ppxscal/embedding_network huggingface dataset:
Conceptual Changes in Learning Mechanics by Error-based Simulation
Authors: Tomoya Horiguchi, Tsukasa Hirashima, Masahiko Okamoto
Venue: Proceeding of the 2005 conference on Towards Sustainable and Scalable Educational Innovations Informed by the Learning Sciences: Sharing Good Practices of Research, Experimentation and Innovation (2005)

This paper reports on the experiment and its results which was conducted to examine what conceptual changes are caused by using Error-based Simulation (EBS) in learning mechanics. The EBS simulates the motion of mechanical systems based on students' erroneous ideas to promote the awareness and correction of their errors. Ninety undergraduate students learned mechanics by solving problems and also worked on the pre-/post-tests. Two-thirds of them used EBSs and the rest didn't. One-third of them were interviewed about their problem-solving. The results were as follows. First, for novice students, the EBS significantly increased their performance in problem-solving and its effect was much greater than the one of interviews for facilitating students' reflection. Second, the effect of EBS was sufficient in simple problems, but insufficient in more complex problems especially for the correction of errors. Third, the effect of EBS on expert students was unclear in this experiment. Finally, though the effect of EBS on the transfer of learning wasn't clarified sufficiently, it was suggested that the EBS promoted the deeper understanding toward the transfer which was beyond merely providing the explanation of correct solutions. From these results, we concluded the EBS was useful to cause some conceptual change in learning mechanics.
Service Agents Based Collaborative Workflow Management Implementation
Authors: Leo Pudhota, Elizabeth Chang
Venue: Proceeding of the 2005 conference on Self-Organization and Autonomic Informatics (I) (2005)

Workflow management systems in collaborative logistic companies require strong information systems to support in a distributed environment. These IT integration requirements have expanded considerably with the advent of collaborative e-business; utilizing B2B (Business to Business) and P2P (Partner to Partner) e-commerce. This paper deals with adaptation management of collaborative workflow changes in such consortia and proposes architecture for implementation of these changes through the process of component integration and agent based workflow management system where by existing workflow systems adapt to the changes. This paper describes conceptual framework required for prototype implementation resulting in new collaborative workflow adaptation.
Learning statistical inference through computer-supported simulation and data analysis
Authors: Javier Alejandro Corredor
Venue:  (2008)

This dissertation explored the effects of two different interventions on the learning of statistics. Each intervention corresponded to a different conception of statistical learning and used a particular type of computer-tool. One intervention used data analysis tools and focused on authentic situations of statistical activity. The other intervention used simulations and focused on formal aspects of probability. Data Analysis (data) and Probability (chance) are the constituent parts of statistical inference and the two lens from which is possible to present this topic. In this study, both perspectives were compared in their effectiveness to teach ANOVA, a central topic in inferential statistics. The results of this study showed that the intervention that used simulations improved students&rsquo; knowledge about probability, sampling and sample size effects. Protocol analysis of students&rsquo; answers indicated that the gains in probability knowledge did not alter the way students explained group differences. The intervention that used data analysis tools showed no significant effects on students&rsquo; data analysis knowledge. Studying the evolution of a sub sample of students suggested that data analysis knowledge develops over periods of time longer than those of this study. Additionally, protocol analysis of students solving statistical questions showed that students use simple decision rules to evaluate sampling and data analysis problems. These rules allowed students coordinating simple descriptions of the problem&rsquo;s elements with conclusions about significance and sampling effects. 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
An Interlaced Extended Kalman Filter for sensor networks localisation
Authors: A. Gasparri, S. Panzieri F. Pascucci
Venue: International Journal of Sensor Networks (2009)

Sensor networks have become a widely used technology for applications ranging from military surveillance to industrial fault detection. So far, the evolution in micro-electronics has made it possible to build networks of inexpensive nodes characterised by modest computation and storage capability as well as limited battery life. In such a context, having an accurate knowledge about nodes position is fundamental to achieve almost any task. Several techniques to deal with the localisation problem have been proposed in literature: most of them rely on a centralised approach, whereas others work in a distributed fashion. However, a number of approaches do require a prior knowledge of particular nodes, i.e. anchors, whereas others can face the problem without relying on this information. In this paper, a new approach based on an Interlaced Extended Kalman Filter (IEKF) is proposed: the algorithm, working in a distributed fashion, provides an accurate estimation of node poses with a reduced computational complexity. Moreover, no prior knowledge for any nodes is required to produce an estimation in a relative coordinate system. Exhaustive experiments, carried on MICAz nodes, are shown to prove the effectiveness of the proposed IEKF.
Learning optimal ranking with tensor factorization for tag recommendation
Authors: Steffen Rendle, Leandro Balby Marinho, Alexandros Nanopoulos, Lars Schmidt-Thieme
Venue: Proceedings of the 15th ACM SIGKDD international conference on Knowledge discovery and data mining (2009)

Tag recommendation is the task of predicting a personalized list of tags for a user given an item. This is important for many websites with tagging capabilities like last.fm or delicious. In this paper, we propose a method for tag recommendation based on tensor factorization (TF). In contrast to other TF methods like higher order singular value decomposition (HOSVD), our method RTF ('ranking with tensor factorization') directly optimizes the factorization model for the best personalized ranking. RTF handles missing values and learns from pairwise ranking constraints. Our optimization criterion for TF is motivated by a detailed analysis of the problem and of interpretation schemes for the observed data in tagging systems. In all, RTF directly optimizes for the actual problem using a correct interpretation of the data. We provide a gradient descent algorithm to solve our optimization problem. We also provide an improved learning and prediction method with runtime complexity analysis for RTF. The prediction runtime of RTF is independent of the number of observations and only depends on the factorization dimensions. Besides the theoretical analysis, we empirically show that our method outperforms other state-of-the-art tag recommendation methods like FolkRank, PageRank and HOSVD both in quality and prediction runtime.
Atrial Anatomy Influences Onset and Termination of Atrial Fibrillation: A Computer Model Study
Authors: Nico Kuijpers, Huub Eikelder, Sander Verheule
Venue: Proceedings of the 5th International Conference on Functional Imaging and Modeling of the Heart (2009)

Vulnerability to atrial fibrillation (AF) is increased in acutely dilated atria and is related to stretch-activated channels (SACs). To investigate the role of atrial anatomy in AF, we apply a computer model of human atrial electromechanics that includes SACs and contraction of the sarcomeres. Trabecular bundle structures are modeled by varying atrial wall thickness in a triangular mesh representing the human atria. Vulnerability to AF is investigated by application of overall stretch, while stimulating near the pulmonary veins. Due to contraction of some areas, stretch increases in other areas, leading to a variation in effective refractory period (ERP). Onset and perpetuation of AF in our model is explained by an increased dispersion in ERP, conduction slowing, and local conduction block. Atrial contraction attributes to the termination of AF through mechanoelectric feedback. We conclude that onset and termination of AF episodes under stretch are related to atrial structure and mechanoelectric feedback.
Data-driven batch scheduling
Authors: John Bent, Timothy E. Denehy, Miron Livny, Andrea C. Arpaci-Dusseau, Remzi H. Arpaci-Dusseau
Venue: Proceedings of the second international workshop on Data-aware distributed computing (2009)

In this paper, we develop data-driven strategies for batch computing schedulers. Current CPU-centric batch schedulers ignore the data needs within workloads and execute them by linking them transparently and directly to their needed data. When scheduled on remote computational resources, this elegant solution of direct data access can incur an order of magnitude performance penalty for data-intensive workloads. Adding data-awareness to batch schedulers allows a careful coordination of data and CPU allocation thereby reducing the cost of remote execution. We offer here new techniques by which batch schedulers can become data-driven. Such systems can use our analytical predictive models to select one of the four data-driven scheduling policies that we have created. Through simulation, we demonstrate the accuracy of our predictive models and show how they can reduce time to completion for some workloads by as much as 80%.
Hand Posture Subspaces for Dexterous Robotic Grasping
Authors: Matei T. Ciocarlie, Peter K. Allen
Venue: International Journal of Robotics Research (2009)

In this paper we focus on the concept of low-dimensional posture subspaces for artificial hands. We begin by discussing the applicability of a hand configuration subspace to the problem of automated grasp synthesis; our results show that low-dimensional optimization can be instrumental in deriving effective pre-grasp shapes for a number of complex robotic hands. We then show that the computational advantages of using a reduced dimensionality framework enable it to serve as an interface between the human and automated components of an interactive grasping system. We present an on-line grasp planner that allows a human operator to perform dexterous grasping tasks using an artificial hand. In order to achieve the computational rates required for effective user interaction, grasp planning is performed in a hand posture subspace of highly reduced dimensionality. The system also uses real-time input provided by the operator, further simplifying the search for stable grasps to the point where solutions can be found at interactive rates. We demonstrate our approach on a number of different hand models and target objects, in both real and virtual environments.
Adaptive fuzzy control for under-actuated ball and beam system with virtual state following
Authors: Yeong-Hwa Chang, Wei-Shou Chan, Chia-Wen Chang, Chang-Hung Hsu, C. W. Tao
Venue: Proceedings of the 9th WSEAS international conference on Robotics, control and manufacturing technology (2009)

This paper mainly investigates the fuzzy stabilizing control for an under-actuated ball and beam system. In order to achieve the tracking performance of each state, the tracking error between each state variable and the virtual tracking command is minimized. The integrating of the tracking errors is considered as the fuzzy input. In addition, the parameters of the fuzzy controller are optimized with an adaptive mechanism to improve the control performance. The closed-loop stability of the presented control scheme is also analyzed using the Lyapunov theorem. Simulations results indicate that the proposed adaptive fuzzy virtual tracking control scheme can provide better tracking responses than the counterparts of conventional fuzzy controls.
A Constant-Time Algorithm for Finding Neighbors in Quadtrees
Authors: Kunio Aizawa, Shojiro Tanaka
Venue: IEEE Transactions on Pattern Analysis and Machine Intelligence (2009)

Quadtrees and linear quadtrees are well-known hierarchical data structures to represent square images of size 2^{r} \times 2^{r}. Finding the neighbors of a specific leaf node is a fundamental operation for many algorithms that manipulate quadtree data structures. In quadtrees, finding neighbors takes O(r) computational time for the worst case, where r is the resolution (or height) of a given quadtree. Schrack [1] proposed a constant-time algorithm for finding equal-sized neighbors in linear quadtrees. His algorithm calculates the location codes of equal-sized neighbors; it says nothing, however, about their existence. To ensure their existence, additional checking of the location codes is needed, which usually takes O(r) computational time. In this paper, a new algorithm to find the neighbors of a given leaf node in a quadtree is proposed which requires just O(1) (i.e., constant) computational time for the worst case. Moreover, the algorithm takes no notice of the existence or nonexistence of neighbors. Thus, no additional checking is needed. The new algorithm will greatly reduce the computational complexities of almost all algorithms based on quadtrees.
Use of artificial intelligence techniques to fault diagnosis in analog systems
Authors: Jerzy Rutkowski, Damian Grzechca
Venue: Proceedings of the 2nd conference on European computing conference (2008)

Basic concepts of fault diagnosis in analog and mixed (analog and digital) electronic systems by means of the simulation-before-test approach, the so called dictionary approach, have been presented. Special attention has been paid to application of artificial intelligence tools, such as: artificial neural networks, fuzzy sets and evolutionary computing.
Semi-Godunov schemes for multiphase flows in porous media
Authors: K. H. Karlsen, S. Mishra, N. H. Risebro
Venue: Applied Numerical Mathematics (2009)

We describe a class of finite volume schemes for 2x2 systems of conservations laws based on a ''local'' decomposition of the system into a series of single conservation laws but with discontinuous coefficients. The resulting schemes are based on Godunov type solvers of the reduced equations. These schemes are very easy to implement since they do not use detailed information about the eigenstructure of the full system. We illustrate the efficiency of the schemes on a variety of numerical experiments focusing on three-phase flows in porous media and show that they are robust and approximate the flow very well, even in the presence of gravity.
Ontological requirements for analogical, teleological, and hypothetical legal reasoning
Authors: Kevin D. Ashley
Venue: Proceedings of the 12th International Conference on Artificial Intelligence and Law (2009)

In 1993, Berman and Hafner criticized case-based models of legal reasoning for not modeling analogical and teleological elements. Another lesson learned since then is the role of ontologies in representing domain knowledge so that a legal reasoning system can represent and solve problems. If the reasoning involves drawing abstract analogies, reasoning teleologically about rules for deciding a case, and posing hypothetical cases to test decision rules, however, it is not clear what requirements the ontology should satisfy. This paper presents an extended example of such legal reasoning to illustrate what an ontology for case-based legal reasoning should provide. The example centers on a microworld of legal discourse, an ensemble of real legal cases, hypothetical examples, concepts, factors, principles and policies. Beginning with any case in the microworld, the system's goal is to generate arguments that a law professor and students might reasonably make in discussing the legal case in class. The example illustrates three roles the ontology should play in providing representational support for the system, distills the ontological requirements, and suggests an incremental approach to making good on Berman's and Hafner's challenge.
Intelligent dataspaces for e-science
Authors: Ibrahim Elsayed, Adnan Muslimovic, Peter Brezany
Venue: Proceedings of the 7th WSEAS international conference on Computational intelligence, man-machine systems and cybernetics (2008)

This work focuses its effort on dataspaces and workflow management, two complementary technologies, which, if applied in conjunction, can provide a highly efficient and powerful scientific data management solution for e-Infrastructures. Key contributions are: (1) a hierarchical and iterative metamodel providing a life cycle view of scientific data showing what ideally should happen to data in e-Infrastructures is presented generally and by the means of two pilot application. (2) An ontology based dataspace model with strong regard on the key dataspace concept - managing relationships among participants - is developed, providing intelligent creation, representation, and searching of semantically rich relationships among primary and derived data sets in e-Science applications. (3) The concept of dataspaces is extended to support the data life cycle in e-Science experiments. At first, supported by the ontology, an e-Science application independent metamodel is set up, which is then applied to describe application-specific e-Science experiments. This profound knowledge about e-Science life cycles, consolidated within instances of the ontology will highly contribute to the development of high productivity e-Science frameworks.
STAH-TREE: Quality Tests of Hybrid Index for Spatio-Temporal Aggregation
Authors: Marcin Gorawski, Michał Gorawski, Michał Faruga
Venue: Proceeding of the 2008 conference on New Trends in Multimedia and Network Information Systems (2008)

This paper presents a new method for storage and access to spatiotemporal data. That is spatial objects that have some non-spatial attributes updated asynchronously. An example of such objects may be water meters. Proposed method is a hybrid of well documented dedicated solutions for spatial, temporal, spatial aggregate and temporal aggregate data processing. Thanks to that it was possible to achieve high performance for detailed and aggregate query processing without usage of approximation. Index name (i.e. STAH-tree) is English abbreviation and can be extended as Spatio-Temporal Aggregation Hybrid Tree. Part of this work aims in creation of cost model checked against experimental results of system performance. Some other experiments that verify system behavior were also performed.
The musical interface technology design space
Authors: Dan Overholt
Venue: Organised Sound (2009)

This article presents a theoretical framework for the design of expressive musical instruments, the Musical Interface Technology Design Space: MITDS. The activities of imagining, designing and building new musical instruments, performing, composing, and improvising with them, and analysing the whole process in an effort to better understand the interface, our physical and cognitive associations with it, and the relationship between performer, instrument and audience can only be seen as an ongoing iterative work-in-progress. It is long-term evolutionary research, as each generation of a new musical instrument requires inventiveness and years of dedication towards the practice and mastery of its performance system (comprising the interface, synthesis and the mappings between them). Many revisions of the system may be required in order to develop musical interface technologies that enable us to achieve truly expressive performances. The MITDS provides a conceptual framework for describing, analysing, designing and extending the interfaces, mappings, synthesis algorithms and performance techniques for interactive musical instruments. It provides designers with a theoretical base to draw upon when creating technologically advanced performance systems, and can be seen as a set of guidelines for analysis, and a taxonomy of design patterns for interactivity in musical instruments. The MITDS focuses mainly on human-centred design approaches to realtime control of the multidimensional parameter spaces in musical composition and performance, where the primary objective is to close the gap between human gestures and complex synthesis methods.
Research on Mobile Robot's Motion Control and Path Planning
Authors: Shigang Cui, Xuelian Xu, Li Zhao, Liguo Tian, Genghuang Yang
Venue: Proceedings of the 6th International Symposium on Neural Networks: Advances in Neural Networks - Part III (2009)

In this article, the kinematics modeling for the practical robot and movement formula have been established, whose are considered by the feasibility and reliability of actual control, and controls the movement of mobile robot by the planning route, guides the robot to complete the mission. On the other hand, ant colony optimization algorithm is used to solve the robot path planning. Based on the original ant colony optimization algorithm, it modifies the route choice strategy and the pheromone updating strategy etc. according to the information provided by the global map and the mission to complete. And the experimental results on MATLAB are convinced the optimal path.
Effectiveness of WebQuest in the Teaching of STS in Secondary Biology
Authors: Ka-leung Tse, Sai-wing Pun
Venue: Proceeding of the 2006 conference on Learning by Effective Utilization of Technologies: Facilitating Intercultural Understanding (2006)

This paper reports an exploratory case-study (one class of secondary 5 students) investigating the effectiveness of WebQuest in enhancing the teaching of STS in biology through collaborative project work. The results generally support that WebQuest is effective in the teaching of STS in biology by promoting positive attitude towards collaboration, arousing interest in learning and enhancing sophisticated thinking skills.