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Article Citation - WoS: 8Citation - Scopus: 10Evaluation of Ten Open-Source Eye-Movement Classification Algorithms in Simulated Surgical Scenarios(Ieee-inst Electrical Electronics Engineers inc, 2019) Dalveren, Gonca Gokce Menekse; Cagiltay, Nergiz ErcilDespite providing several insights into visual attention and evidence regarding certain brain states and psychological functions, classifying eye movements is a highly demanding process. Currently, there are several algorithms to classify eye movement events which use different approaches. However, to date, only a limited number of studies have assessed these algorithms under specific conditions, such as those required for surgical training programmes. This study presents an investigation of ten open-source eye-movement classification algorithms using the Eye Tribe eye-tracker. The algorithms were tested on the eye-movement records obtained from 23 surgical residents, who performed computer-based surgical simulation tasks under different hand conditions. The aim was to offer data for the improvement of surgical training programmes. According to the results, due to the different classification methods and default threshold values, the ten algorithms produced different results. Considering the fixation duration, the only common event for all of the investigated algorithms, the binocular-individual threshold (BIT) algorithm resulted in a different clustering compared to the other algorithms. Based on the other set of common events, three clusters were determined by eight algorithms (except BIT and event detection (ED)), distinguishing dispersion-based, velocity-based and modified versions of velocity-based algorithms. Accordingly, it was concluded that dispersion-based and velocity-based algorithms provided different results. Additionally, as it individually specifies the threshold values for the eye-movement data, when there is no consensus about the threshold values to be set, the BIT algorithm can be selected. Especially for such cases like simulation-based surgical skill-training, the use of individualised threshold values in the BIT algorithm can be more beneficial in classifying the raw eye data and thus evaluating the individual progress levels of trainees based on their eye movement behaviours. In conclusion, the threshold values had a critical effect on the algorithm results. Since default values may not always be suitable for the unique features of different data sets, guidelines should be developed to indicate how the threshold values are set for each algorithm.Article Citation - WoS: 17Citation - Scopus: 22Seven Principles of Instructional Content Design for a Remote Laboratory: a Case Study on Errl(Ieee-inst Electrical Electronics Engineers inc, 2011) Cagiltay, Nergiz Ercil; Aydin, Elif; Aydin, Cansu Cigdem; Kara, Ali; Alexandru, MarianThis paper discusses the results of a study of the requirements for developing a remote radio frequency (RF) laboratory for electrical engineering students. It investigates students' preferred usage of the technical content of a state-of-the-art RF laboratory. The results of this study are compared to previous findings, which dealt with other user groups (technicians in technical colleges and engineers in the RF domain). Based on the results of these analyses, seven essential principles for designing and developing such a laboratory were identified. As a case study, these principles were then implemented into a remote laboratory system. In this paper, the implementation examples are also provided and discussed. The primary aim of this study is to guide remote laboratory platform developers toward the most effective instructional design. This study also determined, from the remote laboratory system case study, what the requirements are of such a laboratory from the students' perspective.Article Citation - WoS: 20Citation - Scopus: 25Detecting Latent Topics and Trends in Software Engineering Research Since 1980 Using Probabilistic Topic Modeling(Ieee-inst Electrical Electronics Engineers inc, 2022) Gurcan, Fatih; Dalveren, Gonca Gokce Menekse; Cagiltay, Nergiz Ercil; Soylu, AhmetThe landscape of software engineering research has changed significantly from one year to the next in line with industrial needs and trends. Therefore, today's research literature on software engineering has a rich and multidisciplinary content that includes a large number of studies; however, not many of them demonstrate a holistic view of the field. From this perspective, this study aimed to reveal a holistic view that reflects topics, trends, and trajectories in software engineering research by analyzing the majority of domain-specific articles published over the last 40 years. This study first presents an objective and systematic method for corpus creation through major publication sources in the field. A corpus was then created using this method, which includes 44 domain-specific conferences and journals and 57,174 articles published between 1980 and 2019. Next, this corpus was analyzed using an automated text-mining methodology based on a probabilistic topic-modeling approach. As a result of this analysis, 24 main topics were found. In addition, topical trends in the field were revealed. Finally, three main developmental stages of the field were identified as: the programming age, the software development age, and the software optimization age.Article Citation - WoS: 90Citation - Scopus: 132Big Data Software Engineering: Analysis of Knowledge Domains and Skill Sets Using Lda-Based Topic Modeling(Ieee-inst Electrical Electronics Engineers inc, 2019) Gurcan, Fatih; Cagiltay, Nergiz ErcilSoftware engineering is a data-driven discipline and an integral part of data science. The introduction of big data systems has led to a great transformation in the architecture, methodologies, knowledge domains, and skills related to software engineering. Accordingly, education programs are now required to adapt themselves to up-to-date developments by first identifying the competencies concerning big data software engineering to meet the industrial needs and follow the latest trends. This paper aims to reveal the knowledge domains and skill sets required for big data software engineering and develop a taxonomy by mapping these competencies. A semi-automatic methodology is proposed for the semantic analysis of the textual contents of online job advertisements related to big data software engineering. This methodology uses the latent Dirichlet allocation (LDA), a probabilistic topic-modeling technique to discover the hidden semantic structures from a given textual corpus. The output of this paper is a systematic competency map comprising the essential knowledge domains, skills, and tools for big data software engineering. The findings of this paper are expected to help evaluate and improve IT professionals' vocational knowledge and skills, identify professional roles and competencies in personnel recruitment processes of companies, and meet the skill requirements of the industry through software engineering education programs. Additionally, the proposed model can be extended to blogs, social networks, forums, and other online communities to allow automatic identification of emerging trends and generate contextual tags.Article Citation - WoS: 26Citation - Scopus: 36Exploratory Analysis of Topic Interests and Their Evolution in Bioinformatics Research Using Semantic Text Mining and Probabilistic Topic Modeling(Ieee-inst Electrical Electronics Engineers inc, 2022) Gurcan, Fatih; Cagiltay, Nergiz ErcilBioinformatics, which has developed rapidly in recent years with the collaborative contributions of the fields of biology and informatics, provides a deeper perspective on the analysis and understanding of complex biological data. In this regard, bioinformatics has an interdisciplinary background and a rich literature in terms of domain-specific studies. Providing a holistic picture of bioinformatics research by analyzing the major topics and their trends and developmental stages is critical for an understanding of the field. From this perspective, this study aimed to analyze the last 50 years of bioinformatics studies (a total of 71,490 articles) by using an automated text-mining methodology based on probabilistic topic modeling to reveal the main topics, trends, and the evolution of the field. As a result, 24 major topics that reflect the focuses and trends of the field were identified. Based on the discovered topics and their temporal tendencies from 1970 until 2020, the developmental periods of the field were divided into seven phases, from the "newborn" to the "wisdom" stages. Moreover, the findings indicated a recent increase in the popularity of the topics "Statistical Estimation", "Data Analysis Tools", "Genomic Data", "Gene Expression", and "Prediction". The results of the study revealed that, in bioinformatics studies, interest in innovative computing and data analysis methods based on artificial intelligence and machine learning has gradually increased, thereby marking a significant improvement in contemporary analysis tools and techniques based on prediction.Article Citation - WoS: 16Citation - Scopus: 26Evolution of Software Testing Strategies and Trends: Semantic Content Analysis of Software Research Corpus of the Last 40 Years(Ieee-inst Electrical Electronics Engineers inc, 2022) Gurcan, Fatih; Dalveren, Gonca Gokce Menekse; Cagiltay, Nergiz Ercil; Roman, Dumitru; Soylu, AhmetFrom the early days of computer systems to the present, software testing has been considered as a crucial process that directly affects the quality and reliability of software-oriented products and services. Accordingly, there is a huge amount of literature regarding the improvement of software testing approaches. However, there are limited reviews that show the whole picture of the software testing studies covering the topics and trends of the field. This study aims to provide a general figure reflecting topics and trends of software testing by analyzing the majority of software testing articles published in the last 40 years. A semi-automated methodology is developed for the analysis of software testing corpus created from core publication sources. The methodology of the study is based on the implementation of probabilistic topic modeling approach to discover hidden semantic patterns in the 14,684 published articles addressing software testing issues between 1980 and 2019. The results revealed 42 topics of the field, highlighting five software development ages, namely specification, detection, generation, evaluation, and prediction. The recent accelerations of the topics also showed a trend toward prediction-based software testing actions. Additionally, a higher trend on the topics concerning "Security Vulnerability", "Open Source" and "Mobile Application" was identified. This study showed that the current trend of software testing is towards prediction-based testing strategies. Therefore, the findings of this study may provide valuable insights for the industry and software communities to be prepared for the possible changes in the software testing procedures using prediction-based approaches.Article Citation - WoS: 28Citation - Scopus: 38Requirements for Remote Rf Laboratory Applications: an Educators' Perspective(Ieee-inst Electrical Electronics Engineers inc, 2009) Cagiltay, Nergiz Ercil; Aydin, Elif; Oktem, Rusen; Kara, Ali; Alexandru, Marian; Reiner, BodoThis paper discusses the results of a study of the requirements for developing a remote RF laboratory. This study draws on the perspectives of educators in university electrical engineering departments and in technical colleges, on the teaching of the radio frequency (RF) domain. The study investigates how these educators would like the technical content of a state of the art RF laboratory to be designed. As far as the authors know, no publication exists in the literature that investigates the requirements and needs of remote laboratories in that particular field. The outcomes of this work are expected to guide remote laboratory platform developers towards the most effective design of their platforms, The analysis of the results showed that educators would like the technical content of the laboratory to cover basic communication techniques, microwave circuits and devices, antennas and propagation, RF technology, and radio system design aspects of modern telecommunication systems. They would therefore like the laboratory instrumentation to be designed to that end. The educators also reported the need for advanced experimental setups which require expensive RF measurement devices. The discrepancy between university and technical college views was also considered in this paper.
