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Minimum wage and spillover effects in a minimum wage society
Get PDFMinimum wage policies are widely implemented in developing countries, but their consequences remain uncertain. This study empirically investigates the impact of the minimum wage on monthly income inequality and its spillover effects in Turkey between 2004 and 2022, utilizing comprehensive micro data. We aim to shed light on the impact of national minimum wage policies by examining their diverse influences on the wage structure within the country. Our findings reveal that the minimum wage significantly reduces income disparities, particularly among formal workers at the lower and upper end of the wage distribution. While wage gaps below the median wage decline, those above it experience a slower growth rate, ultimately leading to wage convergence. Notably, this effect is more pronounced during macroeconomic instability from 2016 to 2022, compared with the relatively stable period of 2004-15. Moreover, the outcomes differ depending on individual attributes like gender, age, education, and other relevant factors. Furthermore, we observe tentative evidence of a lighthouse effect to some degree: the minimum wage seems to exert an equalizing influence on the wage structure of workers in the informal sector beyond a certain percentile
APPLICATION OF MACHINE LEARNING TECHNIQUES IN USED VEHICLE VALUATION
No full textSon yıllarda ikinci el araçların pazar hacmi artmıştır. Bu pazarda satıcı ve alıcı için doğru fiyatlandırma oldukça önemlidir. Son kullanıcı veya kurumlar için ikinci el araç değerlemesine ya da kiralanmasında yardımcı olacak sistemsel bir yapıya ihtiyaç bulunmaktadır. Bu çalışmada ilgili ikinci el araç ilanların yer aldığı sitelerden Selenium test aracı ile 26.000 üzerinde veri toplanmış ve bu veriler üzerinde veri önişleme (temizleme, dönüştürme vs.) adımları uygulanmıştır. Makine öğrenme teknikleri KNIME Analytics Platform veri madenciliği programının 4.7.3 sürümünde uygulanarak ikinci el araç fiyatı tahmin edilmeye çalışılmış ve sonuçlar birbiriyle karşılaştırılmıştır. Performans ölçülürken R² kullanılmıştır. Sonuçlar değerlendirildiğinde Lineer regresyon 0,56 R², Random Forest 0,83 R², GBoosted 0,81 R² ve Tree Ensemble 0,82 R² oranıyla tahminleme için başarılı sonuçlar elde edilmiştir.The market volume of second-hand vehicles has increased in recent years. In this market, accurate pricing is very important for the seller and the buyer. There is a need for a systematic structure that will help end-users or organizations in the valuation or leasing of used vehicles. In this study, over 26,000 data were collected from the relevant used car classifieds websites with Selenium test tool and data preprocessing (cleaning, transformation, etc.) steps were applied on these data. Machine learning techniques were applied in version 4.7.3 of the KNIME Analytics Platform data mining program to predict the used car price and the results were compared with each other. R² was used to measure performance. When the results are evaluated, successful results were obtained with Linear regression 0.56 R², Random Forest 0.83 R², GBoosted 0.81 R² and Tree Ensemble 0.82 R²
Application of artificial intelligence in healthcare systems: A scientometric analysis
Get PDF2024 International Conference on Science, Engineering and Business for Driving Sustainable Development Goals, SEB4SDG 2024 -- 2 April 2024 through 4 April 2024 -- Omu-Aran -- 201895This bibliometric study examines the worldwide progression of machine learning applications in medical and healthcare research between 2010 and 2023. A large dataset of published articles pertaining to machine learning applications in the medical and healthcare sectors is mined for useful information in this study. The data extraction procedure involves retrieving pertinent information from primary sources such as journals, books, and conference proceedings. Subsequently, the retrieved data is subjected to analysis to discern the patterns and tendencies in the use of machine learning in medical and healthcare research. A total of 1,220 publications were found in the Scopus database over the past 14 years. In addition, the study demonstrated that most AIHS research has concentrated on artificial intelligence applications to address a wide range of problems, including patient data security and chronic medical difficulties (such as cardiovascular disorders). Policymakers, healthcare practitioners, and researchers around the world may find this study's conclusions helpful. Emerging ethical concerns, integration, and real-world uses in smart healthcare systems, and the Internet of Things (IoT), could be the focus of future research
Interest rate fluctuation, savings mobilization, and capital formation: evidence from Bangladesh
No full textThis paper focuses on the relationship among interest rate, savings, and capital formation which are macroeconomic indicators of Bangladesh, and provides a scenario of the economy using data from 1976 to 2021. Our analysis performed econometric models of the unit root test, cointegration test, OLS regression model, multicollinearity test, correlation matrix, VECM, and Granger causality test. The regression reveals that interest rate has a negative and statistically significant relationship with capital formation and a positive and statistically insignificant relationship with domestic savings. However, domestic savings and capital formation are negative and statistically insignificant in Bangladesh’s economy. The VECM exhibits a longterm equilibrium association between interest rate and capital formation. Furthermore, Causality implies that there is a unidirectional causal relationship running from domestic savings and capital formation to interest rate. Yet, saving has no causal on capital formation. This outcome has a fantastic execution that can effortlessly stabilize the economy from any unanticipated circumstances. The economy should be concerned with this new study about maintaining a balance with these indicators. Suppose the outcomes of this research work are carried out into policy execution. In that case, that is, proper coordination of regulations on economic variables, progress in the real sector of the economy, velocity of expansion of capital growth, and grass-root mobilization of savings from the surplus market to the deficit market, it will lead to experienced long-run prosperity. We also recommend Policy formulators to accomplish our results properly for the betterment of savings and capital flows in Bangladesh
The influence of LinkedIn group community on postgraduate student experience, satisfaction and grades
Get PDFSocial media platforms represent an opportunity for higher education institutions to complement and enhance classroom teaching and learning. The purpose of this research is to investigate the influence of a LinkedIn group community on student experience, satisfaction and grades. A total of 118 students from three postgraduate programmes at a university in the United Kingdom were randomly assigned during the second week of the semester to either an experimental group representing the LinkedIn group community or to the control group, where students attended the classroom sessions but were not included in a LinkedIn group. In week twelve of the semester, 40 students in the experimental group and 42 in the control group voluntarily completed the Postgraduate Taught Experience Survey questionnaire. The results of independent t-tests indicate that students in the experimental group scored significantly higher than the control group on engagement, satisfaction and grades, and the behavioural engagement within the LinkedIn group community contributes to satisfaction. Analysis of the learning activities reveals that the interactive content produces a higher engagement rate than the informative content. International students who had previous experience with LinkedIn show higher levels of engagement within the experimental LinkedIn group. The research contributes to the educational use of LinkedIn and explains that the effective planning of learning activities in an online group community, which includes the consideration of individual characteristics and content types, may influence positively students' levels of engagement, satisfaction and grades
Modelling of the effects on educational success by machine learning algorithms
No full textSağlık, medya, bankacılık ve finans alanında sınıflandırma, kümeleme ve tahmin amacıyla kullanılan makine öğrenmesi günümüzde eğitim alanında da kullanılmaktadır. Bu çalışmada eğitim öğretim kurumlarının belirleyecekleri stratejilerde veya alacakları önlemlerde yol gösterici olması ve hatta daha büyük ana kütle, daha farklı okul türü ya da farklı kademelerde, farklı sektörlerde uygulanarak sonuçların genelleştirilmesine fayda sağlaması amacıyla makine öğrenmesi yöntemlerinden K-en yakın komşu, naive bayes, rastgele orman, destek vektör makineleri, karar ağaçları, boosting makine öğrenmesi sınıflandırma algoritmaları ile kurulan matematiksel modellemeler ile öğrencilerin akademik başarılarını etkileyen faktörler araştırılmıştır. Kurulan matematiksel modelin başarısına etki eden hiperparametreler ızgara taraması yöntemi ile belirlenerek maksimum model başarısı sağlanmıştır. Matematiksel modellemelerde akademik başarı ölçütü çıktı olarak belirlenerek; kurulan matematiksel modellerde çıktı ve girdi sayılarına ait model başarılarının değişimi incelenmiş; çıktıların ve girdilerin sayısının çeşitli yöntemlerle (denetimli ve denetimsiz yöntemlerle) azaltılması işlemlerinin matematiksel model başarısına etkileri gözlenmiştir. Sonuç olarak, en yüksek model başarılarının iki sınıf etiketli veri setine ait olduğu görülmüştür. K-en yakın komşu, naive bayes, rastgele orman, destek vektör makineleri, karar ağaçları, boosting model başarıları sırasıyla 0,62, 0,61, 0,96, 0,72, 0,86, 0,79 olarak elde edilmiştir.Machine learning, which is used for classification, clustering and prediction in the fields of health, media, banking and finance, is also used in the field of education today. In this study, by using the mathematical models established with machine learning classification methods such as K-nearest neighbour, naive bayes, random forest, support vector machines, decision trees and boosting; the factors affecting students’ academic success were investigated to guide educational institution the strategies , to determine the measures to be taken, and even to benefit the generalization of the results by applying them to a larger population, different types of schools or at different levels, in different sectors. Maximum model success was achieved by determining the hyperparameters that affected the success of the established mathematical model by the grid scanning method. In mathematical modelling, the academic success criterion is determined as the output; The changes in the model success of the output and input numbers in the established mathematical models were examined; The effects of reducing the number of outputs and inputs by various methods (supervised and unsupervised methods) on the success of the mathematical model have been observed. Finally the best accuracy scores were obtained from the data set with two class labels. The accuracy scores of the algorithms (K-nearest neighbour, naive bayes, random forest, support vector machines, decision trees and boosting) respectively were 0,62, 0,61, 0,96, 0,72, 0,86, 0,79
Research on the change of the public relations sector in Turkey: Agency and client perspectives
Get PDFİletişim Bilimi ve İnternet Enstitüsü, Halkla İlişkiler Ana Bilim Dalı, Halkla İlişkiler ve Reklamcılık Bilim DalıKüresel – toplumsal dönüşümler, teknolojinin getirdiği yenilikler iş dünyasını değişime zorlamaktadır. Bu değişimin halkla ilişkiler sektörü ve mesleği için de kaçınılmaz olduğu görülmektedir. Elinizdeki bu çalışmada, "Türkiye'de halkla ilişkiler sektörü ve halkla ilişkiler mesleği nasıl bir değişim – dönüşümden geçiyor? Bu değişimle birlikte hangi kavramların ön plana çıkacağı düşünülüyor?" sorularının yanıtı aranarak halkla ilişkiler mesleği ve sektörün gelecek öngörüsünün ortaya çıkarılması hedeflenmiştir. Bu amaçla halkla ilişkiler sektörünün önemli paydaşlarından olan İDA ve KİD ile görüşülmüş, öncelikle sektörün mevcut durumu ortaya konmuş, sorunlar ve gelişim alanları tespit edilmiş, sonrasında ise geleceğe ilişkin öngörüler ele alınmıştır. Çalışmada halkla ilişkiler ismi ve algısı ile ilgili sorunların devam ettiği, mesleğin kapsamı ve hizmet içeriğinin yeniden tanımlanmaya ihtiyacı olduğu, halkla ilişkiler sektörünün en çok medya ilişkileri ve kriz iletişimi odaklı hizmetlerle eşleştirildiği, sektörün insan kaynağı, algılanma / konumlanma sorunlarının sektörün gelişimini etkilediği, sektörün yeterince dijitalleşemediği ortaya konmuştur. Çalışmamız halkla ilişkiler alanında sürdürülebilirlik – amaca dayalı iletişim ve dijital iletişim gibi iki önemli unsurun gelecekte etkili olacağını ortaya koymaktadır. Katılımcılar yeni kuşağın sürdürülebilirlik çalışmalarını tetikleyeceklerini, değişimin itici gücü olacağını vurgulamaktadırlar. Bu değişimle halkla ilişkilerin değerlerin temsilcisi noktasında olacağı, sürdürülebilirlik çalışmalarında önemli rol üstleneceği ortaya konulmuştur.Global - social transformations, innovations brought by technology force the business world to change. It is seen that this change is also inevitable for the public relations sector and profession. In this study,we try to find response of these questions. "What kind of change and transformation is the public relations sector and the public relations profession going through in Turkey? Which concepts are thought to come to the forefront with this change?", it is aimed to reveal the future foresight of the public relations profession and the sector. For this purpose, IDA and KID, which are important stakeholders of the public relations sector, were interviewed, firstly, the current situation of the sector was revealed, problems and development areas were identified, and then predictions for the future were discussed. The study revealed that the problems related to the name and perception of public relations continue, the scope and service content of the profession need to be redefined, the public relations sector is mostly associated with services focused on media relations and crisis communication, the sector's human resources, perception / positioning problems affect the development of the sector, and the sector is not sufficiently digitalised. Our study reveals that two important elements such as sustainability - purpose-based communication and digital communication will be effective in the field of public relations in the future. Participants emphasise that the new generation will trigger sustainability efforts and be the driving force of change. With this change, it has been revealed that public relations will be at the point of representing values and will play an important role in sustainability studies
Doğu Afrika'nın küresel değer zincirlerine ekonomik entegrasyonunun çevresel bozulma üzerindeki etkisi
Get PDFSosyal Bilimler Enstitüsü, İktisat Ana Bilim DalıSon zamanlarda, Doğu Afrika ülkeleri küresel değer zincirlerine daha yüksek düzeyde entegrasyon deneyimi yaşamıştır. Bu çalışma, gayri safi yurtiçi hasıla, gayri safi yurtiçi hasılanın karesi, yenilenebilir enerji tüketimi, kentsel nüfus ve ticarete açıklık gibi değişkenleri hesaba katarak Doğu Afrika'nın küresel değer zincirlerine ekonomik entegrasyonunun çevresel bozulma üzerindeki etkisini araştırıyor. 1992-2018 dönemine ait yıllık panel veri seti, panel dinamik sabit etki tahmincisi aracılığıyla analiz edilmiştir. Çalışma bulguları, Doğu Afrika'da küresel değer zinciri katılımı ile çevre kalitesi arasında uzun vadeli bir ilişkinin bulunduğunu ve genel küresel değer zinciri katılımının bölgedeki çevre kirliliğini artırdığını ortaya koyuyor. Çalışma ayrıca, Doğu Afrika'nın küresel değer zincirlerine ileri ve geri entegrasyonunun çevresel yansımalarını karşılaştırarak, hangi entegrasyon türünün çevreyi daha fazla etkilediğini tespit etmeye çalışıyor. Ampirik sonuçlar, küresel değer zincirlerine geriye doğru entegrasyonun Doğu Afrika'daki çevresel bozulma üzerinde uzun vadeli olumlu bir etki gösterdiğini, ileri entegrasyonun ise önemli bir etkisinin olmadığını göstermektedir. Bu bulgular göz önüne alındığında, araştırma çeşitli politika önerilerinde bulunmaktadır. Anahtar kelimeler: Doğu Afrika, Küresel Değer Zincirleri, Çevresel Bozulmalar, Dinamik Panel verileri, ARDLIn recent times, East African countries have experienced a greater level of integration into global value chains. This study investigates the impact of East Africa's economic integration into global value chains on environmental degradation while accounting for variables such as gross domestic product, the square of gross domestic product, renewable energy consumption, urban population, and trade openness. Annual panel data set for the period 1992-2018 is analyzed through the panel dynamic fixed-effect estimator. The study findings reveal that a long-term relationship exists between global value chains participation and environmental quality in East Africa, and that the overall global value chains participation aggravates environmental pollution in the region. The study further compares the environmental repercussions of East Africa's backward and forward integration into global value chains, seeking to discern which integration type affects the environment more. The empirical results suggest that while backward integration into global value chains exhibit a positive long-term effect on environmental degradation in East Africa, forward integration has no significant effect. Given these findings, the research makes several policy recommendations. Key words: East Africa, Global Value Chains, Environmental Degradations, Dynamic Fixed Effect, ARD
Analysing the effective use of foreign trade defence instruments in the petrochemical sector and the conditions for the application of anti-dumping measures in appropriate circumstances
No full textBu çalışmada dış ticaretin tarihsel gelişimi ele alınarak yıllara sair yaşanan değişimler incelenecektir. Ardından petrokimyasal ürünlerde dünyada öncü olan ülkelerin yapmış olduğu üretimlerle dış ticarete olan etkisi değerlendirilecek ve dünyadaki ürün talebi çerçevesinde savunma araçlarının kullanımı incelenecektir. Son olarak petrokimyasal ürünler için ön plana çıkan dış ticaret politikası savunma aracı olan anti-dampingin etkin kullanımı belirtilecektir. Bu kapsamda anti-damping başvuru koşullarının da detaylı olarak mercek altına alınması sonrasında, Türkiye’de tek yerli üretici olan şirket tarafından açılan anti-damping başvuru dosyası örneği üzerine finansal değerlendirmeler yapılacak dampingin hesaplamaları üzerine değerlendirmelerde bulunulacaktır.In this study, the historical development of foreign trade will be discussed, and the changes experienced over the years will be examined. Then, the production of petrochemical products by the leading countries in the world and its impact on foreign trade will be evaluated, and the use of defense tools within the framework of product demand in the world will be examined. Finally, the effective use of anti-dumping, which is the most prominent foreign trade policy defense tool for petrochemical products, will be stated. In this context, after analyzing the antidumping application conditions in detail, financial evaluations will be made on the antidumping application file filed by the only domestic producer company in Türkiye and evaluations will be made on the calculations of dumping
An artificial neural network-based numerical estimation of the boiling pressure drop of different refrigerants flowing in smooth and micro-fin tubes
Get PDFIn thermal engineering implementations, heat exchangers need to have improved thermal capabilities and be smaller to save energy. Surface adjustments on tube heat exchanger walls may improve heat transfer using new manufacturing technologies. Since quantifying enhanced tube features is quite difficult due to the intricacy of fluid flow and heat transfer processes, numerical methods are preferred to create efficient heat exchangers. Recently, machine learning algorithms have been able to analyze flow and heat transfer in improved tubes. Machine learning methods may increase heat exchanger efficiency estimates using data. In this study, the boiling pressure drop of different refrigerants in smooth and micro-fin tubes is predicted using an artificial neural network-based machine learning approach. Two different numerical models are built based on the operating conditions, geometric specifications, and dimensionless numbers employed in the two-phase flows. A dataset including 812 data points representing the flow of R12, R125, R134a, R22, R32, R32/R134a, R407c, and R410a through smooth and micro-fin pipes is used to evaluate feed-forward and backward propagation multi-layer perceptron networks. The findings demonstrate that the neural networks have an average error margin of 10?percent when predicting the pressure drop of the refrigerant flow in both smooth and micro-fin tubes. The calculated R-values for the artificial neural network’s supplementary performance factors are found above 0.99 for all models. According to the results, margins of deviations of 0.3?percent and 0.05?percent are obtained for the tested tubes in Model 1, while deviations of 0.79?percent and 0.32?percent are found for them in Model 2