Aydın, Mehmet Nafiz

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Mehmet Nafiz, Aydin
MEHMET NAFIZ AYDIN
Aydın, MEHMET NAFIZ
Mehmet Nafiz AYDIN
AYDIN, MEHMET NAFIZ
Mehmet Nafiz Aydın
Aydın, M.
Aydin,M.N.
Aydin M.
Aydin,Mehmet Nafiz
Aydin, Mehmet Nafiz
A., Mehmet Nafiz
Aydın, M. N.
Aydın,M.N.
Aydın, Mehmet Nafiz
Nafiz Aydin M.
M. Aydın
M. N. Aydın
AYDIN, Mehmet Nafiz
Aydın M.
A.,Mehmet Nafiz
Job Title
Doç. Dr.
Email Address
mehmet.aydin@khas.edu.tr
Scopus Author ID
Turkish CoHE Profile ID
Google Scholar ID
WoS Researcher ID
Scholarly Output

38

Articles

16

Citation Count

127

Supervised Theses

12

Scholarly Output Search Results

Now showing 1 - 10 of 38
  • Conference Object
    Citation Count: 2
    A Country-specific Analysis on Internet Interconnection Ecosystems
    (IEEE, 2017) Aydın, Mehmet Nafiz; Aydın, Mehmet Nafiz
    With the proliferating number of diverse participants and destinations to reach, the Internet construct has become more intricate to assay. Today, Internet Service Providers (ISPs) establish resilient networks from multiple providers and broaden the number of peering links - as financially as viable. However, the complex structure of the global Internet ecosystem and entwined roles of Internet players simply prevent us from conducting generalized models for grasping interconnections which could be applied globally regardless of the local surroundings. In this paper, the global inter-domain Internet topology is scrutinized by the help of interconnection characteristics within a country-specific stance. Our study on the Internet ecosystems helps us highlight the non-uniformity of interconnections by using both "real world" metrics and network science metrics. One of the significant findings that the analysis yields is that presence of well-established Internet Exchange Points (IXPs) in an interconnection ecosystem - besides the benefit of bolstering the peering fabric - increases the competitive nature of Internet transit market and boosts the inclination to multi-home for stub networks, thus increases the resilience of national Internet constructs.
  • Master Thesis
    Hub analysis of health information platform from a network science perspective
    (Kadir Has Üniversitesi, 2015) Aydın, Mehmet Nafiz; Aydın, Mehmet Nafiz
    Online information platforms such as social networking applications are subject to examination of the underlying interactions as a network. Managers of these platforms are often unaware what constitutes the very idea of network growth. Conventional web and social analytics metrics are not adequate to surface the intriguing interplays among individuals interacting on these platforms. Thus, the challenge for managers is to know what underlies growth of the network on these platforms. The goal of this research is to identify growth mechanisms via hubs of an online health platform from a network science perspective. In particular, it is aimed to understand characteristics of the most connected nodes, so-called "Hubs", so that hub contributions to network growth can be discerned. From a network science perspective, the research is realized by examining the time dependent graph of hubs along with their attributes, which are the role and gender attributes. The only common pattern that is observed for hub behavior over time can be best described as typical step functions or "staircase" functions. Furthermore, one of the most prominent features of hub is observed in this online information health platform, appears to be dissassortativity. That is, hubs form edges with different role or gender nodes. Actually, almost all hubs form edges in the opposite gender. Also, they prefer to form edges with different role nodes in general. This research will guide for platform managers to decide alternating product attractiveness or customer loyalty opportunities.
  • Master Thesis
    Application of the right to data portability: A technical and managerial perspective
    (Kadir Has Üniversitesi, 2019) Aydın, Mehmet Nafiz; Aydın, Mehmet Nafiz
    European Union’s General Data Protection Regulation provides individuals with new rights one of which is the Right to Data Portability. The Right to Data Portability has been further explained by relevant European data protection bodies’ guidelines (European Data Protection Board, Article 29 Working Party, Information Commissioner’s Office). Article 29 Working Party and Information Commissioner’s Office refer to midata initiative in the United Kingdom as an exemplary application of the Right to Data Portability. We investigate whether midata initiative is compliant with the Right to Data Portability and these guidelines as it was claimed by relevant European data protection bodies. In this thesis by using open, axial and selective coding to compare and explain the relationships between midata and these guidelines, we found that while midata is compliant with the Right to Data Portability and these guidelines in some respects, it is also not compliant regarding certain elements. We believe that our findings should provoke and shape revisions of these guidelines as many privacy professionals look at these guidelines to understand and interpret General Data Protection Regulation’s Right to Data Portability. This thesis also translates the Right to Data Portability’s provisional requirements to action plan steps in the context of data, technology and management. It provides good practice recommendations, scenarios and discussions for project managers and privacy professionals to support decision making and management practice in the application of the Right to Data Portability.
  • Article
    Citation Count: 1
    School-wide friendship metadata correlations
    (Pergamon-Elsevier Science Ltd, 2019) Aydın, Mehmet Nafiz; Perdahçı, Nazım Ziya
    Managers and education practitioners desire to know an extent to which sustainable school-wide friendship exists. Drawing on theory of network this research focuses on bestfriendships that may contribute to positive school experience or school belonging in the context of school-wide interactions. We emphasize that school-wide unity is essential to refer to shared perceived friendship experience at the school level. The basic trust of this study is that managers should consider interconnectedness as a complex system of entangled interactions among students. We investigate best friendship network on the meso-to-macro scale. Particular attention is paid to the network phenomena of the largest component and network correlations for examining school wide unity. The results show that abundance of asymmetric friendships leads to unity around school wide interactions. As suggested by network theory popular students' tendency to avoid forming closed clusters assures sustainability in school-wide friendships and having same gender type or being classmates correlate highly with the choice of best friends in contrast to achievement scores. Metadata correlations reveal same-gender and same-class clubs. Incorporating meso level findings into macro level indicates that some metadata (e.g. gender) may be considered as salient characteristics of the communities while other metadata (e.g. achievement scores) may be irrelevant.
  • Article
    Citation Count: 18
    Unsupervised Anomaly Detection in Multivariate Spatio-Temporal Data Using Deep Learning: Early Detection of COVID-19 Outbreak in Italy
    (Ieee-Inst Electrıcal Electronıcs Engıneers Inc, 2020) Aydın, Mehmet Nafiz; Aydın, Mehmet Nafiz; Öğrenci, Arif Selçuk
    Unsupervised anomaly detection for spatio-temporal data has extensive use in a wide variety of applications such as earth science, traffic monitoring, fraud and disease outbreak detection. Most real-world time series data have a spatial dimension as an additional context which is often expressed in terms of coordinates of the region of interest (such as latitude - longitude information). However, existing techniques are limited to handle spatial and temporal contextual attributes in an integrated and meaningful way considering both spatial and temporal dependency between observations. In this paper, a hybrid deep learning framework is proposed to solve the unsupervised anomaly detection problem in multivariate spatio-temporal data. The proposed framework works with unlabeled data and no prior knowledge about anomalies are assumed. As a case study, we use the public COVID-19 data provided by the Italian Department of Civil Protection. Northern Italy regions' COVID-19 data are used to train the framework; and then any abnormal trends or upswings in COVID-19 data of central and southern Italian regions are detected. The proposed framework detects early signals of the COVID-19 outbreak in test regions based on the reconstruction error. For performance comparison, we perform a detailed evaluation of 15 algorithms on the COVID-19 Italy dataset including the state-of-the-art deep learning architectures. Experimental results show that our framework shows significant improvement on unsupervised anomaly detection performance even in data scarce and high contamination ratio scenarios (where the ratio of anomalies in the data set is more than 5%). It achieves the earliest detection of COVID-19 outbreak and shows better performance on tracking the peaks of the COVID-19 pandemic in test regions. As the timeliness of detection is quite important in the fight against any outbreak, our framework provides useful insight to suppress the resurgence of local novel coronavirus outbreaks as early as possible.
  • Article
    Citation Count: 1
    Network analysis of innovation mentor community of practice
    (Emerald Group Publishing Ltd, 2023) Aydın, Mehmet Nafiz; Aydin, Mehmet Nafiz; Perdahci, Ziya Nazim; Pasin, Merih
    PurposePositive effect of knowledge sharing (KS) on innovation has come to the fore and government-supported innovation and mentoring communities or mentor networks have become widespread. This article aims to examine the community connectedness and mentors' preferences for professional competency-based KS of such innovation community of practice networks (CoPNs).Design/methodology/approachThe paper constructs a directed weighted CoPN model with a node-attribute-based novel fingerprint edge weights. Based on the CoPN, Social Network Analysis (SNA) metrics and measures including Giant Component (GC) were proposed and analyzed to identify mentors' connectedness preferences. The fingerprint was proposed as a novel binarized node attribute of competence. Jaccard similarity of fingerprints was proposed as edge weights to reveal correlations between competences and preferences for KS.FindingsThe work opted to conduct a survey of 28 innovation mentors to measure a CoPN. Both a name generator question and a second set of questions were employed to invite respondents to name their collaborators and indicate their professional competence. SNA metrics result in differing values for GC and the rest, which lead us to focus on GC to reveal salient metrics of connectedness. Jaccard similarity analysis results on GC demonstrate that mentors collaborate in an interdisciplinary manner.Originality/valueBased on the CoPN, the methods proposed may be effective in predicting preferred relationships for interdisciplinary collaborations, providing the managers with an analytical decision support tool for KS in practice.
  • Master Thesis
    Using gamification approach for scoring application developers of an apaas
    (Kadir Has Üniversitesi, 2014) Aydın, Mehmet Nafiz; Aydın, Mehmet Nafiz
    Cloud Computing has experienced a predominant growth during the past years and businesses who have shifted to the cloud model acknowledge the benefits, however there is still a room for expansion globally, and the growth is expected to continue. IT has invented new ways of accelerating application (app) development during the past 100 years. Cloud is no exception. Platform as a Service (PaaS) is, emerging to raise the abstraction bar of operational aspects of like deployment, availability, scalability, security. Application Platform (aPaaS) is emerging to raise the abstraction bar of app development, aiming to make app development faster and easier for developers. APaaS are offering companies decreased development costs, and higher time to market while boosting productivity. Despite all the aforementioned advantages, to attract attention of app development enthusiasts in a global scale is a challenge. An app platform should be engaging, easy to understand, easy to use, as well as rewarding. Developers should enjoy working with it; the platform should exert the so-called coolness factor, so that a developer sticks to it until the app is leveraged by its customer. Our main focus on this thesis is, with the help of gamification techniques, to convert an aPaaS into an intuitive, engaging platform for developers. We chose ImonaCloud (imona.com) as the application platform. In the scope of this thesis, 30 developers scored and rewarded according to their actions and achievements on the platform. By looking their meta-data actions and scores they got, it can be said that, our scoring model is viable for that kind of aPaaS platforms. This model may help not only the developers but for the novice programmers to learn the platform faster and become more engaged.
  • Master Thesis
    Technology-enabled innovation in airline distribution channels
    (Kadir Has Üniversitesi, 2018) Aydın, Mehmet Nafiz; Aydın, Mehmet Nafiz
    In the past, airline distribution process, which was between airline companies and customers, was under the control of intermediaries such as GDSs. After the advancement of internet technology in airline distribution, online players emerged, and airline companies established their websites to bypass the intermediaries. Since new technologies have still been emerging to meet the key factors such as customer expectations, technological innovations and technical insufficiency of the intermediaries in distribution industry, the structure of airline distribution will continue to evolve in the next decade. In this study, we aimed to understand how the industry evolved according to the emerged players and developed technologies by utilizing secondary data such as relevant literature and industry reports. As a result, we constituted an integrated framework for analyzing the industry in timeline including three phases (past, present, future) and from four aspects (market forces, technology trends, ecosystem players, ecosystem canvas).
  • Conference Object
    Citation Count: 1
    Analysis of the Patients and Physicians Connection Network on an online Health Information Platform
    (IOS Press, 2014) Aydın, Mehmet Nafiz; Perdahci, N. Ziya
    Social network applications have gained popularity in the health domain as they bring health information seekers (patients and alike) and medication advice providers (physicians and other relevant actors) together. By employing a network science perspective this research is aimed to understand an information network establishing connections among and between information seekers and providers. We found that such a connection network surfaces most of the essential characteristics of a typical complex network. Furthermore a detailed structural analysis shows some intriguing relations and connection behaviours in the network. Implications of the findings are discussed from the perspectives of medical informatics and social network analysis.
  • Article
    Citation Count: 0
    Innovation mentor community of practice: a social network analysis perspective
    (Emerald Group Publishing Ltd, 2023) Aydın, Mehmet Nafiz; Aydin, Mehmet Nafiz
    PurposeTo exploit collaboration-driven innovation, in recent years, many government-sponsored innovation programs and mentor services have emerged. These services support an effective exchange of knowledge among innovation actors, including innovation mentors and enable mentor connectedness as an important factor to develop and sustain effective innovation mentors' community of practice (CoP). The purpose of this paper is to examine the degree of connectedness in an innovation mentor CoP. Design/methodology/approachIn this study, the innovation mentors CoP as part of a national innovation program is considered a network. The connectedness and assortative mixing of this CoP and the effects of these two on each other were examined by using social network measures, including component analysis, the giant component (GC) and assortativity. FindingsThe authors provide the analytical interconnectedness results for both the GC and the whole network with network analysis and assortativity measurements of three attributes of mentors (institution, title and degrees). The degree of correlation of community for the GC shows preferential attachment between high-ranking and low-ranking mentors, while preferential attachment was not observed for the whole network. The correlation coefficient for the institution attribute has the highest value for GC, while the title has the highest value for the whole network. Originality/valueThe study is one of the early attempts to apply social network analysis for an innovation mentor CoP. This study reveals the criticality of evaluating the GC and the whole network separately and provides a number of research and practical directions that will contribute to the development of the innovation mentor CoP.