ppxscal/embedding_network huggingface dataset:
Statistical Analysis of Dynamic Actions
Authors: Lihi Zelnik-Manor Michal Irani
Venue: IEEE Transactions on Pattern Analysis and Machine Intelligence (2006)

Real-world action recognition applications require the development of systems which are fast, can handle a large variety of actions without a priori knowledge of the type of actions, need a minimal number of parameters, and necessitate as short as possible learning stage. In this paper, we suggest such an approach. We regard dynamic activities as long-term temporal objects, which are characterized by spatio-temporal features at multiple temporal scales. Based on this, we design a simple statistical distance measure between video sequences which captures the similarities in their behavioral content. This measure is nonparametric and can thus handle a wide range of complex dynamic actions. Having a behavior-based distance measure between sequences, we use it for a variety of tasks, including: video indexing, temporal segmentation, and action-based video clustering. These tasks are performed without prior knowledge of the types of actions, their models, or their temporal extents.
Automatic Intravital Video Mining of Rolling and Adhering Leukocytes
Authors: Xin C. Anders, Chengcui Zhang, Hong Yuan
Venue: Proceedings of the 5th International Conference on Machine Learning and Applications (2006)

In this paper, we present an automatic spatio-temporal mining system of rolling and adherent leukocytes for intravital videos. The magnitude of leukocyte adhesion and the decrease in rolling velocity are common interests for inflammation response studies. Currently, there is no existing system which is perfect for such purposes. Our approach starts with locating moving leukocytes by probabilistic learning of temporal features. It then removes noises through median and location-based filtering, and finally performs motion correspondence through centroid trackers. By extracting the information about moving leukocytes first, we are able to extract adherent leukocytes in a more robust way with an adaptive threshold method. The effectiveness and the efficiency of the proposed method are demonstrated by the experimental results.
Optimal Filtering for Linear System States over Polynomial Observations
Authors: Michael Basin, Joel Perez
Venue: Proceedings of the First International Conference on Innovative Computing, Information and Control - Volume 1 (2006)

In this paper, the optimal filtering problem for linear system states over polynomial observations is treated proceeding from the general expression for the stochastic Ito differential of the optimal estimate and the error variance. As a result, the Ito differentials for the optimal estimate and error variance corresponding to the stated filtering problem are first derived. The procedure for obtaining a closed system of the filtering equations for a linear state over observations with any polynomial drift is then established. In the example, the obtained optimal filter is applied to solution of the optimal third order sensor filtering problem, assuming a Gaussian initial condition for the third order state. The resulting filter yields a reliable and rapidly converging estimate.
"ONE" a new tool for supply chain network optimization and simulation
Authors: Hongwei Ding, Lyès Benyoucef, Xiaolan Xie, Carl Hans, Jens Schumacher
Venue: Proceedings of the 36th conference on Winter simulation (2004)

Nowadays, in a hotly competitive environment, companies are continuously trying to provide products and/or services to customers faster, cheaper, and better than the competitors do. Managers have learned that they cannot do it alone; rather, they must work on a cooperative basis with other organizations in order to succeed. Although the resulting enterprise networks are more competitive, the tasks for planning, management and optimization are much more difficult and complex. In this paper, we present a newly developed toolbox "ONE" to support decision makers for the assessment, design and improvement of such supply chain networks. The toolbox comprises innovative and user-friendly concepts related to the modeling, simulation and optimization of enterprise networks by additionally taking into account social and environmental impacts as well as uncertainty and risk that are always inherent within modern enterprise networks.
UWB Location and tracking for wireless embedded networks
Authors: Kegen Yu, Jean-philippe Montillet, Alberto Rabbachin, Paul Cheong, Ian Oppermann
Venue: Signal Processing (2006)

In this paper, we investigate the performance of different position estimation methods which make use of time-of-arrival (TOA) of ultra wideband (UWB) signals for low cost/low complexity UWB systems. We first propose a simple and robust two-stage, non-coherent TOA estimation approach. We then explore positioning algorithms utilizing both noniterative and iterative techniques. A review of positioning in distributed networks is also performed and a positioning algorithm is proposed for node location in multi-hop distributed networks. Furthermore, we consider smoothing techniques to improve accuracy when tracking moving objects and we propose the use of sinc functions to smooth the estimate of the mobile position in order to achieve both good accuracy and low complexity. The system modelled and investigated corresponds to an actual test environment in a ski field where skiers are tracked.
Fuzzy Trust for Peer-to-Peer Systems
Authors: Nathan Griffiths, Kuo-Ming Chao, Muhammad Younas
Venue: Proceedings of the 26th IEEE International ConferenceWorkshops on Distributed Computing Systems (2006)

Peer-to-peer (P2P) systems are based upon the cooperative interactions of member peers. Typically, peers are both autonomous and self-interested, meaning that there is no hierarchy of control or power, and that individuals seek to maximise their own goal achievement, rather than acting in a benevolent or socially-oriented manner. Consequently, interaction outcomes are uncertain, since peers can break their commitments or provide sub-standard contributions or services. Thus, when a peer cooperates it is entering into an uncertain interaction, that has an associated risk of failure or reduced performance. For peers to be effective they need some mechanism for managing this risk of failure. In this paper we show how peers can use trust to manage this risk. Our model of trust uses fuzzy logic to allow peers to represent and reason with uncertain and imprecise information regarding others' trustworthiness.
Optimal inspection and economical production quantity strategy for an imperfect production process
Authors: Y.-C. Chen
Venue: International Journal of Systems Science (2006)

This paper considers a problem relating to the integration of production, maintenance, inspection and inventory. The optimal inspection interval, inspection frequency and production quantity were studied, assuming an imperfect production process and a maintenance policy that permits minimal repair, shortages and inspection errors. When the process is in the in-control state, preventive maintenance is performed. If the process is in the out-of-control state, there are two possibilities. The first is a relatively mild production process shift, where minimal repair can bring the process back into the in-control state. The second possibility is a more serious shift, where minimal repair cannot bring the process back into the in-control state. In this case, it will be necessary to halt production and perform repair or replacement. It is accepted that, when a production process is in the out-of-control state, an amount of defective goods will be produced. Within the context of a deteriorating production process system, the advantages of preventive maintenance were explored, using numerical analysis to analyse the impact of inspection errors, permitted shortage conditions and minimal repair on cost.
Encoding of Categories by Noncategory-Specific Neurons in the Inferior Temporal Cortex
Authors: Elizabeth Thomas, Marc M. Van Hulle, Rufin Vogels
Venue: Journal of Cognitive Neuroscience (2001)

In order to understand how the brain codes natural categories, e.g., trees and fish, recordings were made in the anterior part of the macaque inferior temporal (IT) cortex while the animal was performing a tree/nontree categorization task. Most single cells responded to exemplars of more than one category while other neurons responded only to a restricted set of exemplars of a given category. Since it is still not known which type of cells contribute and what is the nature of the code used for categorization in IT, we have performed an analysis on single-cell data. A Kohonen self-organizing map (SOM), which uses an unsupervised (competitive) learning algorithm, was used to study the single cell responses to tree and nontree images. Results from the Kohonen SOM indicated that the collected neuronal data consisting of spike counts was sufficient to account for a good level of categorization success (approximately 83%) when categorizing a group of 200 trees and nontrees. Contrary to intuition, the results of the investigation suggest that the population of category-specific neurons (neurons that respond only to trees or only to nontrees) was unimportant to the categorization. Instead, a large majority of the neurons that were most important to the categorization was found to belong to a class of more broadly tuned cells, namely, cells that responded to both categories but that favored one category over the other by seven or more images. A simple algebraic operation (without the Kohonen SOM) between the above-mentioned noncategory-specific neurons confirmed the contribution of these neurons to categorization. Thus, the modeling results suggest (1) that broadly tuned neurons are critical for categorization, and (2) that only one additional layer of processing is required to extract the categories from a population of IT neurons.
Referential logic of proofs
Authors: Vladimir N. Krupski
Venue: Theoretical Computer Science (2006)

We introduce an extension of the propositional logic of single-conclusion proofs by the second-order variables denoting the reference constructors of the type "the formula which is proved by x." The resulting Logic of Proofs with References, FLPref, is shown to be decidable, and to enjoy soundness and completeness with respect to the intended provability semantics. We show that FLPref provides a complete test of admissibility of inference rules in a sound extension of arithmetic. This paper may be regarded as a contribution to the theory of automated reasoning systems.
Multiclass Multiserver Threshold-Based Systems: A Study of Noninstantaneous Server Activation
Authors: Cheng-Fu Chou
Venue: IEEE Transactions on Parallel and Distributed Systems (2007)

In this paper, we consider performance evaluation of a system which shares K servers (or resources) among N heterogeneous classes of workloads, where server allocation and deallocation for class i is dictated by a class specific threshold-based policy with hysteresis control. In particular, the server activation time for class i is noninstantaneous. There are many systems and applications where a multiclass threshold-based queueing system can be of great use. One important utility of using threshold-based approaches is in situations where applications may incur server usage costs. In these cases, one needs to consider not only the performance aspects but also the resulting cost/performance ratio. The motivation for using hysteresis control is to reduce the unnecessary cost of server setup (or activation) and server removal (or deactivation) whenever there are momentary fluctuations in workload. Moreover, servers in such systems and applications are often needed by multiple classes of workloads and, hence, it is desirable to find good approaches to sharing server resources among the different classes of workloads, preferably without statically partitioning the server pool among these classes. An important and distinguishing characteristic of our work is that we consider the modeling and analysis of a multiclass system with noninstantaneous server activation. The main contributions of this work are 1) in developing an efficient approximation method for solving such models, 2) in verifying the convergence of our iterative method, and 3) in evaluating the resulting accuracy of the technique for computing performance measures of interest, which can subsequently be used in making system design choices.
Tree disagreement: measuring and testing incongruence in phylogenies
Authors: Paul J. Planet
Venue: Journal of Biomedical Informatics (2006)

The branching patterns of phylogenetic trees often disagree even when they have been constructed using different portions of the same data. This phylogenetic discord (incongruence) can be explained by real differences in evolutionary process or history, but also may be due simply to random chance or sampling error. Techniques for measuring and testing the significance of phylogenetic incongruence are used widely in systematic biology, and are necessary when considering genome-scale datasets composed of multiple genes that may or may not have different histories. They are also applicable wherever tree algorithms are used for ordering and interpreting data (e.g., DNA microarrays). Here, I review the different incongruence tests and use them to test the phylogenetic discord of a potentially mobile genetic element (the widespread colonization Island) in the γ-proteobacteria. I then consider how incongruence tests may be used as a starting point for phylogenetic analysis that accounts for horizontal transfer and duplication events as explanations for homoplasy.
Multiple Motor Learning Experiences Enhance Motor Adaptability
Authors: Rachael D. Seidler
Venue: Journal of Cognitive Neuroscience (2004)

Traditional motor learning theory emphasizes that skill learning is specific to the context and task performed. Recent data suggest, however, that subjects exposed to a variety of motor learning paradigms may be able to acquire general, transferable knowledge about skill learning processes. I tested this idea by having subjects learn five different motor tasks, three that were similar to each other and two that were not related. A group of experimental subjects first performed a joystick-aiming task requiring adaptation to three different visuomotor rotations, with a return to the null conditions between each exposure. They then performed the same joystick-aiming task but had to adapt to a change in display gain instead of rotation. Lastly, the subjects used the joystick-aiming task to learn a repeating sequence of movements. Two groups of control subjects performed the same number of trials, but learned only the gain change or the movement sequence. Experimental subjects showed generalization of learning across the three visuomotor rotations. Experimental subjects also exhibited transfer of learning ability to the gain change and the movement sequence, resulting in faster learning than that seen in the control subjects. However, transient perturbations affected the movements of the experimental subjects to a greater extent than those of the control subjects. These data demonstrate that humans can acquire a general enhancement in motor skill learning capacity through experience, but it comes with a cost. Although movement becomes more adaptable following multiple learning experiences, it also becomes less stable to external perturbation.
Building learner's ontologies to assist personalized search of learning objects
Authors: Igor Keleberda, Victoria Repka, Yevgen Biletskiy
Venue: Proceedings of the 8th international conference on Electronic commerce: The new e-commerce: innovations for conquering current barriers, obstacles and limitations to conducting successful business on the internet (2006)

The present work is devoted to building learning object's and learner's ontologies using the OntoClean methodology and IDEF5 method, and mapping the ontologies to OWL. The proposed methodology for building learning object's and learner's ontologies accommodates the IEEE LOM standard. The software tool OnToIDEF5 has been developed for the purpose to implement the proposed approaches for building ontologies. These ontologies have been built to be used to assist the personalized search of learning objects on the Semantic Web.
Co-design of innovations with teachers: definition and dynamics
Authors: Jeremy Roschelle, William R. Penuel
Venue: Proceedings of the 7th international conference on Learning sciences (2006)

Researchers in the learning sciences have explored a collaborative approach to developing innovations that fit into real classroom contexts. Co-design relies on teachers' ongoing involvement with design of educational innovations. To date, investigators have described the application and results of co-design, but have not defined the process nor explored how it plays out over time. In this paper, we define co-design, suggest seven key process components, and use data from interviews to illustrate how dynamic tensions in the process can unfold over time.
Series connected quasi-six-phase two-motor drives with independent control
Authors: Martin Jones, Emil Levi
Venue: Mathematics and Computers in Simulation (2006)

Recent research has shown that it is possible to connect in series stator windings of multi-phase machines and control all the machines in the group independently using vector control principles, although the complete multi-drive system is supplied from a single multi-phase voltage source inverter (VSI). The concept has been investigated so far only for symmetrical n-phase machines (i.e., machines with spatial displacement between any two consecutive phases equal to 2π/n). This paper considers all possible configurations for the asymmetrical six-phase machines, with two three-phase stator windings displaced by 30°. Two possible two-motor configurations are presented. The first one utilises two quasi-six-phase machines while the second one connects in series a quasi-six-phase machine and a two-phase machine. Inverter current control schemes in both the stationary reference frame and the rotating reference frame are considered. Verification of the proposed multi-phase multi-machine drive is provided by simulation and the results are given in the paper.
A New Algorithm for Network Anomaly Detection
Authors: Jun Lv, Xing Li, Congsen Ran, Tong Li
Venue: Proceedings of the International Multi-Conference on Computing in the Global Information Technology (2006)

Abstract In this paper, a new algorithm is suggested to solve the network traffic anomaly detection problem. Wavelet Generalized Likelihood Ratio (WGLR) algorithm, which smartly combines Generalized Likelihood Ratio algorithm and wavelet method, and captures the failure point in real time. Simulating and network traffic experiment has demonstrated that the algorithm has the better performance in fault detection.
LIBRAS Signals Recognition: a study with Learning Vector Quantization and Bit Signature
Authors: Sarajane Marques Peres, Franklin Cesar Flores, Denise Veronez, Carlos Jose Maria Olguin
Venue: Proceedings of the Ninth Brazilian Symposium on Neural Networks (2006)

Learning Vector Quantization is a kind of artificial neural network with a competitive and supervised learning. This technique is commonly used to patterns recognition tasks. This artificial neural network was applied to the LIBRAS signals recognition problem, where the images representation was done with bits signatures. This is an unusual combination form and it seems promising, as inferred by the analysis of the results which are shown in this paper.
The learning with technology profile tool: supporting technology planning for engaged learning
Authors: Randy Knuth, Teresa McMahon
Venue: Proceedings of the 1996 international conference on Learning sciences (1996)

The increasing accessibility of the Internet, advent of high performance technologies, and widespread acknowledgment that technology should play an important role in education are all pressuring schools to develop, implement, and evaluate technology plans. However, planning for technology integration is difficult when most members of the school planning team have little technical experience. More significantly, these individuals typically have limited visions of how to plan for technology because they have not seen many cases of students and teachers using technology in innovative ways that result in engaged learning. Furthermore, school teams lack the tools necessary to make critical assessments about how well the implementation of their plan is resulting in technology-supported engaged learning experiences for their students.
Identifying Tools to Support Schools' Collaborative Teaching and Learning
Authors: Hilary Smith, Joshua Underwood, Geraldine Fitzpatrick, Rose Luckin, Danae Stanton Fraser
Venue: Proceedings of the Second IEEE International Conference on e-Science and Grid Computing (2006)

Integration of e-Science and Grid technologies into curriculum teaching is currently an ambitious aim for teachers and school infrastructures to organise. However, it can expose classroom learners and teachers to a wider community of specialists and interested others, enriching the classroom experience beyond the knowledge of the local teacher. This paper reflects on two practical e-Science projects that utilised mobile hand-held technologies to bring the concepts of collaborative e-Science and the Grid to young scientists. Students engaged in hands-on exploration of their surroundings, and were able to communicate with pollution specialists and with a remote classroom of children who had used similar sensors. Communication and data sharing activities in these sessions exposed a requirement for a suite of tools and technologies not currently accessible to schools. From qualitative analysis of data across these two projects, we present a collection of supporting tools to help achieve this aim and future research direction.
A synchronous collaborative editing system for learning to write
Authors: Yukiko Tanikawa, Hideyuki Suzuki, Hiroshi Kato
Venue: Proceedings of the 1999 conference on Computer support for collaborative learning (1999)

A synchronous editing system for creating a wall newspaper collaboratively by using local area networks has been developed and tested. This educational system is intended to foster writing skills through a collaborative learning process that stimulates intensive interaction among learners who edit the same document. It is designed to encourage the writer's awareness of readers and intensive interaction among learners. It has four characteristics: (1) learners are informed when someone else is following their writing process on their screen; (2) learners can instantly see what other learners are writing and revising; (3) the whole newspaper is always displayed; and (4) learners can see which parts of the newspaper other learners are writing and refer to their editing. The authors conducted experiments with the editing system in an elementary school. And the results indicate that (1) students interacted and collaborated well in the writing process; (2) they revised articles repeatedly through interacting with one another; and (3) the system supported the collaborative writing process.