İstanbul Gelişim Üniversitesi Kurumsal Açık Erişim Arşivi
DSpace@Gelişim, İstanbul Gelişim Üniversitesi tarafından doğrudan ve dolaylı olarak yayınlanan; kitap, makale, tez, bildiri, rapor, araştırma verisi gibi tüm akademik kaynakları uluslararası standartlarda dijital ortamda depolar, Üniversitenin akademik performansını izlemeye aracılık eder, kaynakları uzun süreli saklar ve telif haklarına uygun olarak Açık Erişime sunar.
Güncel Gönderiler
Do the Political Uncertainty and Geopolitical Risk Indexes in the G-7 Countries Relate to Stock Prices? Fourier Causality Test Evidence
(TAYLOR & FRANCIS LTD, 2-4 PARK SQUARE, MILTON PARK, ABINGDON OR14 4RN, OXON, ENGLAND, 2024) Tütüncü, Asiye; Savaş Çelik, Burcu; Kahveci, Şükran
This study aims to examine the reciprocal effects of the Economic Policy Uncertainty (EPU) and the Geopolitical Risks (GPR) on the stock
markets (SP) of the G-7 countries. The findings of the study will allow
us to answer the following questions: Do risk and uncertainty conditions in other G-7 countries affect their stock markets as much as
those in the country itself? Which affects G-7 stock markets more, EPU
or GPR? In addition to previous research in the field, this study conducts a comparative analysis of the effects of the EPU and GPR on
the SP of G-7 countries. Therefore, we used the linear VAR Granger,
Fourier and Fourier Fractional Frequency Granger Causality tests. We
found that the EPU indices of the United States, United Kingdom,
and Germany had the greatest impact on the stock markets of their
respective countries and other G-7 countries, and the conclusion
that G-7 stock markets were influenced by economic uncertainties in
other member countries was added to the literature. It has also been
found that the G-7 stock markets have a broad influence on the EPU
index.
Evolution of machine learning applications in medical and healthcare analytics research: A bibliometric analysis
(ELSEVIER, RADARWEG 29, 1043 NX AMSTERDAM, NETHERLANDS, 2024) Ajibade, Samuel-Soma M.; Alhassan, Gloria Nnadwa; Zaidi, Abdelhamid; Oki, Olukayode Ayodele; Awotunde, Joseph Bamidele; Ogbuju, Emeka; Akintoye, Kayode A.
This bibliometric research explores the global evolution of machine learning applications in medical and
healthcare research for 3 decades (1994 to 2023). The study applies data mining techniques to a comprehensive
dataset of published articles related to machine learning applications in the medical and healthcare sectors. The
data extraction process includes the retrieval of relevant information from the source sources such as journals,
books, and conference proceedings. An analysis of the extracted data is then conducted to identify the trends in
the machine learning applications in medical and healthcare research. The Results revealed the publications
published and indexed in the Scopus and PubMed database over the last 30 years. Bibliometric Analysis revealed
that funding played a more significant role in publication productivity compared to collaboration (co-authorships), particularly at the country level. Hotspots analysis revealed three core research themes on MLHC research
hence demonstrating the importance of machine learning applications to medical and healthcare research.
Further, the study showed that the MLHC research landscape has largely focused on ML applications to tackle
various issues ranging from chronic medical challenges (e.g., cardiological diseases) to patient data security. The
findings of this research may be useful to policy makers and practitioners in the medical and healthcare sectors
and to global research endeavours in the field. Future studies could include addressing issues such as growing
ethical considerations, integration, and practical applications in wearable technology, IoT, and smart healthcare
systems.
Mechanical evaluation for the finite element analysis of intramedullary nailing and plate screw system used in humerus transverse fractures
(ELSEVIER, RADARWEG 29, 1043 NX AMSTERDAM, NETHERLANDS, 2024) Akkurt, Ekrem; Yıldırım, Mücahid; Erenler, Ferhat; Tosun, Osman Mücahit; Akkurt, Mustafa Ferit; Akkurt, Burcu; Şen, Zafer; Olçar, Ahmet Hamdi
Aim: This study aims to examine the commonly used plate screw system and intramedullary nailing method in
osteosynthesis in humeral shaft fractures in terms of stress shielding using finite element analysis.
Material and methods: Images were obtained by computerized tomography (CT) to create a 3D model of the
humerus bone. After the CT images were transferred to the ANSYS 2021 R2 program (ANSYS, Inc., Canons-burg,
PA), a transverse fracture model was created from the shaft region of the humeral bone meshed to the humerus
bone and modeled in the 3D environment.
Results: The tetrahedron mesh structure was used for the finite element models in our study. The element size was
chosen as 3.5 mm for the bone model and 2 mm for the plate and intramedullary nail models. The node numbers
of bone, intramedullary nail, and plate were 91230, 462578, and 581352, respectively. The element numbers of
bone, intramedullary nail, and plate were 61350, 311285, and 370350, respectively. Maximum stress values of
260 MPa on the nail and 280 MPa on the plate were detected in this study.
Conclusion: Fewer stress values were obtained and stress concentrations were not formed on the implant in
osteosynthesis performed by intramedullary nailing. It can be concluded that this study may guide further studies
for those focusing on it and may contribute to the development of a more comprehensive understanding of the
topic.
The global burden of overweight-obesity and its association with economic status, benefiting from STEPs survey of WHO member states: A meta-analysis
(ELSEVIER, RADARWEG 29, 1043 NX AMSTERDAM, NETHERLANDS, 2024) Islam, A. N. M. Shamsul; Sultana, Hafıza; Refat, Md. Nazmul Hassan; Farhana, Zaki; Abdulbasah Kamil, Anton; Rahman, Mohammad Meshbahur
Introduction: The World Health Organization (WHO) 2030 agenda for Sustainable Development Goals (SDGs
target 3.4) identifies non-communicable diseases (NCDs) as a key challenge for sustainable development. As one
of the major NCD risks, here, we estimated the prevalence of overweight/obesity in adults and assessed countryeconomic variations using meta-analysis.
Methods: The latest STEPwise approach to NCD risk factor surveillance (STEPS) report of WHO member states
studied on overweight/obesity from 2000 to 2020 were reviewed and related data were assessed further. The
prevalence of overweight/obesity was pooled using the random effects model. The subgroup analysis and metaregression were performed based on countries’ economic status obtained from the World Bank’s country
development index 2019. Study heterogeneity and publication bias were also observed.
Results: Out of 73 studies with 469,766 participants analyzed, the highest overweight/obesity prevalence was
found in American Samoa (93.5 %), while Democratic People’s Republic of Korea had the lowest prevalence (4.4
%). The overall weighted pooled prevalence of overweight/obesity regardless of countries economic status was
37.0 % [95 % CI: 33 %-42 %]. There was significant heterogeneity in the prevalence of overweight/obesity (I2 =
99.91 %; p < 0.001). Subgroup analysis revealed a higher prevalence in high-income countries [60 %; 95 % CI:
47 %-72 %]. Meta-regression revealed a significant (p = 0.001) association and a 14 % increase chance of having
overweight/obesity with increasing economic status.
Conclusion: The prevalence of overweight/obesity is high worldwide, especially in high-income countries that
demands a large-scale awareness campaigns and effective initiatives to control overweight/obesity and the
associated risk factors of adults of these countries.
Measurement of Education Effectiveness in the BRICS countries and Turkey
(HIPATIA PRESS, C-CLARAMUNT 4, BARCELONA 08030, SPAIN, 2024) İmre-Bıyıklı, Süreyya; Abdulbassah Kamil, Anton
The high literacy rate in a country shows that educational attainment is progressing well and
efficiently. In this study, we aim to compare the effectiveness of education in the BRICS
countries - Brazil, India, Russia, China, South Africa - and Turkey. We use the Stochastic
Frontier Analysis method to measure the technical efficiency of education. The study utilizes
2017 and 2018 data, and linear functions to examine technical efficiency. The dataset
comprises cross-sectional data. As a result, South Africa and India show the lowest technical
efficiency scores, followed by China. Russia, Brazil, and Turkey scored high on technical
efficiency for 2017 and 2018. This means that education levels in South Africa and India are
unequal and shared among all residents. The 2017 and 2018 productivity scores are the same
at 0.99% in Turkey, Russia, and Brazil. India's productivity score increased by 0.10% to 0.55%
in 2018. Likewise, the productivity score calculated for China decreased by an average of 0.07
percent to 0.70 percent. However, South Africa's productivity score fell by 0.08 percent to 0.01
percent in 2018.
