Mühendislik Bilimleri Bölümü Koleksiyonu
https://hdl.handle.net/20.500.12573/36
2024-03-29T10:15:39ZOn rings with one middle class of injectivity domains
https://hdl.handle.net/20.500.12573/1658
On rings with one middle class of injectivity domains
Demirci, Yilmaz Mehmet; Alizade, Rafail; Turkmen, Burcu Nisanci; Turkmen, Ergul
A module M is said to be modest if the injectivity domain of M is the class of all crumbling modules. In this paper, we investigate the basic properties of modest modules. We provide characterizations of some classes of rings using modest modules. In particular, we show that a ring having the class of crumbling modules as the only right middle class of injectivity domains is either a right V-ring or right Noetherian; and a commutative ring with this property is regular. We also give criteria for a ring having the class of crumbling modules as the only right middle class of injectivity domains.
2022-01-01T00:00:00ZNeRNA: A negative data generation framework for machine learning applications of noncoding RNAs
https://hdl.handle.net/20.500.12573/1635
NeRNA: A negative data generation framework for machine learning applications of noncoding RNAs
Orhan, Mehmet Emin; Demirci, Yilmaz Mehmet; Sacar Demirci, Muserref Duygu
Many supervised machine learning based noncoding RNA (ncRNA) analysis methods have been developed to
classify and identify novel sequences. During such analysis, the positive learning datasets usually consist of
known examples of ncRNAs and some of them might even have weak or strong experimental validation. On the
contrary, there are neither databases listing the confirmed negative sequences for a specific ncRNA class nor
standardized methodologies developed to generate high quality negative examples. To overcome this challenge,
a novel negative data generation method, NeRNA (negative RNA), is developed in this work. NeRNA uses known
examples of given ncRNA sequences and their calculated structures for octal representation to create negative
sequences in a manner similar to frameshift mutations but without deletion or insertion. NeRNA is tested
individually with four different ncRNA datasets including microRNA (miRNA), transfer RNA (tRNA), long
noncoding RNA (lncRNA), and circular RNA (circRNA). Furthermore, a species-specific case analysis is performed to demonstrate and compare the performance of NeRNA for miRNA prediction. The results of 1000 fold
cross-validation on Decision Tree, Naïve Bayes and Random Forest classifiers, and deep learning algorithms such
as Multilayer Perceptron, Convolutional Neural Network, and Simple feedforward Neural Networks indicate that
models obtained by using NeRNA generated datasets, achieves substantially high prediction performance.
NeRNA is released as an easy-to-use, updatable and modifiable KNIME workflow that can be downloaded with
example datasets and required extensions. In particular, NeRNA is designed to be a powerful tool for RNA
sequence data analysis.
2023-01-01T00:00:00ZAnalysis of the motion of a rigid rod on a circular surface using interpolated variational iteration method
https://hdl.handle.net/20.500.12573/1557
Analysis of the motion of a rigid rod on a circular surface using interpolated variational iteration method
Coskun, Safa Bozkurt; Senturk, Erman; Atay, Mehmet Tarik
In this paper, interpolated variational iteration method (IVIM) is applied to investigate the
vibration period and steady-state response for the motion of rigid rod rocking back and forth
on a circular surface without slipping. The problem can be considered as a strongly nonlinear
oscillator. In this solution procedure, analytical variational iteration technique is utilized
by evaluating the integrals numerically. The approximate analytical results produced by the
presented method are compared with the other existing solutions available in the literature.
The advantage of using numerical evaluation of integrals, the method becomes fast convergent
and a highly accurate solution can be obtained within seconds. The authors believe that
the presented technique has potentially wide application in the other nonlinear oscillation
problems.
2022-01-01T00:00:00ZA fractional-order mathematical model based on vaccinated and infected compartments of SARS-CoV-2 with a real case study during the last stages of the epidemiological event
https://hdl.handle.net/20.500.12573/1530
A fractional-order mathematical model based on vaccinated and infected compartments of SARS-CoV-2 with a real case study during the last stages of the epidemiological event
Bilgil, Halis; Yousef, Ali; Erciyes, Ayhan; Erdinc, Ummugulsum; Ozturk, Zafer
In 2020 the world faced with a pandemic spread that affected almost everything of
humans’ social and health life. Regulations to decrease the epidemiological spread and
studies to produce the vaccine of SARS-CoV-2 were on one side a hope to return back
to the regular life, but on the other side there were also notable criticism about the
vaccines itself. In this study, we established a fractional order differential equations
system incorporating the vaccinated and re-infected compartments to a SIR frame to
consider the expanded and detailed form as an SVIIvR model. We considered in the model
some essential parameters, such as the protection rate of the vaccines, the vaccination
rate, and the vaccine’s lost efficacy after a certain period. We obtained the local stability
of the disease-free and co-existing equilibrium points under specific conditions using the
Routh–Hurwitz Criterion and the global stability in using a suitable Lyapunov function.
For the numerical solutions we applied the Euler’s method. The data for the simulations
were taken from the World Health Organization (WHO) to illustrate numerically some
scenarios that happened
2023-01-01T00:00:00Z