Electrical - Electronic Engineering / Elektrik - Elektronik Mühendisliği

Permanent URI for this collectionhttps://hdl.handle.net/11147/11

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2-D Thresholding of the Connectivity Map Following the Multiple Sequence Alignments of Diverse Datasets
(ACTA Press, 2013) Doğan, Tunca; Karaçalı, Bilge
Multiple sequence alignment (MSA) is a widely used method to uncover the relationships between the biomolecular sequences. One essential prerequisite to apply this procedure is to have a considerable amount of similarity between the test sequences. It's usually not possible to obtain reliable results from the multiple alignments of large and diverse datasets. Here we propose a method to obtain sequence clusters of significant intragroup similarities and make sense out of the multiple alignments containing remote sequences. This is achieved by thresholding the pairwise connectivity map over 2 parameters. The first one is the inferred pairwise evolutionary distances and the second parameter is the number of gapless positions on the pairwise comparisons of the alignment. Threshold curves are generated regarding the statistical parameter values obtained from a shuffled dataset and probability distribution techniques are employed to select an optimum threshold curve that eliminate as much of the unreliable connectivities while keeping the reliable ones. We applied the method on a large and diverse dataset composed of nearly 18000 human proteins and measured the biological relevance of the recovered connectivities. Our precision measure (0.981) was nearly 20% higher than the one for the connectivities left after a classical thresholding procedure displaying a significant improvement. Finally we employed the method for the functional clustering of protein sequences in a gold standard dataset. We have also measured the performance, obtaining a higher F-measure (0.882) compared to a conventional clustering operation (0.827).
Citation - Scopus: 1
3-D Switching Fabric Node Design
(ACTA Press, 2004) Dinleyici, Mehmet Salih; Akın, Osman
In this work we investigate an all-optical switching node that can be controlled by means of a transient grating, which is formed by interference of two Gaussian beams. This design considers 3-D architecture of switching fabrics.. real profile of Gaussian beams and fast switching time requirements. Four Wave Mixing (FWM) technique is applied in the evanescent field region of waveguide, showing chi((3)) nonlinearity. The formed grating is analysed by standart methods to obtain reflection coefficient and then coupling coefficient for power exchange between waveguides.
Active Eye-Glasses With Local Dimming
(Institute of Electrical and Electronics Engineers Inc., 2011) Özvural, Görkem; Gümüştekin, Şevket
The sense of sight provides the most reliable information about the environment. Although the human eye has a wide dynamic range for brightness adaptation, direct exposure to relatively bright light sources wipes out the total visual perception. The most remarkable example of this situation is driving a car at night, while the other cars are coming from the opposite lane with headlights on. In this work, we have proposed and developed a set of LCD equipped active glasses to solve this light adaptation problem. First, the location of the light sources are determined using an on board camera which is assembled in front of the glasses. After processing image data, the locations of the bright light sources are darkened and the disturbing effect of intense light sources is reduced. © 2011 Chamber of Turkish Electric.
Citation - Scopus: 2
Adaptive Bit Partitioning Strategy for Cell-Edge Users in Multi-Antenna Multicell Networks
(Institute of Electrical and Electronics Engineers Inc., 2011) Özbek, Berna; Le Ruyet, Didier
In this paper, we improve the performance of cell-edge users by applying adaptive bit partitioning for intercell interference cancelation in cooperative downlink multicell systems. The strategy for partitioning quantization bits between serving and interfering base stations affects the performance of the cooperative networks which is quite sensitive to the quality of the channel state information. The existing transmission strategies are based on the maximization of average cell rate which results in a reduced rate for the users in the cell-edge regions. We propose an adaptive bit partitioning strategy to improve the rate of cell-edge users at the same average feedback link rate. We show the performance of the cell-edge users is significantly increased while keeping the same average cell rate. © 2011 IEEE.
Citation - WoS: 1
Citation - Scopus: 7
The Adaptive Channel Estimation for Stbc-Ofdm Systems
(İstanbul Üniversitesi, 2005) Özbek, Berna; Yılmaz, Reyat
In this paper, we propose adaptive channel estimation methods based on LMS and RLS for orthogonal STBC-OFDM systems with three transmit antennas. The performance of the proposed algorithms is obtained in the frequency selective channels using Hiperlan/2 characteristics.
Citation - WoS: 43
Citation - Scopus: 48
Adaptive Control of Redundant Robot Manipulators With Sub-Task Objectives
(Cambridge University Press, 2009-10) Tatlıcıoğlu, Enver; Braganza, David; Burg, Timothy C.; Dawson, Darren M.
In this paper, adaptive control of kinematically redundant robot manipulators is considered. An end-effector tracking controller is designed and the manipulator's kinematic redundancy is utilized to integrate a general sub-task controller for self-motion control. The control objectives are achieved by designing a feedback linearizing controller that includes a least-squares estimation algorithm to compensate for the parametric uncertainties. Numerical simulation results are presented to show the validity of the proposed controller.
Citation - WoS: 15
Citation - Scopus: 20
Adaptive Control of Redundant Robot Manipulators With Sub-Task Objectives [proceedings Paper]
(Institute of Electrical and Electronics Engineers Inc., 2008) Tatlıcıoğlu, Enver; Braganza, David; Burg, Timothy C.; Dawson, Darren M.
In this paper, adaptive control of kinematically redundant robot manipulators is considered. An end-effector tracking controller is designed and the manipulator's kinematic redundancy is utilized to integrate a general sub-task controller for self-motion control. The control objectives are achieved by designing a feedback linearizing controller that includes a least-squares estimation algorithm to compensate for the parametric uncertainties.
Citation - Scopus: 5
Adaptive Limited Feedback for Intercell Interference Cancelation in Cooperative Downlink Multicell Networks
(Institute of Electrical and Electronics Engineers Inc., 2010) Özbek, Berna; Le Ruyet, Didier
In this paper, we evaluate intercell interference cancelation techniques in cooperative downlink multicell systems. We compare two classical beamforming strategies for the design of the beamforming vectors: maximum ratio combining precoding and partial zero-forcing. Since full channel state information at the transmission is unfeasible, we consider a limited feedback link and compare different strategies for bit partitioning of the feedback information for serving and interferer base stations. We propose a simple adaptive bit partitioning strategy to select an optimum transmission scheme at the base station. We show that the adaptive bit portioning algorithm is improved the sum capacity performance of the multicell networks significantly.
Citation - WoS: 6
Citation - Scopus: 9
Adaptive Limited Feedback Links for Cooperative Multi-Antenna Multicell Networks
(Springer Verlag, 2014) Özbek, Berna; Ruyet, Didier Le
The overall performance of cooperative networks is quite sensitive to channel state information (CSI) of serving and interfering base stations (BSs) and affected strongly by quality of limited feedback links. In this paper, we propose two adaptive limited feedback strategies for intercell interference cancelation in multi-antenna multicell networks. The first proposed strategy is developed to improve average multicell capacity assuming a fixed rate feedback link. This algorithm is based on adaptation of the number of bits to quantize CSI of serving and interfering BSs according to transmitter power and location of the user in its own cell. The second proposed strategy is designed in a way to increase average capacity of cell-edge users assuming an adaptive rate feedback link. This algorithm is based on the idea of allocating more bits to quantize CSI of users at cell-edge regions while allocating less bits for users near the serving BS. We illustrate performance of the proposed feedback links for downlink cooperative multi-antenna multicell networks in wireless channels.
Adaptive Limited Feedback Scheme for Stream Selection Based Interference Alignment in Heterogeneous Networks
(IEEE, 2016) Beyazıt, Esra Aycan; Özbek, Berna; Le Ruyet,D.
This paper presents a stream selection based interference alignment approach with imperfect channel state information for heterogeneous networks. The proposed algorithm performs the selection of a stream sequence among a predetermined set of sequences. Those selected sequences are the ones that mostly contribute to the sum rate when performing the exhaustive search. These stream sequences form a regular structure where the first stream is associated to a pico user. The effect of imperfect channel state information on the proposed algorithm is analyzed and a bit allocation scheme is proposed by deriving an upper bound on the rate loss due to quantization. © 2016 IEEE.
Citation - WoS: 6
Citation - Scopus: 8
Adaptive Output Tracking Control of a Surface Vessel
(Institute of Electrical and Electronics Engineers Inc., 2008) Lee, Dongbin; Tatlıcıoğlu, Enver; Burg, Timothy C.; Dawson, Darren M.
In this paper, the tracking control of a three degree-of-freedom marine vessel is examined. The novelty of this work is the transformation of the asymmetric inertia matrix into a symmetric, positive definite matrix. The asymmetry arises from the added mass common to practical surface vessels and creates a significant challenge for control design. The control design is further complicated by the parametric uncertainties in the dynamic model of the vessel. Two adaptive control schemes with a projection-based adaptation law are proposed: a full-state feedback controller and an output feedback controller. Both controllers are known to yield a uniformly ultimately bounded tracking result in the presence of parametric uncertainty. Numerical simulation results are shown to demonstrate the validity of the proposed controllers.
Citation - WoS: 4
Citation - Scopus: 7
Adaptive Reduced Feedback Links for Distributed Power Allocation in Multicell Miso-Ofdma Networks
(IEEE Computer Society, 2014-04) Özbek, Berna; Le Ruyet, Didier; Pischella, Mylene
For multi-antenna Orthogonal Frequency-Division Multiple Access (OFDMA) based multicell networks, the channel state information (CSI) of all users is required to share among base stations in order to perform distributed power allocation. However, the amount of feedback increases with the number of users, base stations, subcarriers and antennas. Therefore, it is important to perform a selection at the user side to reduce the feedback load and the complexity of resource allocation. In this letter, we propose adaptive reduced feedback links by choosing the users based on their approximate signal to interference noise ratio (SINR) and their locations in the cell to satisfy users' rate constraints. We illustrate the performance results of reduced feedback links by employing distributed resource allocation with link adaptation.
Citation - WoS: 2
Citation - Scopus: 5
Adaptive Resizer-Based Transfer Learning Framework for the Diagnosis of Breast Cancer Using Histopathology Images
(Springer, 2023) Düzyel, Okan; Çatal, Mehmet Sergen; Kayan, Ceyhun Efe; Sevinç, Arda; Gümüş, Abdurrahman
Breast cancer is a major global health concern, and early and accurate diagnosis is crucial for effective treatment. Recent advancements in computer-assisted prediction models have facilitated diagnosis and prognosis using high-resolution histopathology images, which provide detailed information on cancerous tissue. However, these high-resolution images often require resizing, leading to potential data loss. In this study, we demonstrate the effect of a learnable adaptive resizer for breast cancer classification using the BreakHis dataset. Our approach incorporates the adaptive resizer with various convolutional neural network models, including VGG16, VGG19, MobileNetV2, InceptionResnetV2, DenseNet121, DenseNet201, and EfficientNetB0. Despite producing visually less appealing images, the learnable resizer effectively improves classification performance. DenseNet201, when jointly trained with the adaptive resizer, achieves the highest accuracy of 98.96% for input images of 448x448 resolution. Our experimental results demonstrate that the adaptive resizer performs better at a magnification factor of 40x compared to higher magnifications. While its effectiveness becomes less pronounced as image resolution increases to 100x, 200x, and 400x, the adaptive resizer still outperforms bilinear interpolation. In conclusion, this study highlights the potential of adaptive resizers in enhancing performance for medical image classification. By outperforming traditional image resizing methods, our work contributes to the advancement of deep neural networks in the field of breast cancer diagnostics.
Citation - WoS: 6
Citation - Scopus: 11
Adaptive Resource Allocation for Multicast Ofdm Systems With Multiple Transmit Antennas
(Institute of Electrical and Electronics Engineers Inc., 2006) Özbek, Berna; Le Ruyet, Didier; Khiari, Hajer
We evaluate the impact of multiple transmit antennas on the performance of multicast OFDM systems by proposing a suboptimal low complexity algorithm. Associated with a powerful erasure code, it is possible to increase the data rate of multicast OFDM systems by selecting for each subcarrier to the users with a good channel condition. We show that the resource allocation which includes the precoding vector selection, subcarrier allocation and bit loading is a difficult optimization problem. We propose a suboptimal algorithm to solve this problem by avoiding the optimization to reduce complexity. When the users are not symmetrically distributed around the base station, we add a fair scheduler to guarantee that each user receives the same amount of data. We present simulation results where we compare the proposed multicast systems with the classical multicast OFDM systems. When the users are symmetrically distributed around the base station, the gain is rather small, whereas when the users are non-symmetrically distributed, the proposed algorithm outperforms OFDM systems with subcarrier allocation.
Citation - WoS: 2
Citation - Scopus: 2
Adaptive Resource Allocation for Sdma-Ofdma Systems With Genetic Algorithm
(Institute of Electrical and Electronics Engineers Inc., 2009) Özbek, Berna; Le Ruyet, Didier
In this paper, we propose an adaptive resource allocation algorithm to maximize the sum data rate for spatial division multiplexing access (SDMA) orthogonal division multiple access (OFDMA) systems using genetic algorithm. We perform Zero forcing (ZF) beamforming at the transmitter constructing single and multiple beams for OFDMA systems with multiple transmit antennas. In order to reduce the complexity and convergence time of genetic algorithm (GA), we present an initial condition obtained by allocating the user to the subcarrier with maximum precoding gain. The proposed algorithm reduces the complexity without sacrificing the performance. We obtain the simulation results and compare them with the classical static and adaptive allocation methods. We show that the GA with the proposed initial condition increases the sum data rate compared to classical GA and reduces the convergence time significantly for SDMA-OFDMA systems.
Citation - WoS: 19
Citation - Scopus: 22
Adaptive Sign Algorithm for Graph Signal Processing
(Elsevier, 2022-06) Yan, Yi; Kuruoğlu, Ercan Engin; Altınkaya, Mustafa Aziz
Efficient and robust online processing techniques for irregularly structured data are crucial in the current era of data abundance. In this paper, we propose a graph/network version of the classical adaptive Sign algorithm for online graph signal estimation under impulsive noise. The recently introduced graph adaptive least mean squares algorithm is unstable under non-Gaussian impulsive noise and has high computational complexity. The Graph-Sign algorithm proposed in this work is based on the minimum dispersion criterion and therefore impulsive noise does not hinder its estimation quality. Unlike the recently proposed graph adaptive least mean pth power algorithm, our Graph-Sign algorithm can operate without prior knowledge of the noise distribution. The proposed Graph-Sign algorithm has a faster run time because of its low computational complexity compared to the existing adaptive graph signal processing algorithms. Experimenting on steady-state and time-varying graph signals estimation utilizing spectral properties of bandlimitedness and sampling, the Graph-Sign algorithm demonstrates fast, stable, and robust graph signal estimation performance under impulsive noise modeled by alpha stable, Cauchy, Student's t, or Laplace distributions.
Citation - WoS: 4
Citation - Scopus: 4
Adaptive Visual Servo Regulation Control for Camera-In Configuration With a Fixed Camera Extension
(ACTA Press, 2009) Tatlıcıoğlu, Enver; Dawson, Darren M.; Xian, B.
In this paper, image-based regulation control of a robot manipulator with an uncalibrated vision system is discussed. To compensate for the unknown camera calibration parameters, a novel prediction error formulation is presented. To achieve the control objectives, a Lyapunov-based adaptive control strategy is employed. The control development for the camera-in-hand problem is presented in detail and a fixed-camera problem is included as an extension.
Citation - Scopus: 5
Adaptive Visual Servo Regulation Control for Camera-In Configuration With a Fixed Camera Extension
(Institute of Electrical and Electronics Engineers Inc., 2007) Tatlıcıoğlu, Enver; Dawson, Darren M.; Xian, B.
In this paper, image-based regulation control of a robot manipulator with an uncalibrated vision system is discussed. To compensate for the unknown camera calibration parameters, a novel prediction error formulation is presented. To achieve the control objectives, a Lyapunov-based adaptive control strategy is employed. The control development for the camera-in-hand problem is presented in detail and a fixed-camera problem is included as an extension.
Algıda gecikme ve kısa-ömürlü senkronizasyon temelli yeni bir hayali motor aktivite tanıma yaklaşımı
(IEEE, 2023) Olcay, B. Orkan; Karaçalı, Bilge
This study proposes a novel approach for investigating a brain-computer interface that considers the temporal organization of brain activity, explicitly accounting for perception latency. To this end, we aligned the onset of task periods with the concurrence of left parietal and parieto-occipital electrodes to obtain the timings of perception latencies. Then, activity-specific synchronization timings between channel pairs were calculated using the time-aligned task periods. The perception latency and activity-specific synchronization timings were subsequently used for feature extraction and classification. The proposed approach achieved significantly better performance when comparing the proposed approach with the method that did not account for the perception latency
All-Optical Switching Based on Grating Written Photorefractive Slab/Fiber Waveguide Coupler
(Institute of Electrical and Electronics Engineers Inc., 2002) Dinleyici, Mehmet Salih
Since all optical switching is a key element for all kinds of optical networks, great amount of works have been dedicated either for material researches or various waveguide structures. Generally speaking the switching time of devices based on photorefractive effect are rather slow for today's high capacity optical fiber networks. In the field of waveguide architecture various geometries have been proposed and investigated for grating assisted or guided optical coupling for the purpose of designing all-optical switch, adddrop multiplexers, filters etc.

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