ppxscal/embedding_network huggingface dataset:
Hierarchical Approach for Datatype Matching in XML Schemas
Authors: Tran Hong-Minh, Dan Smith
Venue: Proceedings of the 24th British National Conference on Databases (2007)

Labels and datatypes are together the most important factors in identifying the best correspondences in matching XML Schemas. Besides label matching, datatype matching is also necessary since XML Schema is designed for datatype definitions for XML documents. We here propose a new approach for matching datatypes by taking into account various kinds of relations between datatypes and the mechanisms of definition for user-defined types. All datatypes in two schemas being matched are put into a global hierarchical structure of inheritance and aggregative relations. We show that our approach is flexible enough to deal with additional built-in datatypes and it matches completely or partially user-defined datatypes. Moreover, the experimental results are also promising with 83% correlation to human ratings and 10% superior to other approach (e.g., Cupid's), which provides us a firm baseline for the next research phase.
Robotics learning as a tool for integrating science technology curriculum in K-12 schools
Authors: E. Kolberg
Venue: Proceedings of the Frontiers in Education Conference, 2001. on 31st Annual - Volume 01 (2001)

Technology literacy for all on one hand and continuous demand for skilled technology engineers and workers on the other hand, poses a challenge to education systems worldwide. Recent years show efforts to integrate technology into all levels of the school curriculum. The work presented here introduces one possible approach to familiarize 5/sup th/ to 6/sup th/ grade pupils with high level technology using a mobile robot as the principal tool in the curriculum. Children construct an open ended, autonomous robot while working in teams (6 per team). Each team is divided into sub-groups that represent the various skills needed for the construction and operation of the robot. They use a flow-chart software as their programming frame. At first, the teams are given simple missions, and as they progress, they are challenged with open-ended, more complex assignments. Each weekly session lasts about three hours of which a third is devoted to knowledge expansion and the rest for testing and construction. During the test phase, pupils perform experiments for deducing device properties (sensor, motor, control method, etc.). They add the device of their choice to their mobile robot system. As a typical open-ended problem, the team explores possible solutions to each problem. Then they are expected to define their solutions and implement Them. At the end of the year there is a contest between robots built by the various teams, to accomplish a predefined task.
Frequency offset insensitive multiple symbol detection of MPSK
Authors: J. L. Buetefuer
Venue: Proceedings of the Acoustics, Speech, and Signal Processing, 2000. on IEEE International Conference - Volume 05 (2000)

A novel extension of multiple symbol detection (MSD) of non-coherent MPSK is presented in which the presence of an arbitrary and unknown frequency offset is considered. The resulting detector is insensitive to frequency offset present on the received signal. A near maximum-likelihood (ML), frequency insensitive multiple symbol detection (FI-MSD) metric is derived, and its performance in the detection of double differential MPSK (DD-MPSK) is analysed by simulation. It is shown that as the observation length is increased, the performance approaches that of coherent detection. The new detector removes the need for explicit estimation and removal of frequency offset prior to detection, and may be suited to use with random access communication channels that experience large frequency deviations (such as low Earth orbit (LEO) satellite channels).
Annotating websites with machine-processable information in controlled natural language
Authors: Rolf Schwitter, Marc Tilbrook
Venue: Proceedings of the second Australasian workshop on Advances in ontologies - Volume 72 (2006)

In this paper we present a user friendly approach to annotate websites with machine-processable information in controlled natural language. The controlled natural language serves as a high-level specification and knowledge representation language which allows human annotators to summarise individual web pages of a website and to express domain-specific ontological knowledge about that website in an unambiguous subset of English. The annotation process is backed up by an intelligent text editor which supports the writing process of the controlled natural language with the help of text- and menu-based predictive interface techniques. The text editor runs as a Java applet and is connected over the Internet to a controlled natural language processor and to a reasoning service (consisting of a theorem prover and a model builder). The controlled language processor translates the summaries of web pages and the ontological knowledge about a website into first-order predicate logic and the reasoning service combines this information into a set of micro theories for consistency and informativity checking as well as for question answering. Specification texts written in controlled natural language are both human-readable and machine-processable, and can be easily exported and distributed as web feeds.
Effective techniques for gene expression data mining
Authors: Chun Chung Chan
Venue:  (2006)

Gene expression data mining as a new research area poses new challenges to data mining researchers. Gene expression data are typically very noisy and have very high dimensionality. To tackle bioinformatics problems involving them, traditional data mining techniques may not be the best tools to use as they were not originally developed to deal with such data. For this reason, new effective techniques are required. In this thesis, we propose some such techniques. In particular, these techniques can be used to address the problems of reconstructing gene regulatory networks and clustering gene expression data. The former is concerned with the problem of discovering gene interactions to infer the structures of gene regulatory networks. The latter is concerned with the problem of discovering clusters of co-expressed genes so that genes that have similar expression patterns under different experimental conditions can be identified. To reconstruct gene regulatory networks, we have proposed to use an association-discovery technique, which is based on residual analysis and an information theoretic measure, to detect whether or not there interesting association relationships between genes. Given time-dependent gene expression data, this technique can reveal interesting sequential associations between genes for the effective inference of the structures of gene regulatory networks. The association-discovery technique proposed can also be used to find interesting association relationships between gene expression levels and cluster labels. Based on discovering such relationships, we have developed a two-phase clustering algorithm for gene expression data. This algorithm consists of an initial clustering phase and a second re-clustering phase. Using this two-phase approach, it is able to group genes, whose cluster memberships cannot be easily determined by existing methods, into the appropriate clusters. Since the effectiveness of the two-phase clustering algorithm depends, to some extent, on that of the existing clustering method used in the first phase, therefore, we have developed a novel evolutionary clustering algorithm, called EvoCluster, that can be used in the first phase to overcome some of the limitations of existing ones. By making use of an evolutionary approach and the association-discovery technique, it not only is able to perform well in the presence of very noisy data, it can also be used to discover overlapping clusters. For performance evaluation, the data mining techniques proposed in this thesis have been tested with simulated and real data and the experimental results show that they are very promising.
A novel fuzzy evaluation method to evaluate the reliability of FIN
Authors: Fan Hehong, Sun Xiaohan, Zhang Mingde
Venue: Proceedings of the The 8th International Conference on Communication Systems - Volume 02 (2002)

Based on fuzzy theory, we present the novel concept that a complex system should be described with multiple state linguistic terms (SLT). A network performability index given, the reliability indices of the object with multiple working-state are defined for the first time. On the grounds of linguistic cloud model (LCM), a fuzzy evaluation method for the network reliability is introduced. The method is used to examine the reliability of the fiber industry network (FIN) by way of Monte Carlo simulations. The results for FIN show that the method is efficient for reliability evaluation of industrial control networks thus can be used as a tool to design highly reliable industry networks.
A stereo echo canceller implemented using a stereo shaker and a duo-filter control system
Authors: S. Shimauchi
Venue: Proceedings of the Acoustics, Speech, and Signal Processing, 1999. on 1999 IEEE International Conference - Volume 02 (1999)

Stereo echo cancellation has been achieved and used in daily teleconferencing. To overcome the non-uniqueness problem, a stereo shaker is introduced in eight frequency bands and adjusted so as to be inaudible and not affect stereo perception. A due-filter control system including a continually running adaptive filter and a fixed filter is used for double-talk control. A second-order stereo projection algorithm is used in the adaptive filter. A stereo voice switch is also included. This stereo echo canceller was tested in two-way conversation in a conference room, and the strength of the stereo shaker was subjectively adjusted. A misalignment of 20 dB was obtained in the teleconferencing environment, and changing the talker's position in the transmission room did not affect the cancellation. This echo canceller is now used daily in a high-presence teleconferencing system and has been demonstrated to more than 300 attendees.
Introduction to the Minitrack "IT Governance and Its Mechanisms"
Authors: Wim Van Grembergen
Venue: Proceedings of the 40th Annual Hawaii International Conference on System Sciences (2007)

IT governance is the organizational capacity exercised by the board, executive management and IT management to control the formulation and implementation of IT strategy and in this way ensuring the fusion of business and IT.
EnsemBlue: integrating distributed storage and consumer electronics
Authors: Daniel Peek, Jason Flinn
Venue: Proceedings of the 7th USENIX Symposium on Operating Systems Design and Implementation - Volume 7 (2006)

EnsemBlue is a distributed file system for personal multimedia that incorporates both general-purpose computers and consumer electronic devices (CEDs). EnsemBlue leverages the capabilities of a few general-purpose computers to make CEDs first class clients of the file system. It supports namespace diversity by translating between its distributed namespace and the local namespaces of CEDs. It supports extensibility through persistent queries, a robust event notification mechanism that leverages the underlying cache consistency protocols of the file system. Finally, it allows mobile clients to self-organize and share data through device ensembles. Our results show that these features impose little overhead, yet they enable the integration of emerging platforms such as digital cameras, MP3 players, and DVRs.
OSCAR KernelPicker: Handling Clients Kernels
Authors: Jean Parpaillon
Venue: Proceedings of the 21st International Symposium on High Performance Computing Systems and Applications (2007)

Discusses a method of handling the configuration of kernels and ramdisk images for compute nodes in an OSCARintegrated way. Providing a kernel and ramdisk which differs from the server allows to handle specific hardware and meet new needs (SSI and virtual clusters).
On evolutionary algorithms, neural-network computations, and genetic programming. Mathematical problems
Authors: L. N. Korolev
Venue: Automation and Remote Control (2007)

Some problems related to evolutionary and genetic algorithms, genetic programming, and neural-network computations on solving applied problems that are reduced to analysis of functions prescribed at permutations are roughly studied. Natural parallelism of these algorithms and possibility of their realization on modern computers are noted.
A Conceptual Framework for Knowledge Integration in Distributed Networks of Practice
Authors: Eli Hustad
Venue: Proceedings of the 40th Annual Hawaii International Conference on System Sciences (2007)

This paper presents a conceptual framework for understanding knowledge integration in distributed networks of practice. The framework builds upon Grant's knowledge-based theory of organizational capability in terms of efficiency, flexibility and scope of knowledge integration. Due to challenges related to contextual characteristics in distributed networks of practice, the framework proposes boundary spanning activities in terms of boundary objects and knowledge brokers as critical to ensure knowledge integration and to build a shared repertoire and common ground of knowledge. The framework is applied as the basis for analyzing knowledge integration in distributed networks of practice in the marine insurance industry.
An Aspect-Oriented Programming Model for Bag-of-Tasks Grid Applications
Authors: Marcio E. F. Maia, Paulo H. M. Maia, Nabor C. Mendonca, Rossana M. C. Andrade
Venue: Proceedings of the Seventh IEEE International Symposium on Cluster Computing and the Grid (2007)

This paper presents a novel programming model for explicitly separating parallelization and middlewarespecific concerns in Bag-of-Tasks (BoT) grid applications. The model uses Java threads for application decomposition, and aspect-oriented programming to dynamically (and transparently) convert the application's thread objects into independent grid tasks, using the services of a specific grid middleware API. This paper also describes early experimental results showing the model's modularity gains and performance overhead, when applied to implement BoT grid applications using OurGrid.
Transient detection using a homogeneity test
Authors: Biao Chen
Venue: Proceedings of the Acoustics, Speech, and Signal Processing, 1999. on 1999 IEEE International Conference - Volume 05 (1999)

A simple yet effective statistic is proposed for detecting a transient buried in partially unknown ambient noise. The transient model is frequency scattered increased variance observations. We pose the transient detection problem as a homogeneity test and the statistic is derived as the (generalized) likelihood ratio test of overdispersion when the underlying observation sequence follows a double exponential distribution. Numerical testing focuses on the comparison of this scheme with the CFAR power-law detector.
The Bayesian Decision Tree Technique Using an Adaptive Sampling Scheme
Authors: Vitaly Schetinin, Wojtek Krzanowski, Carsten Maple
Venue: Proceedings of the Twentieth IEEE International Symposium on Computer-Based Medical Systems (2007)

Decision Trees (DTs) provide an attractive classification scheme because clinicians responsible for making reliable decisions can easily interpret them. Bayesian averaging over DTs allows clinicians to evaluate the class posterior distribution and therefore to estimate the risk of making misleading decisions. The use of Markov Chain Monte Carlo (MCMC) methodology of stochastic sampling makes the Bayesian DT technique feasible to perform. The Reversible Jump (RJ) extension of MCMC allows sampling from DTs of different sizes. However, the RJ MCMC process may become stuck in a particular DT far away from the region with maximal posterior. This negative effect can be mitigated by averaging the DTs obtained in different starts. In this paper we describe a new approach based on an adaptive sampling scheme. The performances of Bayesian DT techniques with the restarting and adaptive strategies are compared on a synthetic dataset as well as on some medical datasets. By quantitatively evaluating the classification uncertainty, we found that the adaptive strategy is superior to the restarting strategy.
Localized Support for Injection Point Election in Hybrid Networks
Authors: Matthias R. Brust, Steffen Rothkugel
Venue: Proceedings of the Sixth International Conference on Networking (2007)

Ad-hoc networks, a promising trend in wireless technology, fail to work properly in a global setting. In most cases, self-organization and cost-free local communication cannot compensate the need for being connected, gathering urgent information just-in-time. Equipping mobile devices additionally with GSM or UMTS adapters in order to communicate with arbitrary remote devices or even a fixed network infrastructure provides an opportunity. Devices that operate as intermediate nodes between the ad-hoc network and a reliable backbone network are potential injection points. They allow disseminating received information within the local neighborhood. The effectiveness of different devices to serve as injection point differs substantially. For practical reasons the determination of injection points should be done locally, within the ad-hoc network partitions. We analyze different localized algorithms using at most 2-hop neighboring information. Results show that devices selected this way spread information more efficiently through the ad-hoc network. Our results can also be applied in order to support the election process for clusterheads in the field of clustering mechanisms.
Cut-and-paste file-systems: integrating simulators and file-systems
Authors: Peter Bosch, Sape J. Mullender
Venue: Proceedings of the 1996 annual conference on USENIX Annual Technical Conference (1996)

We have implemented an integrated and configurable file system called the Pegasus fie-systems (PFS) and a trace-driven file-system simulator called Patsy. Patsy is used for off-line analysis of file-system algorithms, PFS is used for on-line file-system data storage. Algorithms are first analyzed in Patsy and when we are satisfied with the performance results, migrated into PFS for on-line usage. Since Patsy and PFS are derived from a common cut-and-paste filesystem framework, this migration proceeds smoothly. We have found this integration quite useful: algorithm bottlenecks have been found through Patsy that could have led to performance degradations in PFS. Off-line simulators are simpler to analyze compared to on-line file-systems because a work load can repeatedly be replayed on the same off-line simulator. This is almost impossible in on-line filesystems since it is hard to provide similar conditions for each experiment run. Since simulator and file-system are integrated (hence, use the same code), experiment results from the simulator have relevance in the real system. This paper describes the cut-and-paste framework, the instantiation of the framework to PFS and Patsy and finally, some of the experiments we conducted in Patsy.
A multidisciplinary polymer electronics laboratory
Authors: D. Braun
Venue: Proceedings of the 30th Annual Frontiers in Education - Volume 01 (2000)

Semiconducting polymers blend several attractive features that enable inexpensive and unique applications. Forming the subjects of numerous research and development projects, semiconducting polymers also make excellent teaching tools. Since the materials and their applications benefit from intrinsically multidisciplinary approaches, polymer electronics exposes both students and faculty to fruitful interdisciplinary collaboration. This paper introduces semiconducting polymers, tours the Cal Poly polymer electronics lab facility, and summarizes lab projects and course modules completed to date.
Studies on reliable and accurate services for event sensing, reporting, and monitoring applications
Authors: Liang Cheng
Venue:  (2006)

In this dissertation, a two-tier network infrastructure, which is composed of an upper-tier service network and multiple lower-tier wireless sensor networks (WSNs), is proposed to support event sensing, reporting, and monitoring applications based on unreliable multi-hop wireless networks. Three functional modules are studied to solve critical problems in this infrastructure. In order to improve the reliability of reporting and monitoring services for sensed events in the upper-tier service network, a Self-Nomination Aided Routing Protocol (SNARP) is proposed to handle packet losses caused by transmission failures, link failures, and network congestion simultaneously. The joint sender-receiver decision-making mechanism and the timeout triggered retransmission mechanism are integrated into a store-and-forwarding packet delivery process to improve the routing reliability. Simulation results show that SNARP can recover more than 99% of lost packets when the packet loss rate is 20% at each hop. It consumes 30% less energy than Extremely Opportunistic Routing (ExOR) while achieving similar packet recovery performance. A distributed node positioning protocol, Protocol for Location And Coordination Estimation (PLACE), is proposed to estimate positions of sensing nodes within the lower-tier WSNs. With the assistance of incomplete information, PLACE first calculates the positions of nodes and then refines the positioning results according to additional references. By solving the practical issues of the alias problem and the range-measurement error problem, the node positioning accuracy of PLACE is 10 times higher than that of DV-Distance in dense WSNs. Time-synchronization is essential in providing useful timestamps in the lower-tier WSNs. An analytical model is proposed in this dissertation to analyze the accuracy of time synchronization. To the best knowledge of the author, it is the first analytical model that studies the effects of processing delay, accessing delay, propagation delay, and receiving delay on the accuracy of time synchronization approaches. The proposed analytical model can help application designers in time synchronization approach selection, performance improvement, and parameter tuning according to the requirements of target applications.
Equivalence of Some Common Linear Feature Extraction Techniques for Appearance-Based Object Recognition Tasks
Authors: M. Asuncion Vicente, Patrik O. Hoyer, Aapo Hyvarinen
Venue: IEEE Transactions on Pattern Analysis and Machine Intelligence (2007)

Recently, a number of empirical studies have compared the performance of PCA and ICA as feature extraction methods in appearance-based object recognition systems, with mixed and seemingly contradictory results. In this paper, we briefly describe the connection between the two methods and argue that whitened PCA may yield identical results to ICA in some cases. Furthermore, we describe the specific situations in which ICA might significantly improve on PCA.
An Adaptation-based Approach to Incrementally Build Component Systems
Authors: Pascal Poizat, Gwen Salaün, Massimo Tivoli
Venue: Electronic Notes in Theoretical Computer Science (ENTCS) (2007)

Software components are now widely used in the development of systems. However, incompatibilities between their behavioural interfaces may make their composition impossible. The objective of software adaptation is to compensate such incompatibilities building as automatically as possible corrective connectors or components. Constructing component-based systems from scratch is difficult, in particular when components cannot be used directly since they have to be adjusted with respect to their mates. Incremental construction methods are therefore essential because they make it possible to build systems step by step and therefore to master the complexity of their adaptation. In this paper, we propose an incremental approach to build component-based systems which relies on the generation of adaptors to overcome behavioural incompatibilities. The adaptation stage can be automated being given an abstract mapping formalising the properties of the system to be adapted.