Bilgisayar Mühendisliği Bölümü Koleksiyonu

Permanent URI for this collectionhttps://hdl.handle.net/20.500.12469/45

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Citation - Scopus: 6
Using Machine Learning Classifiers To Identify the Critical Proteins in Down Syndrome
(Association for Computing Machinery, 2018) Kulan, Handan; Dağ, Tamer
Pharmacotherapies of intellectual disability (ID) are largely unknown as the abnormalities at the complex molecular level which causes ID are difficult to understand. Down syndrome (DS) which is the prevalent cause of ID and caused by an extra copy of the human chromosome21 (Hsa21) has been investigated on protein levels by using the Ts65Dn mouse model of DS which are orthologs of %50 of Hsa21 classical protein coding genes. Recent works have applied the classification methods to understand critical factors in DS as it is believed that the problem was naturally related to classification problem since the determination of proteins discriminatory between classes of mice was required. In this study we apply forward feature selection method to identify correlated proteins and their interactions in DS. After identification we report supervised learning model of expression levels of selected proteins in order to understand the critical proteins for diagnosing and explaining DS. The proposed technique depicts optimum classification results achieved by optimizing parameters with grid search. When compared with the former work our classification results give higher accuracy. © 2018 Association for Computing Machinery.
Citation - WoS: 14
Citation - Scopus: 19
Channel Estimation for Tds-Ofdm Systems in Rapidly Time-Varying Mobile Channels
(IEEE-Inst Electrical Electronics Engineers Inc, 2018) Başaran, Mehmet; Şenol, Habib; Erküçük, Serhat; Çırpan, Hakan Ali
This paper explores the performance of time-domain synchronous orthogonal frequency-division multiplexing (TDS-OFDM) systems operated under rapidly time-varying mobile channels. Since a rapidly time-varying channel contains more unknown channel coefficients than the number of observations, the mobile channel can conveniently be modeled with the discrete Legendre polynomial basis expansion model to reduce the number of unknowns. The linear minimum mean square error (LMMSE) estimate can be exploited for channel estimation on inter-block-interference-free received signal samples owing to transmitting pseudo-noise (PN) sequences. In conventional TDS-OFDM systems, the channel estimation performance is limited due to estimating channel responses only from the beginning part of the channel. Therefore, a new system model named "partitioned TDS-OFDM system" is proposed to improve the system performance by inserting multiple PN sequences to the middle and end parts of the channel as well. In addition to providing the reconstruction error performance, Bayesian Cramer-Rao lower hound is derived analytically. Also, the LMMSE-based symbol detection is employed. To alleviate the negative effects of inter-carrier-interference (ICI) occuring in mobile channels, ICI cancellation is applied to enhance the detection performance. The simulation results demonstrate that the proposed TDS-OFDM system is superior to the conventional system and its corresponding performance is able to approach the achievable lower performance bound.
Joint Phase Noise Estimation And Source Detection [ortak Faz Gürültüsü Kestirimi ve Kaynak Sezimlemesi]
(2010) Kaleli, Burç Arslan; Şenol, Habib; Panayırcı, Erdal
Rapidly time-varying and random disturbing effects on the phase of a signal waveform are known as phase noise. In this paper we consider the problem of joint detection of continuous-valued information source output and estimation of a phase noise by using expectation maximization (EM) algorithm. In order to estimate phase noise initial phase noise values are determined by cubic interpolation that utilizes pilot symbols. Computer simulations are performed for the proposed algorithm and the average mean square error (MSE) - signal to noise ratio (SNR) performance of source detector and phase noise estimator is presented for each iteration of the algorithm. Moreover average MSE - pilot spacing performance curves of phase noise estimator are given for various SNR values. ©2010 IEEE.
New Generation Android Operating System-Basedmobile Application: Rss/News Reader
(Springer Verlag, 2015) Arsan, Taner; Erşahin, Mehmet Arif; Alp, Ebru
RSS (Rich Site Summary)/News Reader is a web-based Android OS application developed by using PhoneGap framework. HTML5 CSS and JavaScript are basically used for implementation instead of native Android programming language. This application has a production process like a web application because it is actually a fully working web program which is wrapped by PhoneGap framework. This means the application could be used on almost every mobile platform with making some basic arrangements.RSS/News Reader mobile application takes advantage of both flexibility of web design and built-in features of the device it is installed. This combination provides a complete mobile application which eliminates the need to use different native languages with its hybrid form. This hybrid structure makes mobile programming faster and easier to implement.In this new generation operating system-based mobile application a combination of PhoneGap framework HTML5 CSS3 JavaScript jQuery Mobile Python and Django is used for implementation. © Springer International Publishing Switzerland 2015.
Citation - WoS: 3
Citation - Scopus: 3
Transmitter Source Location Estimation Using Crowd Data
(Pergamon-Elsevier Science Ltd, 2018) Öğrenci, Arif Selçuk; Arsan, Taner
The problem of transmitter source localization in a dense urban area has been investigated where a supervised learning approach utilizing neural networks has been adopted. The cellular phone network cells and signals have been used as the test bed where data are collected by means of a smart phone. Location and signal strength data are obtained by random navigation and this information is used to develop a learning system for cells with known base station location. The model is applied to data collected in other cells to predict their base station locations. Results are consistent and indicating a potential for effective use of this methodology. The performance increases by increasing the training set size. Several shortcomings and future research topics are discussed. (C) 2017 Elsevier Ltd. All rights reserved.
Citation - WoS: 1
An Analysis for the Use of Compressed Sensing Method in Microwave Imaging
(IEEE, 2017) Yiğit, Enes; 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
Citation - WoS: 1
Citation - Scopus: 1
Hybrid Mpi Plus Upc Parallel Programming Paradigm on an Smp Cluster
(TUBITAK Scientific & Technical Research Council Turkey, 2012) Bozkuş, Zeki
The symmetric multiprocessing (SMP) cluster system which consists of shared memory nodes with several multicore central processing units connected to a high-speed network to form a distributed memory system is the most widely available hardware architecture for the high-performance computing community. Today the Message Passing Interface (MPI) is the most widely used parallel programming paradigm for SMP clusters in which the MPI provides programming both for an SMP node and among nodes simultaneously. However Unified Parallel C (UPC) is an emerging alternative that supports the partitioned global address space model that can be again employed within and across the nodes of a cluster. In this paper we describe a hybrid parallel programming paradigm that was designed to combine MPI and UPC programming models. This paradigm's objective is to mix the MPI's data locality control and scalability strengths with UPC's fine-grain parallelism and ease of programming to achieve multiple-level parallelism at the SMP cluster which itself has multilevel parallel architecture. Utilizing a proposed hybrid model and comparing MPI-only to UPC-only implementations this paper presents a detailed description of Cannon's algorithm benchmark application with performance results of a random-access benchmark and the Barnes-Hut N-Body simulation. Experiments indicate that the hybrid MPI+UPC model can significantly provide performance increases of up to double in comparison with UPC-only implementation and up to 20% increases in comparison to MPI-only implementation. Furthermore an optimization was achieved that improved the hybrid performance by an additional 20%.
Citation - WoS: 1
Citation - Scopus: 5
Optimizing Neuron Brain Simulator With Remote Memory Access on Distributed Memory Systems
(Institute of Electrical and Electronics Engineers Inc., 2016) Shehzad, Danish; Bozkuş, Zeki
The Complex neuronal network models require support from simulation environment for efficient network simulations. To compute the models increasing complexity necessitated the efforts to parallelize the NEURON simulation environment. The computational neuroscientists have extended NEURON by dividing the equations for its subnet among multiple processors for increasing the competence of hardware. For spiking neuronal networks inter-processor spikes exchange consume significant portion of overall simulation time on parallel machines. In NEURON Message Passing Interface (MPI) is used for inter processor spikes exchange MPI-Allgather collective operation is used for spikes exchange generated after each interval across distributed memory systems. However as the number of processors become larger and larger MPI-Allgather method become bottleneck and needs efficient exchange method to reduce the spike exchange time. This work has improved MPI-Allgather method to Remote Memory Access (RMA) based on MPI-3.0 for NEURON simulation environment MPI based on RMA provides significant advantages through increased communication concurrency in consequence enhances efficiency of NEURON and scaling the overall run time for the simulation of large network models.1 © 2015 IEEE.
Citation - WoS: 13
Citation - Scopus: 18
Strategic Early Warning System for the French Milk Market: a Graph Theoretical Approach To Foresee Volatility
(Elsevier, 2017) Bisson, Christophe; Diner, Öznur Yaşar
This paper presents a new approach for developing a Strategic Early Warning System aiming to better detect and interpret weak signals. We chose the milk market as a case study in line with the recent call from the EU Commission for governance tools which help to better address such highly volatile markets. Furthermore on the first of April 2015 the new Common Agricultural Policy ended quotas for milk which led to a milk crisis in the EU. Thus we collaborated with milk experts to get their inputs for a new model to analyse the competitive environment. Consequently we constructed graphs to represent the major factors that affect the milk industry and the relationships between them. We obtained several network measures for this social network such as centrality and density. Some factors appear to have the largest major influence on all the other graph elements while others strongly interact in cliques. Any detected changes in any of these factors will automatically impact the others. Therefore scanning ones competitive environment can allow an organisation to get an early warning to help it avoid an issue (as much as possible) and/or seize an opportunity before its competitors. We conclude that Strategic Early Warning Systems as a corporate foresight approach utilising graph theory can strengthen the governance of markets. (C) 2017 Elsevier Ltd. All rights reserved.
Citation - Scopus: 3
First Impressions on Social Network Sites: Impact of Self-Disclosure Breadth on Attraction
(Academic Conferences and Publishing International Limited, 2017) Baruh, Lemi; Cemacılar, Zeynep; Bisson, Christophe; Chisik, Yoram I.
This paper reports the results of two experiments that investigate the relationship between the quantity of information disclosed on an SNS profile and profile viewers' first impressions of the profile owner. Both experiments utilized a 2 (low quantity of information vs. high quantity of information) by 2 (male vs. female profile) design. In the first experiment (n = 1059), the respondents were randomly assigned to the experimental conditions. The results showed that profile viewers were more favorable to profiles of women. Also, both for female and male SNS profiles, higher quantity of information led to more positive ratings of the profile owner. The second experiment expanded the findings from the first experiment in two ways. First, in the second experiment (n = 320), rather than being randomly assigned to the profile gender condition, the respondents could pick the gender of the profile they would review. Second, informed by previous research on face to face interactions which indicate that quantity of self-disclosure can increase interpersonal attraction by reducing the level of uncertainty about relational outcomes, we tested whether uncertainty reduction mediated the relationship between quantity of information presented in an SNS profile and interpersonal attraction. Female profiles were selected more often than male profiles by both female and male respondents; however, there was no difference in interpersonal attraction ratings that male and female profiles received. Higher quantity of information presented in an SNS profile had a significant impact on interpersonal attraction. The results from the second experiment also indicated that while quantity of information positively influenced profile viewers' perceptions regarding the agreeableness of the profile owner, it did not have an impact on viewers' perceptions regarding the dependability of the profile owner. As predicted, the impact of quantity of information on interpersonal attraction was mediated by a reduction in uncertainty levels.
Citation - WoS: 1
Citation - Scopus: 1
Partitioning 3-Arcs Into Steiner Triple Systems
(Wiley, 2017) Çalışkan, Cafer
In this article it is shown that there is a partitioning of the set of 3-arcs in a projective plane of order three into nine pairwise disjoint Steiner triple systems of order 13.
Citation - WoS: 1
Citation - Scopus: 1
A Framework for Combined Recognition of Actions and Objects
(Springer-Verlag Berlin, 2012) Ar, İlktan; Akgül, Yusuf Sinan
This paper proposes a novel approach to recognize actions and objects within the context of each other. Assuming that the different actions involve different objects in image sequences and there is one-to-one relation between object and action type we present a Bayesian network based framework which combines motion patterns and object usage information to recognize actions/objects. More specifically our approach recognizes high-level actions and the related objects without any body-part segmentation hand tracking and temporal segmentation methods. Additionally we present a novel motion representation based on 3D Haar-like features which can be formed by depth color or both images. Our approach is also appropriate for object and action recognition where the involved object is partially or fully occluded. Finally experiments show that our approach improves the accuracy of both action and object recognition significantly.
Citation - WoS: 1
Joint Channel Estimation and Equalization for Ofdm Based Broadband Communications in Rapidly Varying Mobile Channels
(IEEE, 2010) Şenol, Habib; Poor, H. Vincent
This paper is concerned with the challenging and timely problem of channel estimation for orthogonal frequency division multiplexing (OFDM) systems in the presence of frequency selective and very rapidly time varying channels. In OFDM systems operating over rapidly time-varying channels the orthogonality between subcarriers is destroyed leading to inter-carrier interference (ICI) and resulting in an irreducible error floor. The band-limited discrete cosine serial expansion of low-dimensionality is employed to represent the time-varying channel. In this way the resulting reduced dimensional channel coefficients are estimated iteratively with tractable complexity and independently of the channel statistics. The algorithm is based on the expectation maximization-maximum a posteriori probability (EM-MAP) technique leading to a receiver structure that also yields the equalized output using the channel estimates. The pilot symbols are employed to estimate the initial coefficients effectively and unknown data symbols are averaged out in the algorithm in a non-data-aided fashion. It is shown that the computational complexity of the proposed algorithm to estimate the channel coefficients and to generate the equalized output as a by-product is similar to O(N) per detected symbol N being the number of OFDM subcarriers. Computational complexity as well as computer simulations carried out for the systems described in WiMAX and LTE standards indicate that it has significant performance and complexity advantages over existing suboptimal channel estimation and equalization algorithms proposed earlier in the literature.
Fully Decentralized, Collaborative Multilateration Primitives for Uniquely Localizing Wsns
(Springer, 2009) Cakiroglu, Arda; Erten, Cesim
We provide primitives for uniquely localizing WSN nodes. The goal is to maximize the number of uniquely localized nodes assuming a fully decentralized model of computation. Each node constructs a cluster of its own and applies unique localization primitives on it. These primitives are based on constructing a special order for multilaterating the nodes within the cluster. The proposed primitives are fully collaborative and thus the number of iterations required to compute the localization is fewer than that of the conventional iterative multilateration approaches. This further limits the messaging requirements. With relatively small clusters and iteration counts we can localize almost all the uniquely localizable nodes. © 2009 Springer Berlin Heidelberg.
Citation - WoS: 1
Citation - Scopus: 2
Data-Aided Autoregressive Sparse Channel Tracking for Ofdm Systems
(IEEE, 2016) Buyuksar, Ayse Betul; Şenol, Habib; Erküçük, Serhat; Cirpan, Hakan Ali
In order to meet future communication system requirements channel estimation over fast fading and frequency selective channels is crucial. In this paper Space Alternated Generalized Expectation Maximization Maximum a Posteriori (SAGE-MAP) based channel estimation algorithm is proposed for Orthogonal Frequency Division Multiplexing (OFDM) systems for Autoregressive (AR) modeled time-varying sparse channels. Also an initialization algorithm has been developed from the widely used sparse approximation algorithm Orthogonal Matching Pursuit (OMP) since the performance of SAGE algorithm strictly depends on initialization. The results show that multipath delay positions can be tracked successfully for every time instant using the proposed SAGE-MAP based approach.
An Energy Efficient Routing Algorithm (x-Centric Routing) for Sensor Networks
(INT INST Informatics & Systemics, 2011) Ataç, Göktuğ; Dağ, Tamer
Recent developments in wireless communications and electronics technologies have enabled the progress in low cost sensor networks. Sensor networks differ from traditional networks in several ways such as the severe energy constraints redundant low-rate date and many-to-one flows that the sensor networks require. One of the major challenges facing the design of a routing protocol for Wireless Sensor Networks (WSNs) is to find the most reliable path between the sources and the sink node by considering the energy awareness as an essential design parameter. This paper introduces a new routing protocol called as X-Centric routing by considering the above parameters. Under the X-Centric routing the decision making mechanism depends on the capacity of the sink node by switching between address-centric routing (AC-Routing) and data-centric routing (DC-Routing). The design tradeoffs between energy and communication overhead savings in these routing algorithms have been considered by considering the advantages and performance issues of each routing algorithm.
Citation - WoS: 4
Citation - Scopus: 6
Ask me: A Question Answering System via Dynamic Memory Networks
(Institute of Electrical and Electronics Engineers Inc., 2019) Yiğit, Gülsüm; Amasyalı, Mehmet Fatih
Most of the natural language processing problems can be reduced into a question answering problem. Dynamic Memory Networks (DMNs) are one of the solution approaches for question answering problems. Based on the analysis of a question answering system built by DMNs described in [1], this study proposes a model named DMN∗ which contains several improvements on its input and attention modules. DMN∗ architecture is distinguished by a multi-layer bidirectional LSTM (Long Short Term Memory) architecture on input module and several changes in computation of attention score in attention module. Experiments are conducted on Facebook bAbi dataset [2]. We also introduce Turkish bAbi dataset, and produce increased vocabulary sized tasks for each dataset. The experiments are performed on English and Turkish datasets and the accuracy performance results are compared by the work described in [1]. Our evaluation shows that the proposed model DMN∗ obtains improved accuracy performance results on various tasks for both Turkish and English.
Importance of Regional Differences in Brain Throughout Aging for Down Syndrome
(Association for Computing Machinery, 2018) Kulan, Handan; Dağ, Tamer
Down syndrome (DS) which affects approximately one in 700 live births is caused by an extra copy of the long arm of human chromosome 21 (HSA21). Statistical analysis has been done for understanding the protein expression profiles based on age and sex differences in DS. In addition there are ongoing research efforts for comprehending expression patterns based on different brain regions. However little is known about the mechanisms of expression differences in brain regions throughout aging. Insights into these mechanisms are required to understand the susceptibility of distinct brain regions to neuronal insults with aging. Dissection of this selective vulnerability will be critical to our understanding of DS. By extracting information from the critical proteins which take part in the mechanism of the molecular pathways the diagnosis of DS can become easier. Also understanding the molecular pathways can contribute to develop effective drugs for the treatment of DS. In this work forward feature selection technique is applied for determining the protein subsets for old and young mice datasets which consist of the expression profiles across different brain regions. When these subsets are analyzed it is observed that selected proteins play important roles in the processes such as mTOR signaling pathway AD MAPK signaling pathway and apoptosis. We believe that the subsets of protein selected in our work can be utilized to understand the process of DS and can be used to develop age-related effective drugs.
Citation - Scopus: 4
A Software Architecture for Inventory Management System
(2013) Arsan, Taner; Başkan, Emrah; Ar, Emrah; Bozkuş, Zeki
Inventory Management is one of the basic problems in almost every company. Before computer age and integration paper tables and paperwork solutions were being used as inventory management tools. These we very far from being a solution took so much time even needed employees just for this section of organization. There was no an efficient solution available in the many companies during these days. Every process was based on paperwork human fault rate was high the process and the tracing the inventory losses were not possible and there was no efficient logging systems. After the computer age every process is started to be integrated into electronic environment. And now we have qualified technology to implement new solutions to these problems. Software based systems bring the advantages of having the most efficient control with less effort and employees. These developments provide new solutions for also inventory management systems in this context. In this paper a new solution for Inventory Management System (IMS) is designed and implemented. Most importantly this system is designed for Kadir Has University and used as Inventory Management System. © 2013 Springer Science+Business Media.
Citation - WoS: 4
Citation - Scopus: 6
Channel Estimation for Realistic Indoor Optical Wireless Communication in Aco-Ofdm Systems
(Springer, 2018) Özmen, Atilla; Şenol, Habib
In this paper channel estimation problem in a visible light communication system is considered. The information data is transmitted using asymmetrical clipped optical orthogonal frequency division multiplexing. Channel estimation and symbol detection are performed by the Maximum Likelihood and the Linear Minimum Mean Square Error detection techniques respectively. The system performance is investigated in realistic environment that is simulated using an indoor channel model. Two different channels are produced using the indoor channel model. Symbol error rate (SER) performance of the system with estimated channels is presented for QPSK and 16-QAM digital modulation types and compared with the perfect channel state information. As a mean square error (MSE) performance benchmark for the channel estimator Cramer-Rao lower bound is also derived. MSE and SER performances of the simulation results are presented.

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