ppxscal/embedding_network huggingface dataset:
Zonotope/Hyperplane Intersection for Hybrid Systems Reachability Analysis
Authors: Antoine Girard, Colas Guernic
Venue: Proceedings of the 11th international workshop on Hybrid Systems: Computation and Control (2008)

In this paper, we are concerned with the problem of computing the reachable sets of hybrid systems with (possibly high dimensional) linear continuous dynamics and guards defined by switching hyperplanes. For the reachability analysis of the continuous dynamics, we use an efficient approximation algorithm based on zonotopes. In order to use this technique for the analysis of hybrid systems, we must also deal with the discrete transitions in a satisfactory (i.e. scalable and accurate) way. For that purpose, we need to approximate the intersection of the continuous reachable sets with the guards enabling the discrete transitions. The main contribution of this paper is a novel algorithm for computing efficiently a tight over-approximation of the intersection of (possibly high-order) zonotopes with a hyperplane. We show the accuracy and the scalability of our approach by considering two examples of reachability analysis of hybrid systems.
Simultaneous Optimization of ANFIS-Based Fuzzy Model Driven to Data Granulation and Parallel Genetic Algorithms
Authors: Jeoung-Nae Choi, Sung-Kwun Oh, Ki-Sung Seo
Venue: Proceedings of the 4th international symposium on Neural Networks: Advances in Neural Networks, Part III (2007)

The paper concerns the simultaneous optimization for structure and parameters of fuzzy inference systems that is based on Hierarchical Fair Competition-based Parallel Genetic Algorithms (HFCGA) and information data granulation. HFCGA is used to optimize structure and parameters of ANFIS-based fuzzy model simultaneously. The granulation is realized with the aid of the C-means clustering. Through the simultaneous optimization mechanism to be explored, we can find the overall optimal values related to structure as well as parameter identification of ANFIS-based fuzzy model via HFCGA, C-Means clustering and standard least square method. A comparative analysis demon-strates that the proposed algorithm is superior to the conventional methods.
Automatic NE-adapter Generation by Interface Blending/Diagnosis Methods
Authors: Yu Miyoshi, Atsushi Yoshida, Tatsuyuki Kimura, Yoshihiro Otsuka
Venue: Proceedings of the 10th Asia-Pacific Network Operations and Management Symposium on Managing Next Generation Networks and Services (2007)

Operating a next generation network (NGN) while new services and network elements (NE) are being intermittently introduced is a complex and difficult task. We are trying to establish flexible network operation technology. This article introduces a method of automatically generating NE-adapters in element/network management systems (EMS/NMS) to interact with NEs. This method alleviates the effort of NE configuration tasks by automating the development of functions that operators use to set up NEs. We call this interface blending/diagnosis method. Our approach consists of 1) a blending method that automatically generates NE-adapters for products from different vendors from commands and responses between an EMS and an NE and 2) a diagnosis method that verifies blended adapters with actual NEs. Moreover, this article introduces a configuration support tool that we developed. The tool complements the interface blending/diagnosis method even if there is no adapter to be possible to use as knowledge.
The meta-inferences engine: A new tool to manipulate metaknowledge
Authors: Jean-Marc Nigro, Yann Barloy
Venue: Knowledge-Based Systems (2008)

This paper presents the structure and the performance of a new inference engine: the MIE (meta-inference engine). It is able to manipulate not only the rules but also the meta-rules. The article first describes the architecture of the MIE and gives an example to illustrate its use. A comparison of performance between an RETE network and the MIE is then made. This shows that the MIE is more efficient at manipulating metaknowledge (meta-rules) but that an RETE network is quicker when the system inserts or deletes a fact.
Kinetic Modeling Based Probabilistic Segmentation for Molecular Images
Authors: Ahmed Saad, Ghassan Hamarneh, Torsten Möller, Ben Smith
Venue: Proceedings of the 11th international conference on Medical Image Computing and Computer-Assisted Intervention - Part I (2008)

We propose a semi-supervised, kinetic modeling based segmentation technique for molecular imaging applications. It is an iterative, self-learning algorithm based on uncertainty principles, designed to alleviate low signal-to-noise ratio (SNR) and partial volume effect (PVE) problems. Synthetic fluorodeoxyglucose (FDG) and simulated Raclopride dynamic positron emission tomography (dPET) brain images with excessive noise levels are used to validate our algorithm. We show, qualitatively and quantitatively, that our algorithm outperforms state-of-the-art techniques in identifying different functional regions and recovering the kinetic parameters.
Homography Based State Estimation for Aerial Robots
Authors: Jakob Schwendner
Venue: Proceedings of the 31st annual German conference on Advances in Artificial Intelligence (2008)

Low-cost Unmanned Aerial Vehicles have large potential for applications in the civil sector. Cheap inertial sensors alone can not provide the degree of accuracy required for control and navigation of the UAVs. Additional sensors, and sensor fusion techniques are needed to reduce the state estimation error. In the context of this work, the possibility of using visual information to augment the inertial data is investigated. The projected image of the ground plane is processed by a homography constrained optical flow description and used as a measurement update for an EKF. A simulation environment is used, which models the UAV dynamics, the rate-gyro and accelerometer errors as well as a low resolution vision system.
Integration of Fuzzy Logic in Data Mining to Handle Vagueness and Uncertainty
Authors: G. Raju, Binu Thomas, Th. Shanta Kumar, Sangay Thinley
Venue: Proceedings of the 4th international conference on Intelligent Computing: Advanced Intelligent Computing Theories and Applications - with Aspects of Artificial Intelligence (2008)

Recent developments in the fields of business investment, scientific research and information technology have resulted in the collection of massive data which becomes highly useful in finding certain patterns governing the data source. Clustering algorithms are popular in finding hidden patterns and information from such repository of data. The conventional clustering algorithms have difficulties in handling the challenges posed by the collection of natural data which is often vague and uncertain. This paper presents the concept of fuzzy clustering (fuzzy c-means clustering) and shows how it can handle vagueness and uncertainty in comparison with the conventional k-means clustering algorithm.
Road Networks and Their Incomplete Representation by Network Data Models
Authors: Simon Scheider, Werner Kuhn
Venue: Proceedings of the 5th international conference on Geographic Information Science (2008)

Road networks, roads, and junctions are examples of natural language terms whose semantics can be described by affordances of their physical referents. In order to define affordances in such a way that they can be used for classifying and describing instances in a geographic database, one has to deal with the problems of informational incompleteness and limited definability. In this paper, we propose an affordance-based theory of channel networks, based on the work of Hayes [4], as a means to derive necessary conditions for database representations of road networks. By exploring this example, we show that affordance-based logical definitions are a convenient method to capture essential properties of physical objects usually not present in their database representation, but appropriate to explain and define its structure.
Designing an Architecture for Distributed Shared Data on the Grid
Authors: Dacian Tudor, Vladimir Cretu, Wolfgang Schreiner
Venue: Proceedings of the 8th international conference on Algorithms and Architectures for Parallel Processing (2008)

Despite the continuous advances of the last years in grid computing, the grid computing programming paradigms are dominated by the message passing concept. There is little support for other paradigms such as shared data or associative programming. In this paper we analyze some of the existing solutions for grid shared data programming and highlight some of their drawbacks. We propose a new architecture and its core features as well as new evaluation means of its behavior in various scenarios including the next generation grid systems. In addition to the simplicity of our solution, we believe that it would allow us to easily apply further extensions.
Distributed weighted vertex cover via maximal matchings
Authors: Fabrizio Grandoni, Jochen Könemann, Alessandro Panconesi
Venue: ACM Transactions on Algorithms (TALG) (2008)

In this article, we consider the problem of computing a minimum-weight vertex-cover in an n-node, weighted, undirected graph G &equals; (V,E). We present a fully distributed algorithm for computing vertex covers of weight at most twice the optimum, in the case of integer weights. Our algorithm runs in an expected number of O(log n + log &Wcirc;) communication rounds, where &Wcirc; is the average vertex-weight. The previous best algorithm for this problem requires O(log n(log n + log&Wcirc;)) rounds and it is not fully distributed. For a maximal matching M in G, it is a well-known fact that any vertex-cover in G needs to have at least &verbar;M&verbar; vertices. Our algorithm is based on a generalization of this combinatorial lower-bound to the weighted setting.
Predict Molecular Regulatory Network of Norway Rat under the Frame of Data Integration
Authors: Qiguo Rong, Zhe Zhang
Venue: Proceedings of the 4th international conference on Intelligent Computing: Advanced Intelligent Computing Theories and Applications - with Aspects of Artificial Intelligence (2008)

Build rat's molecular regulatory network by integrating five heterogeneous data types that serve as evidence for either protein-protein interaction or protein-DNA interaction. P-values for evidence types are calculated by different algorithms and merged together by Support Vector Machines according to estimated weights which indicate respective contributions of different evidence types to the final prediction. Proper classification threshold is specified to effectively control the false discovery rate, and the result is validated by searching predicted interactions in related databases as well as projecting them to signaling pathways to mark up key factors in disease mechanism. An analysis of our methodology versus previous studies and data integration versus single evidence is performed to demonstrate that the solution we present here is more comprehensive and advantageous than traditional ones due to its rational frame structure and full use of information.
Theoretical Gas Phase Study of the Gauche and Trans Conformers of 1-Bromo-2-Chloroethane and Solvent Effects
Authors: Ponnadurai Ramasami
Venue: Proceedings of the 7th international conference on Computational Science, Part II (2007)

This is a systematic gas phase study of the gauche and trans conformers of 1-bromo-2-chloroethane. The methods used are second order Moller-Plesset theory (MP2) and density functional theory (DFT). The basis set used is 6-311++G(d,p) for all atoms. The functional used for DFT method is B3LYP. G2/MP2 and CCSD(T) calculations have also been carried out using MP2 optimised structure. The results indicate that there is more preference for the trans conformer. The energy difference between the trans and gauche conformers (ΔEtg) and related rotational thermodynamics are reported. The MP2/6- 311++G(d,p) energy difference (ΔEtg) for 1-bromo-2-chloroethane is 7.08 kJ/mol. The conformers of 1-bromo-2-chloroethane have also been subjected to vibrational analysis. This study has also been extended to investigate solvent effects using the Self-Consistent Reaction Field methods. The structures of the conformers are not much affected by the solvents but the energy difference (ΔEtg) decreases with increasing polarity of the solvent. The results from the different theoretical methods are in good agreement.
A Rental Advising System Based on Service Oriented Architecture
Authors: Jie Liang, Yanyin Zhang, Jianguo Lu, Sabiha Sathulla, Ding Chen, Shaohua Wang
Venue: Proceedings of the 2008 IEEE Congress on Services - Part I (2008)

When considering a location to rent a living place, usually, there will be several factors that affect the final decision. Given various degree of importance to each factor, quite often, the result will be different. This paper describes a rental advising system that takes the importance degrees into consideration when ranking the living place, and provide tenants with suggested places that satisfy their requirements under these factors. We proposed a Rental Evaluation Model to evaluate how each predefined factor affects ranking of living place and provide suggestions to the users. The system is created by mashing up several real web services in order to provide the real data. Overall, the system provides users a new experience to search for a living place to rent.
A Socio-technical Approach towards Supporting Intra-organizational Collaboration
Authors: Mario Aehnelt, Mirko Ebert, Günter Beham, Stefanie Lindstaedt, Alexander Paschen
Venue: Proceedings of the 3rd European conference on Technology Enhanced Learning: Times of Convergence: Technologies Across Learning Contexts (2008)

Knowledge work in companies is increasingly carried out by teams of knowledge workers. They interact within and between teams with the common goal to acquire, apply, create and share knowledge. In this paper we propose a socio-technical model to support intra-organizational collaboration which specifically takes into account the social and collaborative nature of knowledge work. Our aim is to support in particular the efficiency of collaborative knowledge work processes through an automated recommendation of collaboration partners and collaboration media. We report on the theoretical as well as practical aspects of such a socio-technical model.
Finding Data Resources in a Virtual Observatory Using SKOS Vocabularies
Authors: Alasdair J. Gray, Norman Gray, Iadh Ounis
Venue: Proceedings of the 25th British national conference on Databases: Sharing Data, Information and Knowledge (2008)

One problem faced by astronomers using the virtual observatory is finding which of the multitude of data resources is relevant for them. The current tool, VOExplorer, relies on matching searches against tags provided by the resources. This paper shows how skos encoded vocabularies can be used to improve the search results. The techniques are general and applicable to any loose collaborations sharing their resources.
SLA e-Negotiations, Enforcement and Management in an Autonomic Environment
Authors: Giannis Koumoutsos, Spyros Denazis, Kleanthis Thramboulidis
Venue: Proceedings of the 3rd IEEE international workshop on Modelling Autonomic Communications Environments (2008)

The process of SLA acquisition, enforcement and management nowadays includes mostly manual, time-consuming processes both on end-users' and ISPs' side. We need to automate processes and enable real e-Negotiations between end-users and ISPs as well as between ISPs. Ontology based information and knowledge modeling involved in SLA e-Negotiation, Enforcement and Management is presented in this paper. Multiple layers of understanding of a complete SLA are presented on the end-users' application based selection, as well as in the ISPs' side through multiple layers of the policy continuum. Dynamic mappings and translation through model based ontology alignment in Knowledge Bases will use this knowledge to automatically configure network elements.
Maintaining Formal Models of Living Guidelines Efficiently
Authors: Andreas Seyfang, Begoña Martínez-Salvador, Radu Serban, Jolanda Wittenberg, Silvia Miksch, Mar Marcos, Annette Teije, Kitty Rosenbrand
Venue: Proceedings of the 11th conference on Artificial Intelligence in Medicine (2007)

Translating clinical guidelines into formal models is beneficial in many ways, but expensive. The progress in medical knowledge requires clinical guidelines to be updated at relatively short intervals, leading to the term living guideline. This causes potentially expensive, frequent updates of the corresponding formal models.When performing these updates, there are two goals: The modelling effort must be minimised and the links between the original document and the formal model must be maintained. In this paper, we describe our solution, using tools and techniques developed during the Protocure II project.
A Multi-method Approach to the Assessment of Web Page Designs
Authors: S. J. Westerman, E. J. Sutherland, L. Robinson, H. Powell, G. Tuck
Venue: Proceedings of the 2nd international conference on Affective Computing and Intelligent Interaction (2007)

This study used self-report, facial EMG, galvanic skin response, and eye tracking to assess users' participants' responses to two charity web sites. For each site, page content and colour of presentation (colour versus black white) were manipulated. Results support the utility and diversity of these measures. Each provided information about users' responses to web page designs, with a good deal of variation in sensitivity to experimental manipulations. In combination the data from these measures allowed further inferences to be drawn, supporting a multi-dimensional view of user experience and the need for multi-method approaches to evaluation.
Ranking and Reputation Systems in the QBF Competition
Authors: Massimo Narizzano, Luca Pulina, Armando Tacchella
Venue: Proceedings of the 10th Congress of the Italian Association for Artificial Intelligence on AI*IA 2007: Artificial Intelligence and Human-Oriented Computing (2007)

Systems competitions play a fundamental role in the advancement of the state of the art in several automated reasoning fields. The goal of such events is to answer the question: "Which system should I buy?". In this paper, we consider voting systems as an alternative to other procedures which are well established in automated reasoning contests. Our research is aimed to compare methods that are customary in the context of social choice, with methods that are targeted to artificial settings, including a new hybrid method that we introduce.
ARISE Machines: Extending Processors with Hybrid Accelerators
Authors: Nikolaos Vassiliadis, George Theodoridis, Spiridon Nikolaidis
Venue: Proceedings of the 4th international workshop on Reconfigurable Computing: Architectures, Tools and Applications (2008)

ARISE introduces a systematic approach to extend once a processor to support thereafter the coupling of an arbitrary number of Custom Computing Units (CCUs). A CCU, hardwired or reconfigurable, can be utilized in a hybrid, tight and/or loose, model of computation. By selecting the appropriate model for each part of the application, the complete application space can be considered for acceleration, resulting to significant performance improvements. To support these features ARISE proposes: i) a machine organization, ii) a set of Instruction Set Extensions (ISEs), and iii) a micro-architecture. To evaluate our proposal, a MIPS processor is extended with the ARISE infrastructure and implemented on an FPGA. Results show that the ARISE infrastructure can easily fit into the timing model of the processor. A set of benchmarks is mapped on the evaluation machine and it is proved that exploiting the hybrid model of computation, performance improvements of up to 68% are achieved compared to the case when only one model is supported. This results to significant application speedups from 2.4x up to 4.8x.
An Efficient n × n Boolean Mapping Using Additive Cellular Automata
Authors: Sourav Das, Dipanwita Roy Chowdhury
Venue: Proceedings of the 8th international conference on Cellular Automata for Reseach and Industry (2008)

The cellular automata (CA) have found its application in diverse fields. But in order to utilize the whole state space of a maximum length CA one has to run 2 n ¿ 1 clock cycles. Using the closure property of a group CA this paper shows how to reach a state which is far from the initial state using very few cycles. It also develops two algorithms to utilize the whole state space of CA using very few cycles. Using these algorithms it creates n ×n pseudo-random boolean mappings having very good statistical properties.
Speech/Music Classification Based on Distributed Evolutionary Fuzzy Logic for Intelligent Audio Coding
Authors: J. E. Muñoz Expósito, N. Ruiz Reyes, S. Garcia Galán, P. Vera Candeas
Venue: Proceedings of the 3rd Iberian conference on Pattern Recognition and Image Analysis, Part II (2007)

Automatic Speech/Music Discrimination (SMD) has become a research topic of interest in the last years. This paper present a new approach for such goal, which is mainly based on a distributed expert system that incorporates fuzzy rules into its knowledge base. The proposed SMD scheme consists of two stages: 1) features extraction, 2) classification of parameters. Classification is performed by cascading a GMM-based classifier with an Evolutionary Fuzzy Expert (EFE) system. The EFE system improves the accuracy rate provided by the GMM-based classifier taking into account information of current and past audio frames. Testing the kindness of new fuzzy rules for the expert system has a high computacional cost. For that reason, a distributed learning approach based on web services has been implemented.
Prediction of Biomechanical Parameters of the Proximal Femur Using Statistical Appearance Models and Support Vector Regression
Authors: Karl Fritscher, Benedikt Schuler, Thomas Link, Felix Eckstein, Norbert Suhm, Markus Hänni, Clemens Hengg, Rainer Schubert
Venue: Proceedings of the 11th international conference on Medical Image Computing and Computer-Assisted Intervention - Part I (2008)

Fractures of the proximal femur are one of the principal causes of mortality among elderly persons. Traditional methods for the determination of femoral fracture risk use methods for measuring bone mineral density. However, BMD alone is not sufficient to predict bone failure load for an individual patient and additional parameters have to be determined for this purpose. In this work an approach that uses statistical models of appearance to identify relevant regions and parameters for the prediction of biomechanical properties of the proximal femur will be presented. By using Support Vector Regression the proposed model based approach is capable of predicting two different biomechanical parameters accurately and fully automatically in two different testing scenarios.