Computer Engineering

Blended Learning is a learning model that is enriched with traditional learning method and online education materials. Integrating online and face-to-face learning with blending learning can optimize seat time and improve learning experience. In this paper, we present the teaching of Algorithm and Programming course in Computer Engineering Education via blended learning approach. Since 2011, Computer Engineering education in Süleyman Demirel University Computer Engineering Department is taught with blended learning method. Blended learning is achieved through Learning Management System (LMS) of university by using distance education technology. LMS comprises of course materials supported with flash animations, student records, user roles, evaluation system such as surveys and quizzes that meet SCORM standards. In this paper, performance evaluation of students in traditional and blended education for Computer Engineering is provided. Applied blended learning model is presented and evaluation of students who are taking programming courses is done. Therefore, it is aimed that adaptation period of students in blended education is shortened. Our results show that algorithmic thinking abilities of students who enrolled in the Algorithm and Programming course in blended and traditional education are close.

An optimized certificate-based protocol for mobile network with authentication and security has been proposed by Yi et al. This protocol allows efficient computation and less storage requirement in the mobile device. As a result, less power is consumed in the mobile device. However, in 1999 showed that Yi et al.'s scheme is vulnerable to some attacks, but did not remedy these attacks. In this paper, we propose an improved protocol to remedy these attacks. Using the new protocol, the protection against attacks can be assured. The security of the key distribution on the mobile network is enhanced as well.

Ozet: Uzak laterallomber disk herniasyonlan (ULLDH) faset ekleminin lateralinde olu~masl nedeni ile medialde kalan klasik lomber disk herniasyonlarmdan aynlarak hem klinik bulgular hem de cerrahi yakla~lmda farkhhklar gosterir. ULLDH genellikle ust lomber sinir koku basl bulgulan verir ve goruntlileme tekniklerinden bilgisayarh tomografi, magnetik rezonans ile son zamanlarda magnetik rezonans single-shot fast spin-echo sekansm kullamml ile tam konma slkhgl artml~tIr. Posterolateral kas i<;inden ge<;en yakla~lm faset eklemin butlinlUgunu bozmamasl nedeniyle ULLDH'lanmn cerrahi tedavisinde tercih edilen bir tekniktir. Bu makalede adl ge<;en yakla~lmm uygulandlgl bir olgu sunuyoruz ve ilgili literatliru tartl~lYoruZ. Anahtar Sozciikler: Magnetik rezonans single-shot fast spin-echo sekans, posterolateral kas i<;inden ge<;en yakla~lm, uzak laterallomber disk hernisi Abstract: Far lateral lumbar disc herniations differ from classic herniations, which occur on the medial...

Endüstri toplumundan enformasyon toplumuna geçişle birlikte tüketicilerin davranışlarında olduğu kadar pazar yapılarında da önemli değişmeler yaşanmaya başlanmıştır. Bundan dolayı yönetim geleneksel yöntemlerle yoluna devam edemeyeceğini anlamış ve kendini sürekli olarak yenileme dönemine girmiştir.

Transportation and distribution systems are improving with an increasing pace with the help of current technological facilities and additionally, the complexity of those systems are increasing. Vehicle routing problems are difficult to solve with conventional techniques. Improving routes used in distribution systems provides significant savings in terms of time and costs. In this paper, current routes in school buses, which is a sub-branch of vehicle routing problems, are optimized using the Ant Colony Optimization (ACO), which is a heuristic artificial intelligence algorithm. Developed software is used for recommending the most suitable and the shortest route illustrated on a map by taking the instantaneous student wait locations online. Results of this study suggest that the current routes can be improved by using the ACO.

Araç Rotalama Problemi (ARP) klasik yöntemler ile çözülmesi mümkün olmayan ve birçok alt dalı olan karmaşık bir problemdir. Bu çalışmada, ARP'nin bir alt dalı olan Okul Servisi Rotalama Probleminin (OSRP) optimizasyonu amaçlanmıştır. ARP ve OSRP incelenmiş, problemler ve geliştirilen çözüm yöntemleri ile ilgili literatüre yer verilmiştir. OSRP'nin optimizasyonu için kümeleme teknikleri ve yapay zeka yöntemleri kullanılarak, GPS, GIS araçları ve mobil uygulama desteği ile bir yazılım geliştirilmiştir. Geliştirilen yazılım Ankara ilinde hizmet veren servis firmalarından toplanan rota verileri üzerinde uygulanmıştır. Elde edilen deneysel sonuçlar, geliştirilen yöntemin, mesafe, zaman ve rakım değişimi parametreleri açısından rotaları başarılı bir şekilde iyileştirilebileceğini göstermiştir.

Vehicle routing problems (VRP) are complicated problems, which can be
encountered in a variety of different fields and are not possible to solve using classical methods. In this study, optimization of the School Bus Routing Problem(SBRP), which is a sub-branch of VRP, is aimed. VRP and SBRP have been studied, and the literature on the problems and developed solution methods have been given. For the optimization of SBRP, by using the clustering and artificial intelligence techniques a software has been developed with the support of the GPS,
GIS tools and mobile application. The developed software has been applied on the route data collected from school service companies which are in the province of Ankara. The obtained experimental results have showed that the developed method can successfully optimize the school bus routes in terms of distance, time and altitude change parameters.

Kaldiracli doviz alim-satim piyasasi, yaygin olarak bilinen ismiyle Forex veya FX, gunluk 5,5 trilyon dolarlik islem hacmiyle dunyanin en buyuk para piyasasidir. Forex piyasalarinda fiyat yonunun tahmini ve isleme girme yontemleri gelisen teknolojiye paralel olarak her gecen gun degismekte ve gecmis veriler ile egitilerek karar verebilen robotlarin bu alanda etkisi giderek artmaktadir. Makine ogrenmesi, bilgisayarlarin gecmis bilgilerden elde edilen tecrubelerden yararlanarak, gelecekteki olaylari tahmin etmesine ve modelleme yapmasina imkân veren bir yapay zekâ alanidir. Bu calismada, bir makine ogrenme teknigi olan “Naive Bayes“ algoritmasi kullanilarak, gecmisteki veriler isiginda guncel duruma uygun AL ya da SAT sinyali ureten ve bu yonde otomatik islem acan bir robot gelistirilmistir. Robot EUR/USD, GBP/USD, USD/JPY, USD/CHF, USD/CAD, GBP/JPY ve AUD/USD paritelerine ait gecmis veriler uzerine uygulanmis ve elde edilen sonuclar yorumlandiginda Forex piyasalari icin uretilen siny...