Karakaya, Ziya

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Profile URL
https://hdl.handle.net/20.500.14411/8509
Name Variants
Karakaya, Z
K.,Ziya
Ziya, Karakaya
K., Ziya
Z., Karakaya
Karakaya,Z.
Karakaya, Ziya
Z.,Karakaya
Job Title
Doktor Öğretim Üyesi
Email Address
ziya.karakaya@atilim.edu.tr
Main Affiliation
Computer Engineering
Status
Former Staff
Website
ORCID ID
Scopus Author ID
Turkish CoHE Profile ID
Google Scholar ID
WoS Researcher ID

Sustainable Development Goals

5

GENDER EQUALITY
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0

Research Products

14

LIFE BELOW WATER
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1

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10

REDUCED INEQUALITIES
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0

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3

GOOD HEALTH AND WELL-BEING
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1

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2

ZERO HUNGER
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0

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9

INDUSTRY, INNOVATION AND INFRASTRUCTURE
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2

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16

PEACE, JUSTICE AND STRONG INSTITUTIONS
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0

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11

SUSTAINABLE CITIES AND COMMUNITIES
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8

DECENT WORK AND ECONOMIC GROWTH
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13

CLIMATE ACTION
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4

QUALITY EDUCATION
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6

CLEAN WATER AND SANITATION
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0

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1

NO POVERTY
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15

LIFE ON LAND
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0

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17

PARTNERSHIPS FOR THE GOALS
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7

AFFORDABLE AND CLEAN ENERGY
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12

RESPONSIBLE CONSUMPTION AND PRODUCTION
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This researcher does not have a Scopus ID.
This researcher does not have a WoS ID.
Scholarly Output

41

Articles

3

Views / Downloads

12/0

Supervised MSc Theses

13

Supervised PhD Theses

2

WoS Citation Count

78

Scopus Citation Count

98

WoS h-index

4

Scopus h-index

5

Patents

0

Projects

0

WoS Citations per Publication

1.90

Scopus Citations per Publication

2.39

Open Access Source

4

Supervised Theses

15

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JournalCount
UBMK 2018 - 3rd International Conference on Computer Science and Engineering -- 3rd International Conference on Computer Science and Engineering, UBMK 2018 -- 20 September 2018 through 23 September 2018 -- Sarajevo -- 1435604
3rd International Conference on Computer Science and Engineering (UBMK) -- SEP 20-23, 2018 -- Sarajevo, BOSNIA & HERCEG3
2017 International Conference on Computer and Applications, ICCA 2017 -- 2017 International Conference on Computer and Applications, ICCA 2017 -- 6 September 2017 through 7 September 2017 -- Doha -- 1315022
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) -- 7th International Conference on Computational Science, ICCS 2007 -- 27 May 2007 through 30 May 2007 -- Beijing -- 708232
2017 International Conference on Computer Science and Engineering (UBMK) -- OCT 05-08, 2017 -- Antalya, TURKEY1
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Now showing 1 - 10 of 26
  • Thumbnail Image
    Conference Object
    Citation - Scopus: 2
    Big Data on Cloud for Government Agencies: Benefits, Challenges, and Solutions
    (Assoc Computing Machinery, 2018) Rashed, Alaa Hussain; Karakaya, Ziya; Yazici, Ali
    Big Data and Cloud computing are the most important technologies that give the opportunity for government agencies to gain a competitive advantage and improve their organizations. On one hand, Big Data implementation requires investing a significant amount of money in hardware, software, and workforce. On the other hand, Cloud Computing offers an unlimited, scalable and on-demand pool of resources which provide the ability to adopt Big Data technology without wasting on the financial resources of the organization and make the implementation of Big Data faster and easier. The aim of this study is to conduct a systematic literature review in order to collect data to identify the benefits and challenges of Big Data on Cloud for government agencies and to make a clear understanding of how combining Big Data and Cloud Computing help to overcome some of these challenges. The last objective of this study is to identify the solutions for related challenges of Big Data. Four research questions were designed to determine the information that is related to the objectives of this study. Data is collected using literature review method and the results are deduced from there.
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    Citation - WoS: 6
    Jmathnorm: a Database Normalization Tool Using Mathematica
    (Springer-verlag Berlin, 2007) Yazici, Ali; Karakaya, Ziya
    This paper is about designing a complete interactive tool, named JMathNorm, for relational database (RDB) normalization using Mathematica. It is an extension of the prototype developed by the same authors [1] with the inclusion of Second Normal Form (2NF), and Boyce-Codd Normal Form (BCNF) in addition to the existing Third normal Form (3NF) module. The tool developed in this study is complete and can be used for real-time database design as well as an aid in teaching fundamental concepts of DB normalization to students with limited mathematical background. JMathNorm also supports interactive use of modules for experimenting the fundamental set operations such as closure, and full closure together with modules to obtain the minimal cover of the functional dependency set and testing an attribute for a candidate key. JMathNorm's GUI interface is written in Java and utilizes Mathematica's Mink facility to drive the Mathematica kernel.
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    Citation - Scopus: 7
    Normalizing relational database schemas using mathematica
    (Springer Verlag, 2006) Yazici,A.; Karakaya,Z.
    In this paper, basic relational database (DB) normalization algorithms are implemented efficiently as Mathematica modules. It was observed that, Mathematica provided a straightforward platform as opposed to previous ones, mainly Prolog based tools which required complex data structures such as linked list representations with pointers. A Java user interface called JMath-Norm was designed to execute the Mathematica modules in a systematic way. For this purpose, Mathematical Java link facility (JLink) is utilized to drive the Mathematica kernel. JMath-Norm provides an effective interactive tool in an educational setting for teaching DB normalization theory. © Springer-Verlag Berlin Heidelberg 2006.
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    Citation - Scopus: 25
    A Comparison of Stream Processing Frameworks
    (Institute of Electrical and Electronics Engineers Inc., 2017) Karakaya,Z.; Yazici,A.; Alayyoub,M.
    This study compares the performance of Big Data Stream Processing frameworks including Apache Spark, Flink, and Storm. Also, it measures the resource usage and performance scalability of the frameworks against a varying number of cluster sizes. It has been observed that, Flink outperforms both Spark and Storm under equal constraints. However, Spark can be optimized to provide the higher throughput than Flink with the cost of higher latency. © 2017 IEEE.
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    Citation - Scopus: 4
    Software engineering issues in big data application development
    (Institute of Electrical and Electronics Engineers Inc., 2017) Karakaya,Z.
    Big Data has become one of the most important concepts that is being studied in Computer/Software Engineering. The data produced in recent years have increased rapidly and exponentially, necessitating the solution of major problems such as the collection, processing and storage of huge volume of data. Big Data Frameworks are developed specifically to solve these problems that facilitates application developers by providing opportunities to collect, process, manage, monitor and analyze these data. A few examples of these frameworks are Hadoop, Spark, Storm, and Flink, which are developed by Software Engineers as open source projects. Although the challenges raised from coordination of IT resources such as huge amounts of computation power, storage area, memory, and network bandwidth in a distributed manner solved by these frameworks, there still remains many Software Engineering problems in application development phase, even if they based on these frameworks. High scalability, fault tolerance, flexibility, reliability and testability can be listed as the main issues need to be carefully considered in terms of Software Engineering. In this paper, we first clarify the terms Framework-Application, and then the overview information about Big Data and related frameworks are given before emphasizing the problems arising in terms of Software Engineering. Nevertheless, we tried to provide guidance to the people who would develop software for Big Data and tried to give the further research guidance. © 2017 IEEE.
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    Citation - WoS: 4
    Citation - Scopus: 3
    Systematic Mapping Study on Performance Scalability in Big Data on Cloud Using Vm and Container
    (Springer-verlag Berlin, 2016) Gokhan, Cansu; Karakaya, Ziya; Yazici, Ali
    In recent years, big data and cloud computing have gained importance in IT and business. These two technologies are becoming complementing in a way that the former requires large amount of storage and computation power, which are the key enabler technologies of Big Data; the latter, cloud computing, brings the opportunity to scale on-demand computation power and provides massive quantities of storage space. Until recently, the only technique used in computation resource utilization was based on the hypervisor, which is used to create the virtual machine. Nowadays, another technique, which claims better resource utilization, called "container" is becoming popular. This technique is otherwise known as "lightweight virtualization" since it creates completely isolated virtual environments on top of underlying operating systems. The main objective of this study is to clarify the research area concerned with performance issues using VM and container in big data on cloud, and to give a direction for future research.
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    Article
    Citation - WoS: 15
    Citation - Scopus: 17
    A Parallel Boundary Element Formulation for Tracking Multiple Particle Trajectories in Stoke's Flow for Microfluidic Applications
    (Tech Science Press, 2015) Karakaya, Z.; Baranoglu, B.; Cetin, B.; Yazici, A.; Computer Engineering; Software Engineering
    A new formulation for tracking multiple particles in slow viscous flow for microfluidic applications is presented. The method employs the manipulation of the boundary element matrices so that finally a system of equations is obtained relating the rigid body velocities of the particle to the forces applied on the particle. The formulation is specially designed for particle trajectory tracking and involves successive matrix multiplications for which SMP (Symmetric multiprocessing) parallelisation is applied. It is observed that present formulation offers an efficient numerical model to be used for particle tracking and can easily be extended for multiphysics simulations in which several physics involved.
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    Citation - Scopus: 4
    Need for a Software Development Methodology for Research-Based Software Projects
    (Institute of Electrical and Electronics Engineers Inc., 2018) Cereci,I.; Karakaya,Z.
    Software development is mostly carried by a group of individuals. Software development methodologies are heavily utilized to organize these individuals and keep track of the entire software development process. Although previously proposed software development methodologies meet the needs of the industry and the firms, they are not usually suitable for research-based software projects that are carried by universities and individual researchers. In this paper, we aim to show the necessity of a new software development methodology for research-based problems carried by universities. The literature review will show the differences between industry and university software projects from certain aspects. These findings will be supported by the authors own research on the area. This qualitative research involves collecting data through interviews and applying Grounded Theory to better understand the development process. © 2018 IEEE.
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    Citation - Scopus: 2
    Changing Our Educational Institutions: Transition From Traditional To E-Learning Programs
    (2004) Yazici,A.; Karakaya,Z.; Dalgarno,B.; Altas,I.
    In this paper we examine basic elements of e-Learning, the features of the e-Learning model under implementation at Atilim University and the expected impact of the model on the organization of the institution. The paper also draws on examples at other institutions in discussing the issues that form the dynamics of organizational change within Universities in the 21st century. © 2004 IEEE.
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    Citation - WoS: 2
    Need for a Software Development Methodology for Research-Based Software Projects
    (Ieee, 2018) Cereci, Ibrahim; Karakaya, Ziya
    Software development is mostly carried by a group of individuals. Software development methodologies are heavily utilized to organize these individuals and keep track of the entire software development process. Although previously proposed software development methodologies meet the needs of the industry and the firms, they are not usually suitable for research-based software projects that are carried by universities and individual researchers. In this paper, we aim to show the necessity of a new software development methodology for research-based problems carried by universities. The literature review will show the differences between industry and university software projects from certain aspects. These findings will be supported by the authors own research on the area. This qualitative research involves collecting data through interviews and applying Grounded Theory to better understand the development process.