https://turkishstudies.net/appliedsciences?mod=sayi_detay&sayi_id=1283 Turkish Studies-Information Technologies and Applied Sciences en 2024-08-29 Ankara Bilim Üniversitesi https://turkishstudies.net/appliedsciences?mod=makale_tr_ozet&makale_id=46162 https://turkishstudies.net/appliedsciences?mod=makale_tr_ozet&makale_id=46162 Yüksel BALABANİpek Fatma ÇEVİK Animation, which progressed in parallel with the development of technology, has had an unlimited usage area with the widespread use of the Internet as well as technological devices. On the other hand, in online broadcasting areas such as social media channels and search engines on the Internet, different animation types have started to be preferred in order to attract the attention of users and keep them on the page for longer. GIFs, which find their place in Doodle and social media channels on the Google search engine, are animation types prepared with different techniques that can be handled in this framework. In this study, Doodle and GIFs have been compared and analyzed in terms of different aspects. The differences and similarities of the two genres were tried to be determined with the method of content analysis in line with the determined categories. First of all, the development of the Internet, the stages through which it has come up to the present, is mentioned. Afterwards, the content and history of GIF and Doodle studies that form the subject of your study are mentioned. In the analysis part of the study, content analysis was used in line with the samples determined. In this direction, different categories have been determined and sub-categories of these categories have been created and the studies have been analyzed accordingly. GIFs, which are older and traditional in the web world, are more widely known, however, Doodle studies reach a large number of people thanks to the Google search engine, which has many users today. It has been concluded that although GIFs and Doodles contain similarities, they are also very different from each other in terms of aspects such as their functions and the platforms on which they are broadcast. 2024-08-29 https://turkishstudies.net/appliedsciences?mod=makale_tr_ozet&makale_id=46268 https://turkishstudies.net/appliedsciences?mod=makale_tr_ozet&makale_id=46268 İbrahim Hakan DÖNMEZFeyyaz FIRAT , Hasan YURDAKUL This article has been retracted. 2024-08-29 https://turkishstudies.net/appliedsciences?mod=makale_tr_ozet&makale_id=46202 https://turkishstudies.net/appliedsciences?mod=makale_tr_ozet&makale_id=46202 Berkant DULKADİR Coronavirus, which is called Covid19 and turned into an epidemic disease, is spreading rapidly because it appeared in Wuhan, China in December 2019. Coronavirus is an infectious virus with syndromes such as fever, shortness of breath and cough by causing infection with the respiratory tract. The virus spreads quickly and easily with person-to-person contact through the respiratory tract and has been declared a global epidemic by the World Health Organization, except for serious dangers. All kinds of measures to prevent the epidemic, others to apply for remote work in business life to prevent the epidemic. Effective use of various information technology tools for businesses to work remotely with the application. At the beginning of applications using information applications for the activities of the enterprises. It is defined as the information technology that has enabled the information to be presented in the most appropriate way by processing it with various analyzes. Information technologies are more important in teleworking. In this process, businesses will draw a planned roadmap to see the progress of information technologies and to eliminate the deficiencies in order to carry out their activities. The research was conducted to investigate in the Covid19 epidemic, together with the effects of the use of information technology tools in businesses operating with the remote working process. When the data obtained for the questionnaire are analyzed, the importance of information technologies has emerged once. Various evaluations were made and recommendations were made based on the results of the research. 2024-08-29 https://turkishstudies.net/appliedsciences?mod=makale_tr_ozet&makale_id=46708 https://turkishstudies.net/appliedsciences?mod=makale_tr_ozet&makale_id=46708 Sevda GÖKTEPE YILDIZSeda GÖKTEPE KÖRPEOĞLU Game theory has many implementations such as economics, statistics, engineering and computer sciences especially artificial intelligence. In the present study, it has been implemented in the educational technology field. The aim of this study is to compare some features of two mathematics courses that include and not include the use of Smart Board Technology (SBT) via game-theoretical analysis. For this purpose, to form the mathematical game model and to formulate the solution, the data are obtained from the answers of elementary mathematics pre-service teachers to the data collection tool. The questionnaire developed by the researchers as a data collection tool consists of 15 items and is in a 5-point Likert type. According to the answers to the questionnaire, a mathematical game problem is established. The problem is a zero-sum game problem presenting the situation of two mathematics courses conducted in different ways, which are considered as rival to each other. Thirty-eight pre-service mathematics teachers from a public university in Turkey participate in the research. This research has a quantitative nature and is a descriptive study. Results reveal that the usage of SBT is more superior in terms of student features than mathematics lessons exclude the SBT. Namely, teaching with SBT is advantageous in terms of being funny, drawing attention, ensuring retention, being clarity and suitability for group study. It is hoped that this study will shed light on future research in terms of setting an example for the use of game theory in educational research and determining the positive and negative opinions of pre-service mathematics teachers about the use of smart board technology in their lessons. 2024-08-29 https://turkishstudies.net/appliedsciences?mod=makale_tr_ozet&makale_id=47238 https://turkishstudies.net/appliedsciences?mod=makale_tr_ozet&makale_id=47238 Aslan GÜLCÜAli Babapour GOLEZANİ The purpose of this research; Turkey and Iran 10th grade students is to examine the impact of second-order equations units within the scope of the Dynamic Mathematics Learning Objects (DMLO), designed by the 5E learning model of student academic achievement, participation and attitudes in mathematics lessons. In both countries, open-ended interviews were conducted with 28 students in order to determine their views on the effect of mathematics teaching with DMLO’s on students' academic achievement. In addition, the internationalization of education within the scope of Turkey and Iran, considering the conditions of 10th grade students in math classes dlmo of the impact on the use of students were compared. Research; It was carried out in the content analysis and descriptive analysis pattern in qualitative research techniques. The participants of the study in the province of Tabriz in Iran Mehdi Salek Shaheed High School and 28 students from Erzurum in Turkey consisted of 28 students from Mehmet Akif Ersoy High School. In the study, the open-ended questionnaire form (in Persian and Turkish) prepared for the students and the daily observation reports prepared by the researcher were used to collect qualitative data. In the study, notes were taken by observing how students used dynamic mathematics learning objects, their interest and enthusiasm, and reactions for observation reports. Descriptive analysis method was used to interpret the observation reports. Looking at the results of the study; Both countries (Turkey and Iran) 10th grade students in their math classes as a result of the use of DMLO, academic achievement, attitudes and attendance appeared to be affected in a positive way. 2024-08-29 https://turkishstudies.net/appliedsciences?mod=makale_tr_ozet&makale_id=45993 https://turkishstudies.net/appliedsciences?mod=makale_tr_ozet&makale_id=45993 Mustafa Berk KELEŞAytürk KELEŞ , Ali KELEŞ Today, passengers can compare flights of different airline companies, find the most convenient flight in a certain time period, reserve and purchase, thanks to advances in internet technologies. Revenue policies of airlines and competition between them, seasons, holidays, time left to flight, number of seats available, tax policies of countries, travel policies between countries, etc. Many factors are effective in determining flight prices. At the same time, even the price of a ticket for the same flight can change within hours. Therefore, it is very important for airline companies and customers to be able to predict the ticket prices, which are so variable and dynamic. Today, many online travel agencies and airline companies collaborate on AI-focused Research&Development studies on dynamic price prediction. This study is part of the AI-supported "Flight Prices Predictor" project conducted by the Enuygun.com R&D Center. In this part of the the project, machine learning algorithms, which are one of the AI technologies, have been researched and two different prediction models have been developed by using Gradient Boosting (GB-Gradient Boosting) and Random Forest (RF-Random Forest) algorithms. The accuracy performances of "RF-FPPredictor" and "GB-FPPredictor" models, which were developed and tested using Gradient Boosting and Random Forest algorithms, are 90% and 92% respectively. The average absolute percentage errors (MAPE) of the models are 2.49% and 2.26%. These models are quite successful when compared with other models developed before in terms of prediction performance. 2024-08-29 https://turkishstudies.net/appliedsciences?mod=makale_tr_ozet&makale_id=46246 https://turkishstudies.net/appliedsciences?mod=makale_tr_ozet&makale_id=46246 Özge DOĞUÇ Epidural hematoma (EAH) is the accumulation of blood in the space between the outer membrane of the brain (dura mater) and the bone. Acute subdural and epidural hematoma appears on CT scan as a hyper-dense collection often located in brain convexity. Such bleeding can become fatal by increasing intracranial pressure and creating a mass effect. Therefore, it is very important to recognize these bleedings promptly in an emergency trauma setting. Thus, early diagnosis is essential to reduce mortality and morbidity rates in these cases. There has been a growing interest in artificial intelligence (AI) and machine learning (ML) algorithms for diagnostics in medical fields. In this study, a supervised learning method was used in which the decision tree ML algorithm is trained with the patients' statuses (EAH or Normal). This study proposes an early warning system (EWS) that scans all cranial CTs obtained at the trauma center. The EWS in this study, trained with CT scans from about 100 patients, can predict EAH with 100% accuracy using image recognition and supervised learning algorithms. Each MR section obtained for each patient is individually analyzed by image processing and EAH detection is made. For this, the decision tree method, which is a supervised learning algorithm, was trained and used to detect EAH in MR sections. The algorithm has been developed in such a way that it will immediately alert the emergency physician and consultant neurosurgeon by e-mail when it detects EAH in more than 10 sections in any patient. 2024-08-29 https://turkishstudies.net/appliedsciences?mod=makale_tr_ozet&makale_id=46011 https://turkishstudies.net/appliedsciences?mod=makale_tr_ozet&makale_id=46011 Devrim ÜNAY Automatic quality control of food and agricultural products is a challenging problem that needs to be solved accurately, quickly and objectively due to the high quality and safety standards of the sector. The solution to this problem requires automatic classification of products prior to quality control. Based on this need, this study focuses on the problem of automatic classification of fruits and vegetables with the help of machine vision. For this purpose, the classification performance of popular deep learning architectures AlexNet, Vgg16, GoogLeNet, ResNet18, ResNet101, SqueezeNet and ShallowNet were examined using the original and distorted versions of a publicly available data set where the latter include applying Gaussian noise, random noise, and brightness changes. In the study, the performances of deep learning architectures were evaluated with accuracy, precision, sensitivity, F-score and run time with a cross-validation methodology using a personal laptop computer and Matlab. Experimental results have shown that ShallowNet with its low network depth and simple architecture achieves reasonable performances and is more robust to distortions, while SqueezeNet emerges as a promising solution especially in the absence of severe distortions with its high accuracy levels above 80% and low number of trainable parameters. It has also been observed that the GoogLeNet architecture is more robust to Gaussian noise, the Resnet101 architecture to salt and pepper noise, and the SqueezeNet architecture to brightness changes. Repeating the experiments with a larger data set containing more fruit and vegetable categories in the future is important and necessary both to test the validity of the above inferences and to offer a more realistic machine vision solution to the industry. 2024-08-29