ppxscal/embedding_network huggingface dataset:
Symmetry Detection for Multi-object Using Local Polar Coordinate
Authors: Yuanhao Gong, Qicong Wang, Chenhui Yang, Yahui Gao, Cuihua Li
Venue: Proceedings of the 13th International Conference on Computer Analysis of Images and Patterns (2009)

In this paper, a novel method is presented, which detects symmetry axes for multi-object. It uses vertical line detection method in local polar coordinate. The approach costs little computation and can get efficient results, which means that it can be used in database applications. The ACM Portal is published by the Association for Computing Machinery. Copyright © 2010 ACM, Inc. Terms of Usage Privacy Policy Code of Ethics Contact Us Useful downloads: Adobe Acrobat QuickTime Windows Media Player Real Player
A unification of extensive-form games and Markov decision processes
Authors: H. Brendan McMahan, Geoffrey J. Gordon
Venue: Proceedings of the 22nd national conference on Artificial intelligence - Volume 1 (2007)

We describe a generalization of extensive-form games that greatly increases representational power while still allowing efficient computation in the zero-sum setting. A principal feature of our generalization is that it places arbitrary convex optimization problems at decision nodes, in place of the finite action sets typically considered. The possibly-infinite action sets mean we must "forget" the exact action taken (feasible solution to the optimization problem), remembering instead only some statistic sufficient for playing the rest of the game optimally. Our new model provides an exponentially smaller representation for some games; in particular, we show how to compactly represent (and solve) extensive-form games with outcome uncertainty and a generalization of Markov decision processes to multi-stage adversarial planning games.
Hand Pointing Accuracy for Vision-Based Interactive Systems
Authors: Kelvin Cheng, Masahiro Takatsuka
Venue: Proceedings of the 12th IFIP TC 13 International Conference on Human-Computer Interaction: Part II (2009)

Vision-based hand pointing interactive systems always assume implicitly that users' physical pointing accuracy is perfect. However, this may not be the case. We investigated the accuracy provided by users in three pointing strategies. Result showed that pointing inaccuracy can be as high as 239mm at 3 metres away and suggest that the line-up method provides the best accuracy overall.
Sensitivity tests on relations between tsunami signal and seismic rupture characteristics: The 26 December 2004 Indian Ocean event case study
Authors: M. Ioualalen
Venue: Environmental Modelling Software (2009)

The long wave elevation of a tsunami is closely related to the characteristics of its triggering source. Tide gauges, sea level anomaly altimeters can all be used to measure the amplitude of the wave. Numerical modeling can also be used to approximate tsunami propagation based upon a certain parameterisation of the source describing the mode of generation. Once a robust numerical model has been developed, the simulated wave sequence and the various hydrodynamic observations can be compared to develop a better characterization of the tsunami source. This procedure may be used to refine the description of a tsunami source derived from seismological instrumentations. Numerical sensitivity tests of a tsunami propagation model were used to address whether a simple tide gauge record may help in better identifying the nature of the rupture process. Specifically, four different pure thrust faultings - reverse/normal faults and two opposite dipping orientations - of the 26 December 2004 Indian Ocean tsunami were simulated. The model chosen for the investigation used the representation of Okada, Y., [1985. Surface deformation due to shear and tensile faults in a half-space. Bull. Seism. Soc. Am. 75 (4), 1135-1154] to describe the rupture process and the Funwave numerical model to simulate tsunami propagation. The author finds that it is possible to identify the best-fitted scenario among the four, depending on the nature of the leading wave (crest or trough) and the ratio between the first crest amplitudes. It depends, however, on the dipping amount as the trough/crest dipole reverses at around 43^o. Consequently, the depth of the earthquake (location of the epicenter within the interplate slab) also controls the nature of the leading wave (crest or depression).
TSAR: Type-Specific Adaptive Routing for Reliability in Event-based Middleware
Authors: Shruti P. Mahambre, Umesh Bellur
Venue: Proceedings of the Third ACM International Conference on Distributed Event-Based Systems (2009)

In this paper we focus on providing reliability as a service guarantee to subscribers in an Event Based Middleware. We provide an additional level of granularity to subscribers by enabling them to specify individual reliability requirements on a per event type basis. We present the TSAR algorithm which uses persistent path-quality information, in the form of reliability-estimates to establish routes. Initial results show TSAR establishes higher quality routes as compared to it's type-agnostic counterpart with a significantly lower message complexity.
Static and Dynamic Human Shape Modeling
Authors: Zhiqing Cheng, Kathleen Robinette
Venue: Proceedings of the 2nd International Conference on Digital Human Modeling: Held as Part of HCI International 2009 (2009)

Recent developments in static human shape modeling based on range scan data and dynamic human shape modeling from video imagery are reviewed. The topics discussed include shape description, surface registration, hole filling, shape characterization, and shape reconstruction for static modeling and pose identification, skeleton modeling, shape deformation, motion tracking, dynamic shape capture and reconstruction, and animation for dynamic modeling. A new method for human shape modeling is introduced.
The Application of VoiceXML to E-commerce
Authors: Liu Wenyun, Wang Jinglei
Venue: Proceedings of the 2009 International Forum on Information Technology and Applications - Volume 03 (2009)

VoiceXML (Voice eXtensible Markup Language) is a language of the W3C to create voice-user interfaces, particularly for the telephone. It uses speech recognition and touchtone (DTMF keypad) for input, and pre-recorded audio and text-to-speech synthesis (TTS) for output. The text-to-speech synthesis feature opens new perspectives for e-commerce. We are no longer restricted to prerecorded audio but can bring any text to the ear of the user - a user that could be visually impaired and needs a voice channel to communicate - or a user who can read but who prefers to listen. This paper first shows the importance of voice interface to E-commerce, and then presents the VoiceXML techniques and a certain business application. At last, we draw some conclusions.
Generalized PID Algorithm for Batch Reactor's Temperature Control
Authors: Xiaodong Zhao, Weihong Zheng
Venue: Proceedings of the 2009 WRI Global Congress on Intelligent Systems - Volume 01 (2009)

PID algorithms for batch reactor's temperature control of special plants or systems have been used widely. Adaptive PID control is also used to handle the model changing problems. This paper presents a new adaptive control that is based on PID algorithm, expert system and neural networks. Its main structure is a generalized PID (GPID) controller. Neural networks is applied to adjust the GPID parameters and the initial values of the neural networks parameters are given by an expert system.
Extraction of Discriminative Gene Modules between Two-Class DNA Microarray Data and Its Application to Chronic Loneliness Patients' Dataset
Authors: Yoshifumi Okada, Terufumi Inoue, Tomomasa Nagashima
Venue: Proceedings of the 2009 International Conference on Biometrics and Kansei Engineering (2009)

Development of techniques for assisting to discover useful biomarkers for disease diagnosis is a crucial issue in the field of Biometrics as well as clinical area. In this paper, we propose a novel method that searches for informative gene sets (called modules) for discriminating between different but similar two disease classes in DNA microarray data. This method enables us to identify discriminatory modules that are not only differential between the classes but also specific within respective classes. The proposed method is applied to a dataset obtained from peripheral bloods of individuals with chronic loneliness, and the biological functions of the extracted discriminative modules are evaluated by the functional enrichment analysis. As a result, we show that the proposed method can identify not only biologically meaningful genes as suggested by earlier studies but also novel findings not shown so far.
A Color Image Segmentation Using Inhibitory Connected Pulse Coupled Neural Network
Authors: Hiroaki Kurokawa, Shuzo Kaneko, Masato Yonekawa
Venue: Advances in Neuro-Information Processing: 15th International Conference, ICONIP 2008, Auckland, New Zealand, November 25-28, 2008, Revised Selected Papers, Part II (2009)

A Pulse Coupled Neural Network (PCNN) is a kind of numerical model of cat visual cortex and it can explain synchronous dynamics of neurons' activity in the visual cortex. On the other hand, as an engineering application, it is shown that the PCNN can applied to the image processing, e.g. segmentation, edge enhancement, and so on. The PCNN model consists of neurons and two kind of inputs, namely feeding inputs and linking inputs with leaky integrators. These inputs lead to discrete time evolution of its internal state and neurons generate spike output according to the internal state. The linking and feeding inputs are received from the neurons' receptive field which is defined by excitatory synaptic weights. In this study, we propose a PCNN with inhibitory connections and describe an application to a color image segmentation. In proposed model, inhibitory connections are defined by negative synaptic weights among specific neurons which detect RGB component of particular pixel of the image. Simulation results show successful results for the color image segmentation.
Variational Graph Embedding for Globally and Locally Consistent Feature Extraction
Authors: Shuang-Hong Yang, Hongyuan Zha, S. Kevin Zhou, Bao-Gang Hu
Venue: Proceedings of the European Conference on Machine Learning and Knowledge Discovery in Databases: Part II (2009)

Existing feature extraction methods explore either global statistical or local geometric information underlying the data. In this paper, we propose a general framework to learn features that account for both types of information based on variational optimization of nonparametric learning criteria. Using mutual information and Bayes error rate as example criteria, we show that high-quality features can be learned from a variational graph embedding procedure, which is solved through an iterative EM-style algorithm where the E-Step learns a variational affinity graph and the M-Step in turn embeds this graph by spectral analysis. The resulting feature learner has several appealing properties such as maximum discrimination, maximum-relevance- minimum-redundancy and locality-preserving. Experiments on benchmark face recognition data sets confirm the effectiveness of our proposed algorithms.
On the Security of Tandem-DM
Authors: Ewan Fleischmann, Michael Gorski, Stefan Lucks
Venue: Fast Software Encryption: 16th International Workshop, FSE 2009 Leuven, Belgium, February 22-25, 2009 Revised Selected Papers (2009)

We provide the first proof of security for Tandem-DM, one of the oldest and most well-known constructions for turning a block cipher with n-bit block length and 2n-bit key length into a 2n-bit cryptographic hash function. We prove, that when Tandem-DM is instantiated with AES-256, block length 128 bits and key length 256 bits, any adversary that asks less than 2120.4 queries cannot find a collision with success probability greater than 1/2. We also prove a bound for preimage resistance of Tandem-DM.Interestingly, as there is only one practical construction known turning such an (n,2n) bit block cipher into a 2n-bit compression function that has provably birthday-type collision resistance (FSE'06, Hirose), Tandem-DM is one out of two constructions that has this desirable feature.
Inferring Causal Relations from Multivariate Time Series: A Fast Method for Large-Scale Gene Expression Data
Authors: Yinyin Yuan, Chang-Tsun Li
Venue: Proceedings of the 2009 Ninth IEEE International Conference on Bioinformatics and Bioengineering (2009)

Various multivariate time series analysis techniques have been developed with the aim of inferring causal relations between time series. Previously, these techniques have proved their effectiveness on economic and neurophysiological data,which normally consist of hundreds of samples. However, in their applications to gene regulatory inference, the small sample size of gene expression time series poses an obstacle. In this paper, we describe some of the most commonly used multivariate inference techniques and show the potential challenge related to gene expression analysis. In response, we propose a directed partial correlation (DPC) algorithm as an efﬁcient and effective solution to causal/regulatory relations inference on small sample gene expression data. Comparative evaluations on the existing techniques and the proposed method are presented. To draw reliable conclusions, a comprehensive benchmarking on data sets of various setups is essential. Three experiments are designed to assess these methods in a coherent manner. Detailed analysis of experimental results not only reveals good accuracy of the proposed DPC method in large-scale prediction, but also gives much insight into all methods under evaluation.
Accelerating a Virtual Ecology Model with FPGAs
Authors: Julien Lamoureux, Tony Field, Wayne Luk
Venue: Proceedings of the 2009 20th IEEE International Conference on Application-specific Systems, Architectures and Processors (2009)

This paper describes the acceleration of virtual ecology models using field-programmable gate arrays (FPGAs). Our approach targets models generated by the Virtual Ecology Workbench (VEW); an existing tool used by biological oceanographers to build and analyze models of the plankton ecosystem in the upper ocean.Depending on the plankton study and required level of detail, the logic, memory, and data transfer requirements of the generated models can vary significantly.Using FPGAs, hardware implementations can be customized to the specific requirements of the ecological system under study and provide significant speed-ups compared to software implementations.This paper describes a framework for maximizing the speedup of VEW generated models implemented on FPGA-based acceleration platforms and then describes the implementation of a typical VEW generated model to validate the framework and demonstrate that significant speedups are possible.Based on timing and area estimates from a commercial synthesis tool, the example model implemented on a Celoxica RCHTX acceleration board featuring a Xilinx Virtex-4 FPGA performs 39 times faster at 150 MHz than the software implementation on an AMD Opteron 2200 series CPU at 1.0 GHz.
TapSongs: tapping rhythm-based passwords on a single binary sensor
Authors: Jacob Otto Wobbrock
Venue: Proceedings of the 22nd annual ACM symposium on User interface software and technology (2009)

TapSongs are presented, which enable user authentication on a single "binary" sensor (e.g., button) by matching the rhythm of tap down/up events to a jingle timing model created by the user. We describe our matching algorithm, which employs absolute match criteria and learns from successful logins. We also present a study of 10 subjects showing that after they created their own TapSong models from 12 examples (
Challenge and solutions of NAT traversal for ubiquitous and pervasive applications on the Internet
Authors: Yaw-Chung Chen, Wen-Kang Jia
Venue: Journal of Systems and Software (2009)

Network Address Translator (NAT) has brought up many changes and opportunities to the Internet. How do the ubiquitous and pervasive applications coexist with NAT and interoperate with each other? In this article, we discuss the essence of NAT sensitive applications as well as the challenge and response for various NAT traversal solutions. All questions pointed to redesign a new NAT framework with a major change to accommodate NAT problems all at once. We introduce a novel next generation NAT (NATng) framework, which consists of a Bi-directional NAT (BNAT) and a Domain Name System Application Level Gateway (DNS_ALG) with a Border Network Address Translator Control Protocol (BNATCP) function to control all BNATs. The above components coordinate and provide bidirectional access capability between intranet and Internet, so all private hosts can be addressed via Fully Qualified Domain Name (FQDN). Logistically, NATng extends the IPv4 address space from 2^3^2to2^4^8 or even more. It features high potential to solve the problems for ubiquitous and pervasive applications which may encounter IPv4 address exhaustion on the current Internet.
Novel Machine Learning for Hand Gesture Recognition Using Multiple View
Authors: Tianding Chen
Venue: Proceedings of the 2009 IITA International Conference on Control, Automation and Systems Engineering (case 2009) (2009)

Different from the conventional communication method between users and machines, we use hand gesture to control the equipments. This paper presents hand gesture recognition applied human-computer interaction (HCI) system. It presents new method to automatic gesture area segmentation and orientation normalization of the gesture. It is not mandatory for the user to keep upright gestures in the regular position, the system segments and normalizes the gestures automatically. The method is an unsupervised nonlinear dimensionality reduction approach that utilizes the local linearity to discover the low dimensional manifold embedded in the high dimensional space. This suggests that the method may preserve the neighborhood configuration for the nonlinear structure of the multi-view hand shape data distribution. The experiment shows this method is very accurate. The gesture pointing accuracy of our system is measured by 80 times of pointing recognition test, the success rate above 90%.
Estimating Steganographic Fisher Information in Real Images
Authors: Andrew D. Ker
Venue: Information Hiding: 11th International Workshop, IH 2009, Darmstadt, Germany, June 8-10, 2009, Revised Selected Papers (2009)

This paper is concerned with the estimation of steganographic capacity in digital images, using information theoretic bounds and very large-scale experiments to approximate the distributions of genuine covers. The complete distribution cannot be estimated, but with carefully-chosen algorithms and a large corpus we can make local approximations by considering groups of pixels. A simple estimator for the local quadratic term of Kullback-Leibler divergence (Steganographic Fisher Information) is presented, validated on some synthetic images, and computed for a corpus of covers. The results are interesting not so much for their concrete capacity estimates but for the comparisons they provide between different embedding operations, between the information found in differently-sized and -shaped pixel groups, and the results of DC normalization within pixel groups. This work suggests lessons for the future design of spatial-domain steganalysis, and also the optimization of embedding functions.
Coronary artery disease prediction method using linear and nonlinear feature of heart rate variability in three recumbent postures
Authors: Heon Gyu Lee, Wuon-Shik Kim, Ki Yong Noh, Jin-Ho Shin, Unil Yun, Keun Ho Ryu
Venue: Information Systems Frontiers (2009)

In present study, we proposed not only a novel methodology useful in developing the various features of heart rate variability (HRV), but also a suitable prediction model to enhance the reliability of medical examinations and treatments for coronary artery disease. In order to develop the various features of HRV, we analyzed HRV for three recumbent postures. The interaction effects between the recumbent postures and groups of normal people and heart patients were observed based on linear and nonlinear features of HRV. Forty-three control subjects and 64 patients with coronary artery disease participated in this study. In order to extract various features, we tested five classification methods and evaluated performance of classifiers. As a result, SVM and CMAR (gave about 72---88% goodness of accuracy) outperformed the other classifiers.
Heuristic manipulation, tabu search and frequency assignment
Authors: Roberto Montemanni, Derek H. Smith
Venue: Computers and Operations Research (2010)

Heuristic manipulation attempts to modify the search space of an optimization problem, using information provided by an underlying heuristic method. In this paper it is applied in combination with tabu search to the fixed spectrum frequency assignment problem. The frequency assignment problem involves the assignment of discrete channels (or frequencies) to the transmitters of a radio network, such as a mobile telephone network. Frequency separation is necessary to avoid interference by other transmitters to the signal received from the wanted transmitter at the reception points. Unnecessary separation causes an excess requirement for spectrum. Good assignments minimize interference and the spectrum required. In fixed spectrum frequency assignment the frequency spectrum available is given and the target is to minimize the interference in the network. Computational experiments confirm that the manipulation technique is able to drive the underlying tabu search algorithm towards improved solutions.
Some Characterizations about 4-band Symmetric Cardinal Orthogonal Scaling Function
Authors: Guochang Wu, Yanpei Zhao
Venue: Proceedings of the 2009 International Conference on Computational Intelligence and Natural Computing - Volume 02 (2009)

The 4-band symmetric cardinal orthogonal scaling function with compact support is of interest in several applications. In this paper, we provide some characterizations of the 4-band symmetric cardinal orthogonal scaling function. We generalize some results of the symmetric cardinal orthogonal scaling function from the 2-band case to the 4-band case. Also, we find some new results.
User simulations for context-sensitive speech recognition in spoken dialogue systems
Authors: Oliver Lemon, loannis Konstas
Venue: Proceedings of the 12th Conference of the European Chapter of the Association for Computational Linguistics (2009)

We use a machine learner trained on a combination of acoustic and contextual features to predict the accuracy of incoming n-best automatic speech recognition (ASR) hypotheses to a spoken dialogue system (SDS). Our novel approach is to use a simple statistical User Simulation (US) for this task, which measures the likelihood that the user would say each hypothesis in the current context. Such US models are now common in machine learning approaches to SDS, are trained on real dialogue data, and are related to theories of "alignment" in psycholinguistics. We use a US to predict the user's next dialogue move and thereby re-rank n-best hypotheses of a speech recognizer for a corpus of 2564 user utterances. The method achieved a significant relative reduction of Word Error Rate (WER) of 5% (this is 44% of the possible WER improvement on this data), and 62% of the possible semantic improvement (Dialogue Move Accuracy), compared to the baseline policy of selecting the topmost ASR hypothesis. The majority of the improvement is attributable to the User Simulation feature, as shown by Information Gain analysis.