ppxscal/embedding_network huggingface dataset:
Spatially adaptive image restoration using fuzzy punctual kriging
Authors: Anwar M. Mirza, Asmatullah Chaudhry, Badre Munir
Venue: Journal of Computer Science and Technology (2007)

We present a general formulation based on punctual kriging and fuzzy concepts for image restoration in spatial domain. Gray-level images degraded with Gaussian white noise have been considered. Based on the pixel local neighborhood, fuzzy logic has been employed intelligently to avoid unnecessary estimation of a pixel. The intensity estimation of the selected pixels is then carried out by employing punctual kriging in conjunction with the method of Lagrange multipliers and estimates of local semi-variances. Application of such a hybrid technique performing both selection and intensity estimation of a pixel demonstrates substantial improvement in the image quality as compared to the adaptive Wiener filter and existing fuzzykriging approaches. It has been found that these filters achieve noise reduction without loss of structural detail information, as indicated by their higher structure similarity indices, peak signal to noise ratios and the new variogram based quality measures.
Comparing Genetic Algorithms and Newton-Like Methods for the Solution of the History Matching Problem
Authors: Elisa Portes Santos, Carolina Ribeiro Xavier, Paulo Goldfeld, Flavio Dickstein, Rodrigo Weber Dos Santos
Venue: Proceedings of the 9th International Conference on Computational Science: Part I (2009)

In this work we presents a comparison of different optimization methods for the automatic history matching problem of reservoir simulation. The history matching process is an inverse problem that searches a set of parameters that minimizes the difference between the model performance and the historical performance of the field. This model validation process is essential and gives credibility to the predictions of the reservoir model. Derivative-based methods are compared to a free-derivative algorithm. In particular, we compare the Quasi-Newton method, non-linear Conjugate-Gradient, Steepest-Descent and a Genetic Algorithm implementation. Several tests are performed and the preliminary results are presented and discussed.
Context-based ranking in folksonomies
Authors: Fabian Abel, Matteo Baldoni, Cristina Baroglio, Nicola Henze, Daniel Krause, Viviana Patti
Venue: Proceedings of the 20th ACM conference on Hypertext and hypermedia (2009)

With the advent of Web 2.0 tagging became a popular feature. People tag diverse kinds of content, e.g. products at Amazon, music at Last.fm, images at Flickr, etc. Clicking on a tag enables the users to explore related content. In this paper we investigate how such tag-based queries, initialized by the clicking activity, can be enhanced with automatically produced contextual information so that the search result better fits to the actual aims of the user. We introduce the SocialHITS algorithm and present an experiment where we compare different algorithms for ranking users, tags, and resources in a contextualized way.
Non-Commutative Fuzzy Logics and Substructural Logics
Authors: Mayuka F. Kawaguchi, Osamu Watari, Masaaki Miyakoshi
Venue: Proceeding of the 2005 conference on Advances in Logic Based Intelligent Systems: Selected Papers of LAPTEC 2005 (2005)

This report treats the relation between substructural logics and fuzzy logics, especially focuses on the non-commutativity of conjunctive operators i.e. substructural logics without the exchange rule. As the results, the authors show that fuzzy logics based on the left continuous pseudo-t-norms form the models of FLw. Also, we introduce the definition of pseudo-uninorms and give some methods to construct them, and show that such functions realize the fuzzy logical systems as the models of FLc and FL, which is the weakest substructural logic.
On minimum sensing error with spectrum sensing using counting rule in cognitive radio networks
Authors: Tao Jiang, Daiming Qu
Venue: Proceedings of the 4th Annual International Conference on Wireless Internet (2008)

In cognitive radio networks (CRN), spectrum sensing requires each secondary user to efficiently and effectively detect the presence of primary users. In this paper, we study cooperative spectrum sensing (CSS), which is based on counting rules. Particularly, we first derive the optimal sensing strategy of CSS to minimize the sensing error, and then propose a simple algorithm to calculate the optimal parameter settings for CSS. Numerical results have been conducted and also validated that our proposed approach can achieve satisfying performance.
Digital weight watching: reconstruction of scanned documents
Authors: Tim Gielissen, Maarten Marx
Venue: Proceedings of The Third Workshop on Analytics for Noisy Unstructured Text Data (2009)

Scanned and OCRed data leads to large file sizes if facsimile images are included. This makes storage of, and providing online access to large data sets costly. Manually analyzing such data is cumbersome because of long download and processing times. It may thus be advantageous to reconstruct the scanned documents as documents without scanned images which nevertheless closely resemble the original. We have done this reconstruction for a data set of Dutch parliamentary proceedings with positive results. 1.5% of the original storage space was needed, while the documents resembled the originals to a high degree. We describe the reconstruction process and evaluate the costs, the benefits and the quality.
Modeling and simulation for a fossil power plant
Authors: Kwang-Hun Jeong, Woo-Won Jeon, Young-Hoon Bae, Ki-Hyun Lee
Venue: Proceedings of the 4th WSEAS/IASME international conference on Dynamical systems and control (2008)

This paper deals with the description of the APESS (Advanced Plant Engineering and Simulation System), a simulation software for a fossil power plant, and the results of computer simulation which were performed using the system. The APESS was developed by Doosan several years ago for the purpose of dynamic characteristic analysis for a fossil power plant. In this study, an existing fossil power plant in Korea was modeled by the APESS. The simulation model is divided into two parts. The first part is the process model consists of several systems such as air/flue gas system, fuel system and feed water system etc. The second part is the control model included control logics and philosophies. The verification of the model with design data for steady state was performed. Then we predicted the behavior of the main parameters in load change. The results showed satisfying agreement with the real operation data. Hence, the APESS is reliable to estimate the dynamic behavior of the real fossil power plant and capable to predict the operation processes.
Using test case patterns to estimate software development and quality management cost
Authors: Ayman A. Issa, Faisal A. Abu Rub, Fadi F. Thabata
Venue: Software Quality Control (2009)

A novel process to discover test case patterns is proposed. This has led to the construction of a test case patterns catalogue. The catalogue has been analysed to estimate the potential reusability in different software applications. This has shown that 43% of system functions are generally application domain independent, whereas 57% are application domain dependent. Statistical tests showed that the level of specialisation in software systems could be as low as 20%, which supports the direction taken in this research to reuse test case patterns in software engineering activities, in particular, software cost estimation at the early sages of software development.
Plenary lecture 1: analogies in melodies of early Christian liturgical chant originating from different cultural domains
Authors: Eugene Kindler
Venue: Proceedings of the 10th WSEAS international conference on Acoustics & music: theory & applications (2009)

The Christian liturgical chant of the first millennium was forgotten many centuries ago and (more or less) deciphered in relatively recent epoch - e.g. Latin chant in the second half of the XIX century, Byzantine chant after the First World War, Russian kondakarian chant and Armenian medieval chant after the Second World War. The difficulties came from Different modes of graphical recording of that music and - for the modern feeling - different relations between spoken speech and sung texts caused extreme difficulties in the modern studies. The consequence is that some relations between the geographic and/or linguistic types of that chant are studied only from the literary and liturgical point of view (i.e. the melodic aspects are completely neglected), while from the musical point of view the particular types of that chant were often understood as separate subjects of culture. Since 1962, the author has studied various types of the mentioned music by means of formal grammars and since 1980 has been director of a small singing group Musica Poetica that presented those chants at concerts; surprising analogies among melodies of chants arisen in different linguistic and liturgical domains appeared, testifying on common roots of those musical types (Christian religion and classical Greek-Roman musical culture). The analogies will be presented in the lecture both in graphical way (in transcription in modern notation) and in acoustical way as well, with context to the general properties of the relating musical types (Latin, Greek-Byzantine, Syro-Byzantine, Armenian and Palaeoslavic).
HRScribe Excel Problem Solver, 1st edition
Authors: Alison Morris
Venue:  (2007)

Excel 2003 using human resource data that a human resource professional can relate to for solving problems. Over 30 SHOW ME Movies demonstrate Excel teaching pivot tables, VLOOKUPS, managing employee names, employment dates, filters and more! The ACM Portal is published by the Association for Computing Machinery. Copyright © 2010 ACM, Inc. Terms of Usage Privacy Policy Code of Ethics Contact Us Useful downloads: Adobe Acrobat QuickTime Windows Media Player Real Player
Error-Detection-Based Quantum Fault-Tolerance Threshold
Authors: Ben W. Reichardt
Venue: Algorithmica (2009)

A major hurdle in building a quantum computer is overcoming noise, since quantum superpositions are fragile. Developed over the last couple of years, schemes for achieving fault tolerance based on error detection, rather than error correction, appear to tolerate as much as 3&#x2013;6% noise per gate&#x2014;an order of magnitude higher than previous procedures. However, proof techniques could not show that these promising fault-tolerance schemes tolerated any noise at all; the distribution of errors in the quantum state has correlations that conceivably could grow out of control. With an analysis based on decomposing complicated probability distributions into mixtures of simpler ones, we rigorously prove the existence of constant tolerable noise rates (&#x201c;noise thresholds&#x201d;) for error-detection-based schemes. Numerical calculations indicate that the actual noise threshold this method yields is lower-bounded by 0.1% noise per gate.
Performance Evaluation of Computer Aided Diagnostic Tool (CAD) for Detection of Ultrasonic Based Liver Disease
Authors: N. Sriraam, J. Roopa, M. Saranya, M. Dhanalakshmi
Venue: Journal of Medical Systems (2009)

Recent advances in digital imaging technology have greatly enhanced the interpretation of critical/pathology conditions from the 2-dimensional medical images. This has become realistic due to the existence of the computer aided diagnostic tool. A computer aided diagnostic (CAD) tool generally possesses components like preprocessing, identification/selection of region of interest, extraction of typical features and finally an efficient classification system. This paper enumerates on development of CAD tool for classification of chronic liver disease through the 2-D image acquired from ultrasonic device. Characterization of tissue through qualitative treatment leads to the detection of abnormality which is not viable through qualitative visual inspection by the radiologist. Common liver diseases are the indicators of changes in tissue elasticity. One can show the detection of normal, fatty or malignant condition based on the application of CAD tool thereby, further investigation required by radiologist can be avoided. The proposed work involves an optimal block analysis (64¿×¿64) of the liver image of actual size 256¿×¿256 by incorporating Gabor wavelet transform which does the texture classification through automated mode. Statistical features such as gray level mean as well as variance values are estimated after this preprocessing mode. A non-linear back propagation neural network (BPNN) is applied for classifying the normal (vs) fatty and normal (vs) malignant liver which yields a classification accuracy of 96.8%. Further multi classification is also performed and a classification accuracy of 94% is obtained. It can be concluded that the proposed CAD can be used as an expert system to aid the automated diagnosis of liver diseases.
Marker Less Vision-Based Tracking of Partially Known 3D Scenes for Outdoor Augmented Reality Applications
Authors: Fakhreddine Ababsa, Jean-Yves Didier, Imane Zendjebil, Malik Mallem
Venue: Proceedings of the International Conference on Computer Vision and Graphics: Revised Papers (2008)

This paper presents a new robust and reliable marker less camera tracking system for outdoor augmented reality using only a mobile handheld camera. The proposed method is particularly efficient for partially known 3D scenes where only an incomplete 3D model of the outdoor environment is available. Indeed, the system combines an edge-based tracker with a sparse 3D reconstruction of the real-world environment to continually perform the camera tracking even if the model-based tracker fails. Experiments on real data were carried out and demonstrate the robustness of our approach to occlusions and scene changes.
Do code clones matter?
Authors: Elmar Juergens, Florian Deissenboeck, Benjamin Hummel, Stefan Wagner
Venue: Proceedings of the 2009 IEEE 31st International Conference on Software Engineering (2009)

Code cloning is not only assumed to inflate maintenance costs but also considered defect-prone as inconsistent changes to code duplicates can lead to unexpected behavior. Consequently, the identification of duplicated code, clone detection, has been a very active area of research in recent years. Up to now, however, no substantial investigation of the consequences of code cloning on program correctness has been carried out. To remedy this shortcoming, this paper presents the results of a large-scale case study that was undertaken to find out if inconsistent changes to cloned code can indicate faults. For the analyzed commercial and open source systems we not only found that inconsistent changes to clones are very frequent but also identified a significant number of faults induced by such changes. The clone detection tool used in the case study implements a novel algorithm for the detection of inconsistent clones. It is available as open source to enable other researchers to use it as basis for further investigations.
Parallel Programming with Skeletons
Authors: Joel Falcou
Venue: Computing in Science and Engineering (2009)

Parallel programming is bound to become the main concern of software developers in the coming decades. Various models aim to solve this tension, trading efficiency for abstraction or vice versa, but how about getting both?
Intelligent Client-Side Web Caching Scheme Based on Least Recently Used Algorithm and Neuro-Fuzzy System
Authors: Waleed Ali, Siti Mariyam Shamsuddin
Venue: Proceedings of the 6th International Symposium on Neural Networks: Advances in Neural Networks - Part II (2009)

Web caching is a well-known strategy for improving performance of Web-based system by keeping web objects that are likely to be used in the near future close to the client. Most of the current Web browsers still employ traditional caching policies that are not efficient in web caching. This research proposes a splitting client-side web cache to two caches, short-term cache and long-term cache. Primarily, a web object is stored in short-term cache, and the web objects that are visited more than the pre-specified threshold value will be moved to long-term cache, while other objects are removed by Least Recently Used(LRU) algorithm as short-term cache is full. More significantly, when the long-term cache saturates, the trained neuro-fuzzy system is employed in classifying each object stored in long-term cache into cacheable or uncacheable object. The old uncacheable objects are candidate for removing from the long-term cache. By implementing this mechanism, the cache pollution can be mitigated and the cache space can be utilized effectively. Experimental results have revealed that the proposed approach has better performance compared to the most common caching policies and has improved the performance of client-side caching substantially.
Predicate transformers for extended probability and non-determinism
Authors: Klaus Keimel, Gordon d. Plotkin
Venue: Mathematical Structures in Computer Science (2009)

We investigate laws for predicate transformers for the combination of non-deterministic choice and (extended) probabilistic choice, where predicates are taken to be functions to the extended non-negative reals, or to closed intervals of such reals. These predicate transformers correspond to state transformers, which are functions to conical powerdomains, which are the appropriate powerdomains for the combined forms of non-determinism. As with standard powerdomains for non-deterministic choice, these come in three flavours – lower, upper and (order-)convex – so there are also three kinds of predicate transformers. In order to make the connection, the powerdomains are first characterised in terms of relevant classes of functionals. Much of the development is carried out at an abstract level, a kind of domain-theoretic functional analysis: one considers d-cones, which are dcpos equipped with a module structure over the non-negative extended reals, in place of topological vector spaces. Such a development still needs to be carried out for probabilistic choice per se; it would presumably be necessary to work with a notion of convex space rather than a cone.
On the Price of Heterogeneity in Parallel Systems
Authors: P. Brighten Godfrey, Richard M. Karp
Venue: Theory of Computing Systems (2009)

Suppose we have a parallel or distributed system whose nodes have limited capacities, such as processing speed, bandwidth, memory, or disk space. How does the performance of the system depend on the amount of heterogeneity of its capacity distribution? We propose a general framework to quantify the worst-case effect of increasing heterogeneity in models of parallel systems. Given a cost function g(C,W) representing the system&#x2019;s performance as a function of its nodes&#x2019; capacities&#x00a0;C and workload W (such as the makespan of an optimum schedule of jobs W on machines&#x00a0;C), we say that g has price of heterogeneity &#x03b1; when for any workload, cost cannot increase by more than a factor &#x03b1; if node capacities become arbitrarily more heterogeneous. The price of heterogeneity also upper bounds the &#x201c;value of parallelism&#x201d;: the maximum benefit obtained by increasing parallelism at the expense of decreasing processor speed. We give constant or logarithmic bounds on the price of heterogeneity of several well-known job scheduling and graph degree/diameter problems, indicating that in many cases, increasing heterogeneity can never be much of a disadvantage.
Wiener and Hammerstein uncertain models identification
Authors: S. I. Biagiola, J. L. Figueroa
Venue: Mathematics and Computers in Simulation (2009)

Block-oriented models have proved to be useful as simple nonlinear models for a vast number of applications. They are described as a cascade of linear dynamic and nonlinear static blocks. They have emerged as an appealing proposal due to their simplicity and the property of being valid over a larger operating region than a LTI model. In the description of these models, several approaches can be found in the literature to perform the identification process. In this sense, an important improvement is to achieve robust identification of block-oriented models to cope with the presence of uncertainty. In this article, we focus at two special and widely used types of uncertain block-oriented models: Hammerstein and Wiener models. They are assumed to be represented by a parametric representation. The approach herein followed allows to describe the uncertainty as a set of parameters which is found through the solution of an optimization problem. The identification algorithms are illustrated through a set of simple examples.
Towards the realization of synchronous sequential biological circuits
Authors: Miha Moškon, Monika Ciglič, Nikolaj Zimic, Miha Mraz
Venue: Proceedings of the 10th WSEAS international conference on Mathematics and computers in biology and chemistry (2009)

Synthetic biology is an emerging field that is rapidly evolving and is promising many applications in the near future. Information processing capable systems are certainly one of them, especially because we are currently facing many problems with the existent technology upon which computer systems have based for the last 80 years. Here we present the next step towards the construction of a complex biological information processing capable systems which will in our opinion soon be comparable to computer systems used nowadays. We present the model of a first synchronous sequential circuits constructed with the use of gene expression based logic. With the promising results presented in the paper physical realization of the described circuit within the living cell can be initiated.
A Location Prediction-Based Reactive Routing Protocol to Minimize the Number of Route Discoveries and Hop Count per Path in Mobile Ad Hoc Networks
Authors: Natarajan Meghanathan
Venue: The Computer Journal (2009)

We propose a new mobile ad hoc network routing protocol called ‘location prediction-based routing’ (LPBR) to simultaneously minimize the number of route discoveries and hop count of the paths for a source–destination session. During a regular flooding-based route discovery, LPBR collects the location and mobility information of nodes in the network and stores the collected information at the destination node of the route search process. When the minimum hop route discovered through the flooding-based route discovery fails, the destination node attempts to predict the current location of each node using the location and mobility information collected during the latest flooding-based route discovery. A minimum hop Dijkstra algorithm is run on the locally predicted global topology. If the predicted minimum hop route exists in reality, no expensive flooding-based route discovery is needed and the source continues to send data packets on the discovered route; otherwise, the source initiates another flooding-based route discovery. Simulation results indicate that LPBR incurs a significantly reduced number of flooding-based route discoveries, lower hop count per path, smaller route discovery overhead, lower end-to-end delay per packet and higher packet delivery ratio compared with that of the minimum hop-based, stability-based and position-based routing protocols. The ACM Portal is published by the Association for Computing Machinery. Copyright © 2010 ACM, Inc. Terms of Usage Privacy Policy Code of Ethics Contact Us Useful downloads: Adobe Acrobat QuickTime Windows Media Player Real Player