Browsing by Subject "Graphic methods"

Now showing 1 - 20 of 23

Open Access
ALACA: a platform for dynamic alarm collection and alert notification in network management systems
(John Wiley and Sons Ltd., 2017) Solmaz, S. E.; Gedik, B.; Ferhatosmanoğlu, H.; Sözüer, S.; Zeydan, E.; Etemoğlu, Ç. Ö.
Mobile network operators run Operations Support Systems that produce vast amounts of alarm events. These events can have different significance levels and domains and also can trigger other ones. Network operators face the challenge to identify the significance and root causes of these system problems in real time and to keep the number of remedial actions at an optimal level, so that customer satisfaction rates can be guaranteed at a reasonable cost. In this paper, we propose a scalable streaming alarm management system, referred to as Alarm Collector and Analyzer, that includes complex event processing and root cause analysis. We describe a rule mining and root cause analysis solution for alarm event correlation and analyses. The solution includes a dynamic index for matching active alarms, an algorithm for generating candidate alarm rules, a sliding window–based approach to save system resources, and a graph-based solution to identify root causes. Alarm Collector and Analyzer is used in the network operation center of a major mobile telecom provider. It helps operators to enhance the design of their alarm management systems by allowing continuous analysis of data and event streams and predict network behavior with respect to potential failures by using the results of root cause analysis. We present experimental results that provide insights on performance of real-time alarm data analytics systems. Copyright © 2017 John Wiley & Sons, Ltd.
Open Access
Algorithms for effective querying of compound graph-based pathway databases
(BioMed Central Ltd., 2009-11-16) Doğrusöz, Uğur; Çetintaş, Ahmet; Demir, Emek; Babur, Özgün
Background: Graph-based pathway ontologies and databases are widely used to represent data about cellular processes. This representation makes it possible to programmatically integrate cellular networks and to investigate them using the well-understood concepts of graph theory in order to predict their structural and dynamic properties. An extension of this graph representation, namely hierarchically structured or compound graphs, in which a member of a biological network may recursively contain a sub-network of a somehow logically similar group of biological objects, provides many additional benefits for analysis of biological pathways, including reduction of complexity by decomposition into distinct components or modules. In this regard, it is essential to effectively query such integrated large compound networks to extract the sub-networks of interest with the help of efficient algorithms and software tools. Results: Towards this goal, we developed a querying framework, along with a number of graph-theoretic algorithms from simple neighborhood queries to shortest paths to feedback loops, that is applicable to all sorts of graph-based pathway databases, from PPIs (protein-protein interactions) to metabolic and signaling pathways. The framework is unique in that it can account for compound or nested structures and ubiquitous entities present in the pathway data. In addition, the queries may be related to each other through "AND" and "OR" operators, and can be recursively organized into a tree, in which the result of one query might be a source and/or target for another, to form more complex queries. The algorithms were implemented within the querying component of a new version of the software tool PATIKAweb (Pathway Analysis Tool for Integration and Knowledge Acquisition) and have proven useful for answering a number of biologically significant questions for large graph-based pathway databases. Conclusion: The PATIKA Project Web site is http://www.patika.org. PATIKAweb version 2.1 is available at http://web.patika.org. © 2009 Dogrusoz et al; licensee BioMed Central Ltd.
Open Access
Architectural sketch recognition
(1990) Durgun, Fatoş Bengi; Özgüç, Bülent
Sketch recognition is applied to freehand architectural drawings. The purpose is to recognize the architect’s intentions from a quick sketch and generate a detailed drawing. The system can also calibrate itself to interpret the peculiar styles of each individual architect using it. © 1990 Taylor and Francis Group, LLC.
Open Access
Autofocus method in thermal cameras based on image histogram
(IEEE, 2011) Turgay, E.; Teke, Oğuzhan
In this paper, a new histogram based auto-focusing method for thermal cameras is proposed. This proposed method is realized by FPGA (Field Programmable Gate Array) and DSP (Digital Signal Processor) working together and simultaneously. HF (High Frequency) component, obtained from real-time image flow by FPGA and DSP is used for auto-focusing process. Proposed method is able to determine the focus direction from the HF component produced in the process of histogram equalization by FPGA, unlike Fourier transform and pixel differenve based methods in the literature. With this superiority, proposed method requires no extra calculation for thermal cameras for which histogram equalization is necessary. Analysis show that proposed method is successful on the simulations and scanning thermal cameras.
Open Access
Çizge kesit yöntemi ile hiperspektral görüntülerde anomali tabanlı hedef tespiti
(IEEE, 2015-05) Batı, E.; Erdinç, Acar; Çeşmeci, D.; Çalışkan, A.; Koz, A.; Aksoy, Selim; Ertürk, S.; Alatan, A. A.
Hiperspektral hedef tespiti için yürütülen çalışmalar genel olarak iki sınıfta degerlendirilebilir. İlk sınıf olan anomali tespit yöntemlerinde, hedefin görüntünün geri kalanından farklı oldugu bilgisi kullanılarak görüntü analiz edilmektedir. Diğer sınıfta ise daha önceden bilgisi edinilmiş hedefe ait spektral imza ile görüntüdeki herbir piksel arasındaki benzerlik bulunarak hedefin konumu tespit edimektedir. Her iki sınıf yöntemin de önemli bir dezavantajı hiperspektral görüntü piksellerini bagımsız olarak degerlendirip, aralarındaki komşuluk ilişkilerini gözardı etmesidir. Bu makalede anomali tespit ve imza tabanlı tespit yakla¸sımlarını, pikseller arası komşuluk ilişkilerini de göz önünde bulundurarak birleştiren çizge yaklaşımına dayalı yeni bir yöntem önerilmiştir. Hedeflerin hem imza bilgisine sahip olundugu hem de anomali sayılabilecek ölçülerde olduğu varsayılarak önerilen çizge yaklaşımında önplan için imza bilgisi kullanan özgün bir türev tabanlı uyumlu filtre önerilmiştir. Arkaplan için ise seyreklik bilgisi kullanarak Gauss karışım bileşeni kestirimi yapan yeni bir anomali tespit yöntemi geliştirilmiştir. Son olarak komşular arası benzerligi tanımlamak için ise spektral bir benzerlik ölçütü olan spektral açı eleştiricisi kullanılmıştır. Önerilen çizge tabanlı yöntemin önplan, arkaplan ve komşuluk ilişkilerini uygun şekilde birleştirdigi ve önceki yöntemlere göre hedefi gürültüden arınmış bir bütün şeklinde başarıyla tespit edebildigi gözlemlenmiştir. The studies on hyperspectral target detection until now, has been treated in two approaches. Anomaly detection can be considered as the first approach, which analyses the hyperspectral image with respect to the difference between target and the rest of the hyperspectral image. The second approach compares the previously obtained spectral signature of the target with the pixels of the hyperspectral image in order to localize the target. A distinctive disadvantage of the aforementioned approaches is to treat each pixel of the hyperspectral image individually, without considering the neighbourhood relations between the pixels. In this paper, we propose a target detection algorithm which combines the anomaly detection and signature based hyperspectral target detection approaches in a graph based framework by utilizing the neighbourhood relations between the pixels. Assuming that the target signature is available and the target sizes are in the range of anomaly sizes, a novel derivative based matched filter is first proposed to model the foreground. Second, a new anomaly detection method which models the background as a Gaussian mixture is developed. The developed model estimates the optimal number of components forming the Gaussian mixture by means of utilizing sparsity information. Finally, the similarity of the neighbouring hyperspectral pixels is measured with the spectral angle mapper. The overall proposed graph based method has successfully combined the foreground, background and neighbouring information and improved the detection performance by locating the target as a whole object free from noises. © 2015 IEEE.
Open Access
Distributed block formation and layout for disk-based management of large-scale graphs
(Springer, 2017) Yaşar, A.; Gedik, B.; Ferhatosmanoğlu, H.
We are witnessing an enormous growth in social networks as well as in the volume of data generated by them. An important portion of this data is in the form of graphs. In recent years, several graph processing and management systems emerged to handle large-scale graphs. The primary goal of these systems is to run graph algorithms and queries in an efficient and scalable manner. Unlike relational data, graphs are semi-structured in nature. Thus, storing and accessing graph data using secondary storage requires new solutions that can provide locality of access for graph processing workloads. In this work, we propose a scalable block formation and layout technique for graphs, which aims at reducing the I/O cost of disk-based graph processing algorithms. To achieve this, we designed a scalable MapReduce-style method called ICBL, which can divide the graph into a series of disk blocks that contain sub-graphs with high locality. Furthermore, ICBL can order the resulting blocks on disk to further reduce non-local accesses. We experimentally evaluated ICBL to showcase its scalability, layout quality, as well as the effectiveness of automatic parameter tuning for ICBL. We deployed the graph layouts generated by ICBL on the Neo4j open source graph database, http://www.neo4j.org/ (2015) graph database management system. Our results show that the layout generated by ICBL reduces the query running times over Neo4j more than 2 × compared to the default layout. © 2017, Springer Science+Business Media New York.
Open Access
Economic design of EWMA control charts based on loss function
(Elsevier, 2009) Serel, D. A.
For monitoring the stability of a process, various control charts based on exponentially weighted moving average (EWMA) statistics have been proposed in the literature. We study the economic design of EWMA-based mean and dispersion charts when a linear, quadratic, or exponential loss function is used for computing the costs arising from poor quality. The chart parameters (sample size, sampling interval, control limits and smoothing constant) minimizing the overall cost of the control scheme are determined via computational methods. Using numerical examples, we compare the performances of the EWMA charts with Shewhart over(X, -) and S charts, and investigate the sensitivity of the chart parameters to changes in process parameters and loss functions. Numerical results imply that rather than sample size or control limits, the users need to adjust the sampling interval in response to changes in the cost of poor quality.
Open Access
An experiment to observe the impact of UML diagrams on the effectiveness of software requirements inspections
(IEEE, 2009) Albayrak, Özlem
Software inspections aim to find defects early in the development process and studies have found them to be effective. However, there is almost no data available regarding the impact of UML diagram utilization in software requirements specification documents on inspection effectiveness. This paper addresses this issue by investigating whether inclusion of UML diagrams impacts the effectiveness of requirements inspection. We conducted an experiment in an academic environment with 35 subjects to empirically investigate the impact of UML diagram inclusion on requirements inspections' effectiveness and the number of reported defects. The results show that including UML diagrams in requirements specification document significantly impacts the number of reported defects, and there is no significant impact on the effectiveness of individual i nspections. © 2009 IEEE.
Open Access
Fast ray tracing 3D models
(1991) İşler, Veysi; Özgüç, Bülent
In many computer graphics applications such as CAD, realistic displays have very important and positive effects on the users of the system. There are several techniques to generate realistic images with the computer. Ray tracing gives the most effective results by simulating the interaction of light with its environment. However, it may require an excessive amount of time to generate an image. In this article, we present a survey of methods developed to speed up the ray tracing algorithm and introduce a fast ray tracer to process a 3D scene that is defined by interactive 3D modeling software.
Open Access
Finding faces in news photos using both face and name information
(IEEE, 2006) Özkan, Derya; Duygulu, Pınar
We propose a method to associate names and faces for querying people in large news photo collections. On the assumption that a person's face is likely to appear when his/her name is mentioned in the caption, first all the faces associated with the query name are selected, Among these faces, there could be many faces corresponding to the queried person in different conditions, poses and times, but there could also be other faces corresponding to other people in the caption or some non-face images due to the errors in the face detection method used, However, in most cases, the number of corresponding faces of the queried person will be large, and these faces will be more similar to each other than to others. When the similarities of faces are represented in a graph structure, the set of most similar faces will be the densest component in the graph. In this study, we propose a graph-based method to find the most similar subset among the set of possible faces associated with the query name, where the most similar subset is likely to correspond to the faces of the queried person. © 2006 IEEE.
Open Access
GCap: Graph-based automatic image captioning
(IEEE, 2004) Pan J.-Y.; Yang H.-J.; Faloutsos C.; Duygulu, Pınar
Given an image, how do we automatically assign keywords to it? In this paper, we propose a novel, graph-based approach (GCap) which outperforms previously reported methods for automatic image captioning. Moreover, it is fast and scales well, with its training and testing time linear to the data set size. We report auto-captioning experiments on the "standard" Corel image database of 680 MBytes, where GCap outperforms recent, successful auto-captioning methods by up to 10 percentage points in captioning accuracy (50% relative improvement). © 2004 IEEE.
Open Access
Human action recognition with line and flow histograms
(IEEE, 2008-12) İkizler, Nazlı; Cinbiş, R. Gökberk; Duygulu, Pınar
We present a compact representation for human action recognition in videos using line and optical flow histograms. We introduce a new shape descriptor based on the distribution of lines which are fitted to boundaries of human figures. By using an entropy-based approach, we apply feature selection to densify our feature representation, thus, minimizing classification time without degrading accuracy. We also use a compact representation of optical flow for motion information. Using line and flow histograms together with global velocity information, we show that high-accuracy action recognition is possible, even in challenging recording conditions. © 2008 IEEE.
Open Access
Image classification using subgraph histogram representation
(IEEE, 2010) Özdemir, Bahadır; Aksoy, Selim
We describe an image representation that combines the representational power of graphs with the efficiency of the bag-of-words model. For each image in a data set, first, a graph is constructed from local patches of interest regions and their spatial arrangements. Then, each graph is represented with a histogram of subgraphs selected using a frequent subgraph mining algorithm in the whole data. Using the subgraphs as the visual words of the bag-of-words model and transforming of the graphs into a vector space using this model enables statistical classification of images using support vector machines. Experiments using images cut from a large satellite scene show the effectiveness of the proposed representation in classification of complex types of scenes into eight high-level semantic classes. © 2010 IEEE.
Open Access
Image histogram thresholding using Gaussian kernel density estimation (English)
(IEEE, 2013) Suhre, Alexander; Çetin, A. Enis
In this article, image histogram thresholding is carried out using the likelihood of a mixture of Gaussians. In the proposed approach, a prob ability density function (PDF) of the histogram is computed using Gaussian kernel density estimation in an iterative manner. The threshold is found by iteratively computing a mixture of Gaussians for the two clusters. This process is aborted when the current bin is assigned to a different cluster than its predecessor. The method does not envolve an exhaustive search. Visual examples of our segmentation versus Otsu's thresholding method are presented. © 2013 IEEE.
Open Access
Large flat plate models in the physical optics method for RCS calculations
(IEEE, 2004-09) Altıntaş, Ayhan; Çelik, Aslıhan
The calculation of Radar Cross Section (RCS) of arbitrarily large perfectly conducting body is presented. The body is modelled as triangular meshes of any size by the help of graphical tools. For the calculation of scattered field, Physical Optics(PO) surface integral is analytically evaluated over each of the triangular meshes. Due to the analytical integration, there is no limitation on the size of the triangles.
Open Access
A line based pose representation for human action recognition
(2013) Baysal, S.; Duygulu, P.
In this paper, we utilize a line based pose representation to recognize human actions in videos. We represent the pose in each frame by employing a collection of line-pairs, so that limb and joint movements are better described and the geometrical relationships among the lines forming the human figure are captured. We contribute to the literature by proposing a new method that matches line-pairs of two poses to compute the similarity between them. Moreover, to encapsulate the global motion information of a pose sequence, we introduce line-flow histograms, which are extracted by matching line segments in consecutive frames. Experimental results on Weizmann and KTH datasets emphasize the power of our pose representation, and show the effectiveness of using pose ordering and line-flow histograms together in grasping the nature of an action and distinguishing one from the others. © 2013 Elsevier B.V. All rights reserved.
Open Access
LinGraph: a graph-based automated planner for concurrent task planning based on linear logic
(Springer New York LLC, 2017) Kortik S.; Saranli, U.
In this paper, we introduce an automated planner for deterministic, concurrent domains, formulated as a graph-based theorem prover for a propositional fragment of intuitionistic linear logic, relying on the previously established connection between intuitionistic linear logic and planning problems. The new graph-based theorem prover we introduce improves planning performance by reducing proof permutations that are irrelevant to planning problems particularly in the presence of large numbers of objects and agents with identical properties (e.g. robots within a swarm, or parts in a large factory). We first present our graph-based automated planner, the Linear Logic Graph Planner (LinGraph). Subsequently we illustrate its application for planning within a concurrent manufacturing domain and provide comparisons with four existing automated planners, BlackBox, Symba-2, Metis and the Temporal Fast Downward (TFD), covering a wide range of state-of-the-art automated planning techniques and implementations. We show that even though LinGraph does not rely on any heuristics, it still outperforms these systems for concurrent domains with large numbers of identical objects and agents. These gains persist even when existing methods on symmetry reduction and numerical fluents are used, with LinGraph capable of handling problems with thousands of objects. Following these results, we also show that plan construction with LinGraph is equivalent to multiset rewriting systems, formally relating LinGraph to intuitionistic linear logic. © 2017, Springer Science+Business Media New York.
Open Access
Ottoman archives explorer: a retrieval system for digital Ottoman archives
(Association for Computing Machinery, 2009-12) Yalniz, I. Z.; Altingovde, I. S.; Güdükbay, Uğur; Ulusoy, Özgür
This article presents Ottoman Archives Explorer, a Content-Based Retrieval (CBR) system based on character recognition for printed and handwritten historical documents. Several methods for character segmentation and recognition stages are investigated. In particular, sliding-window and histogram segmentation methods are coupled with recognition approaches using spatial features, neural networks, and a graph-based model. The prototype system provides CBR of document images using both example-based queries and a virtual keyboard to construct query words. © 2009 ACM.
Open Access
Quantifying input uncertainty in an assemble-to-order system simulation with correlated input variables of mixed types
(IEEE, 2014) Akçay, Alp; Biller, B.
We consider an assemble-to-order production system where the product demands and the time since the last customer arrival are not independent. The simulation of this system requires a multivariate input model that generates random input vectors with correlated discrete and continuous components. In this paper, we capture the dependence between input variables in an undirected graphical model and decouple the statistical estimation of the univariate input distributions and the underlying dependence measure into separate problems. The estimation errors due to finiteness of the real-world data introduce the so-called input uncertainty in the simulation output. We propose a method that accounts for input uncertainty by sampling the univariate empirical distribution functions via bootstrapping and by maintaining a posterior distribution of the precision matrix that corresponds to the dependence structure of the graphical model. The method improves the coverages of the confidence intervals for the expected profit the per period.
Open Access
RailwayDB: adaptive storage of interaction graphs
(Association for Computing Machinery, 2016) Soulé R.; Gedik, B.
We are living in an ever more connected world, where data recording the interactions between people, software systems, and the physical world is becoming increasingly prevalent. These data often take the form of a temporally evolving graph, where entities are the vertices and the interactions between them are the edges. We call such graphs interaction graphs. Various domains, including telecommunications, transportation, and social media, depend on analytics performed on interaction graphs. The ability to efficiently support historical analysis over interaction graphs requires effective solutions for the problem of data layout on disk. This paper presents an adaptive disk layout called the railway layout for optimizing disk block storage for interaction graphs. The key idea is to divide blocks into one or more sub-blocks. Each sub-block contains the entire graph structure, but only a subset of the attributes. This improves query I/O, at the cost of increased storage overhead. We introduce optimal integer linear program (ILP) formulations for partitioning disk blocks into sub-blocks with overlapping and nonoverlapping attributes. Additionally, we present greedy heuristics that can scale better compared to the ILP alternatives, yet achieve close to optimal query I/O. We provide an implementation of the railway layout as part of RailwayDB—an open-source graph database we have developed. To demonstrate the benefits of the railway layout, we provide an extensive experimental evaluation, including model-based as well as empirical results comparing our approach to baseline alternatives.