Bozkuş, Zeki

Bozkuş, Zeki

Name Variants

Bozkuş, Zeki
Z.,Bozkuş
Z. Bozkuş
Zeki, Bozkuş
Bozkus, Zeki
Z.,Bozkus
Z. Bozkus
Zeki, Bozkus
Bozkus,Z.

Job Title

Doç. Dr.

Email Address

Zekı.bozkus@khas.edu.tr

Main Affiliation

Computer Engineering

Status

Former Staff

Full item page

Sustainable Development Goals Report Points

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Scholarly Output

30

Articles

7

Citation Count

0

Supervised Theses

9 Scholarly Output Search Results

Now showing 1 - 10 of 29

Citation - Scopus: 10
Big Data Platform Development With a Domain Specific Language for Telecom Industries
(IEEE Computer Society, 2013) Senbalci,C.; Arsan, Taner; Altuntas,S.; Bozkuş, Zeki; Bozkus,Z.; Arsan,T.; Computer Engineering
This paper introduces a system that offer a special big data analysis platform with Domain Specific Language for telecom industries. This platform has three main parts that suggests a new kind of domain specific system for processing and visualization of large data files for telecom organizations. These parts are Domain Specific Language (DSL), Parallel Processing/Analyzing Platform for Big Data and an Integrated Result Viewer. In addition to these main parts, Distributed File Descriptor (DFD) is designed for passing information between these modules and organizing communication. To find out benefits of this domain specific solution, standard framework of big data concept is examined carefully. Big data concept has special infrastructure and tools to perform for data storing, processing, analyzing operations. This infrastructure can be grouped as four different parts, these are infrastructure, programming models, high performance schema free databases, and processing-analyzing. Although there are lots of advantages of Big Data concept, it is still very difficult to manage these systems for many enterprises. Therefore, this study suggest a new higher level language, called as DSL which helps enterprises to process big data without writing any complex low level traditional parallel processing codes, a new kind of result viewer and this paper also presents a Big Data solution system that is called Petaminer. © 2013 IEEE.
Use of Machine Learning Techniques for Diagnosis of Thyroid Glang Disorder
(Kadir Has Üniversitesi, 2016) Mofek, İzdihar A.B. El; Bozkuş, Zeki; Bozkuş, Zeki; Computer Engineering
The advancements of computer technologies have generated an incredible amount of data and information from numerous sources. Nowadays, the way of implementing health care are being changing by utilizing the benefits of advancements in computer technologies. It is believed that engineering this amount of data can assist in developing predictive tool that can help physicians to diagnosing and predicting some debilitating life-threatening illness such as thyroid gland disease. Our current work focuses on investigating python languages to diagnose thyroid gland disease based on machine learning, and involves developing a new tool to predict the diagnoses of thyroid gland diseases, which we have called as a MLTDD (Machine Learning App for thyroid Disease Diagnosis). MLTDD has been designed with Qt designer and programmed using PyDev, which is python IDE for Eclipse. MLTDD could diagnose with 99.81% accuracy. Decision tree algorithm has been used to create the ML model, in addition to training dataset to learn from. ML model can be used to get predictions on new data for which you do not know the target and that is what we did to predict the diagnosis of thyroid gland disease as a hyperthyroidism or hypothyroidism or a normal condition using CRT decision tree algorithm. MLTDD can minify the cost, the waiting time, and help physicians for more research, as well as decrease the errors and mistakes that can be made by humans on account of exhaustion and tiredness.
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; Bozkuş, Zeki; Computer Engineering
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 - Scopus: 8
GPU accelerated molecular docking simulation with genetic algorithms
(Springer Verlag, 2016) Bozkuş, Zeki; Bozkus,Z.; Fraguela,B.B.; Computer Engineering
Receptor-Ligand Molecular Docking is a very computationally expensive process used to predict possible drug candidates for many diseases. A faster docking technique would help life scientists to discover better therapeutics with less effort and time. The requirement of long execution times may mean using a less accurate evaluation of drug candidates potentially increasing the number of false-positive solutions, which require expensive chemical and biological procedures to be discarded. Thus the development of fast and accurate enough docking algorithms greatly reduces wasted drug development resources, helping life scientists discover better therapeutics with less effort and time. In this article we present the GPU-based acceleration of our recently developed molecular docking code. We focus on offloading the most computationally intensive part of any docking simulation, which is the genetic algorithm, to accelerators, as it is very well suited to them. We show how the main functions of the genetic algorithm can be mapped to the GPU. The GPU-accelerated system achieves a speedup of around ~ 14x with respect to a single CPU core. This makes it very productive to use GPU for small molecule docking cases. © Springer International Publishing Switzerland 2016.
Citation - WoS: 0
Citation - Scopus: 0
Optimizing Neuron Simulation Environment Using Remote Memory Access With Recursive Doubling on Distributed Memory Systems
(Hindawi Ltd, 2016) Shehzad, Danish; Bozkuş, Zeki; Bozkuş, Zeki; Computer Engineering
Increase in complexity of neuronal network models escalated the efforts to make NEURON simulation environment efficient. The computational neuroscientists divided the equations into subnets amongst multiple processors for achieving better hardware performance. On parallel machines for neuronal networks interprocessor spikes exchange consumes large section of overall simulation time. In NEURON for communication between processors Message Passing Interface (MPI) is used. MPI Allgather collective is exercised for spikes exchange after each interval across distributed memory systems. The increase in number of processors though results in achieving concurrency and better performance but it inversely affects MPI Allgather which increases communication time between processors. This necessitates improving communication methodology to decrease the spikes exchange time over distributed memory systems. This work has improved MPI Allgather method using Remote Memory Access (RMA) by moving two-sided communication to one-sided communication and use of recursive doubling mechanism facilitates achieving efficient communication between the processors in precise steps. This approach enhanced communication concurrency and has improved overall runtime making NEURON more efficient for simulation of large neuronal network models.
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; Bozkuş, Zeki; Computer Engineering
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%.
Big Data Platform Development With a Telecom Dsl
(Kadir Has Üniversitesi, 2013) Senbalci, Cuneyt; Bozkuş, Zeki; Bozkuş, Zeki; Computer Engineering
The amount of data in our world has shown exponential growth in recent years. This creates a very large collection of data sets –so called big data- in many organizations. Enterprises want to process their own big data to generate values from data to improve productivity innovation and customer relationship better than their competitors. However big data is so large and complex that it becomes difficult to process using traditional database management techniques. in this paper we present a system which can be used to analyses for big data of telecom industries. -- Abstract'tan.
Citation - WoS: 0
Software for Brain Network Simulations: a Comparative Study (vol 11, 46, 2017)
(Frontiers Media Sa, 2018) Tikidji-Hamburyan, Ruben A.; Bozkuş, Zeki; Narayana, Vikram; Bozkus, Zeki; El-Ghazawi, Tarek A.; Computer Engineering
[No Abstract Available]
Citation - WoS: 1
Citation - Scopus: 2
Analytical Expense Management System
(IEEE, 2009) Bozkuş, Zeki; Arsan, Taner; Bisson, Christophe; Bozkuş, Zeki; Arsan, Taner; A. Bısson, Chrıstophe Louıs; Management Information Systems; Computer Engineering
Although the development of communication technologies (e.g: UMTS ADSL) allowed the elaboration of multiple users' web applications (e.g. information storage) there are still many improvements on many applications to be done and uncovered areas. Expense management systems on web application area are still in their infancy. Expense management software is widely spread in companies and most of time supported by their intranet. These solutions are quite simple as they mainly collect the information related to the expenses and may propose a simple aggregation of these figures. The result is close to what an excel sheet provides.
Implementation of Information Technology Infrastructure Library (itil) Processes
(Kadir Has Üniversitesi, 2011) Odabaşı, Selma Yilmaz; Bozkuş, Zeki; Bozkuş, Zeki; Computer Engineering
Several frameworks tools and standards have been included in iT management systems in organizations such as COBiT CMMS. These days iT management is focusing particularly on the de facto standard iTiL for implementing iT service management. The information Technology infrastructure Library (iTiL) is a public framework that describes good practices in iT service management. it has been drawn from both the public and private sectors internationally. iTiL helps organizations to become aware of the business value their iT services provide to internal and external stakeholders. This thesis describes iT Service Management the history and components of iTiL. in addition it contains a case study about analyzing some processes of iTiL for a technology company which has 500 employees all over Turkey headquarter located in istanbul. We implemented six iTiL process steps in this company. We described the implementation details steps and Key Performance indicators (KPi) for each of these processes. in this work incident Management Configuration Management Problem Management Change Management and Service Level Management processes were implemented and the KPis of these processes with other benefits and performance results were reported. -- Abstarct.