Browsing by Subject "Data processing"

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Anket : Değeri bilinmemiş şair ve yazarlar
(2001)
Open Access
Association rules for supporting hoarding in mobile computing environments
(IEEE, 2000) Saygın, Yücel; Ulusoy, Özgür; Elmagarmid, A. K.
One of the features that a mobile computer should provide is disconnected operation which is performed by hoarding. The process of hoarding can be described as loading the data items needed in the future to the client cache prior to disconnection. Automated hoarding is the process of predicting the hoard set without any user intervention. In this paper, we describe an application independent and generic technique for determining what should be hoarded prior to disconnection. Our method utilizes association rules that are extracted by data mining techniques for determining the set of items that should be hoarded to a mobile computer prior to disconnection. The proposed method was implemented and tested on synthetic data to estimate its effectiveness. Performance experiments determined that the proposed rule-based methods are effective in improving the system performance in terms of the cache hit ratio of mobile clients especially for small cache sizes.
Open Access
Automatic detection of salient objects and spatial relations in videos for a video database system
(Elsevier BV, 2008-10) Sevilmiş, T.; Baştan M.; Güdükbay, Uğur; Ulusoy, Özgür
Multimedia databases have gained popularity due to rapidly growing quantities of multimedia data and the need to perform efficient indexing, retrieval and analysis of this data. One downside of multimedia databases is the necessity to process the data for feature extraction and labeling prior to storage and querying. Huge amount of data makes it impossible to complete this task manually. We propose a tool for the automatic detection and tracking of salient objects, and derivation of spatio-temporal relations between them in video. Our system aims to reduce the work for manual selection and labeling of objects significantly by detecting and tracking the salient objects, and hence, requiring to enter the label for each object only once within each shot instead of specifying the labels for each object in every frame they appear. This is also required as a first step in a fully-automatic video database management system in which the labeling should also be done automatically. The proposed framework covers a scalable architecture for video processing and stages of shot boundary detection, salient object detection and tracking, and knowledge-base construction for effective spatio-temporal object querying. © 2008 Elsevier B.V. All rights reserved.
Open Access
Automatic performance evaluation of Web search engines
(Elsevier, 2004) Can, F.; Nuray, R.; Sevdik, A. B.
Measuring the information retrieval effectiveness of World Wide Web search engines is costly because of human relevance judgments involved. However, both for business enterprises and people it is important to know the most effective Web search engines, since such search engines help their users find higher number of relevant Web pages with less effort. Furthermore, this information can be used for several practical purposes. In this study we introduce automatic Web search engine evaluation method as an efficient and effective assessment tool of such systems. The experiments based on eight Web search engines, 25 queries, and binary user relevance judgments show that our method provides results consistent with human-based evaluations. It is shown that the observed consistencies are statistically significant. This indicates that the new method can be successfully used in the evaluation of Web search engines. © 2003 Elsevier Ltd. All rights reserved.
Open Access
Building user-defined runtime adaptation routines for stream processing applications
(VLDB Endowment, 2012) Jacques-Silva, G.; Gedik, B.; Wagle, R.; Wu, Kun-Lung; Kumar, V.
Stream processing applications are deployed as continuous queries that run from the time of their submission until their cancellation. This deployment mode limits developers who need their applications to perform runtime adaptation, such as algorithmic adjustments, incremental job deployment, and application-specific failure recovery. Currently, developers do runtime adaptation by using external scripts and/or by inserting operators into the stream processing graph that are unrelated to the data processing logic. In this paper, we describe a component called orchestrator that allows users to write routines for automatically adapting the application to runtime conditions. Developers build an orchestrator by registering and handling events as well as specifying actuations. Events can be generated due to changes in the system state (e.g., application component failures), built-in system metrics (e.g., throughput of a connection), or custom application metrics (e.g., quality score). Once the orchestrator receives an event, users can take adaptation actions by using the orchestrator actuation APIs. We demonstrate the use of the orchestrator in IBM's System S in the context of three different applications, illustrating application adaptation to changes on the incoming data distribution, to application failures, and on-demand dynamic composition. © 2012 VLDB Endowment.
Open Access
Context learning in Okapi
(1997) Göker, A.
A user who makes repeated use of a retrieval system may be assumed to have a context which is common to successive uses (even if the immediate need differs). An IR system which could make use of this context may be better able to match the specific need. A machine-learning approach to inferring the user's context is described, and the results of an evaluation experiment are given. There appears to be scope for IR systems to operate in this way.
Open Access
A data mining approach for location prediction in mobile environments
(Elsevier, 2005) Yavaş G.; Katsaros, D.; Ulusoy, Özgür; Manolopoulos, Y.
Mobility prediction is one of the most essential issues that need to be explored for mobility management in mobile computing systems. In this paper, we propose a new algorithm for predicting the next inter-cell movement of a mobile user in a Personal Communication Systems network. In the first phase of our three-phase algorithm, user mobility patterns are mined from the history of mobile user trajectories. In the second phase, mobility rules are extracted from these patterns, and in the last phase, mobility predictions are accomplished by using these rules. The performance of the proposed algorithm is evaluated through simulation as compared to two other prediction methods. The performance results obtained in terms of Precision and Recall indicate that our method can make more accurate predictions than the other methods. © 2004 Elsevier B.V. All rights reserved.
Open Access
Effect of inverted index partitioning schemes on performance of query processing in parallel text retrieval systems
(Springer, 2006-11) Cambazoğlu, B. Barla; Çatal, A.; Aykanat, Cevdet
Shared-nothing, parallel text retrieval systems require an inverted index, representing a document collection, to be partitioned among a number of processors. In general, the index can be partitioned based on either the terms or documents in the collection, and the way the partitioning is done greatly affects the query processing performance of the parallel system. In this work, we investigate the effect of these two index partitioning schemes on query processing. We conduct experiments on a 32-node PC cluster, considering the case where index is completely stored in disk. Performance results are reported for a large (30 GB) document collection using an MPI-based parallel query processing implementation. © Springer-Verlag Berlin Heidelberg 2006.
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Emerging technologies: Impacts on Distance learning
(1991) Dede, Christopher J.
Open Access
Flame detection in video using hidden Markov models
(IEEE, 2005) Töreyin, B. Uğur; Dedeoğlu, Yiğithan; Çetin, A. Enis
This paper proposes a novel method to detect flames in video by processing the data generated by an ordinary camera monitoring a scene. In addition to ordinary motion and color clues, flame flicker process is also detected by using a hidden Markov model. Markov models representing the flame and flame colored ordinary moving objects are used to distinguish flame flicker process from motion of flame colored moving objects. Spatial color variations in flame are also evaluated by the same Markov models, as well. These clues are combined to reach a final decision. False alarms due to ordinary motion of flame colored moving objects are greatly reduced when compared to the existing video based fire detection systems.
Open Access
From a calculus to an execution environment for stream processing
(ACM, 2012) Soulé, R.; Hirzel, M.; Gedik, Buğra; Grimm, R.
At one level, this paper is about River, a virtual execution environment for stream processing. Stream processing is a paradigm well-suited for many modern data processing systems that ingest high-volume data streams from the real world, such as audio/video streaming, high-frequency trading, and security monitoring. One attractive property of stream processing is that it lends itself to parallelization on multicores, and even to distribution on clusters when extreme scale is required. Stream processing has been co-evolved by several communities, leading to diverse languages with similar core concepts. Providing a common execution environment reduces language development effort and increases portability. We designed River as a practical realization of Brooklet, a calculus for stream processing. So at another level, this paper is about a journey from theory (the calculus) to practice (the execution environment). The challenge is that, by definition, a calculus abstracts away all but the most central concepts. Hence, there are several research questions in concretizing the missing parts, not to mention a significant engineering effort in implementing them. But the effort is well worth it, because using a calculus as a foundation yields clear semantics and proven correctness results. Copyright © 2012 ACM.
Open Access
From virtual to physical: Integration of chemical logic gates
(2011) Guliyev, R.; Ozturk, S.; Kostereli, Z.; Akkaya, E. U.
Integration by parts: Advanced information processing at the molecular level requires integrated logic gates, which has to date been possible only virtually. Now, two independently working AND molecular logic gates are brought together by "click" chemistry to form integrated logic gates which respond exactly as predicted from such an integration scheme (see picture, EET=excitation energy transfer).
Open Access
Hypergraph-theoretic partitioning models for parallel web crawling
(Springer, London, 2012) Türk, Ata; Cambazoğlu, B. Barla; Aykanat, Cevdet
Parallel 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.
Open Access
IBM streams processing language: analyzing big data in motion
(I B M Corp., 2013-05-17) Hirzel M.; Andrade, H.; Gedik, B.; Jacques-Silva, R.; Khandekar, R.; Kumar, V.; Mendell, M.; Nasgaard, H.; Schneider S.; Soule´, R.; Wu, K. L.
The IBM Streams Processing Language (SPL) is the programming language for IBM InfoSphere® Streams, a platform for analyzing Big Data in motion. By “Big Data in motion,” we mean continuous data streams at high data-transfer rates. InfoSphere Streams processes such data with both high throughput and short response times. To meet these performance demands, it deploys each application on a cluster of commodity servers. SPL abstracts away the complexity of the distributed system, instead exposing a simple graph-of-operators view to the user. SPL has several innovations relative to prior streaming languages. For performance and code reuse, SPL provides a code-generation interface to C++ and Java®. To facilitate writing well-structured and concise applications, SPL provides higher-order composite operators that modularize stream sub-graphs. Finally, to enable static checking while exposing optimization opportunities, SPL provides a strong type system and user-defined operator models. This paper provides a language overview, describes the implementation including optimizations such as fusion, and explains the rationale behind the language design.
Open Access
An inquiry into the learning-style and knowledge-building preferences of interior architecture students
(Elsevier, 2016-05) Demirkan, H.
This study explores the learning-style and knowledge-building preferences of interior architecture students using Felder-Soloman's Index of Learning Styles. Considering the learning and knowledge-building skills of students in design education, this study concludes that the instructor should not only be a conveyor of knowledge but also a facilitator. The findings indicate that design students' preferred learning styles are as follows, in descending order: Sensing/Intuitive, Visual/Verbal, Active/Reflective and Sequential/Global. In the two-way analysis, where the student's design studio grade was the dependent variable, significant effects were obtained for each scale. Furthermore, double interactions were highly significant between the Active/Reflective and Sensing/Intuitive scales and between the Active/Reflective and Sequential/Global scales. © 2016 Elsevier Ltd. All rights reserved.
Open Access
Large-scale cluster-based retrieval experiments on Turkish texts
(ACM, 2007) Altıngövde, İsmail Şengör; Özcan, Rıfat; Öcalan Hüseyin C.; Can, Fazlı; Ulusoy, Özgür
We present cluster-based retrieval (CBR) experiments on the largest available Turkish document collection. Our experiments evaluate retrieval effectiveness and efficiency on both an automatically generated clustering structure and a manual classification of documents. In particular, we compare CBR effectiveness with full-text search (FS) and evaluate several implementation alternatives for CBR. Our findings reveal that CBR yields comparable effectiveness figures with FS. Furthermore, by using a specifically tailored cluster-skipping inverted index we significantly improve in-memory query processing efficiency of CBR in comparison to other traditional CBR techniques and even FS.
Open Access
Linear algebraic theory of partial coherence: discrete fields and measures of partial coherence
(SPIE, 2003-08) Özaktaş, Haldun M.; Yüksel, S.; Kutay, M. A.
We present a linear algebraic theory of partial coherence which allows precise mathematical definitions of concepts such as coherence and incoherence. This not only provides new perspectives and insights, but also allows us to employ the tools of linear algebra in applications. We define a scalar measure of the degree of partial coherence of an optical field which is zero for complete incoherence and unity for full coherence.
Open Access
Location and curvature estimation of "spherical" targets using a flexible sonar configuration
(IEEE, 1996) Barshan, Billur
A novel, flexible, three-dimensional (3-D) multi-sensor sonar system is employed to localize the center of a spherical target and estimate its radius of curvature. The interesting limiting cases for the problem under study are the point and planar targets, both of which are important for the characterization of a mobile robot's environment. A noise model is developed based on real sonar data. An extended Kalman filter (EKF) which incorporates the developed noise model is employed as an estimation tool for optimal processing of the sensor data. Simulations and experimental results are provided for specularly reflecting cylindrical targets.
Open Access
Mean-shift tracking of moving objects using multi-dimensional histograms
(Society of Photo-Optical Instrumentation Engineers (SPIE), 2004-04) Cüce, Halil I.; Çetin, A. Enis
In this paper, a moving object tracking algorithm for infrared image sequences is presented. The tracking algorithm is based on the mean-shift tracking method which is based on comparing the histograms of moving objects in consecutive image frames. In video obtained after visible light, the color histogram of the object is used for tracking. In forward looking infrared image sequences, the histogram is constructed not only from the pixel values but also from a highpass filtered version of the original image. The reason behind the use of highpass filter outputs in histogram construction is to capture structural nature of the moving object. Simulation examples are presented.
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Mental models in narrative comprehension
(1990) Bower, Gordon H.