ppxscal/embedding_network huggingface dataset:
SQL TVF Controlling Forms - Express Structured Parallel Data Intensive Computing
Authors: Qiming Chen, Meichun Hsu
Venue: Proceedings of the 19th international conference on Database and Expert Systems Applications (2008)

A key issue in supporting the synthesis of data intensive computation and data management is to liberate users from low-level parallel programming, by specifying applications functionally independent of the underlying server infrastructure, and further, by providing high-level primitives to express the control flow of applying functions to data partitions. Currently only few such primitives, e.g. Map-Reduce and Cross-Apply, are available, and their expressive power is limited to "flat parallel computing". To deal with "structured parallel computing" where a function is applied to multiple objects with execution order dependencies, a general framework for creating and combining such primitives is required.We propose the SQL-FCF framework as the database centric solution to the above problem. We embed into SQL queries the Function Controlling Forms (FCFs) to specify the flow control of applying Table Valued Functions (TVFs) to multiple data partitions. We further support the extensibility of this framework by allowing new FCFs to be defined from existing ones with SQL phrases. Based on this approach, we provided a SQL based high-level interface for "structured parallel computing" in architecting a hydrologic scientific computation platform. Envisioning that the simple parallel computing primitives will evolve and form a general framework, our effort is a step towards that goal.
Inferring Min and Max Invariants Using Max-Plus Polyhedra
Authors: Xavier Allamigeon, Stéphane Gaubert, Éric Goubault
Venue: Proceedings of the 15th international symposium on Static Analysis (2008)

We introduce a new numerical abstract domain able to infer min and max invariants over the program variables, based on max-plus polyhedra. Our abstraction is more precise than octagons, and allows to express non-convex properties without any disjunctive representations. We have defined sound abstract operators, evaluated their complexity, and implemented them in a static analyzer. It is able to automatically compute precise properties on numerical and memory manipulating programs such as algorithms on strings and arrays.
Optimized Reasoning in Description Logics Using Hypertableaux
Authors: Boris Motik, Rob Shearer, Ian Horrocks
Venue: Proceedings of the 21st international conference on Automated Deduction: Automated Deduction (2007)

We present a novel reasoning calculus for Description Logics (DLs)--knowledge representation formalisms with applications in areas such as the Semantic Web. In order to reduce the nondeterminism due to general inclusion axioms, we base our calculus on hypertableau and hyperresolution calculi, which we extend with a blocking condition to ensure termination. To prevent the calculus from generating large models, we introduce "anywhere" pairwise blocking. Our preliminary implementation shows significant performance improvements on several well-known ontologies. To the best of our knowledge, our reasoner is currently the only one that can classify the original version of the GALEN terminology.
A multi-spectral imaging system for geo-spatial applications
Authors: Carl Steidley, Ray Bachnak, R. Stephen Dannelly, Rahul Kulkarni, Chad Mayfield
Venue: Journal of Computational Methods in Sciences and Engineering (2005)

The integration of remote sensing and geographic information systems (GIS) in environmental applications has become increasingly common in recent years. Remotely sensed images are an important data source for environmental GIS applications and conversely GIS capabilities are being used to improve image analysis procedures. When image processing and GIS facilities are combined in an integrated system, vector data can be used to assist in image classification and raster image statistics within vectors can be used as criteria for vector query and analysis. Advances in imaging technology and sensors have made airborne remote sensing systems viable for many GIS applications that require reasonably good resolution at low cost. Digital cameras are making their mark on the market by providing high resolution at very high rates. This paper describes an aircraft-mounted imaging system (AMIS) that has been designed, prototyped and has gone through initial tests at Texas A&M University-Corpus Christi (A&M-CC) with the support of a grant from NASA.
Quality-of-Service Multicast Overlay Spanning Tree Algorithms for Wireless Ad Hoc Networks
Authors: Georgios Rodolakis, Cédric Adjih, Anis Laouiti, Saadi Boudjit
Venue: Proceedings of the 3rd Asian conference on Internet Engineering: Sustainable Internet (2007)

In this article, we explore modified versions of Multicast Overlay Spanning Tree algorithms (MOST) to support quality of service for wireless ad hoc networks. These algorithms ($\mathcal{Q}$-MOST) take into account the interferences due to radio transmissions and the residual capacity of the nodes in the network. Different algorithms are compared to the basic MOST algorithm. We show by simulations the ability and superiority of these algorithms to find spanning trees that connect all multicast group members with respect to the bandwidth requirements.
Pseudo-Randomness of Discrete-Log Sequences from Elliptic Curves
Authors: Zhixiong Chen, Ning Zhang, Guozhen Xiao
Venue: Information Security and Cryptology: Third SKLOIS Conference, Inscrypt 2007, Xining, China, August 31 - September 5, 2007, Revised Selected Papers (2007)

We investigate an upper bound on the discrepancy and a lower bound on the linear complexity of a class of sequences, derived from elliptic curves by using discrete logarithm in this paper. The results indicate that these sequences may have `nice' pseudo-random properties. The important tool in the proof is certain character sums estimate along elliptic curves. In addition, we apply linear recurrence relation over elliptic curves to output binary sequences with very interesting pseudo-random behavior.
A New Band Selection Strategy for Target Detection in Hyperspectral Images
Authors: Marco Diani, Nicola Acito, Mario Greco, Giovanni Corsini
Venue: Proceedings of the 12th international conference on Knowledge-Based Intelligent Information and Engineering Systems, Part III (2008)

This manuscript presents a novel methodology for band selection (BS) for hyperspectral sensors (HSs) tailored to target detection applications. The new selection strategy chooses a subset of bands that maximizes an objective function suitable for target detection. In particular, it extracts the subset of bands that optimizes the probability of detecting a target (P D ) in a given background, for a fixed probability of false alarm (P FA ). An experimental example of the methodology effectiveness is given. In the example the well-known Adaptive Matched Filter (AMF) detector and synthetic data derived from an AVIRIS hyperspectral image are considered. The results obtained show that the the new strategy outperforms two existing BS algorithms.
Neural Coding in the Dorsal Visual Stream
Authors: Eris Chinellato, Angel P. Pobil
Venue: Proceedings of the 10th international conference on Simulation of Adaptive Behavior: From Animals to Animats (2008)

The information flow along the dorsal visual stream of the primate brain is being thoroughly studied in neuroscience, and this research is being used in artificial intelligence applications. The knowledge regarding one of its most critical stages though, the posterior intraparietal area CIP, remains relatively undeveloped. This paper offers new computational descriptions of the tasks performed by CIP as a fundamental relay station between the visual cortex and the visuomotor areas downstream. Analytical expressions of the transfer functions realized by surface and axes orientation selective neurons (SOS and AOS) of CIP are derived and discussed.
Checking Well-Formedness of Pure-Method Specifications
Authors: Arsenii Rudich, Ádám Darvas, Peter Müller
Venue: Proceedings of the 15th international symposium on Formal Methods (2008)

Contract languages such as JML and Spec# specify invariants and pre- and postconditions using side-effect free expressions of the programming language, in particular, pure methods. For such contracts to be meaningful, they must be well-formed: First, they must respect the partiality of operations, for instance, the preconditions of pure methods used in the contract. Second, they must enable a consistent encoding of pure methods in a program logic, which requires that their specifications are satisfiable and that recursive specifications are well-founded.This paper presents a technique to check well-formedness of contracts. We give proof obligations that are sufficient to guarantee the existence of a model for the specification of pure methods. We improve over earlier work by providing a systematic solution including a soundness result and by supporting more forms of recursive specifications. Our technique has been implemented in the Spec# programming system.
Towards Agile Engineering of High-Integrity Systems
Authors: Richard F. Paige, Ramon Charalambous, Xiaocheng Ge, Phillip J. Brooke
Venue: Proceedings of the 27th international conference on Computer Safety, Reliability, and Security (2008)

We describe the results of a pilot study on the application of an agile process to building a high-integrity software system. The challenges in applying an agile process in this domain are outlined, and potential solutions for dealing with issues of communication, scalability, and system complexity are proposed. We report on the safety process, argumentation generated to support the process, and the technology and tools used to strengthen the agile process in terms of support for verification and validation.
Hopcroft's Algorithm and Cyclic Automata
Authors: Giusi Castiglione, Antonio Restivo, Marinella Sciortino
Venue: Language and Automata Theory and Applications: Second International Conference, LATA 2008, Tarragona, Spain, March 13-19, 2008. Revised Papers (2008)

Minimization of deterministic finite automata is a largely studied problem of the Theory of Automata and Formal Languages. It consists in finding the unique (up to isomorphism) minimal deterministic automaton recognizing a set of words. The first approaches to this topic can be traced back to the 1950's with the works of Huffman and Moore (cf. [12,15]). Over the years several methods to solve this problem have been proposed but the most efficient algorithm in the worst case was given by Hopcroft in [11]. Such an algorithm computes in O(n log n) the minimal automaton equivalent to a given automaton with n states. The Hopcroft's algorithm has been widely studied, described and implemented by many authors (cf. [13,4,16,2]). In particular, in [4] the worst case of the algorithm is considered. The authors of [4] introduce an infinite family of automata associated to circular words. The circular words taken into account are the de Bruijn words, and, by using the associated automata, it is shown that the complexity of the algorithm is tight. More precisely, the Hopcroft's algorithm has some degrees of freedom (see Section 3) in the sense that there can be several executions of the algorithm on a given deterministic automaton. The running time of such executions can be different. With regard to the family of automata proposed in [4] it is shown that there exist some "unlucky" sequences of choices that slow down the computation to achieve the bound ¿(nlogn). However, there are also executions that run in linear time for the same automata. The authors of [4] leave the open problem whether there are automata on which all the executions of Hopcroft's algorithm do not run in linear time. In [16] the author proves that the exact worst case (i.e. in terms of the exact number of operations) of the algorithm for unary languages is reached only for the family of automata given in [4] when a queue is used in the implementation. He remarks that a stack implementation is more convenient for such automata. At the same time in [16] the author conjectures that there is a strategy for processing the stack used in the implementation such that the minimization of all unary languages will be realized in linear time by the Hopcroft's algorithm.
A probabilistic framework for entire WSN localization using a mobile robot
Authors: F. Caballero, L. Merino, P. Gil, I. Maza, A. Ollero
Venue: Robotics and Autonomous Systems (2008)

This paper presents a new method for the localization of a Wireless Sensor Network (WSN) by means of collaboration with a robot within a Network Robot System (NRS). The method employs the signal strength as input, and has two steps: an initial estimation of the position of the nodes is obtained centrally by one robot and is based on particle filtering. It does not require any prior information about the position of the nodes. In the second stage, the nodes refine their position estimates employing a decentralized information filter. The paper shows how the method is able to recover the 3D position of the nodes, and is very suitable for WSN outdoor applications. The paper includes several implementation aspects and experimental results.
Real-space computational methods for linear and nonlinear polarizabilities
Authors: Jun-Ichi Iwata, Kazuhiro Yabana, George F. Bertsch
Venue: Journal of Computational Methods in Sciences and Engineering (2004)

We present a real-space method for computing the linear and nonlinear polarizabilities in the time-dependent density-functional theory. In our method, the three-dimensional Cartesian coordinate is discretized on a uniform grid and the wave functions are represented on the grid points. The dynamic polarizabilities may be calculated perturbatively by expanding the dipole moment in a power series of the external field strength or directly by integrating the real-time equations of motion under the time-varying external field. We describe the equations and computational techniques for the both methods. Besides calculating second-order and third-order hyperpolarizabilities, the method can be applied to photon-absorption cross sections, and we show examples of this application as well. We also present here for the first time calculations of the nonlinear polarizabilities using the real-time method.
A Non-cooperative Power Control Algorithm for Wireless Ad Hoc and Sensor Networks
Authors: Qiang Sun, Xianwen Zeng, Niansheng Chen, Zongwu Ke, Raihan Ur Rasool
Venue: Proceedings of the 2008 Second International Conference on Genetic and Evolutionary Computing (2008)

In mobile ad hoc & sensor networks, power control is an efficient way to improve the efficiency of energy. However, it will also produce negative influence on many aspects of the networks such as the network connectivity, delay and network capacity. In this paper, proposed related energy control mechanisms for ad hoc & sensor networks are introduced. Considering the QoS requirement such as maximum network capacity, minimum network radius and guaranteed network connectivity, a power control model based on non-cooperative game theory is given. And a distributed non-cooperative game algorithm to power control for ad hoc & sensor networks is presented. The existing and uniqueness of Nash equilibrium for the algorithm is also proved in this paper. Finally simulation experiments are implemented to verify the algorithm. The results show that the algorithm is efficient and has a good integrated performance.
CaliBree: A Self-calibration System for Mobile Sensor Networks
Authors: Emiliano Miluzzo, Nicholas D. Lane, Andrew T. Campbell, Reza Olfati-Saber
Venue: Proceedings of the 4th IEEE international conference on Distributed Computing in Sensor Systems (2008)

We propose CaliBree, a self-calibration system for mobile wireless sensor networks. Sensors calibration is a fundamental problem in a sensor network. If sensor devices are not properly calibrated, their sensor readings are likely of little use to the application. Distributed calibration is challenging in a mobile sensor network, where sensor devices are carried by people or vehicles, mainly for three reasons: i) the sensing contact time, i.e., the amount of time nodes are within the sensing range of each other, can be very limited, requiring a quick and efficient calibration technique; ii) for scalability and ease of use, the calibration algorithm should not require manual intervention; iii) the computational burden must be low since some sensor platforms have limited capabilities. In this paper we propose CaliBree, a distributed, scalable, and lightweight calibration protocol that applies a discrete average consensus algorithm technique to calibrate sensor nodes. CaliBree is shown to be effective through experimental evaluation using embedded wireless sensor devices, achieving high calibration accuracy.
Paper-craft from 3D polygonal models using generalized cylinders
Authors: Fady Massarwi, Craig Gotsman, Gershon Elber
Venue: Computer Aided Geometric Design (2008)

We introduce an algorithm for approximating a 2-manifold 3D mesh by a set of developable surfaces. Each developable surface is a generalized cylinder represented as a strip of triangles not necessarily taken from the original mesh. Our algorithm is automatic, creates easy-to-assemble pieces, and provides L"@K global error bounds. The algorithm consists of three stages. In the first stage, the mesh is segmented into meaningful components. The second stage approximates each of the mesh components in 3D by a set of triangle strips with smooth (non-jagged) boundaries that guarantee a maximal user-defined error relative to the original mesh. Finally, these strips are unfolded to the plane, resulting in flat patterns, which may be cut and assembled from paper. The approximation quality is controlled by a user-supplied parameter specifying the allowed Hausdorff distance between the input mesh and its piecewise-developable approximation. The strips generated by our algorithm may be parameterized to conform with the parameterization of the original mesh, if given, to facilitate texture mapping. We demonstrate this by physically assembling paper-craft models from the strips generated by our algorithm when run on several polygonal 3D mesh data sets.
MTT: The Maude Termination Tool (System Description)
Authors: Francisco Durán, Salvador Lucas, José Meseguer
Venue: Proceedings of the 4th international joint conference on Automated Reasoning (2008)

Despite the remarkable development of the theory of termination of rewriting, its application to high-level programming languages is far from being optimal. This is due to the need for features such as conditional equations and rules, types and subtypes, (possibly programmable) strategies for controlling the execution, matching modulo axioms, and so on, that are used in many programs and tend to place such programs outside the scope of current termination tools.The operational meaning of such features is often formalized in a proof-theoretic manner by means of an inference system (see, e.g., [2, 3, 17]) rather than just by a rewriting relation. In particular, Generalized Rewrite Theories (GRT) [3] are a recent generalization of rewrite theories at the heart of the most recent formulation of Maude [4].
Characterizations of maximum fractional (g,f)-factors of graphs
Authors: Guizhen Liu, Lanju Zhang
Venue: Discrete Applied Mathematics (2008)

In this paper a characterization of maximum fractional (g,f)-factors of a graph is presented. The properties of the maximum fractional (g,f)-factors and fractional (g,f)-factors with the minimum of edges are also given, generalizing the results given in [William Y.C. Chen, Maximum (g,f)-factors of a general graph, Discrete Math. 91 (1991) 1-7] and [Edward R. Scheinerman, Daniel H. Ullman, Fractional Graph Theory, John Wiley and Sonc, Inc., New York, 1997]. Furthermore, some new results on fractional factors are obtained which may be used in the design of networks. A polynomial time algorithm can be obtained for actually finding such maximum fractional (g,f)-factors in a graph from the proof.
Exploring gene interactions in dna microarray data
Authors: Xintao Wu
Venue:  (2007)

DNA Microarray technology provides a powerful basis for analysis of gene expression levels. Analyzing microarray data can reveal gene activities associated with biological processes and group genes into interaction networks. The discovery and exploration of these networks will help us identify gene functions, design new methods of disease diagnosis and provide target for drug development. Data mining methods such as clustering and association rule mining have been widely applied to Microarray data to find groups of genes that show similar expression patterns. However, these approaches usually can only find associations or co-expressions, but fail to unveil pairwise or multi-way gene interactions within one cluster. Bayesian networks, which are based on directed acyclic graph and can provide model of causal influence, have been used for causal structure learning. However learning Bayesian network structure is an NP-hard problem. Since the number of genes involved in the learning are usually in the size of hundreds or thousands, it can not be used for realtime interactive gene interaction exploration. In this dissertation, we combine the use of graphical model and causal model with other data mining techniques to identify and screen gene interaction networks. We apply Graphical Gaussian Model (GGM) to discover undirected pairwise gene interactions. For causal structure learning, we develop an enhanced constraint based approach which allows fast exploration of directed gene interactions. To solve the dimensionality limitations of these modeling methods, we develop an algorithm based on graphical decomposition. It can divide large interaction networks into smaller components to which our modeling methods can be applied successfully. We also develop an approach to improve the identification of gene interaction networks by incorporating protein function modules. To find meaningful protein modules from usually very sparse protein interaction networks, we first develop two strategies (data integration and using Commute Time) to increase the density of the networks. Then we apply clique finding algorithm to find cliques (and also conserved cliques) from protein interaction networks. The cliques found are further analyzed by using our modeling methods. We design and implement an integrated system with GUI that allows rapid interactive exploration of gene relationships. We also test our methodology on both Yeast and E. coli microarray data and protein interaction data.
Spiral Teaching of Programming to 10---11 Year-Old Pupils After Passed First Training (Based on the Language C++)
Authors: Biserka Boncheva Yovcheva
Venue: Proceedings of the 3rd international conference on Informatics in Secondary Schools - Evolution and Perspectives: Informatics Education - Supporting Computational Thinking (2008)

The article presents a unique approach of teaching programming to 10 --- 11 year old pupils. Based on the idea that teaching pupils of writing algorithms must start right after teaching the first elements of the programming language and develop with time, one and the same problem is considered many times but each time with adding of new knowledge. According to the described methodology a textbook is issued on the basis of which an experimental four-year training of pupils is organized. This article gives the curriculum of the second year of training based on the approach described.