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- ItemA Comprehensive Review of Convolutional Neural Networks based Disease Detection Strategies in Potato Agriculture(Springer, 2024-09) Gülmez, Burak; 222298This review paper investigates the utilization of Convolutional Neural Networks (CNNs) for disease detection in potato agriculture, highlighting their pivotal role in efficiently analyzing large-scale agricultural datasets. The datasets used, preprocessing methodologies applied, specific data collection zones, and the efficacy of prominent algorithms like ResNet, VGG, and MobileNet variants for disease classification are scrutinized. Additionally, various hyperparameter optimization techniques such as grid search, random search, genetic algorithms, and Bayesian optimization are examined, and their impact on model performance is assessed. Challenges including dataset scarcity, variability in disease symptoms, and the generalization of models across diverse environmental conditions are addressed in the discussion section. Opportunities for advancing CNN-based disease detection, including the integration of multi-spectral imaging and remote sensing data, and the implementation of federated learning for collaborative model training, are explored. Future directions propose research into robust transfer learning techniques and the deployment of CNNs in real-time monitoring systems for proactive disease management in potato agriculture. Current knowledge is consolidated, research gaps are identified, and avenues for future research in CNN-based disease detection strategies to sustain potato farming effectively are proposed by this review. This study paves the way for future advancements in AI-driven disease detection, potentially revolutionizing agricultural practices and enhancing food security. Also, it aims to guide future research and development efforts in CNN-based disease detection for potato agriculture, potentially leading to improved crop management practices, increased yields, and enhanced food security.
- ItemAn examination of the psychological resilience of preschool children with and without Montessori education(Wiley, 2024-08) Sezgin, Elif; Şener, Tülay; 157389This study aims to compare the psychological resilience of children who receive Montessori education with those who do not receive Montessori education(the group attends a school where education is provided according to the Preschool Education Programme of the Ministry of National Education). The study used the Relational Scanning Model Comparison Types to compare the psychological resilience of children who received Montessori education with those who did not. The research involved 99 children aged 3–6 years who received regular preschool and Montessori education during the 2021–2022 academic year. It is reported that no developmental or neurological defects were observed in any of the participants. The study group comprised 50 children aged 3–6 years from a private kindergarten affiliated with National Education in Nilüfer district and 49 children aged 3–6 years from a private Montessori kindergarten in Nilüfer district. According to the study, children who received Montessori education demonstrated comparatively higher levels of psychological resilience than those who did not receive Montessori education. It has been observed that there exists a weak but meaningful correlation between the psychological resilience of children and their social relationships/social performance, particularly in those who have received Montessori education for an extended duration. As a result, it can be inferred that Montessori education positively impacts children's psychological resilience.
- ItemComparative analysis of different drying methods on strawberry aroma compounds via multi-criteria decision-making techniques(MDPI, 2025-01) Cengiz, Nurten; Abdulvahitoğlu, Aslı; Abdulvahitoğlu, Adnan; 382420Food and food safety, as one of the basic issues of human life, has made it necessary to store foods for a long time with the increasing population. One of the oldest and most common methods of extending the shelf life of food products is the drying process. The drying process contributes to the higher quality of foods in terms of physical, chemical, and microbial properties by ensuring that beneficial contents such as vitamins, minerals, and aroma compounds are better preserved. The aroma values of foods, which consist of taste and smell components, gain importance. In foods, the taste is determined by permanent components, while smell is determined by volatile components. The loss of volatile aroma compounds in the strawberry drying process negatively affects product quality. Small changes in aroma compounds can lead to significant differences in product taste. Therefore, strawberry aroma is a critical factor for consumer appeal and commercial success. In this study, the effects of drying methods on the aroma compounds of strawberry fruit were compared with Multi Criteria Decision Making (MCDM) techniques. In this study, PSI-based MCDM techniques were used to make the most appropriate choice among strawberry drying methods. The values of 23 distinct aroma compounds obtained with different drying methods applied to strawberry fruit were analyzed with 7 different MCDM techniques. The calculations gave similar results and these results were combined with the Borda rule. Accordingly, the drying methods with the highest scores were determined as freeze drying.
- ItemHope and psychological resilience in primary caregivers of patients with a chronic mental illness followed in a community mental health center(Elsevier, 2024-03) Erkuş, Şeyma; Babacan Gümüş, Aysun; 372023Purpose: The aim of this study is to examine hope and psychological resilience in primary caregivers of patients with a chronic mental illness. Design and methods: The descriptive study was conducted on 297 caregivers in community mental health centers in Turkey. Data were collected using the Introductory Information Form, Dispositional Hope Scale and the Resilience Scale for Adults. Findings: Hope and psychological resilience of primary caregivers of patients with a chronic mental illness were moderate. To sociodemographic and caregiver characteristics; caregivers who are over 40 years old, lost his/her spouse, low education level, housewife or retired, unemployed, who evaluated their incomes low, mother, living in the same house with the patient, caring for ten years or more, caring for another patient and not getting help in care had lower hope and resilience levels. Compared to patients with a diagnosis of bipolar disorder, caregivers of patients with schizophrenia had lower hope and psychological resilience levels. Conclusions: Primary caregivers of patients with a chronic mental illness should be supported in terms of hope and psychological resilience.
- PublicationMathematical model to upcycle end-of-roll leftover fabrics in apparel manufacturing(Sage, 2024-06) İşeri, Ali; Kızılaslan, Recep; 135066This study addresses the problem of end-of-roll leftover fabrics originating after the production of baby/child apparel. The ineffective management of these leftovers results in excess inventory, occupies storage space, and imposes economic and environmental loads. To address this challenge, a novel mathematical modeling approach is proposed. The model maximizes the upcycling of leftovers by incorporating these into the manufacturing of garments while adhering to marketing, production, and ordering constraints. This model also introduces the feasibility of ordering new fabrics with a penalty, as defined by the decision makers, to increase utilization. The model was tested using actual end-of-roll leftover data. The upcycling utilization of leftovers was calculated to be between 57% and 87%. Notably, at an upcycling rate of 58%, 96% of the utilized fabrics were sourced from leftovers. The case study results validate the model efficacy and provide insights into leftover-fabric management.
- ItemSelecting facility location of gendarmerie search and rescue (GSR) units; an analysis of efficiency in disaster response(Elsevier, 2024-10) Abdulvahitoğlu, Adnan; Vural, Danişment; Macit, İrfan; 382420Disasters, referred to as events that result in physical, economic, and social losses for individuals and disrupt the daily activities of human communities, necessitate ongoing preparedness due to their unpredictable nature. Swift response during and after a disaster is crucial for preserving human life. Hence, it is imperative to initiate planning immediately following a disaster to ensure readiness for various tasks. Given these factors, search and rescue units must carefully select a base location that enables them to promptly reach affected areas. Disasters exhibit unique characteristics across different regions of Türkiye. While some regions are prone to earthquakes, others face the risks of landslides, avalanches, or floods. Consequently, the required measures for disaster management vary from region to region. Nevertheless, when the term “disaster” is mentioned in Türkiye, earthquakes often come to mind due to their frequent occurrence and significant impact. The Gendarmerie Search and Rescue (GSR) units have been actively responding to these earthquakes, renowned for their exemplary institutional discipline and working methods. This study aims to examine the operations and deployment locations of GSR units, which play a crucial role in mitigating the impact of frequent earthquakes in Türkiye, utilizing a SWOT analysis. Additionally, a Multi-Criteria Decision Making-based mathematical model will be employed to optimize task activities and to select the most suitable facility locations for GSR units. The use of mathematical modeling in this context ensures that GSR units are strategically positioned to maximize their operational effectiveness and minimize response times. The results will be evaluated through sensitivity analysis.
- ItemThe role of nutrition and nutritional supplements in the prevention and treatment of malnutrition in chronic obstructive pulmonary disease: current approaches in nutrition therapy(Springer, 2025-01) Tuna, Tuğba; Samur, Gülhan; 336342Purpose of Review Malnutrition is a significant comorbidity in Chronic Obstructive Pulmonary Disease (COPD), contributing to disease progression and reduced quality of life. This narrative review examines the role of nutritional therapy in the prevention and management of malnutrition in COPD, emphasizing evidence-based approaches and their clinical implications. Recent Findings COPD patients face increased metabolic demands, systemic inflammation, and reduced dietary intake, resulting in muscle wasting, sarcopenia, and cachexia. Recent evidence highlights the efficacy of targeted nutritional strategies, including essential amino acid supplementation, omega-3 fatty acids, vitamin D, and antioxidants, in improving respiratory function, muscle strength, and patient well-being. Comprehensive nutritional assessments and personalized interventions are increasingly recognized as critical components of COPD care. However, long-term efficacy data remain limited. Summary Nutritional therapy plays a pivotal role in managing malnutrition and improving clinical outcomes in COPD. This review synthesizes the latest evidence, identifies gaps in current research, and proposes strategies for integrating personalized nutrition into COPD care. Future studies are needed to establish the long-term benefits of these interventions and to develop tailored nutritional guidelines for COPD patients.
- ItemUtilizing large language models for EFL essay grading: an examination of reliability and validity in rubric-based assessments(Wiley, 2025-01) Yavuz, Fatih; Çelik, Özgür; Yavaş Çelik, Gamze; 131069This study investigates the validity and reliability of generative large language models (LLMs), specifically ChatGPT and Google's Bard, in grading student essays in higher education based on an analytical grading rubric. A total of 15 experienced English as a foreign language (EFL) instructors and two LLMs were asked to evaluate three student essays of varying quality. The grading scale comprised five domains: grammar, content, organization, style & expression and mechanics. The results revealed that fine-tuned ChatGPT model demonstrated a very high level of reliability with an intraclass correlation (ICC) score of 0.972, Default ChatGPT model exhibited an ICC score of 0.947 and Bard showed a substantial level of reliability with an ICC score of 0.919. Additionally, a significant overlap was observed in certain domains when comparing the grades assigned by LLMs and human raters. In conclusion, the findings suggest that while LLMs demonstrated a notable consistency and potential for grading competency, further fine-tuning and adjustment are needed for a more nuanced understanding of non-objective essay criteria. The study not only offers insights into the potential use of LLMs in grading student essays but also highlights the need for continued development and research.
