ppxscal/embedding_network huggingface dataset:
An Exploratory Study of Incorporating Task-Stage Identification into a Long-Term Document Support Process
Authors: I-Chin Wu, Pei-Cheng Chang
Venue: Proceedings of the 2006 IEEE/WIC/ACM international conference on Web Intelligence and Intelligent Agent Technology (2006)

With the increasing amount of information (and knowledge) in organizational memories and the phenomenal growth of the World Wide Web, knowledge workers are increasingly suffering from information overload. Because of the growing complexity of knowledge-intensive tasks, a profiling technique is needed to deliver task-relevant documents to workers. In this study, we propose a task-stage identification technique that provides effective document support throughout the execution of a task. A pattern similarity analysis method based on the correlation value is used to identify a worker's task-stage. The results are incorporated into a profile adaptation process to generate the worker's current task profile. We conducted a pilot study in a research institute. The results confirm the effectiveness of the proposed document support process in a knowledge-intensive working environment.
State Estimation of a Boiler Using Nonlinear Observer
Authors: A. Ramezanifar, A. Afshar, S. K. Yadavar Nikravesh
Venue: Proceedings of the First International Conference on Innovative Computing, Information and Control - Volume 1 (2006)

State estimation has been favored in many studies. In many control design methods such as state feedback and optimal regulators state variables are needed but very often they are not available at the output of the plant and should be estimated. Also many Fault Detection and Isolation (FDI) techniques use state variables to determine fault kind and location. There exist varies observers for using in linear systems. In this paper a nonlinear observer for state estimation of a nonlinear system is proposed. It is based on the gradient method and its convergence is proved using lyapunov direct method. The method is implemented for boiler which is a nonlinear MIMO system. Also a method to restrict boiler control efforts in optimal control design is suggested. The proposed method in this paper for restriction control effort signals relives us needing saturation function. This is done simply with using time varying weighing functions in optimal control design.
Flexible, Cost-EffectiveMembership Agreement in Synchronous Systems
Authors: Raul Barbosa, Johan Karlsson
Venue: Proceedings of the 12th Pacific Rim International Symposium on Dependable Computing (2006)

This paper presents a processor group membership protocol for fault-tolerant distributed real-time systems that utilize periodic, time-triggered scheduling for sending messages over the system's communication network. The protocol allows fault-free nodes to reach agreement on the operational state of all nodes in the presence of fail-silent or failreporting node failures as well as network failures (lost or corrupted messages). The protocol is based on the principle that each message sent by a node in the membership is acknowledged by k other nodes in a system of n nodes, where k can be set to any number between 2 and n-1. Agreement on node failure (membership departure) and agreement on node recovery (membership reintegration) are handled by two different mechanisms. Agreement on departure is guaranteed if no more than f = k-1 failures occur in the same communication round, while at most one node can be reintegrated into the membership per communication round.
Transactions in Distributed Event-Based Middleware
Authors: Luis Vargas, Jean Bacon, Ken Moody
Venue: Proceedings of the The 8th IEEE International Conference on E-Commerce Technology and The 3rd IEEE International Conference on Enterprise Computing, E-Commerce, and E-Services (2006)

Distributed event-based middleware (DEBM) provides a basis for the interoperation of autonomous components in large-scale systems. Transactions ensure the atomic and reliable execution of operations that involve interconnected clients. Integrating transactions and DEBM is a challenging software design problem with important applications. This paper presents the Hermes Transaction Service (HTS), a service that supports event-driven applications with transactional requirements. HTS uses transaction-context propagation via event notifications, where the contexts of publishers and subscribers are interrelated within a mixed transaction. Clients may opt to be compensatable or noncompensatable. Optional anonymity of transaction participants is supported through hash-based set memberships.
The Pairing Session as the Atomic Unit of Work
Authors: Troy Frever, Paul Ingalls
Venue: Proceedings of the conference on AGILE 2006 (2006)

We have an Extreme Programming team at a small company dedicated to the Agile approach. Our team of 7 developers decided to use the pairing session as the fundamental unit of work for all organizing, planning, estimating, tracking, and of course, pair programming. It's been a great way to structure the day, provide rhythm and facilitate partner swaps. Estimating and tracking in pairing sessions provides us concrete feedback for improving estimates. This approach constitutes a hybrid between real time and abstractunit estimating, resulting in highly effective planning and an extremely stable velocity. We have been working this way for about a year and have been exceptionally pleased with the results.
Design of the ATRON lattice-based self-reconfigurable robot
Authors: Esben Hallundbæk Østergaard, Kristian Kassow, Richard Beck, Henrik Hautop Lund
Venue: Autonomous Robots (2006)

Self-reconfigurable robots are robots that can change their shape in order to better suit their given task in their immediate environment. Related work on around fifteen such robots is presented, compared and discussed. Based on this survey, design considerations leading to a novel design for a self-reconfigurable robot, called "ATRON", is described. The ATRON robot is a lattice-based self-reconfigurable robot with modules composed of two hemispheres joined by a single revolute joint. Mechanical design and resulting system properties are described and discussed, based on FEM analyses as well as real-world experiments. It is concluded that the ATRON design is both competent and novel. Even though the ATRON modules are minimalistic, in the sense that they have only one actuated degree of freedom, the collective of modules is capable of self-reconfiguring in three dimensions. Also, a question is raised on how to compare and evaluate designs for self-reconfigurable robots, with a focus on lattice-based systems.
Chaotic Signal Design with Selected Parameters
Authors: Baishan Zhao, Yi-Sheng Zhu
Venue: Proceedings of the 2006 International Conference on Intelligent Information Hiding and Multimedia (2006)

Chaotic signal is very important for chaotic communication and chaotic encryption. In his paper a method of producing chaotic signals with arbitrary magnitude and spectrum is presented, which is based on the Lorentz system by introducing some parameters of the system to realize the selected magnitude and spectrum. Furthermore, the validity of this method by theory and simulation is shown. In addition, this kind of generators is easily implemented, and the signal is suitable for protecting the information in communication systems.
Mass Customization as an Educational Paradigm: Design and Pilot Evaluation of a Mass-Customized, Problem-Based Learning Environment
Authors: Nicolae Nistor
Venue: Proceedings of the Sixth IEEE International Conference on Advanced Learning Technologies (2006)

Several authors point at mass customization as an application that is already proven and established in the economical sector. They demand similar applications in education, aimed at adapting courses and training to the individual characteristics of a high number of students, but without causing additional costs. However the available educational research literature provides neither explicit design principles for mass-customized learning environments nor examples of such applications. This contribution formulates in its first section four design principles of MC, deduced from a literature review in the field of economics. It shows related work from the educational field, discussing its relevance for MC as well as its limitations. The second part presents amit^TM, an example of mass-customized, problembased learning environment, along with the pilot evaluation results and some conclusions for further development and research.
Estimation and model selection of the interest rates
Authors: Pouyan Mashayekh Ahangarani
Venue: Proceedings of the 37th conference on Winter simulation (2005)

A variety of continuous time series models of the short term riskless rate are estimated using Maximum Likelihood method on discretized models. Then the best model will be found that can fit the data better. A number of well-known models perform poorly in the comparison. Indirect Inference method is used for the best model in order to obtain consistent estimates. At the end, an empirical application of the stochastic model for interest rates will be used for pricing the call options of Nokia Company. The ACM Portal is published by the Association for Computing Machinery. Copyright © 2010 ACM, Inc. Terms of Usage Privacy Policy Code of Ethics Contact Us Useful downloads: Adobe Acrobat QuickTime Windows Media Player Real Player
Multiple Peak Alignment in Sequential Data Analysis: A Scale-Space-Based Approach
Authors: Weichuan Yu, Xiaoye Li, Junfeng Liu, Baolin Wu, Kenneth R. Williams, Hongyu Zhao
Venue: IEEE/ACM Transactions on Computational Biology and Bioinformatics (TCBB) (2006)

In this paper, we address the multiple peak alignment problem in sequential data analysis with an approach based on the Gaussian scale-space theory. We assume that multiple sets of detected peaks are the observed samples of a set of common peaks. We also assume that the locations of the observed peaks follow unimodal distributions (e.g., normal distribution) with their means equal to the corresponding locations of the common peaks and variances reflecting the extension of their variations. Under these assumptions, we convert the problem of estimating locations of the unknown number of common peaks from multiple sets of detected peaks into a much simpler problem of searching for local maxima in the scale-space representation. The optimization of the scale parameter is achieved using an energy minimization approach. We compare our approach with a hierarchical clustering method using both simulated data and real mass spectrometry data. We also demonstrate the merit of extending the binary peak detection method (i.e., a candidate is considered either as a peak or as a nonpeak) with a quantitative scoring measure-based approach (i.e., we assign to each candidate a possibility of being a peak).
Imagineering inauthentic legitimate peripheral participation: an instructional design approach for motivating computing education
Authors: Mark Guzdial, Allison Elliott Tew
Venue: Proceedings of the second international workshop on Computing education research (2006)

Since its publication, Lave and Wenger's concept of legitimate peripheral participation (LPP) [18] has become an important concept for understanding situated learning. LPP states that learning only occurs when students perceive that what's being taught is aligned with their goals (in LPP terms, with the students' perceived community of practice). This has implications for our traditional CS courses (e.g., are we teaching what the students perceive as being relevant for their future careers?), but even greater implications for courses for non-CS majors. When computer science educators are asked to teach non-CS majors, we are often placed in the position of teaching in alignment with a community of practice that does not, or does not yet, exist. In that sense, our teaching is inauthentic---not aligned with a community of practice. However, there is the possibility that we can generate a perception of authenticity or alignment. We use the example of two classes at Georgia Tech that seem successful by several measures, yet suffer this inauthenticity. We propose that a useful tool for understanding how these classes work is the Disney Corporation's Imagineering---their process of story-telling in three-dimensions as used in their theme parks. However, in the end, we find that what students actually learn is not necessarily the story that we are telling them, which points toward future research.
Harmonic Detection Based Hopfield Neural Network Optimum Algorithm
Authors: Yu Zou, Ping Wang
Venue: Proceedings of the First International Conference on Innovative Computing, Information and Control - Volume 2 (2006)

Current harmonics generated by nonlinear loads and the use of semiconductor switching drives caused widespread concern and attracted attention in power systems at all times. This paper applied an adaptive detection approach based on Hopfield Neural Network optimum theory to the harmonic detection. It presents the principle of estimation first, and then the neural network architecture will be built and simulated. The adaptive neural network-based signal processing technique is used to know the harmonic parameters. This knowledge would make it possible to compensate the harmonic components. By emulating this harmonic detection system in MATLAB, the result verifies the validity and the rapidity of the approach.
Using IMS Learning Design to model collaborative learning activities
Authors: Colin Tattersall
Venue: Proceedings of the Sixth IEEE International Conference on Advanced Learning Technologies (2006)

IMS Learning Design provides a counter to the trend towards designing for lone-learners reading from screens. It guides staff and educational developers to start not with content, but with learning activities and the achievement of learning objectives. It recognises that learning can happen without learning objects, that learning is different from content consumption and that learning comes from being active. It recognises, too, that learning happens when learners cooperate to solve problems in social and work situations. In all this, it stresses that focus should fall on the learning in eLearning.
A framework for seamless roaming across heterogeneous next generation wireless networks
Authors: Nirmala Shenoy
Venue: Wireless Networks (2005)

In the future, wireless and mobile users will have increased demands for seamless roaming across different types of wireless networks, quality of service guarantees and support of different types of services. This awareness has led to research activities directed towards inter-system and global roaming and can be noticed in the numerous products like multimode handsets, inter-working gateways and some ongoing standards and research work on signaling protocols for inter-system roaming. This article proposes a global mobility management framework. The framework is like an overlay network comprising of Inter-System Interface Control Units (IICU) to support inter-network communication and control for Location Management. The protocols and functions of this framework will be distributed and exist partly within the wireless networks and partly within the core-network. A hierarchy introduced among the IICUs will accommodate for the varying mobility coverage required by the mobile user. The IICU may be configured to perform various functions depending on its placement in the hierarchy of the framework. This approach aims to optimize across call set up delays, signaling traffic, database processing, handoff facilitation for seamless roaming and QoS mapping and negotiations as the user moves across different wireless networks. It avoids centralized database dependency with its associated single-point bottleneck and failures. We restrict our analysis of the framework to a 2-network and a 3-network roaming scenario. The presentation has been further restricted to cost and delay analysis of the location update and call delivery procedures. We have taken into account the signalling requirements when the mobile user roams across networks with and without an active call.
Grid-Based Data Stream Processing in e-Science
Authors: Richard Kuntschke, Tobias Scholl, Sebastian Huber, Alfons Kemper, Angelika Reiser, Hans-Martin Adorf, Gerard Lemson, Wolfgang Voges
Venue: Proceedings of the Second IEEE International Conference on e-Science and Grid Computing (2006)

The field of e-science currently faces many challenges. Among the most important ones are the analysis of huge volumes of scientific data and the connection of various sciences and communities, thus enabling scientists to share scientific interests, data, and research results. These issues can be addressed by processing large data volumes on-thefly in the form of data streams and by combining multiple data sources and making the results available in a network. In this paper, we demonstrate how e-science can benefit from research in computer science in the field of data stream management. In particular, we are concerned with processing multiple data streams in grid-based peer-to-peer (P2P) networks. We introduce spatial matching, which is a current issue in astrophysics, as a real-life e-science scenario to show how a data stream management system (DSMS) can help in efficiently performing associated tasks. We describe our new way of solving the spatial matching problem and present some evaluation results. In the course of the evaluation, our DSMS StarGlobe proves to be a valuable computing platform for astrophysical applications.
Local averaging of heterogeneous regression models
Authors: S. B. Kotsiantis
Venue: International Journal of Hybrid Intelligent Systems (2006)

Many learning problems involve an exploration of relationships between features in heterogeneous datasets, where different learning models can be more suitable for different regions. We propose herein a technique of localized averaging of regression models. This technique identifies local regions which have similar characteristics and then uses the average value of local experts to describe the relationship between the predictive feature values and the target value. We performed a comparison with other famous combining methods on standard benchmark datasets, and the correlation coefficient of the proposed method was higher.
Structure modeling of machine tools and internet-based implementation
Authors: Yoonho Seo, Dong-Pyo Hong, Insu Kim, Donmok Sheen, Taioun Kim, Gyu-Bong Lee
Venue: Proceedings of the 37th conference on Winter simulation (2005)

Reconfigurability of machine tools is one of the critical factors to realize the responsive manufacturing systems to satisfy the mass-customization production. This paper presents the methods to model and simulate the machine tools on Internet in response to change in the machining requirements. Specifically, a set of module combination rules and a modeling method of the structure of machine tools using connectivity graph are developed. In response to the user requirements, kinematic relations and structures of machine tools can be derived using the module combination rules and connectivity graph relationships. Internet-based simulator of machine tools is implemented and presented. The developed machine tool simulator can be used to verify the structure of machine tools derived from the user requirements.
Students collaborating with computer models and physical experiments
Authors: Robert B. Kozma
Venue: Proceedings of the 1999 conference on Computer support for collaborative learning (1999)

This study examines the actions and discourse of students in a chemistry laboratory course as they interact with available social and material resources. In one session, students conduct wet lab experiments; in another, they use molecular modeling software. The analysis demonstrates that the features of the computer-generated representations afford conceptual discussions. The structure of the task and the available material resources in the wet lab more often result in help-seeking behavior.
Approximate time-parallel cache simulation
Authors: Tobias Kiesling
Venue: Proceedings of the 36th conference on Winter simulation (2004)

In time-parallel simulation, the simulation time axis is decomposed into a number of slices which are assigned to parallel processes for concurrent simulation. Although a promising parallelization technique, it is difficult to be applied. Recently, using approximation with time-parallel simulation has been proposed to extend the class of suitable models and to improve the performance of existing models. In trace-driven cache simulation, sequences of memory requests are processed to determine the performance of variously sized caches. Time-parallel simulation has been applied to trace-driven cache simulation, but only with limited scalability of the parallel algorithm. In order to solve the scaling problem, this work uses approximation with time-parallel cache simulation. Although introducing an uncertainty in the results, the approximate algorithms work in a way that result accuracy increases monotonically with time, allowing a direct control of the quality of results. Experiments with a prototypical implementation indicate the viability of this approach.
A rate-distortion optimized error control scheme for scalable video streaming over the Internet
Authors: Fan Zhai, R. Beryy, T. N. Pappas, A. K. Katsaggelos
Venue: Proceedings of the 2003 International Conference on Multimedia and Expo - Volume 1 (2003)

Video streaming over the Internet is a challenging task due, in part to the wide range of bandwidth variations caused by network congestion. To deal with this challenge, we propose an optimal error control scheme for scalable video transmission over the Internet. The three major components of error controlerror resilience, forward error correction (FEC), and error concealment- are considered in the proposed framework. Rate-distortion (R-D) optimization is carried out to determine the encoding mode for each packet and the channel coding rates, in order to minimize the overall expected end-to-end distortion. Our simulation study demonstrates that the proposed approach is robust to the wide range channel bandwidth variations and greatly outperforms the classical R-D optimization scheme.
Image Color Reduction Based on Self-Organizing Maps and Growing Self-Organizing Neural Networks
Authors: Guojian Cheng, Jinquan Yang, Kuisheng Wang, Xiaoxiao Wang
Venue: Proceedings of the Sixth International Conference on Hybrid Intelligent Systems (2006)

Color is one of the most important properties for object detection. Color Reduction of Image (CRI) is an important factor for segmentation, compression, presentation and transmission of images. The main purpose of CRI is to cut off the image storage spaces and computation time. Kohonen's Self-Organizing Maps (KSOM) can generate mappings from high-dimensional signal spaces to lower dimensional topological structures. The main characteristics of KSOM are formation of topology preserving feature maps and approximation of input probability distribution. Growing Self-Organizing Neural Network (GSONN) has got more and more attentions in the past decade, to overcome some limitations of KSOM. An effective approach to solve CRI problem is to consider it as a clustering problem and solve it by using some adaptive clustering methods, such as KSOM and GSONN. This paper first gives an introduction to KSOM and neural gas network. Then, we discuss a typical GSONN, growing neural gas. After that, a performance comparison of KSOM and GSONN for CRI is given. It is ended with some conclusions.