ppxscal/embedding_network huggingface dataset:
On the Relationships between Notions of&#x00a0;Simulation-Based Security
Authors: Ralf K&#x00fc;sters, Anupam Datta, John C. Mitchell, Ajith Ramanathan
Venue: Journal of Cryptology (2008)

Several compositional forms of simulation-based security have been proposed in the literature, including Universal Composability, Black-Box Simulatability, and variants thereof. These relations between a protocol and an ideal functionality are similar enough that they can be ordered from strongest to weakest according to the logical form of their definitions. However, determining whether two relations are in fact identical depends on some subtle features that have not been brought out in previous studies. We identify two main factors: the position of a &#x201c;master process&#x201d; in the distributed system and some limitations on transparent message forwarding within computational complexity bounds. Using a general computational framework, called Sequential Probabilistic Process Calculus (SPPC), we clarify the relationships between the simulation-based security conditions. Many of the proofs are carried out based on a small set of equivalence principles involving processes and distributed systems. These equivalences exhibit the essential properties needed to prove relationships between security notions and allow us to carry over our results to those computational models which satisfy these equivalences.
A Smart Indoor Navigation Solution Based on Building Information Model and Google Android
Authors: Ferial Shayeganfar, Amin Anjomshoaa, A Min Tjoa
Venue: Proceedings of the 11th international conference on Computers Helping People with Special Needs (2008)

There are many types of indoor and outdoor navigation tools and methodologies available. A majority of these solutions are based on Global Positioning Systems (GPS) and instant video and image processing. These approaches are ideal for open world environments where very few information about the target location is available, but for large scale building environments such as hospitals, governmental offices, etc the end-user will need more detailed information about the surrounding context which is especially important in case of people with special needs. This paper presents a smart indoor navigation solution that is based on Semantic Web technologies and Building Information Model (BIM). The proposed solution is also aligned with Google Android's concepts to enlighten the realization of results.
GenTax: A Generic Methodology for Deriving OWL and RDF-S Ontologies from Hierarchical Classifications, Thesauri, and Inconsistent Taxonomies
Authors: Martin Hepp, Jos Bruijn
Venue: Proceedings of the 4th European conference on The Semantic Web: Research and Applications (2007)

Hierarchical classifications, thesauri, and informal taxonomies are likely the most valuable input for creating, at reasonable cost, non-toy ontologies in many domains. They contain, readily available, a wealth of category definitions plus a hierarchy, and they reflect some degree of community consensus. However, their transformation into useful ontologies is not as straightforward as it appears. In this paper, we show that (1) it often depends on the context of usage whether an informal hierarchical categorization schema is a classification, a thesaurus, or a taxonomy, and (2) present a novel methodology for automatically deriving consistent RDF-S and OWL ontologies from such schemas. Finally, we (3) demonstrate the usefulness of this approach by transforming the two e-business categorization standards eCl@ss and UNSPSC into ontologies that overcome the limitations of earlier prototypes. Our approach allows for the script-based creation of meaningful ontology classes for a particular context while preserving the original hierarchy, even if the latter is not a real subsumption hierarchy in this particular context. Human intervention in the transformation is limited to checking some conceptual properties and identifying frequent anomalies, and the only input required is an informal categorization plus a notion of the target context. In particular, the approach does not require instance data, as ontology learning approaches would usually do.
A Policy Iteration Technique for Time Elapse over Template Polyhedra
Authors: Sriram Sankaranarayanan, Thao Dang, Franjo Ivančić
Venue: Proceedings of the 11th international workshop on Hybrid Systems: Computation and Control (2008)

We present a technique to compute over-approximations of the time trajectories of an affine hybrid system using template polyhedra. Such polyhedra are obtained by conjoining a set of inequality templates with varying constant coefficients. Given a set of template expressions, we show the existence of a smallest template polyhedron that is a positive invariant w.r.t to the dynamics of the continuous variables, and hence, an over-approximation of the time trajectories. However, the least invariant is hard to compute efficiently. Therefore, we propose a policy iteration technique that iterates over the space of invariant certificates to converge onto a solution that is close to the least solution. We incorporate our ideas in our prototype tool TimePass for safety verification of affine hybrid systems, with promising results on benchmarks.
Perception of Emotions from Static Postures
Authors: Ahmad S. Shaarani, Daniela M. Romano
Venue: Proceedings of the 2nd international conference on Affective Computing and Intelligent Interaction (2007)

Human synthetic characters in any computer simulated environment need to be capable of behaving the appropriate way of expressing emotion like normal human do. If the characters fail to express the suitable emotional expression, they will likely to break the users mood and belief. These imply that the key problem in designing synthetic characters is to make them believable in their overall behavior. Therefore the study was directed to construct human synthetic characters that can improve humans respond as well as identify intensity rating of emotions. Ekmans six emotional expressions [1], which are happiness, sadness, anger, surprise, fear and disgust were used because these basic emotions are clear, widely accepted and sufficient. An experiment was conducted to measure believable emotional expression from static images. Sets of virtual human static images of posed expressions of emotions were shown to the subjects. A total of 36 thirty-six volunteers (18 men and 18 women) took part in the experiment. The mean age was 29 years old. The subjects were asked to recognize the expressions by grouping them into six basic emotions and provide the level of emotion for each posture to study the intensity-rating tasks.
An integrated method of parameter design and tolerance design for multiple criteria systems
Authors: Qianmei Feng
Venue: International Journal of Computer Applications in Technology (2008)

The complicated engineering design is accomplished through three steps: system design, parameter design, and tolerance design. Parameter design and tolerance design are typically performed sequentially to determine nominal values and tolerance levels of control factors. While production costs are often reduced and quality levels are increased at the parameter design stage, the further improvement in quality at the tolerance design stage usually increases the cost. In order to reduce the product life cycle and manufacturing costs, this paper presents an integrated approach for parameter design and tolerance design to find the optimal settings of nominal values and tolerance levels for a system with multiple criteria. The case study of a passive filter network demonstrates that the proposed methodology provides, not only the reduced cost during the design phases, but also the decreased variation from multiple output responses.
A Mutation-Particle Swarm Algorithm for Error-Bounded Polygonal Approximation of Digital Curves
Authors: Bin Wang, Hua-Zhong Shu, Bao-Sheng Li, Zhi-Mei Niu
Venue: Proceedings of the 4th international conference on Intelligent Computing: Advanced Intelligent Computing Theories and Applications - with Aspects of Theoretical and Methodological Issues (2008)

This paper presents a particle swarm optimization algorithm (PSO) to solve error-bounded polygonal approximation of digital curves. Different from the existing PSO-based methods for polygonal approximation problem, the mutation operators borrowed from genetic algorithms, are incorporated into the PSO, so we call it MPSO. This scheme can increase the diversity of the population and help the particles effectively escape from the local optimum. Experiments were performed on three commonly used benchmark curves to test the effectiveness of the proposed MPSO. The results manifest that the proposed MPSO has the higher performance than the existing GA-based methods and PSO methods.
An offline foundation for online accountable pseudonyms
Authors: Bryan Ford, Jacob Strauss
Venue: Proceedings of the 1st Workshop on Social Network Systems (2008)

Online anonymity often appears to undermine accountability, offering little incentive for civil behavior, but accountability failures usually result not from anonymity itself but from the disposability of virtual identities. A user banned for misbehavior---e.g., spamming from a free E-mail account or stuffing an online ballot box---can simply open other accounts or connect from other IP addresses. Instead of curtailing freedom of expression by giving up anonymity, online services and communities should support accountable pseudonyms: virtual personas that can provide both anonymity and accountability. We propose Pseudonym parties, a scheme for creating accountable pseudonyms, which combine inperson social occasions (parties) with technical infrastructure (a pseudonymous sign-on service) to enforce the rule that one real person gets one virtual persona on any participating online service. Pseudonym parties enable the user to adopt different personas in different online spaces without revealing the connection between them, while ensuring that each user has only one accountable pseudonym in each space. Pseudonym parties can be started incrementally in a fully decentralized fashion, can run on volunteer labor with minimal funds, and may even be fun.
Measuring the Node Energy Consumption in USB Based WSN Testbeds
Authors: Andreas Kopke, Adam Wolisz
Venue: Proceedings of the 2008 The 28th International Conference on Distributed Computing Systems Workshops (2008)

Energy consumption is one of the critical concerns in sensor networks. In particular, there is substantial interest to investigate the distribution of the energy consumption among different nodes depending on the protocol stack applied for specific traffic characteristics. Unfortunately, experimental investigations to this point are rather difficult, as means for cheap, easy to deploy, while precise estimation of actual energy consumption are not really available. As a solution we developed an affordable and precise circuit that measures the energy consumption in situ. It delivers the result to the sensor node, enabling nodes to take their remaining energy into account. Furthermore, it is to some extent independent from the node type and the testbed type.
Performance evaluation of a two stage adaptive genetic algorithm (TSAGA) in structural topology optimization
Authors: R. Balamurugan, C. V. Ramakrishnan, Nidur Singh
Venue: Applied Soft Computing (2008)

Genetic algorithm with island and adaptive features has been used for reaching the global optimal solution in the context of structural topology optimization. A two stage adaptive genetic algorithm (TSAGA) involving a self-adaptive island genetic algorithm (SAIGA) for the first stage and adaptive techniques in the second stage is proposed for the use in bit-array represented topology optimization. The first stage, consisting a number of island runs each starting with a different set of random population and searching for better designs in different peaks, helps the algorithm in performing an extensive global search. After the completion of island runs the initial population for the second stage is formed from the best members of each island that provides greater variety and potential for faster improvement and is run for a predefined number of generations. In this second stage the genetic parameters and operators are dynamically adapted with the progress of optimization process in such a way as to increase the convergence rate while maintaining the diversity in population. The results obtained on several single and multiple loading case problems have been compared with other GA and non-GA-based approaches, and the efficiency and effectiveness of the proposed methodology in reaching the global optimal solution is demonstrated.
Characteristics Preserving of Ultrasound Medical Images Based on Kernel Principal Component Analysis
Authors: Tongsen Hu, Ting Gui
Venue: Medical Imaging and Informatics: 2nd International Conference, MIMI 2007, Beijing, China, August 14-16, 2007 Revised Selected Papers (2008)

Kernel Principal Component Analysis (KPCA) is one of the methods available for analyzing ultrasound medical images of liver cancer. First the original ultrasound images need airspace filtering, frequency filtering and morphologic operation to form the characteristic images and these characteristic images are fused into a new characteristic matrix. Then analyzing the matrix by using KPCA and the principle components (in general, they are not unique) are found in order to that the most general characteristics of the original image can be preserved accurately. Finally the eigenvector projection matrix of the original image which is composed of the principle components can reflect the most essential characteristics of the original images. The simulation experiments were made and effective results were acquired. Compared with the experiments of wavelets, the experiment of KPCA showed that KPCA is more effective than wavelets especially in the application of ultrasound medical images.
Simultaneously modeling humans' preferences and their beliefs about others' preferences
Authors: Sevan G. Ficici, Avi Pfeffer
Venue: Proceedings of the 7th international joint conference on Autonomous agents and multiagent systems - Volume 1 (2008)

In strategic multiagent decision making, it is often the case that a strategic reasoner must hold beliefs about other agents and use these beliefs to inform its decision making. The behavior thus produced by the reasoner involves an interaction between the reasoner's beliefs about other agents and the reasoner's own preferences. A significant challenge faced by model designers, therefore, is how to model such a reasoner's behavior so that the reasoner's preferences and beliefs can each be identified and distinguished from each other. In this paper, we introduce a model of strategic reasoning that allows us to distinguish between the reasoner's utility function and the reasoner's beliefs about another agent's utility function as well as the reasoner's beliefs about how that agent might interact with yet other agents. We show that our model is uniquely identifiable. That is, no two different parameter settings will cause the model to give the same behavior over all possible inputs. We then illustrate the performance of our model in a multiagent negotiation game played by human subjects. We find that our subjects have slightly incorrect beliefs about other agents in the game.
Multi-pose Ear Recognition Based on Improved Locally Linear Embedding
Authors: Xu Han, Zhi-Chun Mu
Venue: Proceedings of the 2008 Congress on Image and Signal Processing, Vol. 2 - Volume 02 (2008)

In this paper, an improved Locally Linear Embedding method is proposed and used in the multi-pose ear recognition. In the traditional LLE method, the neighbors of a data point are selected by using k-nearest neighbor algorithm or e-nearest neighbor algorithm. Both of these methods neglect the different neighborhood of each data point and use a uniform way to select neighbors which leads to the sensitiveness of LLE method to the sparseness of data structure. Some sophisticated methods are used to avoid this problem, but they may be time-consuming. The improved idea solves this problem by selecting a basic value Kb first and partially calculating the reconstruction error within a ball with a radius fixed by multiplying the distance of the Kb-th nearest point with an h, selecting the value of K with minimal reconstruction error. Experimental results on multi-pose ear recognition show the improvement and effectiveness of this method.
Solving shallow-water systems in 2D domains using Finite Volume methods and multimedia SSE instructions
Authors: M. J. Castro, J. A. García-Rodríguez, J. M. González-Vida, C. Parés
Venue: Journal of Computational and Applied Mathematics (2008)

The goal of this paper is to construct efficient parallel solvers for 2D hyperbolic systems of conservation laws with source terms and nonconservative products. The method of lines is applied: at every intercell a projected Riemann problem along the normal direction is considered which is discretized by means of well-balanced Roe methods. The resulting 2D numerical scheme is explicit and first-order accurate. In [M.J. Castro, J.A. Garcia, J.M. Gonzalez, C. Pares, A parallel 2D Finite Volume scheme for solving systems of balance laws with nonconservative products: Application to shallow flows, Comput. Methods Appl. Mech. Engrg. 196 (2006) 2788-2815] a domain decomposition method was used to parallelize the resulting numerical scheme, which was implemented in a PC cluster by means of MPI techniques. In this paper, in order to optimize the computations, a new parallelization of SIMD type is performed at each MPI thread, by means of SSE (''Streaming SIMD Extensions''), which are present in common processors. More specifically, as the most costly part of the calculations performed at each processor consists of a huge number of small matrix and vector computations, we use the Intel^(C) Integrated Performance Primitives small matrix library. To make easy the use of this library, which is implemented using assembler and SSE instructions, we have developed a C++ wrapper of this library in an efficient way. Some numerical tests were carried out to validate the performance of the C++ small matrix wrapper. The specific application of the scheme to one-layer Shallow-Water systems has been implemented on a PC's cluster. The correct behavior of the one-layer model is assessed using laboratory data.
Automatic Target Recognition in SAR Images Based on a SVM Classification Scheme
Authors: Wolfgang Middelmann, Alfons Ebert, Ulrich Thoennessen
Venue: Proceedings of the 8th international conference on Adaptive and Natural Computing Algorithms, Part II (2007)

The performance of classifiers is commonly evaluated by classification rate and false alarm rate (FAR). Many applications like traffic monitoring, surveillance and other security relevant tasks suffer from the problem balancing the performance criteria in an appropriate way. In this contribution, we propose a kernel classification scheme with high performance in discriminating classes and rejecting clutter objects. Especially, it determines a class membership assessment. The classification scheme consists of two kernel classification stages and a maximum decision module as combiner. For tests, we use targets taken from the MSTAR synthetic aperture radar (SAR) dataset and clutter objects extracted from SAR scenes by a screening process. The dependency on parameter variations is shown and receiver operator characteristic (ROC) curves are given. The results confirm the high classification performance at low FARs. The integration into an operational demonstration system is in progress.
An efficient adaptive analysis procedure for certified solutions with exact bounds of strain energy for elasticity problems
Authors: G. Y. Zhang, G. R. Liu, Y. Li
Venue: Finite Elements in Analysis and Design (2008)

We present an efficient adaptive analysis procedure to obtain certified solutions of desired accuracy with bounds to the exact solution in energy norm for elasticity problems. The procedure makes the use of the recent finding that the upper bound to the exact strain energy can be obtained using the linearly conforming point interpolation method (LC-PIM), and the well-known fact that the lower bound can be obtained using the standard displacement-based fully compatible finite element method (FEM). To perform the adaptive analysis, a residual error-based error indicator and a simple h-type refinement scheme are employed and the relative error of the computed strain energy is used as the global stopping criteria. A number of numerical examples, including problems with singularity, have been studied to demonstrate the effectiveness and efficiency of the present procedure. The numerical results have been found converging very fast to the exact solution, and the bounds to the exact strain energy can be obtained efficiently at any stage in the adaptive process whenever required.
Nonlinear and Neural Networks Based Adaptive Control for a Wastewater Treatment Bioprocess
Authors: Emil Petre, Dan Selişteanu, Dorin Şendrescu, Cosmin Ionete
Venue: Proceedings of the 12th international conference on Knowledge-Based Intelligent Information and Engineering Systems, Part II (2008)

The paper studies the design and analysis of some nonlinear and neural adaptive control strategies for a wastewater treatment process, which is an activated sludge process with nonlinear, time varying and not exactly known kinetics. In fact, an adaptive controller based on a dynamical neural network used as a model of the unknown plant is developed and then is compared with a classical linearizing controller. The neural controller design is achieved by using an input-output feedback linearization technique.
A Terminology for Control Models at Optical Exchanges
Authors: Freek Dijkstra, Bas Oudenaarde, Bert Andree, Leon Gommans, Paola Grosso, Jeroen Ham, Karst Koymans, Cees Laat
Venue: Proceedings of the 1st international conference on Autonomous Infrastructure, Management and Security: Inter-Domain Management (2007)

Optical or lambda exchanges have emerged to interconnect networks, providing dynamic switching capabilities on OSI layer 1 and layer 2. So far, the only inter-domain dynamics have occurred on layer 3, the IP layer. This new functionality in the data plane has consequences on the control plane. We explain this by comparing optical exchanges with current Internet exchanges.Descriptions of optical exchanges have appeared in the literature, but discussions about these exchanges have been hampered by a lack of common terminology. This paper defines a common terminology for exchanges. Discussion in the community revealed four different meaning for the term "open exchange". We list them in this paper.We classify the different kind of exchanges based on the interactions between the domains at the control plane. We use these control models to distinguish between different types of interconnection points.