A fundamental challenge in behavioral informatics is the development of methodologies and systems that can achieve its goals and tasks, including behavior pattern analysis. This study presents such a methodology, that can be converted into a decision support system, by the appropriate integration of existing tools for association mining and graph visualization. The methodology enables the linking of behavioral patterns to personal attributes, through the re-mining of colored association graphs that represent item associations. The methodology is described and mathematically formalized and is demonstrated in a case study related with the retail industry.

Ertek, G., Demiriz, A., Çakmak, F. (2012) “Linking Behavioral Patterns to Personal Attributes through Data Re-Mining” in Behavior Computing: Modeling, Analysis, Mining, and Decision. Eds: Longbing Cao, Philip S. Yu. Springer.

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Linking Behavioral Patterns to Personal Attributes through Data Re-Mining

Dr. Gürdal Ertek recommends the following related books:

• Behavior Computing: Modeling, Analysis, Mining and Decision 2012th Edition
• Analyzing Social Media Networks with NodeXL: Insights from a Connected World 1st Edition
• The Craft of Information Visualization: Readings and Reflections (Interactive Technologies) 1st Edition

 

 

 

This study examines the study skills and the learning styles of university students by using scoring method. The study investigates whether the study skills can be summarized in a single universal score that measures how hard a student works. The sample consists of 418 undergraduate students of an international university. The presented scoring was method adapted from the domain of risk management. The proposed method computes an overall score that represents the study skills, using a linear weighted summation scheme. From among 50 questions regarding to learning and study skills, the 30 highest weighted questions are suggested to be used in the future studies as a learning and study skills inventor. The proposed scoring method and study yield results and insights that can guide educators regarding how they can improve their students’ study skills. The main point drawn from this study is that the students greatly value opportunities for interaction with instructors and peers, cooperative learning and active engagement in lectures.

Gogus, A. & Ertek, G. (2012). “Statistical Scoring Algorithm for Study Skills and Kolb’s Learning Styles”. Presented at the International Conference of New Horizons in Education-2012 (INTE-2012), Prague, CZECH REPUBLIC, June 6, 2012.

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

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Statistical Scoring Algorithm for Learning and Study Skills

Dr. Gürdal Ertek recommends the following related books:

Essentials of Business Analytics 2nd Edition

 

 

 

 

 

 

 

 

 

 

 

This study presents a methodology to determine risk scores of individuals, for a given financial risk preference survey. To this end, we use a regression-based iterative algorithm to determine the weights for survey questions in the scoring process. Next, we generate classification models to classify individuals into risk-averse and risk-seeking categories, using a subset of survey questions. We illustrate the methodology through a sample survey with 656 respondents. We find that the demographic (indirect) questions can be almost as successful as risk-related (direct) questions in predicting risk preference classes of respondents. Using a decision-tree based classification model, we discuss how one can generate actionable business rules based on the findings.

Ertek, G., Kaya, M., Kefeli, C., Onur, Ö., Uzer, K. (2012) “Scoring and predicting risk preferences” in Behavior Computing: Modeling, Analysis, Mining and Decision. Eds: Longbing Cao, Philip S. Yu. Springer.

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Scoring and Predicting Risk Preferences
[su_spoiler title=”view PDF” style=”fancy” icon=”caret”][pdfviewer width=”600px” height=”849px” beta=”true/false”]https://ertekprojects.com/gurdal-ertek-publications/wp-content/uploads/2014/07/ertek_et_al_Risk_Book_Chapter_LNCS.pdf[/pdfviewer][/su_spoiler]

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Supplementary Document for “Scoring and Predicting Risk Preferences”

Dr. Gürdal Ertek recommends the following related books:

• Behavior Computing: Modeling, Analysis, Mining and Decision 2012th Edition
• Data Mining Techniques: For Marketing, Sales, and Customer Relationship Management Paperback – April 12, 2011

 

 

 

Bilişim Sistemleri, verinin toplanması, işlenmesi, depolanması ve bilgisayar ağları üzerinden istenen bir uca güvenli bir şekilde iletilerek kullanıcıların hizmetine sunulmasında kullanılan,ve donanım, yazılım ve iletişim teknolojilerini bütünleştiren sistemlerdir. Bu tümleşik yapılar, yazılım uygulamaları ve bilgisayar donanımının tasarlanması, geliştirilmesi, işletimi, yönetimi ve desteğini içeren hizmetler ile oluşturulur ve sürdürülürler.

Bilişim Sistemleri, bilginin işlendiği ve paylaşıldığı tüm yapılarda kullanılmaktadır. Her bilim dalı ve iş kolu,bilişim sistemlerini kendi ihtiyaçları doğrultusunda yapılandırır. Bilginin işlendiği bilgisayar sistemleri genel olarak tüm yapılarda benzer olmakla birlikte özellikle yazılım her alanda farklılık gösterir. Benzer şekilde her iş kolunda bilgiyi toplama ve erişim için farklı çevre birimleri ve yöntemler kullanılır. Bu bölümde lojistik faaliyetlerine dönükLojistik Bilişim Sistemleri incelenecektir.

Ertek, G. Aba, B., (2012) “Lojistik Bilişim Sistemleri (Logistics Information Systems)”, Uluslararası Lojistik, Anadolu Üniversitesi Yayınları, Açıköğretim Fakültesi Yayını No: 1593. Eds. Bülent Çatay and Gürkan Öztürk.

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Lojistik Bilişim Sistemleri

 

 

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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ertek_et_al_wind_turbine

• 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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Supplement Document For “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