ppxscal/embedding_network huggingface dataset:
Development and evaluation of methodologies for vulnerability analysis of ad-hoc routing protocols
Authors: John S. Baras
Venue:  (2007)

This thesis presents a number methodologies for computer assisted vulnerability analysis of routing protocols in ad-hoc networks towards the goal of automating the process of finding vulnerabilities (possible attacks) on such network routing protocols and correcting the protocols. The methodologies developed are (each) based on a different representation (model) of the routing protocol, which model predicated the quantitative methods and algorithms used. Each methodology is evaluated with respect to effectiveness feasibility and possibility of application to realistically sized networks. The first methodology studied is based on formal models of the protocols and associated symbolic partially ordered model checkers. Using this methodology, a simple attack in unsecured AODV is demonstrated. An extension of the Strands model is developed which is suitable for such routing protocols. The second methodology is based on timed-probabilistic formal models which is necessary due to the probabilistic nature of ad-hoc routing protocols. This second methodolgy uses natural extensions of the first one. A nondeterministic-timing model based on partially ordered events is considered for application towards the model checking problem. Determining probabilities within this structure requires the calculation of the volume of a particular type of convex volume, which is known to be # P-hard. A new algorithm is derived, exploiting the particular problem structure, that can be used to reduce the amount of time used to compute these quantities over conventional algorithms. We show that timed-probabilistic formal models can be linked to trace-based techniques by sampling methods, and conversely how execution traces can serve as starting points for formal exploration of the state space. We show that an approach combining both trace-based and formal methods can have faster convergence than either alone on a set of problems. However, the applicability of both of these techniques to ad-hoc network routing protocols is limited to small networks and relatively simple attacks. We provide evidence to this end. To address this limitation, a final technique employing only trace-based methods within an optimization framework is developed. In an application of this third methodology, it is shown that it can be used to evaluate the effects of a simple attack on OLSR. The result can be viewed (from a certain perspective) as an example of automatically discovering a new attack on the OLSR routing protocol.
Analysing Graph Transformation Rules through OCL
Authors: Jordi Cabot, Robert Clarisó, Esther Guerra, Juan Lara
Venue: Proceedings of the 1st international conference on Theory and Practice of Model Transformations (2008)

In this paper we present an approach to the analysis of graph transformation rules based on an intermediate OCL representation. We translate different semantics of rules into OCL, together with the properties of interest (like rule applicability, conflict or independence). The intermediate representation serves three purposes: (i) allows the seamless integration of graph transformation rules with the MOF and OCL standards, and enables taking into account meta-model and OCL constraints when verifying the correctness of the rules; (ii) permits the interoperability of graph transformation concepts with a number of standards-based model-driven development tools; and (iii) makes available a plethora of OCL tools to actually perform the rule analysis.
Letters: Adaptive biomimetic control of robot arm motions
Authors: Sungho Jo
Venue: Neurocomputing (2008)

By introducing a biologically inspired robotic model that combines a modified feedback error learning, an unsupervised learning, and the viscoelastic actuator system in order to drive adaptive arm motions, this paper discusses the potential usefulness of a biomimetic design of robot skill. The feedback error learning is consistent with the cerebellar adaptation, the unsupervised learning, the synergy network adaptation, and the viscoelastic system of the muscles. The proposed model applies a feedforward adaptive scheme in the low dimensional control space and an adaptive synergy distribution to control redundant actuators effectively. The combination of the two adaptive control schemes is tested by controlling a two-link planar robot arm with six muscular actuators in the gravitational field. The simulation-based study demonstrates that the control scheme adapts the robot arm motions quickly and robustly to generate smooth, human-like motions.
Predicting admission counseling triumph of colleges using neural networks
Authors: Maitrei Kohli, Priti Puri
Venue: Proceedings of the 7th WSEAS International Conference on Artificial intelligence, knowledge engineering and data bases (2008)

Forecasting student admission in colleges and as a result ranking the colleges has intrigued many scholars and academic industry leaders as a difficult and challenging problem. In this study, the use of neural networks in forecasting the performance of technical colleges in the counseling session before it actually takes place is explored. We convert this forecasting problem into a classification one, i.e., we classify a college based upon its total number of seats filled in one of the five categories, ranging from 'flop' to 'top'. Because our neural network model can predict the success of a college in gaining maximum admissions in an academic year before the actual admissions take place, it can be used as a powerful decision aid by university management, colleges and anticipating students. Since we have used the evaluation version of the software, we are therefore getting the maximum accuracy of 72%. This is mainly due to the reason that the evaluation version does not incorporate all the features required to compute accurate result. Employing the neural network model by using the 10-fold cross validation methodology shows that the neural networks do a much better job of predicting in this setting.
Global EDF-Based Scheduling with Efficient Priority Promotion
Authors: Shinpei Kato, Nobuyuki Yamasaki
Venue: Proceedings of the 2008 14th IEEE International Conference on Embedded and Real-Time Computing Systems and Applications (2008)

This paper presents an algorithm, called Earliest Deadline Critical Laxity (EDCL), for the efficient scheduling of sporadic real-time tasks on multiprocessors systems. EDCL is a derivative of the Earliest Deadline Zero Laxity (EDZL) algorithm in that the priority of a job reaching certain laxity is imperiously promoted to the top, but it differs in that the occurrence of priority promotion is confined to at the release time or the completion time of a job. This modification enables EDCL to bound the number of scheduler invocations and to relax the implementation complexity of scheduler, while the schedulability is still competitive with EDZL. The schedulability test of EDCL is designed through theoretical analysis. In addition, an error in the traditional schedulability test of EDZL is corrected. Simulation studies demonstrate the effectiveness of EDCL in terms of guaranteed schedulability and exhaustive schedulability by comparing with traditional efficient scheduling algorithms.
Sosemanuk, a Fast Software-Oriented Stream Cipher
Authors: Côme Berbain, Olivier Billet, Anne Canteaut, Nicolas Courtois, Henri Gilbert, Louis Goubin, Aline Gouget, Louis Granboulan, Cédric Lauradoux, Marine Minier, Thomas Pornin, Hervé Sibert
Venue: New Stream Cipher Designs: The eSTREAM Finalists (2008)

Sosemanuk is a new synchronous software-oriented stream cipher, corresponding to Profile 1 of the ECRYPT call for stream cipher primitives. Its key length is variable between 128 and 256 bits. It accommodates a 128-bit initial value. Any key length is claimed to achieve 128-bit security. The Sosemanuk cipher uses both some basic design principles from the stream cipher SNOW 2.0 and some transformations derived from the block cipher SERPENT. Sosemanuk aims at improving SNOW 2.0 both from the security and from the efficiency points of view. Most notably, it uses a faster IV-setup procedure. It also requires a reduced amount of static data, yielding better performance on several architectures.
A Hierarchical Key Distribution Scheme for Conditional Access System in DTV Broadcasting
Authors: Mengyao Zhu, Ming Zhang, Xiaoling Chen, Ding Zhang, Zhijie Huang
Venue: Computational Intelligence and Security: International Conference, CIS 2006, Guangzhou, China, November 3-6, 2006, Revised Selected Papers (2007)

A variety of subscriptions in Conditional Access System (CAS) of DTV broadcasting network bring complexity to the key distribution scheme. In this paper, an innovation of hierarchical key distribution scheme for CAS in DTV broadcasting is proposed to reduce the computation of encryption and the number of messages for key refreshment. Compared with the conventional key distribution schemes, no encrypted message is distributed for key refreshment when a subscriber leaves. Further more, our hierarchical tree of key can provide a lot more dynamic management, from which broadcasters can improve efficiency in managing program channels.
Approximate predictive state representations
Authors: Britton Wolfe, Michael R. James, Satinder Singh
Venue: Proceedings of the 7th international joint conference on Autonomous agents and multiagent systems - Volume 1 (2008)

Predictive state representations (PSRs) are models that represent the state of a dynamical system as a set of predictions about future events. The existing work with PSRs focuses on trying to learn exact models, an approach that cannot scale to complex dynamical systems. In contrast, our work takes the first steps in developing a theory of approximate PSRs. We examine the consequences of using an approximate predictive state representation, bounding the error of the approximate state under certain conditions. We also introduce factored PSRs, a class of PSRs with a particular approximate state representation. We show that the class of factored PSRs allow one to tune the degree of approximation by trading off accuracy for compactness. We demonstrate this trade-off empirically on some example systems, using factored PSRs that were learned from data.
Flow and diffusion distributed structures with noise at the inlet
Authors: Pavel V. Kuptsov, Razvan A. Satnoianu
Venue: Mathematics and Computers in Simulation (2008)

Flow and diffusion distributed structures (FDS) are stationary spatially periodic patterns that can be observed in reaction-diffusion-advection systems. These structures arise when the flow rate exceeds a certain bifurcation point provided that concentrations of interacting species at the inlet differ from steady-state values and the concentrations are held constant. Normally, theoretical studies of these patterns are developed without concerning a noise. In this paper we consider FDS for a more realistic conditions and assume that the inlet concentrations are perturbed by a small noise. When the flow rate is small, the FDS is linearly sensitive to noise at the inlet. Even weak fluctuations destroy the stationary pattern and an oscillatory solution appears instead. For higher flow rates the instability becomes nonlinear; the pattern remains unaltered for a weak noise and undergoes the destruction when the noise amplitude passes a certain threshold. We represent a detailed description of these effects and examine two scenarios for the stabilization.
Heuristic Genetic Algorithm for Multicast Overlay Network Link Selection
Authors: Dezhi Wang, Jinying Gan, Deyu Wang
Venue: Proceedings of the 2008 Second International Conference on Genetic and Evolutionary Computing (2008)

The application level multicast overlay network (ON) is composed by the hosts based on the physics unicast links between them. The initial ON is a completely connectivity network, which make the multicast tree construction and routing is lower efficiency. For improving the ON routing performance, the ON links should be selected. Based on a new presented ON link selection model with reliability and minimal routing cost constraints, put forward an heuristic genetic algorithm (HGA). The algorithm combines the characteristics of the heuristic algorithm and genetic algorithm. The algorithm can reduce the ON links and be satisfied with the network constraints. Simulation results show that the HGA has fast converging speed and stabilization, and simply operation
On Existence of Non-stationary Realization of a Linear Multivariable Control System
Authors: V. A. Rusanov, A. V. Daneev, A. E. Kumenko, D. Yu. Sharpinskiy
Venue: Proceedings of the 2008 19th International Conference on Systems Engineering (2008)

We define the main conception for the methodology, which forms the basis of the procedures for constructing abstract Kalman-Mesarovic realization of a dynamic system with state equations that belong to the class of linear non-stationary differential equations. From this viewpoint, the authors interpreted the key approaches to solving classical problems of realization theory in terms of the Rayleigh-Ritz operator.
Bounded Unpopularity Matchings
Authors: Chien-Chung Huang, Telikepalli Kavitha, Dimitrios Michail, Meghana Nasre
Venue: Proceedings of the 11th Scandinavian workshop on Algorithm Theory (2008)

We investigate the following problem: given a set of jobs and a set of people with preferences over the jobs, what is the optimal way of matching people to jobs? Here we consider the notion of popularity. A matching M is popular if there is no matching M¿ such that more people prefer M¿ to M than the other way around. Determining whether a given instance admits a popular matching and, if so, finding one, was studied in [2]. If there is no popular matching, a reasonable substitute is a matching whose unpopularity is bounded. We consider two measures of unpopularity - unpopularity factor denoted by u(M) and unpopularity margin denoted by g(M). McCutchen recently showed that computing a matching M with the minimum value of u(M) or g(M) is NP-hard, and that if G does not admit a popular matching, then we have u(M) ¿ 2 for all matchings M in G.Here we show that a matching M that achieves u(M) = 2 can be computed in $O(m\sqrt{n})$ time (where m is the number of edges in G and n is the number of nodes) provided a certain graph H admits a matching that matches all people. We also describe a sequence of graphs: H = H 2, H 3,...,H k such that if H k admits a matching that matches all people, then we can compute in $O(km\sqrt{n})$ time a matching M such that u(M) ≤ k ¿ 1 and $g(M) \le n(1-\frac{2}{k})$. Simulation results suggest that our algorithm finds a matching with low unpopularity.
WebGen System - Visually Impaired Users Create Web Pages
Authors: Luděk Bártek, Jaromír Plhák
Venue: Proceedings of the 11th international conference on Computers Helping People with Special Needs (2008)

The aim of the WebGen system is to allow visually impaired users to create web presentations in a simple and natural way by means of dialogue. This paper describes the basic methods and principles used in the system Web-Gen, especially the system structure and the dialogue interface. An illustrative example of a dialogue is included as well as the resulting web page.
Using the Intension of Classes and Properties Definition in Ontologies for Word Sense Disambiguation
Authors: Khaled Khelif, Fabien Gandon, Olivier Corby, Rose Dieng-Kuntz
Venue: Proceedings of the 16th international conference on Knowledge Engineering: Practice and Patterns (2008)

We present an ontology-driven word sense disambiguation process. The main idea consists of using the context of the ambiguous word to decide which class can be assigned to it. The disambiguation relies on similarities between classes assigned to the ambiguous word, classes assigned to terms close to it in the text, and on the type of properties that could occur between them. The computation of the similarity uses domain ontologies to provide semantic distances based on definitions in intension. We tested our approach in the extraction of annotations from biomedical texts.
Flask: staged functional programming for sensor networks
Authors: Geoffrey Mainland, Greg Morrisett, Matt Welsh
Venue: Proceeding of the 13th ACM SIGPLAN international conference on Functional programming (2008)

Severely resource-constrained devices present a confounding challenge to the functional programmer: we are used to having powerful abstraction facilities at our fingertips, but how can we make use of these tools on a device with an 8- or 16-bit CPU and at most tens of kilobytes of RAM? Motivated by this challenge, we have developed Flask, a domain specific language embedded in Haskell that brings the power of functional programming to sensor networks, collections of highly resource-constrained devices. Flask consists of a staging mechanism that cleanly separates node-level code from the meta-language used to generate node-level code fragments; syntactic support for embedding standard sensor network code; a restricted subset of Haskell that runs on sensor networks and constrains program space and time consumption; a higher-level "data stream" combinator library for quickly constructing sensor network programs; and an extensible runtime that provides commonly-used services. We demonstrate Flask through several small code examples as well as a compiler that generates node-level code to execute a network-wide query specified in a SQL-like language. We show how using Flask ensures constraints on space and time behavior. Through microbenchmarks and measurements on physical hardware, we demonstrate that Flask produces programs that are efficient in terms of CPU and memory usage and that can run effectively on existing sensor network hardware.
Why Petascale Visualization and Analysis Will Change the Rules
Authors: Hank Childs
Venue: Proceedings of the 8th international conference on Computational Science, Part I (2008)

In the last decade, supercomputers and the scientific simulations performed on them have dramatically increased in size. Currently, simulations can use hundreds of TeraFLOPs (trillions of floating point operations per second) and generate many, many terabytes of data. In the near future, we will see PetaFLOP computing and petabytes of data. In addition, a critical step in the simulation process is "postprocessing": applying visualization and analysis techniques to better understand the simulation. As a result, the issues of visualizing and analyzing massive data sets have never been more important. This puts the spotlight on two key issues. One, are we prepared for the unprecedented scale of data that we will need to postprocess? And, two, assuming that we can handle data of this size, can we intelligently analyze these simulations? I will argue that, for both of these questions, we must "change the rules" and make dramatic departures from our current modus operandi.
Traffic Management by Constant Time to Collision
Authors: Valentina E. Balas, Marius M. Balas
Venue: Proceedings of the 12th international conference on Knowledge-Based Intelligent Information and Engineering Systems, Part III (2008)

The paper is presenting a new method for the management of the traffic flow on highways, based on the constant time to collision criterion. The criterion is applied at two levels, for each car implied in traffic, and for the whole highway. Each car is provided with a constant time to collision cruise controller, that is maintaining optimal distance-gaps between cars, in accor dance to the technical data of each car, the actual speed, and an imposed time to collision. The highway's traffic management center has the possibility to im pose the same optimal time to collision to all the cars in the traffic. This way the traffic is permanently organizing itself, by distributing the cars such way that the collision risk is uniformly distributed. The traffic intensity is controlled by the imposed time to collision.
Efficient Inclusion Checking for Deterministic Tree Automata and DTDs
Authors: Jérôme Champavère, Rémi Gilleron, Aurélien Lemay, Joachim Niehren
Venue: Language and Automata Theory and Applications: Second International Conference, LATA 2008, Tarragona, Spain, March 13-19, 2008. Revised Papers (2008)

We present a new algorithm for testing language inclusion L(A) ¿ L(B) between tree automata in time O(|A|*|B|) where B is deterministic. We extend this algorithm for testing inclusion between automata for unranked trees A and deterministic DTDs D in time O(|A|*|Σ|*|D|). No previous algorithms with these complexities exist.
Stakeholder Perception of Enterprise Architecture
Authors: Bas Raadt, Sander Schouten, Hans Vliet
Venue: Proceedings of the 2nd European conference on Software Architecture (2008)

Enterprise Architecture (EA) is increasingly being used by large organizations to get a grip on the complexity and inflexibility of their business processes, information systems and technical infrastructure. Although seen as an important instrument to help solve major organizational problems, effectively applying EA seems no easy task. Efficient collaboration between architects and EA stakeholders is one of the main critical success factors for EA. The basis for efficient collaboration between architects and EA stakeholders is mutual understanding. In EA research, there has been much focus on the role of the architect; there is little research on the EA stakeholder. In this article we present the cognitive structure of four EA stakeholder groups, revealing how they expect the EA function to help them achieve their goals. With this we gain understanding of the EA stakeholder and provide the basis for better collaboration between architects and EA stakeholders.
Fighting untrustworthy Internet content: In search of regulatory scenarios
Authors: J. E. J. Prins, M. H. M. Schellekens
Venue: Information Polity (2005)

The question of liability for the consequences of misleading information on the Internet is deeply problematic. The information chain can be long and pass through several jurisdictions en route from information supplier to information consumer. Organisations along the chain, such as ISPs, which attempt to provide quality or reliability checks, are inhibited from so doing by potential liabilites if they make public statements about their filtering policy. Self regulation would seem to offer one possible solution, but here too there are difficulties in both enforcement and with bodies which are outside the self regulatory environment. These problems are discussed and some proposals are put forward as to how self regulation could be made more effective and provide a greater degree of assurance to the consumer of online information.
Rethinking the Semantics of Complex Nominals
Authors: Nabil Abdullah, Richard A. Frost
Venue: Proceedings of the 20th conference of the Canadian Society for Computational Studies of Intelligence on Advances in Artificial Intelligence (2007)

Complex Nominals (CNs) have simple syntactic structure that conceals non-trivial semantic characteristics. While speakers of natural languages combine noun(s)/adjective(s) with a head noun to indicate existing or novel concepts with ease, formalizing such a semantic process, however, has proven to be a daunting task. In this paper, we present a unified semantic approach for constructions involving a head-noun and modifier(s), i.e., adjective(s)/noun(s). Based on a rigorous typing system, this approach uses set intersection as the only underlying semantic rule. We argue that this novel approach is compositional and warrants consistent inferences.