Sürdürülebilir Kalkınma Amaçları
Yazarlar
- Ateşşahin, Tuncay(1)
- Cigerci, Ali Erdem(1)
- Cömert, Zafer(1)
- Doğan, Gürkan(1)
- Dürrani, Syeda Zahra(1)
- Dürrani, Ömerhan(1)
- Ergen, Burhan(1)
- Genç, Harun(1)
- Gündogdu, Serhat Dogu(1)
- Gürses, Veli Volkan(1)
- Imak, Andaç(1)
- Kizar, Oktay(1)
- Polatcan, Ismail(1)
- Sengur, Abdulkadir(1)
- Tekin, Irem(1)
- Türkmen, Mustafa(1)
- Türkoğlu, Muammer(1)
- Ökmen, Mehmet Serif(1)
- İmak, Andaç(1)
- İşgüzar, Seda(1)
Yayınlar
- MakaleYayıncıda açık erişim2026Scopus SJRQ1Effects of 8-week plyometric training program on balance, reaction time, and attention on elite adolescent female taekwondo athletes
Genç, Harun; Türkmen, Mustafa; Tekin, Irem; Cigerci, Ali Erdem; Gürses, Veli Volkan; Kizar, Oktay; Ökmen, Mehmet Serif; Polatcan, Ismail; Gündogdu, Serhat Dogu
Introduction: Taekwondo is a complex combat sport requiring high levels of strength, balance, reaction time, attention, agility, and endurance for effective performance under rapid offensive and defensive conditions. This study aimed to investigate the effects of an 8-week plyometric training program on static balance (SB), dynamic balance (DB), reaction time (RT), and attention (AT) in adolescent female taekwondo athletes. Methods: Twenty female athletes (age: 14.85 +/- 1.53 years; height: 162.27 +/- 7.12 cm; body mass: 56.69 +/- 6.45 kg) voluntarily participated in the study at Mardin Halit Demir Martial Arts Club. Participants were randomly assigned to either an experimental group (EG, n = 10) or a control group (CG, n = 10). The EG performed plyometric training twice weekly for 8 weeks in addition to regular taekwondo training, while the CG continued only taekwondo training. Static balance was defined as the primary outcome, whereas dynamic balance, reaction time, and attention were considered secondary outcomes. A 2 & times; 2 repeated-measures analysis of variance (group & times; time) was used to examine intervention effects. Results: Significant group & times; time interactions were observed for static balance and dynamic balance (p < 0.05), favoring the experimental group. However, no significant group & times; time interactions were found for reaction time or attention (p > 0.05). Discussion: These findings suggest that plyometric training may effectively improve balance performance in adolescent female taekwondo athletes, particularly static and dynamic balance. However, no significant effects were observed for reaction time or attention. Further studies with larger sample sizes are needed to clarify the potential effects of plyometric training on cognitive performance.
- MakaleAçık Erişim2025Scopus SJRQ2HASK-Net: new hybrid attention selective kernel network for automatic colon cancer detection from colonoscopy images
Imak, Andaç; Doğan, Gürkan; Sengur, Abdulkadir; Ergen, Burhan
Colorectal cancer is a frequently analyzed cancer type seen today. It is the third leading of cancer in terms of incidence. It is among the second leading cases resulting in death. However, when detecting pre-cancerous polyps using traditional methods, the rate of being overlooked is high. Therefore, the rate of missed polyps can be greatly reduced with deep learning-based computer-aided diagnosis (CADx) methods. In this study, a novel convolutional neural network based on CADx, called HASK-Net, is proposed for automatic polyp detection. While HASK-Net uses ResNet50 as a feature extractor in the encoder network, the novely designed hybrid attention selective kernel convolution uses it in the decoder network to increase the representation power in feature maps and learn more complex features. In experimental results on the publicly available Hiper-Kvasir and EndoTech 2020 benchmark datasets, HASK-Net showed extremely promising performance with a dice similarity score of 97.02% and 84.83% and an mIoU score of 95.38% and 84.32%, respectively.
- MakaleAçık Erişim2025Scopus SJRQ1MobileNet- and attention-based MLP-Mixer architecture for geographical-region recognition of a marine fish (Perciformes: Carangidae) using otolith images
Dürrani, Ömerhan; İşgüzar, Seda; İmak, Andaç; Ateşşahin, Tuncay; Cömert, Zafer; Dürrani, Syeda Zahra; Türkoğlu, Muammer
Fishery management is crucial to sustain marine ecosystems by preventing overfishing and ensuring a fair distribution of fishing quotas. Accurately identifying the geographical origins of fish stocks is a key challenge in region-specific management strategies. Otoliths, calcified structures found in the heads of all fish species (except sharks and rays), provide insights into the life history and geographical origins of these fish. Traditional otolith analysis is time-consuming and error-prone because of manual inspection. Our study presents a novel approach using deep learning and computer vision to automate the geographical recognition of fish using otolith images. We propose a model that integrates MobileNet, which is known for its efficiency, with an advanced Mlp-Mixer that incorporates an attention mechanism to extract enhanced features. When tested on a diverse dataset of otolith images from five regions, the proposed model achieved a remarkable 96% accuracy, significantly outperforming traditional methods. This high accuracy demonstrates the potential to revolutionise fishery management by providing a fast, reliable, and automated solution for geographical region identification. In conclusion, the proposed method demonstrates the transformative potential of combining MobileNet and an attention-based Mlp-Mixer for automated fish geographic recognition using otolith images. This innovative method addresses the limitations of traditional manual inspection and paves the way for more effective and sustainable fishery management practices.
AtıfScopus4OpenAlex4
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