Karakaya, Ziya

Profile Picture
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

NO POVERTY1
NO POVERTY
0
Research Products
ZERO HUNGER2
ZERO HUNGER
0
Research Products
GOOD HEALTH AND WELL-BEING3
GOOD HEALTH AND WELL-BEING
1
Research Products
QUALITY EDUCATION4
QUALITY EDUCATION
0
Research Products
GENDER EQUALITY5
GENDER EQUALITY
0
Research Products
CLEAN WATER AND SANITATION6
CLEAN WATER AND SANITATION
0
Research Products
AFFORDABLE AND CLEAN ENERGY7
AFFORDABLE AND CLEAN ENERGY
0
Research Products
DECENT WORK AND ECONOMIC GROWTH8
DECENT WORK AND ECONOMIC GROWTH
0
Research Products
INDUSTRY, INNOVATION AND INFRASTRUCTURE9
INDUSTRY, INNOVATION AND INFRASTRUCTURE
2
Research Products
REDUCED INEQUALITIES10
REDUCED INEQUALITIES
0
Research Products
SUSTAINABLE CITIES AND COMMUNITIES11
SUSTAINABLE CITIES AND COMMUNITIES
0
Research Products
RESPONSIBLE CONSUMPTION AND PRODUCTION12
RESPONSIBLE CONSUMPTION AND PRODUCTION
0
Research Products
CLIMATE ACTION13
CLIMATE ACTION
0
Research Products
LIFE BELOW WATER14
LIFE BELOW WATER
1
Research Products
LIFE ON LAND15
LIFE ON LAND
0
Research Products
PEACE, JUSTICE AND STRONG INSTITUTIONS16
PEACE, JUSTICE AND STRONG INSTITUTIONS
0
Research Products
PARTNERSHIPS FOR THE GOALS17
PARTNERSHIPS FOR THE GOALS
0
Research Products
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

Patents

0

Projects

0

WoS Citations per Publication

1.90

Scopus Citations per Publication

2.39

Open Access Source

4

Supervised Theses

15

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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Author: Yazici,A.End date: 2019

Scholarly Output Search Results

Now showing 1 - 9 of 9
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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 - Scopus: 11
    Jmathnorm: a Database Normalization Tool Using Mathematica
    (Springer Verlag, 2007) Yazici,A.; Karakaya,Z.
    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 JLink facility to drive the Mathematica kernel. © Springer-Verlag Berlin Heidelberg 2007.
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    Informatics Engineering Education in Turkey and Expectations of Software Industry;
    (Institute of Electrical and Electronics Engineers Inc., 2018) Yazici,A.; Mishra,A.; Karakaya,Z.; Ustunkok,T.
    In this study, using the ÖSYM data, the number of intakes in Informatics Engineering programs in Turkey, accreditation data and the medium of instruction of the program are summarized for the years 2016 and 2017. In addition, the software sector's expectations from the informatics engineering graduates are reassessed based on the academic studies. The developed knowledge-skill gap set was used to evaluate the situation in Turkish informatics engineering programs. Sector expectations are discussed in the context of 2017-2019 Turkey Software Sector Strategy and Action Plan prepared by the Ministry of Science, Industry and Technology of Turkey and some proposals are made for the academia. As a result, it was observed that the expectations of the software industry were similar in all studies. Additionally, the expectations were changed in the direction of developing technologies and this change should be reflected in the informatics engineering programs. © 2018 IEEE.
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    Perceptions, Expectations and Implementations of Big Data in Public Sector : Kamuda Buÿük Veri: Alglar, Beklentiler Ve Uygulamalar
    (Institute of Electrical and Electronics Engineers Inc., 2018) Dogdu,E.; Ozbayoglu,M.; Yazici,A.; Karakaya,Z.
    Big Data is one of the most commonly encountered buzzwords among IT professionals nowadays. Technological advancements in data acquisition, storage, telecommunications, embedded systems and sensor technologies resulted in huge inflows of streaming data coming from variety of sources, ranging from financial streaming data to social media tweets, or wearable health gadgets to drone flight logs. The processing and analysis of such data is a difficult task, but as appointed by many IT experts, it is crucial to have a Big Data Implementation plan in today's challenging industry standards. In this study, we performed a survey among IT professionals working in the public sector and tried to address some of their implementation issues and their perception of Big Data today and their expectations about how the industry will evolve. The results indicate that most of the public sector professionals are aware of the current Big Data requirements, embrace the Big Data challenge and are optimistic about the future. © 2018 IEEE.
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    Jmathnorm: a Database Normalization Tool Using Mathematica
    (Springer Verlag, 2007) Yazici,A.; Karakaya,Z.
    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 JLink facility to drive the Mathematica kernel. © Springer-Verlag Berlin Heidelberg 2007.
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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: 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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    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: 2
    Systematic Mapping for Big Data Stream Processing Frameworks
    (Institute of Electrical and Electronics Engineers Inc., 2016) Alayyoub,M.; Yazıcı, Ali; Yazici,A.; Karakaya,Z.; Karakaya, Ziya; Yazıcı, Ali; Karakaya, Ziya; Software Engineering; Computer Engineering; Software Engineering; Computer Engineering
    There has been lots of discussions about the choice of a stream processing framework (SPF) for Big Data. Each of the SPFs has different cutting edge technologies in their steps of processing the data in motion that gives them a better advantage over the others. Even though, the cutting edge technologies used in each stream processing framework might better them, it is still hard to say which framework bests the rest under different scenarios and conditions. In this study, we aim to show trends and differences about several SPFs for Big Data by using the Systematic Mapping (SM) approach. To achieve our objectives, we raise 6 research questions (RQs), in which 91 studies that conducted between 2010 and 2015 were evaluated. We present the trends by classifying the research on SPFs with respect to the proposed RQs which can help researchers to obtain an overview of the field. © 2016 IEEE.