ppxscal/embedding_network huggingface dataset:
Intercultural Socializing via Mobile Games for Backpackers
Authors: Chui Yin Wong, Kimberly Chu, Chee Weng Khong, Sheila Paul
Venue: Proceedings of the 3d International Conference on Online Communities and Social Computing: Held as Part of HCI International 2009 (2009)

Mobile phones are currently shipped with pre-installed games all around the world. In most cases, these pre-installed games contain very little elements of sharing local heritage, traditional values and beliefs. Naturally, such pre-installed mobile games are provided with a different intent and under various commercial contexts. This paper looks at the design and development of intercultural mobile games aimed for backpackers. This is to allow backpackers to socialize, to share and to learn new cultures during their travels. User evaluation studies were conducted to collect the backpacker's feedback and to improve on conceptualization during the design process. The results were used collectively to provide input for improving the design concepts and interfaces. Screenshots of the mobile games are provided. In general, the results highlight important considerations when deploying an intercultural mobile game to backpackers.
Automated multiword expression prediction for grammar engineering
Authors: Yi Zhang, Valia Kordoni, Aline Villavicencio, Marco Idiart
Venue: Proceedings of the Workshop on Multiword Expressions: Identifying and Exploiting Underlying Properties (2006)

However large a hand-crafted wide-coverage grammar is, there are always going to be words and constructions that are not included in it and are going to cause parse failure. Due to their heterogeneous and flexible nature, Multiword Expressions (MWEs) provide an endless source of parse failures. As the number of such expressions in a speaker's lexicon is equiparable to the number of single word units (Jackendoff, 1997), one major challenge for robust natural language processing systems is to be able to deal with MWEs. In this paper we propose to semi-automatically detect MWE candidates in texts using some error mining techniques and validating them using a combination of the World Wide Web as a corpus and some statistical measures. For the remaining candidates possible lexico-syntactic types are predicted, and they are subsequently added to the grammar as new lexical entries. This approach provides a significant increase in the coverage of these expressions.
'Is it mine, is it yours? it is ours.' shared epistemic agency in collaborative research activities
Authors: Crina Damsa, Jerry Andriessen, Gijsbert Erkens, Paul Kirschner
Venue: Proceedings of the 8th international conference on International conference for the learning sciences - Volume 3 (2008)

Knowledge creation entails collaborative learning processes, involving groups of students that act collaboratively in order to create new knowledge. In this study, we discuss shared epistemic agency as one of the main concepts capturing the process and evolution of collaboratively creating knowledge. A multiple-method approach was employed when analyzing the data collected from a research module in higher education. Central in these analyses was the manner in which shared epistemic agency was instantiated during collaborative students' work on their shared knowledge objects, the research reports. A number of activities characterizing shared epistemic agency during collaborative work on shared knowledge objects are identified and described. These results feed back into new insights on how shared epistemic agency is enacted in this specific context, and into a fine-tuning of our description of the concept itself.
Adaptive synchronization of a network of interconnected nonlinear Lur'e systems
Authors: I. A. Dzhunusov, A. L. Fradkov
Venue: Automation and Remote Control (2009)

The problem of adaptive synchronization is formulated for networks of interconnected dynamical subsystems containing a leading subsystem. Considered are networks of subsystems specified in the Lur'e form (a linear part plus nonlinearity) of the following three types: Subsystems containing Lipschitz nonlinearities, those with non-Lipschitz nonlinearities in a certain class, and networks with structural matching between the leading subsystem and the driven ones. Decentralized algorithms of adaptive control are synthesized using the speed gradient method. The conditions of synchronizability are obtained through use of the method of passification and the Yakubovich-Kalman lemma. In contrast to the existing results, the case of incomplete measurements is considered along with the situation where the control input may not affect the equations of all subsystems. The results are exemplified by applications to Chua's circuits.
Self-matched Patterns, Golomb Rulers, and Sequence Reconstruction
Authors: Franco P. Preparata
Venue: Efficient Algorithms: Essays Dedicated to Kurt Mehlhorn on the Occasion of His 60th Birthday (2009)

The reconstruction of an unknown target sequence from the collection of its subsequences is a problem originating in computational biology (sequencing by hybridization), but with combinatorial significance in its own right. Retracing the history of the topic, this paper explores the power of the subsequence pattern in extracting information from the target, and proposes a new class of effective patterns, named self-matched, characterized by their autocorrelation function.
The Design of an Intelligent Guide Equipment Based on C8051F020 Microcontroller for Optimal Operation of Locomotive
Authors: Ping Li, Yarong Li, Xiaodong Liu
Venue: Proceedings of the 2009 International Conference on Measuring Technology and Mechatronics Automation - Volume 03 (2009)

In this paper, an intelligent guide equipment for optimal operation of locomotive is introduced .The principle of it is based on optimal principle and adaptive control theory. This equipment combines off-line optimization with on-line parameter self-tuning and predictive controlling, which is established on the C8051F020 measuring and controlling hardware flat. Because the equipment makes use of the methods of part parameter self-tuning, prediction and forecast, the problem—when train travels with high-speed, its inertia is too large to optimally operate is resolved, meanwhile the methods can reduce frequent operation and attain the best effect of energy saving.
Efficient AdaBoost Region Classification
Authors: M. Moed, E. N. Smirnov
Venue: Proceedings of the 6th International Conference on Machine Learning and Data Mining in Pattern Recognition (2009)

The task of region classification is to construct class regions containing the correct classes of the objects being classified with an error probability ¿ ¿ [0,1]. To turn a point classifier into a region classifier, the conformal framework is employed [11,14]. However, to apply the framework we need to design a non-conformity function. This function has to estimate the instance's non-conformity for the point classifier used.This paper introduces a new non-conformity function for AdaBoost. The function has two main advantages over the only existing non-conformity function for AdaBoost. First, it reduces the time complexity of computing class regions with a factor equal to the size of the training data. Second, it results in statistically better class regions.
Transferring localization models across space
Authors: Sinno Jialin Pan, Dou Shen, Qiang Yang, James T. Kwok
Venue: Proceedings of the 23rd national conference on Artificial intelligence - Volume 3 (2008)

Machine learning approaches to indoor WiFi localization involve an offline phase and an online phase. In the offline phase, data are collected from an environment to build a localization model, which will be applied to new data collected in the online phase for location estimation. However, collecting the labeled data across an entire building would be too time consuming. In this paper, we present a novel approach to transferring the learning model trained on data from one area of a building to another. We learn a mapping function between the signal space and the location space by solving an optimization problem based on manifold learning techniques. A low-dimensional manifold is shared between data collected in different areas in an environment as a bridge to propagate the knowledge across the whole environment. With the help of the transferred knowledge, we can significantly reduce the amount of labeled data which are required for building the localization model. We test the effectiveness of our proposed solution in a real indoor WiFi environment.
A Study on the Motion Energy of Biped Robot Walking on Different Postures
Authors: Kuo-Yang Tu, Mi-Shin Liu
Venue: Proceedings of the FIRA RoboWorld Congress 2009 on Advances in Robotics (2009)

It is interested for a bipedal robot manipulated by different Degree of Freedoms (DoFs) to spend how much motion energy. In this paper, the motion energy of a biped robot influenced by the manipulation of different DoFs is studied. For calculating the motion energy, the forward and inverse kinematics of the designed biped robot are first derived. The 4-3-4 trajectory for planning the movement of robot joints in smoothing is designed for the walking finished by the biped joint movement. Once the joint trajectories of the biped robot are solved, the motion energy including kinetic and potential energy can be calculated. The walking of the biped robot manipulated by 2, 4 and 6 DoFs, respectively, is also included. The study provides the mechanical design of biped robots in the future.
Program constructor of cellular self-reproducing structures
Authors: S. M. Achasova
Venue: Programming and Computing Software (2009)

A simple program for constructing a cellular self-reproducing rectangular loop of arbitrary size is developed based on the parallel substitution algorithm (PSA), which provides a spatial model for representing fine-grained parallel computations. In order to launch the self-reproduction of a loop of some specified size, one should enter its description into the input tape. The program includes operators for preliminary cleaning the cellular array, which makes it possible to easily change its internal functional structure. Two variants of the program are developed. The first variant constructs a chain of self-reproducing loops of the given size, and the second variant constructs an array of such loops.
Tackling River Pollution Ecologically: A Case Study on the Ji River of Gansu Province
Authors: An-guo Qi, Li-fang Qiao, Yong-dong Sun, Lian-fang Yao, Yi-chuan Zhang, Wei-rong Luo
Venue: Proceedings of the 2009 International Conference on Environmental Science and Information Application Technology - Volume 02 (2009)

Against the background of conspicuous problem of river pollution in China’s water resources affairs, we made a case study on the Ji River of Gansu Province to apply the principle that water can be naturally purified by plant communities to the functional division and tackling plan of the urban rivers in northwest China. The district section of the Ji River is mainly divided into three parts: (1) the ecological filtration area at the upper reaches; (2) the ecological landscape area at the middle reaches; (3) the ecological purifying area at the lower reaches. Each part has been designed specifically to form the study as a component of the first engineering of Ji River’s reconstruction which has been completed and has got satisfactory ecological effect & economic benefit.
Research to Protect Database by Shaking Random Sampling Interference (SRSI)
Authors: Tung-Shou Chen, Jeanne Chen, Yung-Ching Lin, Ying-Chih Tsai
Venue: Proceedings of the 2009 WRI Global Congress on Intelligent Systems - Volume 03 (2009)

Data mining is used widely by enterprises to mine hidden knowledge from databases. However, mined data containing sensitive trade secret could jeopardize the enterprise's competitive edge. In this paper, we proposed an anti-data mining concept to allow readable mined data that only contained unimportant information. The proposed shaking random sampling interference algorithm (SRSI) inserts interference data within a database to camouflage the real data. The scheme makes use of the data classification step in data mining to introduce interference data that has characteristics similar to the real data. Experimental results using four different classification algorithms showed that the interference data will decrease the accuracy of the database. The original database can be accurately recovered by using the correct parameters used in protecting the database.
Audio-visual speech asynchrony detection using co-inertia analysis and coupled hidden markov models
Authors: Enrique Argones R&#x00fa;a, Herv&#x00e9; Bredin, Carmen Garc&#x00ed;a Mateo, G&#x00e9;rard Chollet, Daniel Gonz&#x00e1;lez Jim&#x00e9;nez
Venue: Pattern Analysis Applications (2009)

This paper addresses the subject of liveness detection, which is a test that ensures that biometric cues are acquired from a live person who is actually present at the time of capture. The liveness check is performed by measuring the degree of synchrony between the lips and the voice extracted from a video sequence. Three new methods for asynchrony detection based on co-inertia analysis (CoIA) and a fourth based on coupled hidden Markov models (CHMMs) are derived. Experimental comparisons are made with several methods previously used in the literature for asynchrony detection and speaker location. The reported results demonstrate the effectiveness and superiority of the proposed new methods based on both CoIA and CHMMs as asynchrony detection methods.
An Algorithm of Static Load Balance Based on Topology for MPLS Traffic Engineering
Authors: Ya-qin Fang, Lin-zhu Wang
Venue: Proceedings of the 2009 WASE International Conference on Information Engineering - Volume 02 (2009)

Aimed to the limitations of traditional routing algorithms and to perfect MPLS application in the domain of load balance, an algorithm of static load balance based on topology is designed in this dissertation. When the shortest path is congested in the network, the algorithm is used to find a low load sub-shortest path for the congestion path based on the bandwidth occupied situation and the topology. By using MATLAB to simulate the algorithms and compared with traditional algorithm, this algorithm can better ease the network congestion problems because of unbalanced allocation of network resource
Sensitivity to spatial resolution of modeling systems designing air quality control policies
Authors: Enrico Pisoni, Claudio Carnevale, Marialuisa Volta
Venue: Environmental Modelling Software (2010)

Different approaches are available in literature to support the modeling of ''what if'' outcomes and the development of strategies, namely scenario analysis, cost-benefit technique, cost-effectiveness technique and multi-objective optimization. All such methods use atmospheric modeling simulations at an appropriate spatial resolution to compute different air quality indexes. This paper analyses the sensitivity of control policies to the spatial resolution of the air quality model, when a multi-objective approach is considered. This assessment is useful for balancing on one hand the request for greater detail in the air quality modeling description and in the strength of the results, and on the other the heavy computational demand required by optimization approaches. The domain selected to implement this sensitivity analysis is the Northern Italy domain, an area often affected by high exposure to PM10, due to very high anthropogenic emissions and particular meteorological conditions.
Egocentric Information Abstraction for Heterogeneous Social Networks
Authors: Cheng-Te Li, Shou-De Lin
Venue: Proceedings of the 2009 International Conference on Advances in Social Network Analysis and Mining (2009)

Social network is a powerful data structure that allows the depiction of relationship information between entities. However, real-world social networks are sometimes too complex for human to pursue further analysis. In this work, an unsupervised mechanism is proposed for egocentric information abstraction in heterogeneous social networks. To achieve this goal, we propose a vector space representation for heterogeneous social networks to identify linear combination of relations as features and compute statistical dependencies as feature values. Then we design several abstraction criteria to distill representative and important information to construct the abstracted graphs for visualization. The evaluations conducted on a real world movie dataset and an artificial crime dataset demonstrate that the abstractions can indeed retain important information and facilitate more accurate and efficient human analysis.
Weighting Structures: Evolutionary Dynamics of Innovation Networks in Virtual Communities
Authors: Vitaliano Barberio, Alessandro Lomi
Venue: Proceedings of the 3d International Conference on Online Communities and Social Computing: Held as Part of HCI International 2009 (2009)

We discuss and illustrate alternative analytical strategies for representing coordination networks in innovative virtual communities bounded by production relationships among participants. We use information on email communication networks reconstructed using data from the Apache Open Source project to give empirical contents to our arguments and to substantiate our claims that: (i) Self-organizing networks provide the basic principles of coordination in such communities; (ii) Once in place, deliberate governance arrangements affect coordination patterns within virtual communities; (iii) Structural properties of communication networks change significantly over time depending on their internal organizational logics, and (iv) Affiliation (a.k.a. two mode) networks provide a useful representation for detecting community structures.
Low-Power ASIP Architecture Exploration and Optimization for Reed-Solomon Processing
Authors: Andreas Genser, Christian Bachmann, Christian Steger, Jos Hulzink, Mladen Berekovic
Venue: Proceedings of the 2009 20th IEEE International Conference on Application-specific Systems, Architectures and Processors (2009)

The advent of the mobile age has heavily changed the requirements of today's communication devices. Data transmission over interference-prone wireless channels requires additional steps of data processing, such as forward error correction, to ensure reliable communication. In this work we present RS(63,55) Reed-Solomon encoding and decoding algorithms according to the IEEE 802.15.4a standard executed on dedicated application-specific processor architectures. Algorithmic as well as architectural modifications to speed up execution and well-known low-power techniques to reduce the power consumption are discussed. The speed-up for our proposed designs compared to a general purpose baseline architecture is up to two orders of magnitude. Power reduction due to clock-gating and guarded evaluation results in a 40% power drop and the energy consumption is decreased up to 60x.
Preprocessing for Optimization of Probabilistic-Logic Models for Sequence Analysis
Authors: Henning Christiansen, Ole Torp Lassen
Venue: Proceedings of the 25th International Conference on Logic Programming (2009)

A class of probabilistic-logic models is considered, which increases the expressibility from HMM's and SCFG's regular and context-free languages to, in principle, Turing complete languages. In general, such models are computationally far too complex for direct use, so optimization by pruning and approximation are needed. The first steps are taken towards a methodology for optimizing such models by approximations using auxiliary models for preprocessing or splitting them into submodels. Evaluation of such approximating models is challenging as authoritative test data may be sparse. On the other hand, the original complex models may be used for generating artificial evaluation data by efficient sampling, which can be used in the evaluation, although it does not constitute a foolproof test procedure. These models and evaluation processes are illustrated in the PRISM system developed by other authors, and we discuss their applicability and limitations.
The Paradigms for the Inquiry in Decision Support System (DSS) and a Design Framework of Cognitive DSS
Authors: Yinghong Zhong, Yingchun Zhong
Venue: Proceedings of the 2009 International Conference on Computational Intelligence and Natural Computing - Volume 01 (2009)

Research paradigm plays an important role in the study of decision support system (DSS). Currently most researches in DSS heavily rely on positivist paradigm while other paradigms are ignored. Firstly this paper compares the paradigms for the inquiry in DSS. Then we propose a design framework of cognitive DSS based on dialectic pluralist paradigm. Some major components of the system and the design of key recommendation algorithm are introduced.
Large-scale localization from wireless signal strength
Authors: Julia Letchner, Dieter Fox, Anthony LaMarca
Venue: Proceedings of the 20th national conference on Artificial intelligence - Volume 1 (2005)

Knowledge of the physical locations of mobile devices such as laptops or PDA's is becoming increasingly important with the rise of location-based services such as specialized web search, navigation and social network applications; furthermore, location information is a key foundation for high-level activity inferencing. In this paper we propose a novel technique for accurately estimating the locations of mobile devices and their wearers from wireless signal strengths. Our technique estimates time-varying device locations on a spatial connectivity graph whose outdoor edges correspond to streets and whose indoor edges represent hallways. staircases, elevators. etc. Use of a hierarchical Bayesian framework for learning a signal strength sensor model allows us not only to achieve higher accuracy than existing approaches. but to overcome many of their limitations. In particular, our technique is able to (1) seamlessly integrate new access points into the model, (2) make use of negative information (not detecting an access point), and (3) bootstrap a sensor model from sparse training data. Experiments demonstrate various properties of our system.
Approximations for Aligned Coloring and Spillage Minimization in Interval and Chordal Graphs
Authors: Douglas E. Carroll, Adam Meyerson, Brian Tagiku
Venue: Proceedings of the 12th International Workshop and 13th International Workshop on Approximation, Randomization, and Combinatorial Optimization. Algorithms and Techniques (2009)

We consider the problem of aligned coloring of interval and chordal graphs. These problems have substantial applications to register allocation in compilers and have recently been proven NP-Hard. We provide the first constant approximations: a $\frac{4}{3}$-approximation for interval graphs and a $\frac{3}{2}$-approximation for chordal graphs. We extend our techniques to the problem of minimizing spillage in these graph types.