Literature on renewable energy alternative of wind turbines does not include a multidimensional benchmarking studythat can help investment decisions as well as design processes. This paper presents a data-centric analysis of commercial on-shore wind turbines and provides actionable insights through analytical benchmarking through Data Envelopment Analysis (DEA), visual data analysis, and statistical hypothesis testing. The paper also introduces a novel visualization approach for the understanding and the interpretation of reference sets, the set of efficient wind turbines that should be taken as benchmark by inefficient ones.

Ertek, G., Tunç, M.M., Kurtaraner, E., Kebude, D., 2012, ‘Insights into the Efficiencies of On-Shore Wind Turbines: A Data-Centric Analysis’, INISTA 2012 Conference. July 2-4, 2012, Trabzon, Turkey. (indexed in IEEE Electronic Library)

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Insights into the Efficiencies of On-Shore Wind Turbines: A Data-Centric Analysis

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• Introduction to Data Envelopment Analysis and Its Uses: With DEA-Solver Software and References 2006th Editionhttp://amzn.to/2rjTPxH
• Information Visualization: Design for Interaction (2nd Edition)
• Wind Turbine Technology (Go Green with Renewable Energy Resources) 1st Edition

 

Lojistik Bilisim Sistemleri – Bilişim Sistemleri, donanım, yazılım ve iletişim teknolojilerini bütünleştiren ve verinin toplanması, işlenmesi, depolanması ve bilgisayar ağları üzerinden istenen bir uca güvenli bir şekilde iletilerek kullanıcıların hizmetine sunulmasında kullanılan sistemlerdir. Bilişim sistemleri temel olarak belirtilen bu amaçlara hizmet eden bilgisayar donanımı ve yazılım uygulamalarını içerir. Bu donanım ve yazılımların geliştirilmesi, işletimi, yönetimi ve desteğini içeren hizmet süreçleri ilebilişim sistemleri oluşturulur ve sürdürülürler.

Günümüzde bilişim sistemlerinin yaygınlaşması ile çok fazla miktarda yeni kavram gündeme gelmektedir. Lojistik konusunda temel ilgi alanı olarak çalışan profesyonellerin kayda değer bir kısmı da dahil olmak üzere lojistikle ilgili pek çok kişi, Lojistik Bilişim Sistemleri’yle ilgili tüm resmi görebilecekleri bir kaynağa sahip değildir. Sınıflandırma (taksonomi), belli bir konudaki (örneğin bir bilim dalı konusundaki) bilgi birikiminin sınıflandırılmasını, bu konuyla ilgili gerçeklerin bütünsel bir çerçevede yapılandırılmasını konu alır (McCarthy and Keith, 2000). Bu makalede, Lojistik Bilişim Sistemleri kavramlarıyla ilgili büyük resmi bütünsel bir biçimde görebilmeyi sağlayacak bir sınıflandırma (taksonomi) sunulacaktır.

Ertek, G., Aba, B. (2012) “Lojistik Bilişim Sistemleri İçin Bir Sınıflandırma (Taksonomi)” Lojistik, Sayı: 25, Sayfa: 27-31.

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Lojistik Bilişim Sistemleri İçin Bir Siniflandirma (taksonomi)

Dr. Gurdal Ertek’in onerdigi kitaplar:

World-Class Warehousing and Material Handling, Second Edition

 

 

 

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This paper proposes a cross-disciplinary methodology for a fundamental question in product development: How can the innovation patterns during the evolution of an engineering system (ES) be encapsulated, so that it can later be mined through data analysis methods? Reverse engineering answers the question of which components a developed engineering system consists of, and how the components interact to make the working product. TRIZ answers the question of which problem-solving principles can be, or have been employed in developing that system, in comparison to its earlier versions, or with respect to similar systems. While these two methodologies have been very popular, to the best of our knowledge, there does not yet exist a methodology that reverse-engineers, encapsulates and represents the information regarding the application of TRIZ through the complete product development process. This paper suggests such a methodology that consists of mathematical formalism, graph visualization, and database representation. The proposed approach is demonstrated by analyzing the design and development process for a prototype wrist-rehabilitation robot and representing the process as a graph that consists of TRIZ principles.

Ertek, G., Erdogan, A., Patoglu, V., Tunç, M.M., Citak, C., Vanli, T., 2012, ‘Encapsulating And Representing The Knowledge On The Evolution Of An Engineering System’, Asme Idetc/Cie 2012. August 12-15, Chicago, Il, Usa.

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Encapsulating And Representing The Knowledge On The Evolution Of An Engineering System

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• TRIZ Matrix
• And Suddenly the Inventor Appeared: TRIZ, the Theory of Inventive Problem Solving 2nd Edition
• Engineering Design: A Practical Guide

 

 

 

In this paper, a taxonomy of supply chain and logistics innovations was developed and presented. The taxonomy was based on an extensive literature survey of both theoretical research and case studies. The primary goals are to provide guidelines for choosing the most appropriate innovations for a company and helping companies in positioning themselves in the supply chain innovations landscape. To this end, the three dimensions of supply chain innovations, namely the goals, supply chain attributes, and innovation attributes were identified and classified. The taxonomy allows for the efficient representation of critical supply chain innovations information, and serves the mentioned goals, which are fundamental to companies in a multitude of industries.

Başar, A., Özsamlı, N., A. E. Akçay, G. Kahvecioğlu, Ertek., G. (2011). “A taxonomy of supply chain innovations”. African Journal of Business Management. 5(30), pp. 11968-11977, 30 November, 2011.

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A taxonomy of supply chain innovations

Dr. Gürdal Ertek recommends the following related books:

• Supply Chain Management (5th Edition)
• World-Class Warehousing and Material Handling 1st Edition

 

 

 

Re-mining is a general framework which suggests the execution of additional data mining steps based on the results of an original data mining process. This study investigates the multi-faceted re-mining of association mining results, develops and presents a practical methodology, and shows the applicability of the developed methodology through real world data. The methodology suggests re-mining using data visualization, data envelopment analysis, and decision trees. Six hypotheses, regarding how re-mining can be carried out on association mining results, are answered in the case study through empirical analysis.

Ertek, G., Tunç, M.M., (2012) “Re-Mining Association Mining Results through Visualization, Data Envelopment Analysis, and Decision Trees”, in Computational Intelligence Applications in Industrial Engineering, Ed: C. Kahraman, Springer.

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Re-mining Association Mining Results Through Visualization, Data Envelopment Analysis, And Decision Trees

Dr. Gürdal Ertek recommends the following related books:

• Information Visualization: Design for Interaction (2nd Edition)
• Introduction to Data Envelopment Analysis and Its Uses: With DEA-Solver Software and References 2006th Edition
• Data Mining: Concepts and Techniques, Third Edition (The Morgan Kaufmann Series in Data Management Systems) 3rd Edition
• Post-mining of Association Rules: Techniques for Effective Knowledge Extraction 1st Edition
  

 

 

 

Association mining is the conventional data mining technique for analyzing market basket data and it reveals the positive and negative associations between items. While being an integral part of transaction data, pricing and time information have not been integrated into market basket analysis in earlier studies. This paper proposes a new approach to mine price, time and domain related attributes through re-mining of association mining results. The underlying factors behind positive and negative  relationships can be characterized and described through this second data mining stage. The applicability of the methodology is demonstrated through the analysis of data coming from a large apparel retail chain, and its algorithmic complexity is analyzed in comparison to the existing techniques.

Demiriz, A., Ertek, G., Kula, U., Atan, T. (2011). “Re-Mining Item Associations: Methodology and a Case Study in Apparel Retailing”. Decision Support Systems, 52,pp. 284–293.

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Re-mining item associations: Methodology and a case study in apparel retailing

Dr. Gürdal Ertek recommends the following related books:

• Analyzing Social Media Networks with NodeXL: Insights from a Connected World 1st Edition
• Data Mining: Concepts and Techniques, Third Edition (The Morgan Kaufmann Series in Data Management Systems) 3rd Edition

 

 

 

Association mining is the methodology within data mining that researches associations among the elements of a given set, based on how they appear together in multiple subsets of that set. Extensive literature exists on the development of efficient algorithms for association mining computations, and the fundamental motivation for this literature is that association mining reveals actionable insights and enables better policies. This motivation is proven valid for domains such as retailing, healthcare and software engineering, where elements of the analyzed set are physical or virtual items that appear in transactions. However, the literature does not prove this motivation for databases where items are “derived items”, rather than actual items. This study investigates the association patterns in changes of exchange rates of US Dollar, Euro and Gold in the Turkish economy, by representing the percentage changes as “derived items” that appear in “derived market baskets”, the day on which the observations are made. The study is one of the few in literature that applies such a mapping and applies association mining in exchange rate analysis, and the first one that considers the Turkish case. Actionable insights, along with their policy implications, demonstrate the usability of the developed analysis approach.

Please cite this paper as follows:

Arabacı, M., Aktuğ, A., Ertek, G. (2011) “Actionable Insights Through Association Mining of Exchange Rates: A Case Study.” Proceedings of International Symposium on Innovations in Intelligent Systems and Applications 2011. (IEEE). June 15-17, 2011, Istanbul, Turkey.

Dr. Gürdal Ertek recommends the following related books:

Essentials of Business Analytics 2nd Edition

Information Visualization: An Introduction, 3rd Ed. 2014 Edition

Literature on association mining, the data mining methodology that investigates associations between items, has primarily focused on efficiently mining larger databases. The motivation for association mining is to use the rules obtained from historical data to influence future transactions. However, associations in transactional processes change significantly over time, implying that rules extracted for a given time interval may not be applicable for a later time interval. Hence, an analysis framework is necessary to identify how associations change over time. This paper presents such a framework, reports the implementation of the framework as a tool, and demonstrates the applicability of and the necessity for the framework through a case study in the domain of finance.

Çinicioğlu, E. N., Ertek, G., Demirer, D., Yörük, E., (2011) “A Framework for Automated Association Mining Over Multiple Databases”. Proceedings of International Symposium on Innovations in Intelligent Systems and Applications 2011. (IEEE). June 15-17, 2011, Istanbul, Turkey.

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A Framework for Automated Association Mining Over Multiple Databases

Dr. Gürdal Ertek recommends the following related books:

• Data Mining: Concepts and Techniques, Third Edition (The Morgan Kaufmann Series in Data Management Systems) 3rd Edition
• Analyzing Social Media Networks with NodeXL: Insights from a Connected World 1st Edition
• Post-mining of Association Rules: Techniques for Effective Knowledge Extraction 1st Edition

 

 

 

This chapter investigates the relationship between interbank funds and efficiencies for the commercial banks operating in Turkey between 2001 and 2006. Data Envelopment Analysis (DEA) is executed to find the efficiency scores of the banks for each year, and fixed effects panel data regression is carried out, with the efficiency scores being the response variable. It is observed that interbank funds (ratio) has negative effects on bank efficiency, while bank capitalization and loan ratio have positive, and profitability has insignificant effects. This chapter serves as novel evidence that interbank funds can have adverse effects in an emerging market.

Aysan, A. F., Ertek, G., Öztürk, S. (2011) “Assessing the Adverse Effects of Interbank Funds on Bank Efficiency Through Using Semiparametric and Nonparametric Methods” in , Financial Services: Efficiency and Risk Management (Studies in Financial Optimization and Risk Management). Eds: Meryem Duygun Fethi, Chrysovalantis Gaganis, Fotios Pasiouras, Constantin Zopounidis. Nova Science Pub Inc.

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ASSESSING THE ADVERSE EFFECTS OF INTERBANK FUNDS ON BANK EFFICIENCY THROUGH USING SEMIPARAMETRIC AND NONPARAMETRIC METHODS

Dr. Gürdal Ertek recommends the following related books:

• Financial Services:: Efficiency and Risk Management (Studies in Financial Optimization and Risk Management)
• Introduction to Data Envelopment Analysis and Its Uses: With DEA-Solver Software and References 2006th Edition

 

 

 

Positive and negative association mining are well-known and
extensively studied data mining techniques to analyze market basket
data. Efficient algorithms exist to find both types of association, separately or simultaneously. Association mining is performed by operating on the transaction data. Despite being an integral part of the transaction data, the pricing and time information has not been incorporated into market basket analysis so far, and additional attributes have been handled using quantitative association mining. In this paper, a new approach is proposed to incorporate price, time and domain related attributes into data mining by re-mining the association mining results. The underlying factors behind positive and negative relationships, as indicated by the association rules, are characterized and described through the second data mining stage re-mining. The applicability of the methodology is demonstrated by analyzing data coming from apparel retailing industry, where price markdown is an essential tool for promoting sales and generating increased revenue.

Demiriz, A., Ertek, G., Atan, T., and Kula, U. (2010) “Re-mining Positive and Negative AssociationMining Results” P. Perner (Ed.): Advances in Data Mining. Applications and Theoretical Aspects, 10th Industrial Conference, ICDM 2010, Berlin, Germany, July 12-14, 2010. Proceedings. LNAI 6171, pp. 101–114.

Note: This is the final draft version of this paper. Please cite this paper (or this final draft) as above.

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Re-mining Positive and Negative Association Mining Results

Dr. Gürdal Ertek recommends the following related books:

• Data Mining and Analysis: Fundamental Concepts and Algorithms 1st Edition
• Post-mining of Association Rules: Techniques for Effective Knowledge Extraction 1st Edition