ppxscal/embedding_network huggingface dataset:
A fast and accurate online self-organizing scheme for parsimonious fuzzy neural networks
Authors: Ning Wang, Meng Joo Er, Xianyao Meng
Venue: Neurocomputing (2009)

In this paper, we present a fast and accurate online self-organizing scheme for parsimonious fuzzy neural networks (FAOS-PFNN), where a novel structure learning algorithm incorporating a pruning strategy into new growth criteria is developed. The proposed growing procedure without pruning not only speeds up the online learning process but also facilitates a more parsimonious fuzzy neural network while achieving comparable performance and accuracy by virtue of the growing and pruning strategy. The FAOS-PFNN starts with no hidden neurons and parsimoniously generates new hidden units according to the proposed growth criteria as learning proceeds. In the parameter learning phase, all the free parameters of hidden units, regardless of whether they are newly created or originally existing, are updated by the extended Kalman filter (EKF) method. The effectiveness and superiority of the FAOS-PFNN paradigm is compared with other popular approaches like resource allocation network (RAN), RAN via the extended Kalman filter (RANEKF), minimal resource allocation network (MRAN), adaptive-network-based fuzzy inference system (ANFIS), orthogonal least squares (OLS), RBF-AFS, dynamic fuzzy neural networks (DFNN), generalized DFNN (GDFNN), generalized GAP-RBF (GGAP-RBF), online sequential extreme learning machine (OS-ELM) and self-organizing fuzzy neural network (SOFNN) on various benchmark problems in the areas of function approximation, nonlinear dynamic system identification, chaotic time-series prediction and real-world regression problems. Simulation results demonstrate that the proposed FAOS-PFNN algorithm can achieve faster learning speed and more compact network structure with comparably high accuracy of approximation and generalization.
A Novel Multi-Swarm Particle Swarm Optimization Algorithm Applied in Active Contour Model
Authors: Rui Li, Yirong Guo, Yujuan Xing, Ming Li
Venue: Proceedings of the 2009 WRI Global Congress on Intelligent Systems - Volume 01 (2009)

PSO (particle swarm optimization) algorithm provides a robust and efficient approach for searching for the object's concavities with the snake model.However, since single particle swarm optimization algorithm converges slowly and easily converges to local optima, it is not suitable well to be applied in active contour model directly. In this paper, a novel multi-swarm particle swarm optimization method was proposed to solve this problem. The proposed algorithm could expand the control point of the searching area and optimize convergence speed. It sets swarm for each control point and then every swarm search best point collaboratively through shared information, so it avoids the premature deficiency in traditional PSO algorithm. Compared our proposed algorithm with traditional algorithm, the experimental results showed that our method has superior performance than conventional snake model without spending extra time.
Player Experience Evaluation: An Approach Based on the Personal Construct Theory
Authors: Francesco Bellotti, Riccardo Berta, Alessandro Gloria, Ludovica Primavera
Venue: Proceedings of the 8th International Conference on Entertainment Computing (2009)

The scientific and industrial community related to the videogame (VG) research and business is ever more concerned about the need for proper evaluation and assessment of games. This paper proposes an assessment methodology based on the Personal Construct Theory (PCT). The PCT allows identifying constructs can be processed to define a space where domain-relevant items --- VGs, in our case - can be positioned. The main praise of PCT is that the test-leading researcher does not supply users with a predefined set of constructs, which may bias the evaluation process. Moreover, PCT joins qualitative aspects with a quantitative evaluation of their relevance, which is particularly useful for an operational approach also to game design. In this paper, we study the application of the PCT to the particular case of the evaluation of whole typologies of VGs. Discussing the results, we draw and highlight that VGs are perceived as engaging challenges where personal abilities are continuously put to the test. This stresses the reactive nature of VGs and the fact that players like being stimulated and developing and testing their reaction capabilities.
The design of a mixed-reality book: Is it still a real book?
Authors: Raphael Grasset, Andreas Dunser, Mark Billinghurst
Venue: Proceedings of the 7th IEEE/ACM International Symposium on Mixed and Augmented Reality (2008)

In this paper we present the results of our long term development of a mixed reality book. Most previous work in the area has focused on the technology of augmented reality books, such as providing registration using fiducial markers. In this work, however, we focused on exploring the design and development process of this type of application in a broader sense. We studied the semantics of a mixed reality book, the design space and the user experience with this type of interface.
Proceedings of the Conference on Empirical Methods in Natural Language Processing
Venue: Annual Meeting of the ACL (2008)

Welcome to the 2008 Conference on Empirical Methods in Natural Language Processing! The conference is organized under the auspices of SIGDAT, the ACL Special Interest Group for linguistic data and corpus-based approaches to natural language processing. It is co-located this year with AMTA 2008 and the International Workshop on Spoken Language Translation, in Honolulu, Hawaii. EMNLP received 385 submissions. We were able to accept 116 papers in total (an acceptance rate of 30%). 81 of the papers (21%) were accepted for oral presentation, and 35 (9%) for poster presentation. Two poster papers were subsequently withdrawn after acceptance. The papers were selected by a program committee of 15 area chairs, from Asia, Europe, and North America, assisted by a panel of 339 reviewers. This year EMNLP introduced an author response period. Authors were able to read and respond to the reviews of their paper before the program committee made a final decision. They were asked to correct factual errors in the reviews and answer questions raised in the reviewer comments. The intention was to help produce more accurate reviews. In some cases, reviewers changed their scores in view of the authors' response and the area chairs read all responses carefully prior to making recommendations for acceptance.
Mechanism and Design of EV Changing Modes Propulsion System
Authors: Lipeng Zhang, Cheng Lin, Bingnan Qi
Venue: Proceedings of the 2009 International Conference on Measuring Technology and Mechatronics Automation - Volume 03 (2009)

In order to make full use of the advantages of every electric vehicle (EV) driveway and reduce the demand of motor properties, a changing modes propulsion system was designed. According to the requirement of EV running conditions to power performance, this system can achieve modes transfusion between single motor driving, two motors joint driving and independent wheel driving. The working mechanism of this system and its influence to EV dynamic performance were analyzed. Because of realizing single motor driving, this system can effectively avoid the defects of EV abnormal running when one of the motors unexpected failure. Besides this, it has two speed transmissions and can effectively enhance the power performance of EV. So it is more flexible and reliable than independent wheel driving or focus driving, and can effectively improve the reliability and continued mileage of EV.
Composing Visual Syntax for Domain Specific Languages
Authors: Luis Pedro, Matteo Risoldi, Didier Buchs, Bruno Barroca, Vasco Amaral
Venue: Proceedings of the 13th International Conference on Human-Computer Interaction. Part II: Novel Interaction Methods and Techniques (2009)

With the increasing interest in metamodeling techniques for Domain Specific Modeling Languages (DSML) definition, there is a strong need to improve the language modeling process. One of the problems to solve is language evolution. Possible solutions include maximizing the reuse of metamodel patterns, composing them to form new, more expressive DSMLs.In this paper we improve the process of rapid prototyping of DSML graphical editors in meta-modeling tools, by defining composition rules for the graphical syntax layer. The goal is to provide formally defined operators to specify what happens to graphical mappings when their respective metamodels are composed. This improves reuse of Domain Specific Modeling Languages definitions and reduces development time.
Privacy-Preserving Information Markets for Computing Statistical Data
Authors: Aggelos Kiayias, Bülent Yener, Moti Yung
Venue: Financial Cryptography and Data Security: 13th International Conference, FC 2009, Accra Beach, Barbados, February 23-26, 2009. Revised Selected Papers (2009)

Consider an "information market" where private and potentially sensitive data are collected, treated as commodity and processed into aggregated information with commercial value. Access and processing privileges of such data can be specified by enforceable "service contracts" and different contract rules can be associated with different data fields.Clearly the sources of such data, which may include companies, organizations and individuals, must be protected against loss of privacy and confidentiality. However, mechanisms for ensuring privacy per data source or data field do not scale well due to state information that needs to be maintained. We propose a scalable approach to this problem which assures data sources that the information will only be revealed as an aggregate or as part of a large set (akin of k-anonymity constraints).In particular, this work presents a model and protocols for implementing "privacy preserving data markets" in which privacy relies on the distribution of the processing servers and the compliance of some (a quorum) of them with the service contract. We then show how to compute statistical information important in financial and commercial information systems, while keeping individual values private (e.g., revealing only statistics that is performed on a large enough sample size). In detail, we present two novel efficient protocols for privacy-preserving S-moments computation (for S = 1,2,...) and for computing the Pearson correlation coefficients.
Geometrical Method for Description of the 6-PGK Parallel Robot's Workspace
Authors: Liviu Moldovan
Venue: Proceedings of the 2008 First International Conference on Complexity and Intelligence of the Artificial and Natural Complex Systems. Medical Applications of the Complex Systems. Biomedical Computing (2008)

The 6-PGK parallel robot has a new configuration different from the Stewart platform. In this paper a geometrical method to determine exactly the boundary of the workspace in a horizontal cross-section, due to the limitations on the range motion of the prismatic kinematics pairs is presented. This method is illustrated with examples.
A parallel solution to the HIP game based on genetic algorithms
Authors: Tatiana Tambouratzis
Venue: International Journal of Intelligent Systems (2009)

In this piece of research, genetic algorithms are put forward for solving the HIP game. The proposed parallel approach manipulates candidate solutions via mutation and selection; no crossover has been employed. The population is limited to one candidate solution per generation, thus keeping the computational complexity of the approach to a minimum. It is shown that the proposed approach is superior to the approaches reported in the literature: Solutions are more speedily provided, whereas the frequency of finding a solution is significantly higher; furthermore, considerably more complex instances of the HIP game are successfully solved. &copy; 2009 Wiley Periodicals, Inc.
Development and Experimental of a Multifunctional Instrument for Fabricating Glass Microfluidic Device
Authors: Lili Mu, Huawei Jin, Liya Hou
Venue: Proceedings of the 2009 International Conference on Measuring Technology and Mechatronics Automation - Volume 01 (2009)

In order to obtain a better microflow characteristicsof a transparent microfluid device, the microfluidic deviceinstrument based on the glass material is designed in the paper.Ordinary borosilicate glass capillary heated to hot molten state and drawn to shape as the blank can be produced into microneedle, microchannel, the four-way microchannel et al.The influencing parameters to the dimention of microneedle are analysised by the experiment based on the two factors of pull force and temperature. The four-way microchannel with the thermal processing technology is produced by opening microhole and welding way. Finally, the influencing factors of microhole are studied too. The drawn instrument has multifunctions and low cost with simple structure.
Protecting digital circuits against hold time violation due to process variability
Authors: Gustavo Neuberger, Gilson Wirth, Ricardo Reis
Venue: Proceedings of the 22nd Annual Symposium on Integrated Circuits and System Design: Chip on the Dunes (2009)

Statistical process variations are a critical issue to define circuit design strategies to ensure high yield in sub-100nm technologies. This work focuses on hold time violation probabilities in sub-100 nm technologies. The variability in flip-flop race immunity and clock skew is evaluated, and a methodology for the estimation of hold time violation probability is developed. This violation probability is analyzed at different technologies, flip-flop strength, supply voltage and padding. Then three different methods to protect against hold time violations are evaluated: Vdd reduction, race immunity increase, and padding. Each of them has different advantages and drawbacks that must be taken into account. It is shown that at design time the most effective method is padding. An algorithm to automatically insert padding in digital circuits considering process variability is presented. The proposed algorithm will be evaluated compared to other ways to protect against violations.
A new multiobjective simulated annealing based clustering technique using symmetry
Authors: Sriparna Saha, Sanghamitra Bandyopadhyay
Venue: Pattern Recognition Letters (2009)

In this paper, we have proposed a multiobjective clustering technique which optimizes simultaneously two objectives, one reflecting the total 'goodness' present in the data set in terms of total compactness (measured using Euclidean distance) of the clusters, and the other reflecting the total symmetry present in the clusters of the data set. The proposed algorithm uses a simulated annealing based multiobjective optimization method as the underlying optimization criterion. Center based encoding is used. The proposed multiobjective clustering technique is able to suitably evolve these cluster centers in such a way so that the two objectives are optimized 'simultaneously'. Assignment of points to different clusters is done based on the newly developed point symmetry based distance rather than the Euclidean distance. Results on eight artificial and six real-life data sets show that the proposed technique is well-suited to detect true partitioning from data sets with clusters having either the hyperspherical shape or point symmetric structure. Results are compared with those obtained by five existing clustering techniques, one multiobjective clustering technique, MOCK, average linkage clustering algorithm, expectation maximization clustering algorithm, well-known genetic algorithm based K-means clustering technique (GAK-means) and a newly developed genetic algorithm with point symmetry based clustering technique (GAPS).
Performance of some metaheuristic algorithms for localization in wireless sensor networks
Authors: Aloor Gopakumar, Lillykutty Jacob
Venue: International Journal of Network Management (2009)

In this paper we propose two novel and computationally efficient metaheuristic algorithms based on tabu search (TS) and particle swarm optimization (PSO) principles for locating the sensor nodes in a distributed wireless sensor network (WSN) environment. The WSN localization problem is formulated as a non-linear optimization problem with mean squared range error resulting from noisy distance measurement as the objective function. Unlike gradient descent methods, both TS and PSO methods ensure minimization of the objective function without the solution being trapped into local optima. We further implement a refinement phase with error propagation control for improvement of the results. The performance of the proposed algorithms are compared with each other and also against simulated annealing based WSN localization. The effects of range measurement error, anchor node density and uncertainty in the anchor node position on localization performance are also studied through various simulations. The simulation results establish better accuracy, computational efficiency and convergence characteristics for TS and PSO methods. Further, the efficacy of the proposed methods is verified with data collected from an experimental sensor network reported in the literature.
User acceptance of mobile TV services
Authors: Eija Kaasinen, Minna Kulju, Tuomo Kivinen, Virpi Oksman
Venue: Proceedings of the 11th International Conference on Human-Computer Interaction with Mobile Devices and Services (2009)

Mobile digital television technology facilitates broadcast TV on a mobile phone as well as interactive add-on services provided on top of the selected TV channel. In this paper we describe the results of a six-month field trial where 27 users were evaluating commercially available mobile TV services and 10 different pilot services. Mobile TV found a role in the everyday lives of the users as an extension to ordinary TV. The users appreciated easy and continuous access to TV contents. The results highlight that short usage situations typical to mobile TV use are hindering the adoption of new add-on services. The adoption can be supported by using content, appearance or functionality familiar from other media. The main problems with add-on services were related to knowing about the mere existence of these services and their contents as well as understanding the concept of services available only during a certain TV show.
A comparison of Bayesian estimators for unsupervised Hidden Markov Model POS taggers
Authors: Jianfeng Gao, Mark Johnson
Venue: Proceedings of the Conference on Empirical Methods in Natural Language Processing (2008)

There is growing interest in applying Bayesian techniques to NLP problems. There are a number of different estimators for Bayesian models, and it is useful to know what kinds of tasks each does well on. This paper compares a variety of different Bayesian estimators for Hidden Markov Model POS taggers with various numbers of hidden states on data sets of different sizes. Recent papers have given contradictory results when comparing Bayesian estimators to Expectation Maximization (EM) for unsupervised HMM POS tagging, and we show that the difference in reported results is largely due to differences in the size of the training data and the number of states in the HMM. We invesigate a variety of samplers for HMMs, including some that these earlier papers did not study. We find that all of Gibbs samplers do well with small data sets and few states, and that Variational Bayes does well on large data sets and is competitive with the Gibbs samplers. In terms of times of convergence, we find that Variational Bayes was the fastest of all the estimators, especially on large data sets, and that explicit Gibbs sampler (both pointwise and sentence-blocked) were generally faster than their collapsed counterparts on large data sets.
Information relationships: the source of useful and usable content
Authors: Michael J. Albers
Venue: Proceedings of the 27th ACM international conference on Design of communication (2009)

Effective communication requires more than what the content says and how it's formatted and instead requires focusing on the interrelationships between information elements and how those interrelationships fit together to help a person understand the situation. The design presented to readers must be an integrated presentation that supports achieving their goals within their situational context. For an integrated presentation to help people find and use content, it must provide the cross-references and interconnections between different information elements to form the highly interconnected structures that typify most complex problems. Unfortunately, this integrated presentation varies between each audience group and normally involves connections between information elements which have little in common with a conventional information hierarchy or architecture.
The Improved Algorithm of ART2 in Data Mining
Authors: Liangun Li, Bin Zhang, Yuanyuan Che
Venue: Proceedings of the 2009 First International Workshop on Database Technology and Applications (2009)

Clustering analysis is an important research topic in data mining field, and it is one of main task of data mining. Adaptive Resonance Theory (ART) neural network is an effective method to realize clustering. But the classical ART2 network has some shortcoming and insufficiency in data clustering application. The classical ART2 network must designate p alert parameters before the network training, the configuration of this parameter has a direct impact on the network clustering result. The classical ART2 uses the "winner takes all" competition rule, in general only considers winning neuron information, but neglects other useful neuron information in the output layer. The classical ART2 network output is essentially one-dimension structure, is unable to manifest the whole relation to entire input mode space. By improving the structure of ART2, ample considering amplitude information of mining object, which can decrease the requirement of vigilance parameter and earn cluster result with administrative level structure .The validity of this improve is verified by experimental result.
Hidden Topic Analysis Based Formal Framework for Finding Experts in Metadata Corpus
Authors: Hao Wu, Yijian Pei, Jiang Yu
Venue: Proceedings of the 2009 Eigth IEEE/ACIS International Conference on Computer and Information Science (2009)

As a retrieval task, expert finding has recently attracted much attention. And various methods have been proposed to rank expert candidates against topical query. The most efficient approach is document-based method that treats supporting documents as a “bridge” and ranks the candidates based on the co-occurrences of topic and candidate mentions in the supporting documents.However, such kind of methods models relevance between query and candidates on the much lower and hence less ambiguous level. It lacks of the capability to capture the hidden semantic association between queries and candidates. In this paper, we propose a hidden topic analysis based approach to estimate the relevance between query and candidates. It models query and supporting document as a word-topic-document association instead of the word-document association in language model. In addition, the prior knowledge of supporting document is considered to favor expert ranking. The empirical results on metadata corpus have demonstrated the model can effectively catch the semantic association between queries and candidates, thus improves the performance of expert finding.