ppxscal/embedding_network huggingface dataset:
Encoding First Order Proofs in SAT
Authors: Todd Deshane, Wenjin Hu, Patty Jablonski, Hai Lin, Christopher Lynch, Ralph Eric Mcgregor
Venue: Proceedings of the 21st international conference on Automated Deduction: Automated Deduction (2007)

We present a method for proving rigid first order theorems by encoding them as propositional satisfiability problems. We encode the existence of a first order connection tableau and the satisfiability of unification constraints. Then the first order theorem is rigidly unsatisfiable if and only if the encoding is propositionally satisfiable. We have implemented this method in our theorem prover CHEWTPTP, and present experimental results. This method can be useful for general first order problems, by continually adding more instances of each clause.
The Efficient Digital Implementation of Subtractive Music Synthesis
Authors: S. Bass, T. Goeddel
Venue: IEEE Micro (1981)

The coming generation of discrete-time organs can use subtractive synthesis to achieve considerable advantages over their present-day continuous-time counterparts.
An Experiment in Robot Discovery with ILP
Authors: Gregor Leban, Jure Žabkar, Ivan Bratko
Venue: Proceedings of the 18th international conference on Inductive Logic Programming (2008)

We describe an experiment in the application of ILP to autonomous discovery in a robotic domain. An autonomous robot is performing experiments in its world, collecting data and formulating predictive theories about this world. In particular, we are interested in the robot's "gaining insights" through predicate invention. In the first experimental scenario in a pushing blocks domain, the robot discovers the notion of objects' movability. The second scenario is about discovering the notion of obstacle. We describe experiments with a simulated robot, as well as an experiment with a real robot when robot's observations contain noise.
Minimum Vertex Ranking Spanning Tree Problem on Some Classes of Graphs
Authors: Ruei-Yuan Chang, Guanling Lee, Sheng-Lung Peng
Venue: Proceedings of the 4th international conference on Intelligent Computing: Advanced Intelligent Computing Theories and Applications - with Aspects of Artificial Intelligence (2008)

A vertex ranking of a graph G is a labeling of the vertices of G with positive integers such that every path between two vertices with the same label i contains a vertex with label j > i. A vertex ranking is minimum if the largest label used in it is the smallest among all possible vertex rankings of G. The minimum vertex ranking spanning tree problem on G is to find a spanning tree T of G such that the minimum vertex ranking of T is minimum among all possible spanning trees of G. In this paper, we show that the minimum vertex ranking spanning tree problem on interval graphs, split graphs, and cographs can be solved in linear time. It improves a previous result that runs in O(n 3) time on interval graphs where n is the number of vertices in the input graph.
An analysis of security threats to mobile IPv6
Authors: Michael Durr, Ray Hunt
Venue: International Journal of Internet Protocol Technology (2008)

In parallel with the design of IPv6, several protocol extensions for mobility support of IPv6 nodes have been proposed and these continue to evolve. However, a variety of security threats arise and these have to be taken in to account in the design of such protocol extensions. This paper provides a short introduction to Mobile IPv6 and presents a comprehensive overview of security issues that have to be taken into account when introducing mobility support. Furthermore, security solutions included in the protocol design are addressed and a detailed explanation on how these solutions can assist in preventing security attacks is provided.
Sequential Blind Signal Extraction with the Linear Predictor
Authors: Yunxia Li, Zhang Yi
Venue: Proceedings of the 4th international symposium on Neural Networks: Advances in Neural Networks, Part III (2007)

The sequential blind signal extraction method with a linear predictor is proposed. The Kalman filter is introduced to overcome the problem of the choice of the linear predictor coefficients. Using a deflation technique, the proposed algorithm is able to sequentially recover the source signals one-by-one. Simulation results verify the validity and performance of the proposed algorithm.
OpenMP Implementation of Parallel Linear Solver for Reservoir Simulation
Authors: Changjun Hu, Jilin Zhang, Jue Wang, Jianjiang Li
Venue: Proceedings of the 3rd international workshop on OpenMP: A Practical Programming Model for the Multi-Core Era (2007)

In this paper, we discuss an OpenMP implementation of an evolutionary LSOR method, the MBLSOR method, for solution of system of linear equations related to reservoir simulation on SMPs. MBLSOR method not only can improve the data locality by spatial computational domain decomposition technique, but it also can parallel the sub blocks with no data dependence. We compare the performance of different parallel LSOR methods in terms of efficiency and data locality. Numerical results on SMPs indicate that MBLSOR algorithm is more efficient.
An automatic abstraction technique for verifying featured, parameterised systems
Authors: M. Calder, A. Miller
Venue: Theoretical Computer Science (2008)

A general technique combining model checking and abstraction is presented that allows property based analysis of systems consisting of an arbitrary number of featured components. We show how parameterised systems can be specified in a guarded command form with constraints placed on variables which occur in guards. We prove that results that hold for a small number of components can be shown to scale up. We then show how featured systems can be specified in a similar way, by relaxing constraints on guards. The main result is a generalisation theorem for featured systems which we apply to two well known examples.
Suppressing Maximum Burst Size Throughout the Path with Non-work Conserving Schedulers
Authors: Hongkyu Jeong, Kyoung Y. Bae, Jinoo Joung
Venue: Proceedings of the 3rd international conference on Algorithmic Aspects in Information and Management (2007)

Because of the scalability problem, the aggregation of flows and the queueing/scheduling based on those flow-aggregates is unavoidable in Quality of Service (QoS) architectures for large scale networks. We investigate the effect of flow aggregation on the end-to-end delay bounds. It has observed that with traditional work-conserving schedulers, the maximum burst size of each flow increases linearly as it traverses the network. The increased maximum burst size does not affect the delay bound of a flow in cases where the schedulers are flow-based. In cases where deaggregation and aggregation take places in the middle of the network, however, the increased maximum burst size affects severely in terms of delay bound. This is in fact the case for the most of real network deployments since at the edge of a subnetwork the flows have to be deaggregated and then handed over to another subnetwork. We suggest a simple alternative to the existing work-conserving scheduler, the Smoothing-DRR (S-DRR) server, which is based on the Deficit Round Robin (DRR) server. S-DRR has a non-work conserving characteristic. S-DRR is proved to suppress the maximum burst size of the aggregated flow to a constant throughout the path, so that the delay bound is only linearly proportional to the hop counts.
Brain-controlled finite state machine for wheelchair navigation
Authors: Amir Teymourian, Thorsten Lueth, Axel Graeser, Torsten Felzer, Rainer Nordmann
Venue: Proceedings of the 10th international ACM SIGACCESS conference on Computers and accessibility (2008)

This proposal is about a brain-controlled electrically powered wheelchair. The system comprises a brain-computer interface based on steady-state visual evoked potentials and a processing unit relying on a finite state machine (FSM). Results of first simulation experiments comparing two different FSMs are presented.
Reconciling usability and interactive system architecture using patterns
Authors: Ahmed Seffah, Taleb Mohamed, Halima Habieb-Mammar, Alain Abran
Venue: Journal of Systems and Software (2008)

Traditional interactive system architectures such as MVC [Goldberg, A., 1984. Smaltalk-80: The Interactive Programming Environment, Addison-Wesley Publ.] and PAC [Coutaz, J., 1987. PAC, an implementation model for dialog design. In: Interact'87, Sttutgart, September 1987, pp. 431-436; Coutaz, J., 1990. Architecture models for interactive software: faillures and trends. In: Cockton, G. (Ed.), Engineering for Human-Computer Interaction, Elsevier Science Publ., pp. 137-153.] decompose the system into subsystems that are relatively independent, thereby allowing the design work to be partitioned between the user interfaces and underlying functionalities. Such architectures extend the independence assumption to usability, approaching the design of the user interface as a subsystem that can designed and tested independently from the underlying functionality. This Cartesian dichotomy can be fallacious, as functionalities buried in the application's logic can sometimes affect the usability of the system. Our investigations model the relationships between internal software attributes and externally visible usability factors. We propose a pattern-based approach for dealing with these relationships. We conclude by discussing how these patterns can lead to a methodological framework for improving interactive system architectures, and how these patterns can support the integration of usability in the software design process.
A Model for Representing Topological Relations Between Simple Concave Regions
Authors: Jihong Ouyang, Qian Fu, Dayou Liu
Venue: Proceedings of the 7th international conference on Computational Science, Part I: ICCS 2007 (2007)

At present, qualitative spatial reasoning has become the hot issues in many research fields. The most popular models of spatial topological relations are Region Connection Calculus (RCC) and 9-inter-section model. However, there are few contributions on topological relations of concave regions in which the representative model is Cohn's RCC23. There are some limitations of RCC23 especially in practical applications due to its less expressiveness. In order to construct a more expressive model of topological relations between concave regions, this paper completed the following works: 9-intersection matrix is extended to 16-intersection matrix, and RCC23 is refined to RCC62 based on 16-intersection matrix. More relations can be distinguished in RCC62, which is more expressive than RCC23. In order to further reason about relations in RCC62, the Conceptual Neighborhood Graph (CNG) and the Closest Topological Relation Graph (CTRG) of RCC62 are given.
Logical Engineering with Instance-Based Methods
Authors: Peter Baumgartner
Venue: Proceedings of the 21st international conference on Automated Deduction: Automated Deduction (2007)

The term "instance based methods" (IMs) refers to a certain family of methods for first-order logic theorem proving. IMs share the principle of carrying out proof search by maintaining a set of instances of input clauses and analyzing it for satisfiability until completion. IMs are conceptually essentially different to well established methods like resolution or free-variable analytic tableaux. (See [Pla94] for a comparison of various calculi and strategies, including an instance based method.) Also, IMs exhibit a search space and termination behaviour (in the satisfiable case) different from those methods, which makes them attractive from a practical point of view as a complementary method.
Arguing about Reputation: The LRep Language
Authors: Isaac Pinyol, Jordi Sabater-Mir
Venue: Engineering Societies in the Agents World VIII: 8th International Workshop, ESAW 2007, Athens, Greece, October 22-24, 2007, Revised Selected Papers (2008)

Since electronic and open environments became a reality, computational models of trust and reputation have attracted increasing interest in the field of multi-agent systems (MAS). In virtual societies of human actors very well-known mechanisms are already used to control non normative agents, for instance, the eBay scoring system. In virtual societies of artificial and autonomous agents, the same necessity arises, and several computational trust and reputation models have appeared in literature to cover this necessity. Typically, these models provide evaluations of agents' performance in a specific context, taking into account direct experiences and third party information. This last source of information is the communication of agents' own opinions. When dealing with cognitive agents endowed with complex reasoning mechanisms, we would like that these opinions could be justified in a way such that the resulting information was more complete and reliable. In this paper we present LRep, a language based on an existing ontology of reputation that allows building justifications of communicated social evaluations.
@neurIST - Towards a System Architecture for Advanced Disease Management through Integration of Heterogeneous Data, Computing, and Complex Processing Services
Authors: Hariharan Rajasekaran, Luigi Lo Iacono, Peer Hasselmeyer, Jochen Fingberg, Paul Summers, Siegfried Benkner, Gerhard Engelbrecht, Antonio Arbona, Alessandro Chiarini, Christoph M. Friedrich, Martin Hofmann-Apitius, Kai Kumpf, Bob Moore, Philippe Bijlenga, Jimison Iavindrasana, Henning Mueller, Rod D. Hose, Robert Dunlop, Alejandro Frangi
Venue: Proceedings of the 2008 21st IEEE International Symposium on Computer-Based Medical Systems (2008)

This paper presents the system architecture of the @neurIST project, which aims at supporting the research and treatment of cerebral aneurysms by bringing together heterogeneous data, computing and complex processing services. The architecture is generic enough to adapt it to the treatment of other diseases beyond cerebral aneurysms. The paper describes the generic requirements of the system and presents the architecture, applications and middleware technologies used to realise the system and highlights the innovations in @neurIST.
A New Protocol for Conditional Disclosure of Secrets and Its Applications
Authors: Sven Laur, Helger Lipmaa
Venue: Proceedings of the 5th international conference on Applied Cryptography and Network Security (2007)

Many protocols that are based on homomorphic encryption are private only if a client submits inputs from a limited range $\mathcal{S}$. Conditional disclosure of secrets (CDS) helps to overcome this restriction. In a CDS protocol for a set $\mathcal{S}$, the client obtains server's secret if and only if the client's inputs belong to $\mathcal{S}$ and thus the server can guard itself against malformed queries. We extend the existing CDS protocols to work over additively homomorphic cryptosystems for every set from NP/ poly. The new construction is modular and easy to apply. As an example, we derive a new oblivious transfer protocol with log-squared communication and a millionaire's protocol with logarithmic communication. We also implement private, universally verifiable and robust multi-candidate electronic voting so that all voters only transmit an encryption of their vote. The only hardness assumption in all these protocols is that the underlying public-key cryptosystem is IND-CPA secure and the plaintext order does not have small factors.
Improved Fast Fuzzy C-Means Algorithm for Medical MR Images Segmentation
Authors: Min Li, Tinglei Huang, Gangqiang Zhu
Venue: Proceedings of the 2008 Second International Conference on Genetic and Evolutionary Computing (2008)

Fuzzy c-means (FCM) clustering algorithm has been widely used in automated image segmentation. However, the standard FCM algorithm takes a long time to partition a large dataset. In addition, in current fuzzy cluster algorithms it is difficult to determine the cluster centers. This paper proposes a modified FCM algorithm for MR (Magnetic Resonance) brain images segmentation. This method fetches in statistic histogram information for minimizing the iteration times, and in the iteration process, the optimal number of clusters is automatically determined. Using this method, an optimal classification rate is obtained in the test dataset, which includes large stochastic noises. The experiment results have shown that the segmentation method proposed in this paper is more accurate and faster than the standard FCM or the fast fuzzy c-means (FFCM) algorithm.
Predictions for the Future of Optimisation Research
Authors: David Corne
Venue: Proceedings of the 7th international conference on Unconventional Computing (2008)

The global effort to find good optimisation methods is an evolutionary algorithm (note "is", not "is analogous to"). A team's research effort is an individual, or `chromosome', and peer review is a (very) noisy and multiobjective fitness metric. Genetic operators (new directions and ideas for research efforts) are guided partly by discussions at conferences, maybe even sometimes guided by plenary talks. In this talk I will predict what kind of research in optimisation I expect to have the highest fitness scores in the next several years. They will be, mainly, combinations of learning and optimisation that are theoretically justified, or simply justified by their excellent results, and they will be works concerned with generating algorithms that quickly solve a distribution of problem instances, rather than one at a time. These combinations of learning and optimisation will be informed by the (slow) realisation that several separate studies, emerging from different subfields, are converging on very similar styles of approach. A particular point is that, in this way, we see that theoretical work on optimisation is slowly beginning to understand aspects of methods used by nature. Finally, these are predictions, and certainly not prescriptions. The overarching evolutionary process that we serve cannot succeed unless lots of diversity is maintained. So, please ignore what I say.
On the Longest RNG Edge of Wireless Ad Hoc Networks
Authors: Peng-Jun Wan, Lixin Wang, Frances Yao, Chih-Wei Yi
Venue: Proceedings of the 2008 The 28th International Conference on Distributed Computing Systems (2008)

Relative neighborhood graph (RNG) has been widely used in topology control and geographic routing in wireless ad hoc networks. Its maximum edge length is the minimum requirement on the maximum transmission radius by those applications of RNG. In this paper, we derive the precise asymptotic probability distribution of the maximum edge length of the RNG on a Poisson point process over a unit-area disk. Since the maximum RNG edge length is a lower bound on the critical transmission radius for greedy forward routing, our result also leads to an improved asymptotic almost sure lower bound on the critical transmission radius for greedy forward routing.
Ultra High Performance ECC over NIST Primes on Commercial FPGAs
Authors: Tim Güneysu, Christof Paar
Venue: Proceeding sof the 10th international workshop on Cryptographic Hardware and Embedded Systems (2008)

Elliptic Curve Cryptosystems (ECC) have gained increasing acceptance in practice due to their significantly smaller bit size of the operands compared to other public-key cryptosystems. Since their computational complexity is often lower than in the case of RSA or discrete logarithm schemes, ECC are often chosen for high performance public-key applications. However, despite a wealth of research regarding high-speed software and high-speed FPGA implementation of ECC since the mid 1990s, providing truly high-performance ECC on readily available (i.e., non-ASIC) platforms remains an open challenge. This holds especially for ECC over prime fields, which are often preferred over binary fields due to standards in Europe and the US.This work presents a new architecture for an FPGA-based ultra high performance ECC implementation over prime fields. Our architecture makes intensive use of the DSP blocks in modern FPGAs, which are embedded arithmetic units actually intended to accelerate digital signal processing algorithms. We describe a novel architecture and algorithms for performing ECC arithmetic and describe the actual implementation of standard compliant ECC based on the NIST primes P-224 and P-256. We show that ECC on Xilinx's Virtex-4 SX55 FPGA can be performed at a rate of more than 37,000 point multiplications per second. Our architecture outperforms all single-chip hardware implementations over prime fields in the open literature by a wide margin.
Preimage Attacks on Step-Reduced MD5
Authors: Yu Sasaki, Kazumaro Aoki
Venue: Proceedings of the 13th Australasian conference on Information Security and Privacy (2008)

In this paper, we propose preimage attacks on step-reduced MD5. We show that a preimage of a 44-step MD5 can be computed to a complexity of 296. We also consider a preimage attack against variants of MD5 where the round order is modified from the real MD5. In such a case, a preimage of a 51-step round-reordered MD5 can be computed to a complexity of 296. Our attack uses "local collisions" of MD5 to create a degree of message freedom. This freedom enables us to match the two 128-bit intermediate values efficiently.
ARPM: Agent-based Routing Protocol for MANET
Authors: Helen Bakhsh, Manal Abdullah
Venue: International Journal of Internet Protocol Technology (2008)

Routing problem in MANETs has become challenging because of the advances in mobile wireless technologies and infrastructures. Mobile Agent's (MA) technologies are ideal for such environments, it offers a promising solution of routing problems, where it can reduce network traffic and maintain load balancing, and thereby increasing routing performance. In this paper, we have proposed an agent-based Routing Protocol for MANET (ARPM) that is a multi-agent-based protocol, which makes nodes in the network topology-aware. ARPM has been implemented and tested using QualNet simulator.
Carry Small, Live Large
Authors: Roy Want
Venue: IEEE Pervasive Computing (2007)

The phrase "Carry Small, Live Large" embodies the idea that for mobility, small computers are attractive; they fit in a pocket and can be carried without encumbering their owner. "Live large" speaks to the idea that we have high expectations for our interactions with computers, and we expect them to positively impact our lives.
Research on Real-Time Sequential Decision of Texas Star Assembly
Authors: Ying Zhou, Zhen Zhang, Chenyong Liu
Venue: Proceedings of the 4th international conference on Intelligent Computing: Advanced Intelligent Computing Theories and Applications - with Aspects of Theoretical and Methodological Issues (2008)

Sequential decision processes can be described as Markov processes. Because it is difficult to solve Markov processes, the real-time sequential decision processes based on VR simulation, which avoids to calculate the state transition probability matrix, is discussed. A new mechanism of driving directly VRML scene by simulator which is developed by VRMLScript is put forward. The mechanism solves the thorny problem of simulation control, such as scene glint and logic error of simulation etc. The real-time sequential decision system of texas star (a component of a passenger plane) assembly is developed .It is proved that the expected goal of the real-time sequential decision of texas star assembly can be approaching gradually.