ppxscal/embedding_network huggingface dataset:
Fast Decoupled Power Flow Using Interval Arithmetic Considering Uncertainty in Power Systems
Authors: Shouxiang Wang, Chengshan Wang, Gaolei Zhang, Ge Zhao
Venue: Proceedings of the 6th International Symposium on Neural Networks: Advances in Neural Networks - Part III (2009)

In order to overcome the weakness of the conventional crisp analysis method, interval arithmetic is used in this paper to represent uncertainty in power sysetems. An interval fast decoupled power flow algorithm, which can be applied in large-scale power system analysis under uncertainty, is proposed. This proposed interval algorithm, taking many kinds of uncertainty into account, uses the Gauss elimination to solve two sets of interval linear equations, i.e. the decoupled P equations and Q equations. And the bounds of power flow results under uncertainty, namely the solution of interval flow equations, are obtained. Monte Carlo method based on fast decoupled power flow is also implemented to verify the validity of the proposed interval algorithm. The proposed mehtod is testified with IEEE 14-node test system and a real large scale power system in North China. The test results illustrate the effectiveness and practical value of the proposed method by comparing with the results of Monte Carlo simulation and traditional crisp method.
Concurrency and parallelism in the computing ontology
Authors: Lillian Cassel, Richard LeBlanc, Andrew McGettrick, Michael Wrinn
Venue: Proceedings of the 14th annual ACM SIGCSE conference on Innovation and technology in computer science education (2009)

This poster will describe ongoing work to modify the Computing Ontology to incorporate issues of parallelism and concurrency, motivated by recent developments in computer hardware design.
Swarm intelligence based energy saving and load balancing in wireless ad hoc networks
Authors: Floriano De Rango, Mauro Tropea
Venue: Proceedings of the 2009 workshop on Bio-inspired algorithms for distributed systems (2009)

Energy saving and traffic load balancing are two important issues that affect the performance of wireless networks, especially MANET. In this work, a novel routing algorithm over MANETs called LBE-ARAMA has been proposed. It allows to discover minimum MDR paths preserving the energy and to balance the data traffic through the Round Trip Time (RTT) delay evaluation on the path from source to destination. This algorithm is based on Swarm Intelligence approach, in particular, ant colony behavior. The proposed algorithm is able to satisfy multiple metrics for a multi-objective optimization like end-to-end delay, load balancing and energy saving. The novelty of our approach is the introduction of a new pheromone updating policy associated with the use of multiple metrics. In order to evaluate the proposed algorithm simulation campaigns have been conducted and a performance comparison with AODV and ARAMA protocols have been carried out through the NS-2 simulator.
New stability criteria for BAM neural networks with time-varying delays
Authors: Liang Hu, Hao Liu, Yingbo Zhao
Venue: Neurocomputing (2009)

In this paper, the exponential stability is investigated for a class of time-delay BAM neural networks (NNs). Time delays of two layers are taken into account separately rather than as a whole with the idea of delay fractioning. Then we generalize the result to time-varying interval delay condition. Exploiting the known constant part of delay sufficiently to estimate the upper bounds, we can derive an improved stability for BAM NNs with time-varying interval delay. Two examples are provided to demonstrate the less conservatism and effectiveness of the proposed linear matrix inequality (LMI) conditions.
Approaching OWL and MDA through Knowledge Management System: Application to project Memory
Authors: Hatem Ben Sta, Khaled Ghedira
Venue: Proceeding of the 2007 conference on New Trends in Software Methodologies, Tools and Techniques: Proceedings of the sixth SoMeT_07 (2007)

The knowledge preservation of design project is an important issue for high technological industry. A general framework for managing knowledge pertaining to design projects is proposed. The objective is to allow preserving relevant information to be used later, thanks to a product design project memory. We introduce a generic platform-independent model that fits requirements of project memory management; this platform is based on UML generic models. We describe the original implementation over object-relational technology in a multi-tier architecture; model transformation based on Model Driven Architecture (MDA) is developed. We present some ontology concepts, three mechanisms for exportation database under Oracle to platform dedicated for representation and exploitation Knowledge, Protégé platform. Finally, we discuss the benefits of ontology engineering for Project Memory management.
A calculation method of the reaction force and moment for a delta-type parallel link robot fixed with a frame
Authors: Jangho Hong, Motoji Yamamoto
Venue: Robotica (2009)

The paper presents a method of reaction force and moment calculation for a 3-RSS pure translational parallel link robot (Delta-type parallel robot), in which the inverse and forward kinematics of the parallel link robot are directly analyzed according to kinematic structure of the parallel robot. For dynamic analysis, the parallel robot is imaginarily parted into three serial ones, and their actual joint torques are determined by the virtual work principle. To obtain the reaction force and moment of the parallel robot acting on the base, which is the composition of the reaction forces and moments of the three serial robots, the Newton–Euler Method is adopted. To show the validity of the presented method, the simulation analysis and experimental results are given, the experimental results tally with the calculation value.
Route kernels for trees
Authors: Fabio Aiolli, Giovanni Da San Martino, Alessandro Sperduti
Venue: Proceedings of the 26th Annual International Conference on Machine Learning (2009)

Almost all tree kernels proposed in the literature match substructures without taking into account their relative positioning with respect to one another. In this paper, we propose a novel family of kernels which explicitly focus on this type of information. Specifically, after defining a family of tree kernels based on routes between nodes, we present an efficient implementation for a member of this family. Experimental results on four different datasets show that our method is able to reach state of the art performances, obtaining in some cases performances better than computationally more demanding tree kernels.
Improving Pseudobagging techniques
Authors: Angela Chieppa, Karina Gibert, Ignasi Gómez-Sebastià, Miquel Sànchez-Marrè
Venue: Proceeding of the 2008 conference on Artificial Intelligence Research and Development: Proceedings of the 11th International Conference of the Catalan Association for Artificial Intelligence (2008)

We present an important improvement related to the computation and use of Mutual Information index in Pseudobagging, a technique that adapts “bagging” to unsupervised context. The Mutual Information index plays a key role in this technique, assessing the quality of a partition. We propose the use of such an index to improve the Pseudobagging voting scheme for determining the final partition of the data. Issues related to the estimation of Mutual Information index in the multivariate continuous case become crucial for the application of Pseudobagging to real data: we discuss some practical approaches to computation in this situation. Finally, experimental results are presented, related to application of new “pooled voting” scheme and to the evaluation of the impact of different computing methods for Mutual Information.
Evaluating advanced search interfaces using established information-seeking models
Authors: Max L. Wilson, M. C. schraefel, Ryen W. White
Venue: Journal of the American Society for Information Science and Technology (2009)

When users have poorly defined or complex goals, search interfaces that offer only keyword-searching facilities provide inadequate support to help them reach their information-seeking objectives. The emergence of interfaces with more advanced capabilities, such as faceted browsing and result clustering, can go some way toward addressing such problems. The evaluation of these interfaces, however, is challenging because they generally offer diverse and versatile search environments that introduce overwhelming amounts of independent variables to user studies; choosing the interface object as the only independent variable in a study would reveal very little about why one design outperforms another. Nonetheless, if we could effectively compare these interfaces, then we would have a way to determine which was best for a given scenario and begin to learn why. In this article, we present a formative inspection framework for the evaluation of advanced search interfaces through the quantification of the strengths and weaknesses of the interfaces in supporting user tactics and varying user conditions. This framework combines established models of users and their needs and behaviors to achieve this. The framework is applied to evaluate three search interfaces and demonstrates the potential value of this approach to interactive information retrieval evaluation. &copy; 2009 Wiley Periodicals, Inc.
Building Agent-Based Appliances with Complementary Methodologies
Authors: Leon Sterling, Kuldar Taveter, The Daedalus Team
Venue: Proceeding of the 2006 conference on Knowledge-Based Software Engineering: Proceedings of the Seventh Joint Conference on Knowledge-Based Software Engineering (2006)

This paper describes a part of the Intelligent Lifestyle project conducted at the University of Melbourne in cooperation with our industrial partner Adacel Technologies in 2004. The Intelligent Lifecycle project aimed to design and build a system of intelligent agent-based appliances. It further aimed to demonstrate that agent development methods were suitable for wide acceptance by software developers with object-oriented but no agent-oriented experience. In this paper we describe how initial requirements engineering activities undertaken using the ROADMAP methodology can be complemented by rapid prototyping performed by using the RAP/AOR methodology. Overall, this paper defines and explains the first two stages of a systematic approach for achieving systems of intelligent agents.
Knowledge-base representation and reasoning for the autonomic management of pervasive healthcare
Authors: Eleftheria Katsiri
Venue: Proceeding of the 2008 conference on Knowledge-Based Software Engineering: Proceedings of the Eighth Joint Conference on Knowledge-Based Software Engineering (2008)

Two recent programming paradigms, Body Area Networks (BAN) and Body Sensor Networks (BSNs) interact with a ubiquitous computing environment in order to monitor the health and well being of patients in hospitals or at home. Previous work in DSE, Imperial College, discusses the Self Managed Cell (SMC), as the basic architectural pattern of self-configuring and self-managing BAN networks. Devices in BANs become autonomic, by specifying their behavior reactively, in terms of the Ponder2 policy language. As a result, such networks require very little or no user input in order to adapt autonomously to changes in the users' environment, resulting from user activity, device failure, and the addition or loss of services. Body Sensor Networks (BSN) are the next generation pervasive monitoring systems and are significantly lower-scale than BANs. BSN consist of very small nodes with limited computational memory and power resources that are not currently programmable in a reactive (rule-based) manner. This means that the SMC model cannot be applied directly to Body Sensor Networks; a new knowledge representation and reasoning model is needed to program such devices. This paper discusses the design decisions we took the design and implementation of an embedded policy interpreter (EPI) for autonomous BSN nodes.
Automatic congestion detection and visualization using networked GPS unit data
Authors: Benjamin Bishop, Joseph Casabona
Venue: Proceedings of the 47th Annual Southeast Regional Conference (2009)

The goal of this work is to explore systems for the automatic determination of vehicle traffic congestion using GPS-enabled networked mobile phones. A location based data set is collected and analyzed. Additionally, sample filtering and route matching approaches are considered.
Multi-slot semantics for natural-language call routing systems
Authors: Johan Boye, Mats Wirén
Venue: Proceedings of the Workshop on Bridging the Gap: Academic and Industrial Research in Dialog Technologies (2007)

Statistical classification techniques for natural-language call routing systems have matured to the point where it is possible to distinguish between several hundreds of semantic categories with an accuracy that is sufficient for commercial deployments. For category sets of this size, the problem of maintaining consistency among manually tagged utterances becomes limiting, as lack of consistency in the training data will degrade performance of the classifier. It is thus essential that the set of categories be structured in a way that alleviates this problem, and enables consistency to be preserved as the domain keeps changing. In this paper, we describe our experiences of using a two-level multi-slot semantics as a way of meeting this problem. Furthermore, we explore the ramifications of the approach with respect to classification, evaluation and dialogue design for call routing systems.
Apple Training Series: Mac OS X Server Essentials, 2nd edition
Authors: Schoun Regan, David Pugh
Venue:  (2008)

The only Apple-certified book on Mac OS X 10.5 Leopard, this comprehensive reference takes support technicians and ardent Mac users deep inside their operating systems, covering everything from networking technologies to system administration, customizing the operating system, command-line programming, and more. Keyed to the learning objectives of the AppleCertified Technical Coordinator certification exam, the lessons in this self-paced volume serve as a perfect supplement to Apples own training class and a first-rate primer for computer support personnel who need to troubleshoot and optimize Mac OS X as part of their jobs. Self-quizzes and chapter tests reinforce the knowledge gained along the way.
Monotonicity and error bounds for networks of Erlang loss queues
Authors: Richard J. Boucherie, Nico M. Dijk
Venue: Queueing Systems: Theory and Applications (2009)

Networks of Erlang loss queues naturally arise when modelling finite communication systems without delays, among which, most notably are classical circuit switch telephone networks (loss networks) and present-day wireless mobile networks. Performance measures of interest such as loss probabilities or throughputs can be obtained from the steady state distribution. However, while this steady state distribution has a closed product form expression in the first case (loss networks), it does not have one in the second case due to blocked (and lost) handovers. Product form approximations are therefore suggested. These approximations are obtained by a combined modification of both the state space (by a hypercubic expansion) and the transition rates (by extra redial rates). It will be shown that these product form approximations lead to upper bounds for loss probabilities and analytic error bounds for the accuracy of the approximation for various performance measures. The proofs of these results rely upon both monotonicity results and an analytic error bound method as based on Markov reward theory. This combination and its technicalities are of interest by themselves. The technical conditions are worked out and verified for two specific applications: pure loss networks as under (i) GSM networks with fixed channel allocation as under (ii). The results are of practical interest for computational simplifications and, particularly, to guarantee that blocking probabilities do not exceed a given threshold such as for network dimensioning.
Secure system for sharing multilevel security documents in groups
Authors: C. Dianne Martin, Sead Muftic
Venue:  (2008)

In modern distributed computing environments the demand for applications that provide secure sharing of documents and sensitive data is exponentially growing. Highly valuable documents created every day need to be securely shared between, and updated by, the authorized users. One of the security challenges is to protect these documents at different authorization levels in cryptographic group environments. In this work we provide a solution for protecting documents whose contents have varying sensitivity levels to be viewed by users with varying clearance levels. Our security system facilitates the process of structuring and enforcing security constraints, applicable to both, inside documents for individual sections and also outside, to the entire documents. Our system is using a range of technologies such as Open Office, XML, XACML, and group key management protocols. In our system, we provide a comprehensive access control system that, in addition to protecting documents and their internal content, it protects access control policies themselves from unauthorized access. Current protocols for distribution of group messages and group keys require group members to be online in order to receive re-key and group management messages. These are very restrictive protocols both for scheduling and distribution of group keys, as well as for deployment by secure group applications such as long-term sharing of protected documents, but they are suitable for on-line exchange of short messages within groups. In this work we redefined group membership by introducing two membership states: on-line and off-line, and two group memberships: group membership and session membership. Group membership is used to identify group members, which means that it is used for registration purposes. Session membership is used for communication purposes because it identifies the subset of group members who can participate in the group communication at any time. Using our new group membership concept, we introduce the new features of secure group communication systems, i.e. the possibility to archive group messages, as well as group keys. This provides the possibility for delayed verification of messages, as well as continuous membership in a group, even after leaving the session.
High Frequency Assessment from Multiresolution Analysis
Authors: Tássio Knop Castro, Eder Almeida Perez, Virgínia Fernandes Mota, Alexandre Chapiro, Marcelo Bernardes Vieira, Wilhelm Passarella Freire
Venue: Proceedings of the 9th International Conference on Computational Science: Part I (2009)

We propose a method for the assessment and visualization of high frequency regions of a multiresolution image. We combine both orientation tensor and multiresolution analysis to give a scalar descriptor of high frequency regions. High values of this scalar space indicate regions having coincident detail vectors in multiple scales of a wavelet decomposition. This is useful for finding edges, textures, collinear structures and salient regions for computer vision methods. The image is decomposed into several scales using the Discrete Wavelet Transform (DWT). The resulting detail spaces form vectors indicating intensity variations which are combined using orientation tensors. A high frequency scalar descriptor is then obtained from the resulting tensor for each original image pixel. Our results show that this descriptor indicates areas having relevant intensity variation in multiple scales.
A computational unification of cognitive control, emotion, and learning
Authors: John E. Laird, Richard L. Lewis
Venue:  (2008)

Existing models that integrate emotion and cognition generally do not fully specify why cognition needs emotion and conversely why emotion needs cognition. In this thesis, we present a unified computational model that combines an abstract cognitive theory of behavior control (PEACTIDM) and a detailed theory of emotion (based on an appraisal theory), integrated in a theory of cognitive architecture (Soar). The theory of cognitive control specifies a set of required computational functions and their abstract inputs and outputs, while the appraisal theory specifies in more detail the nature of these inputs and outputs and an ontology for their representation. We argue that there is a surprising functional symbiosis between these two independently motivated theories that leads to a deeper theoretical integration than has been previously obtained in other computational treatments of cognition and emotion. We use an implemented model in Soar to test the feasibility of the resulting integrated theory, and explore its implications and predictive power in several task domains. With this integration, we then explore a possible functional benefit of emotion; namely, as an intrinsic motivator of reinforcement learning. This integration leads to other reinforcement learning extensions, such as automatic setting of the learning and exploration rate parameters.
Semantic predicate types and approximation for class-based object oriented programming
Authors: Steffen van Bakel, Reuben N. S. Rowe
Venue: Proceedings of the 11th International Workshop on Formal Techniques for Java-like Programs (2009)

We apply the principles of the intersection type discipline to the study of class-based object oriented programs and; our work follows from a similar approach (in the context of Abadi and Cardelli's &sigmaf;-object calculus) taken by van Bakel and de'Liguoro. We define an extension of Featherweight Java, pFJ, and present a predicate system which we show to be sound and expressive. We also show that our system provides a semantic underpinning for the object oriented paradigm by generalising the concept of approximant from the Lambda Calculus and demonstrating an approximation result: all expressions to which we can assign a predicate have an approximant that satisfies the same predicate. Crucial to this result is the notion of predicate language, which associates a family of predicates with a class.
Using social data as context for making recommendations: an ontology based approach
Authors: Salma Noor, Kirk Martinez
Venue: Proceedings of the 1st Workshop on Context, Information and Ontologies (2009)

Web-based knowledge systems support an impressive and growing amount of information. Among the difficulties faced by these systems is the problem of overwhelming the user with a vast amount of data, often referred to as information overload. The problem has escalated with the ever increasing issues of time constraints and the extensive use of handheld devices. The use of context is one possible way out helping with this situation. To provide a more robust approach to context gathering we propose the use of Social Web technologies alongside the Semantic Web. As the social web is heavily used it could provide a better understanding of a user's interests and intentions. The proposed system gathers information about users from their social web identities and enriches it with ontological knowledge. Thus an interest model for the user can be created which can serve as a good source of contextual knowledge. This work bridges the gap between the user and system searches by analyzing the virtual existence of a user and making interesting recommendations accordingly.