Search results for: Orhan Coban

Authors: F. Nur Baran Aksakal, Özge Dinç, H. Tanju Besler, Begüm Mutuş, Özlem Üliç Çatar, Orhan Aydoğdu, Serhat Ünal

Abstract:

Healthy eating habits are associated not only with the newborn, child, and maternal health but also with longer life expectancy by acting as a protective factor against non-communicable diseases such as obesity, diabetes, cardiovascular diseases, and cancer. The role of nutrition in medical education is to provide information about the relationship between healthy nutrition and malnutrition as well as diet-related non-communicable diseases. Considering the information pollution experienced in the field of nutrition and health in the society, it is seen that more than half of the population receives information from family physicians as the closest counseling unit. However, postgraduate nutrition education programs for physicians and other health professionals who wish to improve their current knowledge of the role of nutrition communication in the prevention and management of chronic diseases are limited worldwide. However, nutrition courses are either not included in the undergraduate medical education curriculum of physicians or they are insufficient. Based on this need, the main aim of the study group was to develop a "Nutrition and Nutrition Communication Training for Physicians" program that would be conducted in cooperation with the Sabri Ülker Foundation and the Federation of Family Physicians Associations (AHEF). This program is the first online nutrition and nutrition communication information platform for physicians in Turkey. This program aims to present the concept of adequate and balanced nutrition to physicians, the importance of nutrition in diseases with scientific data, and to gain communication skills that may be necessary while transferring scientific information to the public. A needs assessment questionnaire was applied to identify pre-program training needs. A study plan was made to allow the participation of all family physicians in the population, and a complete inventory was targeted. In other words, we aimed to reach the whole source without taking a section of the population. Participation in the training is based on volunteerism. The needs assessment study is conducted using 25,102 family physicians for whom email addresses are available. The online questionnaire was sent to all the family physicians with a reminder email one week after the first one, and 1308 responded. Considering the topics determined, a training program was prepared for family physicians under eight online training titles, starting in March 2022, and conducted once every two weeks. The number of audience members present at each session was between 1217 and 1673, and a minimum of 17 and a maximum of 53 questions were received in each session. We strongly believe that to prevent individuals' health problems and to have better control over chronic diseases, the information level of physicians should be increased via these kinds of interventions, and better collaboration between family physicians and dieticians should be established.

Keywords: nutrition communication, nutrition training, communication, nutrition

Procedia PDF Downloads 71

Authors: Orhan Akınoğlu, Arif Çömek, Ersin Elmacı, Tuğba Gündoğdu

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The concept map is known to be a powerful tool to organize the ideas and concepts of an individuals’ mind. This tool is a kind of visual map that illustrates the relationships between the concepts of a certain subject. The effect of concept mapping on cognitive and affective qualities is one of the research topics among educational researchers for last decades. We educators want to utilize it both as an instructional tool or an assessment tool in classes. For that reason, this study aimed to determine the effect of concept mapping as a learning strategy in science classes on students’ academic achievement and attitude. The research employed a randomized pre-test post-test control group design. Data collected from 60 sixth grade students participated in the study from a randomly selected primary school in Turkey. Sixth-grade classes of the school were analyzed according to students’ academic achievement, science attitude, gender, mathematics, science courses grades, and their GPAs before the implementation. Two of the classes found to be equivalent (t=0,983, p>0,05) and one of them was defined as experimental and the other one control group randomly. During a 5-weeks period, the experimental group students (N=30) used the paper-based concept mapping method while the control group students (N=30) were taught with the traditional approach according to the science and technology education curriculum for light and sound subject. Both groups were taught by the same teacher who is experienced using concept mapping in science classes. Before the implementation, the teacher explained the theory of the concept maps and showed how to create paper-based concept mapping individually to the experimental group students for two hours. Then for two following hours she asked them to create some concept maps related to their former science subjects and gave them feedback by reviewing their concept maps to be sure that they can create during the implementation. The data were collected by science achievement test, science attitude scale and personal information form. Science achievement test and science attitude scale were implemented as pre-test and post-test while personal information form was implemented just as once. The reliability coefficient of the achievement test was KR20=0,76 and Cronbach’s Alpha of the attitude scale was 0,89. SPSS statistical software was used to analyze the data. According to the results, there was a statistically significant difference between the experimental and control group for academic achievement but not for attitude. The experimental group had significantly greater gains from academic achievement test than the control group (t=0,02, p<0,05). The findings showed that the paper-and-pencil concept mapping can be used as an effective method for students’ academic achievement in science classes. The results have implications for further researches.

Keywords: concept mapping, science education, constructivism, academic achievement, science attitude

Procedia PDF Downloads 382

Authors: Endalkachew Abebe Kebede, Bojin Bojinov, Andon Vasilev Andonov, Orhan Dengiz

Abstract:

Remote sensing has a potential application in assessing and monitoring the plants' biophysical properties using the spectral responses of plants and soils within the electromagnetic spectrum. However, only a few reports compare the performance of different remote sensing sensors against in-situ field spectral measurement. The current study assessed the potential applications of open data source satellite images (Sentinel 2 and Landsat 9) in estimating the biophysical properties of the wheat crop on a study farm found in the village of OvchaMogila. A Landsat 9 (30 m resolution) and Sentinel-2 (10 m resolution) satellite images with less than 10% cloud cover have been extracted from the open data sources for the period of December 2021 to April 2022. An Unmanned Aerial Vehicle (UAV) has been used to capture the spectral response of plant leaves. In addition, SpectraVue 710s Leaf Spectrometer was used to measure the spectral response of the crop in April at five different locations within the same field. The ten most common vegetation indices have been selected and calculated based on the reflectance wavelength range of remote sensing tools used. The soil samples have been collected in eight different locations within the farm plot. The different physicochemical properties of the soil (pH, texture, N, P₂O₅, and K₂O) have been analyzed in the laboratory. The finer resolution images from the UAV and the Leaf Spectrometer have been used to validate the satellite images. The performance of different sensors has been compared based on the measured leaf spectral response and the extracted vegetation indices using the five sampling points. A scatter plot with the coefficient of determination (R2) and Root Mean Square Error (RMSE) and the correlation (r) matrix prepared using the corr and heatmap python libraries have been used for comparing the performance of Sentinel 2 and Landsat 9 VIs compared to the drone and SpectraVue 710s spectrophotometer. The soil analysis revealed the study farm plot is slightly alkaline (8.4 to 8.52). The soil texture of the study farm is dominantly Clay and Clay Loam.The vegetation indices (VIs) increased linearly with the growth of the plant. Both the scatter plot and the correlation matrix showed that Sentinel 2 vegetation indices have a relatively better correlation with the vegetation indices of the Buteo dronecompared to the Landsat 9. The Landsat 9 vegetation indices somewhat align better with the leaf spectrometer. Generally, the Sentinel 2 showed a better performance than the Landsat 9. Further study with enough field spectral sampling and repeated UAV imaging is required to improve the quality of the current study.

Keywords: landsat 9, leaf spectrometer, sentinel 2, UAV

Procedia PDF Downloads 73

Authors: Fatih Gundogan, Fatih Kafali, Abdullah Karadag, Alper Baloglu, Ersoy Pehlivan, Mustafa Eruyar, Osman Bayram, Orhan Karademiroglu, Wasim Shoman

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Nowadays many cities around the world are investing their efforts and resources for the purpose of facilitating their citizen’s life and making cities more livable and sustainable by implementing newly emerged phenomena of smart city. For this purpose, related research institutions prepare and publish smart city indices or benchmarking reports aiming to measure the city’s current ‘smartness’ status. Several functional domains, various indicators along different selection and calculation methods are found within such indices and reports. The selection criteria varied for each institution resulting in inconsistency in the ranking and evaluating. This research aims to evaluate the impact of selecting such functional domains, indicators and calculation methods which may cause change in the rank. For that, six functional domains, i.e. Environment, Mobility, Economy, People, Living and governance, were selected covering 19 focus areas and 41 sub-focus (variable) areas. 60 out of 191 indicators were also selected according to several criteria. These were identified as a result of extensive literature review for 13 well known global indices and research and the ISO 37120 standards of sustainable development of communities. The values of the identified indicators were obtained from reliable sources for ten cities. The values of each indicator for the selected cities were normalized and standardized to objectively investigate the impact of the chosen indicators. Moreover, the effect of choosing an integration method to represent the values of indicators for each city is investigated by comparing the results of two of the most used methods i.e. geometric aggregation and fuzzy logic. The essence of these methods is assigning a weight to each indicator its relative significance. However, both methods resulted in different weights for the same indicator. As a result of this study, the alternation in city ranking resulting from each method was investigated and discussed separately. Generally, each method illustrated different ranking for the selected cities. However, it was observed that within certain functional areas the rank remained unchanged in both integration method. Based on the results of the study, it is recommended utilizing a common platform and method to objectively evaluate cities around the world. The common method should provide policymakers proper tools to evaluate their decisions and investments relative to other cities. Moreover, for smart cities indices, at least 481 different indicators were found, which is an immense number of indicators to be considered, especially for a smart city index. Further works should be devoted to finding mutual indicators representing the index purpose globally and objectively.

Keywords: functional domain, urban city index, indicator, smart city

Procedia PDF Downloads 121

Authors: Merve Begum Terzi, Orhan Arikan, Adnan Abaci, Mustafa Candemir

Abstract:

Acute myocardial infarction is a major cause of death in the world. Therefore, its fast and reliable diagnosis is a major clinical need. ECG is the most important diagnostic methodology which is used to make decisions about the management of the cardiovascular diseases. In patients with acute myocardial ischemia, temporary chest pains together with changes in ST segment and T wave of ECG occur shortly before the start of myocardial infarction. In this study, a technique which detects changes in ST/T sections of ECG is developed for the early diagnosis of acute myocardial ischemia. For this purpose, a database of real ECG recordings that contains a set of records from 75 patients presenting symptoms of chest pain who underwent elective percutaneous coronary intervention (PCI) is constituted. 12-lead ECG’s of the patients were recorded before and during the PCI procedure. Two ECG epochs, which are the pre-inflation ECG which is acquired before any catheter insertion and the occlusion ECG which is acquired during balloon inflation, are analyzed for each patient. By using pre-inflation and occlusion recordings, ECG features that are critical in the detection of acute myocardial ischemia are identified and the most discriminative features for the detection of acute myocardial ischemia are extracted. A classification technique based on support vector machine (SVM) approach operating with linear and radial basis function (RBF) kernels to detect ischemic events by using ST-T derived joint features from non-ischemic and ischemic states of the patients is developed. The dataset is randomly divided into training and testing sets and the training set is used to optimize SVM hyperparameters by using grid-search method and 10fold cross-validation. SVMs are designed specifically for each patient by tuning the kernel parameters in order to obtain the optimal classification performance results. As a result of implementing the developed classification technique to real ECG recordings, it is shown that the proposed technique provides highly reliable detections of the anomalies in ECG signals. Furthermore, to develop a detection technique that can be used in the absence of ECG recording obtained during healthy stage, the detection of acute myocardial ischemia based on ECG recordings of the patients obtained during ischemia is also investigated. For this purpose, a Gaussian mixture model (GMM) is used to represent the joint pdf of the most discriminating ECG features of myocardial ischemia. Then, a Neyman-Pearson type of approach is developed to provide detection of outliers that would correspond to acute myocardial ischemia. Neyman – Pearson decision strategy is used by computing the average log likelihood values of ECG segments and comparing them with a range of different threshold values. For different discrimination threshold values and number of ECG segments, probability of detection and probability of false alarm values are computed, and the corresponding ROC curves are obtained. The results indicate that increasing number of ECG segments provide higher performance for GMM based classification. Moreover, the comparison between the performances of SVM and GMM based classification showed that SVM provides higher classification performance results over ECG recordings of considerable number of patients.

Keywords: ECG classification, Gaussian mixture model, Neyman–Pearson approach, support vector machine

Procedia PDF Downloads 119