Ahmet Arif AYDIN, PhD

Department of Computer Science, Inonu University


Refereed Journal Publications

J.3 A. A. Aydin and K. M. Anderson, “Data modelling for large-scale social media analytics : design challenges and lessons learned” in International Journal of Data Mining, Modelling, Management, vol. 12, no. 4, pp. 386–414, 2020. DOI: 10.1504/IJDMMM.2020.111409 ( Scopus,(E-SCI) )
J.2 Ahmet Arif Aydin “Prominent quality attributes of crisis software systems: a literature review” in TURKISH JOURNAL OF ELECTRICAL ENGINEERING & COMPUTER SCIENCES. 2020. DOI:10.3906/elk-1911-5 (SCI-E)
J.1 Mario Barrenechea, Sahar Jambi, Ahmet Arif Aydin, Mazin Hakeem, and Kenneth M Anderson “ Getting the Query Right for Crisis Informatics Design Issues for Web-Based Analysis Environments” in Journal of Web Engineering. 2017. (SCI-E)

Refereed Conference/Symposium Publications

C.9 H. M. Erzİ and A. A. Aydin, "IoT Based Mobile Smart Home Surveillance Application," in 2020 4th International Symposium on Multidisciplinary Studies and Innovative Technologies (ISMSIT), Istanbul, Turkey, 2020, pp. 1-5, doi: 10.1109/ISMSIT50672.2020.9255303.
C.8 T. B. Doğuç and A. A. Aydın, "CAP-based Examination of Popular NoSQL Database Technologies in Streaming Data Processing," in 2019 International Artificial Intelligence and Data Processing Symposium (IDAP), Malatya, Turkey, 2019, pp. 1-6.
C.7 Ahmet Arif Aydin “An Overview of Quality Attributes for Data Intensive Systems in Crisis Informatics” in IDAP 2017, International Symposium on Artificial Intelligence and Data Processing, 2017.
C.6 Ahmet Arif Aydin and Kenneth M. Anderson “Batch to Real-Time: Incremental Data Collection & Analytics Platform” in Hawaii International Conference on System Sciences, 10 pages. January 2017.
C.5 Mario Barrenechea, Kenneth M Anderson, Ahmet Arif Aydin, Mazin Hakeem, Sahar Jambi, “Getting the Query Right: User Interface Design of Analysis Platforms for Crisis Research,” in 15th International Conference on Web Engineering (ICWE 2015), pp. 547-564, June 23-26, 2015.
C.4 Ahmet Arif Aydin and Kenneth M. Anderson, “Incremental Sorting for Large Dynamic Data Sets,” in First IEEE International Conference on Big Data Computing Service and Applications, pp. 170-175, March 31-April 2, 2015.
C.3 Kenneth M. Anderson, Ahmet Arif Aydin, Mario Barrenechea, Adam Cardenas, Mazin Hakeem, and Sahar Jambi, “Design Challenges/Solutions for Environments Supporting the Analysis of Social Media Data in Crisis Informatics Research,” in 48th Hawaii International Conference on System Sciences, pp. 163–172, January 2015.
C.2 Ahmet Arif Aydin and Gita Alaghband, “Sequential & Parallel Hybrid Approach for Non-Recursive Most Significant Digit Radix Sort,” in 10th Int. Conf. on Applied Computing, pp. 51–58, October 2013.
C.1 Ahmet Arif Aydin and Gita Alaghband, “Performance Benchmarking Of Sequential, Parallel And Hybrid Radix Sort Algorithms and Analyzing Impact Of Sub Vectors, Created On Each Level, On Hybrid Msd Radix Sort’s Runtime” in 15th Annual Research and Creative Activities Symposium, pp. 40, April 2012.(Poster Presentation)

Ph.D. Dissertation

Abstract Everyday, enormous amounts of data are generated by a wide variety of computational systems. This data needs to be collected, stored, and analyzed to generate insights and information useful to the organizations performing this work. Typical workflows include consumer behavior interpretation, product recommendations, predicting future trends, and even support for emergency management before, during, and after mass emergency events. In the emergency management space, a new area of study—crisis informatics—examines how members of the public make use of social media during times of disaster. Crisis informatics software aims to collect and analyze the large amount of information generated on social media during times of mass emergency. In general, current crisis informatics software is focused on the batch processing of crisis data after an event has transitioned out of the immediate response and recovery phases. Now, there is a need to collect and analyze crisis data in real-time as it is streaming in during the crisis event itself. This thesis offers an examination of the software architectures, techniques, frameworks, and middleware that are needed to augment crisis informatics software that make use of batch processing techniques to perform data analysis with those that incrementally process, store, and analyze data as it arrives. This thesis work responds to the desires of analysts who need access to real-time data analytics and efficient batch data processing techniques to comprehensively analyze a mass emergency event. The techniques developed to achieve these goals have been implemented in a system called the Incremental Data Collection and Analytics Platform (IDCAP). This platform enables a comprehensive evaluation of the utility of these techniques. The system provides the following features: incremental data collection and indexing in real-time of social media data; support for real-time analytics at interactive speeds; highly concurrent batch data processing supported by a novel data model; and a front-end web client, known as the IDCA App, that allows an analyst to manage IDCAP resources, to monitor incoming data in real- time, and to provide an interface that allows incremental queries to be performed on top of large datasets.
Committee Members Kenneth M. Anderson (Chair), Judith Stafford, Richard Han, Qin Lv, and Gita Alaghband.

M.Sc. Thesis

Abstract This study is about the importance of sorting and parallelism in numerous scientific fields. Sorting is one of the most studied problems in the Computer Science field. The goal of the studies is decreasing sorting time, which relates to saving power and money. Meanwhile, parallelism is also another vital field which appeals to Scientists in order to run their operations fast. The main goal of the project is implementing alternative sequential versions of Radix Sort Algorithm. We also have parallel versions of these sequential versions which are suitable to parallelize. In the first phase of the project, Sequential Least Significant Digit (LSD) Radix Sort versions are implemented. After that, Parallel LSD radix sort versions are implemented with different synchronization constructs, Critical Section and Lock Routine, and different scheduling methods, static, dynamic, and guided, to analyze their impact on the running time. In the second phase of the project, sequential, parallel, and hybrid versions of the Most Significant Digit (MSD) Radix Sort versions are implemented. First, Sequential MSD1 Radix Sort version is implemented which is an alternative implementation of Traditional Recursive MSD Radix Sort Algorithm. After that, we come up with parallel version of MSD1 Radix Sort. Finally, Hybrid versions of MSD Radix Sort are implemented which utilize Quicksort Algorithm.
Committee Members Gita Alaghband(Chair),Tom Altman,Ellen Gethner and lkyeun Ra.