185) and control group (n=185). Questionnaire, information evaluation form, and informed consent forms were used as date collection tools. The analysis of the data which were collected in the study was carried out on Statistical Package for Social Science (SPSS 15.0). It was found out that 62.5 % of the students who were in peer educator group had smoked in some period of their lives; however, none of them continued to smoke. When they were asked about their reasons to start smoking, 25% said they just wanted to try it, and 25% of them answered that it was because of their friend groups. When the pre-peer education and post-peer education point averages of peer educator group were evaluated, the results showed that there was a significant difference between the point averages (p < 0.05). When the cigarette use of experimental group and the control group were evaluated, it was clear that 18.2% of the experimental group and 24.2%of the control group still smokes. 9.1% of the experimental group and 14.8% of control group stated that they started smoking because of their friend groups. Among the students who smoke 15.9% of the ones who belongs to the experimental group and 21.9% of the ones who belong to the control group stated they are thinking of quitting smoking. It was clear that there is a significant difference between the pre-education and post-education point averages of experimental group statistically (p ≤ 0.05); however, in terms of control group, there were no significant differences between the pre-test post-test averages statistically. Between the pre-test post-test averages of experimental and control groups there were not any statistically significant differences (p > 0.05). It was found out in the study that the peer education programme is not effective on the smoking habit of Vocational Health School students. When the future studies are being planned in order to evaluate the peer education activity, it can be taken into consideration that the peer education takes a long term and the students in the educator group will be more enthusiastic and a kind of leader in their environment.

Keywords: midwifery, peer, peer education, smoking

Procedia PDF Downloads 224

Authors: Sezin Ekşioğlu

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Multilabel classification has a huge importance for several applications, it is also a challenging research topic. It is a kind of supervised learning that contains binary targets. The distance between multilabel and binary classification is having more than one class in multilabel classification problems. Features can belong to one class or many classes. There exists a wide range of applications for multi label prediction such as image labeling, text categorization, gene functionality. Even though features are classified in many classes, they may not always be properly classified. There are many ensemble methods for the classification. However, most of the researchers have been concerned about better multilabel methods. Especially little ones focus on both efficiency of classifiers and pairwise relationships at the same time in order to implement better multilabel classification. In this paper, we worked on modified ensemble methods by getting benefit from k-Nearest Neighbors and neural network structure to address issues within a beneficial way and to get better impacts from the multilabel classification. Publicly available datasets (yeast, emotion, scene and birds) are performed to demonstrate the developed algorithm efficiency and the technique is measured by accuracy, F1 score and hamming loss metrics. Our algorithm boosts benchmarks for each datasets with different metrics.

Keywords: multilabel, classification, neural network, KNN

Procedia PDF Downloads 155

Authors: Sinem Toraman, Aysun Öztuna Kaplan, Hatice Mertoğlu, Esra Macaroğlu Akgül

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This study aims to examine pre-service teachers’ opinions on disabled people taking into consideration various variables. The participants of the study are composed of 170 pre-service teachers being 1st year students of different branches at Education Department of Yıldız Technical, Yeditepe, Marmara and Sakarya Universities. Data of the research was collected in 2013-2014 fall term. This study was designed as a phenomenological study appropriately qualitative research paradigm. Pre-service teachers’ opinions about disabled people were examined in this study, open ended question form which was prepared by researcher and focus group interview techniques were used as data collection tool. The study presents pre-service teachers’ opinions about disabled people which were mentioned, and suggestions about teacher education.

Keywords: pre-service teachers, disabled people, teacher education, teachers' opinions

Procedia PDF Downloads 460

Authors: Mustafa Ümi̇t Ünal, Nafi̇z Çeli̇ktaş, Aysun Şener, Sara Betül Dolgun, Duygu Keser

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The aim of this study was to compare acid and base pretreatment of switchgrass for bioethanol production. Switchgrass was pretreated with sulfuric acid and sodium hydroxide at 0.5, 1.0 and 1.5% (v/v) at 120, 140, 180 °C for 10, 60 and 90. Optimization of enzymatic hydrolysis of the pretreated switchgrass samples were carried out using three different enzyme mixtures (22.5 mg cellulase and 75 mg cellobiase /g biomass; 45 mg cellulase and 150 mg cellobiase /g biomass; 90 mg cellulase and 300 mg cellobiase /g biomass). Samples were removed at 24-h interval for fermentable sugar analyses with HPLC. The results showed that use of 90 mg cellulase and 300 mg cellobiase/g biomass resulted in the highest fermentable sugar formation. Furthermore, the highest fermentable sugar yield was obtained by pretreatment at 120 °C for 10 min using 1.0 % sodium hydroxide.

Keywords: switchgrass, acid pretreatment, enzymatic hydrolysis, base pretreatment, ethanol production

Procedia PDF Downloads 532

Authors: Aysun Sezer

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Magnetic Resonance Imaging (MRI) is one of the advanced diagnostic tools for evaluating shoulder pathologies. Proton Density (PD)-weighted MRI sequences prove highly effective in detecting edema. However, they are deficient in the anatomical identification of bones due to a trauma-induced decrease in signal-to-noise ratio and blur in the traumatized cortices. Computer-based diagnostic systems require precise segmentation, identification, and localization of anatomical regions in medical imagery. Deep learning-based object detection algorithms exhibit remarkable proficiency in real-time object identification and localization. In this study, the YOLOv8 model was employed to detect humeral head and scapular regions in 665 axial PD-weighted MR images. The YOLOv8 configuration achieved an overall success rate of 99.60% and 89.90% for detecting the humeral head and scapula, respectively, with an intersection over union (IoU) of 0.5. Our findings indicate a significant promise of employing YOLOv8-based detection for the humerus and scapula regions, particularly in the context of PD-weighted images affected by both noise and intensity inhomogeneity.

Keywords: YOLOv8, object detection, humerus, scapula, IRM

Procedia PDF Downloads 66

Authors: Yasemin Seki, Aysun Akşit

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The goal of this research is to modify the surface characterization of jute yarns with different chemical agents to improve the compatibility with a non-polar polymer, polypropylene, when used as reinforcement. A literature review provided no knowledge on surface treatment of jute fibers with sodium perborate trihydrate. This study also aims to compare the efficiency of sodium perborate trihydrate on jute fiber treatment with other commonly used chemical agents. Accordingly, jute yarns were treated with 0.02% potassium dichromate (PD), potassium permanganate (PM) and sodium perborate trihydrate (SP) aqueous solutions in order to enhance interfacial compatibility with polypropylene in this study. The effect of treatments on surface topography, surface chemistry and interfacial shear strength of jute yarns with polypropylene were investigated. XPS results revealed that surface treatments enhanced surface hydrophobicity by increasing C/O ratios of fiber surface. Surface roughness values increased with the treatments. The highest interfacial adhesion with polypropylene was achieved after SP treatment by providing the highest surface roughness values and hydrophobic character of jute fiber.

Keywords: jute, chemical modification, sodium perborate, polypropylene

Procedia PDF Downloads 509

Authors: Aysun Pınarbaşı, Béla Vizvári

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The countries are the units that procure the vaccines during the COVID-19 pandemic. The delivered quantities are huge. The countries must bear the inventory holding cost according to the variation of stock quantities. This cost depends on the speed of the vaccination in the country. This speed is time-dependent. The vaccinated portion of the population can be approximated by the cumulative distribution function of the Cauchy distribution. A model is provided for determining the minimal-cost inventory policy, and its optimality conditions are provided. The model is solved for 20 countries for different numbers of procurements. The results reveal the individual behavior of each country. We provide an inventory policy for the pandemic period for the countries. This paper presents a deterministic model for vaccines with a demand rate variable over time for the countries. It is aimed to provide an analytical model to deal with the minimization of holding cost and develop inventory policies regarding this aim to be used for a variety of perishable products such as vaccines. The saturation process is introduced, and an approximation of the vaccination curve of the countries has been discussed. According to this aspect, a deterministic model for inventory policy has been developed.

Keywords: covid-19, vaccination, inventory policy, bounded total demand, inventory holding cost, cauchy distribution, sigmoid function

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Authors: Seda Yavuz, Anıl Çelebi, Aysun Taşyapı Çelebi, Oğuzhan Urhan

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Nowadays, demand for using real-time video transmission capable devices is ever-increasing. So, high resolution videos have made efficient video compression techniques an essential component for capturing and transmitting video data. Motion estimation has a critical role in encoding raw video. Hence, various motion estimation methods are introduced to efficiently compress the video. Low bit‑depth representation based motion estimation methods facilitate computation of matching criteria and thus, provide small hardware footprint. In this paper, a hardware implementation of a two-bit transformation based low-complexity motion estimation method using local binary pattern approach is proposed. Image frames are represented in two-bit depth instead of full-depth by making use of the local binary pattern as a binarization approach and the binarization part of the hardware architecture is explained in detail. Experimental results demonstrate the difference between the proposed hardware architecture and the architectures of well-known low-complexity motion estimation methods in terms of important aspects such as resource utilization, energy and power consumption.

Keywords: binarization, hardware architecture, local binary pattern, motion estimation, two-bit transform

Procedia PDF Downloads 314

Authors: Ebru Cubukcu, Gozde Eksioglu Cetintahra, Burcin Hepguzel Hatip, Mert Cubukcu

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Obesity and overweight cause serious health problems. Public and private organizations aim to encourage walking in various ways in order to cope with the problem of obesity and overweight. This study aims to understand how the spatial characteristics of urban street pattern, connectivity and complexity influence young people’s choice to walk or not. 185 public university students in Izmir, the third largest city in Turkey, participated in the study. Each participant had worn an accelerometer and a global positioning (GPS) device for a week. The accelerometer device records data on the intensity of the participant’s activity at a specified time interval, and the GPS device on the activities’ locations. Combining the two datasets, activity maps are derived. These maps are then used to differentiate the participants’ walk trips and motor vehicle trips. Given that, the frequency of walk and motor vehicle trips are calculated at the street segment level, and the street segments are then categorized into two as ‘preferred by pedestrians’ and ‘preferred by motor vehicles’. Graph Theory-based accessibility indices are calculated to quantify the spatial characteristics of the streets in the sample. Six different indices are used: (I) edge density, (II) edge sinuosity, (III) eta index, (IV) node density, (V) order of a node, and (VI) beta index. T-tests show that the index values for the ‘preferred by pedestrians’ and ‘preferred by motor vehicles’ are significantly different. The findings indicate that the spatial characteristics of the street network have a measurable effect on young people’s choice to walk or not. Policy implications are discussed. This study is funded by the Scientific and Technological Research Council of Turkey, Project No: 116K358.

Keywords: graph theory, walkability, accessibility, street network

Procedia PDF Downloads 228