Browsing by Subject "Probability"

Now showing 1 - 20 of 37

Open Access
Adaptive filtering for non-gaussian stable processes
(IEEE, 1994) Arıkan, Orhan; Çetin, A. Enis; Erzin, E.
A large class of physical phenomenon observed in practice exhibit non-Gaussian behavior. In this letter, a-stable distributions, which have heavier tails than Gaussian distribution, are considered to model non-Gaussian signals. Adaptive signal processing in the presence of such a noise is a requirement of many practical problems. Since direct application of commonly used adaptation techniques fail in these applications, new algorithms for adaptive filtering for α-stable random processes are introduced.
Open Access
Automated detection of objects using multiple hierarchical segmentations
(IEEE, 2007-07) Akçay H. Gökhan; Aksoy, Selim
We introduce an unsupervised method that combines both spectral and structural information for automatic object detection. First, a segmentation hierarchy is constructed by combining structural information extracted by morphological processing with spectral information summarized using principal components analysis. Then, segments that maximize a measure consisting of spectral homogeneity and neighborhood connectivity are selected as candidate structures for object detection. Given the observation that different structures appear more clearly in different principal components, we present an algorithm that is based on probabilistic Latent Semantic Analysis (PLSA) for grouping the candidate segments belonging to multiple segmentations and multiple principal components. The segments are modeled using their spectral content and the PLSA algorithm builds object models by learning the object-conditional probability distributions. Labeling of a segment is done by computing the similarity of its spectral distribution to the distribution of object models using Kullback-Leibler divergence. Experiments on two data sets show that our method is able to automatically detect, group, and label segments belonging to the same object classes. © 2007 IEEE.
Open Access
Automatic detection of geospatial objects using multiple hierarchical segmentations
(Institute of Electrical and Electronics Engineers, 2008-07) Akçay, H. G.; Aksoy, S.
The object-based analysis of remotely sensed imagery provides valuable spatial and structural information that is complementary to pixel-based spectral information in classification. In this paper, we present novel methods for automatic object detection in high-resolution images by combining spectral information with structural information exploited by using image segmentation. The proposed segmentation algorithm uses morphological operations applied to individual spectral bands using structuring elements in increasing sizes. These operations produce a set of connected components forming a hierarchy of segments for each band. A generic algorithm is designed to select meaningful segments that maximize a measure consisting of spectral homogeneity and neighborhood connectivity. Given the observation that different structures appear more clearly at different scales in different spectral bands, we describe a new algorithm for unsupervised grouping of candidate segments belonging to multiple hierarchical segmentations to find coherent sets of segments that correspond to actual objects. The segments are modeled by using their spectral and textural content, and the grouping problem is solved by using the probabilistic latent semantic analysis algorithm that builds object models by learning the object-conditional probability distributions. The automatic labeling of a segment is done by computing the similarity of its feature distribution to the distribution of the learned object models using the Kullback-Leibler divergence. The performances of the unsupervised segmentation and object detection algorithms are evaluated qualitatively and quantitatively using three different data sets with comparative experiments, and the results show that the proposed methods are able to automatically detect, group, and label segments belonging to the same object classes. © 2008 IEEE.
Open Access
Automatic multimedia cross-modal correlation discovery
(ACM, 2004-08) Pan, J.-Y.; Yang, H.-J.; Faloutsos, C.; Duygulu, Pınar
Given an image (or video clip, or audio song), how do we automatically assign keywords to it? The general problem is to find correlations across the media in a collection of multimedia objects like video clips, with colors, and/or motion, and/or audio, and/or text scripts. We propose a novel, graph-based approach, "MMG", to discover such cross-modal correlations. Our "MMG" method requires no tuning, no clustering, no user-determined constants; it can be applied to any multi-media collection, as long as we have a similarity function for each medium; and it scales linearly with the database size. We report auto-captioning experiments on the "standard" Corel image database of 680 MB, where it outperforms domain specific, fine-tuned methods by up to 10 percentage points in captioning accuracy (50% relative improvement).
Open Access
Available bit rate traffic engineering in MPLS networks with flow-based multipath routing
(Institute of Electronics Information and Communication Engineers, 2004) Akar, N.; Hökelek, İ.; Karasan, E.
In this paper, we propose a novel traffic engineering architecture for IP networks with MPLS backbones. In this architecture, two link-disjoint label switched paths, namely the primary and secondary paths, are established among every pair of IP routers located at the edges of an MPLS backbone network. As the main building block of this architecture, we propose that primary paths are given higher priority against the secondary paths in the MPLS data plane to cope with the so-called knock-on effect. Inspired by the ABR flow control mechanism in ATM networks, we propose to split traffic between a source-destination pair between the primary and secondary paths using explicit rate feedback from the network. Taking into consideration the performance deteriorating impact of packet reordering in packet-based load balancing schemes, we propose a traffic splitting mechanism that operates on a per-flow basis (i.e., flow-based multipath routing). We show via an extensive simulation study that using flow-based multipath traffic engineering with explicit rate feedback not only provides consistently better throughput than that of a single path but is also void of out-of-order packet delivery.
Open Access
Bounds on the capacity of random insertion and deletion-additive noise channels
(IEEE, 2013) Rahmati, M.; Duman, T. M.
We develop several analytical lower bounds on the capacity of binary insertion and deletion channels by considering independent uniformly distributed (i.u.d.) inputs and computing lower bounds on the mutual information between the input and output sequences. For the deletion channel, we consider two different models: i.i.d. deletion-substitution channel and i.i.d. deletion channel with additive white Gaussian noise (AWGN). These two models are considered to incorporate effects of the channel noise along with the synchronization errors. For the insertion channel case, we consider Gallager's model in which the transmitted bits are replaced with two random bits and uniform over the four possibilities independently of any other insertion events. The general approach taken is similar in all cases, however the specific computations differ. Furthermore, the approach yields a useful lower bound on the capacity for a wide range of deletion probabilities of the deletion channels, while it provides a beneficial bound only for small insertion probabilities (less than 0.25) of the insertion model adopted. We emphasize the importance of these results by noting that: 1) our results are the first analytical bounds on the capacity of deletion-AWGN channels, 2) the results developed are the best available analytical lower bounds on the deletion-substitution case, 3) for the Gallager insertion channel model, the new lower bound improves the existing results for small insertion probabilities. © 1963-2012 IEEE.
Open Access
Componentwise bounds for nearly completely decomposable Markov chains using stochastic comparison and reordering
(Elsevier, 2005) Pekergin, N.; Dayar T.; Alparslan, D. N.
This paper presents an improved version of a componentwise bounding algorithm for the state probability vector of nearly completely decomposable Markov chains, and on an application it provides the first numerical results with the type of algorithm discussed. The given two-level algorithm uses aggregation and stochastic comparison with the strong stochastic (st) order. In order to improve accuracy, it employs reordering of states and a better componentwise probability bounding algorithm given st upper- and lower-bounding probability vectors. Results in sparse storage show that there are cases in which the given algorithm proves to be useful. © 2004 Elsevier B.V. All rights reserved.
Open Access
Convexity properties of outage probability under Rayleigh fading
(IEEE, 2012) Dülek, Berkan; Vanlı, N. Denizcan; Gezici, Sinan
In this paper, convexity properties of outage probability are investigated under Rayleigh fading for an average power-constrained communications system that employs maximal-ratio combining (MRC) at the receiver. By studying the first and second order derivatives of the outage probability with respect to the transmitted signal power, it is found out that the outage probability is a monotonically decreasing function with a single inflection point. This observation suggests the possibility of improving the outage performance via on-off type power randomization/sharing under stringent average transmit power constraints. It is shown that the results can also be extended to the selection combining (SC) technique in a straightforward manner. Finally, a numerical example is provided to illustrate the theoretical results. © 2012 IEEE.
Unknown
Cost-effectiveness of adjuvant FOLFOX and 5FU/LV chemotherapy for patients with stage II colon cancer
(2013) Ayvaci, M.U.S.; Shi J.; Alagoz O.; Lubner, S.J.
Purpose. We evaluated the cost-effectiveness of adjuvant chemotherapy using 5-fluorouracil, leucovorin (5FU/LV), and oxaliplatin (FOLFOX) compared with 5FU/LV alone and 5FU/LV compared with observation alone for patients who had resected stage II colon cancer. Methods. We developed 2 Markov models to represent the adjuvant chemotherapy and follow-up periods and a single Markov model to represent the observation group. We used calibration to estimate the transition probabilities among different toxicity levels. The base case considered 60-year-old patients who had undergone an uncomplicated hemicolectomy for stage II colon cancer and were medically fit to receive 6 months of adjuvant chemotherapy. We measured health outcomes in quality-adjusted life-years (QALYs) and estimated costs using 2007 US dollars. Results. In the base case, adjuvant chemotherapy of the FOLFOX regimen had an incremental cost-effectiveness ratio (ICER) of $54,359/QALY compared with the 5FU/LV regimen, and the 5FU/LV regimen had an ICER of $14,584/QALY compared with the observation group from the third-party payer perspective. The ICER values were most sensitive to 5-year relapse probability, cost of adjuvant chemotherapy, and the discount rate for the FOLFOX arm, whereas the ICER value of 5FU/LV was most sensitive to the 5-year relapse probability, 5-year survival probability, and the relapse cost. The probabilistic sensitivity analysis indicates that the ICER of 5FU/LV is less than $50,000/QALY with a probability of 99.62%, and the ICER of FOLFOX as compared with 5FU/LV is less than $50,000/QALY and $100,000/QALY with a probability of 44.48% and 97.24%, respectively. Conclusion. Although adjuvant chemotherapy with 5FU/LV is cost-effective at all ages for patients who have undergone an uncomplicated hemicolectomy for stage II colon cancer, FOLFOX is not likely to be cost-effective as compared with 5FU/LV.
Unknown
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.
Unknown
Differentiated ABR: a new architecture for flow control and service differentiation in optical burst switched networks
(IEEE, 2005) Akar, Nail; Boyraz, Hakan
In this paper, we study a new control plane protocol, called Differentiated ABR (D-ABR), for flow control and service differentiation in optical burst switched networks. Using D-ABR, we show using simulations that the optical network can be designed to work at any desired burst blocking probability by the flow control service of the proposed architecture. This architecture requires certain modifications to the existing control plane mechanisms as well as incorporation of certain scheduling mechanisms at the ingress nodes; however we do not make any specific assumptions on the data plane for the optical core nodes. Moreover, with this protocol, it is possible to almost perfectly isolate high priority and low priority traffic throughout the optical network as in the strict priority-based service differentiation in electronically switched networks.
Unknown
Discovering modulators of gene expression
(Oxford University Press, 2010-09-01) Babur, Özgün; Demir, Emek; Gönen, M.; Sander, C.; Doğrusöz, Uğur
Proteins that modulate the activity of transcription factors, often called modulators, play a critical role in creating tissue- and context-specific gene expression responses to the signals cells receive. GEM (Gene Expression Modulation) is a probabilistic framework that predicts modulators, their affected targets and mode of action by combining gene expression profiles, protein-protein interactions and transcription factor-target relationships. Using GEM, we correctly predicted a significant number of androgen receptor modulators and observed that most modulators can both act as co-activators and co-repressors for different target genes. © The Author(s) 2010. Published by Oxford University Press.
Unknown
Diverse consequences of algorithmic probability
(Springer, Berlin, Heidelberg, 2013) Özkural, Eray
We reminisce and discuss applications of algorithmic probability to a wide range of problems in artificial intelligence, philosophy and technological society. We propose that Solomonoff has effectively axiomatized the field of artificial intelligence, therefore establishing it as a rigorous scientific discipline. We also relate to our own work in incremental machine learning and philosophy of complexity. © 2013 Springer-Verlag Berlin Heidelberg.
Unknown
Error rate analysis of cognitive radio transmissions with imperfect channel sensing
(Institute of Electrical and Electronics Engineers Inc., 2014) Ozcan, G.; Gursoy, M. C.; Gezici, Sinan
This paper studies the symbol error rate performance of cognitive radio transmissions in the presence of imperfect sensing decisions. Two different transmission schemes, namely sensing-based spectrum sharing (SSS) and opportunistic spectrum access (OSA), are considered. In both schemes, secondary users first perform channel sensing, albeit with possible errors. In SSS, depending on the sensing decisions, they adapt the transmission power level and coexist with primary users in the channel. On the other hand, in OSA, secondary users are allowed to transmit only when the primary user activity is not detected. Initially, for both transmission schemes, general formulations for the optimal decision rule and error probabilities are provided for arbitrary modulation schemes under the assumptions that the receiver is equipped with the sensing decision and perfect knowledge of the channel fading, and the primary user's received faded signals at the secondary receiver has a Gaussian mixture distribution. Subsequently, the general approach is specialized to rectangular quadrature amplitude modulation (QAM). More specifically, the optimal decision rule is characterized for rectangular QAM, and closed-form expressions for the average symbol error probability attained with the optimal detector are derived under both transmit power and interference constraints. The effects of imperfect channel sensing decisions, interference from the primary user and its Gaussian mixture model, and the transmit power and interference constraints on the error rate performance of cognitive transmissions are analyzed.
Unknown
Estimating the chance of success in IVF treatment using a ranking algorithm
(Springer, 2015) Güvenir, H. A.; Misirli, G.; Dilbaz, S.; Ozdegirmenci, O.; Demir, B.; Dilbaz, B.
In medicine, estimating the chance of success for treatment is important in deciding whether to begin the treatment or not. This paper focuses on the domain of in vitro fertilization (IVF), where estimating the outcome of a treatment is very crucial in the decision to proceed with treatment for both the clinicians and the infertile couples. IVF treatment is a stressful and costly process. It is very stressful for couples who want to have a baby. If an initial evaluation indicates a low pregnancy rate, decision of the couple may change not to start the IVF treatment. The aim of this study is twofold, firstly, to develop a technique that can be used to estimate the chance of success for a couple who wants to have a baby and secondly, to determine the attributes and their particular values affecting the outcome in IVF treatment. We propose a new technique, called success estimation using a ranking algorithm (SERA), for estimating the success of a treatment using a ranking-based algorithm. The particular ranking algorithm used here is RIMARC. The performance of the new algorithm is compared with two well-known algorithms that assign class probabilities to query instances. The algorithms used in the comparison are Naïve Bayes Classifier and Random Forest. The comparison is done in terms of area under the ROC curve, accuracy and execution time, using tenfold stratified cross-validation. The results indicate that the proposed SERA algorithm has a potential to be used successfully to estimate the probability of success in medical treatment.
Unknown
Evaluating probabilistic forecasts of stock prices in a developing stock market
(Elsevier, 1994) Önkal D.; Muradoğlu, G.
Recent literature on the accuracy of forecasting in financial markets reveals contradictory results. These discrepancies can be attributed to the differences in forecasting environments as well as the differences in forecaster expertise that are employed by the researchers. Since the use of point and interval predictions by themselves do not aid in explaining the various aspects of forecaster performance, probabilistic forecasting provides a better alternative that can be used to gain insight into forecasting accuracy in such settings. This study aims to test the effects of forecaster expertise and forecasting environment on forecasting accuracy. Accordingly, various aspects of forecasting performance are studied in a developing stock-market framework.
Unknown
Exact calculation of blocking probabilities for bufferless optical burst switched links with partial wavelength conversion
(IEEE, 2004-10) Akar, Nail; Karasan, Ezhan
In this paper, we study the blocking probabilities in a wavelength division multiplexing-based asynchronous bufferless optical burst switch equipped with a bank of tuneable wavelength converters that is shared per output link. The size of this bank is generally chosen to be less than the number of wavelengths on the link because of the relatively high cost of wavelength converters using current technologies; this case is referred to as partial wavelength conversion in the literature. We present a probabilistic framework for exactly calculating the blocking probabilities. Burst durations are assumed to be exponentially distributed. Burst arrivals are first assumed to be Poisson and later generalized to the more general phase-type distribution. Unlike existing literature based on approximations and/or simulations, we formulate the problem as one of finding the steadystate solution of a continuous-time Markov chain with a block tridiagonal infinitesimal generator. We propose a numerically efficient and stable solution technique based on block tridiagonal LU factorizations. We show that blocking probabilities can exactly and efficiently be found even for very large systems and rare blocking probabilities. Based on the results of this solution technique, we also show how this analysis can be used for provisioning wavelength channels and converters. © 2004 IEEE.
Unknown
Feedback-labelling synergies in judgmental stock price forecasting
(Elsevier, 2004) Goodwin, P.; Önkal-Atay, D.; Thomson, M. E.; Pollock, A. C.; Macaulay, A.
Research has suggested that outcome feedback is less effective than other forms of feedback in promoting learning by users of decision support systems. However, if circumstances can be identified where the effectiveness of outcome feedback can be improved, this offers considerable advantages, given its lower computational demands, ease of understanding and immediacy. An experiment in stock price forecasting was used to compare the effectiveness of outcome and performance feedback: (i) when different forms of probability forecast were required, and (ii) with and without the presence of contextual information provided as labels. For interval forecasts, the effectiveness of outcome feedback came close to that of performance feedback, as long as labels were provided. For directional probability forecasts, outcome feedback was not effective, even if labels were supplied. Implications are discussed and future research directions are suggested.
Unknown
Functional mobility, depressive symptoms, level of independence, and quality of life of the elderly living at home and in the nursing home
(Elsevier Inc., 2009) Karakaya, M. G.; Bilgin, S. C.; Ekici, G.; Köse, N.; Otman, A. S.
Objectives: To compare functional mobility, depressive symptoms, level of independence, and quality of life of the elderly living at home and in the nursing home. Design: A prospectively designed, comparative study. Setting: A nursing home and a university hospital department. Participants: In this study, 33 elderly living in a nursing home and 25 elderly living at home, who fulfilled the inclusion criteria and volunteered to participate, were included. Measurements: Sociodemographic characteristics were recorded. Functional mobility (Timed Up & Go Test), depressive symptoms (Geriatric Depression Scale), level of independence (Kahoku Aging Longitudinal Study Scale), and quality of life (Visual Analogue Scale) scores were compared between the groups. Results: Functional mobility and independence level of the nursing home residents were higher than the home-dwelling elderly (95% CI: -4.88, -0.29 and 0.41, 6.30, respectively), but they had more depressive symptoms (95% CI: 0.30, 5.45), and their level of QoL was lower (95% CI: -15.55, -2.93). Conclusion: These findings are thought to be important and of benefit for health care professionals and caregivers as indicating the areas that need to be supported for the elderly living at home (functional mobility and independence) and in the nursing home (depressive symptoms and quality of life). © 2009 American Medical Directors Association.
Unknown
Gibbs random field model based 3-D motion estimation from video sequences
(IEEE, 1994) Alatan, A. A.; Levent, O.
In contrast to previous global 3D motion concept, a Gibbs random field based method, which models local interactions between motion parameters defined at each point on the object, is proposed. An energy function which gives the joint probability distribution of motion vectors, is constructed. The energy function is minimized in order to find the most likely motion vector set. Some convergence problems, due to ill-posedness of the problem, are overcome by using the concept of hierarchical rigidity. In hierarchical rigidity, the objects are assumed to be almost rigid in the coarsest level and this rigidness is weakened at each level until the finest level is reached. The propagation of motion information between levels, is encouraged. At the finest level, each point have a motion vector associated with it and the interaction between these vectors are described by the energy function. The minimization of the energy function is achieved by using hierarchical rigidity, without trapping into a local minimum. The results are promising.