ppxscal/embedding_network huggingface dataset:
Generating and drawing area-proportional euler and venn diagrams
Authors: Stirling Christopher Chow
Venue:  (2007)

An Euler diagram C = {c 1, c2, . . . , cn} is a collection of n simple closed curves (i.e., Jordan curves) that partition the plane into connected subsets, called regions, each of which is enclosed by a unique combination of curves. Typically, Euler diagrams are used to visualize the distribution of discrete characteristics across a sample population; in this case, each curve represents a characteristic and each region represents the sub-population possessing exactly the combination of containing curves' properties. Venn diagrams are a subclass of Euler diagrams in which there are 2n regions representing all possible combinations of curves (e.g., two partially overlapping circles). In this dissertation, we study the Euler Diagram Generation Problem (EDGP), which involves constructing an Euler diagram with a prescribed set of regions. We describe a graph-theoretic model of an Euler diagram's structure and use this model to develop necessary-and-sufficient existence conditions. We also use the graph-theoretic model to prove that the EDGP is NP-complete. In addition, we study the related Area-Proportional Euler Diagram Generation Problem (&omega;-EDGP), which involves constructing an Euler diagram with a prescribed set of regions, each of which has a prescribed area. We develop algorithms for constructing area-proportional Euler diagrams composed of up to three circles and rectangles, as well as diagrams with an unbounded number of curves and a region of common intersection. Finally, we present implementations of our algorithms that allow the dynamic manipulation and real-time construction of area-proportional Euler diagrams.
Negative Generator Border for Effective Pattern Maintenance
Authors: Mengling Feng, Jinyan Li, Limsoon Wong, Yap-Peng Tan
Venue: Proceedings of the 4th international conference on Advanced Data Mining and Applications (2008)

In this paper, we study the maintenance of frequent patterns in the context of the generator representation. The generator representation is a concise and lossless representation of frequent patterns. We effectively maintain the generator representation by systematically expanding its Negative Generator Border. In the literature, very few work has addressed the maintenance of the generator representation. To illustrate the proposed maintenance idea, a new algorithm is developed to maintain the generator representation for support threshold adjustment. Our experimental results show that the proposed algorithm is significantly faster than other state-of-the-art algorithms. This proposed maintenance idea can also be extended to other representations of frequent patterns as demonstrated in this paper.
Physics of flow in weighted complex networks
Authors: H. Eugene Stanley
Venue:  (2008)

This thesis uses concepts from statistical physics to understand the physics of flow in weighted complex networks. The traditional model for random networks is the Erdo&huml;s-R&eacute;nyi (ER.) network, where a network of N nodes is created by connecting each of the N(N - 1)/2 pairs of nodes with a probability p. The degree distribution, which is the probability distribution of the number of links per node, is a Poisson distribution. Recent studies of the topology in many networks such as the Internet and the world-wide airport network (WAN) reveal a power law degree distribution, known as a scale-free (SF) distribution. To yield a better description of network dynamics, we study weighted networks, where each link or node is given a number. One asks how the weights affect the static and the dynamic properties of the network. In this thesis, two important dynamic problems are studied: the current flow problem, described by Kirchhoff's laws, and the maximum flow problem, which maximizes the flow between two nodes. Percolation theory is applied to these studies of the dynamics in complex networks. We find that the current flow in disordered media belongs to the same universality class as the optimal path. In a randomly weighted network, we identify the infinite incipient percolation cluster as the "superhighway", which contains most of the traffic in a network. We propose an efficient strategy to improve significantly the global transport by improving the superhighways, which comprise a small fraction of the network. We also propose a network model with correlated weights to describe weighted networks such as the WAN. Our model agrees with WAN data, and provides insight into the advantages of correlated weights in networks. Lastly, the upper critical dimension is evaluated using two different numerical methods, and the result is consistent with the theoretical prediction.
On Practical Information Flow Policies for Java-Enabled Multiapplication Smart Cards
Authors: Dorina Ghindici, Isabelle Simplot-Ryl
Venue: Proceedings of the 8th IFIP WG 8.8/11.2 international conference on Smart Card Research and Advanced Applications (2008)

In the multiapplicative context of smart cards, a strict control of underlying information flow between applications is highly desired. In this paper we propose a model to improve information flow usability in such systems by limiting the overhead for adding information flow security to a Java Virtual Machine. We define a domain specific language for defining security policies describing the allowed information flow inside the card. The applications are certified at loading time with respect to information flow security policies. We illustrate our approach on the LoyaltyCard, a multiapplicative smart card involving four loyalty applications sharing fidelity points.
Conjunctive queries for ontology based agent communication in MAS
Authors: Cassia Trojahn, Paulo Quaresma, Renata Vieira
Venue: Proceedings of the 7th international joint conference on Autonomous agents and multiagent systems - Volume 2 (2008)

In order to obtain semantic interoperability in open Multi-Agent Systems, agents need to agree on the basis of different ontologies. In this paper we formally define mapping as correspondences between queries over ontologies. Individual mappings are computed by specialized agents using different mapping approaches. Next, these agents use argumentation to exchange their local results, in order to agree on the mappings. Based on their preferences and strength of the arguments, the agents compute their preferred mapping sets. The arguments in such preferred sets are viewed as the set of globally acceptable arguments. These arguments are then represented as conjunctive queries in OWL-DL extended with DL-safe rules [9], a restriction imposed to attain decidability in such query answering system.
Energy Constrained Multipath Routing in Wireless Sensor Networks
Authors: Antoine B. Bagula, Kuzamunu G. Mazandu
Venue: Proceedings of the 5th international conference on Ubiquitous Intelligence and Computing (2008)

This paper addresses the issue of Quality of Service (QoS) Routing to improve energy consumption in wireless sensor networks (WSNs). Building upon a previously proposed QoS provisioning benchmark model, we formulate the problem of routing sensed information in a WSN network as a path-based energy minimization problem subject to QoS routing constraints expressed in terms of reliability, delay and geo-spatial energy consumption. Using probabilistic approximations, we transform the path-based model into a link-based model and apply methods borrowed from the zero-one optimization framework to solve this problem. By comparing the performance achieved by its solution to the benchmark model, simulation results reveal that our model outperforms the benchmark model in terms of energy consumption and quality of paths used to route the sensed information.
Coupling Deformable Models for Multi-object Segmentation
Authors: Dagmar Kainmueller, Hans Lamecker, Stefan Zachow, Hans-Christian Hege
Venue: Proceedings of the 4th international symposium on Biomedical Simulation (2008)

For biomechanical simulations, the segmentation of multiple adjacent anatomical structures from medical image data is often required. If adjacent structures are hardly distinguishable in image data, automatic segmentation methods for single structures in general do not yield sufficiently accurate results. To improve segmentation accuracy in these cases, knowledge about adjacent structures must be exploited. Optimal graph searching based on deformable surface models allows for a simultaneous segmentation of multiple adjacent objects. However, this method requires a correspondence relation between vertices of adjacent surface meshes. Line segments, each containing two corresponding vertices, may then serve as shared displacement directions in the segmentation process. The problem is how to define suitable correspondences on arbitrary surfaces. In this paper we propose a scheme for constructing a correspondence relation in adjacent regions of two arbitrary surfaces. When applying the thus generated shared displacement directions in segmentation with deformable surfaces, overlap of the surfaces is guaranteed not to occur. We show correspondence relations for regions on a femoral head and acetabulum and other adjacent structures, as well as preliminary segmentation results obtained by a graph cut algorithm.
Fingerprint Scaling
Authors: Chun-Xiao Ren, Yi-Long Yin, Jun Ma, Hao Li
Venue: Proceedings of the 4th international conference on Intelligent Computing: Advanced Intelligent Computing Theories and Applications - with Aspects of Theoretical and Methodological Issues (2008)

The problem of fingerprint scaling has received limited attention in the literature. Fingerprint scaling is an important issue for fingerprint sensor interoperability. However, no systematic study has been conducted to ascertain its effect on fingerprint systems. In this paper, a fingerprint scaling scheme using the average inter-ridge distance is presented. At first, the average inter-ridge distances of two fingerprint images acquired with two different fingerprint sensors are estimated respectively. Then the images are zoomed according to scale of the two average inter-ridge distances. Experiments have shown that the proposed fingerprint scaling method has good performance.
Crew resource management training for surgeons: feasibility and impact
Authors: Stephanie Guerlain, Florence E. Turrentine, David T. Bauer, J. Forrest Calland, Reid Adams
Venue: Cognition, Technology and Work (2008)

This paper describes a prospective, within-subjects study to measure the before-after effect of training five general surgery attendings on crew resource management (CRM) strategies on the resultant use and perceived utility of those strategies. Subjects were trained via a 1-h lecture on seven CRM skills after their second observed case, and participated in a 15&#x00a0;min debriefing with the trainers immediately following their fourth through sixth observed cases. These interventions led to a significant increase in frequency (by 26&#x2013;70%) of preoperative briefing elements over baseline. There was a significant correlation between the use of CRM practices and their perceived utility in improving team coordination and reducing error.
A New Method for Robust and Efficient Occupancy Grid-Map Matching
Authors: Jose-Luis Blanco, Javier Gonzalez, Juan-Antonio Fernandez-Madrigal
Venue: Proceedings of the 3rd Iberian conference on Pattern Recognition and Image Analysis, Part II (2007)

In this paper we propose a new matching method for occupancy grid-maps under the perspective of image registration. Our approach is based on extracting feature descriptors by means of a polar coordinate transformation around highly distinctive points. The proposed method presents a modest computation complexity, although it can find matchings between features reliably and regardless their orientation. Experimental results show the robustness of the estimates even for dynamic environments. Our proposal has important applications into the field of mobile robotics.
Cognitive and Technical Artefacts for Supporting Reusing Learning Scenario Patterns
Authors: Emmanuelle Villiot-Leclercq, Aude Dufresne
Venue: Proceedings of the 9th international conference on Intelligent Tutoring Systems (2008)

We present an intelligent tutoring system for teachers, which was designed to support them while they learn and adapt a learning scenario for their teaching. The system is a learning environment where teachers can explore different learning scenarios and get advice on the criteria for choosing among them. Then they choose a "case study" scenario and learn to adapt it to their own context. Different kind of support are given during the interaction with the system, declarative and procedural help is presented as indexed help on each activity, but also as contextual help using a rule based advice system. The system was experimented with eight teachers (four academic and four from industry), who succeeded to adapt the `case study" scenario to their own context. The evaluation and discussion present what help they found more useful and how the system could be improved.
Immune Algorithm Versus Differential Evolution: A Comparative Case Study Using High Dimensional Function Optimization
Authors: Vincenzo Cutello, Natalio Krasnogor, Giuseppe Nicosia, Mario Pavone
Venue: Proceedings of the 8th international conference on Adaptive and Natural Computing Algorithms, Part I (2007)

In this paper we propose an immune algorithm (IA) to solve high dimensional global optimization problems. To evaluate the effectiveness and quality of the IA we performed a large set of unconstrained numerical optimisation experiments, which is a crucial component of many real-world problem-solving settings. We extensively compare the IA against several Differential Evolution (DE) algorithms as these have been shown to perform better than many other Evolutionary Algorithms on similar problems. The DE algorithms were implemented using a range of recombination and mutation operators combinations. The algorithms were tested on 13 well known benchmark problems. Our results show that the proposed IA is effective, in terms of accuracy, and capable of solving large-scale instances of our benchmarks. We also show that the IA is comparable, and often outperforms, all the DE variants, including two Memetic algorithms.
Evolutionary Strategy for Political Districting Problem Using Genetic Algorithm
Authors: Chung-I Chou, You-Ling Chu, Sai-Ping Li
Venue: Proceedings of the 7th international conference on Computational Science, Part IV: ICCS 2007 (2007)

The aim of the Political Districting Problem is to partition a zone into electoral districts with constraints such as contiguity, population equality, etc. By using statistical physics methods, the problem can be mapped onto a q-state Potts model system, and the political constraints are written as an energy function with interactions between sites or external fields acting on the system. This problem is then transformed into an optimization problem. In this paper, we apply the genetic algorithm to Political Districting Problem. We will illustrate the evolutionary strategy for GA and compare with results from other optimization algorithms.
Stability of two player game structures
Authors: Andreas Polyméris
Venue: Discrete Applied Mathematics (2008)

We have extended a two player game-theoretical model proposed by V. Gurvich [To theory of multi-step games, USSR Comput. Math and Math. Phys. 13 (1973)] and H. Moulin [The Strategy of Social Choice, North Holland, Amsterdam, 1983]: All the considered game situations are framed by the same game structure. The structure determines the families of potential decisions of the two players, as well as the subsets of possible outcomes allowed by pairs of such choices. To be a solution of a game, a pair of decisions has to determine a (pure) functional equilibrium of the situational pair of payoff mappings which transforms the realized outcome into real-valued rewards of the players. Accordingly we understand that a structure is stable, if it admits functional equilibria for all possible game situations; and that it is complete, if every situation that only partitions the potential outcomes, is dominated by one of the players. We have generalized and strengthened a theorem by V. Gurvich [Equilibrium in pure strategies, Soviet Math. Dokl. 38 (1989)], proving that a proper structure is stable iff it is complete. Additional results provide game-theoretical insight that focuses the inquiry on the complexity of the stability decision problem; in particular, for coherent structures. These results also have combinatorial importance because every structure is characterized by a pair of hypergraphs [C. Berge, Graphes et Hypergraphes, Dunod, 1970] over a common ground set. The structure is dual (complete/coherent) iff the clutter of one hypergraph equals (includes/is included in) the blocker of the other one. So, for non-void coherent structures, the stability decision problem is equivalent to the much studied subexponential [M.L. Fredman, L. Khachiyan, On the complexity of dualization of monotone disjunctive normal forms, J. Algorithms 21 (1996)] hypergraph duality decision problem.
Palmprint Linear Feature Extraction and Identification Based on Ridgelet Transforms and Rough Sets
Authors: Shanwen Zhang, Shulin Wang, Xuelin Li
Venue: Proceedings of the 4th international conference on Intelligent Computing: Advanced Intelligent Computing Theories and Applications - with Aspects of Artificial Intelligence (2008)

As one of the most important biometrics features, palmprint with many strong points has significant influence on research. In this paper, we propose a novel method of palmprint feature extraction and identification using ridgelet transforms and rough sets. Firstly, the palmprints are first converted into the time-frequency domain image by ridgelet transforms without any further preprocessing such as image enhancement and texture thinning, and then feature extraction vector is conducted. Different features are used to lead a detection table. Then rough set is applied to remove the redundancy of the detection table. By this way, the length of conduction attribute is much shorter than that by traditional algorithm. Finally, the effectiveness of the proposed method is evaluated by the classification accuracy of SVM classifier. The experimental results show that the method has higher recognition rate and faster processing speed.
Text Generation in the SmartWeb Multimodal Dialogue System
Authors: Ralf Engel, Daniel Sonntag
Venue: Proceedings of the 30th annual German conference on Advances in Artificial Intelligence (2007)

This paper presents the text generation module of SmartWeb, a multimodal dialogue system. The generation module bases on NipsGen which combines SPIN, originally a parser developed for spoken language, and a tree-adjoining grammar framework for German. NipsGen allows to mix full generation with canned text.
Three-Dimensional Ultrasonic Assessment of Atherosclerotic Plaques
Authors: José Seabra, João Sanches, Luís M. Pedro, J. Fernandes E Fernandes
Venue: Proceedings of the 3rd Iberian conference on Pattern Recognition and Image Analysis, Part II (2007)

Carotid atherosclerosis is the most common life-threatening neurological disease and therefore an accurate assessment of atheromatous plaques is clinically important. Several studies were developed to characterize plaques from two-dimensional (2D) ultrasound images that are associated with high risk of stroke. However, 2D characterization may not be very accurate because it depends on the selection of a representative ultrasound image of the plaque by an experimented physician. In this paper we present a novel approach for diagnosis based on 3D ultrasound, which only requires a common ultrasound equipment without need of any additional and expensive devices like spatial locators. The semi-automatic algorithm uses medical guidance to obtain a 3D representation of the carotid artery and plaque and automatically generates measures to characterize the plaque in terms of dimensions and texture. A useful analysis tool is provided to allow the identification of vulnerable foci within the plaque.
Revising Probabilistic Prolog Programs
Authors: Luc Raedt, Kristian Kersting, Angelika Kimmig, Kate Revoredo, Hannu Toivonen
Venue: Inductive Logic Programming: 16th International Conference, ILP 2006, Santiago de Compostela, Spain, August 24-27, 2006, Revised Selected Papers (2007)

The ProbLog (probabilistic prolog) language has been introduced in [1], where various algorithms have been developed for solving and approximating ProbLog queries. Here, we define and study the problem of revising ProbLog theories from examples.
Modes of concept definition and varieties of vagueness
Authors: Brandon Bennett
Venue: Applied Ontology (2005)

The paper considers the problem of defining concepts within formal ontologies. A number of distinct modes of definition are identified, which represent alternative viewpoints on the classification of objects. The nature of these modes is examined and interactions and correlations between them are considered. This analysis is used to characterise a number of key problems that confront the attempt to analyse the meanings of natural language concepts by means of a precise formal ontology. Some proposals are made as to how these problems might be overcome. It is argued that specification of precise formal semantics requires clear separation between aspects of meaning that are based on different modes of classification. But, to provide an adequate ontological framework to describe the semantics of natural language terms, additional formal apparatus is required to synthesise their meaning by combining the different modes. This meta-level ontological formalism must articulate the interactions between the different modes.
On the Stability and Bias-Variance Analysis of Kernel Matrix Learning
Authors: V. Vijaya Saradhi, Harish Karnick
Venue: Proceedings of the 20th conference of the Canadian Society for Computational Studies of Intelligence on Advances in Artificial Intelligence (2007)

Stability and bias-variance analysis are two powerful tools to understand learning algorithms better. We use these tools to analyze learning the kernel matrix (LKM) algorithm. The motivation comes from: (i) LKM works in the transductive setting where both training and test data points are to be given apriori. Hence, it is worth knowing the stability of LKM under small variations in the data set and (ii) It has been argued that LKMs overfit the given data set. In particular we are interested in answering the following questions: (a) Is LKM a stable algorithm? (b) do they overfit (c) what is the bias behavior with different optimal kernels?. Our experimental results show that LKMs do not overfit the given data set. The stability analysis reveals that LKMs are unstable algorithms.
Building Trusted Sub-domain for the Grid with Trusted Computing
Authors: Jing Zhan, Huanguo Zhang, Fei Yan
Venue: Information Security and Cryptology: Third SKLOIS Conference, Inscrypt 2007, Xining, China, August 31 - September 5, 2007, Revised Selected Papers (2007)

The Grid is all about collaboration, which is supported by dynamic, multi-institutional virtual organizations (VO). The fact that Grid users and resource providers often suffer from attacks outside or inside the VO make it necessary to build a trusted sub-domain. The TCG (Trusted Computing Group) proposes Trusted Computing (TC) to enhance users' trust on today's open architecture platforms by adding a tamper-resistant hardware module called Trusted Platform Module (TPM) to the end system. In this paper, we propose and design an open-source security system based on Linux and TPM hardware to extend the trust on the platform to the Grid environment, and hereby provide sharing of trusted environment. Especially, we demonstrate how to build a trusted sub-domain for the Grid with our system by using trusted attestation and migration based on the TC.