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On a modified Bernstein operators approximation method for computational solution of Volterra integral equation
Full text linkThe main feature of this paper is an application of the modified Bernstein operator in the approximate and numerical solution of integral equations. The stability of the algorithm is discussed in the context of errors resulting from the numerical approximation of Volterra integral equations. The mechanism of the proposed method is explained in detail, including its main features. Furthermore, a comparison with an alternative numerical technique is made, and the superiority of the proposed solution is shown. Numerical experiments are also performed to verify the validity of the proposed method and to assess its accuracy. Finally, several conclusions are drawn from the results of the numerical experiments. The proposed method provides a powerful and efficient tool for the approximate solution of Volterra integral equations, and its results are promising. The results obtained from this algorithm are useful in the numerical analysis of integral equations.Deanship of Research and Graduate Studies at King Khalid University [RGP2/203/45]The first author (K.J.A) extends his appreciation to the Deanship of Research and Graduate Studies at King Khalid University for funding this work through Large Research Project under grant number RGP2/203/45
Novel green hydrochar production for renewable fuel substitutes, and experimental investigation of its usability on CI engine performance, combustion, and emission characteristics
Full text linkIn the present work, green hydrochars from renewable sources (cellulose (HC-Cel), and glucose (HC-Glu) are obtained via the hydrothermal carbonization method. Then different dosages (100 ppm, and 200 ppm) of these nano-sized hydrochar particles are added to the waste cooking oil biodiesel (20 %) and diesel blends (80 %) with the aid of an ultrasonification process. The experiments are performed at an indirect injection, water-cooled, three-cylinder diesel engine. During the experiments, the engine runs at a fixed engine speed of 2000 revolutions per minute (rpm), and at different loading conditions (15-60 Nm with intervals of 15 Nm). Then the impact of hydrochar addition to the diesel-biodiesel blends under these operation parameters is discussed in terms of engine behaviors (combustion, performance, and environmental). Considering the engine performance outputs, the brake specific fuel consumption (BSFC), and brake thermal efficiency (BTE) metrics for B20 are firstly 9.74 % higher, and 9 % lower than D100. The addition of 100 ppm HC-Glu, 200 ppm HC-Glu, 100 ppm HC-Cel, 100 ppm HC-Cel, and 200 ppm HC-Cel to B20 decreased the BSFC values by 17 %, 21.9 %, 15.31 %, 22.76 %, and enhanced the BTE by 13 %, 16 %, 12.07 %, 16.7 %, respectively. On the other hand, significant drops of 27.45 %, 39.22 %, 18.63 %, and 30.39 % for Carbon monoxide (CO) emission, 7.80 %, 12.52 %, 9.11 %, and 11.54 % for Nitrogen oxide (NOx) emission, and 8.91 %, 19.80 %, 5.94 %, and 15.84 % for uHC emission are recorded for B20 + 100 ppm HC-Glu, B20 + 200 ppm HC-Glu, B20 + 100 ppm HC-Cel, and B20 + 200 ppm HC-Cel test fuels, respectively. In conclusion, this work proves that hydrochars are efficient green agents to improve the worsened engine combustion, performance, and emission characteristics of diesel-biodiesel binary mixtures
SON ADA ROMANINA EKOLOJİK BİR YAKLAŞIM
Full text linkDoğanın bir parçası olan insanoğlunun hayatına doğa, tarihin ilk zamanlarında hükmedendir ve doğa karşısında insan, daha zayıf bir varlıktır. Bilginin az olduğu bu dönemlerde doğa olaylarına olağanüstü efsanevi anlamlar yüklenir. Bilginin artması, teknolojinin gelişmesiyle insanoğlu, doğayı çözmenin, doğaya hakim olmanın yollarını aradı. Bu yollar aranırken çoğu zaman doğadaki ekosisteme zarar verildi, insanoğlu doğanın bir parçası olduğunu unutup, hakimi olduğu düşüncesine kapıldı. Doğa ise zaman zaman buna şiddetli bir şekilde cevap vererek, var olan teknolojinin halen insanoğlunun ona hükmetmeye yetmediğini gösterdi. Zaman içerisinde insanoğlunun doğaya verdiği tahribat arttıkça, doğadaki tahribata dikkat çekmek isteyen yazarlar, çevre sorunlarını edebi eserlerde işleyerek, sorunlara çözümler getirmeye çalışmaktadırlar. Zülfü Livaneli’nin Son Ada romanında varlıklı bir kişinin bir adayı satın almasını, zamanla tanıdıklarını adaya davet etmesini, adada yeni evlerin inşa edilir, daha sonra darbeci Başkan’ın adaya yerleşmesiyle beraber adeta adaya darbe yaparak, adadaki huzurlu hayatın yerini distopik bir durum meydana gelirken, insanoğlunun doğaya yaptığı acımasız tahribat anlatılır. Bu çalışmada ekoleştiri kuramı göz önünde tutularak, ada halkının doğayla olan ilişkisi irdelenecektir
Gender Classification Using Parameters Obtained from the Dens Axis with Machine Learning Algorithms and Multilayer Perceptron Classifier
Full text linkBackground and Objectives: Due to the difficulties associated with the separation, damage, cremation, and commingling of skeletal remains, it is of great importance in forensic medicine to assess the accuracy and reliability of sex estimates derived from different skeletal components. For this purpose, this study aimed to classify gender using machine learning (ML) algorithms and a multilayer perceptron classifier (MLPC) based on morphometric data of the dens axis obtained from computed tomography (CT) images. Methods: Retrospectively, measurements were taken from CT images of 300 male and 300 female individuals aged between 18-65 years, including dens axis height (DAH), anteroposterior (APDDA) and anterosuperior lengths (ASDDA), dens axis angle (DAA), clivodental angle (CDA), and Boogard angle (BOO). Machine learning models such as Extra Tree Classifier (ETC), Random Forest (RF), Decision Tree (DT), Gaussian Naive Bayes (GaussianNB), k-Nearest Neighbors (k-NN), Linear Discriminant Analysis (LDA), Quadratic Discriminant Analysis (QDA), and Logistic Regression (LR) were used. MLPC was chosen as artificial neural networks (ANN) model. Results: Significant differences were found between genders in all dens axis parameters except BOO (p<0.05). The highest accuracy rate in ML algorithm modeling was found to be 0.80 with LDA, RF, k-NN algorithms, and MLPC. The parameter with the highest impact on gender classification was the dens axis anterosuperior length. Conclusion: It was found that the parameters obtained from the dens axis using MLCP and ML algorithms have sufficient accuracy rates the classification of sex. It was concluded that in forensic medicine, in cases of deterioration, loss, and deficiencies in bone sources for biological identity determination, the morphometric features of the dens axis can be considered for gender prediction
A Novel and Robust LSTM Model for Customer Churn Analysis Using Deep, Machine Learning, and Ensemble Learning: A Telecommunications Case
Full text linkCustomer churn is an important issue in increasing both the long- and short-term revenues. If companies identify customers' churn behavior, they can prevent churn, ensure customer loyalty, and, in turn, gain better financial returns. The telecommunications sector is a customer-oriented sector that requires customer retention to survive in the market. In this sector, customer churn is observed at a high level. In recent years, artificial intelligence-based customer churn analysis has been widely used to predict customer churn behavior. In this study, a customer churn analysis was conducted using publicly shared Telco telecommunications data. Predictive models were constructed using machine learning (LR, KNN, SVM, DT, RF, ANN), ensemble learning (XGBoost, Majority Voting), and deep learning (LSTM) methods. In addition, a 3-layered LSTM model was proposed. Accuracy (Acc), F1-score (F1), Precision (Prec), and Recall (Rec) rates were used to evaluate the models. As a result, the novel3-layered LSTM model achieved 91.90% Acc, 91.49% Prec, 92.31% Rec, and 91.90% F1 values. The proposed model is competitive with the existing models
Unrecognized poets and their poems in 2022 master's theses on poetry journals (Analysis and textual study)
Full text linkTürk edebiyatı tarihinin eksiksiz bir şekilde incelenebilmesi için edebî metinlerin yayımlanması üzerine yapılan çalışmalar büyük önem taşımıştır. Bu tür çalışmalar, yalnızca tanınmış şairlerin şiirlerini gün yüzüne çıkarmakla kalmayıp, edebiyat tarihinde yeterince incelenmemiş şairleri ve şiirleri de görünür kılmıştır. MESTAP (Şiir Mecmualarının Sistematik Tasnifi Projesi) gibi projelerle desteklenen araştırmalar, edebiyatımızdaki eksik yönleri aydınlatarak mevcut kaynakların derinleşmesine katkı sağlamıştır. Bu tez çalışmasında, 2022 yılında Ulusal Tez Merkezinde yayımlanan şiir mecmuaları konulu 65 yüksek lisans tezi incelenmiş; bu tezlerde araştırmacılar tarafından başka kaynaklarda yer almadığı belirtilen şiirler tespit edilerek sistematik bir doküman oluşturulmuştur. İncelenen tezlerde, divanı bulunmayan şairlerin şiirleri ile divanı olmakla birlikte divanında yer almayan şiirler bir araya getirilmiş ve bu şiirlerdeki şair mahlasları ile nazım şekilleri tablolar hâlinde düzenlenmiştir. Ayrıca, elde edilen veriler şiir metinleri ile birlikte çalışmanın ikinci bölümünde sunulmuştur. Çalışma sonucunda, bilinmeyen şiirlerin derlenmesiyle edebiyat tarihine katkı sağlanmış, araştırmacılar için kapsamlı ve işlevsel bir kaynak oluşturulmuştur. Anahtar Sözcükler: Bilinmeyen Şiirler, Klasik Türk Edebiyatı, MESTAP, Şiir Mecmuası, Yüksek Lisans Tezleri.Studies focusing on the publication of literary texts have played a crucial role in enabling a comprehensive examination of the history of Turkish literature. Such studies not only bring to light the poems of well-known poets but also reveal the works of poets and poems that have not been sufficiently explored in literary history. Research projects supported by initiatives like MESTAP (Systematic Classification Project of Poetry Journals) have illuminated gaps in our literary heritage and contributed to the deepening of existing sources. In this dissertation, 65 master's theses on poetry journals published in the National Thesis Center in 2022 were analyzed, and the poems identified by researchers as not found in other sources were compiled into a systematic document. In the theses examined, poems by poets without a divan as well as poems not included in the divans of poets who have divans were gathered, and the pseudonyms of poets and poetic forms in these poems were organized into tables. Additionally, the data obtained were presented along with the full texts of the poems in the second part of the study. As a result of the study, a contribution to literary history was made through the compilation of unknown poems, and a comprehensive and functional resource was created for researchers
I'm a Little Refugee in ED: Trauma Exposure and Outcomes in Refugee Children
Full text linkAmaç: Bu çalışmada, acil servise fiziksel travma nedeniyle başvuran mülteci çocukların travma mekanizmaları, klinik özellikleri ve sonuçlarının değerlendirilmesi amaçlanmıştır
Innovative techniques to chaotic dynamics and kinetic differ-integral equations
Full text linkIn this work, we analyse advancements in chaotic modelling by applying a modified version of the Atangana-Baleanu Caputo (MABC) fractional derivative operator (FDO) with respect to another function within a mathematical model (MMd). We employ an iterative method and fixed-point theory to verify the existence of a unique solution for this model. Additionally, due to the high non-linearity of the problem, we apply an appropriate numerical scheme to solve this system of equations computationally. Graphical representations illustrate the convergence of solutions within the chaotic model. To test the versatility of the modified Atangana-Baleanu Riemann (MABR) FDO, we generalize a kinetic differ-integral equation and compute its solution. The main contribution of our research is the construction of a chaotic model with the MABC FDO and a non-local, nonlinear kernel. Utilizing advanced numerical methods, we transform the non-local kernel into its local counterpart in order to obtain efficient and accurate solutions
Related Party Transactions from the Perspective of Public Shareholders
Full text linkTransactions between related parties, particularly those involving controlling shareholders, may pose a risk of financial detriment to minority shareholders while simultaneously providing a mechanism for controlling shareholders to accumulate profits in a manner that may be considered inequitable. This research seeks to examine the effects of related party transactions on shareholders from four distinct analytical angles, to enhance the investment decision-making process for investors. The study explores the relationship between related party transactions and several financial indicators of companies listed on Borsa Istanbul, including the free float ratio, stock price performance, dividend payout ratio, and Tobin's Q. The research utilized financial data from 339 companies listed on Borsa Istanbul, resulting in 1478 instances within an unbalanced panel data set. Methodologically, both fixed effects and random effects regression analyses were conducted. The analysis shows a positive relationship between debts owed to related parties and the free float ratio, as well as Tobin's Q ratio. Furthermore, a positive relationship is identified between receivables from related parties and the free float ratio, while a negative relationship is observed between receivables from related parties and Tobin's Q ratio. These findings corroborate the existence of agency costs and conflicts of interest between majority shareholders and minority shareholders. Despite the statistical significance of the findings, it is pertinent to note that the explanatory efficacy of the equations utilized is relatively modest
Being Both an Earthquake Survivor and a Nurse: Türkiye's Twin Earthquakes
Full text linkBackground: In February 2023, twin earthquakes struck 11 provinces in T & uuml;rkiye, devastating infrastructure and healthcare services. Nurses, as both survivors and frontline responders, faced extreme physical, emotional, and organizational challenges. Their experiences offer critical insights into disaster-related occupational risks and the structural gaps in worker health and safety. This study aims to explore the experiences of nurses working in hospitals affected by the twin earthquakes in T & uuml;rkiye in 2023.Methods: A qualitative, descriptive research design was used. Study participants were selected using purposeful sampling among nurses who experienced the earthquakes and continued working in the affected areas. In-depth online interviews were conducted with 17 nurses, achieving data saturation. The data were analyzed using content analysis, and the COREQ checklist was followed for study reporting.Results: As a result of the analysis, four themes were revealed; (1) earthquake shock, (2) working conditions, (3) living conditions, and (4) family and psychosocial situation. Nurses reported overwhelming psychological strain, unsafe working environments, lack of disaster plans, inadequate managerial support, and severe resource shortages-all of which posed significant threats to worker health and safety.Conclusions/Applications to Practice: This study highlights how nurses' dual roles as victims and caregivers during a large-scale disaster exposed critical vulnerabilities in worker health and safety. The findings underline the urgency of disaster-specific worker health and safety strategies, including trauma-informed mental health care, rapid staff support systems, and safety-oriented organizational planning to protect frontline healthcare workers in emergencies