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International Symposium for Production Research
No full textPart of the book series: Lecture Notes in Mechanical Engineering ((LNME)).Within the domain of inbound logistics, the express air cargo transportation sector has become an essential component of global trade. As the disparity between actual demand and forecasted demand in express cargo transportation widens, the potential for resource wastage correspondingly increases due to the unpredictability of volume and weight. Therefore, this study aims to forecast the daily quantity and weight of incoming cargo, categorized by type, within the context of inbound logistics. Utilizing a case study of express cargo transportation in Turkey, we employ both Long Short-Term Memory (LSTM) and Seasonal Autoregressive Integrated Moving Average (SARIMA) models to compare the forecasting performance of the LSTM approach. In the LSTM model, the maximum epoch, batch size, number of neurons and optimizer parameters are adjusted using grid search to reduce the prediction error. This forecasting capability enables businesses to better prepare for sudden fluctuations in incoming shipments and provides a methodological and analytical framework that influences daily operations. Additionally, we seek to contribute to the existing literature on operational planning by developing a model capable of generating daily forecasts, as opposed to traditional forecasting models that operate on different temporal scales. The numerical results indicate that the improved LSTM model outperforms the SARIMA model for all data sets
Test-Retest Reliability and Concurrent Validity of the One-Minute Sit to Stand Test in Children and Adolescents Who are Overweight or Obese
No full textAims: To assess test-retest reliability and concurrent validity of the 1-min sit-to-stand test (1-minSTST) in children and adolescents who are overweight or obese. Methods: Thirty-nine overweight and obese children and adolescents were included. The 1-minSTST was administered twice with a one-hour break. Concurrent validity was evaluated by assessing correlations between 1-minSTST repetitions and six-minute walk test (6MWT) distances. The cardiorespiratory measures (blood pressure, heart rate, oxygen saturation, respiratory rate, dyspnea, and perceived fatigue) were recorded before and after each test. Results: Test-retest reliability was excellent (ICC: 0.90, 95% confidence interval 0.90–0.97). There was no relationship between scores on the 1-minSTST and 6MWT (r = –0.06, p = 0.71). No statistically significant correlation was found between scores on each test and change in cardiorespiratory responses, except for respiratory rate (r = 0.43, p = 0.006). Change in cardiorespiratory responses was similar when performing each test (p > 0.05). Conclusion: While the 1-minSTST seems promising, it is not significantly related to the 6MWT, indicating they may assess different dimensions of fitness in this population. Further investigations are needed to determine the clinical implications of 1-minSTST outcomes in pediatric population
Yabancı Dil Olarak Türkçe Öğrenen Öğrencilerin Üretici Söz Varlığının Geliştirilmesi Üzerine Bir Eylem Araştırması
No full textBu çalışma, nitel araştırma yöntemlerinden eylem araştırması ile gerçekleştirildi. Çalışma Mısır'ın başkenti Kahire'deki El Ezher Üniversitesi Tercüme ve Diller Fakültesi Türk Dili ve Edebiyatı Bölümü'nde öğrenim gören 3. ve 4. sınıf A2 seviyesindeki 12 kişilik bir katılımcı grubunun katılımıyla gerçekleştirildi. Çalışma 2021-2022 öğretim yılı güz yarı yılında hafta içi her gün ikişer ders saati olarak icra edildi ve 6 aylık bir süreyle sınırlı tutuldu. Çalışma gerçekleştirilirken Corona Virus salgını nedeniyle yüz yüze çalışma yapmak için katılımcı bulunamadığı için bilgisayar üzerinden Zoom adlı görüşme programı kullanılarak sanal ortamda gerçekleştirildi. Katılımcılar defter, kalem ve kitap gibi öğretim malzemeleri kullanmadılar. Katılımcılara uygulama dışında yapmaları gereken ev ödevi verilmedi. Sadece uygulama sırasında araştırmacı tarafından görsellerle desteklenen kısa masallar, kısa anlatım metinleri, kısa öyküler ve benzeri özgün öğretim malzemeleri kullanıldı. Bu malzemeler, katılımcıların üretici söz varlıklarını artırmak ve konuşma becerilerini geliştirmek amacıyla seçildi. Görselli destekleme, öğrenme sürecini daha etkili hale getirerek katılımcıların dikkatini çekmeyi ve kavramları daha iyi anlamalarını sağlamayı hedefledi. Ayrıca metinler çok tekrar edilerek bağlam içindeki alıcı söz varlığının üretici hale gelmesi amaçlandı. Üretici söz varlığının tespiti, ön test ve son test yapılarak belirlendi. Sonrasında yapılan ön test ve son test sonuçları karşılaştırıldı. Üretici söz varlığının geliştirilmesindeki başarı/başarısızlık yapılan çalışma ile net bir şekilde ortaya kondu
Market Basket Analysis Using Apriori and Eclat Algorithm in an E-Commerce Company
No full textPart of the book series: Lecture Notes in Networks and Systems ((LNNS,volume 1531)).E-commerce companies are facing significant challenges due to escalating competition, the homogenization of products and services, rapid shifts in customer demands, and the burgeoning volume of customer transactions. Consequently, these companies grapple with complex problems such as customer segmentation, customer churn analysis, market basket analysis, and the design of product recommendation systems. Leveraging data mining and machine learning algorithms offers substantial opportunities to effectively address these issues. For e-commerce enterprises, analysing customers’ purchasing behaviours and crafting personalized product recommendations not only enhances customer loyalty but also encourages impulse purchases. This approach also contributes to a more user-friendly platform, thereby increasing customer satisfaction. The present study aims to conduct a market basket analysis utilizing real-world data from an e-commerce company. Association rule mining algorithms, specifically Apriori and Eclat, are employed for this analysis. Through these methods, correlations and patterns between product categories are uncovered. Moreover, each algorithm is analyzed by comparing its execution duration and the quality of its results. These specified techniques, including Apriori, an intelligent join-based algorithm, and Eclat, a sophisticated tree-based algorithm, demonstrate remarkable intelligence by efficiently identifying and analyzing patterns within complex datasets. Their innovative methodologies enable them to dynamically adapt to data structures and extract frequent itemset with high performance, as evidenced by their outstanding results in current literature
Aronia (Chokeberry) Fruit Extract is a Potential Candidate for Managing Metabolic Syndrome in Elderly Patients
No full textObjectives: Natural products like Aronia (Aronia melanocarpa) are promising candidates to manage metabolic abnormalities due to their bioactive compounds. This study aimed to evaluate the effects of daily Aronia fruit extract supplementation on the components of Metabolic Syndrome (MetS), cardiovascular health, inflammation, and atherogenic markers in elderly patients. Methods: Our study is a randomized controlled trial of 44 subjects (12 males and 32 females) diagnosed with MetS. The study groups were the intervention group (n = 22), which received daily 10 g Aronia fruit extract for 8 wk, and the control group, which did not receive the extract (n = 22). Demographics, dietary intake, and food habits were recorded by an extended survey. Baseline and post-intervention measurements of anthropometric data, dietary intake, cardiovascular parameters, blood pressure, blood lipid composition, plasma atherogenic index (PAI), triglyceride (TG), and the triglyceride-glucose index (TyG), and biomarkers of inflammation, including tumor necrosis factor-alpha (TNF-α), Interleukin 6 (IL-6), high-sensitivity C-reactive protein (hs-CRP), and oxidative stress biomarkers, were represented as delta values. Results: No significant changes were observed in anthropometric measurements within or between groups over the 8 wk. However, several cardiovascular health parameters, including diastolic blood pressure (−10.00 mmHg), PAI index (−0.06), triglycerides (−9.0 mg/dL), and low-density lipoprotein cholesterol (LDL-C) (−6.30 mg/dL) were significantly decreased in the intervention group compared to the control group at the end of 8 wk of use (p < 0.05). Inflammatory markers TNF-α (−7.87 pg/mL) and IL-6 (−0.58 pg/mL), as well as oxidative stress markers, oxidized low-density lipoprotein (ox-LDL) (−132.17 U/L) and small dense low-density lipoprotein (sdLDL) (−0.79 mg/dL), also significantly decreased in the intervention group (p < 0.001). Conclusion: Our findings suggest that daily supplementation with Aronia fruit extract significantly improves cardiovascular health markers and reduces inflammation and oxidative stress in elderly patients with MetS. Hence, Aronia extract may be an effective dietary supplement for managing MetS in high-risk groups
1. Dış Ticaret Zirvesi Konuşmalar “Uluslararası Ticarette 100 Yılın Mirası ve Sürdürülebilir Gelecek Vizyonu”
No full textİstanbul Kültür Üniversitesi, İktisadi ve İdari Bilimler Fakültesi, Uluslararası Ticaret ve Finansman Bölümü ve DIŞYÖNDER (Dış Ticarete Yön Verenler Derneği) ortaklığında düzenlenmiştir.
Co-organized by Department of International Trade and Finance, Faculty of Economics and Administrative Sciences, Istanbul Kultur University and DIŞYÖNDER (Dış Ticarete Yön Verenler Derneği
Combination Ensemble and Explainable Deep Learning Framework for High-Accuracy Classification of Wild Edible Macrofungi
No full textAccurate identification of wild edible macrofungi is essential for biodiversity conservation, food safety, and ecological sustainability, yet remains challenging due to the morphological similarity between edible and toxic species. In this study, a curated dataset of 24 wild edible macrofungi species was analyzed using six state-of-the-art convolutional neural networks (CNNs) and four ensemble configurations, benchmarked across eight evaluation metrics. Among individual models, EfficientNetB0 achieved the highest performance (95.55% accuracy), whereas MobileNetV3-L underperformed (90.55%). Pairwise ensembles yielded inconsistent improvements, highlighting the importance of architectural complementarity. Notably, the proposed Combination Model, integrating EfficientNetB0, ResNet50, and RegNetY through a hierarchical voting strategy, achieved the best results with 97.36% accuracy, 0.9996 AUC, and 0.9725 MCC, surpassing all other models. To enhance interpretability, explainable AI (XAI) methods Grad-CAM, Eigen-CAM, and LIME were employed, consistently revealing biologically meaningful regions and transforming the framework into a transparent decision-support tool. These findings establish a robust and scalable paradigm for fine-grained fungal classification, demonstrating that carefully engineered ensemble learning combined with XAI not only advances mycological research but also paves the way for broader applications in plant recognition, spore analysis, and large-scale vegetation monitoring from satellite imagery
Başkası Hesabına İşlem Yapıldığının Bildirilmemesi Suçu
No full text5549 sayılı Suç Gelirlerinin Aklanmasının Önlenmesi Hakkında Kanun’un 15. maddesiyle başkası hesabına işlem yapıldığının bildirilmemesi fiili suç olarak düzenlenmiştir. Buna göre, kimlik tespitini gerekli kılan işlemlerde kendi adına ve fakat başkası hesabına işlem yapanların yazılı bildirimde bulunması gerekecektir. Suçun düzenlenmesiyle bu türdeki işlemlerin esas sahibinin kimliğinin gizli tutulmasının, böylelikle suçtan kaynaklanan malvarlığı değerlerinin aklanması suçuyla birlikte kayıt dışı işlemlerin önlenmesinin hedeflendiği anlaşılmaktadır. Böylece iktisadi hayattaki düzen korunacak, kayıt dışı ekonomi önlenecek, suç örgütlerinin ekonomik gücü ortadan kaldırılacak ve bunların faillerine ulaşılabilecektir. Düzenlenişi itibariyle bir soyut tehlike suçu olan başkası hesabına işlem yapıldığının bildirilmemesi suçunda, suçu bastırmaktan çok suçla mücadele anlayışı ön plana çıkmaktadır. Bu anlayış da cezalandırılabilirliğin öne alınmasına sebep olduğu gerekçesiyle doktrinde eleştiri konusu yapılmaktadır. Uygulamada ise suçun cezalandırdığı fiilin ne olduğuna dair yaşanan yanılgılar nedeniyle hatalı sonuçlara varıldığı görülmektedir
Letter to the Editor Regarding "Effectiveness of Bracing Combined With Exercise-based Treatment of Adolescent Idiopathic Scoliosis: Assessing the Synergistic Benefits: A Systematic Review"
No full textThe Asian Mathematical Conference 2025
No full textIn this paper, we develop a finite difference scheme based on the Crank-Nicolson method for solving the chiral nonlinear Schrödinger (CNLS) equation, which describes the dynamics of nonlinear wave propagation with chirality effects. The CNLS equation supports two types of progressive wave solutions: bright solitons and dark solitons. The proposed Crank-Nicolson scheme is implicit, unconditionally stable, and achieves second-order accuracy in both space and time. To evaluate the accuracy of the method, numerical results are compared with exact analytical soliton solutions. Numerical simulations are presented for the propagation of single bright and dark solitons. The results demonstrate that the Crank-Nicolson method accurately preserves soliton structures, making it an effective tool for studying the dynamics governed by the chiral nonlinear Schrödinger equation. The study demonstrates the effectiveness of the Crank-Nicolson method in capturing the dynamics of chiral nonlinear wave propagation and lays the foundation for further exploration of chiral effects in quantum and optical systems