Browsing by Subject "Information science"
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Item Open Access Algorithms for sink mobility in wireless sensor networks to improve network lifetime(Springer, 2012-09) Koç, Metin; Körpeoğlu, İbrahimSink mobility is an effective solution in the literature for wireless sensor network lifetime improvement. In this paper, we propose a set of algorithms for sink site determination (SSD) and movement strategy problems of sink mobility. We also present experiment results that compare the performance of our algorithms with other approaches in the literature. © 2012 Springer-Verlag London Limited.Item Open Access Auction based scheduling for distributed systems(International Institute of Informatics and Systemics, 2006) Zarifoğlu, Emrah; Sabuncuoğlu, İhsanBusinesses deal with huge databases over a geographically distributed supply network. When this is combined with scheduling and planning needs, it becomes too difficult to handle. Recently, Fast Consumer Goods sector tends to consolidate their manufacturing facilities on a single supplier serving to a distributed customer network. This decentralized structure causes imperfect information sharing between customers and the supplier. We model this problem as a single machine distributed scheduling problem with job agents representing the customers and the machine agent representing the supplier. We developed Auction Based Algorithm by exploiting the opportunity to use game theoretic approach to solve the problem in the decentralized utility case. Results of our extensive computational experiments indicate that Auction Based Algorithm converges to the upper bound found for the total utility measure.Item Open Access Authorship attribution: performance of various features and classification methods(IEEE, 2007-11) Bozkurt, İlker Nadi; Bağlıoğlu, Özgür; Uyar, ErkanAuthorship attribution is the process of determining the writer of a document. In literature, there are lots of classification techniques conducted in this process. In this paper we explore information retrieval methods such as tf-idf structure with support vector machines, parametric and nonparametric methods with supervised and unsupervised (clustering) classification techniques in authorship attribution. We performed various experiments with articles gathered from Turkish newspaper Milliyet. We performed experiments on different features extracted from these texts with different classifiers, and combined these results to improve our success rates. We identified which classifiers give satisfactory results on which feature sets. According to experiments, the success rates dramatically changes with different combinations, however the best among them are support vector classifier with bag of words, and Gaussian with function words. ©2007 IEEE.Item Open Access Automatic categorization of ottoman literary texts by poet and time period(Springer, London, 2012) Can, Ethem F.; Can, Fazlı; Duygulu, Pınar; Kalpaklı, MehmetMillions of manuscripts and printed texts are available in the Ottoman language. The automatic categorization of Ottoman texts would make these documents much more accessible in various applications ranging from historical investigations to literary analyses. In this work, we use transcribed version of Ottoman literary texts in the Latin alphabet and show that it is possible to develop effective Automatic Text Categorization techniques that can be applied to the Ottoman language. For this purpose, we use two fundamentally different machine learning methods: Naïve Bayes and Support Vector Machines, and employ four style markers: most frequent words, token lengths, two-word collocations, and type lengths. In the experiments, we use the collected works (divans) of ten different poets: two poets from five different hundred-year periods ranging from the 15th to 19th century. The experimental results show that it is possible to obtain highly accurate classifications in terms of poet and time period. By using statistical analysis we are able to recommend which style marker and machine learning method are to be used in future studies. © 2012 Springer-Verlag London Limited.Item Open Access Carcinoma cell line discrimination in microscopic images using unbalanced wavelets(IEEE, 2012-03) Keskin, Furkan; Suhre, Alexander; Erşahin, Tüli,; Çetin Atalay, Rengül; Çetin, A. EnisCancer cell lines are widely used for research purposes in laboratories all over the world. In this paper, we present a novel method for cancer cell line image classification, which is very costly by conventional methods. The aim is to automatically classify 14 different classes of cell lines including 7 classes of breast and 7 classes of liver cancer cells. Microscopic images containing irregular carcinoma cell patterns are represented by randomly selected subwindows which possibly correspond to foreground pixels. For each subwindow, a correlation descriptor utilizing the fractional unbalanced wavelet transform coefficients and several morphological attributes as pixel features is computed. Directionally selective textural features are preferred primarily because of their ability to characterize singularities at multiple orientations, which often arise in carcinoma cell lines. A Support Vector Machine (SVM) classifier with Radial Basis Function (RBF) kernel is employed for final classification. Over a dataset of 280 images, we achieved an accuracy of 88.2%, which outperforms the classical correlation based methods. © 2012 IEEE.Item Open Access Cepstrum based method for moving shadow detection in video(Springer, 2010-09) Cogun, Fuat; Çetin, A. EnisMoving shadows constitute problems in various applications such as image segmentation and object tracking. Main cause of these problems is the misclassification of the shadow pixels as target pixels. Therefore, the use of an accurate and reliable shadow detection method is essential to realize intelligent video processing applications. In this paper, the cepstrum based method for moving shadow detection is presented. The proposed method is tested on outdoor and indoor video sequences using well-known benchmark test sets. To show the improvements over previous approaches, quantitative metrics are introduced and comparisons based on these metrics are made. © 2011 Springer Science+Business Media B.V.Item Open Access A compression method based on compressive sampling for 3-D laser range scans of indoor environments(Springer, Dordrecht, 2010) Dobrucalı, Oğuzcan; Barshan, BillurWhen 3-D models of environments need to be transmitted or stored, they should be compressed efficiently to increase the capacity of the communication channel or the storage medium. We propose a novel compression technique based on compressive sensing, applied to sparse representations of 3-D range measurements. We develop a novel algorithm to generate sparse innovations between consecutive range measurements along the axis of the sensor's motion, since the range measurements do not have highly sparse representations in common domains. Compared with the performances of widely used compression techniques, the proposed method offers the smallest compression ratio and provides a reasonable balance between reconstruction error and processing time. © 2011 Springer Science+Business Media B.V.Item Open Access A content-based social network study of evliyâ çelebi's seyahatnâme-bitlis section(Springer, London, 2012) Karbeyaz, Ceyhun; Can, Ethem F; Can, Fazlı; Kalpaklı, MehmetEvliyâ Çelebi, an Ottoman writer, scholar and world traveler, visited most of the territories and also some of the neighboring countries of the Ottoman Empire in the seventeenth century. He took notes about his trips and wrote a 10-volume book called Seyahatnâme (Book of Travels). In this paper, we present two methods for constructing social networks by using textual data and apply it to Seyahatnâme-Bitlis Section from book IV. The first social network construction method is based on proximity of co-occurence of names. The second method is based on 2-pair associations obtained by association rule mining by using sliding text blocks as transactions. The social networks obtained by these two methods are validated using a Monte Carlo approach by comparing them with the social network created by a scholar-historian. © 2012 Springer-Verlag London Limited.Item Open Access Data and model driven hybrid approach to activity scoring of cyclic pathways(Springer, Dordrecht, 2010) Işık, Z.; Atalay V.; Aykanat, Cevdet; Çetin-Atalay, RengülAnalysis of large scale -omics data based on a single tool remains inefficient to reveal molecular basis of cellular events. Therefore, data integration from multiple heterogeneous sources is highly desirable and required. In this study, we developed a data- and model-driven hybrid approach to evaluate biological activity of cellular processes. Biological pathway models were taken as graphs and gene scores were transferred through neighbouring nodes of these graphs. An activity score describes the behaviour of a specific biological process was computed by owing of converged gene scores until reaching a target process. Biological pathway model based approach that we describe in this study is a novel approach in which converged scores are calculated for the cellular processes of a cyclic pathway. The convergence of the activity scores for cyclic graphs were demonstrated on the KEGG pathways. © 2011 Springer Science+Business Media B.V.Item Open Access Editing heightfield using history management and 3D widgets(IEEE, 2009-09) Yalçın, M. Aydın; Çapin, Tolga K.In virtual environments, terrain is generally modeled by heightfield, a 2D structure. To be able to create desired terrain geometry, software editors for this specific task have been developed. The graphics hardware, data structures and rendering techniques are developing fast to open up new possibilities to the user and terrain editor functionalities are following such improvements (such as real-time lighting updates during editing operations and multi-texture blending). Yet, current terrain editors mostly fail to give the user feedback about their actions and also fail to help the users understand and undo the editing operations on the terrain. The aim of this study is to investigate the 3d-widget based visualization of possible editing (sculpturing) actions on terrain and to help user undo previous operations. © 2009 IEEE.Item Open Access Efficiency and effectiveness of query processing in cluster-based retrieval(Elsevier, 2004) Can, F.; Altingövde I.S.; Demir, E.Our research shows that for large databases, without considerable additional storage overhead, cluster-based retrieval (CBR) can compete with the time efficiency and effectiveness of the inverted index-based full search (FS). The proposed CBR method employs a storage structure that blends the cluster membership information into the inverted file posting lists. This approach significantly reduces the cost of similarity calculations for document ranking during query processing and improves efficiency. For example, in terms of in-memory computations, our new approach can reduce query processing time to 39% of FS. The experiments confirm that the approach is scalable and system performance improves with increasing database size. In the experiments, we use the cover coefficient-based clustering methodology (C3M), and the Financial Times database of TREC containing 210158 documents of size 564 MB defined by 229748 terms with total of 29545234 inverted index elements. This study provides CBR efficiency and effectiveness experiments using the largest corpus in an environment that employs no user interaction or user behavior assumption for clustering. © 2003 Elsevier Ltd. All rights reserved.Item Open Access Energy consumption forecasting via order preserving pattern matching(IEEE, 2014-12) Vanlı, N. Denizcan; Sayın, Muhammed O.; Yıldız, Hikmet; Göze, Tolga; Kozat, Süleyman S.We study sequential prediction of energy consumption of actual users under a generic loss/utility function. Particularly, we try to determine whether the energy usage of the consumer will increase or decrease in the future, which can be subsequently used to optimize energy consumption. To this end, we use the energy consumption history of the users and define finite state (FS) predictors according to the relative ordering patterns of these past observations. In order to alleviate the overfitting problems, we generate equivalence classes by tying several states in a nested manner. Using the resulting equivalence classes, we obtain a doubly exponential number of different FS predictors, one among which achieves the smallest accumulated loss, hence is optimal for the prediction task. We then introduce an algorithm to achieve the performance of this FS predictor among all doubly exponential number of FS predictors with a significantly reduced computational complexity. Our approach is generic in the sense that different tying configurations and loss functions can be incorporated into our framework in a straightforward manner. We illustrate the merits of the proposed algorithm using the real life energy usage data. © 2014 IEEE.Item Open Access Energy cost model for frequent item set discovery in unstructured P2P networks(Springer, London, 2012) Cem, E.; Demirkaya, Ender; Esiner, E.; Ozaydin, B.; Ozkasap O.For large scale distributed systems, designing energy efficient protocols and services has become as significant as considering conventional performance criteria like scalability, reliability, fault-tolerance and security. We consider frequent item set discovery problem in this context. Although it has attracted attention due to its extensive applicability in diverse areas, there is no prior work on energy cost model for such distributed protocols. In this paper, we develop an energy cost model for frequent item set discovery in unstructured P2P networks. To the best of our knowledge, this is the first study that proposes an energy cost model for a generic peer using gossip-based communication. As a case study protocol, we use our gossip-based approach ProFID for frequent item set discovery. After developing the energy cost model, we examine the effect of protocol parameters on energy consumption using our simulation model on PeerSim and compare push-pull method of ProFID with the well-known push-based gossiping approach. Based on the analysis results, we reformulate the upper bound for the peer's energy cost. © 2012 Springer-Verlag London Limited.Item Open Access G-network modelling based abnormal pathway detection in gene regulatory networks(Springer, London, 2012) Kim H.; Atalay, Rengül; Gelenbe, E.Gene expression centered gene regulatory networks studies can provide insight into the dynamics of pathway activities that depend on changes in their environmental conditions. Thus we propose a new pathway analysis approach to detect differentially behaving pathways in abnormal conditions based on G-network theory. Using this approach gene regulatory network model parameters are estimated from normal and abnormal samples using optimization techniques with corresponding constraints. We show that in a "p53 network" application, the proposed method effectively detects anomalous activated/inactivated pathways related with MDM2, ATM/ATR and RB1 genes, which could not be observed from previous analyses of gene regulatory network normal and abnormal behaviour. © 2012 Springer-Verlag London Limited.Item Open Access Generalized ID-based blind signatures from bilinear pairings(IEEE, 2008-10) Kalkan, Said; Kaya, Kamer; Selçuk, Ali AydınBlind signature schemes provide the feature that a user is able to get a signature without giving the actual message to the signer. Recently a number of ID-based blind signatures have been proposed. In this paper, we introduce the concept of generalized ID-based blind signatures based on ElGamal signature variants. We obtain several new ID-based blind signatures from this generalized scheme which have not been explored before and some of them turn out to be more efficient than previously proposed schemes. © 2008 IEEE.Item Open Access Generalized ID-based ElGamal signatures(IEEE, 2007-11) Kalkan, Said; Kaya, Kamer; Selçuk, Ali AydınID-based cryptography has been a very active area of research in cryptography since bilinear pairings were introduced as a cryptographic tool, and there have been many proposals for ID-based signatures recently. In this paper, we introduce the concept of generalized ID-based ElGamal signatures and show that most of the proposed ID-based signature schemes in the literature are special instances of this generalized scheme. We also obtain numerous new signatures from this generalized scheme which have not been proposed before. ©2007 IEEE.Item Open Access Hypergraph-theoretic partitioning models for parallel web crawling(Springer, London, 2012) Türk, Ata; Cambazoğlu, B. Barla; Aykanat, CevdetParallel web crawling is an important technique employed by large-scale search engines for content acquisition. A commonly used inter-processor coordination scheme in parallel crawling systems is the link exchange scheme, where discovered links are communicated between processors. This scheme can attain the coverage and quality level of a serial crawler while avoiding redundant crawling of pages by different processors. The main problem in the exchange scheme is the high inter-processor communication overhead. In this work, we propose a hypergraph model that reduces the communication overhead associated with link exchange operations in parallel web crawling systems by intelligent assignment of sites to processors. Our hypergraph model can correctly capture and minimize the number of network messages exchanged between crawlers. We evaluate the performance of our models on four benchmark datasets. Compared to the traditional hash-based assignment approach, significant performance improvements are observed in reducing the inter-processor communication overhead. © 2012 Springer-Verlag London Limited.Item Open Access Induction of logical relations based on specific generalization of strings(IEEE, 2007-11) Uzun, Yasin; Çiçekli, İlyasLearning logical relations from examples expressed as first order facts has been studied extensively by the Inductive Logic Programming research. Learning with positive-only data may cause over generalization of examples leading to inconsistent resulting hypotheses. A learning heuristic inferring specific generalization of strings based on unique match sequences is shown to be capable of learning predicates with string arguments. This paper describes an inductive learner based on the idea of specific generalization of strings, and the given clauses are generalized by considering the background knowledge. ©2007 IEEE.Item Open Access Information arts and information science: time to unite?(Wiley, 2006) Karamuftuoglu, M.This article explicates the common ground between two currently independent fields of Inquiry, namely information arts and information science, and suggests a frame-work that could unite them as a single field of study. The article defines and clarifies the meaning of information art and presents an axiological framework that could be used to judge the value of works of information art. The axiological framework is applied to examples of works of information art to demonstrate its use. The article argues that both Information arts and Information science could be studied under a common framework; namely, the domain-analytic or sociocognitive approach. It also is argued that the unification of the two fields could help enhance the meaning and scope of both information science and information arts and therefore be beneficial to both fields.Item Open Access Joint visual attention modeling for naturally interacting robotic agents(IEEE, 2009-09) Yücel, Zeynep; Salah, A. A.; Meriçli, C.; Meriçli, T.This paper elaborates on mechanisms for establishing visual joint attention for the design of robotic agents that learn through natural interfaces, following a developmental trajectory not unlike infants. We describe first the evolution of cognitive skills in infants and then the adaptation of cognitive development patterns in robotic design. A comprehensive outlook for cognitively inspired robotic design schemes pertaining to joint attention is presented for the last decade, with particular emphasis on practical implementation issues. A novel cognitively inspired joint attention fixation mechanism is defined for robotic agents. © 2009 IEEE.
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