ppxscal/embedding_network huggingface dataset:
An Approximation to Mean-Shift via Swarm Intelligence
Authors: M. Thomas, C. Kambhamettu
Venue: Proceedings of the 18th IEEE International Conference on Tools with Artificial Intelligence (2006)

Mean shift based feature space analysis has been shown to be an elegant, accurate and robust technique. The elegance in this non-parametric algorithm is mainly due to its simplicity in performing gradient ascent to estimate the modes in a multidimensional data. One characteristic aspect of mean shift is that the mode estimation is performed at each data point. Since it is important to describe the data in as succinct manner as possible, it is important to focus on modal points in the data instead of every data point. In this paper, we attempt to tackle the mean shift problem through a "mode centric" approach using swarm intelligence. Here, the mode estimation is cast as a problem of goal seeking for the swarm as it moves through the multidimensional data space. Local maxima/minima and plateaus are avoided through information exchange between each member of the swarm, thereby converging at the mode values efficiently.
Using Technology to Support Self-Regulation in University Writing
Authors: Tracey L. Leacock, Philip H. Winne, Vive Kumar, Jurika Shakya
Venue: Proceedings of the Sixth IEEE International Conference on Advanced Learning Technologies (2006)

This paper describes an integrated writing support system that includes diagnostic tests, online scaffolding, computer-based coaching, and peer collaboration and feedback tools. The system has been tailored to improve students' self-regulation skills in the domain of writing and to foster their understanding of writing as means for negotiating shared understandings.
On the efficiency of fluid simulation of networks
Authors: Daniel R. Figueiredo, Benyuan Liu, Yang Guo, Jim Kurose, Don Towsley
Venue: Computer Networks: The International Journal of Computer and Telecommunications Networking (2006)

Performance evaluation of computer networks through tratitional packet-level simulation is becoming increasingly difficult as networks grow in size along different dimensions. Due to its higher level of abstraction, fluid simulation is a promising approach for evaluating large-scale network models. In this paper we focus on evaluating and comparing the computaional effort required for fluid-and packet-level simulation. To measure the computaional effort required by a simulation approach, we introduce the concept of "simulation event rate", a measure that is both analytically tractable and adequate. We identify the fundamental factors that contribute to the simulation event rate in fluid- and packet-level simulations and provide an analytical characterization of the simulation event rate for specific network models. Among such factors, we identify the "ripple effect" as a significant contributor to the computational effort required by fluid simulation. We also show that the parameter space of a given network model can be divided into different regions where one simulation technique is more efficient than the other. In particular, we consider a realistic large-scale network and demonstrate how the computational effort depends on simulation parameters. Finally, we show that flow aggregation can effectively reduce the impact of the ripple effect and that the ripple effect has less impact when simulating the WFQ scheduling policy.
SOFIA's Challenge: Automated Scheduling of Airborne Astronomy Observations
Authors: Jeremy Frank
Venue: Proceedings of the 2nd IEEE International Conference on Space Mission Challenges for Information Technology (2006)

The Stratospheric Observatory for Infrared Astronomy (SOFIA) will require scheduling flights in support of observations proposed by many different investigators. Automation will be crucial to enable efficient and effective scheduling of SOFIA flights. We have designed an Automated Flight Planner (AFP) that accepts as input a set of requested observations, designated flight days, weather predictions and fuel limitations, and searches automatically for highquality flight plans that satisfy all relevant aircraft and astronomer specified constraints. The AFP can generate one week's worth of flights in tens of minutes of computation time, a feat beyond the capabilities of human flight planners. The rate at which the AFP can generate flights enables a small staff to assess and analyze complex tradeoffs between fuel consumption, estimated science quality and the percentage of scheduled observations.
LinkClus: efficient clustering via heterogeneous semantic links
Authors: Xiaoxin Yin, Jiawei Han, Philip S. Yu
Venue: Proceedings of the 32nd international conference on Very large data bases (2006)

Data objects in a relational database are cross-linked with each other via multi-typed links. Links contain rich semantic information that may indicate important relationships among objects. Most current clustering methods rely only on the properties that belong to the objects per se. However, the similarities between objects are often indicated by the links, and desirable clusters cannot be generated using only the properties of objects.In this paper we explore linkage-based clustering, in which the similarity between two objects is measured based on the similarities between the objects linked with them. In comparison with a previous study (SimRank) that computes links recursively on all pairs of objects, we take advantage of the power law distribution of links, and develop a hierarchical structure called SimTree to represent similarities in multi-granularity manner. This method avoids the high cost of computing and storing pairwise similarities but still thoroughly explore relationships among objects. An efficient algorithm is proposed to compute similarities between objects by avoiding pairwise similarity computations through merging computations that go through the same branches in the SimTree. Experiments show the proposed approach achieves high efficiency, scalability, and accuracy in clustering multi-typed linked objects.
Methodology to optimize the cost/performance of disk subsystems
Authors: R. Recio
Venue: Proceedings of the 2000 IEEE International Symposium on Performance Analysis of Systems and Software (2000)

The storage hierarchy plays a major role in the price and performance of high-end enterprise servers. In fact, the total price of a high-end server's hardware is dominated by its memory and disk configuration. Similarly, the performance is significantly influenced by the design and configuration of the server's memory and disk subsystems. Given these realities, the design and development of future server systems requires special attention to the storage subsystem. The paper describes a methodology that can be applied to optimize the disk size and RAID type used in key high-end server workloads.
Multiple Fiducial Identification Using the Hidden Markov Model in Image Guided Radiosurgery
Authors: Zhiping Mu, Dongshan Fu, Gopinath Kuduvalli
Venue: Proceedings of the 2006 Conference on Computer Vision and Pattern Recognition Workshop (2006)

A multi-fiducial identification method for image guided radiotherapy and radiosurgery is presented. A modified hidden Markov model is adopted to incorporate context information. A novel algorithm, modified from the Viterbi algorithm, is introduced to identify fiducials concurrently in two orthogonal projections. This method is robust and efficient, requires a small number of control parameters, exhibits large search range, and can accommodate deformations. A simple implementation is presented as an example to verify the efficacy of the framework. Experiments were carried out using clinical images acquired during patient treatments, and very promising results were achieved and reported in the paper. The algorithm successfully identified fiducials even in very difficult cases, demonstrating the effectiveness and robustness of the proposed probabilistic framework and the concurrent search algorithm.
Mining top-K frequent itemsets from data streams
Authors: Raymond Chi-Wing Wong, Ada Wai-Chee Fu
Venue: Data Mining and Knowledge Discovery (2006)

Frequent pattern mining on data streams is of interest recently. However, it is not easy for users to determine a proper frequency threshold. It is more reasonable to ask users to set a bound on the result size. We study the problem of mining top K frequent itemsets in data streams. We introduce a method based on the Chernoff bound with a guarantee of the output quality and also a bound on the memory usage. We also propose an algorithm based on the Lossy Counting Algorithm. In most of the experiments of the two proposed algorithms, we obtain perfect solutions and the memory space occupied by our algorithms is very small. Besides, we also propose the adapted approach of these two algorithms in order to handle the case when we are interested in mining the data in a sliding window. The experiments show that the results are accurate.
Simulator sickness in virtual display gaming: a comparison of stereoscopic and non-stereoscopic situations
Authors: Jukka Häkkinen, Monika Pölönen, Jari Takatalo, Göte Nyman
Venue: Proceedings of the 8th conference on Human-computer interaction with mobile devices and services (2006)

In this paper we compare simulator sickness symptoms produced by racing game in three different conditions. In the first experiment the participants played the Need for Speed car racing game with an ordinary 17" display and in the second and third experiments they used a head-worn virtual display for the game playing. The difference between experiments 2 and 3 was in the use of stereoscopy, as in the third experiment the car racing game was seen in stereoscopic three-dimensions. Our results indicated that there were no significant differences in sickness symptoms when we compared the ordinary display and the virtual display in non-stereoscopic mode. In stereoscopic condition the eye strain and disorientation symptoms were significantly elevated compared to the ordinary display. We conclude that using a virtual display as an accessory in a mobile device is a viable alternative, because the non-stereoscopic virtual display did not produce significantly more sickness symptoms compared to ordinary game playing.
Deploying Approaches for Pattern Refinement in Text Mining
Authors: Sheng-Tang Wu, Yuefeng Li, Yue Xu
Venue: Proceedings of the Sixth International Conference on Data Mining (2006)

Text mining is the technique that helps users find useful information from a large amount of digital text documents on the Web or databases. Instead of the keyword-based approach which is typically used in this field, the pattern-based model containing frequent sequential patterns is employed to perform the same concept of tasks. However, how to effectively use these discovered patterns is still a big challenge. In this study, we propose two approaches based on the use of pattern deploying strategies. The performance of the pattern deploying algorithms for text mining is investigated on the Reuters dataset RCV1 and the results show that the effectiveness is improved by using our proposed pattern refinement approaches.
Design of a Gain-Scheduling Anti-Swing Controller for Tower Cranes Using Fuzzy Clustering Techniques
Authors: N. Sadati, A. Hooshmand
Venue: Proceedings of the International Conference on Computational Inteligence for Modelling Control and Automation and International Conference on Intelligent Agents Web Technologies and International Commerce (2006)

The main objective of this paper is to design a fast, non-expensive and practical controller for tower cranes. The controllers are designed to transfer the loads from point to point, as fast as possible, and at the same time the load swing is kept small during the transfer process. Moreover, variations of the system parameters such as cable length are taken into consideration. It is shown how the state feedback controllers along with the gain scheduling could be used for a time varying linear model with varying parameters. For this reason, linear controllers are designed for a number of operating points, where their parameters are interpolated for conditions in between. In this way, a globally nonlinear controller is obtained. However, the selection of the operating points and the design of the interpolation scheme remains a time-consuming procedure. In order to reduce the design efforts, an automated procedure for determination of the number of operating points and their locations using fuzzy clustering have been proposed. This approach also provides the interpolation mechanism, using membership functions, for the local controller parameters.
Image Retrieval of Songket Motifs Using Simple Shape Descriptors
Authors: Nursuriati Jamil, Zainab Abu Bakar, Tengku Mohd Tengku Sembok
Venue: Proceedings of the conference on Geometric Modeling and Imaging: New Trends (2006)

Songket is a traditional handwoven cloth of the Malays and its beauty lies on the design of the songket motifs intricately woven on the cloth. Even though color is a feature of the motif, shape is more important in determining the type of the motifs. This paper describes and tests the efficiency of retrieving songket motifs images using different combination of five geometric shape descriptors. Even though there are many existing approaches of shape-based image retrievals, the goal of this paper is to take advantage of the faster calculations of the geometric shape descriptors to retrieve the images. Fifty selected songket motifs are used as sample queries in this paper. Similarities of these images are measured using Euclidean distance and performance of the retrieval effectiveness is evaluated using recall and precision rate. Results of the experiment showed that geometric shape descriptors are effective in retrieving the songket motifs.
Using simulation for economic policy analysis in the global agricultural suppy chain
Authors: James N. Barnes, Nicholas G. Kalaitzandonakes, Thomas J. Crowe
Venue: Proceedings of the 37th conference on Winter simulation (2005)

The purpose of this paper is to demonstrate how discrete dynamic simulation can be used to measure the impact regulation has on business processes and therefore operational-contractual costs in global agricultural supply chains. In particular, we examine how regulation of genetically modified organisms (GMOs) in the European Union (EU) affects the cost of contracting for soybean supplies between farmers and grain elevator firms in the U.S. Using a simulation model of business processes at a grain elevator operation, we examine how sensitive contract costs are to changes in a purity threshold for non-GMO content set by EU regulation. Results indicate elevator business processes are extremely sensitive to changes in non-GMO thresholds. Even at small changes in purity, contracting costs varied between $0.04--0.09 cents per bushel. The implication is regulation of GMOs might protect EU consumer rights, but protection may be costly and borne by agribusinesses in the U.S. agricultural supply chain.
Shrinked Data Marts Enabled for Negative Caching
Authors: Maik Thiele, Wolfgang Lehner
Venue: Proceedings of the 10th International Database Engineering and Applications Symposium (2006)

Data marts storing pre-aggregated data, prepared for further roll-ups, play an essential role in data warehouse environments and lead to significant performance gains in the query evaluation. However, in order to ensure the completeness of query results on the data mart without to access the underlying data warehouse, null values need to be stored explicitly; this process is denoted as negative caching. Such null values typically occur in multidimensional data sets, which are naturally very sparse. To our knowledge, there is no work on shrinking the null tuples in a multi-dimensional data set within ROLAP. For these tuples, we propose a lossless compression technique, leading to a dramatic reduction in size of the data mart. Queries depending on null value information can be answered with 100% precision by partially inflating the shrunken data mart. We complement our analytical approach with an experimental evaluation using real and synthetic data sets, and demonstrate our results.
Synchronized Control of Dual Linear Motors Position Servo System Based on Fuzzy Self-Learning Compensation
Authors: Dongmei Yu, Qingding Guo, Qing Hu
Venue: Proceedings of the First International Conference on Innovative Computing, Information and Control - Volume 1 (2006)

This paper introduces the position synchronized control strategy that meets position tracking performance and the closed loop robustness to external disturbance in dual linear motors servo system. In order to achieve the desired dynamic synchronized performance for dual position servo axes in machining, the same position feedback controller is used to single linear motor position servo axis independently, and an electrical cross-coupled control algorithms based on fuzzy self-learning are applied to dual linear motor position servo system. The simulation results show that proposed method is effective on improving synchronized performance.
Probing the Use and Value of Video for Multi-Disciplinary Medical Teams in Teleconference
Authors: Bridget Kane, Saturnino Luz
Venue: Proceedings of the 19th IEEE Symposium on Computer-Based Medical Systems (2006)

Face-to-face interactions, via teleconferencing link, are investigated for multidisciplinary medical team (MDT) meetings. Comparison is made between colocated MDT meetings and those held in teleconference. Attitudes towards video changed positively, over a period of 8 months, following participants' experience of teleconferencing. Analysis of display screen use reveals 60% of case discussion time was time spent in face-to-face view with remote sites, contrary to expressed views of its relative unimportance. The value of the video link in MDT meetings, held in teleconference, is found to have higher than expected value.
Instantaneous spectral estimation of nonstationary signals
Authors: Y. Takizawa, K. Oda, A. Fukasawa
Venue: Proceedings of the Acoustics, Speech, and Signal Processing,1994. on IEEE International Conference - Volume 04 (1994)

In this paper, new methods are proposed to estimate a nonstationary spectrum based on the covariance method (COV) and maximum entropy method (MEM). First, their evaluation functions are improved by an instantaneous expression. Secondly, the 2-D spectrum is defined as the spectrum frequency of the variation of the conventional spectrum, and band-limitation is achieved on the 2-D spectrum. The instantaneous covariance method (ICOV) and instantaneous maximum entropy method (IMEM) are newly derived from the above procedure. In this paper, the Wigner-Boashash method is also derived from the same viewpoint. IMEM was applied to analyze nonstationary signals of automobile vibration and speech signals.
New initiatives in youth development: technology works enterprises
Authors: David Cavallo
Venue: Proceedings of the 1996 international conference on Learning sciences (1996)

This paper describes a new initiative, Technology Works Enterprises (TWE), a radically different learning environment for low-income, at-risk adolescents. This article probes which aspects of the technological and educational infrastructure of Technology Works helped to make the project successful. It uses a case study of an individual and the developing learning culture to highlight these aspects. Finally, the paper discusses the implications of this project on approaches to vocational education.
Unitary ESPRIT: how to exploit additional information inherent in the relational invariance structure
Authors: M. Haardt, M. E. Ali-Hackl
Venue: Proceedings of the Acoustics, Speech, and Signal Processing,1994. on IEEE International Conference - Volume 04 (1994)

ESPRIT is a high-resolution signal parameter estimation technique based on the translational invariance structure of a sensor array. Previous ESPRIT algorithms do not use the fact that the operator representing the phase delays between the two subarrays is unitary. Unitary ESPRIT, however, exploits this knowledge to estimate the directions of arrival in a straightforward way yielding more accurate results. This is particularly useful in situations where the standard ESPRIT algorithm faces severe problems, such as closely spaced sources or short window lengths. The improved subspace estimates form the basis for several algorithms to separate and reconstruct superimposed signals arriving from different directions. Moreover, Unitary ESPRIT improves the performance of recently developed subspace estimation schemes, that only approximate the optimal signal subspace, but can be updated with significant computational savings.
On the Interest of Using HL7 CDA Release 2 for the Exchange of Annotated Medical Documents
Authors: Michel Treins, Olivier Cure, Gabriella Salzano
Venue: Proceedings of the 19th IEEE Symposium on Computer-Based Medical Systems (2006)

During the last past years, cooperatives medical practices in healthcare networks have emerged and evolved drastically. Within these networks, healthcare professionals take care of patients, according to their degree of expertise, in contact with the others members for heaviest or simplest cases. An ubiquitous element in these medical documents is annotation. The issue of considering these annotations in computerized medical documents exchanged within healthcare networks is fundamental to the integrity and quality of future medical information systems. In this paper we highlight, based on the study of concrete medical information and their annotations, the fact that these documents belong to the peculiar category of "documents for action" and we also emphasize the potential of the HL7 CDA standard to represent and exchange these annotations in such networks.
Graphical UML View from Extended Backus-Naur Form Grammars
Authors: Fathi Essalmi, Leila Jemni Ben Ayed
Venue: Proceedings of the Sixth IEEE International Conference on Advanced Learning Technologies (2006)

This paper addresses the graphical representation of Context-Free Grammars (CFG) written in extended Backus- Naur Form (EBNF), using UML class diagrams. These diagrams can help understand the grammar for users who are not familiar with concepts of EBNF grammars. The additional structure afforded by UML could help to clarify how the derived language is constructed and allows learner to build significance relations between the concepts presented. We propose derivation rules of EBNF grammars into UML class diagrams which will be illustrated over an example of a grammar written in EBNF.
Interactive Processing of Sensory Input and Motor Output in the Human Hippocampus
Authors: C. D. Tesche, J. Karhu
Venue: Journal of Cognitive Neuroscience (1999)

Recent studies of visuomotor integration suggest that the motor system may be intimately involved in the detection of salient features of the sensory scene. The final stages of sensory processing occur in hippocampal structures. We measured human neuromagnetic responses during motor reaction to an auditory cue embedded in high-speed multimodal stimulation. Our results demonstrate that large-scale cognitive networks may recruit additional resources from the hippocampus during sensorimotor integration. Hippocampal activity from 300 msec before to 200 msec after cued movements was enhanced significantly over that observed during self-paced movements. The dominant hippocampal activity appeared equally synchronized to both sensory input and motor output, consistent with timing by an intrinsic mechanism, possibly provided by ongoing theta oscillations.