Bilgisayar Mühendisliği Bölümü Koleksiyonu

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

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Citation - WoS: 1
Citation - Scopus: 1
Orthogonal Projection and Liftings of Hamilton-Decomposable Cayley Graphs on Abelian Groups
(Elsevier Science Bv, 2013) Alspach, Brian; Çalışkan, Cafer; Kreher, Donald L.
In this article we introduce the concept of (p alpha)-switching trees and use it to provide sufficient conditions on the abelian groups G and H for when CAY (G x H
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.
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: 12
Citation - Scopus: 15
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.
A Location-Based Movie Advisor Application for Android Devices
(Springer Verlag, 2015) Arsan, Taner; Çayır, Aykut; Umur, Hande Nur; Güney, Tacettin Dogacan; Panya, Büke
Android is one of the world’s most popular mobile platforms. There are more than 600000 applications available today’s market place. Movie advisor applications are also available in Google Play but there is no location-based movie advisor application for Android devices in Google Play and any other marketplace. A Location-Based Service is a mobile computing application that provides information and functionality to users based on their geographical location. In this study a location-based movie advisor which is a special application for Android devices to find nearest movie theaters is developed and implemented. Android devices are getting smarter with new features. By using these devices we can use new technologies and new ideas. Location-based services are one of these ideas. Wherever you are you can search and find new possibilities for almost everything. The aim of the location-based movie advisor application for Android devices is to give a brief summary about movies movie times and also nearest location information of the movie theaters depending on the location of the user. © Springer International Publishing Switzerland 2015.
Rapidly Varying Sparse Channel Tracking With Hybrid Kalman-Omp Algorithm
(Springer, 2019) Büyükşar, Ayşe Betül; Şenol, Habib; Erküçük, Serhat; Cirpan, Hakan Ali
It is expected from future communication standards that channel estimation algorithms should be able to operate over very fast varying frequency selective channel models. Therefore in this study autoregressive (AR) modeled fast varying channel has been considered and tracked with Kalman filter over one orthogonal frequency division multiplexing (OFDM) symbol. Channel sparsity is exploited which decreases the complexity requirements of the Kalman algorithm. Since Kalman filter is not directly applicable to sparse channels orthogonal matching pursuit (OMP) algorithm is modified for AR modeled sparse signal estimation. Also by using windows sparsity detection errors have been decreased. The simulation results showed that sparse fast varying channel can be tracked with the proposed hybrid Kalman-OMP algorithm and windowing method offers improved MSE results.

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