ppxscal/embedding_network huggingface dataset:
Alice and robotics in introductory CS courses
Authors: Briana Lowe Wellman, James Davis, Monica Anderson
Venue: The Fifth Richard Tapia Celebration of Diversity in Computing Conference: Intellect, Initiatives, Insight, and Innovations (2009)

Statistics for underrepresented minority groups and women continue to show low numbers in enrollment and rates of retention in academic computer science programs. A new approach to increase student interest in computer science in a first year program is introduced. Laboratory modules for an introductory programming course have been developed at the University of Alabama with the goal to increase student motivation and understanding of fundamental programming concepts. The course utilizes robots and Alice, a 3D graphical programming environment. The drag and drop interface of Alice allows students to program real robots using instructions that correspond to statements of programming languages such as Java, C++, and C#. Students gain programming experience that is transferable to upper level courses by engaging in a stimulating and less frustrating environment using Alice interfaced with robots.
Roles: A Four-Dimensional Analysis
Authors: Matthew West
Venue: Proceeding of the 2008 conference on Formal Ontologies Meet Industry (2008)

In ontology the underlying nature of things is sought. Thus it is that the roles things play can sometimes be neglected. Some different sorts of things that get called roles: places in relations, ways of participating in activities, and ways of being a part of a system, are considered. Roles are then analysed from a 4-dimensional and extensional perspective. We find that in individuals a role is a state of some individual that participates in a relationship or an activity, whereas with classes it is the class itself that participate in a place in a relation. In systems (both social and functional roles) we find that roles are replaceable parts of the system that are the purpose the part plays in the whole. A 4-dimensionalist ontology of roles, linked to an upper ontology is presented, and this is used to set out the key properties of roles as found here and by others.
Semi-implicit Krylov deferred correction methods for ordinary differential equations
Authors: Sunyoung Bu, Jingfang Huang, Michael L. Minion
Venue: Proceedings of the 15th american conference on Applied mathematics (2009)

In the recently developed Krylov deferred correction (KDC) methods for ordinary differential equation initial value problems [11], a Picard-type collocation formulation is preconditioned using low-order time integration schemes based on spectral deferred correction (SDC), and the resulting system is solved efficiently using a Newton-Krylov method. Existing analyses show that these KDC methods are super convergent, A-stable, B-stable, symplectic, and symmetric. In this paper, we investigate the efficiency of semi-implicit KDC (SI-KDC) methods for problems which can be decomposed into stiff and non-stiff components. Preliminary analysis and numerical results show that SI-KDC methods display very similar convergence of Newton-Krylov iterations compared with fully-implicit (FI-KDC) methods but can significantly reduce the computational cost in each SDC iteration for the same accuracy requirement for certain problems.
Social search and discovery using a unified approach
Authors: Einat Amitay, David Carmel, Nadav Har'El, Shila Ofek-Koifman, Aya Soffer, Sivan Yogev, Nadav Golbandi
Venue: Proceedings of the 20th ACM conference on Hypertext and hypermedia (2009)

This research explores new ways to augment the search and discovery of relations between Web 2.0 entities using multiple types and sources of social information. Our goal is to allow the search for all object types such as documents, persons and tags, while retrieving related objects of all types. We implemented a social-search engine using a unified approach, where the search space is expanded to represent heterogeneous information objects that are interrelated by several relation types. Our solution is based on multifaceted search, which provides an efficient update mechanism for relations between objects, as well as efficient search over the heterogeneous data. We describe a social search engine positioned within a large enterprise, applied over social data gathered from several Web 2.0 applications. We conducted a large user study with over 600 people to evaluate the contribution of social data for search. Our results demonstrate the high precision of social search results and confirm the strong relationship of users and tags to the topics retrieved.
Gene Sorting in Differential Evolution
Authors: Remi Tassing, Desheng Wang, Yongli Yang, Guangxi Zhu
Venue: Proceedings of the 6th International Symposium on Neural Networks: Advances in Neural Networks - Part III (2009)

Gene sorting is a method proposed in this article that consists of ordering trial vector's component in differential evolution (DE). This method tends to significantly increase the convergence speed of DE with just a little modification on the original algorithm. A benchmark set of 18 functions is used for comparing both algorithms. Most importantly, the proposed methods can be incorporated in other variants of DE to further increase their respective speeds; Iterated Function System Based Adaptive Differential Evolution (IFDE) is used in this paper as a variant example and it is about 5 times faster for 30-dimension problems.
Toward a robot-assisted assessment of the control processes of the motor system
Authors: David Meary, Gabriel Baud-Bovy
Venue: Proceedings of the World Haptics 2009 - Third Joint EuroHaptics conference and Symposium on Haptic Interfaces for Virtual Environment and Teleoperator Systems (2009)

We present a visuo-haptic display and a set of tasks aimed at evaluating upper-limb sensory-motor functions. The visual and force feedbacks were manipulated to assess the functioning of different feedforward and feedback elements of movement control. We report the results of healthy adults who performed these tasks with both hands over two different experimental sessions. Results reproduced known effects related to motor learning and handedness. The whole procedure lasted about 15 minutes per hand so as to be potentially usable with patients in clinic. Such evaluation routine could improve the detection of age- or disease-related changes in motor behavior, and the assessment of the outcomes of rehabilitation methods.
Model-driven architectural monitoring and adaptation for autonomic systems
Authors: Thomas Vogel, Stefan Neumann, Stephan Hildebrandt, Holger Giese, Basil Becker
Venue: Proceedings of the 6th international conference on Autonomic computing (2009)

Architectural monitoring and adaptation allows self-management capabilities of autonomic systems to realize more powerful adaptation steps, which observe and adjust not only parameters but also the software architecture. However, monitoring as well as adaptation of the architecture of a running system in addition to the parameters are considerably more complex and only rather limited and costly solutions are available today. In this paper we propose a model-driven approach to ease the development of architectural monitoring and adaptation for autonomic systems. Using meta models and model transformation techniques, we were able to realize an incremental synchronization between the run-time system and models for different self-management activities. The synchronization might be triggered when needed and therefore the activities can operate concurrently.
Potential of wind energy in sustainable development of resort island in Malaysia: a case study of Pulau Perhentian (Perhentian island)
Authors: Zuhairuse Md. Darus, Nor Atikah Hashim, Siti Nurhidayah Abdul Manan, Mohd Azhar Abdul Rahman, Khairul Nizam Abdul Maulud, Othman Abdul Karim
Venue: Proceedings of the 10th WSEAS international conference on Mathematical methods, computational techniques and intelligent systems (2008)

The world oil crisis in 1970s powerfully illustrated that the concerns over the energy resources which exposed the vulnerability of the energy supply and the over dependence on oil as a fuel for energy. This conditions lead to the necessity for the diversification of energy resources. The government strategies of achieving national energy objectives which among others are diversification of fuel type sources, technology, maximise use of indigenous energy resources and minimizing negative environment impact. The energy efficiency and renewable energy under the Eight Malaysia Plan (2001 - 2005) and Ninth Malaysian Plan (2006 - 2010) focused on targeting for renewable energy to be significant contributor and for better utilization of energy resources. An emphasis to further reduce the dependency on petroleum provides for more effort to integrate alternative source of energy. Aware at the potential of the harvesting the wind energy, Malaysian Government under Joint venture partnership with the State Government of Terengganu and National Electric Board in 2007 embark on the project of integrating power supply at Pulau Perhentian (Perhentian Island). The project consists of installing two wind turbine, solar farm (Solar Panel), Generator and battery. This paper will encompass the potential of wind energy in Malaysia. It will also cover and present a case study of wind energy at system and application at Pulau perhentian.
Stability oriented task-structure based multi-agent replanning
Authors: Li Jin
Venue: Proceedings of The 8th International Conference on Autonomous Agents and Multiagent Systems - Volume 2 (2009)

In this paper, we evaluate the stability of a plan solution at the task level and argue that it is important for task structure based multi-agent replanning. With a plan solution represented by a T&AElig;MS (Task Analysis, Environment Modeling and Simulation) task structure, we define new metrics of the stability of a T&AElig;MS solution and use it to rank and recommend plan candidates. We preliminarily evaluate our approach with a producer-consumer-transporter domain.
Qualitative and Quantitative Student Models
Authors: Jose-Luis Perez-de-la-Cruz, Ricardo Conejo, Eduardo Guzmán
Venue: Proceeding of the 2005 conference on Artificial Intelligence in Education: Supporting Learning through Intelligent and Socially Informed Technology (2005)

This paper is a first attempt to relate quantitative, unidimensional models to the fine-grained models usually found in the AI-ED community. More concretely, we define a certain type of qualitative student models that take into account the strict prerequisite relation, and show how a quantitative model arises from it in a natural way.
Numerical study of hydrogen permeation flux in ytterbium doped strontium cerate and thulium doped strontium cerate (II)
Authors: Maki Matsuka, Roger D. Braddock, Igor E. Agranovski
Venue: Mathematics and Computers in Simulation (2009)

This study analyses the hydrogen permeation flux model with (1) modifications in the defect concentration calculations where the concentration of substitutional cation on cerium site is utilised as the independent variable for the calculation, instead of the previous step-wise calculation with the concentration of oxygen vacancy as the independent variable and (2) the additional terms to include the oxygen partial pressure gradients for calculation of hydrogen permeation flux. The modification in the defect concentration method allows a short model simulation run time, which consequently allows incorporation of the concentration constraints in the parametric sensitivity analysis, but still produces the same set of defect concentrations as calculated in the previous methods. It is also found in this study that the discrepancy between the model and experimental results (in terms of the effect of changes in hydrogen partial pressure gradients on the hydrogen permeation flux) is not due to the influence of oxygen partial pressure gradients. Parametric sensitivity analysis shows that there is no significant difference in the sensitivity of the model by comparing Case A and B. The result of parameter tuning to predict the hydrogen permeation flux for 5% thulium doped strontium cerate in Case B shows a similar trend to the previous study (Case A). These results suggest negligible oxygen ion conductivities in these types of membrane, as reported in the literature.
Generalized quasi-cyclic codes: structural properties and code construction
Authors: M. Esmaeili, S. Yari
Venue: Applicable Algebra in Engineering, Communication and Computing (2009)

Generalized quasi-cyclic (GQC) codes are defined by generator matrices comprised of circulant matrices of lengths not necessarily identical. A decomposition of these codes is given by using the Chinese reminder theorem. The focus is to characterize &#x03c1;-generator GQC codes in details. A good lower bound on the minimum distance of such a code in terms of the minimum distance of the constituent codes is given. Construction methods are given and a set of GQC codes is provided that from minimum distance perspective are optimal codes among the known linear codes having the same length and dimension.
A Nonlinear Master Equation for a Degenerate Diffusion Model of Biofilm Growth
Authors: Hassan Khassehkhan, Thomas Hillen, Hermann J Eberl
Venue: Proceedings of the 9th International Conference on Computational Science: Part I (2009)

We present a continuous time/discrete space model of biofilm growth, starting from the semi-discrete master equation. The probabilities of biomass movement into neighboring sites depend on the local biomass density and on the biomass density in the target site such that spatial movement only takes place if (i) locally not enough space is available to accommodate newly produced biomass and (ii) the target site has capacity to accommodate new biomass. This mimics the rules employed by Cellular Automata models of biofilms. Grid refinement leads formally to a degenerate parabolic equation. We show that a set of transition rules can be found such that a previously studied ad hoc density-dependent diffusion-reaction model of biofilm formation is approximated well. The ACM Portal is published by the Association for Computing Machinery. Copyright © 2010 ACM, Inc. Terms of Usage Privacy Policy Code of Ethics Contact Us Useful downloads: Adobe Acrobat QuickTime Windows Media Player Real Player
Search for Compromise Solutions in Multiobjective State Space Graphs
Authors: Lucie Galand, Patrice Perny
Venue: Proceeding of the 2006 conference on ECAI 2006: 17th European Conference on Artificial Intelligence August 29 -- September 1, 2006, Riva del Garda, Italy (2006)

The aim of this paper is to introduce and solve new search problems in multiobjective state space graphs. Although most of the studies concentrate on the determination of the entire set of Pareto optimal solution paths, the size of which can be, in worst case, exponential in the number of nodes, we consider here more specialized problems where the search is focused on Pareto solutions achieving a well-balanced compromise between the conflicting objectives. After introducing a formal definition of the compromise search problem, we discuss computational issues and the complexity of the problem. Then, we introduce two algorithms to find the best compromise solution-paths in a state space graph. Finally, we report various numerical tests showing that, as far as compromise search is concerned, both algorithms are very efficient (compared to MOA*) but they present contrasted advantages discussed in the conclusion.
A Measure of Disclosure Risk for Tables of Counts
Authors: Duncan Smith, Mark Elliot
Venue: Transactions on Data Privacy (2008)

The paper describes a new method for assessing disclosure risk for tables of counts; the <em>subtraction-attribution probability</em> (SAP) method. The SAP score is the probability of an intruder recovering a.risky. subpopulation table given a quantity of information about the individuals in a population table. The method can be applied to exact or perturbed individual tables and sets of tables. The method can also be used to compare the risk impact of different disclosure control regimes.
Serial and parallel dynamic adaptation of general hybrid meshes
Authors: Eric B. Becker, J. Kallinderis
Venue:  (2008)

The Navier-Stokes equations are a standard mathematical representation of viscous fluid flow. Their numerical solution in three dimensions remains a computationally intensive and challenging task, despite recent advances in computer speed and memory. A strategy to increase accuracy of Navier-Stokes simulations, while maintaining computing resources to a minimum, is local refinement of the associated computational mesh in regions of large solution gradients and coarsening in regions where the solution does not vary appreciably. In this work we consider adaptation of general hybrid meshes for Computational Fluid Dynamics (CFD) applications. Hybrid meshes are composed of four types of elements; hexahedra, prisms, pyramids and tetrahedra, and have been proven a promising technology in accurately resolving fluid flow for complex geometries. The first part of this dissertation is concerned with the design and implementation of a serial scheme for the adaptation of general three dimensional hybrid meshes. We have defined 29 refinement types, for all four kinds of elements. The core of the present adaptation scheme is an iterative algorithm that flags mesh edges for refinement, so that the adapted mesh is conformal. Of primary importance is considered the design of a suitable dynamic data structure that facilitates refinement and coarsening operations and furthermore minimizes memory requirements. A special dynamic list is defined for mesh elements, in contrast with the usual tree structures. It contains only elements of the current adaptation step and minimal information that is utilized to reconstruct parent elements when the mesh is coarsened.In the second part of this work, a new parallel dynamic mesh adaptation and load balancing algorithm for general hybrid meshes is presented. Partitioning of a hybrid mesh reduces to partitioning of the corresponding dual graph. Communication among processors is based on the faces of the interpartition boundary. The distributed termination detection algorithm of Dijkstra is employed for (i) parallel flagging of mesh edges, (ii) global numbering of newly created nodes, and (iii) deletion of nodes after coarsening. An inexpensive dynamic load balancing strategy is employed to redistribute work load among processors after adaptation. In particular, only the initial coarse mesh, with proper weighting, is balanced, which yields savings in computation time and a simple implementation of mesh quality preservation rules, while facilitating coarsening of refined elements. Special algorithms are employed for (i) parallel flow feature detection, (ii) data migration and dynamic updates of local data structures, (iii) determination of the new interpartition boundary and (iv) determination of the communication pattern of processors after load balancing.
Numerical simulation of lid-driven cavity flow using the lattice Boltzmann method
Authors: M. A. Mussa, S. Abdullah, C. S. Nor Azwadi, N. Muhamad, K. Sopian
Venue: Proceedings of the 13th WSEAS international conference on Applied mathematics (2008)

This paper presents the simulation of lid-driven cavity for deep and shallow flow using the lattice Boltzmann method. The effect the Reynolds number on the flow pattern at aspect ratio of 0.25, 0.5, 1.5, 4 was studied extensively. The lattice Boltzmann method is one of the most recent simulation techniques based on molecular theory which is found to be a very efficient numerical tool due to its capability to go deeper into the particle's domain, simulating their interaction among groups of particle and relating the parameters back to macro condition. The comparison of the results was made with CFD software, FLUENT version 6.1. Excellent agreement was obtained even relatively with coarse grids applied on lattice the Boltzmann simulation scheme.
Risk-aware beacon scheduling for tree-based ZigBee/IEEE 802.15.4 wireless networks
Authors: Li-Hsing Yen, Yee Wei Law, Marimuthu Palaniswami
Venue: Proceedings of the 4th Annual International Conference on Wireless Internet (2008)

In a tree-based ZigBee network, ZigBee routers (ZRs) must schedule their beacon transmission times to avoid beacon collisions. The beacon schedule determines packet delivery latency from the end devices to the ZigBee coordinator at the root of the tree. Traditionally, beacon schedules are chosen such that a ZR does not reuse the beacon slots already claimed by its neighbors, or the neighbors of its neighbors. We observe however that beacon slots can be reused judiciously, especially when the risk of beacon collision caused by such reuse is low. The advantage of such reuse is that packet delivery latency can be reduced. We formalize our observation by proposing a node pair classification scheme, that classifies pairs of nodes that are at most two hops apart. Based on this scheme, we can easily assess the risk of slot reuse by a node pair. If the risk is high, slot reuse is disallowed; otherwise, slot reuse is allowed. This forms the essence of our ZigBee-compliant, distributed, risk-aware, probabilistic beacon scheduling algorithm. Simulation results confirm that our algorithm produces a lower latency compared to if a more conventional slot reuse rule is used.
Automatic control based on wasp behavioral model and stochastic learning automata
Authors: Florin Stoica, Dana Simian
Venue: Proceedings of the 10th WSEAS international conference on Mathematical methods, computational techniques and intelligent systems (2008)

A stochastic automaton can perform a finite number of actions in a random environment. When a specific action is performed, the environment responds by producing an environment output that is stochastically related to the action. The aim is to design an automaton, using a reinforcement scheme based on the computational model of wasp behaviour that can determine the best action guided by past actions and environment responses. Using Stochastic Learning Automata techniques, we introduce a decision/control method for intelligent vehicles receiving data from on-board sensors or from the localization system of highway infrastructure.
Large-scale sparse logistic regression
Authors: Jun Liu, Jianhui Chen, Jieping Ye
Venue: Proceedings of the 15th ACM SIGKDD international conference on Knowledge discovery and data mining (2009)

Logistic Regression is a well-known classification method that has been used widely in many applications of data mining, machine learning, computer vision, and bioinformatics. Sparse logistic regression embeds feature selection in the classification framework using the l1-norm regularization, and is attractive in many applications involving high-dimensional data. In this paper, we propose Lassplore for solving large-scale sparse logistic regression. Specifically, we formulate the problem as the l1-ball constrained smooth convex optimization, and propose to solve the problem using the Nesterov's method, an optimal first-order black-box method for smooth convex optimization. One of the critical issues in the use of the Nesterov's method is the estimation of the step size at each of the optimization iterations. Previous approaches either applies the constant step size which assumes that the Lipschitz gradient is known in advance, or requires a sequence of decreasing step size which leads to slow convergence in practice. In this paper, we propose an adaptive line search scheme which allows to tune the step size adaptively and meanwhile guarantees the optimal convergence rate. Empirical comparisons with several state-of-the-art algorithms demonstrate the efficiency of the proposed Lassplore algorithm for large-scale problems.