ppxscal/embedding_network huggingface dataset:
"Whiter than white" noise
Authors: T. S. Durrani, I. R. Leyman, J. J. Soraghan
Venue: Proceedings of the Acoustics, Speech, and Signal Processing,1994. on IEEE International Conference - Volume 04 (1994)

This paper brings together two strands of current interest in signal processing. While second order techniques and minimum variance criteria are well understood, there is a growing requirement to study the performance criteria that involve higher order statistics in order to evaluate deviation from Gaussianity, linearity and stationarity of observed data. There is a complimentary requirement for the generation of random test sequences which have prescribed (or minimal) higher order statistics, to facilitate the analysis of systems in order to determine linearity/non-linearity, time invariance vs time varying parameters. This paper proposes a new method for minimising the third order cumulant spread of random sequences with symmetric pdf, and provides a closed form solution for the weightings required to achieve this. Numerous computed results are included to verify performance.
Detecting and Exploiting Symmetry in Discrete-state Markov Models
Authors: W. Douglas II Obal, Michael G. McQuinn, William H. Sanders
Venue: Proceedings of the 12th Pacific Rim International Symposium on Dependable Computing (2006)

Dependable systems are usually designed with multiple instances of components or logical processes, and often possess symmetries that may be exploited in model-based evaluation. The problem of how best to exploit symmetry in models has received much attention from the modeling community, but no solution has garnered widespread support, primarily because each solution is limited in terms of either the types of symmetry that can be exploited or the difficulty of translating from the system description to the model formalism. We propose a new method for detecting and exploiting model symmetry in which 1) models retain the structure of the system, and 2) all symmetry inherent in the structure of the model can be detected and exploited for the purposes of state-space reduction. Composed models are constructed from models through specification of connections between models that correspond to shared state fragments. The composed model is interpreted as an undirected graph, and results from group and graph theory are used to develop procedures for automatically detecting and exploiting all symmetries in the composed model. A statespace generator which implements these algorithms within M¨obius [10] is then presented.
Mining Frequent Induced Subtrees by Prefix-Tree-Projected Pattern Growth
Authors: Lei Zou, Yansheng Lu, Huaming Zhang, Rong Hu, Chong Zhou
Venue: Proceedings of the Seventh International Conference on Web-Age Information Management Workshops (2006)

Frequent subtree pattern mining is an important data mining problem with broad applications. Most existing algorithms, such as Apriori-like algorithms, are based on candidate-generation-and-test framework, except for Chopper and XSpanner [8]. Unfortunately, candidate pattern generation and test used in Apriori-like algorithms are always time and space consuming, and this is especially true when candidate patterns are numerous and large. To solve this problem, the technique of pattern growth was proposed by Han et al [6]. And the famous PrefixSpan algorithm was proposed for sequential pattern mining by Pei et al. in [7]. Along this line, in this paper, we propose a novel induced subtree mining algorithm, called PrefixTreeISpan (i.e. Prefix-Tree-projected Induced-Subtree pattern), which finds induced subtree patterns by growing the frequent prefix-trees. Thus, using divide and conquer, mining local length-1 frequent subtree patterns in Prefix- Tree-Projected database recursively will lead to the complete set of frequent patterns. Different from Chopper and XSpanner, PrefixTreeISpan is for mining induced subtree patterns and it does not need a checking process. Our performance study shows that PrefixTreeISpan has achieved good performance in both different large synthetic datasets and real datasets.
An online tool for learning collaboration and learning while collaborating
Authors: Robert Kildare, R. N. Williams, Jacky Hartnett
Venue: Proceedings of the 8th Austalian conference on Computing education - Volume 52 (2006)

Individuals are increasingly required to join as teams to complete online tasks. This impacts education in three ways. Firstly teachers increasingly set collaborative online tasks for students when teaching curriculum. Secondly individuals need to learn online collaboration skills. Finally, collaborative knowledge creation and innovation can occur when team members take risks. Educationally sound software must promote a psychologically secure environment. Software currently available for online learning and collaboration is predominantly task-based and does not support personal and social aspects of team interaction. Computer Supported Collaborative Learning (CSCL) and Computer Supported Collaborative Work (CSCW) communities are actively researching team interaction. Time Interaction and Performance (TIP) theory, while providing some framework for understanding interaction, does not recognise the unpredictability of team processes. This paper describes software which is hypothesised to support the education and performance of online team members. The software captures democratically created symbolic interaction rules and monitors indicators of the team's interaction. If the conditions are met for the rules to fire, the software enacts the rule consequent. The software, based on a model-free expert system, will accommodate emergent team interaction patterns and provide evolutionary, analytical feedback to both team members and researchers. Constructivist principles of activity and metacognition underlie the validity of this as an educational tool.
Design of laser pulses for STIRAP processes with geometric control techniques
Authors: U. Boscain
Venue: Proceedings of the 2003 International Conference on Physics and Control - Volume 3 (2003)

We apply techniques of geometric control theory to stimulated Raman adiabatic passage (STIRAP) in the rotating-wave approximation (RWA). After reduction to real variables, we develop a systematic way of designing laser pulses to improve the transfer that allows one to reach the target state precisely.
Quest for a Silver Bullet: Creating Software Product Value through Requirements Selection
Authors: Sebastian Barney, Aybuke Aurum, Claes Wohlin
Venue: Proceedings of the 32nd EUROMICRO Conference on Software Engineering and Advanced Applications (2006)

This paper provides results of an empirical study on how software product value is both understood and created through release planning for software products in Australia. We examine how IT professionals perceive value creation through requirements engineering and how the release planning process is conducted to create software product value. We then look at the degree to which the major stakeholders' perspectives are represented in the decision making process. Our findings show that the client and market base of the software product represents the most influential group in the decision to implement specific requirements. This is reflected both in terms of deciding the processes followed and the decisionmaking criteria applied when selecting requirements for the product. It is concluded that the creation of software product value is dependant on the context in which the software product exists, including issues such as the market or the age of the product.
Student-generated animations: supporting middle school students' visualization, interpretation and reasoning of chemical phenomena
Authors: Hsin-Yi Chang, Chris Quintana
Venue: Proceedings of the 7th international conference on Learning sciences (2006)

The study explores the roles of instructional animation to support middle school students' learning of chemistry concepts. We discuss two roles of animations: a constructivist tool to support visualization and interpretation of chemical processes, and a problem-solving tool to support reasoning about chemical phenomena. We developed Chemation, a handheld-based chemistry animation tool, to address the roles. We conducted an initial evaluation study to assess the impact of Chemation for supporting students' visualization, interpretation, and reasoning of chemical phenomena. Two teachers and 73 seventh grade students participated in the study. The results of pre- and posttests indicated a positive gross effect of the learning environment including all aspects such as teacher and tool supports. Close examination through classroom observations, student interviews, and student artifacts revealed the relationships between student learning and tool supports. The results inform the design of interactive learning environments that incorporate animation as a learning support.
Construction of 3D Composite Objects from Range Data
Authors: Keita Sato, Yoshihiro Okada, Koichi Niijima
Venue: Proceedings of the International Conference on Computer Graphics, Imaging and Visualisation (2006)

Recent advances of computer hardware technologies have made it possible to render 3D CG images in real time, and 3D graphics has become in great demand for various applications. However the development of 3D graphics software is still laborious work compared to 2D software development. Hence, the research group of the authors has proposed a component-based 3D graphics software development system called IntelligentBox. However, developers have to construct 3D composite components manually when developing an application even using such a component-based tool, and this is time consuming task. Hence, this paper proposes an automatic construction method of 3D composite objects from range data of artifacts. The 3D object construction system based on this method decomposes a unified surface model obtained from range data of a certain artifact to several elements by segmenting it, automatically exchanges each element into its similar shape model, which is already prepared as a functional component of IntelligentBox, and composes them into one functional composite component which looks like the original artifact. In this way, the user obtains functional composite 3D objects from range data easily.
Complexity-based program phase analysis and classification
Authors: Chang-Burm Cho, Tao Li
Venue: Proceedings of the 15th international conference on Parallel architectures and compilation techniques (2006)

Modeling and analysis of program behavior are at the foundation of computer system design and optimization. As computer systems become more adaptive, their efficiency increasingly depends on program dynamic characteristics. Previous studies have revealed that program runtime execution manifests phase behavior. Recently, methods and tools to analyze and classify program phases have also been developed. However, very few studies have been proposed so far to understand and evaluate program phases from their dynamics and complexity perspectives. In this work, we propose new methods, metrics and frameworks which aim to analyze, quantify, and classify the dynamics and complexity of program phases. Our methods use wavelet techniques to represent program phases at multiresolution scales. The cross-correlation coefficients between phase dynamics observed at different scales are then computed as metrics to quantify phase complexity. We propose to apply wavelet-based multiresolution analysis and data clustering to classify program execution into phases that exhibit similar degree of complexity. Experimental results on SPEC CPU 2000 benchmarks show that the proposed schemes classify complexity-based program phases better than currently used approaches.
Blindsight Modulation of Motion Perception
Authors: James M. Intriligator, Ruiman Xie, Jason J. S. Barton
Venue: Journal of Cognitive Neuroscience (2002)

Monkey data suggest that of all perceptual abilities, motion perception is the most likely to survive striate damage. The results of studies on motion blindsight in humans, though, are mixed. We used an indirect strategy to examine how responses to visible stimuli were modulated by blind-field stimuli. In a 26-year-old man with focal striate lesions, discrimination of visible optic flow was enhanced about 7&percnt; by blind-field flow, even though discrimination of optic flow in the blind field alone (the direct strategy) was at chance. Pursuit of an imagined target using peripheral cues showed reduced variance but not increased gain with blind-field cues. Preceding blind-field prompts shortened reaction times to visible targets by about 10 msec, but there was no attentional crowding of visible stimuli by blind-field distractors. A similar efficacy of indirect blind-field optic flow modulation was found in a second patient with residual vision after focal striate damage, but not in a third with more extensive medial occipito-temporal damage. We conclude that indirect modulatory strategies are more effective than direct forced-choice methods at revealing residual motion perception after focal striate lesions.
Strategies for Optimised STG Decomposition
Authors: Mark Schaefer, Walter Vogler, Ralf Wollowski, Victor Khomenko
Venue: Proceedings of the Sixth International Conference on Application of Concurrency to System Design (2006)

When synthesising an asynchronous circuit from an STG, one often encounters the state explosion problem. In order to alleviate this problem one can decompose the STG into smaller components. This paper deals with the decomposition method of [11], [12] and introduces several strategies for efficient implementations, proves them correct and compares them by means of benchmark examples.
The Datacrossing DSS: A Data-GRID Based Decision Support System for Groundwater Management
Authors: Simone Manca, Pierluigi Cau, Ernesto Bonomi, Alessandro Mazzella
Venue: Proceedings of the Second IEEE International Conference on e-Science and Grid Computing (2006)

The Datacrossing DSS (http://datacrossing.crs4.it) is a basin-scale groundwater model that relies on a geographically distributed GIS to support decision makers, through a user-friendly Web interface, in the field of sustainable water resources management. The portal, for the general user, exposes hydrological applications based on complex models that make use of large volumes of distributed data available in a GRID infrastructure. Free software and in-house technologies are combined to transparently and automatically deploy the applications. Our objective is to build a development platform that by introducing the computational and data-sharing advantages of the GRID infrastructure promotes joint initiatives and encourages cooperation among multidisciplinary teams operating in environmental sciences. To illustrate the potential of our data-grid DSS, we present its application to a Sardinian case history where a coastal aquifer is threatened by the leakage of highly toxic inorganic residuals from the Portoscuso industrial settlements.
Determining the impact of digital humans in fidelity-rich, simulated environments on learner performance
Authors: Mary Dereshiwsky
Venue:  (2006)

A challenge facing many organizations is the creation of computer-based training that fits learner needs in different working environments. One possible solution to this challenge is using digital humans that represent the physical properties of real people to teach tasks. The hypothesis of this study was whether digital humans enhance learner performance in computer-based training as compared to not utilizing digital humans. True experimentation was used to determine learner performance from technicians of a global telecommunications firm. The experimental group received training with digital humans while the control group had identical training without digital humans. The results of this study identified that digital humans are as effective for enhancing learner performance as compared to identical training without digital humans.
Embedded Agile Project by the Numbers With Newbies
Authors: Nancy Van Schooenderwoert
Venue: Proceedings of the conference on AGILE 2006 (2006)

There is a class of projects that can only be accomplished via agile practices due to their complexity and risks. It is rare for such a project to be staffed with newbies but it happened, and this paper tells the story. It is also rare for an agile project to have substantial hard numbers to tell its story but this one does. This paper presents detailed metrics from a three year long agile project where a newly formed development team produced a new embedded software product from scratch. The team experimented with various agile practices while recording data on bug rates, bug root causes, code size, schedule compliance, and labor expended. Although most of the team members lacked important technical skills for this work, they outperformed far more experienced teams. The natural learning environment and safety net that Agile provides allowed them to learn fast while keeping them from serious mistakes.
A longitudinal investigation of continued online shopping behavior: An extension of the theory of planned behavior
Authors: Meng-Hsiang Hsu, Chia-Hui Yen, Chao-Min Chiu, Chun-Ming Chang
Venue: International Journal of Human-Computer Studies (2006)

The purpose of this study is to propose an extended model of Theory of Planned Behavior (TPB) by incorporating constructs drawn from the model of Expectation Disconfirmation Theory (EDT) and to examine the antecedents of users' intention to continue using online shopping (continuance intention). Prior research has demonstrated that TPB constructs, including attitude, subjective norm, and perceived behavioral control, are important factors in determining the acceptance and use of various information technologies. These factors, however, are insufficient to explain a user's continuance intention in the online shopping context. In this study we extended TPB with two EDT constructs-disconfirmation and satisfaction-for studying users' continuance intention in the online shopping context. By employing longitudinal method with two-stage survey, we empirically validated the proposed model and research hypotheses.
Music by ear: an interactive system to teach old-time fiddle
Authors: Matthew Osment, Todd Reimer
Venue: Proceedings of the 7th international conference on Learning sciences (2006)

Our learning module is a virtual, interactive training environment designed to guide learners through the stages of learning to play the old-time fiddle. Students are placed in mastery oriented learning situations that reflect informal, historical settings where students learn music as part of a community. In our design, students benefit from just-in-time interactions while developing their identity within a community of practice. This presentation highlights our needs assessment, design solutions, and our system's functionality.
Heterogeneous RSVP Extension for End-to-End QoS Support in UMTS/WLAN Interworking Systems
Authors: Gwo-Chuan Lee, Long-Sheng Li, Wei-Yu Chien
Venue: Proceedings of the Seventh International Conference on Parallel and Distributed Computing, Applications and Technologies (2006)

Because of the popularity of WLAN, UMTS and WLAN networks are often combined into two-tier heterogeneous networks. However, it is important for mobile hosts to have an end-to-end QoS support for service continuity in the UMTS/WLAN interworking systems. To maintain mobility in the QoS control of multimedia services when integrating UMTS and WLAN networks, an efficient resource management mechanism for the two-tier network is necessary. This paper proposes a heterogeneous RSVP extension mechanism, denoted as HeMRSVP (Heterogeneous Mobile RSVP), which allows mobile hosts to reach the required QoS service continuity while roaming across UMTS and WLAN networks. A performance comparison of HeMRSVP and conceivable two-tier resource management schemes is presented. Besides, two approaches were studied, namely hierarchical reservations as well as repacking on demand, for the performance enhancement of HeMRSVP. Numerical results show that the HeMRSVP significantly outperforms other two-tier resource management schemes and the enhanced mechanisms perform well in UMTS/WLAN combination networks.
Automated web issue analysis: a nurse prescribing case study
Authors: Mike Thelwall, Saheeda Thelwall, Ruth Fairclough
Venue: Information Processing and Management: an International Journal (2006)

Web issue analysis, a new automated technique designed to rapidly give timely management intelligence about a topic from an automated large-scale analysis of relevant pages from the Web, is introduced and demonstrated. The technique includes hyperlink and URL analysis to identify common direct and indirect sources of Web information. In addition, text analysis through natural language processing techniques is used identify relevant common nouns and noun phrases. A case study approach is taken, applying Web issue analysis to the topic of nurse prescribing. The results are presented in descriptive form and a qualitative analysis is used to argue that new information has been found. The nurse prescribing results demonstrate interesting new findings, such as the parochial nature of the topic in the UK, an apparent absence of similar concepts internationally, at least in the English-speaking world, and a significant concern with mental health issues. These demonstrate that automated Web issue analysis is capable of quickly delivering new insights into a problem. General limitations are that the success of Web issue analysis is dependant upon the particular topic chosen and the ability to find a phrase that accurately captures the topic and is not used in other contexts, as well as being language-specific.
Dynamical Statistical Shape Priors for Level Set-Based Tracking
Authors: Daniel Cremers
Venue: IEEE Transactions on Pattern Analysis and Machine Intelligence (2006)

In recent years, researchers have proposed introducing statistical shape knowledge into level set-based segmentation methods in order to cope with insufficient low-level information. While these priors were shown to drastically improve the segmentation of familiar objects, so far the focus has been on statistical shape priors which are static in time. Yet, in the context of tracking deformable objects, it is clear that certain silhouettes (such as those of a walking person) may become more or less likely over time. In this paper, we tackle the challenge of learning dynamical statistical models for implicitly represented shapes. We show how these can be integrated as dynamical shape priors in a Bayesian framework for level set-based image sequence segmentation. We assess the effect of such shape priors "with memory” on the tracking of familiar deformable objects in the presence of noise and occlusion. We show comparisons between dynamical and static shape priors, between models of pure deformation and joint models of deformation and transformation, and we quantitatively evaluate the segmentation accuracy as a function of the noise level and of the camera frame rate. Our experiments demonstrate that level set-based segmentation and tracking can be strongly improved by exploiting the temporal correlations among consecutive silhouettes which characterize deforming shapes.