Concept map model is a method that creates domain model by identifying the relationship between concepts in course contents. This study presents an adaptive intelligent web based learning system called OPCOMITS (Object Oriented Programming Tutor using Concept Map Model). OPCOMITS has a free domain model which can be regulated by an expert for any course. It uses concept map model to regulate the topic hierarchy, to measure the student's knowledge about a topic and to stimulate learning. By employing a concept map model, it structures the course and provides an environment in which the lecturer can arrange the chapters, topics, concepts and the prerequisite relationships between the concepts. Thus, it offers an adaptive and effective learning environment by measuring the level of student's knowledge about a topic, offering reinforcing feedback, diagnosing students' weaknesses and directing them to related chapter topic in the domain for revisions. To evaluate the effectiveness of the proposed approach an experiment has been conducted on Computer Programming department in Object Oriented Programming course. From the experimental results, it is found that OPCOMITS has contributed to the academic success of students using it and students have exhibited much better learning than those who have used a conventional e-learning system. ß

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Fabrication and characterization of flexible optical fiber bundles (FBs) with inhouse synthesized high-index and low-index thermally matched glasses are presented. The FBs composed of around 15000 single-core fibers with pixel sizes between 1.1 and 10 μm are fabricated using the stack-and-draw technique from sets of thermally matched zirconiumsilicate ZR3, borosilicate SK222, sodium-silicate K209, and F2 glasses. With high refractive index contrast pair of glasses ZR3/SK222 and K209/F2, FBs with numerical apertures (NAs) of 0.53 and 0.59 are obtained, respectively. Among the studied glass materials, ZR3, SK222, and K209 are in-house synthesized, while F2 is commercially acquired. Seven different FBs with varying pixel sizes and bundle diameters are characterized. Brightfield imaging of a micro-ruler and a Convallaria majalis sample and fluorescence imaging of a dye-stained paper tissue and a cirrhotic mice liver tissue are demonstrated using these FBs, demonstrating their good potential for microendoscopic imaging. Brightfield and fluorescence imaging performance of the studied FBs are compared. For both sets of glass compositions, good imaging performance is observed for FBs, with core diameter and core-to-core distance values larger than 1.6 μm and 2.3 μm, respectively. FBs fabricated with K209/F2 glass pairs revealed better performance in fluorescence imaging due to their higher NA of 0.59.

ÖzetBilgi teknolojilerinin gelişimi, rekabetin artması, müşteri profilinin değişmesi günümüzde işletmelerin müşteri ile olan ilişkisini de etkilemiştir. MİY(Müşteri İlişkileri Yönetimi), müşterinin sadakatini ve memnuniyetini arttırmak amacıyla müşterilerle sürekli ilişki içerisinde olmayı ve müşterilerin beklentilerine uygun ihtiyaç ve istekleri belirleyip müşteriye sunmayı hedeflemektedir. Müşteri ilişkileri yönetimi öncelikle müşteriler hakkında olabildiğince veri toplamaya dayanır. Bu nedenle şirketlerin toplamış olduğu veri ambarlarındaki veriler bir araya getirilerek müşterilerin karakteristik özelliklerini belirlemek için analizler yapılmaktadır. Bu veriler ile hangi tür ürünleri tercih ettiklerini bulmak ve bunların ışığında müşteriyle yapılacak iletişime yön vermek mümkündür. VM(Veri Madenciliği) bu aşamada fayda sağlamakta olup, veri analizleri sayesinde anlamlı bilgi ve örüntüleri açığa çıkarma sürecini kapsamaktadır. Bu çalışmada, Türkiye'de faaliyet gösteren sektöründe öncü bir sigorta şirketinin müşterilerine ait veriler VM'nin en çok kullanılan birliktelik kuralı algoritmalarından Apriori algoritması ile analiz edilmiştir. Bu analiz sonucunda müşterilerin daha çok hangi ürün gruplarını bir arada almayı tercih ettiği ortaya çıkmaktadır. Müşteri ilişkileri yönetimi açısından, birliktelik kuralı analiz sonuçlarından faydalanılarak daha etkin sonuç verecek satış kampanyası ve pazarlama stratejisi geliştirmek mümkündür. Using Association Rule Mining for Customer Relationship Management in Insurance Sector AbstractToday, the development of information technology, increased competition, change in customer profile have affected firms' relationship with customers. CRM (Customer Relationship Management) is required to be in continuous contact with customers to increase customer loyalty and satisfactions and it aims to identify customer's needs and requests to meet the expectations. Customer relationship management is primarily based on the collection of data about customers as much as possible. Therefore, data warehouses in companies are combined together and analyses are performed to determine the characteristics of customers. With this data, it is possible to find which types of products customers prefer to buy and this information will help and give directions of communication with the customers. DM (Data Mining) provides benefits at this stage which is the process of extraction of meaningful information and patterns through the analysis of data. In this study, a leading insurance company's customer data that is operating in Turkey is used. Apriori algorithm which is the most widely used association rule mining algorithm is applied to this dataset. This analysis reveals combinations of product groups that customers prefer to buy. Taking advantage of this association rule analysis results in terms of customer relationship management, it is possible to make more effective sales campaign and to develop marketing strategies.

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Unmanned Aerial Vehicle (UAV) technology is being used increasingly for military and civilian purposes. The primary reason for this increase is that UAVs eliminate the risk to human life in difficult and dangerous missions, are cost effective, and easily are deployed. Developments in UAV technology and decreasing costs have increased UAV usage. However, when multiple UAVs are deployed, inter UAV communication becomes complicated. For this reason, communication in multi-UAV systems is the most important problem that needs to be solved. To enable communication among UAVs without infrastructure support, a Flying Ad Hoc Network (FANET) is used. A FANET provides UAVs to fly in tandem without colliding. To ensure coordinated flight, UAVs require the location information of other UAVs. In this study, we developed a common channel multi-token circulation protocol to share location information in multi-UAV systems that communicate using a FANET. The proposed method ensures that UAVs in multi-UAV systems know each other's coordinate information with minimum error.

Educational data mining is a very novel research area, offering fertile ground for many interesting data mining applications. Educational data mining can extract useful information from educational activities for better understanding and assessment of the student learning process. In this way, it is possible to explore how students learn topics in interactive learning environments such as an intelligent tutoring system (ITS). In this article, we demonstrate the use of association rule mining to extract mistakes often occurring together in the student data captured in an ITS we developed, called "intelligent tutor for computer systems course" (ITCS). Student assessment results from the ITCS were analyzed using association rule mining. This analytical process could help teachers to carry out modification to the ITCS to improve it together with the concept and sub-concept relationships obtained. We further developed two software programs to extract hidden patterns from the student assessment results on the ITCS using association rule mining. The first program analyzes and finds association rules derived from the students' incorrect answers to the concepts by single dimensional association rule mining, while the second program does so by multidimensional association rule mining. Design of these programs and the data mining results in this study are described.

Ozet�e-Bu !;ah�mada, Fundus Floresein Anjiografi (FFA) yontemi ile elde edilen retina goriintiileri iizerinde Ya�a Bagh Makula Dejenerasyonu (YBMD) hastahgmm Bilgisayar Destekli Tespit (BDT) i�leminin ger!;ekle�tirilmesi ama!;lanml�tlr. Toplam 87 goriintii kullamlarak olu�turulan veri seti iizerinde BDT ile hastahk tespit i�lemleri ger!;ekle�tirilmi�tir. Yapllan !;ah�manm amaCI, geli�tirilen BDT sistemi ile YBMD hastahgmdan etkilenen ilgili bOigelerin (iB) i�aretlenerek, bu bOigelerin tespit edilmesini saglamaktlr. Boylelikle, i�aretlenen bOigelerin goz hekimleri tarafmdan daha klsa siirede degerlendirilmesi ve hasta takibini kolayla�tlrmasl miimkiin olacaktlr. BDT sisteminin on i�leme a�amasmda morfoloik goriintii i�leme, boIii tleme a�amasmda sobel kenar algllama filtresi, iB'lerin belirlenmesi a�amasmda !;Ikanlan ozelliklere gore iB olabilecek bOigelerin tespiti ve karar verme a�amasmda optik diskin eliminasyonu yapllarak, ilgili bOige olarak etiketlenmi� yapmm belirlenmesi i�lemleri ger!;ekle�tirilmi�tir. Geli�tirilen BDT sistemi ile elde edilen sonu!;lar uzman bir goz hekimi tarafmdan kontrol edilerek, BDT sisteminin elde ettigi performans kriterleri sonu!; olarak belirtilmi�tir. Sonu!; olarak, 74 (DP ve DN) dogru tespit, 13 (YP ve YN) yanh� tespit sonucu, geli�tirilen BDT sistemi ile %85,05 dogruluk yiizdesine ula�llml�tlr. Anahtar Kelimeler -YBMD; BDT sistemi; medikal goriintii i!jleme; morfolojik yapllandlrma. Abstract-This work aims to realize Age related macular degeration (ARMD) detection process on the retinal images obtained by the Fundus Floresein Angiography (FFA). Critic area process has been performed by Computer Aided Detection (CAD) system which was detected on data sets generated with the use of 87 images of total. The purpose of this work, regions of interest affected by ARMD disease is to provide detection with CAD system. Thus, monitoring of the treatment of the patient can be made by doctors labeled on retinal images. This study intends to provide the detection of ARMD by separating structure like blood vessels, optic disc from retinal images using pre-processing techniques as bands of color separation, histogram processes of images. In CAD pre-processing stage the areas that can be ARMD are 978-1-4799-4874-1114/$31.00 ©2015 IEEEmade to be more clearer and sharpener and edge filters and dilation algorithms are used to perform successful segmentation process. At the end of the pre-processing and segmentation stages, regions of interest are labeled based on feature extracted. Regions of interest are issued to characteristics, optic disc has been eliminated by the algorithm developed. In the final stage the regions of interest are labeled according to these features. Accuracy of system is tested by ophthalmologist as controlling the ARMD and healthy retinal images labeled by CAD process. Finally, 74 (TP and TN) positive, 13 (FP and FN) negative results in detection were reached with the developed CAD system. In detection of ARMD study, using performance evaluation criteria, the accuracy of th...