Sürdürülebilir Kalkınma Amaçları

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• MakaleAçık Erişim2026Scopus SJRQ1/r/gumushane/10619
  YOLOv8 computer vision for automated offside detection in professional football validated through supervised learning

  Abdel-Fattah, Abdul-Rahman; Belhaouari, Samir Brahim; Ceylan, Halil Ibrahim; Bayrakdaroglu, Serdar; Muntean, Raul Ioan; Dhahbi, Wissem; Dergaa, Ismail; Omri, Abdelfatteh El

  Offside calls are integral to maintaining fairness and competitive integrity in football, yet current officiating processes are constrained by limitations in accuracy despite technological advancements. This investigation developed and validated an automated offside detection system using YOLOv8 object detection architecture to address documented limitations of Video Assistant Referee (VAR) systems in offside decision accuracy. Supervised learning validation employed 400 annotated instances from professional match footage. The YOLOv8 medium variant was configured for four-class detection, with a focus on extreme player positions, reducing computational complexity by approximately 70% relative to comprehensive player tracking while accepting accuracy trade-offs in marginal scenarios. The system was optimized for computational efficiency through highly accurate tracking of player positions. Data were partitioned into 40% (n = 160) for training and 60% (n = 240) for testing, with 5-fold cross-validation. The automated system achieved robust performance metrics across 240 test instances: overall accuracy of 83.0%, precision of 85.0%, recall of 87.0%, and F1-score of 86.0%. Confusion matrix analysis revealed true positives (n = 130), true negatives (n = 70), false positives (n = 22), and false negatives (n = 18). Individual case analysis demonstrated 80% agreement with ground truth classifications. System performance significantly exceeded the random classification baseline (p < 0.001). The strategic extreme player tracking approach achieved substantial computational efficiency while maintaining decision accuracy across diverse match scenarios. A YOLOv8-based offside detection system demonstrates proof-of-concept feasibility for decision-support applications in football officiating. Performance (83% accuracy, 95% CI: 79-87%) on 240 test instances remains below professional benchmarks (> 93%), with single-camera constraints and limited dataset size restricting generalizability to proof-of-concept validation rather than operational deployment.

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• MakaleAçık Erişim2026Scopus SJRQ1/r/gumushane/10656
  Comparison of plyometric repeated sprint and plyometric aerobic training on physical performance in youth soccer players

  Selmi, Mohamed Amin; Hammami, Raouf; Ceylan, Halil Ibrahim; Duncan, Michael; Sassi, Radhouane Haj; Morgans, Ryland; Bayrakdaroglu, Serdar; Bragazzi, Nicola Luigi

  High-intensity interval training (HIIT) and repeated-sprint sets (RSS) are established conditioning methods in soccer, yet their integration with plyometric training among highly trained youth soccer players remains underexplored. This study investigated the effects of an 8-week program combining plyometric training with either RSS (PLYO-RSS) or HIIT (PLYO-HIIT) on physical fitness in young soccer players. Twenty-nine male players (14-15 years) were randomly assigned to PLYO-RSS (n = 14) or PLYO-HIIT (n = 15). Both interventions lasted 20 minutes per session and replaced part of regular soccer training. Physical fitness assessments included countermovement jump (CMJ), 15-s repeated vertical jumps (15''RJ), five-jump test (5JT), 10 m and 30 m sprint, maximal aerobic speed (MAS), VO2max, and repeated sprint performance (total sprint time, best sprint, fatigue index). Physiological markers (lactate, rating of perceived exertion, and HRmax) were also monitored. Significant improvements over time were observed in muscle power, sprint speed, aerobic capacity, and repeated-sprint ability (p <= 0.001; eta & sup2;p = 0.339-0.489). However, no main effects or group & times; time interaction effects were observed, indicating no evidence of differential responses between the two training modes. In conclusion, integrating plyometric training with either RSS or HIIT effectively enhances physical fitness in highly trained youth soccer players, offering flexible options for training prescription.

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• MakaleAçık Erişim2026Scopus SJRQ1/r/gumushane/13477
  Serum and hepatic lipid fractions and total protein status of laying hens supplemented with tarragon (Artemisia dracunculus L.) under different stocking densities

  Kaya, Hacer; Karaalp, Musa; Kaynar, Özgür; Elmastaş, Mahfuz

  High stocking density can induce metabolic disturbances in laying hens, particularly in lipid metabolism. This study evaluated the effects of dietary tarragon (Artemisia dracunculus L.) supplementation on serum and hepatic total protein and lipid parameters in laying hens reared under different stocking densities. A total of 192 50-week-old Lohmann Brown laying hens were assigned to a 2 × 4 factorial arrangement with two stocking densities, 5 or 7 hens per cage, and four dietary tarragon treatments providing 0, 1, 5, or 10 mmol/kg feed of tarragon-derived additional antioxidant activity for 8 weeks. Serum total protein concentration was not affected by stocking density but increased with tarragon supplementation, rising from 7.5 to 8.3 g/dL. Liver total protein concentration remained unchanged. SDS-PAGE analysis of pooled treatment-group samples identified 24 serum and 39 hepatic protein bands. High stocking density altered the serum lipid profile by increasing cholesteryl ester, free fatty acid, and acylglycerol proportions, as well as total cholesterol and triacylglycerol concentrations, while decreasing triacylglycerol and phospholipid proportions. Tarragon supplementation increased serum cholesteryl ester and phospholipid proportions and reduced serum triacylglycerol and free fatty acid proportions, together with lower total cholesterol and triacylglycerol concentrations. In the liver, high stocking density increased cholesteryl ester and free cholesterol proportions and triacylglycerol concentration, whereas it decreased triacylglycerol and phospholipid proportions and total cholesterol concentration. Tarragon supplementation increased hepatic cholesteryl ester, free cholesterol, and phospholipid proportions and reduced hepatic triacylglycerol proportion and concentration. Significant stocking density × tarragon-derived additional antioxidant activity interactions were observed for serum free fatty acid and hepatic free fatty acid and free cholesterol. Overall, stocking density had a stronger effect on lipid metabolism than on total protein status.

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• MakaleAçık Erişim2026Scopus SJRQ1/r/gumushane/13464
  The mediating effect of self-compassion and cognitive emotion regulation on the relationship between tolerance and social appearance anxiety in adolescents

  Bingöl, Orhan; Çelebi, Gülin Yazıcı; Kaya, Feridun

  The aim of this study is to examine the effect of tolerance on social appearance anxiety and to test the roles of emotion regulation and self-compassion as mediating psychological mechanisms in this relationship. The sample of the study consists of 647 adolescent individuals living in Turkey. The Personal Information Form, Cognitive Emotion Regulation Questionnaire, Tolerance Scale, Self-Compassion Scale – Short Form, and Social Appearance Anxiety Scale were used in the study. Data were collected online using convenience sampling methods. Pearson correlation analysis was used to determine the relationships between the variables in the study, while regression-based mediation analysis (Process macro model 81) was used to test the mediation model examined in the study. Upon examining the findings, tolerance was positively correlated with self-compassion (r =.323, p <.001) and adaptive cognitive emotion regulation (r =.200, p <.001); while tolerance was negatively and statistically significantly related to maladaptive cognitive emotion regulation (r = -.250, p <.001) and social appearance anxiety (r = -.229, p <.001). Additionally, a positive correlation was found between self-compassion and adaptive cognitive emotion regulation (r =.358, p <.001); and negative and statistically significant relationships between self-compassion and maladaptive cognitive emotion regulation (r = -.576, p <.001) and social appearance anxiety (r = -.530, p <.001). Finally, a statistically significant negative relationship was found between social appearance anxiety and adaptive cognitive emotion regulation (r = -.219, p <.001); and a statistically significant positive relationship was found between social appearance anxiety and maladaptive cognitive emotion regulation (r =.484, p <.001). The mediation analysis, tested with 10,000 bootstrap samples at a 95% confidence interval, revealed that emotion regulation dimensions and self-compassion have a full mediating effect. The findings indicate that the tolerance factor reduces social appearance anxiety not only directly but also indirectly through emotion regulation and self-compassion. In line with these findings, it was concluded that individuals with high tolerance levels need to be supported not only through mindfulness programs but also through emotion regulation and self-compassion levels.

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• MakaleAçık Erişim2026Scopus SJRQ1/r/gumushane/13425
  Machine learning–enabled ECG arrhythmia classification: a systematic and educational study from signal processing to decision support

  Melek, Negin

  Electrocardiogram (ECG) signals play a critical role in the early detection of cardiac arrhythmias, which remain a major cause of morbidity and mortality worldwide. While deep learning approaches have achieved high classification accuracy, their increasing complexity often limits interpretability and practical applicability. This study presents a systematic and interpretable framework for multi-class ECG arrhythmia classification, examining the effects of signal processing, feature extraction, feature selection, and evaluation strategies on classification performance. Experiments were conducted on the MIT-BIH Arrhythmia Database using two feature representations: (i) morphological and temporal features, and (ii) a compact wavelet-based representation. Sequential Forward Feature Selection (SFFS) revealed that classification performance saturates at approximately 15 features, indicating that most discriminative information is captured within a compact subset. Using this feature space, the support vector machine (SVM) achieved the best overall performance, reaching 98.54% accuracy with stable results across different configurations. The wavelet-based representation further improved performance balance, yielding lower Golden Distance (GD) values (as low as 0.0249), indicating more consistent behavior across evaluation metrics. Overall, the results demonstrate that carefully designed feature extraction and selection enable classical machine learning methods, particularly SVM, to achieve high and reliable performance, providing an interpretable alternative to more complex black-box models in ECG arrhythmia classification.

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  AtıfScopus1

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• MakaleAçık Erişim2026Scopus SJRQ1/r/gumushane/13406
  Physicochemical properties of fifteen flower honey samples from five districts in Türkiye

  Ucuncu, Osman; Kul, Merve Kalafat; Baltaci, Cemalettin; Aykoc, Ayse Muslu

  This study analyzed the physicochemical characteristics, mineral composition, and antioxidant potential of fifteen floral honey samples collected from five districts of Gümüşhane, Türkiye. The average values for moisture (17.44 g/100 g), insoluble solids (0.04 g/100 g), conductivity (0.35 mS/cm), diastase activity (54.15 DN), free acidity (38.18 meq/kg), and fructose + glucose content (68.95 g/100 g) were mostly within the acceptable limits defined by national honey standards. Proline content ranged from 562.66 to 1466.15 mg/kg, while hydroxymethylfurfural (0.37–18.89 mg/kg) confirmed the freshness of all samples. Potassium, calcium, sodium, and magnesium were identified as the major mineral elements in the analyzed honey samples, with considerable variation observed among samples collected from different districts. Antioxidant activity (Total phenolic content (mg GAE/100 g): 9.21–98.25; SC₅₀ (mg/mL): 5.23–41.29) revealed a strong antioxidant potential of Gümüşhane honeys. This work provides the first detailed characterization of Gümüşhane honeys, confirming their high physicochemical quality, rich mineral profile, and notable antioxidant potential, and underscores their value as a distinctive regional product with functional and commercial significance.

  AtıfScopus4·WoS5

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• MakaleAçık Erişim2025Scopus SJRQ1/r/gumushane/10320
  FinTech driven green energy transition foreign direct investment and ecological footprint in BRICST countries

  Ayaydin, Hasan; Ergün, Tolga; Barut, Abdulkadir; Erdem, Azad; Pilatin, Abdulmuttalip

  The increasing emphasis on climate change and environmental sustainability worldwide has brought about the convergence and increased focus on financial technologies (FinTech) and green energy initiatives. In light of this, the study's objective is to investigate how FinTech moderates the relationship between the ecological footprint (EF) and green energy transition (GTE) in the BRICS-T nations between 1990 and 2021. This study examines how fintech moderated the GTE and EF in the BRICS-T from 1990 to 2021. We applied the Fully Modified Ordinary Least Squares (FMOLS) and used Dynamic Ordinary Least Squares (DOLS) as the main estimators for longitudinal analysis. In contrast, Driscoll-Kraay was used to verify the robustness of the results under cross-sectional dependence and heteroskedasticity. The results reveal that FinTech indirectly hinders EF by facilitating GTE. The outcomes also show that FinTech significantly constrains EF, while GDP and industrialization worsen EF. The results also confirm the important role of GTE and foreign direct investment (FDI) in reducing CO2 emissions in BRICS-T countries. Lastly, the paper offers policymakers useful recommendations for lowering EF in light of these outcomes. The study suggests establishing appropriate policies and strategies that encourage FinTech platforms to invest in green energy projects, including financial technology, promoting energy-efficient and low-carbon foreign direct investment, and encouraging GTE.

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  AtıfScopus13·WoS12·OpenAlex12

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• MakaleAçık Erişim2025Scopus SJRQ1/r/gumushane/14193
  Snow cover detection using remote sensing techniques over different climate zones of Türkiye

  Çakir, Günay; Bozali, Nuri; Sivrikaya, Fatih

  Snow-covered land surfaces can be easily mapped using remote sensing technologies. Accurate estimation of snow cover on the land surface allows for the construction of water resource management today. Using Landsat TM/ETM + satellite images, this study tried to assess how much snowfall covered the soil in Trabzon, Gümüşhane, and Bayburt provinces between 1999 and 2023. Satellite images were classified into three categories using the ERDAS 9.1 TM software. These classes are classified as snow-covered surfaces, other places, and data loss (cloud-shadow). When performing image analysis, it was important to verify that the cloudiness rate in the images was less than 15%. Images with cloudiness rates of more than 15% were not used. Seasonal and annual trend analysis of snow-covered areas (SCA) over three distinct regions (Trabzon, Gümüşhane, and Bayburt) were examined using the Mann-Kendall test. When three distinct study regions were examined together, Bayburt had the highest SCA rate, followed by Gümüşhane and Trabzon. In all three fields, the highest SCA was recorded in 2000, while the lowest SCA was recorded in 2017. The trends noticed that SCA on both annual and seasonal scales did not reach the statistical significance level of 0.05. Although snowfall in Trabzon, Gümüşhane, and Bayburt was beneficial in the autumn and spring seasons, no statistically significant association was found. The research concluded that the existing data are inadequate to make any statements on the impact of global warming in the area. However, the study figured out that satellite data may be effectively used to identify snowy places as a result of the study. Comparable investigations need to be undertaken in regions with varying climates, utilizing diverse remote sensing data and classification methodologies.

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  AtıfScopus2·WoS3·OpenAlex3

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• MakaleAçık Erişim2025Scopus SJRQ1/r/gumushane/13748
  A novel q-ROHFS prospect theory based MABAC method for failure mode risk prioritization in aircraft landing systems

  Köseoğlu, Ali; Altun, Fatma; Şahin, Rıdvan

  Failure mode risk prioritization is crucial in aircraft landing systems, where undetected or misjudged failures can lead to catastrophic outcomes. Effective risk analysis enables proactive maintenance and enhances aviation safety in such critical phases of flight. In this study, a novel hybrid decision-making framework is proposed to prioritize failure modes in aircraft landing systems by integrating the Multi-Attributive Border Approximation Area Comparison (MABAC) method with Prospect Theory under a q-Rung Orthopair Hesitant Fuzzy Set (q-ROHFS) environment. Traditional failure modes and effects analysis (FMEA) approaches often suffer from rigid weighting schemes, lack of sensitivity to expert hesitancy, and an inability to incorporate psychological factors such as risk aversion or subjective evaluations—especially in high-risk domains like aviation. To address these limitations, the proposed model incorporates human psychological behaviour and uncertainty in expert assessments. Prospect Theory is employed to capture decision makers’ risk attitudes and reference-dependent evaluations, while q-ROHFSs allow more flexible and comprehensive representation of hesitant and uncertain information. In this approach, Best-Worst Method (BWM) is used to determine the relative importance of risk factors for each decision maker, and their individual weights are obtained using TOPSIS-based similarity measures. A novel generalized q-ROHF Minkowski distance measure is also introduced and implemented to determine the weights of decision makers in the TOPSIS method, as well as to construct the prospect decision matrix and the distance matrix in the MABAC method, thereby enhancing computational precision. The applicability and effectiveness of the proposed method are demonstrated through a real-world case study on aircraft landing systems, and a sensitivity analysis is conducted to validate the robustness of the results. The findings highlight the method’s capability to reflect expert preferences more realistically and improve risk prioritization decisions in complex safety-critical systems.

  AtıfOpenAlex1

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• MakaleAçık Erişim2025Scopus SJRQ1/r/gumushane/13741
  The role of cognitive flexibility and psychological well-being in the effect of mindfulness on problematic internet use

  Yazıcı Çelebi, Gülin; Güngör, Sunay; Kaya, Feridun

  With the widespread use of digital technologies today, the Internet has become an indispensable part of life but has also led to negative outcomes such as problematic internet use in some individuals. Problematic internet use is seen as a critical risk factor that negatively impacts individuals’ academic, social, and psychological functioning. Research has presented a lot of evidence in recent years that psychological resources, such as mindfulness, cognitive flexibility, and psychological well-being, play a noteworthy role in protecting individuals against such risky behaviors. This study aimed to examine the chain (serial) mediation roles of cognitive flexibility and psychological well-being in the effect of individuals’ mindfulness on problematic internet use. The majority of the participants in this study, using a cross-sectional, correlational design, were female (73.1%), their socio-economic level was moderate (70.4%), and their mothers (69.6%) and fathers (52.3%) had secondary school education. It was found that the majority of the participants used the Internet for 2–4 h a day (44.2%). Participant age ranged between 18 and 26 (Mean = 19.16, SD = 1.52). Data were collected using a Personal Information Form, the Mindfulness Scale, the Cognitive Flexibility Inventory, the Psychological Well-Being Scale, and the Problematic Internet Usage Scale. When the research findings were examined, it was found that mindfulness had a positive significant relationship with cognitive flexibility and psychological well-being. Negative significant relationships were observed between problematic internet use and mindfulness, cognitive flexibility, and psychological well-being. When the mediation analyses of the study were examined, it was determined that both cognitive flexibility and psychological well-being had mediation roles in the relationship between mindfulness and problematic internet use. In addition, it was revealed that cognitive flexibility and psychological well-being had a chain (serial) mediation role in the relationship between mindfulness and problematic internet use. It was determined that as the mindfulness levels of individuals increased, their cognitive flexibility and psychological well-being levels increased, too. On the other hand, it was observed that having high levels of mindfulness, cognitive flexibility, and psychological well-being decreased problematic internet use levels. In addition to these results, it was found that the relationship between mindfulness and problematic internet use was mediated by cognitive flexibility and psychological well-being. The findings obtained from the research were discussed in light of the literature, and various suggestions were made.

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  AtıfScopus8·WoS7·OpenAlex10

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