Sürdürülebilir Kalkınma Amaçları

• 1
• 1

Yazarlar

• Aljobair, Moneera O.(1)
• Arpa Zemzemoglu, Tuba Eda(1)
• Gürfidan, Remzi(1)
• Kilim, Oguzhan(1)
• Mohamed Ahmed, Isam A.(1)
• Reis, Hatice Catal(1)
• Tokatli Demirok, Nazan(1)
• Tokatli, Nazli(1)
• Turk, Veysel(1)
• Türkol, Melikenur(1)
• Yikmis, Seydi(1)
• Yinanç, Abdullah(1)

• MakaleYalnız künye2026Scopus SJRQ1/r/gumushane/13913
  Efficient ensemble learning with multi-scale fusion based deep neural network for skin lesion classification

  Reis, Hatice Catal; Turk, Veysel

  Melanoma, a type of skin cancer, is a severe skin cancer that is critical for early diagnosis but difficult to detect. Deep learning is promising in melanoma diagnosis because it can automatically analyze visual features and perform end-to-end learning. However, achieving the optimum balance between performance and computational efficiency for the effective use of these models in clinical applications is an important research topic. In this study, three innovative methods are proposed for skin cancer detection: PADSCNet, P-DEFF, and M–DEFF. The PADSCNet is an effective neural network developed with CNN and multi-head attention techniques, designed with fusion methods, and stands out with its minimum number of parameters despite being quite deep. The P-DEFF and M–DEFF are based on ensemble learning techniques; P-DEFF was developed with a single deep learning model, and M–DEFF was developed with multiple pre-trained deep learning models. The proposed approaches were tested on the Skin Cancer: Malignant vs. Benign dataset, which was pre-processed using image enhancement techniques. According to the experimental results, PADSCNet achieved accuracy rates of 88.12 %, P-DEFF 93.75 %, and M–DEFF 95.00 %. In additional experiments conducted with the PADSCNet model, 93.12 % accuracy rates were achieved in the CNN for Melanoma Detection Dataset, and 95.00 % accuracy rates were achieved in the PH2 dataset. These findings show that the proposed methods are effective in skin cancer detection and can achieve successful results in clinical applications.

  • 
  AtıfScopus4·WoS3·OpenAlex4

  İncele
• MakaleAçık Erişim2026Scopus SJRQ1/r/gumushane/10348
  Thermosonication improves the bioactive properties and in vitro bioaccessibility of broccoli juice through integrated RSM and metaheuristic optimization

  Arpa Zemzemoglu, Tuba Eda; Tokatli Demirok, Nazan; Türkol, Melikenur; Gürfidan, Remzi; Kilim, Oguzhan; Tokatli, Nazli; Yikmis, Seydi; Mohamed Ahmed, Isam A.; Aljobair, Moneera O.; Yinanç, Abdullah

  Broccoli juice is highly nutritious, containing phenolic compounds, chlorophyll derivatives, antioxidants, and other biologically active phytochemicals; however, conventional thermal processing may reduce their stability and bioaccessibility. The aim of this study was to analyse the impact of thermosonication on the following properties of broccoli juice: bioactivity, antioxidant capacity, phenolic profile and in vitro bioaccessibility. Thermosonication conditions were optimized using Response Surface Methodology (RSM) integrated with the Gray Wolf Optimizer (GWO) and Particle Swarm Optimization (PSO) algorithms. Broccoli juice samples were subjected to conventional pasteurization and thermosonication under different processing conditions, and total chlorophyll, ascorbic acid (AA), ferric reducing antioxidant power (FRAP), total phenolic content (TPC), and individual phenolic compounds were evaluated. Digestive stability and post-digestion bioaccessibility were also assessed using a standardized in vitro gastrointestinal digestion model. The developed quadratic models exhibited high statistical significance for TPC and FRAP responses (p < 0.001), with coefficients of determination (R2) of 0.9949 and 0.9853, respectively. The optimum thermosonication conditions were identified as 40 degrees C, 6.75 min, and 64.04% amplitude, under which experimentally validated FRAP and TPC values reached 12.86 mmol TE/L and 149.77 mg GAE/100 ml, respectively. HPLC-DAD analysis showed that gallic acid and naringin were the pre-dominant phenolic compounds, and that thermosonication promoted greater phenolic retention than conventional pasteurization. In vitro digestion results demonstrated that thermosonicated broccoli juice maintained significantly higher levels of TPC, FRAP, chlorophyll, and AA throughout gastrointestinal digestion, with higher TPC recovery (30.45%) than pasteurized samples (26.22%), indicating improved post-digestion bioaccessibility of phenolic compounds. Similar improvements were observed for antioxidant capacity and chlorophyll retention. Furthermore, PSO and GWO optimization results showed strong agreement with RSM predictions, confirming the robustness of the proposed optimization strategy. Overall, thermosonication was shown to effectively and sustainably enhance the functional quality, antioxidant properties, phenolic stability, and digestive bioaccessibility of broccoli juice.

  • 
  AtıfScopus1·WoS1·OpenAlex1

  İncele