ppxscal/embedding_network huggingface dataset:
Learning in Communities: Interdisciplinary Perspectives on Human Centered Information Technology
Authors: John M. Carroll
Venue:  (2009)

Most learning takes place in communities. People continually learn through their participation with others in everyday activities. Such learning is important in contemporary society because formal education cannot prepare people for a world that changes rapidly and continually. We need to live in learning communities. This volume gathers together all of the scholarly materials directly emanating from a workshop held in August 2005, when a multidisciplinary group of scholars met at Penn States College of Information Sciences and Technology to discuss learning in communities. Initially, a sectioned report on the workshop was published as a special section in the Journal of Community Informatics in 2006. Subsequently, a special issue of 5 full papers was published in the Journal of Computer-Supported Cooperative Work, and a special section of 2 full papers was published in the International Journal of Computer-Supported Collaborative Learning. This collection of papers is not the definitive summary of learning in communities. It is assuredly more prolegomena than coda. Learning is increasing recognized as a critical facet of lifetime activity, one that must become better integrated with all that people do. At the same time, community structures are increasingly recognized as a critical category of social organization flexible and adaptable, capable of innovation and development, and yet just as strongly nurturing and supportive. The promise of learning in communities lies ahead of us. This set of essays hopes to propel us all along that path.
Parakeet: a continuous speech recognition system for mobile touch-screen devices
Authors: Keith Vertanen, Per Ola Kristensson
Venue: Proceedings of the 13th international conference on Intelligent user interfaces (2009)

We present Parakeet, a system for continuous speech recognition on mobile touch-screen devices. The design of Parakeet was guided by computational experiments and validated by a user study. Participants had an average text entry rate of 18 words-per-minute (WPM) while seated indoors and 13 WPM while walking outdoors. In an expert pilot study, we found that speech recognition has the potential to be a highly competitive mobile text entry method, particularly in an actual mobile setting where users are walking around while entering text.
Revealing gauguin: engaging visitors in robot guide's explanation in an art museum
Authors: Keiichi Yamazaki, Akiko Yamazaki, Mai Okada, Yoshinori Kuno, Yoshinori Kobayashi, Yosuke Hoshi, Karola Pitsch, Paul Luff, Dirk vom Lehn, Christian Heath
Venue: Proceedings of the 27th international conference on Human factors in computing systems (2009)

Designing technologies that support the explanation of museum exhibits is a challenging domain. In this paper we develop an innovative approach - providing a robot guide with resources to engage visitors in an interaction about an art exhibit. We draw upon ethnographical fieldwork in an art museum, focusing on how tour guides interrelate talk and visual conduct, specifically how they ask questions of different kinds to engage and involve visitors in lengthy explanations of an exhibit. From this analysis we have developed a robot guide that can coordinate its utterances and body movement to monitor the responses of visitors to these. Detailed analysis of the interaction between the robot and visitors in an art museum suggests that such simple devices derived from the study of human interaction might be useful in engaging visitors in explanations of complex artifacts.
Optimizing inspection strategies for multi-stage manufacturing processes using simulation optimization
Authors: Vahid Sarhangian, Abolfazl Vaghefi, Hamidreza Eskandari, Mostafa K. Ardakani
Venue: Proceedings of the 40th Conference on Winter Simulation (2008)

This paper deals with the problem of determining the optimal inspection strategy for a multi-stage production process using simulation optimization. An optimal inspection strategy is the one that results in the lowest total inspection cost, while still assuring a required output quality. Because of the complexity of the problem, simulation is used to model the multi-stage process subject to inspection and to calculate the resulting inspection costs. Simulation optimization is then used to find the optimal inspection strategy. The performance of the proposed method is presented through the use of a numerical example.
Throughput analysis of IEEE 802.11e EDCA under heterogeneous traffic
Authors: Shih-Wei Pan, Jung-Shyr Wu
Venue: Computer Communications (2009)

The amended version of IEEE 802.11e defines the enhanced distributed channel access (EDCA) for quality of service (QoS) connections. EDCA provides a priority scheme to classify different traffic categories by the arbitration inter-frame space (AIFS), and the initial and maximum contention window sizes. Most previous Markov chain analyses of EDCA have concentrated on the effect of contention window size, they neglected the effect of AIFS. In this paper, we consider of AIFS events among each back-off procedure and evaluate the saturation throughput of the IEEE 802.11e EDCA under heterogeneous traffic scenarios. The analytical model is based on the differentiated AIFS and uses the discrete time slot to analyses the external collision time. We take advantage of extensive simulation studies to validate the accuracy of the proposed model. Our models accurately estimate the effects of varied back-off window size and AIFS under heterogeneous traffic.
Extensive facility location problems on networks with equity measures
Authors: Justo Puerto, Federica Ricca, Andrea Scozzari
Venue: Discrete Applied Mathematics (2009)

This paper deals with the problem of locating path-shaped facilities of unrestricted length on networks. We consider as objective functions measures conceptually related to the variability of the distribution of the distances from the demand points to a facility. We study the following problems: locating a path which minimizes the range, that is, the difference between the maximum and the minimum distance from the vertices of the network to a facility, and locating a path which minimizes a convex combination of the maximum and the minimum distance from the vertices of the network to a facility, also known in decision theory as the Hurwicz criterion. We show that these problems are NP-hard on general networks. For the discrete versions of these problems on trees, we provide a linear time algorithm for each objective function, and we show how our analysis can be extended also to the continuous case.
Extended IMS specification for accumulative test system
Authors: M. Sokolova, G. Totkov
Venue: Proceedings of the 9th International Conference on Computer Systems and Technologies and Workshop for PhD Students in Computing (2008)

There are different methods for automatic generation of test questions (term extraction, templates, accumulation, etc.), but there is no clear specification of that process. In the work is proposed a schema for the process of automatic generation of assessment items. The IMS specification scheme is used as basis and some new elements are complemented for the accumulation, like visualization Declaration, accumulation Processing and accumulative Feedback to present the accumulation objects. Using the new elements we can overcome some of the problems in e-testing: remembering of the assessment item from the students, automatic creation of different questions, automatic adaptation of the test process, etc.
A small spiking neural network with LQR control applied to the acrobot
Authors: Lukasz Wiklendt, Stephan Chalup, Rick Middleton
Venue: Neural Computing and Applications (2009)

This paper presents the results of a computer simulation which, combined a small network of spiking neurons with linear quadratic regulator (LQR) control to solve the acrobot swing-up and balance task. To our knowledge, this task has not been previously solved with spiking neural networks. Input to the network was drawn from the state of the acrobot, and output was torque, either directly applied to the actuated joint, or via the switching of an LQR controller designed for balance. The neural network&#x2019;s weights were tuned using a (&#x03bc;&#x00a0;+&#x00a0;&#x03bb;)-evolution strategy without recombination, and neurons&#x2019; parameters, were chosen to roughly approximate biological neurons.
Social Media Marketing: An Hour a Day
Authors: Dave Evans
Venue:  (2008)

If the idea of starting a social media marketing campaign overwhelms you, the author of Social Media Marketing: An Hour a Day will introduce you to the basics, demonstrate how to manage details and describe how you can track results. Case studies, step-by-step guides, checklists, quizzes and hands-on tutorials will help you execute a social media marketing campaign in just one hour a day. In addition, learn how to integrate social media metrics with traditional media measurements and how to leverage blogs, RSS feeds, podcasts, and user-generated content sharing sites like YouTube.
Robust network monitoring in the presence of non-cooperative traffic queries
Authors: Pere Barlet-Ros, Gianluca Iannaccone, Josep Sanjuís-Cuxart, Josep Solé-Pareta
Venue: Computer Networks: The International Journal of Computer and Telecommunications Networking (2009)

We present the design of a predictive load shedding scheme for a network monitoring platform that supports multiple and competing traffic queries. The proposed scheme can anticipate overload situations and minimize their impact on the accuracy of the traffic queries. The main novelty of our approach is that it considers queries as black boxes, with arbitrary (and highly variable) input traffic and processing cost. Our system only requires a high-level specification of the accuracy requirements of each query to guide the load shedding procedure and assures a fair allocation of computing resources to queries in a non-cooperative environment. We present an implementation of our load shedding scheme in an existing network monitoring system and evaluate it with a diverse set of traffic queries. Our results show that, with the load shedding mechanism in place, the monitoring system can preserve the accuracy of the queries within predefined error bounds even during extreme overload conditions.
Using a Signing Avatar as a Sign Language Research Tool
Authors: Delroy Nelson
Venue: Multimodal Signals: Cognitive and Algorithmic Issues: COST Action 2102 and euCognition International School Vietri sul Mare, Italy, April 21-26, 2008 Revised Selected and Invited Papers (2009)

The first section of this paper introduces the Hamnosys/Visicast signing avatar, which has been designed to produce individual signs and sentences in a number of different sign languages. The operating systems which underlie the avatar are described in detail. The second part of the paper describes a research project which aims to use the avatar's properties to develop a toolkit for sign language research.
An Improved Divide-and-Conquer Algorithm for Finding All Minimum k-Way Cuts
Authors: Mingyu Xiao
Venue: Proceedings of the 19th International Symposium on Algorithms and Computation (2008)

Given a positive integer k and an edge-weighted undirected graph G = (V,E;w), the minimum k -way cut problem is to find a subset of edges of minimum total weight whose removal separates the graph into k connected components. This problem is a natural generalization of the classical minimum cut problem and has been well-studied in the literature. A simple and natural method to solve the minimum k-way cut problem is the divide-and-conquer method: getting a minimum k-way cut by properly separating the graph into two small graphs and then finding minimum k'-way cut and k''-way cut respectively in the two small graphs, where k' + k'' = k. In this paper, we present the first algorithm for the tight case of $k'=\lfloor k/2\rfloor$. Our algorithm runs in $O(n^{4k-\lg k})$ time and can enumerate all minimum k-way cuts, which improves all the previously known divide-and-conquer algorithms for this problem.
Simulation-optimization using a reinforcement learning approach
Authors: Carlos D. Paternina-Arboleda, Jairo R. Montoya-Torres, Aldo Fábregas-Ariza
Venue: Proceedings of the 40th Conference on Winter Simulation (2008)

The global optimization of complex systems such as industrial systems often necessitates the use of computer simulation. In this paper, we suggest the use of reinforcement learning (RL) algorithms and artificial neural networks for the optimization of simulation models. Several types of variables are taken into account in order to find global optimum values. After a first evaluation through mathematical functions with known optima, the benefits of our approach are illustrated through the example of an inventory control problem frequently found in manufacturing systems. Single-item and multi-item inventory cases are considered. The efficiency of the proposed procedure is compared against a commercial tool.
Modeling of power BAW resonators
Authors: M. Nitescu, F. Constantinescu, Al. G. Gheorghe
Venue: Proceedings of the 5th conference on Applied electromagnetics, wireless and optical communications (2007)

The circuit models aimed to reproduce both the amplitude-frequency and the intermodulation effects in a power BAW resonator are reviewed. It is shown that the linear parametric models are not able to reproduce the intermodulation effect and cannot be implemented in circuit simulators. Some new nonlinear circuit models are discussed, pointing out that they reproduce both effects and can be implemented in frequency domain and time domain circuit simulators.
On the complexity of graph cuboidal dual problems for 3-D floorplanning of integrated circuit design
Authors: Renshen Wang, Chung-Kuan Cheng
Venue: Proceedings of the 19th ACM Great Lakes symposium on VLSI (2009)

This paper discusses the impact of migrating from 2-D to 3-D on floorplanning and placement. By looking at a basic formulation of graph cuboidal dual problem, we show that the 3-D case and the 3-layer 2.5-D case are fundamentally more difficult than the 2-D case in terms of computational complexity. By comparison among these cases, the intrinsic complexity in 3-D floorplan structures is revealed in the hard-deciding relations between topological connections and geometrical contacts. The results show future challenges for physical design and CAD of 3-D integrated circuits.
The policy, structure and evaluation of long-term care networks: the differentiated requirements referred to the example of integrated long-term care in Austria
Authors: Herwig Ostermann, Bettina Staudinger, Oskar Staudinger, Katharina Kern, Christa Them, Roland Staudinger
Venue: International Journal of Networking and Virtual Organisations (2009)

Long-term care facilities are currently exposed to powerful forces demanding organisational change based on synergy and cooperation. The adoption of network structures is frequently regarded as an appropriate solution to this challenge by health politics. Focusing on the concrete example of the integrated long-term care network for the elderly in the Austrian land of Tyrol, the article aims (1) to explore which criteria the lawgiver formulated for the nursing cooperation structures, (2) to examine which targets and functional requirements the managers of the nursing institutions involved theoretically demand from a network structure in long-term care and (3) to investigate the functionality of the network by means of an empirical study focusing on the processes at interorganisational interfaces. Merging the major findings of the legal, theoretical and empirical enquiry, structural and functional efficiency criteria are derived, which are suggested as a framework for the evaluation of integrative nursing networks.
Crossover Can Be Constructive When Computing Unique Input Output Sequences
Authors: Per Kristian Lehre, Xin Yao
Venue: Proceedings of the 7th International Conference on Simulated Evolution and Learning (2008)

Unique input output (UIO) sequences have important applications in conformance testing of finite state machines (FSMs). Previous experimental and theoretical research has shown that evolutionary algorithms (EAs) can compute UIOs efficiently on many FSM instance classes, but fail on others. However, it has been unclear how and to what degree EA parameter settings influence the runtime on the UIO problem. This paper investigates the choice of acceptance criterion in the (1+1) EA and the use of crossover in the (μ+1) Steady State Genetic Algorithm. It is rigorously proved that changing these parameters can reduce the runtime from exponential to polynomial for some instance classes.
Group Scribbles to Support Knowledge Building in Jigsaw Method
Authors: Chee-Kit Looi, Chiu-Pin Lin, Kuo-Ping Liu
Venue: IEEE Transactions on Learning Technologies (2008)

Jigsaw method empowers students to build their own knowledge through interactively communicating and discussing in group-based cooperation. However, when students return to their original group to share with teammates what they have learned in their expert groups, they may need to review the records of the previous discussion in order to integrate and share the key ideas arising from that discussion. Paper-and-pencil records often do not meet students? in-time need, thereby affecting the learning process. Group Scribbles (GS) is an activity tool that enables the collaborative generation, collection and aggregation of ideas through a shared space. The aim of this study is to deploy GS with Tablet PCs to facilitate 12 graduate school students doing cooperative learning by the jigsaw method and to examine how GS supports knowledge building and deeper understanding through interactive questioning, dialogue and continuous improvement of ideas. Results of this exploratory study suggest that GS-mediated cooperative learning jigsaw model could positively benefit students in their interaction and knowledge building processes.
A New Face Recognition Approach to Boosting the Worst-Case Performance
Authors: Fang Chen, Senjian An, Wanquan Liu
Venue: Proceedings of the 9th Pacific Rim Conference on Multimedia: Advances in Multimedia Information Processing (2008)

In this paper, we aim to develop a new classifier for increasing the worst case performance for individual person. Technically, we adopt the idea from LDA and improve the worst recognition performance for individuals. This is achieved via introducing different weighting coefficients in LDA optimization process for obtaining the projection matrix. By increasing the weighting coefficients associated with the smallest between-class distance, the pair of classes with the nearest distance can exert more powerful influence on the optimization process in derivation of the projection matrix. The algorithm is tested on the Extended YaleB dataset and the ORL dataset.
Evolving Digital Circuits in an Industry Standard Hardware Description Language
Authors: Jamie Cullen
Venue: Proceedings of the 7th International Conference on Simulated Evolution and Learning (2008)

Evolutionary Meta Compilation (EMC) is a recent technique that enables unmodified external applications to seamlessly perform target program compilation and fitness evaluation for an Evolutionary Computation system. Grammatical Evolution (GE) is a method for evolving computer programs in an arbitrary programming language using a grammar specified in Backus-Naur Form. This paper combines these techniques to demonstrate the evolution of both sequential and combinational digital circuits in an Industry Standard Hardware Description Language (Verilog) using an external hardware synthesis engine and simulator. Overall results show the successful evolution of core digital circuit components. An extension to GE is also presented to attempt to increase the probability of maintaining an evolved program's semantic integrity after crossover operations are performed. Early results show performance improvements in applying this technique to the majority of the presented test cases. It is suggested that this feature may also be considered for use in the evolution of software programs in C and other languages.
CMAC-based neuro-fuzzy approach for complex system modeling
Authors: Kuo-Hsiang Cheng
Venue: Neurocomputing (2009)

A cerebellar model arithmetic computer (CMAC)-based neuron-fuzzy approach for accurate system modeling is proposed. The system design comprises the structure determination and the hybrid parameter learning. In the structure determination, the CMAC-based system constitution is used for structure initialization. With the advantage of generalization of CMAC, the initial receptive field constitution is formed in a systematic way. In the parameter learning, the random optimization algorithm (RO) is combined with the least square estimation (LSE) to train the parameters, where the premises and the consequences are updated by RO and LSE, respectively. With the hybrid learning algorithm, a compact and well-parameterized CMAC can be achieved for the required performance. The proposed work features the following salient properties: (1) good generalization for system initialization; (2) derivative-free parameter update; and (3) fast convergence. To demonstrate potentials of the proposed approach, examples of SISO nonlinear approximation, MISO time series identification/prediction, and MIMO system mapping are conducted. Through the illustrations and numerical comparisons, the excellences of the proposed work can be observed.
On Providing One-to-One Marketing with Customers' Privacy in Stationary Retail
Authors: Jens Strüker, Rafael Accorsi, Günter Müller
Venue: Proceedings of the 2008 10th IEEE Conference on E-Commerce Technology and the Fifth IEEE Conference on Enterprise Computing, E-Commerce and E-Services (2008)

Electronic commerce has provided retailers with effective instruments to deploy one-to-one marketing over the internet. While the increasing use of sensors, RFID tags and other technologies enables the deployment of one-to-one marketing also in stationary retail stores, ini-tial experiments in realizing personalization in this setting have shown that customers' acceptance is low, as services require personal data to be collected, thereby raising imminent privacy concerns.In this paper, we argue that one-to-one marketing in stationary retail and privacy do not constitute a dichotomy, but can be brought together by focusing on individualized services solely built upon context information and techniques to allow customers to control the collection and usage of such context information.
Intuitionistic fuzzy sets: Spherical representation and distances
Authors: Y. Yang, F. Chiclana
Venue: International Journal of Intelligent Systems (2009)

Most existing distances between intuitionistic fuzzy sets are defined in linear plane representations in 2D or 3D space. Here, we define a new interpretation of intuitionistic fuzzy sets as a restricted spherical surface in 3D space. A new spherical distance for intuitionistic fuzzy sets is introduced. We prove that the spherical distance is different from those existing distances in that it is nonlinear with respect to the change of the corresponding fuzzy membership degrees. &copy; 2009 Wiley Periodicals, Inc.