Bölüm & Birim & Kişi

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    Art Therapy to Control Nail Biting Using a Cognitive Behavioral Approach Through New Innovative Game and Animation
    (Springer Nature, 2024) SHABANI, SEVİL MOMENİ; Darabi, Fatemeh; Azimi, Ahad; Nejaddagar, Nazila; Vaziri, Keyvan; Shabani, Masoud
    Background: Nail biting is categorized as a habitual behavior, commonly observed in children and occasionally in adults. This disorder occurs unconsciously, with individuals often unaware of their behavior. Since there are physical and psychological complications and quality of life problems in nail -biting, addressing this problem is very important and there are many theories in support of art therapy including: psychodynamic; humanistic (phenomenological, gestalt, person centered); psycho-educational (behavioral, cognitive behavioral, developmental); systemic (family and group therapy); as well as integrative and eclectic approaches. Art therapy, applied through various methods, serves as a strategy for habit modification. This study evaluates the impact of art therapy as a game and animation on controlling nail biting. Methods: The research was conducted as a single-group clinical trial, assessing participants before and after the intervention without a control group. The sample size was 14 participants, picked by the convenience technique. All students were referred to a counseling service center for nail-biting management. Seven girls and seven boys aged 9–12 participated in this study. Initially, the children were medically examined to confirm their physical well-being. Subsequently, assessments were made regarding parenting styles and anxiety levels, followed by baseline measurements and documentation of nail-biting frequency prior to the counseling intervention. Considering the importance of family support in empathizing with the child and the role of loneliness and anxiety in nail biting, two questionnaires (Goodenough’s Draw-a-Man Test and Baumrind’s Parenting Style Inventory) have been used for this study. A game and animation that increases self-awareness skills and reveals the cognitive error of the false pleasure of nail biting for the child, as well as alternative preventive behaviors are used in this study. Parents and children were then instructed as to how to use the new games and animations created for this purpose as part of the counseling sessions to address nail biting. The frequency of nail biting was monitored throughout the study, and finally, the data were subjected to a statistical analysis. It should be said that not having a control group in this research is one of the limitations of the study. Results: The results indicated a remarkable improvement in nail biting frequency following the introduction of the games, demonstrating a significant reduction in the behavior. The findings showed that the total number of times of nail biting in the group increased from 149 times a day at the beginning of the study to 20 times a day at the end of the intervention, and it actually shows an 86 percent decrease in the habit of nail biting in the group. Conclusion: Given the effectiveness of the art therapy intervention in curbing nail biting, it is recommended that future research be conducted as a controlled clinical trial with parallel groups and a larger sample. Additionally, at the beginning of studies related to art therapy and habitual behavioral disorders, it is better to measure children’s life skills, including self-awareness, problem-solving skills, and creative thinking. Dealing with various tools and methods of art therapy in a comparative manner is another research need in the future because it provides a suitable structure for digital and internet-based services and finally artificial intelligence in this field. © The Author(s) 2024.
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    Detecting Phishing Websites Using Machine Learning
    (Institute of Electrical and Electronics Engineers Inc., 2022) ALREFAAI, SAFA; ÖZDEMİR, GHINA; MOHAMED, AFNAN
    Phishing, a cybercriminal's attempted attack, is a social web-engineering attack in which valuable data or personal information might be stolen from either email addresses or websites. There are many methods available to detect phishing, but new ones are being introduced in an attempt to increase detection accuracy and decrease phishing websites ' success to steal information. Phishing is generally detected using Machine Learning methods with different kinds of algorithms. In this study, our aim is to use Machine Learning to detect phishing websites. We used the data from Kaggle consisting of 86 features and 11,430 total URLs, half of them are phishing and half of them are legitimate. We trained our data using Decision Tree (DT), Random Forest (RF), XGBoost, Multilayer Perceptrons, K-Nearest Neighbors, Naive Bayes, AdaBoost, and Gradient Boosting and reached the highest accuracy of 96.6using X G Boost. © 2022 IEEE.
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    Increased Femoral Anteversion May Not Cause Hip Abductor Muscle Weakness During Walking
    (Elsevier Ireland Ltd., 2023) APTİ, ADNAN; AKALAN, NAZİF EKİN; KUCHIMOV, SHAVKAT; Temelli, Yener
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    Optimal Energy Consuming on Spraying an Agricultural Field by Using Multiple UAVs
    (Springer Science and Business Media Deutschland GmbH, 2022) GÜZEY, ALPARSLAN; Akıncı, Mehmet Mutlu; Mehmet Güzey H.
    Recently, agricultural areas are decreasing day by day in the face of the constantly increasing population. As a result, it is inevitable that existing production techniques are made much more efficient. In this study, starting from this point, it was aimed to spray the spraying areas of the pre-determined targets in the agricultural land of autonomous unmanned aerial vehicles in communication with each other with time minimization. For this purpose, two scenarios were compared on how to use the drones in the stations placed in all four corners of the field in the most effective way. In the first scenario, the field is divided into four equal parts in a classical way. In the second scenario, the field was divided into 2–4 regions by using the k-means method according to the areas to be sprayed. The route that the drone will use in spraying has been analyzed using the segmental method developed for the traveling salesman problem. For calculations, Julia programming language was used. Each scenario has been examined 100 times for different number of spraying sites. In light of the results obtained, it was found that the k-means method improved the flight time by an average of 19% compared to classical segmentation. In addition, with the developed method, unnecessary flight times of drones were prevented, and their useful lives were extended by finding which stations should be used the least in different situations. © 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.