Scopus İndeksli Yayınlar Koleksiyonu
Permanent URI for this collectionhttps://hdl.handle.net/20.500.12573/395
Browse
5 results
Search Results
Article Citation - WoS: 3Citation - Scopus: 3The Angular Electronic Band Structure and Free Particle Model of Aromatic Molecules: High-Frequency Photon-Induced Ring Current(World Scientific Publ Co Pte Ltd, 2017-03) Oncan, Mehmet; Koc, Fatih; Sahin, Mehmet; Koksal, KorayThis work introduces an analysis of the relationship of first-principles calculations based on DFT method with the results of free particle model for ring-shaped aromatic molecules. However, the main aim of the study is to reveal the angular electronic band structure of the ring-shaped molecules. As in the case of spherical molecules such as fullerene, it is possible to observe a parabolic dispersion of electronic states with the variation of angular quantum number in the planar ring-shaped molecules. This work also discusses the transition probabilities between the occupied and virtual states by analyzing the angular electronic band structure and the possibility of ring currents in the case of spin angular momentum (SAM) or orbital angular momentum (OAM) carrying light. Current study focuses on the benzene molecule to obtain its angular electronic band structure. The obtained electronic band structure can be considered as a useful tool to see the transition probabilities between the electronic states and possible contribution of the states to the ring currents. The photoinduced current due to the transfer of SAM into the benzene molecule has been investigated by using analytical calculations within the frame of time-dependent perturbation theory.Article Citation - WoS: 2Citation - Scopus: 2Structural Profile Matrices for Predicting Structural Properties of Proteins(World Scientific Publ Co Pte Ltd, 2020-07-10) Azginoglu, Nuh; Aydin, Zafer; Celik, MetePredicting structural properties of proteins plays a key role in predicting the 3D structure of proteins. In this study, new structural profile matrices (SPM) are developed for protein secondary structure, solvent accessibility and torsion angle class predictions, which could be used as input to 3D prediction algorithms. The structural templates employed in computing SPMs are detected by eight alignment methods in LOMETS server, gap affine alignment method, ScanProsite, PfamScan, and HHblits. The contribution of each template is weighted by its similarity to target, which is assessed by several sequence alignment scores. For comparison, the SPMs are also computed using Homolpro, which uses BLAST for target template alignments and does not assign weights to templates. Incorporating the SPMs into DSPRED classifier, the prediction accuracy improves significantly as demonstrated by cross-validation experiments on two difficult benchmarks. The most accurate predictions are obtained using the SPMs derived by threading methods in LOMETS server. On the other hand, the computational cost of computing these SPMs was the highest.Article Citation - WoS: 3Citation - Scopus: 3Real Representatives of Equisingular Strata of Simple Quartic Surfaces(World Scientific Publ Co Pte Ltd, 2019-11) Aktas, Cisem GunesWe develop an algorithm detecting real representatives in equisingular strata of projective models of K3-surfaces. We apply this algorithm to spatial quartics and find two new examples of real strata without real representatives. As a by-product, we also give a new proof for the only previously known example of plane sextics.Article Citation - WoS: 6Citation - Scopus: 8Dimensionality Reduction for Protein Secondary Structure and Solvent Accesibility Prediction(World Scientific Publ Co Pte Ltd, 2018-10) Aydin, Zafer; Kaynar, Oguz; Gormez, YasinSecondary structure and solvent accessibility prediction provide valuable information for estimating the three dimensional structure of a protein. As new feature extraction methods are developed the dimensionality of the input feature space increases steadily. Reducing the number of dimensions provides several advantages such as faster model training, faster prediction and noise elimination. In this work, several dimensionality reduction techniques have been employed including various feature selection methods, autoencoders and PCA for protein secondary structure and solvent accessibility prediction. The reduced feature set is used to train a support vector machine at the second stage of a hybrid classifier. Cross-validation experiments on two difficult benchmarks demonstrate that the dimension of the input space can be reduced substantially while maintaining the prediction accuracy. This will enable the incorporation of additional informative features derived for predicting the structural properties of proteins without reducing the accuracy due to overfitting.Article Citation - WoS: 7Citation - Scopus: 11Chaotic Map Construction From Common Nonlinearities and Microcontroller Implementations(World Scientific Publ Co Pte Ltd, 2016-06-30) Ablay, GunyazThis work presents novel discrete-time chaotic systems with some known physical system non-linearities. Dynamic behaviors of the models are examined with numerical methods and Arduino microcontroller-based experimental studies. Many new chaotic maps are generated in the form of x(k + 1) = rx(k) + f(x(k)) and high-dimensional chaotic systems are obtained by weak coupling or cross-coupling the same or different chaotic maps. An application of the chaotic maps is realized with Arduino for chaotic pulse width modulation to drive electrical machines. It is expected that the new chaotic maps and their microcontroller implementations will facilitate practical chaos-based applications in different fields.