ppxscal/embedding_network huggingface dataset:
Institutionalizing information security risk management: a multi-method empirical study on the effects of regulation
Authors: Janine L. Spears
Venue:  (2007)

Information security has traditionally focused on known vulnerabilities to technological assets in order to safeguard organizational information from external threats, such as hackers and viruses. However, the majority of information security breaches are believed to be caused by internal employees, suggesting that more attention may be needed in managing internal people and process-related threats and vulnerabilities. In recent years, a series of regulations has forced organizations to manage various aspects of information security-related risk. The research question examined is: How does regulation affect information security risk management? A multi-method study was conducted. Interviews with twenty practitioners across ten organizations were conducted as part of a qualitative interpretive study. Informants included participants in Sarbanes-Oxley compliance and information security experts. Interpretive results informed a theoretical model that was tested in a subsequent positivist study. Institutional theory and process maturity were applied to examine the effects of regulation on institutionalizing information risk management practices. Two hundred and eighteen completed survey responses were obtained from ISACA members, a professional association specialized in IT audit and governance. A multi-dimensional model was examined using structural equation modeling. The model contained both causal and effect indicators, resulting in a model that is both descriptive and predictive. Findings from both the interpretive and positivist studies suggest that regulation may contribute to institutionalized risk management in at least two ways. First, regulation encourages a more formalized risk management process because organizations must be able to provide documented proof of their practices for compliance. Secondly, regulation raises the level of organizational awareness of information risk management when business managers are explicitly held accountable or when the regulation is aimed at business processes. Mature risk management practices and business participation in managing risk were found to result in an organizational culture that exhibits a shared language, heightened awareness and business ownership of risk management. Results from the interpretive study suggested that information security has two dimensions: management and practice. Support for these two dimensions was found in the positivist study. Institutionalized information security risk management was found to result in improved performance of operational and technical security controls from increased efficiency.
A generalized Takagi&#x2013;Sugeno&#x2013;Kang recurrent fuzzy-neural filter for adaptive noise cancelation
Authors: Paris Mastorocostas, Dimitris Varsamis, Constantinos Hilas, Constantinos Mastorocostas
Venue: Neural Computing and Applications (2008)

This paper presents a recurrent fuzzy-neural filter for adaptive noise cancelation. The cancelation task is transformed to a system-identification problem, which is tackled by use of the dynamic neuron-based fuzzy neural network (DN-FNN). The fuzzy model is based on Takagi&#x2013;Sugeno&#x2013;Kang fuzzy rules, whose consequent parts consist of linear combinations of dynamic neurons. The orthogonal least squares method is employed to select the number of rules, along with the number and kind of dynamic neurons that participate in each rule. Extensive simulation results are given and performance comparison with a series of other dynamic fuzzy and neural models is conducted, underlining the effectiveness of the proposed filter and its superior performance over its competing rivals.
Networks Become Navigable as Nodes Move and Forget
Authors: Augustin Chaintreau, Pierre Fraigniaud, Emmanuelle Lebhar
Venue: Proceedings of the 35th international colloquium on Automata, Languages and Programming, Part I (2008)

We propose a dynamic process for network evolution, aiming at explaining the emergence of the small world phenomenon, i.e., the statistical observation that any pair of individuals are linked by a short chain of acquaintances computable by a simple decentralized routing algorithm, known as greedy routing. Our model is based on the combination of two dynamics: a random walk (spatial) process, and an harmonic forgetting (temporal) process. Both processes reflect natural behaviors of the individuals, viewed as nodes in the network of inter-individual acquaintances. We prove that, in k-dimensional lattices, the combination of these two processes generates long-range links mutually independently distributed as a k-harmonic distribution. We analyze the performances of greedy routing at the stationary regime of our process, and prove that the expected number of steps for routing from any source to any target in any multidimensional lattice is a polylogarithmic function of the distance between the two nodes in the lattice. Up to our knowledge, these results are the first formal proof that navigability in small worlds can emerge from a dynamic process for network evolution. Our dynamica process can find practical applications to the design of spatial gossip and resource location protocols.
Interactive Video Game Platform for Game-Based Learning
Authors: Han-Bin Chang, Hui-Huang Hsu, Louis R. Chao
Venue: Proceedings of the 7th international conference on Advances in Web Based Learning (2008)

Interactive video technologies are developed for providing interactions for users to get better interactivity in watching TV programs. Since receiving TV programs is a common affair for general users, many systems with interactive TV technologies are implemented for educational or commercial purposes. Learning by playing game is a hot topic in current distance learning systems. Most of game-based learning systems designed by computer programmers and domain experts. Generating interactive game courses is hard for content providers since they are not computer experts. The interactive game authoring tool proposed in this paper provides a friendly interface to help users to create their educational games easily. The students will be attracted in such learning platform with entertaining elements.
Realistic simulation of vehicular communication and vehicle-2-X applications
Authors: Björn Schünemann, Kay Massow, Ilja Radusch
Venue: Proceedings of the 1st international conference on Simulation tools and techniques for communications, networks and systems & workshops (2008)

In future intelligent transport systems, wireless vehicular communication will provide the basis for new applications to enhance safety, traffic efficiency, and provide infotainment services. In the near future, field tests are to be carried out to verify the improvements that could be achieved by these new Vehicle-2-X applications. However, the realisation of such field tests is very complex and expensive. Therefore, detailed simulations are necessary to prepare the tests in the real world and reduce their costs. Current simulation tools do not support all aspects necessary for Vehicle-2-X applications. In this paper, we present an integrated software simulation environment that fulfils the special requirements of Vehicle-2-X applications. Furthermore, we introduce our testbed architecture that allows simulating vehicular communication under real physical conditions.
A Limit to the Power of Multiple Nucleation in Self-assembly
Authors: Aaron D. Sterling
Venue: Proceedings of the 22nd international symposium on Distributed Computing (2008)

Majumder, Reif and Sahu presented in [7] a model of reversible, error-permitting tile self-assembly, and showed that restricted classes of tile assembly systems achieved equilibrium in (expected) polynomial time. One open question they asked was how the model would change if it permitted multiple nucleation, i.e., independent groups of tiles growing before attaching to the original seed assembly. This paper provides a partial answer, by proving that no tile assembly model can use multiple nucleation to achieve speedup from polynomial time to constant time without sacrificing computational power: if a tile assembly system $\mathcal{T}$ uses multiple nucleation to tile a surface in constant time (independent of the size of the surface), then $\mathcal{T}$ is unable to solve computational problems that have low complexity in the (single-seeded) Winfree-Rothemund Tile Assembly Model. The proof technique defines a new model of distributed computing that simulates tile assembly, so a tile assembly model can be described as a distributed computing model.
simpA: A Simple Agent-Oriented Java Extension for Developing Concurrent Applications
Authors: Alessandro Ricci, Mirko Viroli, Giulio Piancastelli
Venue: Languages, Methodologies and Development Tools for Multi-Agent Systems: First International Workshop, LADS 2007, Durham, UK, September 4-6, 2007. Revised Selected Papers (2008)

More and more aspects of concurrency and concurrent programming are becoming part of mainstream programming and software engineering, as a result of several factors, such as the widespread availability of multi-core / parallel architectures and Internet-based systems. Java has been one of the first mainstream languages providing a first-class native support for multi-threading, with basic low level fine-grained concurrency mechanisms. Besides this fine-grained support to concurrency, the identification of higher-level--more coarse-grained--support is important as soon as programming and engineering complex concurrent applications is considered, helping to bridge the gap between system design, implementation and testing.Accordingly, in this paper we present simpA, a library-based extension of Java which introduces a high-level coarse-grained support to prototyping complex, multi-threaded / concurrent applications: Java programmers are provided with an agent-oriented abstraction layer on top of the basic OO layer to organize and structure applications.
A functional implementation of the garsia--wachs algorithm: (functional pearl)
Authors: Jean-Christophe Filliatre
Venue: Proceedings of the 2008 ACM SIGPLAN workshop on ML (2008)

This functional pearl proposes an ML implementation of the Garsia-Wachs algorithm. This somewhat obscure algorithm builds a binary tree with minimum weighted path length from weighted leaf nodes with given inorder. Our solution exhibits the usual benefits of functional programming (use of immutable data structures, pattern-matching, polymorphism) and nicely compares to the purely imperative implementation from The Art of Computer Programming.
Using Web-Content for Retrieving Snippets
Authors: Okky Hendriansyah, Tri Firgantoro, Mirna Adriani
Venue: Advances in Multilingual and Multimodal Information Retrieval: 8th Workshop of the Cross-Language Evaluation Forum, CLEF 2007, Budapest, Hungary, September 19-21, 2007, Revised Selected Papers (2008)

We report on our participation in the web task of the 2007 Cross-Language Evaluation Forum (CLEF). We compared the results of snippet extraction based on topic title, ordered window, and unordered window. The precision and recall of the snippet extraction based on topic title was the best compared to those of the ordered window and unordered window.
Acoustic Modems for Ubiquitous Computing
Authors: Cristina Videira Lopes, Pedro M. Q. Aguiar
Venue: IEEE Pervasive Computing (2003)

In a world in which several small computing devices communicate with each other and with humans in a context-aware manner, short-range, localized communication is critical. Efforts such as IrDA and Bluetooth show that simply scaling down the existing communication network does not properly address short-range communication. The authors argue that sound will play an important role in this new computing world. Sound offers features not available with other short-range, low bandwidth communication technologies, such as radio and infrared. For example, sound can be constrained within a room, eliminating outside interference. Sound can also expose the communication to humans when necessary. The authors describe several aerial acoustic modems that account for various human factors, such as the appeal and familiarity of message sounds.
Interpolating Vectors: Powerful Algorithm for Pattern Recognition
Authors: Kunihiko Fukushima
Venue: Neural Information Processing: 14th International Conference, ICONIP 2007, Kitakyushu, Japan, November 13-16, 2007, Revised Selected Papers, Part II (2008)

This paper proposes the use of interpolating vectors for robust pattern recognition. Labeled reference vectors in a multi-dimensional feature space are first produced by a kind of competitive learning. We then assume a situation where interpolating vectors are densely placed along lines connecting all pairs of reference vectors of the same label. From these interpolating vectors, we choose the one that has the largest similarity to the test vector. Its label shows the result of pattern recognition. We applied this method to the neocognitron for handwritten digit recognition, and reduced the error rate from 1.48% to 1.00% for a blind test set of 5000 digits.
Belief update in CLG Bayesian networks with lazy propagation
Authors: A. L. Madsen
Venue: International Journal of Approximate Reasoning (2008)

In recent years, Bayesian networks with a mixture of continuous and discrete variables have received an increasing level of attention. In this paper, we focus on the restricted class of mixture Bayesian networks known as conditional linear Gaussian Bayesian networks (CLG Bayesian networks) and present an architecture for exact belief update for this class of mixture networks. The proposed architecture is an extension of lazy propagation using operations of Lauritzen and Jensen [S.L. Lauritzen, F. Jensen, Stable local computation with mixed Gaussian distributions, Statistics and Computing 11(2) (2001) 191-203] and Cowell [R.G. Cowell, Local propagation in conditional Gaussian Bayesian networks, Journal of Machine Learning Research 6 (2005) 1517-1550]. By decomposing clique and separator potentials into sets of factors, the proposed architecture takes advantage of independence and irrelevance properties induced by the structure of the graph and the evidence. The resulting benefits are illustrated by examples and assessed by experiments. The performance of the proposed architecture has been evaluated using a set of randomly generated networks. The results indicate a significant potential of the proposed architecture.
Hypersequent Calculus for Intuitionistic Logic with Classical Atoms
Authors: Hidenori Kurokawa
Venue: Proceedings of the international symposium on Logical Foundations of Computer Science (2007)

We introduce a hypersequent calculus for intuitionistic logic with classical atoms, i.e. intuitionistic logic augmented with a special class of propositional variables for which we postulate the decidability property. This system combines classical logical reasoning with constructive and computationally oriented intuitionistic logic in one system. Our main result is the cut-elimination theorem with the subformula property for this system. We show this by a semantic method, namely via proving the completeness theorem of the hypersequent calculus without the cut rule. The cut-elimination theorem gives a semantic completeness of the system, decidability, and some form of the disjunction property. The ACM Portal is published by the Association for Computing Machinery. Copyright © 2010 ACM, Inc. Terms of Usage Privacy Policy Code of Ethics Contact Us Useful downloads: Adobe Acrobat QuickTime Windows Media Player Real Player
Anti-pattern Matching Modulo
Authors: Claude Kirchner, Radu Kopetz, Pierre-Etienne Moreau
Venue: Language and Automata Theory and Applications: Second International Conference, LATA 2008, Tarragona, Spain, March 13-19, 2008. Revised Papers (2008)

Negation is intrinsic to human thinking and most of the time when searching for something, we base our patterns on both positive and negative conditions. In a recent work, the notion of term was extended to the one of anti-term, i.e. terms that may contain complement symbols.Here we generalize the syntactic anti-pattern matching to anti-pattern matching modulo an arbitrary equational theory ¿, and we study the specific and practically very useful case of associativity, possibly with a unity ($\mathcal{AU}$). To this end, based on the syntacticness of associativity, we present a rule-based associative matching algorithm, and we extend it to $\mathcal{AU}$. This algorithm is then used to solve $\mathcal{AU}$ anti-pattern matching problems. This allows us to be generic enough so that for instance, the AllDiff standard predicate of constraint programming becomes simply expressible in this framework. $\mathcal{AU}$ anti-patterns are implemented in the Tom language and we show some examples of their usage.
Extensions of Manifold Learning Algorithms in Kernel Feature Space
Authors: Yaoliang Yu, Peng Guan, Liming Zhang
Venue: Proceedings of the 4th international symposium on Neural Networks: Advances in Neural Networks (2007)

Manifold learning algorithms have been proven to be capable of discovering some nonlinear structures. However, it is hard for them to extend to test set directly. In this paper, a simple yet effective extension algorithm called PIE is proposed. Unlike LPP, which is linear in nature, our method is nonlinear. Besides, our method will never suffer from the singularity problem while LPP and KLPP will. Experimental results of data visualization and classification validate the effectiveness of our proposed method.
Fault Diagnosis of Distributed Discrete Event Systems Using OBDD
Authors: Fei Xue, Da-zhong Zheng, Lu Yan
Venue: Informatica (2005)

In this paper, we study the fault diagnosis problem for distributed discrete event systems. The model assumes that the system is composed of distributed components that are modeled in labeled Petri nets and interact with each other via sets of common resources (places). Further, a component's own access to a common resource is an observable event. Based on the diagnoser approach proposed by Sampath et al, a distributed fault diagnosis algorithm with communication is presented. The distributed algorithm assumes that the local diagnosis process can exchange messages upon the occurrence of observable events. We prove the distribute diagnosis algorithm is correct in the sense that it recovers the same diagnostic information as the centralized diagnosis algorithm. And then, the OBDD (Ordered Binary Decision Diagrams) is introduced to manage the state explosion problem in state estimation of the system.
Activity recognition through multi-scale motion detail analysis
Authors: Youtian Du, Feng Chen, Wenli Xu, Weidong Zhang
Venue: Neurocomputing (2008)

Activity recognition is one of the most challenging problems in the video content analysis and high-level computer vision. This paper proposes a novel activity recognition approach in which we decompose an activity into multiple interactive stochastic processes, each corresponding to one scale of motion details. For modeling the interactive processes, we present a hierarchical durational-state dynamic Bayesian network (HDS-DBN) to model two stochastic processes which are related to two appropriate scales in intelligent surveillance. In HDS-DBN, states are decomposed in terms of multi-scale motion details, and each kind of state indicates legible meaning. The effectiveness of this approach is demonstrated by experiments of individual activity recognition and two-person interacting activity recognition.
Three-dimensional modeling from photometry and geometry
Authors: Long Quan
Venue:  (2007)

In this thesis, we focus on the 3D reconstruction from multiple images. We explore different approaches for reconstruction including photometric methods, i.e. modeling from a changing lighting, and geometric methods, i.e. modeling from a changing viewpoint. Photometric stereo uses images from different lighting conditions to build 3D model of an object. In this work, we improve photometric stereo from both reconstruction accuracy and data capturing simplicity. In conventional photometric stereo algorithms, surface shape can only be recovered at the resolution of input images, since only one normal direction is computed for each pixel. However, for a rough surface, there often exists sub-pixel level geometry structures. We have studied the relationship between surface reflectance and sub-pixel geometry structures to design a new photometric stereo algorithm that recovers sub-pixel level geometry structures. Our method significantly improves the modeling accuracy. Another limitation in conventional photometric stereo is that, the lighting conditions have to be recorded in data capturing. Otherwise, surface shape can only be recovered up to an unknown General Bas-Relief (GBR) shape ambiguity. In this thesis, we have observed that isotropy/reciprocity induces symmetry structures on Gauss sphere for any isotropic surface. And these symmetry structures are destroyed by a GBR transformation. Hence, we can resolve the unknown GBR shape ambiguity by restoring the broken symmetry for any isotropic surface. With our method, there is no need to record lighting conditions in data capturing for isotropic surface. This makes the data capturing procedure significantly simplified. Image-based modeling (IBM) uses images from different viewpoints to build 3D model of an object. Previous methods on image-based modeling are very successful at recovering camera poses and a set of 3D points of the object. But these recovered 3D points are typically unstructured. To generate 3D models ready to be used in applications such as movies, games or virtual tours, we organize these unstructured 3D points and build high quality texture mapped models from them. There are two key contributions in our approach. Firstly, we propose to segment 3D points together with 2D images into individual objects by a joint 2D-3D segmentation method. General segmentation of images is a very dicult problem. But since we have both 2D and 3D information which reinforce each other, the segmentation can be performed quite efficiently. Segmentation results provide clearly defined object boundary which is very useful for high quality modeling. Secondly, we proposed to synthesize occluded structure according to object priors learned from visible structures. An inevitable problem in image-based method is occlusion. No or less information is available in occluded regions. Our method can successfully propagate information from visible regions to invisible regions. Our method is tested on image-based modeling of trees. With our approach, we can build highly realistic digital model of trees from their images.
A New Bit-Serial Architecture for Field Multiplication Using Polynomial Bases
Authors: Arash Reyhani-Masoleh
Venue: Proceeding sof the 10th international workshop on Cryptographic Hardware and Embedded Systems (2008)

Multiplication is the main finite field arithmetic operation in elliptic curve cryptography and its bit-serial hardware implementation is attractive in resource constrained environments such as smart cards, where the chip area is limited. In this paper, a new serial-output bit-serial multiplier using polynomial bases over binary extension fields is proposed. It generates a bit of the multiplication in each clock cycle with the latency of one cycle. To the best of our knowledge, this is the first time that such a serial-output bit-serial multiplier architecture using polynomial bases for general irreducible polynomials is proposed.