153
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Departman Tezleri
3G wireless multicasting service description discovery and transport
Wireless Multicasting is a technology that enables data and multimedia services to be delivered from a single source to a group of mobile receivers particularly for the actors in the broadcasting and telecommunication world. Although multicasting has been extensively researched in the past, the wired IP Multicast model has not picked up due to various limitations. The new generation wireless counterpart of this technology is receiving tremendous interest from all over the world.In this work, first we have provided a survey of recent technological improvements for wireless multicasting in both cellular and broadcast world. Then, one of the 3G wireless multicasting architecture, 3GPP?s MBMS (Multimedia Broadcast Multicast Services) in UMTS (Universal Mobile Telecommunication System) networks, is investigated with a focus on reliable download mechanism. We have provided an end to end download prototype for MBMS. Our prototype, called MBMS legacy download, also covers an implementation of a Service Discovery Architecture. As a unique contribution the thesis provides the gain of using progressive download instead of legacy download and proposes ways to increase the gain for streamable multimedia files for MBMS. With progressive download, downloadable media can be streamed earlier after some waiting time, while the downloading still continues in the background. First we provide optimizations of the parameters for an efficient MBMS legacy download. Then based on these optimizations, we provide experimental analyses to show the gain in using progressive download in MBMS. Finally in order to further increase the progressive download performance, we apply our application layer interleaving strategy to our MBMS download systems and give a performance comparison of the legacy, interleaved and progressive download delivery. This work has has been fully funded by TUBITAK and Vidiator Technology US under the project EEEAG 104E163.
Simulation of wave propagation in anisotropic media
Analyzing complex structures such as electromagnetic waves requires interactive visualization techniques for better interpretation. Based on deep mathematical knowledge, model of the structure and the medium is defined with computationally expensive explicit formulas. Without using computer resources, it is difficult to make robust analyses over the model. In such cases using computers are necessary for rapid and reliable data computation and visualization. Moreover, computers are necessary for disseminating the resulting information to other researchers. To fulfill these requirements, interdisciplinary research between mathematics and computer science is needed.Considering the above requirements, in this thesis we studied the simulation of wave propagation in anisotropic media. Firstly the explicit formulas are constructed as a solution of the problem. Secondly appropriate parallel computation and visualization technique is implemented. For this purpose we used graphic card processing unit that is capable of executing hundreds of instructions in milliseconds. Using this approach makes it possible to access the computation result directly in the graphic card. By this way we eliminate the data transmission between main memory and the graphic card memory. Immediately after computation, resulting data in the graphic card?s memory is directly visualized. Finally we developed a web based prototype platform that makes it possible to share the experiment results with other scientists.
Reliable transport for wireless sensor and actor networks
Wireless Sensor and Actor Networks (WSANs) are used for monitoring the physical world, processing data, making decisions and performing appropriate actions. Reliable transport of information in these networks is necessary for the correctness of an appropriate action, for obtaining the exact picture of phenomenon and for updating the modules of sensor nodes.A scalable, energy-aware and flexible transport solution for WSANs is presented in this study. The proposed transport solution is divided into two major parts sensors-to-actors and actor-to-sensors reliable transport. In order to fulfill different reliability requirements of events, the sensors-to-actors transport is further sub-divided into different transport modes; simple, fair, prioritized and real-time.Since the sudden impulse of event information from the sensors to the actor results in congestion, a novel congestion control scheme based on packet delivery time and buffer size of nodes is also presented in this study. In order to decrease the affect of interference, a novel schedule based packet forwarding scheme is introduced at the transport layer for orderly delivery of event packets to underlying layers. The actor to sensors reliable transport is aimed to provide successful transport of all data packets from the source to sensor nodes. In this study it is shown that, the rate at which lost packets should be recovered depends on the arrangement of nodes in the network.
Supervised techniques in data mining
Usage of Data Mining techniques is very common for reaching info on huge database. Techniques especially canalized by the user are used in this study. Theory of Data Mining is shortly described in first 6 chapters. Subjects are: learning and reaching info methods, Database Operational System types and selection, organizing data, removal of problems related data and presentation of obtained results.Data mining application is very common on especially commercial and medical areas. However, known application has not been encountered in earth sciences. Therefore, data is being used which obtained from Seyitömer Coal Basin in this application. When data examined: it is noted that there is no standardization for material naming. First of all, it is tried to hinder to name material in different ways at the stage of forming database. Summarized info is being represented after entering the data. Even if summary is not canalized by the user, it is added to the application because it may help to searcher. User chooses the material. Finds the first layer met for the chosen material in bore-hole. Therefore, reaches the material list takes place above this layer. Besides finds the last layer met. And obtains the material list takes place under this layer.User may wish to group some material under same name. And can re-organize the database according to this. The above described studies can be applied on this new database. This application also obtains vertical cross-section diagram drawing. At last, user can classify bore-holes according to code of layer which chosen material first met. The result of this procedure is represented on a plane by using different colored points to the researcher.Keywords : Data mining, database, Seyitömer Coal Basin, application for coal beds.
indexliAçık ErişimTRAkıllı üretim sistemlerinde çoklu hata teşhisi için hibrit derin öğrenme yaklaşımları
Endüstriyel üretim süreçlerinde akıllı sistemlerindeki ürünün yüzey arızalarının erkenden teşhis edilmesi, kalite kontrol süreçleri otomasyonu, maliyetlerin azaltılması ve kalite standartlarının korunması açısından kritiktir. Akıllı üretim sistemlerinde çoklu hata teşhisi ile birbirinden farklı türdeki arızaların saptanması sağlanmaktadır. Endüstri 4.0 ile üretim hatlarında veri miktarının artması sonucunda, klasik makine öğrenmesi yaklaşımları ile arızanın teşhis edilmesi yetersiz olması sonucunu doğurmuştur. Bu durumda, daha gelişmiş analiz yöntemlerine ihtiyaç artmıştır. Bu kapsamda bu tezde, hibrit derin öğrenme mimarileri ile farklı türdeki arızalı veri örneklerinin sınıflandırılması yüksek doğruluklarla sağlanmıştır. Bu tezde, metal ve kumaş yüzeylerde meydana gelen çoklu kusurların belirlenmesi için hibrit derin öğrenme yaklaşımları incelenmiştir. Önerilen yöntemde, farklı derin öğrenme mimarileri birlikte kullanılarak hem nesne tespiti hem de segmentasyon işlemleri gerçekleştirilmiştir. Bu çalışmada, arızalı görüntülerden elde edilen özellikler konvolüsyonel sinir ağları ile çıkarılmış, ardından bu özellikler farklı sınıflandırıcılar ile analiz edilmiştir. Sınıflandırma aşamasında kullanılan derin mimariler Vision Transformer (ViT) ve dikkat tabanlı derin sinir ağları gibi yenilikçi yaklaşımlardır. Gerçekleştirilen deneysel çalışmalar sonucunda görülmüştür ki önerilen yöntem farklı tipteki arızaları yüksek performans elde edilmiştir. Bu çalışma, akıllı üretim sistemlerinde kalite kontrol süreçlerinin iyileştirilmesine katkı sağlamaktadır.
Karmaşık olay işleme sistemleri için gerçek zamanlı olay ilişkilendirme ve alarm kural madenciliği modelleri
World is creating the same quantity of data every two days, as it created from up until 2003. Evolving data streams are key factor for the growth of data created over the last few years. Streaming data analysis in real-time is becoming the fastest and most effective way to get useful information from what is happening right now, thus allowing organizations to take action quickly when problems occur or to detect new trends to improve their performance. Data stream analytics is needed to manage the data currently produced from applications such as sensor networks, measurements in network monitoring, mobile traffic management, web click streams, mobile call detail records,social media posts/blogs and many others. Stream data analytics is hard because data are temporally ordered, fast changing, massive and potentially infinite. In order to cope with the challenges of data stream mining, in this thesis two main contributions are discussed. Both of them summarize the high volume streaming data and present meaningful, actionable information to end users. The first one is finding ?event correlations? over the data stream pairs on real GPS data of public transportation buses. The second one is alarm sequence rule mining, with a new parameter called ?time confidence?, that helps automatically set time-window values for registered rules and also reduces the generated alarm rule count.
Üç boyutlu konumlandırma problemleri için yeni bir veri eşleştirme çözüm yöntemi: One-poınt ransac wıth epıpolar constraınt
The problem of Localization or Simultaneous Localization and Mapping has received a great deal of attention within the robotics literature, and the importance of the solutions to this problem has been well documented for successful operation of autonomous agents in a number of environments. Of the numerous solutions that have been developed for solving the problems, many of the most successful approaches continue to either rely on, or stem from noise ltering techniques, especially the Extended Kalman Filter method or Particle Filtering methods. Localization problems are downgraded to a data association problem after using mentioned lters. This topic has also received a great deal of attention in the robotics literature in recent years, and various solutions have been proposed. In the thesis, rst mostly studied methods, such as Joint Compatibility, Sequential Compatibility Nearest Neighbor, Joint Maximum Likelihood, one point RANSAC and epipolar consistency, are studied. As the second part of the thesis a new method is presented. One-Point RANSAC with Epipolar Constraint (OPRF) is based on RANSAC and epipolar geometry. Later the performance and consistency of the method will be compared to epipolar consistency solution.
Bir yabancı dilde bilgi çıkarımı sonuçlarının semantik temsilciliğinin sağlanması ve bir uygulama
Son yıllarda İnternet'in hızla gelişmesi ve yaygın kullanımı ile Web, dünyada erişilebilir en geniş veri kaynağı haline gelmiştir. Internet'teki bilgi yığınları aşırı şekilde artarken, Web ziyaretçilerinin isteklerine uygun hizmetlerin sağlanabilmesi, Web site yapısının iyileştirilebilmesi, geliştirilebilmesi ve etkin olarak kullanılabilmesi gibi amaçları sağlamak için kullanılan Bilgi Çıkarım Metodu, gün geçtikçe daha çok ilgi çeken bir konu haline gelmiştir.En büyük bilgi kaynağı olarak görülen İnternet'te, bilgiye ulaşabilmenin önündeki en büyük engel, içindeki bilgilerin %90'ının doğal dille oluşturulmuş olmasıdır. Bilgisayarların doğal dili henüz yeterli bir şekilde anlayamıyor olmalarından dolayı sayfalardaki bilgileri bulup çıkarmak yine insanlara düşmektedir.Bu çalışma, doğal dillerden bilgiyi elde etmek için kullanılan metotlardan biri olan Bilgi Çıkarımı'na (Information Extraction) dayanarak geliştirilmektedir. Bu kapsamda doğal dillerin bileşenleri olan sıfatlar, isimler, fiiller, zarflar vb. kaynaklar kullanılarak nitel bir sınıflandırma çıktısı elde edilmes amaçlanmaktadır. Bu çalışmada odaklanılan yabancı dil Arapça olarak seçilmiş ve teknoloji olarak Java diliyle geliştirilmiş olan GATE platformu tercih edilmiştir.
Tümce kökenli konu modelleme
Fast augmentation of large text collections in digital world makes inevitable to automatically extract short descriptions of those texts. Even if a lot of studies have been done on detecting hidden topics in text corpora, almost all models follow the bag-of-words assumption. This study presents a new unsupervised learning method that reveals topics in a text corpora and the topic distribution of each text in the corpora. The texts in the corpora are described by a generative graphical model, in which each sentence is generated by a single topic and the topics of consecutive sentences follow a hidden Markov chain. In contrast to bag-of-words paradigm, the model assumes each sentence as a unit block and builds on a memory of topics slowly changing in a meaningful way as the text flows. The results are evaluated both qualitatively by examining topic keywords from particular text collections and quantitatively by means of perplexity, a measure of generalization of the model. Keywords: probabilistic graphical model, topic model, hidden Markov model, Markov chain Monte Carlo.
Contextproxy: Ağ tabanlı bağlamdan-haberdar hizmetleri ve uygulamaları desteklemek için yerden-haberdar HTTP proxy sunucusu
ABSTRACT CONTEXTPROXY: A LOCATION-AWARE HTTP PROXY SERVER TO SUPPORT WEB BASED CONTEXT-AWARE SERVICES AND APPLICATIONS Alper R. Uluçınar M.S. in Computer Engineering Supervisor: Asst Prof. Dr. David Davenport January, 2005 The pervasion of computing in our physical world promises more than the ubiquitous availability of computing resources; totally new and exciting interaction schemes are to be explored. Context-awareness, one of the most important aspects of ubiquitous computing, enables applications that make use of their users' context to provide dynamically adapting information and services to their users or to other applications. Although the technological infrastructure to support ubiquitous and context-aware applications is being deployed rapidly, the standards and the best practices for the interactions of various components in a context-aware application are still missing. In our work we have developed a location-aware HTTP proxy server, called ContextProxy that runs on the popular Symbian platform. ContextProxy acts as a standard HTTP proxy server from the client application's perspective but it augments the service request of the client with the available location information while submitting the request to the service provider. This allows the existing nomadic applications to immediately become location- aware if they can be configured to make use of a standard HTTP proxy which is a common scheme for web based applications. And also it is possible to write new nomadic applications without considering the context-awareness aspect at the service requestor level. The contextual information added by ContextProxy can then be utilized by the service provider to dynamically adapt its services according to the service requestor's context. Keywords: Context- Aware/Nomadic Computing, Symbian, Bluetooth, GSM m