afak Saraydemir1, Necmi Tapınar2, Osman Eroğul3 and Hülya Kayserili4 1Department of Electronics Engineering, Turkish Mili tary Academy, Turkey 2Department of Electrical and Electronics Engineering, Erciyes University, Turkey 3Department of Biomedical Engineering Centre, Gülhan e Military Medicine Academy, Turkey 4Department of Medical Genetics, Đstanbul University Medicine Faculty, Turkey

#Dysmorphology # GWT # Principal component analysis # f ace recognition # SVM # K+NN

Orthophoto Information System in Turkey in the

Department of Geomatic Engineering, Osmaniye Korkut Ata University, Turkey

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Illicit Material Detection using Dual-Energy X-Ray

Computer Engineering Department, Cankaya University , Turkey

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A Decision Support System Using Demographic Issues: A Case Study in Turkey

Abstract: The demographic distribution of people by cities is an important parameter to address the people’s behaviour. To

#Agglomerative clustering # customer behaviour # data mining # decision support

Multiuser Detection with Neural Network MAI Detector in CDMA Systems for AWGN and

Necmi Taspinar1 and Yalcin Isik2 1Department of Electrical and Electronics Engineerin g, Erciyes University, Turkey 2Silifke"Tasucu Vocational School, Selcuk University , Turkey

#CDMA # multi5user detection # neural network # MAI det ector

Exploitation of ICMP Time Exceeded Packets for A Large-Scale Router Delay Analysis

Ali Gezer1 and Gary Warner2 1Electronic and Telecommunication Technology, Kayseri University, Turkey 2Computer Science, University of Alabama at Birmingham, US

#ICMP time exceeded packet # iot botnet # Mirai botnet # rtt delay # performance analysis # quality of service

Enhanced Bagging (eBagging): A Novel Approach for Ensemble Learning

Goksu Tuysuzoglu1 and Derya Birant2 1Graduate School of Natural and Applied Sciences, Dokuz Eylul University, Turkey 2Department of Computer Engineering, Dokuz Eylul University, Turkey

#Bagging # boosting # classification algorithms # machine learning # random forest # supervised learning

Empirical Evaluation of Leveraging Named Entities for Arabic Sentiment Analysis

Hala Mulki1, Hatem Haddad2, Mourad Gridach3, and Ismail Babaoğlu1 1Computer Engineering Department, Konya Technical University, Turkey 2Computer Science Department, University of Manouba, Tunisia 3Computational Bioscience Departments, University of Colorado Boulder, USA

#Named entity recognition # Arabic sentiment analysis # supervised learning method # lexicon-based method