ppxscal/embedding_network huggingface dataset:
Decision Analysis of Fuzzy Partition Tree Applying AIC and Fuzzy Decision
Authors: Kimiaki Shinkai, Shuya Kanagawa, Takenobu Takizawa, Hajime Yamashita
Venue: Proceedings of the 12th international conference on Knowledge-Based Intelligent Information and Engineering Systems, Part III (2008)

We often use fuzzy graph to analyze inexact information such as sociogram structure ([1] and [2]). Concerning the hierarchical cluster analysis of a fuzzy graph ([3], [4] and [5] ), the number of clusters may have to be decided in the actual cluster analysis. In other word, we woud like to decide the optimal level with a partition tree. Concerning this problem, while AIC method in statistical analysis has been designed by us ([6] and [10]), we will now propose a fuzzy decision method which is based on the evaluation function paying attention to the size and number of clusters at each level.
DCAR: Distributed Coding-Aware Routing in Wireless Networks
Authors: Jilin Le, John Chi Shing Lui, Dah Ming Chiu
Venue: Proceedings of the 2008 The 28th International Conference on Distributed Computing Systems (2008)

The practical network coding system proposed in [1] has two fundamental limitations: 1) the coding opportunity is crucially dependent on the established routes; 2) the coding structure is limited within a two-hop region. To overcome these limitations, we propose DCAR, the first distributed coding-aware routing mechanism which combines (a) the discovery for available paths between a given source and destination, and (b) the detection for potential network coding opportunities. DCAR has the potential to find high throughput paths with coding opportunities while conventional routing fails to do so. In addition, DCAR can detect coding opportunities on the entire path, thus eliminating the "two-hop" coding limitation in [1]. We also propose a novel routing metric called "CRM" (Coding-aware Routing Metric) which facilitates the comparison between coding-possible and coding-impossible paths. We implement the DCAR system in NS-2 and conduct extensive evaluation, which shows that DCAR achieves 7\% to 20\% throughput gain over the coding system in [1].
Extending the Four Russian Algorithm to Compute the Edit Script in Linear Space
Authors: Vamsi Kundeti, Sanguthevar Rajasekaran
Venue: Proceedings of the 8th international conference on Computational Science, Part I (2008)

Computing the edit distance between two strings is one of the most fundamental problems in computer science. The standard dynamic programming based algorithm computes the edit distance and edit script in O(n 2) time and space. Often the edit script is of more importance than the value of the edit distance. The Four Russian Algorithm [1] computes the edit distance in O(n 2/logn) time but does not address how to compute edit script within that runtime. Hirschberg [2] gave an algorithm to compute edit script in linear space but the runtime remained O(n 2). In this paper we present algorithms that compute both the edit script and edit distance in $O(\frac{n^2}{\log n})$ time using O(n) space.
A New Mechatronic Component for Adjusting the Footprint of Tracked Rescue Robots
Authors: Winai Chonnaparamutt, Andreas Birk
Venue: RoboCup 2006: Robot Soccer World Cup X (2006)

There is no ideal footprint for a rescue robot. In some situations, for example when climbing up a rubble pile or stairs, the footprint has to be large to maximize traction and to prevent tilting over. In other situations, for example when negotiating narrow passages or doorways, the footprint has to be small to prevent to get stuck. The common approach is to use flippers, i.e., additional support tracks that can change their posture relative to the main locomotion tracks. Here a novel mechatronic design for flippers is presented that overcomes a significant drawback in the state of the art approaches, namely the large forces in the joint between main locomotion tracks and flippers. Instead of directly driving this joint to change the posture, a link mechanism driven by a ballscrew is used. In this paper, a formal analysis of the new mechanism is presented including a comparison to the state of the art. Furthermore, a concrete implementation and results from practical experiments that support the formal analysis are presented.
Improving the Detection of Unknown Computer Worms Activity Using Active Learning
Authors: Robert Moskovitch, Nir Nissim, Dima Stopel, Clint Feher, Roman Englert, Yuval Elovici
Venue: Proceedings of the 30th annual German conference on Advances in Artificial Intelligence (2007)

Detecting unknown worms is a challenging task. Extant solutions, such as anti-virus tools, rely mainly on prior explicit knowledge of specific worm signatures. As a result, after the appearance of a new worm on the Web there is a significant delay until an update carrying the worm's signature is distributed to anti-virus tools. We propose an innovative technique for detecting the presence of an unknown worm, based on the computer operating system measurements. We monitored 323 computer features and reduced them to 20 features through feature selection. Support vector machines were applied using 3 kernel functions. In addition we used active learning as a selective sampling method to increase the performance of the classifier, exceeding above 90% mean accuracy, and for specific unknown worms 94% accuracy.
A model for adapting 3D graphics based on scalable coding, real-time simplification and remote rendering
Authors: Marius Preda, Paulo Villegas, Franciso Mor&#x00e1;n, Gauthier Lafruit, Robert-Paul Berretty
Venue: The Visual Computer: International Journal of Computer Graphics (2008)

Most current multiplayer 3D games can only be played on dedicated platforms, requiring specifically designed content and communication over a predefined network. To overcome these limitations, the OLGA (On-Line GAming) consortium has devised a framework to develop distributive, multiplayer 3D games. Scalability at the level of content, platforms and networks is exploited to achieve the best trade-offs between complexity and quality.
Coalitional skill games
Authors: Yoram Bachrach, Jeffrey S. Rosenschein
Venue: Proceedings of the 7th international joint conference on Autonomous agents and multiagent systems - Volume 2 (2008)

We consider Coalitional Skill Games (CSGs), a simple model of cooperation among agents. This is a restricted form of coalitional games, where each agent has a set of skills that are required to complete various tasks. Each task requires a set of skills in order to be completed, and a coalition can accomplish the task only if the coalition's agents cover the set of required skills for the task. The gain for a coalition depends only on the subset of tasks it can complete. We consider the computational complexity of several problems in CSGs, for example, testing if an agent is a dummy or veto agent, computing the core of the game or testing whether the core is empty, and finding the Shapley value or Banzhaf power index of agents.
User-Driven Service Lifecycle Management --- Adopting Internet Paradigms in Telecom Services
Authors: Juan C. Yelmo, Rubén Trapero, José M. Álamo, Juergen Sienel, Marc Drewniok, Isabel Ordás, Kathleen Mccallum
Venue: Proceedings of the 5th international conference on Service-Oriented Computing (2007)

The user-centric service creation paradigm set out in Web 2.0 technologies on the Internet allows users to define and share their new content and applications. Open services and interfaces provided by Google et al can be used to build easily, and quickly deploy exciting applications. User-centric service creation provides a cheap solution in contrast with the huge engineering effort that has to be spent both on development and marketing in order to get a new telecom service running and deployed in the market. Adopting Internet paradigms in telecom services requires major flexibility and dynamicity in managing service lifecycle compared to current service management systems.This paper proposes an approach to user-centric service lifecycle management in telecom-oriented platforms. It allows users to drive their services' lifecycle, e.g. when and for how long they must be available, as well as automating the process between the creation and the execution of the services.
Fingerprint Liveness Detection Using Curvelet Energy and Co-Occurrence Signatures
Authors: Shankar Bhausaheb Nikam, Suneeta Agarwal
Venue: Proceedings of the 2008 Fifth International Conference on Computer Graphics, Imaging and Visualisation (2008)

This paper proposes a new curvelet transform-based method to detect spoof fingerprint attacks in fingerprint biometric systems. It uses only one image to differentiate a real fingerprint from a spoof one. It is based on the observation that, real and spoof fingerprints exhibit different textural characteristics. Textural measures based on curvelet energy signatures and curvelet co-occurrence signatures are used to characterize fingerprint texture. Dimensionalities of the feature sets are reduced by running Pudil's Sequential Forward Floating Selection (SFFS) algorithm. We test two feature sets independently on various classifiers like: AdaBoost. M1, support vector machine and k-nearest neighbor; then we fuse all the mentioned classifiers using the "Majority Voting Rule" to form an Ensemble classifier. Classification rates achieved with these classifiers for energy signatures range from ~94.12% to ~97.41%. Likewise, classification rates for co-occurrence signatures range from ~94.35% to ~98.12%. Thus, the performance of a new liveness detection approach is very promising, as it needs only one fingerprint and no extra hardware to detect vitality.
Network Anomaly Detection System: The State of Art of Network Behaviour Analysis
Authors: Shu Yun Lim, Andy Jones
Venue: Proceedings of the 2008 International Conference on Convergence and Hybrid Information Technology (2008)

This paper presents a taxonomy of anomaly detection techniques that is then used to survey and classify a number of research prototypes and commercial products. Commercial products and solutions based anomaly detection techniques are beginning to establish themselves in mainstream security solutions alongside firewalls, intrusion prevention systems and network monitoring solutions. These solutions are focused mainly on network-based anomaly detection, thus creating a new industry buzzword that describes it: Network Behavior Analysis. This classification is used predictably, pointing towards a number of areas of future research in the field of anomaly detection.
Butterfly dress
Authors: Alexander Reeder
Venue: Proceedings of the 3rd international conference on Digital Interactive Media in Entertainment and Arts (2008)

The Butterfly Dress is an exploration of wearables, social computing and unspoken conversations. Butterflies on the dress flap in tandem with its wearer's heartbeat. The dress is beautiful and opens doors to new communication.
Interactive Multilingual Web Applications with Grammatical Framework
Authors: Moisés Salvador Meza Moreno, Björn Bringert
Venue: Proceedings of the 6th international conference on Advances in Natural Language Processing (2008)

We present an approach to multilingual web content based on multilingual grammars and syntax editing for a controlled language. Content can be edited in any supported language and it is automatically kept within a controlled language fragment. We have implemented a web-based syntax editor for Grammatical Framework (GF) grammars which allows both direct abstract syntax tree manipulation and text input in any of the languages supported by the grammar. With this syntax editor and the GF JavaScript API, GF grammars can be used to build multilingual web applications. As a demonstration, we have implemented an example application in which users can add, edit and review restaurants in English, Spanish and Swedish.
Mixtures of Experts: As an Attempt to Integrate the Dual Route Cascaded and the Triangle Models for Reading English Words
Authors: Shin-Ichi Asakawa
Venue: Neural Information Processing: 14th International Conference, ICONIP 2007, Kitakyushu, Japan, November 13-16, 2007, Revised Selected Papers, Part II (2008)

An implementation of neural network models for reading English words aloud is proposed. Since 1989, there has been existing a debate in neuropsycholgy and cognitive science about the models of reading. One is the Dual Route Cascaded model, another is the Triangle model. Since there exist arbitrary variables in both models, it was difficult to decide which model would be appropriate to explain the data from psychological experiments and neuropsychological evidence. Therefore, in order to provide a solution of this debate, an attempt to integrate both models was attempted. By introducing the Mixtures of Experts Network model, a solution to overcome the arbitrariness of both models could be given. The Mixtures of Experts Network model could include both models as a special case. From the Mixtures of Experts network's point of view, the difference between the Dual Route Cascaded model and the Triangle model would be considered as a quantitative difference of the dispersion parameters.
Fusion of feature selection methods for pairwise scoring SVM
Authors: Man-Wai Mak, Sun-Yuan Kung
Venue: Neurocomputing (2008)

It has been recently discovered that stacking the pairwise comparison scores between unknown patterns and a set of known patterns can result in feature vectors with desirable discriminative properties for classification. However, such technique can be hampered by the curse of dimensionality because the vectors size is equal to the training set size. To overcome this problem, this paper investigates various filter and wrapper feature selection techniques for reducing the feature dimension of pairwise scoring matrices and argues that these two types of selection techniques are complementary to each other. Two fusion strategies are then proposed to (1) combine the ranking criteria of filter and wrapper methods at algorithmic level and (2) merge the features selected by the filter and wrapper methods. Evaluations on a subcellular localization benchmark and a microarray dataset demonstrate that feature subsets selected by the fusion methods are either superior to or at least as good as those selected by the individual methods alone for a wide range of feature dimensions.
A Synergy of Planning and Ontology Concept Ranking for Semantic Web Service Composition
Authors: Ourania Hatzi, Georgios Meditskos, Dimitris Vrakas, Nick Bassiliades, Dimosthenis Anagnostopoulos, Ioannis Vlahavas
Venue: Proceedings of the 11th Ibero-American conference on AI: Advances in Artificial Intelligence (2008)

This paper presents a prototype system that exploits planning and an ontology concept ranking algorithm for composing semantic Web services (PORSCE). The system exploits the inferencing capabilities of a Description Logics Reasoner in order to compute the subsumption hierarchy of the ontologies whose concepts are used in the OWL-S Profile descriptions as input and output concepts. The concept ranking algorithm is applied over this hierarchy in order to determine similar concepts based on different degrees of semantic matching relaxation, such as subclass or sibling hierarchical relationships. The domain independent planning system's role is to semantically search the space of possible compositions of Web services, generating plans according to the desirable level of relaxation.
A Novel Solution for Surveillance System Based on Skillful Image Sensor
Authors: Tianding Chen
Venue: Proceedings of the 4th international conference on Intelligent Computing: Advanced Intelligent Computing Theories and Applications - with Aspects of Theoretical and Methodological Issues (2008)

Omni-camera is almost near or even beyond a full hemisphere, it is popularly applied in the fields of visual surveillance, and vision-based robot or autonomous vehicle navigation. The captured omni-directional image should be rectified into a normal perspective-view or panoramic image for convenient human viewing or image-proof preservation. It develops a real-time system to supervise the situation of the indoor environments. This surveillance system combines a panoramic video camera and three active PTZ cameras. We use the omnidirectional video that is caught by panoramic video camera as input to track the moving subjects in an indoor room. We can automatically track the moving subjects or manually find the moving subjects. The coordinate of each subject in the indoor room is estimated in order to direct the attention of one active pan-tilt-zoom camera. When we find the moving subjects automatically or manually, this system can automatically control these PTZ cameras to obtain the high-resolution images and video sequences of moving subjects. Compared with the other kinds of tracking systems, our system can more easily enlarge the monitoring area by adding cameras. The experimental results show that those moving object can be tracked exactly and can be integrated with the guiding system very well.
A Comparison of Different Conceptual Structures Projection Algorithms
Authors: Heather D. Pfeiffer, Roger T. Hartley
Venue: Proceedings of the 15th international conference on Conceptual Structures: Knowledge Architectures for Smart Applications (2007)

Knowledge representation (KR) is used to store and retrieve meaningful data. This data is saved using dynamic data structures that are suitable for the style of KR being implemented. The KR allows the system to manipulate the knowledge in the data by using reasoning operations. The data structure, together with the contents of the transformed knowledge, is known as the knowledge base (KB). An algorithm and the associated data structures make up the reasoning operation, and the performance of this operation is dependent on the KB.In this paper, the basic reasoning operation for a query-answer system, projection, is explored using different theoretical algorithms. Within this discussion, the associated algorithms will be using different KBs for their Conceptual Graph (CG) knowledge representation. The basic projection algorithm defined using the CG representation is looking for a graph morphism of a query graph onto a graph from the KB.The overall running time for the projection operation is known to be a NP class problem; however, by modifying the algorithm, taking into account the associated KB, the actual time needed for discovering and creating the projection/s can be improved. In fact, a new projection algorithm will be defined that, given a typical query onto a carefully defined KB, presents a running time for the actual projection that only grows with the number of projections present.
An overview of conditionals and biconditionals in probability
Authors: Nataniel Greene
Venue: Proceedings of the American Conference on Applied Mathematics (2008)

Conditional and biconditional statements are a standard part of symbolic logic but they have only recently begun to be explored in probability for applications in artificial intelligence. Here we give a brief overview of the major theorems involved and illustrate them using two standard model problems from conditional probability.
CsharpSimpleModule: writing OMNeT++ modules with C# and mono
Authors: Andreas Lagemann, Jörg Nolte
Venue: Proceedings of the 1st international conference on Simulation tools and techniques for communications, networks and systems & workshops (2008)

Simulation normally serves one of two purposes. The first one is evaluation of certain algorithms. The second one is development and test of applications with infrastructural requirements which exceed those commonly available (e.g. distributed applications for wireless networks). In the latter case it is highly desirable that the code used for simulation can be easily adopted to real hardware with minor modifications. The .NET framework is -- like Java -- platform independent insofar as it only depends on a virtual machine implementation for each device it is meant to run on. Therefore for some application fields it is attractive to be able to write plain C# code which can then be run with a simulator like OMNeT++. This paper introduces CsharpSimpleModule, an extension to OMNeT++, which -- like its companion JSimpleModule does for Java -- allows you to write OMNeT++ simulation modules in C# and mix them freely with plain OMNeT++ modules, thus allowing you to build upon existing OMNeT++ frameworks (e.g INET or Mobility Framework). Besides giving a short introduction to the usage of CsharpSimpleModule its general architecture will be illustrated and selected implementation issues will be discussed.
Searching for Messages Conforming to Arbitrary Sets of Conditions in SHA-256
Authors: Marko Hölbl, Christian Rechberger, Tatjana Welzer
Venue: Research in Cryptology: Second Western European Workshop, WEWoRC 2007, Bochum, Germany, July 4-6, 2007, Revised Selected Papers (2008)

Recent progress in hash functions analysis has led to collisions on reduced versions of SHA-256. As in other hash functions, differential collision search methods of SHA-256 can be described by means of conditions on and between state and message bits. We describe a tool for efficient automatic searching of message pairs conforming to useful sets of conditions, i. e. stemming from (interleaved) local collisions. We not only considerably improve upon previous work [7], but also show the extendability of our approach to larger sets of conditions.Furthermore, we present the performance results of an actual implementation and pose an open problem in this context.
Constructing Bayesian networks for criminal profiling from limited data
Authors: K. Baumgartner, S. Ferrari, G. Palermo
Venue: Knowledge-Based Systems (2008)

The increased availability of information technologies has enabled law enforcement agencies to compile databases with detailed information about major felonies. Machine learning techniques can utilize these databases to produce decision-aid tools to support police investigations. This paper presents a methodology for obtaining a Bayesian network (BN) model of offender behavior from a database of cleared homicides. The BN can infer the characteristics of an unknown offender from the crime scene evidence, and help narrow the list of suspects in an unsolved homicide. Our research shows that 80% of offender characteristics are predicted correctly on average in new single-victim homicides, and when confidence levels are taken into account this accuracy increases to 95.6%.
FDI based on pattern recognition using Kalman prediction: Application to an induction machine
Authors: O. Ondel, E. Boutleux, G. Clerc, E. Blanco
Venue: Engineering Applications of Artificial Intelligence (2008)

A pattern recognition technique associated with a new state estimator is developed in order to supervise electrical process. For this purpose, diagnostic features are extracted from current and voltage measurements for monitoring different operating modes. Then, a feature selection method is applied in order to select the most relevant features which define the feature space. In this frame, the classification is realized by a non-parametric method (''k-nearest neighbors'' rule) with reject options. However, this method does not take into account the evolution of the operating modes. Thus, it is necessary to enhance the initial knowledge database. For that, a polynomial approach allows characterizing the intermediate states of each operating modes and an original use of Kalman algorithm allows predicting the evolution of the partially known modes. A simple behavioral model is used to describe the evolution of the pattern vector. An estimation step provides the parameter of such model and a prediction step determines the future evolution of the pattern vector. This approach is illustrated on an asynchronous motor of 5.5kW, in order to detect broken bars under any load level. The experimental results prove the efficiency of pattern recognition methods in condition monitoring of electrical machines.