ppxscal/embedding_network huggingface dataset:
Field Flow Sensitive Pointer and Escape Analysis for Java Using Heap Array SSA
Authors: Prakash Prabhu, Priti Shankar
Venue: Proceedings of the 15th international symposium on Static Analysis (2008)

Context sensitive pointer analyses based on Whaley and Lam's bddbddb system have been shown to scale to large Java programs. We provide a technique to incorporate flow sensitivity for Java fields into one such analysis and obtain an escape analysis based on it. First, we express an intraprocedural field flow sensitive analysis, using Fink et al.'s Heap Array SSA form in Datalog. We then extend this analysis interprocedurally by introducing two new ¿ functions for Heap Array SSA Form and adding deduction rules corresponding to them. Adding a few more rules gives us an escape analysis. We describe two types of field flow sensitivity: partial (PFFS) and full (FFFS), the former without strong updates to fields and the latter with strong updates. We compare these analyses with two different (field flow insensitive) versions of Whaley-Lam analysis: one of which is flow sensitive for locals (FS) and the other, flow insensitive for locals (FIS). We have implemented this analysis on the bddbddb system while using the SOOT open source framework as a front end. We have run our analysis on a set of 15 Java programs. Our experimental results show that the time taken by our field flow sensitive analyses is comparable to that of the field flow insensitive versions while doing much better in some cases. Our PFFS analysis achieves average reductions of about 23% and 30% in the size of the points-to sets at load and store statements respectively and discovers 71% more "caller-captured" objects than FIS.
Shape analysis with inductive recursion synthesis
Authors: David I. August
Venue:  (2008)

For program optimization and verification purposes, shape analysis can be used to statically determine structural properties of the runtime heap. One promising formalism for describing heap is separation logic, with recursively defined predicates that allow for concise yet precise summarization of linked data structures. A major challenge in this approach is the derivation of the predicates directly from the program being analyzed. As a result, current uses of separation logic rely heavily on predefined predicates, limiting the class of programs analyzable to those that manipulate only predefined data types. This thesis addresses this problem by proposing a general algorithm based on inductive program synthesis that automatically infers recursive predicates in a canonical form. This technique yields a separation logic based shape analysis that can be effective on a much wider range of programs. A key strength of separation logic is that it facilitates, via explicit expression of structural separation, local reasoning about heap where the effects of altering one part of a data structure are analyzed in isolation from the rest. The interaction between local reasoning and the global invariants given by recursive predicates is a difficult area, especially in the presence of complex internal sharing in the data structures. Existing approaches, using logic rules specifically designed for the list predicate to unfold and fold linked lists, again require a priori knowledge about the data structures and do not easily generalize to more complex data structures. We introduce a notion of &ldquo;truncation points&rdquo; in a recursive predicate, which gives rise to generic algorithms for unfolding and folding arbitrary data structures. We present a fully implemented interprocedural analysis algorithm that handles recursive procedures. A combination of pointer analysis and program slicing is used to deal with the scalability issue typically faced by shape analyses. Finally, we present a data dependence test for recursive data structures that takes advantage of the results of our shape analysis.
Texture Classification in Lung CT Using Local Binary Patterns
Authors: Lauge Sørensen, Saher B. Shaker, Marleen Bruijne
Venue: Proceedings of the 11th international conference on Medical Image Computing and Computer-Assisted Intervention - Part I (2008)

In this paper we propose to use local binary patterns (LBP) as features in a classification framework for classifying different texture patterns in lung computed tomography. Image intensity is included by means of the joint LBP and intensity histogram, and classification is performed using the k nearest neighbor classifier with histogram similarity as distance measure.The proposed method is evaluated on a set of 168 regions of interest comprising normal tissue and different emphysema patterns, and compared to a filter bank based on Gaussian derivatives. The joint LBP and intensity histogram, achieving a classification accuracy of 95.2%, shows superior performance to using the common approach of taking moments of the filter response histograms as features, and slightly better performance than using the full filter response histograms instead. Classification results are better than some of those previously reported in the literature.
Analytic Reconstruction of Transparent and Opaque Surfaces from Texture Images
Authors: Mohamad Ivan Fanany, Itsuo Kumazawa
Venue: Proceedings of the 3rd Iberian conference on Pattern Recognition and Image Analysis, Part II (2007)

This paper addresses the problem of reconstructing non- overlapping transparent and opaque surfaces from multiple view images. The reconstruction is attained through progressive refinement of an initial 3D shape by minimizing the error between the images of the object and the initial 3D shape. The challenge is to simultaneously reconstruct both the transparent and opaque surfaces given only a limited number of images. Any refinement methods can theoretically be applied if analytic relation between pixel value in the training images and vertices position of the initial 3D shape is known. This paper investigates such analytic relations for reconstructing opaque and transparent surfaces. The analytic relation for opaque surface follows diffuse reflection model, whereas for transparent surface follows ray tracing model. However, both relations can be converged for reconstruction both surfaces into texture mapping model. To improve the reconstruction results several strategies including regularization, hierarchical learning, and simulated annealing are investigated.
Effective energy functions for protein structure prediction based on predicted structural features
Authors: Pierre Baldi
Venue:  (2008)

Protein tertiary structure prediction is a fundamental problem in computational biology. An accurate model of a protein's three-dimensional structure provides a wealth of information about its possible functions. An accurate template-based model can be built for a target protein if its sequence is highly similar to that of a protein with a known structure, however, as the evolutionary signal between target and template degrade, the reliability of the models produced also degrades. The difficulty of identifying the best template increases as the evolutionary signal weakens. A variety of methods have been developed for ranking potential templates. For targets with no detectable similarity to a template protein, models can be built by free-modeling methods. In the absence of a single clear high confidence template, a set of protein structure prediction methods will produce diverse ensemble of models. Inevitably, some models will be more accurate than others. This dissertation presents an energy function comprising physical, statistical, and predicted structural terms, that consistently selects one of the best models from ensembles of models predicted by automated methods. Novel terms include predicted secondary structure, predicted solvent accessibility, predicted contact map, beta-strand pairing, and side-chain hydrogen bonding. The energy function is calculated on each model independently, making it more general than methods that rely on similarity between models when scoring them. The energy function can be applied to any size model set and can be incorporated into existing protein structure prediction pipelines in a variety of important areas, including analogous fold recognition, refinement of sequence-structure alignments, and free-modeling. The method has been made available to the prediction community for model scoring and selection as the web-server SELECTpro. The energy function is also the basis of the stand-alone free-modeling prediction method ABIpro, and is one component in the comprehensive tertiary structure prediction method 3Dpro. In addition to the globular protein energy function, this dissertation presents a related energy function specifically designed for transmembrane beta-barrel (TMB) proteins. The specialized energy function is applied in the TMBpro tertiary structure prediction protocol. SELECTpro, ABIpro, 3Dpro, and TMBpro are all freely available to the prediction community through: www.igb.uci.edu/servers/psss.html.
The Evolution of Negotiation and Impasse in Two-Party Multi-issue Bargaining
Authors: Fernando Lopes, A. Q. Novais, Helder Coelho
Venue: Proceedings of the 11th Ibero-American conference on AI: Advances in Artificial Intelligence (2008)

Automated negotiation systems are becoming increasingly important and pervasive. Most previous research on automated negotiation has focused on understanding and formalizing "successful" negotiations, i.e., negotiations that do not become contentious to the point of impasse. This paper shifts the emphasis to negotiations that are "difficult" to resolve and can hit an impasse. It analyses a situation where two agents bargain over the division of the surplus of several distinct issues to demonstrate how a procedure to avoid impasses can be utilized in a specific negotiation setting. The procedure is based on the addition of new issues to the agenda during the course of negotiation and the exploration of the differences in the valuation of these issues to capitalize on Pareto optimal agreements. This paper also lays the foundation for performing an experiment to investigate how the evolution of negotiation contributes to the avoidance of impasses, paying particular attention to the expansion of the number of issues to be deliberated and its impact on the frequency of impasses.
Introducing join-computing
Authors: Giacomo Cabri
Venue: Proceedings of the 7th WSEAS International Conference on Software Engineering, Parallel and Distributed Systems (2008)

Engineering the interaction between components is a key issue in the development of complex software systems. While technologies for developing components are spread, more difficult is the composition of such components in heterogeneous, unpredictable and dynamic scenarios. In this paper we introduce the Join-Computing as a general model in which components are able to "join" in order to exploit each other features. We discuss also the technological issues related to the Join-Computing, which can be exploited to concretize the model.
A Static Multiprocessor Scheduling Algorithm for Arbitrary Directed Task Graphs in Uncertain Environments
Authors: Jun Yang, Xiaochuan Ma, Chaohuan Hou, Zheng Yao
Venue: Proceedings of the 8th international conference on Algorithms and Architectures for Parallel Processing (2008)

The objective of a static scheduling algorithm is to minimize the overall execution time of the program, represented by a directed task graph, by assigning the nodes to the processors. However, sometimes it is very difficult to estimate the execution time of several parts of a program and the communication delays under different circumstances. In this paper, an uncertain intelligent scheduling algorithm based on an expected value model and a genetic algorithm is presented to solve the multiprocessor scheduling problem in which the computation time and the communication time are given by stochastic variables. In simulation examples, it shows that the algorithm performs better than other algorithms in uncertain environments.
Friction Model by Using Fuzzy Differential Equations
Authors: Barnabás Bede, Imre J. Rudas, János Fodor
Venue: Proceedings of the 12th international Fuzzy Systems Association world congress on Foundations of Fuzzy Logic and Soft Computing (2007)

In the present paper we propose a novel approach for modeling friction, by using fuzzy differential equations under the strongly generalized differentiability concept. The key point is a continuous fuzzyfication of the signum function. The lack of the uniqueness for the solutions of a fuzzy differential equation allows us to choose the solution which better reflects the behavior of the modeled real-world system, so it allows us to incorporate expert's knowledge in our model. Numerical solutions of the fuzzy differential equations modeling dry friction are proposed. In order to show how the expert's knowledge can be incorporated in the system, we study the dry friction equation with different additional assumptions.
Note: A description of the outer automorphism of S6, and the invariants of six points in projective space
Authors: Ben Howard, John Millson, Andrew Snowden, Ravi Vakil
Venue: Journal of Combinatorial Theory Series A (2008)

We use a simple description of the outer automorphism of S"6 to cleanly describe the invariant theory of six points in P^1, P^2, and P^3.
A note on the inapproximability of correlation clustering
Authors: Jinsong Tan
Venue: Information Processing Letters (2008)

We consider inapproximability of the correlation clustering problem defined as follows: Given a graph G=(V,E) where each edge is labeled either ''+'' (similar) or ''-'' (dissimilar), correlation clustering seeks to partition the vertices into clusters so that the number of pairs correctly (resp., incorrectly) classified with respect to the labels is maximized (resp., minimized). The two complementary problems are called MaxAgree and MinDisagree, respectively, and have been studied on complete graphs, where every edge is labeled, and general graphs, where some edge might not have been labeled. Natural edge-weighted versions of both problems have been studied as well. Let S-MaxAgree denote the weighted problem where all weights are taken from set S, we show that S-MaxAgree with weights bounded by O(|V|^1^/^2^-^@d) essentially belongs to the same hardness class in the following sense: if there is a polynomial time algorithm that approximates S-MaxAgree within a factor of @l=O(log|V|) with high probability, then for any choice of S^', S^'-MaxAgree can be approximated in polynomial time within a factor of (@l+@e), where @e>0 can be arbitrarily small, with high probability. A similar statement also holds for S-MinDisagree. This result implies it is hard (assuming NP
Effective Application of Paro: Seal Type Robots for Disabled People in According to Ideas of Occupational Therapists
Authors: Kaoru Inoue, Kazuyoshi Wada, Yuko Ito
Venue: Proceedings of the 11th international conference on Computers Helping People with Special Needs (2008)

Paro is an autonomous seal type robot for those who cannot take care of real animals and those who live in places where pet-animals are forbidden. This paper describes effective application for disabled people of Paro in according to idea of Occupational Therapists. OTs thought that Paro is an effective tool on occupational therapy but OTs should consider clients' characters, situations. We think OTs should have skills to introduce activities to clients proficiently, to explain Paro's attractive points skillfully, to keep clients' interest for activities.
Implementation of SEA Algorithm on the Windows Platforms
Authors: Hui-Ting Hsieh, Chung-Huang Yang, TaeNam Ahn
Venue: Proceedings of the 2008 International Conference on Convergence and Hybrid Information Technology (2008)

In FIPS 186-2, NIST (National Institute of Standards and Technology) recommends five elliptic curve parameters over prime field for building up secure elliptic curve cryptosystem. If the user can randomly produce elliptic curve parameters over prime field, the cryptosystem will be more secure. One of the important steps is to count the number of rational points on an elliptic curve over prime field and find the curve of prime order. Because SEA algorithm is an effective algorithm for counting points on elliptic curve over prime field, we can build up secure elliptic curve cryptosystem by using it to search for curve of prime order. The study uses MIRACL as embedded function library, C++ Builder to design the graphic user’s interface, and the computer with Pentium 2.80G CPU, 2G memory, and Windows server 2003 platforms for experiment. On average, it takes individually 610, 1386, 2093, 24514, and 100203 seconds to search out elliptic curve of prime order for cryptosystem; it takes 32, 69, 108, 751, and 3413 seconds individually to count the number of points on elliptic curve on the basis of 192, 224, 256, 384, and 521 bits of underlying field.
UPMS - UML Profile and Metamodel for Services - an Emerging Standard
Authors: Arne J. Berre
Venue: Proceedings of the 2008 12th International IEEE Enterprise Distributed Object Computing Conference (2008)

UPMS is an emerging standard from OMG (Object Management Group) that includes both a UML profile (SOA-Pro) and a metamodel for modeling of service-oriented architectures. The approach supports both top down (synergistic) and bottom up (opportunistic) modeling (middle-out), and utilizes UML collaboration diagrams and UML 2.0 component diagrams with a new concept of service interfaces. It is also linked into a business modeling framework with business process modeling (BPMN) and goal modeling (BMM). UPMS provides a foundation for modeling of SHA (Service-oriented Heterogeneous Architectures) including support for P2P, Grid, Agents and semantic services., which is being addressed in the European SHAPE project.
Implementation of a teaching training method in E-learning information system
Authors: Huay Chang
Venue: Proceedings of the 8th WSEAS International Conference on Multimedia systems and signal processing (2008)

In previous research paper, the author uses the corresponding information system technologies to present a newly teaching training method. Based on the E-Learning web-site and the network teaching, we use skilled system to establish the interactive Sport Teaching E-Learning structure. The proposed method provides a newly teaching model and an innovative learning point. In this paper, we implement the proposed teaching training method in the Network Sport Teaching E-Learning Platform and discuss the associated facilities.
Epistemic Actions in Science Education
Authors: Kim A. Kastens, Lynn S. Liben, Shruti Agrawal
Venue: Proceedings of the international conference on Spatial Cognition VI: Learning, Reasoning, and Talking about Space (2008)

Epistemic actions are actions in the physical environment taken with the intent of gathering information or facilitating cognition. As students and geologists explain how they integrated observations from artificial rock outcrops to select the best model of a three-dimensional geological structure, they occasionally take the following actions, which we interpret as epistemic: remove rejected models from the field of view, juxtapose two candidate models, juxtapose and align a candidate model with their sketch map, rotate a candidate model into alignment with the full scale geological structure, and reorder their field notes from a sentential order into a spatial configuration. Our study differs from prior work on epistemic actions in that our participants manipulate spatial representations (models, sketches, maps), rather than non-representational objects. When epistemic actions are applied to representations, the actions can exploit the dual nature of representations by manipulating the physical aspect to enhance the representational aspect.
Iterated Tabu Search for the Unconstrained Binary Quadratic Optimization Problem
Authors: Gintaras Palubeckis
Venue: Informatica (2006)

Given a set of objects with profits (any, even negative, numbers) assigned not only to separate objects but also to pairs of them, the unconstrained binary quadratic optimization problem consists in finding a subset of objects for which the overall profit is maximized. In this paper, an iterated tabu search algorithm for solving this problem is proposed. Computational results for problem instances of size up to 7000 variables (objects) are reported and comparisons with other up-to-date heuristic methods are provided.
A Multi-agent Architecture Based Cooperation and Intelligent Decision Making Method for Multirobot Systems
Authors: Tao Yang, Jia Ma, Zeng-Guang Hou, Gang Peng, Min Tan
Venue: Neural Information Processing: 14th International Conference, ICONIP 2007, Kitakyushu, Japan, November 13-16, 2007, Revised Selected Papers, Part II (2008)

The design of a hybrid multi-agent architecture is proposed for multirobot systems. Analysis of the architecture shows that it is suitable for multirobot systems dealing with changing environments. Meanwhile, it is capable of controlling a group of robots to accomplish multiple tasks simultaneously. Two associated issues about the architecture are cooperation between robots and intelligent decision making. Ability vector, cost function and reward function are used as criteria to describe and solve the role assignment problem in multirobot cooperation. A solution of information fusion based on RBF neural networks is applied to solve the reality problem in decision making of multirobot systems. And an experiment about robot soccer shooting is designed. The experimental results verify that the method can improve the whole decision system in accuracy.
Small scale high dimensional model representation
Authors: Evrim Korkmaz, Metin Demiralp
Venue: Proceedings of the 1st WSEAS International Conference on Multivariate Analysis and its Application in Science and Engineering (2008)

HDMR, High Dimensional Model Representation is one of the recently developed tool in the approximation of multivariate functions. It is based on multivariate integration over orthogonal geometries under product type weight functions and uses a divide-and-conquer algorithm such that the target function is separated into components in ascending multivariance. In almost all applications HDMR is desired to be truncated at constant, univariate, or at most, bivariate components as approximations. The approximating quality of these components increases as the target functions additive nature dominates. Here, our purpose is to investigate the role of the geometric scale of HDMR be anticipating to get efficiency in the small scale geometries. The ultimate goal of this approach is to develop a new HDMR like finite elements.
Byzantine Fault-Tolerant Web Services for n-Tier and Service Oriented Architectures
Authors: Sajeeva L. Pallemulle, Haraldur D. Thorvaldsson, Kenneth J. Goldman
Venue: Proceedings of the 2008 The 28th International Conference on Distributed Computing Systems (2008)

Mission-critical services must be replicated to guarantee correctness and high availability in spite of arbitrary (Byzantine) faults. Traditional Byzantine fault tolerance protocols suffer from several major limitations. Some protocols do not support interoperability between replicated services. Other protocols provide poor fault isolation between services leading to cascading failures across organizational and application boundaries. Moreover, traditional protocols are unsuitable for applications with tiered architectures, long-running threads of computation, or asynchronous interaction between services. We present Perpetual, a protocol that supports Byzantine fault-tolerant execution of replicated services while enforcing strict fault isolation. Perpetual enables interaction between replicated services that may invoke and process remote requests asynchronously in long-running threads of computation. We present a modular implementation, an Axis2 Web Services extension, and experimental results that demonstrate only a moderate overhead due to replication.