ppxscal/embedding_network huggingface dataset:
Testing of a Novel Web Browser Interface for the Chinese Market
Authors: Siu-Tsen Shen, Stephen D. Prior, Kuen-Meau Chen
Venue: Proceedings of the 3rd International Conference on Internationalization, Design and Global Development: Held as Part of HCI International 2009 (2009)

This paper compares the perspicacity, appropriateness and preference of web browser icons from leading software providers with those of a culture-specific design. This online study was conducted in Taiwan and involved 103 participants, who were given three sets of web browser icons to review, namely Microsoft Internet Explorer, Macintosh Safari, and culturally specific icons created using the Culture-Centred Design methodology. The findings of the study show that all three sets have generally high recognition rates, but that some icon functions (e.g. Go/Visit and Favourite) in all three sets have poor recognition rates and are considered inappropriate.
Security Enhancing Compiler for Localization Schemes in Pervasive Sensor Networks
Authors: Ji Young Chun, Yong Ho Kim, Jung Yeon Hwang, Dong Hoon Lee
Venue: Proceedings of the 2009 Eigth IEEE/ACIS International Conference on Computer and Information Science (2009)

Localization is one of the important issues in pervasive sensor networks. Extensive techniques have been proposed recently to make efficient localization schemes. Most existing localization schemes utilize some powerful nodes (called anchor nodes) which can discover their own locations through GPS or manual configuration, and then provide the location information of other sensor nodes. However, since most of these localization schemes have been studied in non-adversarial settings, these schemes are vulnerable to malicious attacks, especially, when anchor nodes are compromised. In this paper, we propose a general compiler that transforms the localization schemes in non-adversarial settings to the localization schemes secure against malicious attacks. This compiler is very useful in that it can cover not only the existing localization schemes but also the new schemes that will be proposed. Moreover, our proposed compiler also supports key management method between sensor nodes and anchor nodes. Therefore, there is no necessity for assuming that each sensor node already has pair-wise key with anchor node.
Characterization of 2n-periodic binary sequences with fixed 2-error or 3-error linear complexity
Authors: Ramakanth Kavuluru
Venue: Designs, Codes and Cryptography (2009)

The linear complexity of sequences is an important measure of the cryptographic strength of key streams used in stream ciphers. The instability of linear complexity caused by changing a few symbols of sequences can be measured using k-error linear complexity. In their SETA 2006 paper, Fu et al. (SETA, pp. 88---103, 2006) studied the linear complexity and the 1-error linear complexity of 2 n -periodic binary sequences to characterize such sequences with fixed 1-error linear complexity. In this paper we study the linear complexity and the k-error linear complexity of 2 n -periodic binary sequences in a more general setting using a combination of algebraic, combinatorial, and algorithmic methods. This approach allows us to characterize 2 n -periodic binary sequences with fixed 2- or 3-error linear complexity. Using this characterization we obtain the counting function for the number of 2 n -periodic binary sequences with fixed k-error linear complexity for k = 2 and 3.
Online query relaxation via Bayesian causal structures discovery
Authors: Ion Muslea, Thomas J. Lee
Venue: Proceedings of the 20th national conference on Artificial intelligence - Volume 2 (2005)

We introduce a novel algorithm, TOQR, for relaxing failed queries over databases, that is, over-constrained DNF queries that return an empty result. TOQR uses a small dataset to discover the implicit relationships among the domain attributes, and then it exploits this domain knowledge to relax the failed query. TOQR starts with a relaxed query that does not include any constraint, and it tries to add to it as many as possible of the original constraints or their relaxations. The order in which the constraints are added is derived from the domain's causal structure, which is learned by applying the TAN algorithm to the small training dataset. Our experiments show that TOQR clearly outperforms other approaches: even when trained on a handful of examples, it successfully relaxes more that 97% of the failed queries; furthermore, TOQR'S relaxed queries are highly similar to the original failed query.
An Enhanced Location Privacy Framework with Mobility Using Host Identity Protocol
Authors: Keiji Maekawa, Yasuo Okabe
Venue: Proceedings of the 2009 Ninth Annual International Symposium on Applications and the Internet (2009)

Location privacy is one of the problems involved in IP mobility. There are two proposed frameworks for this problem based on Host Identity Protocol (HIP); HIP Location Privacy Framework provides partial location privacy with mobility, while BLIND provides complete location privacy without mobility. In this paper, we integrate their strong points, i.e. complete location privacy with mobility. Our framework gives a way to decouple identifiers for mobility from identifiers for end-to-end communications. We construct an extensional mobility management protocol of BLIND, and discuss a trade-off in terms of efficiency and operational cost.
Optimum Design for Fault Detection Filter with Sensor Location
Authors: Tao Peng, Yong Xie, Wei-hua Gui, Jie Chen
Venue: Proceedings of the 2009 WRI Global Congress on Intelligent Systems - Volume 03 (2009)

An optimum design approach to fault detection filter (FDF) with sensor location is proposed. A multi-objective optimization problem based on optimal sensor location for FDF is formulated for linear time invariant system. Optimal sensor location are formed by selecting minimum number measured outputs by sensors available, so that ensures FDF is as high sensitive as possible to faults and simultaneously as enhanced robust as possible against the unknown inputs such as disturbance under the given cost constrain. The dynamics of generated residual by FDF is formulated as non-convex and in terms of bilinear matrix inequality (BMI). The existence condition of multi-objective optimal problem and the solution of observer gain and post-filter matrix are also given and proved.
Extracting salient keywords from instructional videos using joint text, audio and visual cues
Authors: Youngja Park, Ying Li
Venue: Proceedings of the Human Language Technology Conference of the NAACL, Companion Volume: Short Papers on XX (2006)

This paper presents a multi-modal feature-based system for extracting salient keywords from transcripts of instructional videos. Specifically, we propose to extract domain-specific keywords for videos by integrating various cues from linguistic and statistical knowledge, as well as derived sound classes and characteristic visual content types. The acquisition of such salient keywords will facilitate video indexing and browsing, and significantly improve the quality of current video search engines. Experiments on four government instructional videos show that 82% of the salient keywords appear in the top 50% of the highly ranked keywords. In addition, the audiovisual cues improve precision and recall by 1.1% and 1.5% respectively.
PLOW: a collaborative task learning agent
Authors: James Allen, Nathanael Chambers, George Ferguson, Lucian Galescu, Hyuckchul Jung, Mary Swift, William Taysom
Venue: Proceedings of the 22nd national conference on Artificial intelligence - Volume 2 (2007)

To be effective, an agent that collaborates with humans needs to be able to learn new tasks from humans they work with. This paper describes a system that learns executable task models from a single collaborative learning session consisting of demonstration, explanation and dialogue. To accomplish this, the system integrates a range of AI technologies: deep natural language understanding, knowledge representation and reasoning, dialogue systems, planning/agent-based systems and machine learning. A formal evaluation shows the approach has great promise.
Object-Oriented Parallel Image Processing Library
Authors: Evgeny V. Rusin
Venue: Proceedings of the 10th International Conference on Parallel Computing Technologies (2009)

The paper describes the experimental library SSCC_PIPL for image processing on multicomputers. Basic principles of library building, some architectural solutions, and test results are given.
Effect of Cooperative Communication on Steganography Based on NP-Complete Theory
Authors: Libo Liu
Venue: Proceedings of the 2009 International Conference on Environmental Science and Information Application Technology - Volume 01 (2009)

Many security experts would agree that, had it not been for IPv6, the understanding of Internet QoS might never have occurred. In this work, it the private unification of congestion control and Internet QoS are shown, which embodies the important principles of fuzzy complexity theory. Despite the fact that it is never a practical aim, it always conflicts with the need to provide simulated annealing to cyberinformaticians. In conclusion, the efforts are concentrated on showing that the well-known robust algorithm for the refinement of multi-processors is NP-complete.
Red Eye Detection through Bag-of-Keypoints Classification
Authors: Sebastiano Battiato, Mirko Guarnera, Tony Meccio, Giuseppe Messina
Venue: Proceedings of the 15th International Conference on Image Analysis and Processing (2009)

Red eye artifacts are a well-known problem in digital photography. Small compact devices and point-and-click usage, typical of non-professional photography, greatly increase the likelihood for red eyes to appear in acquired images. Automatic detection of red eyes is a very challenging task, due to the variability of the phenomenon and the general difficulty in reliably discerning the shape of eyes.This paper presents a method for discriminating between red eyes and other objects in a set of red eye candidates. The proposed method performs feature-based image analysis and classification just considering the bag-of-keypoints paradigm. Experiments involving different keypoint detectors/descriptors are performed. Achieved results are presented, as well as directions for future work.
Temporal Data Classification Using Linear Classifiers
Authors: Peter Revesz, Thomas Triplet
Venue: Proceedings of the 13th East European Conference on Advances in Databases and Information Systems (2009)

Data classification is usually based on measurements recorded at the same time. This paper considers temporal data classification where the input is a temporal database that describes measurements over a period of time in history while the predicted class is expected to occur in the future. We describe a new temporal classification method that improves the accuracy of standard classification methods. The benefits of the method are tested on weather forecasting using the meteorological database from the Texas Commission on Environmental Quality.
A Neural Network Blind Multi-user Detection Algorithm
Authors: He Li
Venue: Proceedings of the 2009 International Conference on Measuring Technology and Mechatronics Automation - Volume 02 (2009)

This paper proposed a blind multi-user detection algorithm based on neural network. The constant modulus cost function was constructed and cost function with restricted condition was optimized by augmented Lagrange method. Iterative formula of neural network weight and parameters were deduced by Least Mean Square. Blind multi-user detection can be realized by iterative functions of neural network. Simulation indicates the new algorithm improves the ability of anti-MAI., reduces error rate, and speeds up convergence rate.
CAMS: OLAPing Multidimensional Data Streams Efficiently
Authors: Alfredo Cuzzocrea
Venue: Proceedings of the 11th International Conference on Data Warehousing and Knowledge Discovery (2009)

In the context of data stream research, taming the multidimensionality of real-life data streams in order to efficiently support OLAP analysis/mining tasks is a critical challenge. Inspired by this fundamental motivation, in this paper we introduce CAMS (C ube-based A cquisition model for M ultidimensional S treams), a model for efficiently OLAPing multidimensional data streams. CAMS combines a set of data stream processing methodologies, namely (i) the OLAP dimension flattening process, which allows us to obtain dimensionality reduction of multidimensional data streams, and (ii) the OLAP stream aggregation scheme, which aggregates data stream readings according to an OLAP-hierarchy-based membership approach. We complete our analytical contribution by means of experimental assessment and analysis of both the efficiency and the scalability of OLAPing capabilities of CAMS on synthetic multidimensional data streams. Both analytical and experimental results clearly connote CAMS as an enabling component for next-generation Data Stream Management Systems.
A Method to Analyze Preferred MTF for Printing Medium Including Paper
Authors: Masayuki Ukishima, Martti Mäkinen, Toshiya Nakaguchi, Norimichi Tsumura, Jussi Parkkinen, Yoichi Miyake
Venue: Proceedings of the 16th Scandinavian Conference on Image Analysis (2009)

A method is proposed to analyze the preferred Modulation Transfer Function (MTF) of printing medium like paper for the image quality of printing. First, the spectral intensity distribution of printed image is simulated by changing the MTF of medium. Next, the simulated image is displayed on a high-precision LCD to reproduce the appearance of printed image. An observer rating evaluation experiment is carried out to the displayed image to discuss what the preferred MTF is. The appearance simulation of printed image was conducted on particular printing conditions: several contents, ink colors, a halftoning method and a print resolution (dpi). The experiments on different printing conditions can be conducted since our simulation method is flexible about changing conditions.
Advances in the Wetland Ecosystem of China
Authors: Lifang Qiao, Anguo Qi, Shaowei Zhang, Haichao Luo, Xinzheng Li
Venue: Proceedings of the 2009 International Conference on Environmental Science and Information Application Technology - Volume 01 (2009)

The wetland ecosystem is a special natural complex formed by reciprocity between land and water. In recent years, there have many studies about wetland ecosystem in China. The aim of this paper is to summarize the “hot research topics” in the wetland ecosystem researches of China, which include value evaluation of wetland ecosystem services; circulation of materials; evaluation of wetland ecosystem health; wetland ecosystem restoration; landscape structure of wetland ecosystem; resource utilization of wetland ecosystem; wetland ecosystem management and so on. The results show that: the mainly research fields of wetland ecosystem in china are synchronous with the world. The following fields should be paid more attentions in future studies including: landscape structure and change of wetland ecosystem; application of 3S techniquesin wetland ecosystem; effective models of wetland resource utilization; synthesis restoration techniques; effective measures of wetland ecosystem management.
Forest-based translation rule extraction
Authors: Haitao Mi, Liang Huang
Venue: Proceedings of the Conference on Empirical Methods in Natural Language Processing (2008)

Translation rule extraction is a fundamental problem in machine translation, especially for linguistically syntax-based systems that need parse trees from either or both sides of the bi-text. The current dominant practice only uses 1-best trees, which adversely affects the rule set quality due to parsing errors. So we propose a novel approach which extracts rules from a packed forest that compactly encodes exponentially many parses. Experiments show that this method improves translation quality by over 1 BLEU point on a state-of-the-art tree-to-string system, and is 0.5 points better than (and twice as fast as) extracting on 30-best parses. When combined with our previous work on forest-based decoding, it achieves a 2.5 BLEU points improvement over the base-line, and even outperforms the hierarchical system of Hiero by 0.7 points.
Processing, Visualization and Analysis of Medical Images of the Heart: An Example of Fast Prototyping Using MeVisLab
Authors: Samuel Silva, Beatriz Sousa Santos, Joaquim Madeira, Augusto Silva
Venue: Proceedings of the 2009 Second International Conference in Visualisation (2009)

Developing and testing new algorithms for medical imaging processing can be a tiresome task as it often requires an additional set of tools to visualize the data and results and perform validation steps along the development. The integration among all these tools is also very important as it speeds all the process allowing the developer to concentrate on the real problems.This article briefly presents how MeVisLab is beingused as a prototyping platform to develop a semi-automatic segmentation algorithm to extract the left ventricle from 4D MDCT images of the heart and then build a simple framework to perform a preliminary evaluation of the obtained results.
NGOSS Data Management Solution Based on Web Service
Authors: Wenli Dong
Venue: Proceedings of the 2009 International Conference on Computational Intelligence and Natural Computing - Volume 02 (2009)

NGOSS defines a comprehensive, integrated framework for developing and deploying operational and business support systems for communications service providers. With increasing telecommunication services, NGOSS becomes more and more important to improve the management and operation of information and communication services. Collecting network data and configuring network data based on SLA is the important part of NGOSS, and network data become more and more complex with the increasing telecom services and development of distributed and heterogeneous network management systems. To efficiently build distribution transparency and business independent from implementation management environment, we present a NGOSS data management solution based on Web Service, which based on NGOSS data flow framework.
Dynamics Response Characteristic of Moving Beam's Displacement for 300 MN Die Forging Hydraulic Press
Authors: Changzheng Huang, Jianping Tan, Jianxin Yang
Venue: Proceedings of the 2009 International Conference on Measuring Technology and Mechatronics Automation - Volume 02 (2009)

The displacement of moving beam is one of key parameters for 300MN die forging hydraulic press. Its dynamic response characteristic can affect operation control performance of hydraulic press and control precision of moving beam’s displacement. Dynamics mechanical-hydraulic coupling model of moving beam’s drive system and moving beam’s displacement are established with analytical method. The simulation result agrees well with the experimental result. These results of the simulation and test show that: Fisrtly, moving beam’s displacement is decreased gradually with the increasing load under the same open gap while distributor’s spool is being opened and the displacement oscillation phenomena is not occurred. Secondly, moving beam’s displacement is increased gradually with the increasing open gap under the same load. The variation regularity of moving beam’s displacement during the distributor’s spool being opened serves as the foundation for how to control the moving beam’s displacement.
A Novel Dry Electrode for Brain-Computer Interface
Authors: Eric W. Sellers, Peter Turner, William A. Sarnacki, Tobin Mcmanus, Theresa M. Vaughan, Robert Matthews
Venue: Proceedings of the 13th International Conference on Human-Computer Interaction. Part II: Novel Interaction Methods and Techniques (2009)

A brain-computer interface is a device that uses signals recorded from the brain to directly control a computer. In the last few years, P300-based brain-computer interfaces (BCIs) have proven an effective and reliable means of communication for people with severe motor disabilities such as amyotrophic lateral sclerosis (ALS). Despite this fact, relatively few individuals have benefited from currently available BCI technology. Independent BCI use requires easily acquired, good-quality electroencephalographic (EEG) signals maintained over long periods in less-than-ideal electrical environments. Conventional, wet-sensor, electrodes require careful application. Faulty or inadequate preparation, noisy environments, or gel evaporation can result in poor signal quality. Poor signal quality produces poor user performance, system downtime, and user and caregiver frustration. This study demonstrates that a hybrid dry electrode sensor array (HESA) performs as well as traditional wet electrodes and may help propel BCI technology to a widely accepted alternative mode of communication.
New global optimization algorithms for model-based clustering
Authors: Jeffrey W. Heath, Michael C. Fu, Wolfgang Jank
Venue: Computational Statistics Data Analysis (2009)

The Expectation-Maximization (EM) algorithm is a very popular optimization tool for mixture problems and in particular for model-based clustering problems. However, while the algorithm is convenient to implement and numerically very stable, it only produces local solutions. Thus, it may not achieve the globally optimal solution in problems that have a large number of local optima. This paper introduces several new algorithms designed to produce global solutions in model-based clustering. The building blocks for these algorithms are methods from the operations research literature, namely the Cross-Entropy (CE) method and Model Reference Adaptive Search (MRAS). One problem with applying these methods directly is the efficient simulation of positive definite covariance matrices. We propose several new solutions to this problem. One solution is to apply the principles of Expectation-Maximization updating, which leads to two new algorithms, CE-EM and MRAS-EM. We also propose two additional algorithms, CE-CD and MRAS-CD, which rely on the Cholesky decomposition. We conduct numerical experiments of varying complexity to evaluate the effectiveness of the proposed algorithms in comparison to classical EM. We find that although a single run of the new algorithms is slower than a single run of EM, all have the potential for producing significantly better solutions. We also find that although repeat application of EM may achieve similar results, our algorithms provide automated, data-driven decision rules which may significantly reduce the burden of searching for the global optimum.
Automatic Verification of Directory-Based Consistency Protocols
Authors: Parosh Aziz Abdulla, Giorgio Delzanno, Ahmed Rezine
Venue: Proceedings of the 3rd International Workshop on Reachability Problems (2009)

We propose a symbolic verification method for directory-based consistency protocols working for an arbitrary number of controlled resources and competing processes. We use a graph-based language to specify in a uniform way both client/server interaction schemes and manipulation of directories that contain the access rights of individual clients. Graph transformations model the dynamics of a given protocol. Universally quantified conditions defined on the labels of edges incident to a given node are used to model inspection of directories, invalidation loops and integrity conditions. Our verification procedure computes an approximated backward reachability analysis by using a symbolic representation of sets of configurations. Termination is ensured by using the theory of well-quasi orderings.