ppxscal/embedding_network huggingface dataset:
Termination Problems in Chemical Kinetics
Authors: Gianluigi Zavattaro, Luca Cardelli
Venue: Proceedings of the 19th international conference on Concurrency Theory (2008)

We consider nondeterministic and probabilistic termination problems in a process algebra that is equivalent to basic chemistry. We show that the existence of a terminating computation is decidable, but that termination with any probability strictly greater than zero is undecidable. Moreover, we show that the fairness intrinsic in stochastic computations implies that termination of all computation paths is undecidable, while it is decidable in a nondeterministic framework.
BTL++: From Performance Assessment to Optimal Libraries
Authors: Laurent Plagne, Frank Hülsemann
Venue: Proceedings of the 8th international conference on Computational Science, Part III (2008)

This paper presents the Benchmark Template Library in C++, in short BTL++, which is a flexible framework to assess the run time of user defined computational kernels. When the same kernel is implemented in several different ways, the collected performance data can be used to automatically construct an interface library that dispatches a function call to the fastest variant available.The benchmark examples in this article are mostly functions from the dense linear algebra BLAS API. However, BTL++ can be applied to any kernel that can be called by a function from a C++ main program. Within the same framework, we are able to compare different implementations of the operations to be benchmarked, from libraries such as ATLAS, over procedural solutions in Fortran and C to more recent C++ libraries with a higher level of abstraction. Results of single threaded and multi-threaded computations are included.
Minimal non-deletable sets and minimal non-codeletable sets in binary images
Authors: T. Yung Kong
Venue: Theoretical Computer Science (2008)

The concepts of strongly 8-deletable and strongly 4-deletable sets of 1s in binary images on the 2D Cartesian grid were introduced by Ronse in the mid-1980s to formalize the connectivity preservation conditions that parallel thinning algorithms are required to satisfy. In this paper we call these sets deletable and codeletable, respectively. To establish that a proposed parallel thinning algorithm for binary images on the 2D Cartesian grid preserves 8-(4-)connected foreground components and 4-(8-)connected background components, it is enough to prove that the set of 1s which are changed to 0s at each pass of the algorithm is always a deletable (codeletable) set. Ronse established results that are very useful in this context for proving that a finite set D of 1s is deletable or codeletable. In particular, he showed that D and its proper subsets are all codeletable in a binary image if each singleton and each pair of 8-adjacent pixels in D is codeletable. He further showed that D and its proper subsets are all deletable in a binary image if (1) each singleton and each pair of 4-adjacent pixels in D is deletable, and (2) no set of 2, 3, or 4 pairwise 8-adjacent pixels that is an 8-connected foreground component of the image is entirely contained in D. In the 1990s and early 2000s analogous results were obtained by Hall, Ma, Gau, and the author for binary images on the 2D hexagonal grid, the 3D Cartesian and face-centered cubic grids, and the 4D Cartesian grid. This paper extends the above-mentioned work to binary images on almost any polytopal complex whose union is n-dimensional Euclidean space, for n@?4. Our main results generalize and unify the corresponding results of the earlier work.
The Maximum Independent Set Problem in Planar Graphs
Authors: Vladimir E. Alekseev, Vadim Lozin, Dmitriy Malyshev, Martin Milanič
Venue: Proceedings of the 33rd international symposium on Mathematical Foundations of Computer Science (2008)

We study the computational complexity of finding a maximum independent set of vertices in a planar graph. In general, this problem is known to be NP-hard. However, under certain restrictions it becomes polynomial-time solvable. We identify a graph parameter to which the complexity of the problem is sensible and produce a number of both negative (intractable) and positive (solvable in polynomial time) results, generalizing several known facts.
Finding the Near Workload Type between TPC-C and TPC-W Environments
Authors: Jeong Seok Oh, Kyung Suhk Choi, Jeong Rock Kwon, Sang Ho Lee
Venue: Proceedings of the 2008 International Conference on Convergence and Hybrid Information Technology (2008)

Database system can be performed more than a database application and shown peculiar workload characteristics as a database application. However, as a database system can be performed a lot of database applications, detecting workload characteristics might be more difficult. This paper proposes the method of finding near workload characteristics by mixed workloads. The workload find method is evaluated by the modified k-NN algorithm that is an extension of the existing the fuzzy k-NN algorithm. The modified k-NN algorithm measures how close workloads in TPC-C or TPC-W are to the mixed workloads between TPC-C and TPC-W. Furthermore, the result of our method is better than others for finding near workloads because its results are lower than others in the oscillation depending on the k parameter and the error rate. This study is able to contribute to finding similar information for providing autonomic database analysis and intelligent service in ubiquitous environments
Extracting Average Shapes from Occluded Non-rigid Motion
Authors: Alessio Bue
Venue: Proceedings of the 3rd Iberian conference on Pattern Recognition and Image Analysis, Part II (2007)

This paper presents a method to efficiently estimate average 3-D shapes from non-rigid motion in the case of missing data. Such a shape can be further used to accomplish full reconstruction of deformable objects and registration of non-rigid shapes. The approach is based firstly on a power method which linearly provides an initial estimate of the 3-D structure and motion components of the object shape. Secondly, non-linear optimisation is used to refine the initial linear estimation. Tests on both real and synthetic sequences show the procedure effectiveness in dealing with different degrees of occlusions in the measurements.
Improving the Classification Ability of DC* Algorithm
Authors: Corrado Mencar, Arianna Consiglio, Giovanna Castellano, Anna Maria Fanelli
Venue: Proceedings of the 7th international workshop on Fuzzy Logic and Applications: Applications of Fuzzy Sets Theory (2007)

DC* (Double Clustering by A*) is an algorithm for interpretable fuzzy information granulation of data. It is mainly based on two clustering steps. The first step applies the LVQ1 algorithm to find a suitable representation of data relationships. The second clustering step is based on the A* search strategy and is aimed at finding an optimal number of fuzzy granules that can be labeled with linguistic terms. As a result, DC* is able to linguistically describe hidden relationships among available data. In this paper we propose an extension of the DC* algorithm, called DC$^{*} _{1.1}$, which improves the generalization ability of the original DC* by modifying the A* search procedure. This variation, inspired by Support Vector Machines, results empirically effective as reported in experimental results.
Following the Perturbed Leader to Gamble at Multi-armed Bandits
Authors: Jussi Kujala, Tapio Elomaa
Venue: Proceedings of the 18th international conference on Algorithmic Learning Theory (2007)

Following the perturbed leader (fpl) is a powerful technique for solving online decision problems. Kalai and Vempala [1] rediscovered this algorithm recently. A traditional model for online decision problems is the multi-armed bandit. In it a gambler has to choose at each round one of the k levers to pull with the intention to minimize the cumulated cost. There are four versions of the nonstochastic optimization setting out of which the most demanding one is a game played against an adaptive adversary in the bandit setting. An adaptive adversary may alter its game strategy of assigning costs to decisions depending on the decisions chosen by the gambler in the past. In the bandit setting the gambler only gets to know the cost of the choice he made, rather than the costs of all available alternatives. In this work we show that the very straightforward and easy to implement algorithm Adaptive Bandit fpl can attain a regret of $O(\sqrt{T \ln T})$ against an adaptive adversary. This regret holds with respect to the best lever in hindsight and matches the previous best regret bounds of $O(\sqrt{T \ln T})$.
Energy, Economy, Population, and Climate's Influences on Environment in Anhui Province, China
Authors: Kai-Ya Wu, Lin Liu, Ju-Liang Jin
Venue: Proceedings of the 7th international conference on Computational Science, Part III: ICCS 2007 (2007)

Energy consumption, economic development level, population growth, and climate change and so on all have close relations with environment pollution. Based on the statistical data of Anhui province in China from 1987 to 2004, this paper analyzes the direct and indirect influences of energy consumption, total output value of industry, population, temperature and precipitation on environment pollution. The results show production pattern of industry and consumption of electric power are main reasons of environmental pollution.
Cooperative Building of Multiple Points-of-View Topic Maps with Hypertopic
Authors: L'Hédi Zaher, Jean-Pierre Cahier, Claude Guittard
Venue: Scaling Topic Maps: Third International Conference on Topic Maps Research and Applications, TMRA 2007 Leipzig, Germany, October 11-12, 2007 Revised Selected Papers (2008)

This paper presents socio-semantic web applications based on the Hypertopic knowledge representation model. The Hypertopic [4] model is used to collaboratively construct topic maps with multiple user points-of-view within related communities. Three model building methods are presented herein: centralized, conflict-based, and hybrid. These methods are expressed using the socio-technical `SeeMe' notation and method [7,8]. This paper will also illustrate how various co-building approaches can be used to construct Hypertopic maps in real communities.
Righting Software
Authors: James R. Larus, Thomas Ball, Manuvir Das, Robert DeLine, Manuel Fahndrich, Jon Pincus, Sriram K. Rajamani, Ramanathan Venkatapathy
Venue: IEEE Software (2004)

Correctness tools can improve software development by supplementing human shortcomings, detecting programming errors such as null-pointer dereferences, API usage errors, and failing to close file descriptors. Microsoft Research has developed two generations of correctness tools: The first are heuristic tools widely used inside the organization to find programming errors; the second are tools based on sound program analysis and driven by rules describing interface behavior. Together, these tools offer a systematic approach for finding and fixing errors early in the development process.
Evolution of a Spherical Universe in a Short Range Collapse/Generation Interval
Authors: Ivana Bochicchio, Ettore Laserra
Venue: Proceedings of the 7th international conference on Computational Science, Part II (2007)

We study the final/initial behavior of a dust Universe with spatial spherical symmetry. This study is done in proximity of the collapse/generation times by an expansion in fractional Puiseux series. Even if the evolution of the universe has different behaviours depending on the initial data (in particular on the initial spatial curvature), we show that, in proximity of generation or collapse time, the Universe expands or collapses with the same behavior.
Recalibration of rotational locomotion in immersive virtual environments
Authors: Scott A. Kuhl, Sarah H. Creem-Regehr, William B. Thompson
Venue: ACM Transactions on Applied Perception (TAP) (2008)

This work uses an immersive virtual environment (IVE) to examine how people maintain a calibration between biomechanical and visual information for rotational self-motion. First, we show that no rotational recalibration occurs when visual and biomechanical rates of rotation are matched. Next, we demonstrate that mismatched physical and visual rotation rates cause rotational recalibration. Although previous work has shown that rotational locomotion can be recalibrated in real environments, this work extends the finding to virtual environments. We further show that people do not completely recalibrate left and right rotations independently when different visual--biomechanical discrepancies are used for left and right rotations during a recalibration phase. Finally, since the majority of participants did not notice mismatched physical and visual rotation rates, we discuss the implications of using such mismatches to enable IVE users to explore a virtual space larger than the physical space they are in.
Improving the Performance of Graph Coloring Algorithms through Backtracking
Authors: Sanjukta Bhowmick, Paul D. Hovland
Venue: Proceedings of the 8th international conference on Computational Science, Part I (2008)

Graph coloring is used to identify independent objects in a set and has applications in a wide variety of scientific and engineering problems. Optimal coloring of graphs is an NP-complete problem. Therefore there exist many heuristics that attempt to obtain a near-optimal number of colors. In this paper we introduce a backtracking correction algorithm which dynamically rearranges the colors assigned by a top level heuristic to a more favorable permutation thereby improving the performance of the coloring algorithm. Our results obtained by applying the backtracking heuristic on graphs from molecular dynamics and DNA-electrophoresis show that the backtracking algorithm succeeds in lowering the number of colors by as much as 23%. Variations of backtracking algorithm can be as much as 66% faster than standard correction algorithms, like Culberson's Iterated Greedy method, while producing a comparable number of colors.
Variable predictive models-A new multivariate classification approach for pattern recognition applications
Authors: Rao Raghuraj, Samavedham Lakshminarayanan
Venue: Pattern Recognition (2009)

Many pattern recognition algorithms applied in literature exhibit data specific performances and are also computationally intense and complex. The data classification problem poses further challenges when different classes cannot be distinguished just based on decision boundaries or conditional discriminating rules. As an alternate to existing methods, inter-relations among the feature vectors can be exploited for distinguishing samples into specific classes. Based on this idea, variable predictive model based class discrimination (VPMCD) method is proposed as a new and alternative classification approach. Analysis is carried out using seven well studied data sets and the performance of VPMCD is benchmarked against well established linear and non-linear classifiers like LDA, kNN, Bayesian networks, CART, ANN and SVM. It is demonstrated that VPMCD is an efficient supervised learning algorithm showing consistent and good performance over these data sets. The new VPMCD method has the potential to be effectively and successfully extended to many pattern recognition applications of recent interest.
First exit time probability for multidimensional diffusions: A PDE-based approach
Authors: P. Patie, C. Winter
Venue: Journal of Computational and Applied Mathematics (2008)

First exit time distributions for multidimensional processes are key quantities in many areas of risk management and option pricing. The aim of this paper is to provide a flexible, fast and accurate algorithm for computing the probability of the first exit time from a bounded domain for multidimensional diffusions. First, we show that the probability distribution of this stopping time is the unique (weak) solution of a parabolic initial and boundary value problem. Then, we describe the algorithm which is based on a combination of the sparse tensor product finite element spaces and an hp-discontinuous Galerkin method. We illustrate our approach with several examples. We also compare the numerical results to classical Monte Carlo methods.
Spine Segmentation Using Articulated Shape Models
Authors: Tobias Klinder, Robin Wolz, Cristian Lorenz, Astrid Franz, Jörn Ostermann
Venue: Proceedings of the 11th international conference on Medical Image Computing and Computer-Assisted Intervention - Part I (2008)

Including prior shape in the form of anatomical models is a well-known approach for improving segmentation results in medical images. Currently, most approaches are focused on the modeling and segmentation of individual objects. In case of object constellations, a simultaneous segmentation of the ensemble that uses not only prior knowledge of individual shapes but also additional information about spatial relations between the objects is often beneficial. In this paper, we present a two-scale framework for the modeling and segmentation of the spine as an example for object constellations. The global spine shape is expressed as a consecution of local vertebra coordinate systems while individual vertebrae are modeled as triangulated surface meshes. Adaptation is performed by attracting the model to image features but restricting the attraction to a former learned shape. With the developed approach, we obtained a segmentation accuracy of 1.0 mm in average for ten thoracic CT images improving former results.
Area Reliability Trade-Off in Improved Reed Muller Coding
Authors: Costas Argyrides, Stephania Loizidou, Dhiraj K. Pradhan
Venue: Proceedings of the 8th international workshop on Embedded Computer Systems: Architectures, Modeling, and Simulation (2008)

Nanotechnology based fabrication, which relies on self-assembly of nanotubes or nanowires has been predicted to be an alternative to silicon technology since lithography based IC is approaching its limit in terms of feature size. However, such processes are expected to be less reliable, to have high defect density and to be handled with effective defect tolerant techniques. Thus, reliability is a major challenge in the future of IC design. To this end, different coding techniques have been proposed to improve reliability of future technologies. In this paper we analyze the trade-off between the area and the reliability added in each chip employing the Reed Muller coding as the coding technique. We estimate the reliability and area increase of different orders of the Reed Muller decoding and observed that while the area increases, the reliability decreases. Our approach is to define a framework and help designers in order to decide on the configuration of the Reed Muller to be used. Finally, we provide a guideline to optimize the architecture making an optimal trade off between the area and the reliability.
The Fortran-P Translator: Towards Automatic Translation of Fortran 77 Programs for Massively Parallel Processors
Authors: Matthew O'Keefe, Terence Parr, B. Kevin Edgar, Steve Anderson, Paul Woodward, Hank Dietz
Venue: Scientific Programming (1995)

Massively parallel processors (MPPs) hold the promise of extremely high performance that, if realized, could be used to study problems of unprecedented size and complexity. One of the primary stumbling blocks to this promise has been the lack of tools to translate application codes to MPP form. In this article we show how applications codes written in a subset of Fortran 77, called Fortran-P, can be translated to achieve good performance on several massively parallel machines. This subset can express codes that are self-similar, where the algorithm applied to the global data domain is also applied to each subdomain. We have found many codes that match the Fortran-P programming style and have converted them using our tools. We believe a self-similar coding style will accomplish what a vectorizable style has accomplished for vector machines by allowing the construction of robust, user-friendly, automatic translation systems that increase programmer productivity and generate fast, efficient code for MPPs.
Optimal Design of Passive Power Filters Based on Multi-objective Cultural Algorithms
Authors: Yi-Nan Guo, Jian Cheng, Yong Lin, Xingdong Jiang
Venue: Proceedings of the 4th international conference on Intelligent Computing: Advanced Intelligent Computing Theories and Applications - with Aspects of Theoretical and Methodological Issues (2008)

Design of passive power filters shall meet the demand of harmonics suppression effect and economic target. However, existing optimization methods for this problem only take technology target into account or do not utilize knowledge enough, which limits the speed of convergence and the performance of solutions. To solve the problem, two objectives including minimum total harmonics distortion of current and minimum cost for equipments are constructed. In order to achieve the optimal solution effectively, a novel multi-objective optimization method, which adopts dual evolution structure in cultural algorithms, is adopted. Implicit knowledge describing the dominant space are extracted and utilized to induce the direction of evolution. Taken three-phase full wave controlled rectifier as harmonic source, simulation results show that filter designed by the proposed algorithm have better harmonics suppression effect and lower investment for equipments than filter designed by existing methods.
A new approximation method based on linear programming for fuzzy
Authors: Murat Alper Basaran, Cagdas Hakan Aladag, Cem Kadilar
Venue: Proceedings of the WSEAS International Conference on Applied Computing Conference (2008)

Instead of doing arithmetic operations using fuzzy membership functions for fuzzy numbers, parameterized representation of fuzzy numbers have been used in arithmetic operations in the literature. The most applied parameterized fuzzy numbers used in many of the research papers are symmetric and asymmetric triangular and trapezoidal fuzzy numbers. Although addition and subtraction of parameterized fuzzy numbers give closed form results, multiplication and division of these fuzzy numbers generate approximated results. Therefore, some approximation methods have been proposed for fuzzy multiplication and division. In this study, we propose a new approximation method based on linear programming for fuzzy division. In order to show the applicability of the proposed method, some examples are solved using this method and the results are compared with those generated by other methods in the literature. The proposed method has produced better results than those generated by the others.
An Intelligent Tutoring System for Entity Relationship Modelling
Authors: Pramuditha Suraweera, Antonija Mitrovic
Venue: International Journal of Artificial Intelligence in Education (2004)

The paper presents KERMIT, a Knowledge-based Entity Relationship Modelling Intelligent Tutor. KERMIT is a problem-solving environment for the university-level students, in which they can practise conceptual database design using the Entity-Relationship data model. KERMIT uses Constraint-Based Modelling (CBM) to model the domain knowledge and generate student models. We have used CBM previously in tutors that teach SQL and English punctuation rules. The research presented in this paper is significant because we show that CBM can be used to support students learning design tasks, which are very different from domains we dealt with in earlier tutors. The paper describes the system's architecture and functionality. The system observes students' actions and adapts to their knowledge and learning abilities. KERMIT has been evaluated in the context of genuine teaching activities. We present the results of two evaluation studies with students taking database courses, which show that KERMIT is an effective system. The students have enjoyed the system's adaptability and found it a valuable asset to their learning.