Mühendislik ve Doğa Bilimleri Fakültesi

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Citation Count: 0
"2-pirazolin yapısındaki yeni bir bileşiğin sentezi, moleküler modellemesi ve monoaminoksidaz inhibitörü etkisinin araştırılması"
(Türkiye Halk Sağlığı Kurumu, 2018) Yelekçi, Kemal; Uçar, Gülberk; Yelekçi, Kemal
Amaç: Nöromediatörlerin yıkımından sorumlu olan monoamin oksidaz (MAO) enziminin izoformlarının (MAO-A ve -B) birçok hastalık ile yakından ilişkili olduğu; MAO inhibitörlerinin depresyon, Parkinson ve Alzheimer hastalığı gibi hastalıkların tedavisinde kullanıldığı bilinmektedir. Grubumuzca daha etkin, tersinir ve az yan etkili yeni bir MAO inhibitörü (SH2U bileşiği) sentezlenmiş ve bu bileşiğin insan MAO enzimini (hMAO) inhibe etme yeteneği incelenmiştir. Ayrıca bu yeni bileşiğin hMAO ile etkileşimi, moleküler modelleme çalışmaları ile detaylı bir şekilde araştırılmıştır. Sentezlenen yeni bileşiğin hMAO’yu kuvvetli bir şekilde yarışmalı ve tersinir olarak inhibe ettiği bulunmuştur. Söz konusu bileşiğin Parkinson ve Alzheimer hastalıklarının tedavisinde ümit verici bir ilaç etken maddesi olabileceği düşünülmektedir. Yöntem: 3’,5’-Dikloro-2’-hidroksi asetofenon ile p-tolualdehit’in metanol içinde KOH varlığında reaksiyona girmesiyle 1-(3,5-dikloro-2-hidroksifenil)- 3-p-tolil prop-2-en-1-on (3’,5’-Dikloro-2’-hidroksi-4- metil şalkon) bileşiği sentez edilmiştir. Daha sonra elde edilen bu bileşiğin etanol içerisinde geri çeviren soğutucu altında izonikotinik asit hidrazit ile muamele edilmesiyle [3-(3,5-dikloro-2-hidroksifenil)-5-p-tolil-4,5- dihidropirazol-1-il] (piridin-4-il) metanon bileşiği sentez edilmiştir. Yapısı doğrulanan bu bileşiğin hMAO enzimi ile etkileşimi, ticari tayin kiti kullanılarak fluorometrik bir yöntemle incelenmiştir. Ayrıca, söz konusu yeni bileşik ile hMAO arasındaki etkileşimler, moleküler modelleme çalışmaları ile aydınlatılmıştır. Bulgular: Sentezlenen bileşiğin yapısı, IR, Mass, 1H-NMR ve elemental analiz yöntemleri kullanılarak doğrulanmıştır. Yapısı doğrulanan bu bileşiğin etkin, seçici, tersinir, toksik olmayan bir hMAO-B inhibitörü olduğu ve inhibisyonun yarışmalı olduğu görülmüştür. Moleküler yerleştirme programı kullanılarak bileşiğin hMAO-B enziminin aktif bölgesinde hangi amino asit yan zincirleri ile ne tür girişimleri yaptığı belirlenmiştir. Sonuç: Yeni sentezlenen SH2U bileşiği, hMAO-B enzimini kuvvetle, seçici, yarışmalı ve tersinir olarak inhibe etmiştir. Sentezlediğimiz bileşik, bilinen seçici ama tersinmez MAO-B inhibitörü olan selejilin’den daha etkin ve seçici, tersinir olarak hMAO-B enzimini inhibe etmiştir ve Parkinson ile Alzheimer hastalığı tedavisinde kullanılabilecek bir ilaç etken maddesi olarak ümit vadetmektedir.
Citation Count: 5
(3+3+2) warped-like product manifolds with Spin(7) holonomy
(Elsevier Science Bv, 2011) Bilge, Ayşe Hümeyra; Bilge, Ayşe Hümeyra
We consider a generalization of eight-dimensional multiply warped product manifolds as a special warped product by allowing the fiber metric to be non-block diagonal. We define this special warped product as a (3 + 3 + 2) warped-like manifold of the form M = F x B. where the base B is a two-dimensional Riemannian manifold and the fibre F is of the form F = F-1 x F-2 where the F-i(i = 1 2) are Riemannian 3-manifolds. We prove that the connection on M is completely determined by the requirement that the Bonan 4-form given in the work of Yasui and Ootsuka [Y. Yasui and T. Ootsuka Spin(7) holonomy manifold and superconnection Class. Quantum Gravity 18(2001)807-816] be closed. Assuming that the F-i are complete connected and simply connected it follows that they are isometric to S-3 with constant curvature k > 0 and the Yasui-Ootsuka solution is unique in the class of (3 + 3 + 2) warped-like product metrics admitting a specific Spin(7) structure. Crown Copyright (C) 2011 Published by Elsevier B.V. All rights reserved.
Citation Count: 18
Absolute configuration and biological profile of pyrazoline enantiomers as MAO inhibitory activity
(Wiley, 2019) Yelekçi, Kemal; Sarıgül, Sevgi; Bultinck, Patrick; Herrebout, Wouter; Doğan, İlknur; Yelekçi, Kemal; Uçar, Gülberk; Kelekçi, Nesrin Gökhan
A new racemic pyrazoline derivative was synthesized and resolved to its enantiomers using analytic and semipreparative high-pressure liquid chromatography. The absolute configuration of both fractions was established using vibrational circular dichroism. The in vitro monoamine oxidase (MAO) inhibitory profiles were evaluated for the racemate and both enantiomers separately for the two isoforms of the enzyme. The racemic compound and both enantiomers were found to inhibit hMAO-A selectively and competitively. In particular the R enantiomer was detected as an exceptionally potent and a selective MAO-A inhibitor (K-i = 0.85 x 10(-3) +/- 0.05 x 10(-3) mu M and SI: 2.35 x 10(-5)) whereas S was determined as poorer compound than R in terms of K-i and SI (0.184 +/- 0.007 and 0.001). The selectivity of the enantiomers was explained by molecular modeling docking studies based on the PDB enzymatic models of MAO isoforms.
Citation Count: 0
Abstraction in FPGA implementation of neural networks
(World Scientific and Engineering Academy and Society, 2008) Öğrenci, Arif Selçuk
A model for FPGA implementation of multilayer perceptron neural networks is presented. The model tries to incorporate object oriented design principles in the analysis training and design of components using hardware description languages. The synthesis will be based on the tools supplied by the FPGA vendors. The results indicate that the method can be utilized and it can be further improved to create a general methodology that bridges the gap between hardware and software in embedded system design.
Citation Count: 1
Accelerating Brain Simulations on Graphical Processing Units
(IEEE, 2015) Bozkuş, Zeki; El-Ghazawi, Tarek A.; Bozkuş, Zeki
NEural Simulation Tool(NEST) is a large scale spiking neuronal network simulator of the brain. In this work we present a CUDA(R) implementation of NEST. We were able to gain a speedup of factor 20 for the computational parts of NEST execution using a different data structure than NEST's default. Our partial implementation shows the potential gains and limitations of such possible port. We discuss possible novel approaches to be able to adapt generic spiking neural network simulators such as NEST to run on commodity or high-end GPGPUs.
Citation Count: 4
Accurate indoor positioning with ultra-wide band sensors
(Tubitak, 2020) Arsan, Taner
Ultra-wide band is one of the emerging indoor positioning technologies. In the application phase, accuracy and interference are important criteria of indoor positioning systems. Not only the method used in positioning, but also the algorithms used in improving the accuracy is a key factor. In this paper, we tried to eliminate the effects of off-set and noise in the data of the ultra-wide band sensor-based indoor positioning system. For this purpose, optimization algorithms and filters have been applied to the raw data, and the accuracy has been improved. A test bed with the dimensions of 7.35 m x 5.41 m and 50 cm x 50 cm grids has been selected, and a total of 27,000 measurements have been collected from 180 test points. The average positioning error of this test bed is calculated as 16.34 cm. Then, several combinations of algorithms are applied to raw data. The combination of Big Bang-Big Crunch algorithm for optimization, and then the Kalman Filter have yielded the most accurate results. Briefly, the average positioning error has been reduced from 16.34 cm to 7.43 cm.
Citation Count: 11
Accurate Refinement Of Docked Protein Complexes Using Evolutionary Information And Deep Learning
(Imperıal College Press, 2016) Akbal-Delibas, Bahar; Farhoodi, Roshanak; Pomplun, Marc; Haspel, Nurit
One of the major challenges for protein docking methods is to accurately discriminate native-like structures from false positives. Docking methods are often inaccurate and the results have to be refined and re-ranked to obtain native-like complexes and remove outliers. In a previous work we introduced AccuRefiner a machine learning based tool for refining protein-protein complexes. Given a docked complex the refinement tool produces a small set of refined versions of the input complex with lower root-mean-square-deviation (RMSD) of atomic positions with respect to the native structure. The method employs a unique ranking tool that accurately predicts the RMSD of docked complexes with respect to the native structure. In this work we use a deep learning network with a similar set of features and five layers. We show that a properly trained deep learning network can accurately predict the RMSD of a docked complex with 1.40 angstrom error margin on average by approximating the complex relationship between a wide set of scoring function terms and the RMSD of a docked structure. The network was trained on 35000 unbound docking complexes generated by RosettaDock. We tested our method on 25 different putative docked complexes produced also by RosettaDock for five proteins that were not included in the training data. The results demonstrate that the high accuracy of the ranking tool enables AccuRefiner to consistently choose the refinement candidates with lower RMSD values compared to the coarsely docked input structures.
Citation Count: 6
Achievable Performance of Bayesian Compressive Sensing Based Spectrum Sensing
(IEEE, 2014) Erküçük, Serhat; Erküçük, Serhat; Çırpan, Hakan Ali
In wideband spectrum sensing compressive sensing approaches have been used at the receiver side to decrease the sampling rate if the wideband signal can be represented as sparse in a given domain. While most studies consider the reconstruction of primary user's signal accurately it is indeed more important to analyze the presence or absence of the signal correctly. Furthermore these studies do not consider the achievable lower bounds of reconstruction error and how well the selected method performs correspondingly. Motivated by these issues we investigate in detail the primary user detection performance of Bayesian compressive sensing (BCS) approach in this paper. Accordingly we (i) determine the BCS signal reconstruction performance in terms of mean-square error (MSE) compression ratio and signal-to-noise ratio (SNR) and compare it with the conventionally used basis pursuit approach (ii) determine how well BCS performs compared with the Bayesian Cramer-Rao lower bound (BCRLB) of the signal reconstruction error and (iii) assess the probability of detection performance of BCS for various SNR and compression ratio values. The results of this study are important for determining the achievable performance of BCS based spectrum sensing.
Citation Count: 1
Across dimensions: Two- and three-dimensional phase transitions from the iterative renormalization-group theory of chains
(2020) Keçoğlu, İbrahim; Berker, A. Nihat
Sharp two- and three-dimensional phase transitional magnetization curves are obtained by an iterative renormalization-group coupling of Ising chains, which are solved exactly. The chains by themselves do not have a phase transition or nonzero magnetization, but the method reflects crossover from temperaturelike to fieldlike renormalization-group flows as the mechanism for the higher-dimensional phase transitions. The magnetization of each chain acts, via the interaction constant, as a magnetic field on its neighboring chains, thus entering its renormalization-group calculation. The method is highly flexible for wide application.
Citation Count: 4
Action Recognition Using Random Forest Prediction with Combined Pose-based and Motion-based Features
(IEEE, 2013) Ar, İlktan; Akgül, Yusuf Sinan
In this paper we propose a novel human action recognition system that uses random forest prediction with statistically combined pose-based and motion-based features. Given a set of training and test image sequences (videos) we first adopt recent techniques that extract low-level features: motion and pose features. Motion-based features which represent motion patterns in the consecutive images are formed by 3D Haar-like features. Pose-based features are obtained by the calculation of scale invariant contour-based features. Then using statistical methods we combine these low-level features to a novel compact representation which describes the global motion and the global pose information in the whole image sequence. Finally Random Forest classification is employed to recognize actions in the test sequences by using this novel representation. Our experimental results on KTH and Weizmann datasets have shown that the combination of pose-based and motion-based features increased the system recognition accuracy. The proposed system also achieved classification rates comparable to the state-of-the-art approaches.
Citation Count: 2
Active reconfigurable control of a submarine with indirect adaptive control
(2003) Kerestecioğlu, Feza; Kerestecioğlu, Feza
An indirect adaptive controller is designed for submersibles. The design is developed using a linearized MIMO model of a submarine. Standard recursive least squares estimation method is used to estimate the parameters. Depth and pitch angle of the submarine is controlled by means of the well-known indirect self-tuning method. In case of a system fault estimated parameters of the submarine model have been used to update the controller coefficients.
Citation Count: 0
Advanced signal processing algorithms for wireless communications
(Springer-Verlag Berlin, 2006) Panayırcı, Erdal; Çırpan, Hakan Ali
Traditional wireless technologies are not well suited to meet the extremely demanding requirements of providing the very high data rates with the ubiquity mobility and portability characteristic of cellular systems. Some fundamental barriers related to the nature of the radio channel as well as the limited bandwidth availability at the frequencies of interest stand in the way. Unique sets of efficient advanced signal processing algorithms and techniques is the one of the primary enablers that will allow lifting these limits primarily due to the impressive advent of low cost and low power digital signal processors. As an application of advanced signal processing techniques we will consider the solution of blind phase noise estimation and data detection problem via a computationally efficient sequential Monte Carlo (SMC) methodology in this paper.
Citation Count: 4
Agent-based Optimization to Estimate Nash Equilibrium in Power Markets
(Taylor & Francis Inc, 2013) Yücekaya, Ahmet; Valenzuela, Jorge
In most deregulated power markets firms bid daily into a day-ahead power market. The auction mechanism supply and demand determine the equilibrium at each hour. In this environment firms aim to maximize their revenues by carefully determining their bids. This requires the development of effective computational methods that help them estimate their competitors' behaviors under incomplete information. In this article an agent-based method that uses particle swarm optimization is described to simulate the behavior of market participants. Particle swarm optimization is used in the bidding process and an agent-based model is applied to find a Nash equilibrium. Different stopping conditions are used to determine the equilibrium. Experimental results are presented for two power systems.
Citation Count: 0
AHP-BASED APPROACH TO EVALUATE SOLAR POWER PLANT LOCATION ALTERNATIVES
(Intl Inst Social & Economic Sci, 2016) Ayağ, Zeki
Solar energy is the most readily available source of energy, and one of the most important sources of the renewable energy, because it is non-polluting and helps in lessening the greenhouse effect. Main problem of establishing a solar power plant is to determine its location. In the presence of many location alternatives and evaluation criteria, a multiple-criteria decision making problem arises. In this work, the location problem will be solved by using analytic hierarchy process (AHP) to figure out the most satisfying alternative. A numerical example is also included to show the proposed methodology in Turkey. . . . .
Citation Count: 0
An Alternative Approach To Design Lumped Element Delay Equalizers
(Istanbul Univ Fac Engineering, 2015) Şengül, Metin Y.
In this paper an algorithm has been proposed to design lumped element delay equalizers which is considered as a single block as opposed to the existing methods in literature. Then after obtaining the desired delay performance the designed delay equalizer is divided and realized as cascaded first-order and/or second-order all-pass circuits. An example is given to illustrate the utilization of the proposed algorithm.
Citation Count: 0
Alternative Transducer Power Gain Expression in Broadband Matching Network Designs
(IEEE, 2016) Şengül, Metin Y.
In this paper a reflection coefficient based transducer power gain expression has been derived which is an alternative to the impedance based expression exists in the literature. A broadband double matching problem is solved by using the derived gain expression and the obtained performance has been compared with the performance obtained via the existing expression.
Citation Count: 0
Amplitude and Frequency Modulations with Cellular Neural Networks
(Springer, 2015) Tander, Baran; Özmen, Atilla
Amplitude and frequency modulations are still the most popular modulation techniques in data transmission at telecommunication systems such as radio and television broadcasting gsm etc. However the architectures of these individual systems are totally different. In this paper it is shown that a cellular neural network with an opposite-sign template can behave either as an amplitude or a frequency modulator. Firstly a brief information about these networks is given and then the amplitude and frequency surfaces of the generated quasi-sine oscillations are sketched with respect to various values of their cloning templates. Secondly it is proved that any of these types of modulations can be performed by only varying the template components without ever changing their structure. Finally a circuit is designed simulations are presented and performance of the proposed system is evaluated. The main contribution of this work is to show that both amplitude and frequency modulations can be realized under the same architecture with a simple technique specifically by treating the input signals as template components.
Citation Count: 0
Analysis and Optimization of Matching Networks-I Getting Started with ADS
(Springer-Verlag Berlin, 2008) Şengül, Metin Y.
[Abstract Not Available]
Citation Count: 0
Analysis and Optimization of Matching Networks-II Getting Started with Microwave Office
(Springer-Verlag Berlin, 2008) Şengül, Metin Y.
[Abstract Not Available]
Citation Count: 1
An Analysis for the Use of Compressed Sensing Method in Microwave Imaging
(IEEE, 2017) Çalışkan, Cafer; Tekbaş, Mustafa; Ünal, İlhami; Erdoğan, Sercan; Çalışkan, Cafer
One of the most important problems encountered in microwave imaging methods is intensive data processing traffic that occurs when high resolution and real time tracking is desired. Radar signals can be recovered without loss of data with a randomly selected subset of the measurement data by compression sensing (CS) method which has been popular in recent years. For this reason, in this study, the use and capabilities of the CS method were investigated for tracking moving human, and the target information was correctly determined for the data obtained much below the Nyquist sampling criterion. In this study, it was revealed that the CS method can be developed for target detection and tracking

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