ppxscal/embedding_network huggingface dataset:
An Efficient Algorithm for Discovering all Frequent Patterns
Authors: Fuzan Chen, Minqiang Li, Jisong Kou
Venue: Proceedings of the 2009 WRI Global Congress on Intelligent Systems - Volume 02 (2009)

Discovering frequent patterns is one of the essential topic data mining. An efficient algorithm based on compressed bitmap and two-way-hybrid strategy is proposed. Firstly, a hierarchical search space organization is presented, based on which the original search space can be recursively decomposed into some smaller independent pieces. Secondly, a compressed bitmap index technique is employed to speed up the support counting. The original bitmap can be impacted efficiently by this way. Thirdly, a novel HFMI algorithm, which explores a flexible two-way-hybrid search method, is given. It can discovery both longer and shorter frequent patterns as many as possible. And experimental and analytical results are presented in the end of this paper.
Autonomy of Self at Criticality: The Perspective from Synthetic Neuro-Robotics
Authors: Jun Tani
Venue: Adaptive Behavior - Animals, Animats, Software Agents, Robots, Adaptive Systems (2009)

This article investigates the phenomenological aspects of selves in relation to autonomous agents. Through a review of a series of neuro-robotics experiments conducted by the authorâs group, we elucidate three different aspects of selves, namely, minimal selves, social selves and self-referential selves. Upon integrative discussions of these selves, it is suggested that genuine constructs of âauthenticâ selves may appear with criticality, which is self-organized in the iterative interplay between regression of past experience and lookahead prediction of future outcomes. It is concluded that genuine autonomy of agents likely originates from genuine autonomy of authentic selves.
Proving the Correctness of the Implementation of a Control-Command Algorithm
Authors: Olivier Bouissou
Venue: Proceedings of the 16th International Symposium on Static Analysis (2009)

In this article, we study the interactions between a control-command program and its physical environment via sensors and actuators. We are interested in finding invariants on the continuous trajectories of the physical values that the program is supposed to control. The invariants we are looking for are periodic sequences of intervals that are abstractions of the values read by the program. To compute them, we first build octrees that abstract the impact of the program on its environment. Then, we compute a period of the abstract periodic sequence and we finally define the values of this sequence as the fixpoint of a monotone map. We present a prototype analyzer that computes such invariants for C programs using a simple specification language for describing the continuous environment. It shows good results on classical benchmarks for hybrid systems verification. 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
Location Discovery in SpeckNets Using Relative Direction Information
Authors: Ryan Mcnally, D. K. Arvind
Venue: Proceedings of the 4th International Conference on Wireless Algorithms, Systems, and Applications (2009)

A speck is intended to be a miniature (5X5X5mm) semiconductor device that combines sensing, processing, wireless communication and energy storage capabilities. A specknet is an ad-hoc wireless network of specks. The location of specks in the network is useful in processing information, for reasons ranging from routing data to giving the data sensed a spatial context. This paper presents an algorithm for discovering the location of specks and updating that information in the face of movement. The proposed algorithm exploits the location constraints implied by the sensed directions to a speck's one-hop neighbours in order to compute a likely location. Direction information may be gleaned in a robust manner through the use of free-space optical communications systems. The algorithm is fully distributed, requires no special infrastructural support, has modest requirements in terms of computation and communication and does not rely on range measurement or anchor nodes. The performance of the location discovery algorithm is evaluated in the SpeckSim simulator under a range of adverse conditions.
Exploring the Feasibility of Reputation Models for Improving P2P Routing under Churn
Authors: Marc Sànchez-Artigas, Pedro García-López, Blas Herrera
Venue: Proceedings of the 15th International Euro-Par Conference on Parallel Processing (2009)

Reputation mechanisms help peer-to-peer (P2P) networks to detect and avoid unreliable or uncooperative peers. Recently, it has been discussed that routing protocols can be improved by conditioning routing decisions to the past behavior of forwarding peers. However, churn -- the continuous process of node arrival and departure -- may severely hinder the applicability of rating mechanisms. In particular, short lifetimes mean that reputations are often generated from a small number of transactions.To examine how high rates of churn affect rating mechanisms, this paper introduces an analytical model to compute at which rate transactions has to be performed so that the generated reputations are sufficiently reliable. We then propose a new routing protocol for structured P2P systems that exploits reputation to improve the decision about which neighbor choose as next hop. Our results demonstrate that routing algorithms can extract substantial benefits from reputations even when peer lifetimes are short.
Microstructure Evolution of Stainless Steel during Laser Metal Deposition Shaping
Authors: Kai Zhang, Weijun Liu
Venue: Proceedings of the 2009 International Conference on Measuring Technology and Mechatronics Automation - Volume 02 (2009)

Laser Metal Deposition Shaping (LMDS) is a process that fuses gas delivered metal powders within a focal zone of a laser beam to produce fully dense, 3-dimensional metal components. A variety of materials have been processed with LMDS, ranging from stainless steel to superalloy. To evaluate the processing parameters and resulting microstructures, solidification studies have been performed on defined alloy systems. For example, solidification cooling rates and growth velocities have been determined based upon secondary dendrite arm spacings formed during solidification in stainless steel. Corresponding to the great change of cooling rates, growth rates vary dramatically. As a result, process definition has been developed based upon the microstructure evolution during solidification.
Modeling dialogue structure with adjacency pair analysis and hidden Markov models
Authors: Kristy Elizabeth Boyer, Robert Phillips, Eun Young Ha, Michael D. Wallis, Mladen A. Vouk, James C. Lester
Venue: Proceedings of Human Language Technologies: The 2009 Annual Conference of the North American Chapter of the Association for Computational Linguistics, Companion Volume: Short Papers (2009)

Automatically detecting dialogue structure within corpora of human-human dialogue is the subject of increasing attention. In the domain of tutorial dialogue, automatic discovery of dialogue structure is of particular interest because these structures inherently represent tutorial strategies or modes, the study of which is key to the design of intelligent tutoring systems that communicate with learners through natural language. We propose a methodology in which a corpus of human-human tutorial dialogue is first manually annotated with dialogue acts. Dependent adjacency pairs of these acts are then identified through X2 analysis, and hidden Markov modeling is applied to the observed sequences to induce a descriptive model of the dialogue structure.
Kernel-Based Copula Processes
Authors: Sebastian Jaimungal, Eddie K. Ng
Venue: Proceedings of the European Conference on Machine Learning and Knowledge Discovery in Databases: Part I (2009)

Kernel-based Copula Processes (KCPs), a new versatile tool for analyzing multiple time-series, are proposed here as a unifying framework to model the interdependency across multiple time-series and the long-range dependency within an individual time-series. KCPs build on the celebrated theory of copula which allows for the modeling of complex interdependence structure, while leveraging the power of kernel methods for efficient learning and parsimonious model specification. Specifically, KCPs can be viewed as a generalization of the Gaussian processes enabling non-Gaussian predictions to be made. Such non-Gaussian features are extremely important in a variety of application areas. As one application, we consider temperature series from weather stations across the US. Not only are KCPs found to have modeled the heteroskedasticity of the individual temperature changes well, the KCPs also successfully discovered the interdependencies among different stations. Such results are beneficial for weather derivatives trading and risk management, for example.
Development of a High Resolution 3D Infant Stomach Model for Surgical Planning
Authors: Qaiser Chaudry, S. Hussain Raza, Jeonggyu Lee, Yan Xu, Mark Wulkan, May D. Wang
Venue: Proceedings of the 13th International Conference on Computer Analysis of Images and Patterns (2009)

Medical surgical procedures have not changed much during the past century due to the lack of accurate low-cost workbench for testing any new improvement. The increasingly cheaper and powerful computer technologies have made computer-based surgery planning and training feasible. In our work, we have developed an accurate 3D stomach model, which aims to improve the surgical procedure that treats the infant pediatric and neonatal gastro-esophageal reflux disease (GERD). We generate the 3-D infant stomach model based on in vivo computer tomography (CT) scans of an infant. CT is a widely used clinical imaging modality that is cheap, but with low spatial resolution. To improve the model accuracy, we use the high resolution Visible Human Project (VHP) in model building. Next, we add soft muscle material properties to make the 3D model deformable. Then we use virtual reality techniques such as haptic devices to make the 3D stomach model deform upon touching force. This accurate 3D stomach model provides a workbench for testing new GERD treatment surgical procedures. It has the potential to reduce or eliminate the extensive cost associated with animal testing when improving any surgical procedure, and ultimately, to reduce the risk associated with infant GERD surgery.
JavaGI in the battlefield: practical experience with generalized interfaces
Authors: Stefan Wehr, Peter Thiemann
Venue: Proceedings of the eighth international conference on Generative programming and component engineering (2009)

Generalized interfaces are an extension of the interface concept found in object-oriented languages such as Java or C#. The extension is inspired by Haskell's type classes. It supports retroactive and type-conditional interface implementations, binary methods, symmetric multimethods, interfaces over families of types, and static interface methods. This article reports practical experience with generalized interfaces as implemented in the JavaGI language. Several real-world case studies demonstrate how generalized interfaces provide solutions to extension and integration problems with components in binary form, how they make certain design patterns redundant, and how they eliminate various run-time errors. In each case study, the use of JavaGI results in elegant and highly readable code. Furthermore, the article discusses the implementation of a compiler and a run-time system for JavaGI. Benchmarks show that our implementation offers acceptable performance.
Experiences of students with disabilities in computing
Authors: Richard Ladner
Venue: Journal of Computing Sciences in Colleges (2009)

This panel will address how to make computer science, computer engineering, and information technology programs more accessible to students with disabilities. The panel will have three students with disabilities, to be announced, who are currently in or have recently graduated from computing departments. The students will have a variety of disabilities, blind, deaf, learning disabled to give a broad perspective to the attendees.
Economic land evaluation for agricultural resource management in Northern Thailand
Authors: Chalermpol Samranpong, Benchaphun Ekasingh, Methi Ekasingh
Venue: Environmental Modelling Software (2009)

This paper describes a GIS-based system, EconSuit, that supports dynamic assessment of economic land suitability for major economic crops in Northern Thailand. Prior to economic land evaluation, a physical land suitability index is computed using a fuzzy set approach in GIS. The procedure bypasses crop modeling and permits suitability to be defined in a continuous scale with a graphic interface enabling a user to dynamically assign diagnostic factors and weights for physical land evaluation. Economic land evaluation is accomplished by assigning field survey data to land mapping units using spatial interpolation. Unit costs of inputs and outputs can be entered through the graphic user interface, allowing constant updates of economic values in the system. Scenarios of agricultural land use planning may be formulated by users depending on policy or economic circumstances.
Improving performance of transfer-driven machine translation with extra-linguistic information from context, situation and environment
Authors: Hideki Mima, Osamu Furuse, Hitoshi Iida
Venue: Proceedings of the Fifteenth international joint conference on Artifical intelligence - Volume 2 (1997)

This paper describes an improvement in the performance of Transfer-Driven Machine Translation (TDMT) by the use of extralinguistic information. In evaluating what constitutes natural speech, particular attention was paid to word usage that depended on the extra-linguistic information from the context, situation, environment and so on. We discuss what types of extra-linguistic information a spoken-language translation system requires to create naturally communicative dialogs. We then propose a method of improving the precision of translation by utilizing this extralinguistic information. Preliminary experimentation showing performance improvements in TDMT makes us believe that the proposed scheme can improve the performance of dialog MT.
Feature Selection for Value Function Approximation Using Bayesian Model Selection
Authors: Tobias Jung, Peter Stone
Venue: Proceedings of the European Conference on Machine Learning and Knowledge Discovery in Databases: Part I (2009)

Feature selection in reinforcement learning (RL), i.e. choosing basis functions such that useful approximations of the unkown value function can be obtained, is one of the main challenges in scaling RL to real-world applications. Here we consider the Gaussian process based framework GPTD for approximate policy evaluation, and propose feature selection through marginal likelihood optimization of the associated hyperparameters. Our approach has two appealing benefits: (1) given just sample transitions, we can solve the policy evaluation problem fully automatically (without looking at the learning task, and, in theory, independent of the dimensionality of the state space), and (2) model selection allows us to consider more sophisticated kernels, which in turn enable us to identify relevant subspaces and eliminate irrelevant state variables such that we can achieve substantial computational savings and improved prediction performance.
Unsupervised methods for head assignments
Authors: Federico Sangati, Willem Zuidema
Venue: Proceedings of the 12th Conference of the European Chapter of the Association for Computational Linguistics (2009)

We present several algorithms for assigning heads in phrase structure trees, based on different linguistic intuitions on the role of heads in natural language syntax. Starting point of our approach is the observation that a head-annotated treebank defines a unique lexicalized tree substitution grammar. This allows us to go back and forth between the two representations, and define objective functions for the unsupervised learning of head assignments in terms of features of the implicit lexicalized tree grammars. We evaluate algorithms based on the match with gold standard head-annotations, and the comparative parsing accuracy of the lexicalized grammars they give rise to. On the first task, we approach the accuracy of hand-designed heuristics for English and inter-annotation-standard agreement for German. On the second task, the implied lexicalized grammars score 4% points higher on parsing accuracy than lexicalized grammars derived by commonly used heuristics.
Research on Texture Images Retrieval Based on the Gabor Wavelet Transform
Authors: Yang Jie, Zhao Qiang, Zhou Liang, Chen Yin Wuhan
Venue: Proceedings of the 2009 WASE International Conference on Information Engineering - Volume 01 (2009)

A technique of texture images retrieval based on Gabor wavelet transform is presented in this paper.A group of filters of different directions and different scales, generated from the basic wavelet of Gabor function are used for the wavelet transforamtion of texture images,then the means and Variances of the wavelet transformation coefficients are calculated as texture features of the image for the use of image retrieval. The parameters used in experiments are circumspectly selected according to the retrieval results.Experiments show that this method has an excellent performance on texture images retrieval.
Four Subareas of the Theory of Constraints, and Their Links
Authors: Albert Atserias
Venue: Proceedings of the 34th International Symposium on Mathematical Foundations of Computer Science 2009 (2009)

Let V = {x1,...,xn} be a set of variables that range over a set of values D = {d1,...,dq}. A constraint is an expression of the type $R(x_{i_1},\ldots,x_{i_r})$, where R ¿ Dr is a relation on the domain set D and $x_{i_1},\ldots,x_{i_r}$ are variables in V. The space of assignments, or configurations, is the set of all mappings ¿: V ¿D. We say that ¿ satisfies the constraint $R(x_{i_1},\ldots,x_{i_r})$ if $(\sigma(x_{i_1}),\ldots,\sigma(x_{i_r})) \in R$. Otherwise we say that it falsifies it. On a given system of constraints we face a number of important computational problems.
OcVFDT: one-class very fast decision tree for one-class classification of data streams
Authors: Chen Li, Yang Zhang, Xue Li
Venue: Proceedings of the Third International Workshop on Knowledge Discovery from Sensor Data (2009)

Current research on data stream classification mainly focuses on supervised learning, in which a fully labeled data stream is needed for training. However, fully labeled data streams are expensive to obtain, which make the supervised learning approach difficult to be applied to real-life applications. In this paper, we model applications, such as credit fraud detection and intrusion detection, as a one-class data stream classification problem. The cost of fully labeling the data stream is reduced as users only need to provide some positive samples together with the unlabeled samples to the learner. Based on VFDT and POSC4.5, we propose our OcVFDT (One-class Very Fast Decision Tree) algorithm. Experimental study on both synthetic and real-life datasets shows that the OcVFDT has excellent classification performance. Even 80% of the samples in data stream are unlabeled, the classification performance of OcVFDT is still very close to that of VFDT, which is trained on fully labeled stream.
Detecting Underlying Stance Adopted When Human Construe Behavior of Entities
Authors: Kazunori Terada, Kouhei Ono, Akira Ito
Venue: Proceedings of the FIRA RoboWorld Congress 2009 on Advances in Robotics (2009)

Whether or not humans can construe the behaviors of entities depends on their psychological stance. The philosopher Dennett proposed human cognitive strategies (three stances) in which humans construe the behavior of other animated objects, including other humans, artifacts, and physical phenomena:`intentional', `design' and `physical' stances. Detecting the psychological stance taken toward entities is difficult, because such mental state attribution is a subjective cognitive process and hard to measure. In the present study, we proposed a novel method for detecting underlying stance adopted when human construe behavior of entities. In our method the subject was asked to select the most suitable action sequence shown in three movies each of which representing Dennett's three stances. To valid our method we have conducted an experiment in which the subjects were presented thirty short videos and asked to compare them to the three movies. The result indicated that the subjects did not focused on prior knowledge about the entity but could focused on motion characteristics per se, owing to simple and typical motion of an abstract shaped object.
Multifractal correlation characteristic for radar detecting low-observable target in sea clutter
Authors: Jian Guan, Ningbo Liu, Jian Zhang, Jie Song
Venue: Signal Processing (2010)

This paper studies the multifractal correlation characteristic of sea clutter which can be applied to radar low-observable target detection in sea clutter. Multifractal correlation is a generalization of multifractal 'single point' statistic, and takes the spatial correlation of two points with different singularity intensity into account. The important content of this paper is the derivation of multifractal correlation from multifractal, and obtains the multifractal correlation spectrum. Then the multifractal correlation spectrum is used as a characteristic to analyze the membership degree to match board. In fact, radar target detection can be regarded as a binary-classification question, therefore the SVM (support vector machine) is applied to target detection. In the end, the real sea clutter under several conditions is used to verify the method proposed in this paper. The results show that the method has a strong performance of target detection and sea clutter suppression.
Assessment of Cognitive Neural Correlates for a Functional Near Infrared-Based Brain Computer Interface System
Authors: Hasan Ayaz, Patricia A. Shewokis, Scott Bunce, Maria Schultheis, Banu Onaral
Venue: Proceedings of the 5th International Conference on Foundations of Augmented Cognition. Neuroergonomics and Operational Neuroscience: Held as Part of HCI International 2009 (2009)

Functional Near Infrared Spectroscopy (fNIR) is a promising brain imaging technology that relies on optical techniques to detect changes of hemodynamic responses within the prefrontal cortex in response to sensory, motor, or cognitive activation. fNIR is safe, non-invasive, affordable, and highly portable. The objective of this study is to determine if biomarkers of neural activity generated by intentional cognitive activity, as measured by fNIR, can be used to communicate directly from the brain to a computer. A bar-size-control task based on a closed-loop system was designed and tested with 5 healthy subjects across two days. Comparisons of the average task and rest period oxygenation changes are significantly different (p<0.01). The average task completion time (reaching +90%) decreases with practice: day1 (mean 52.3 sec) and day2 (mean 39.1 sec). These preliminary results suggest that a closed-loop fNIR-based BCI can allow for a human-computer interaction with a mind switch task.