ppxscal/embedding_network huggingface dataset:
Two-Dimensional Micro-Hartmann Gas Flows
Authors: Chunpei Cai, Khaleel R. Khasawneh
Venue: Proceedings of the 9th International Conference on Computational Science: Part I (2009)

We analyze and simulate a near continuum MagnetoGasDynamic(MGD) flow inside a two-dimensional microchannel with a low magnetic Reynolds number assumption. Complex physics such as rarefication, electric and magnetic effects are considered in the asymptotic solutions. This work represents an extension from the classical Hartmann flow in a two-dimensional channel of infinite length to a microchannel of finite length. We obtain a non-dimensional equation that relates the pressure ratio, Reynolds number, Mach number, magnetic Reynolds number and magnetic force number. We also solved for asymptotic solutions of compressible gas flow based on the velocity-slip and temperature-jump wall boundary conditions while maintaining a consistent quasi-isothermal assumption. Numerical solutions of the same formulation are obtained for validation of the present analytical solutions.
An Ω(n logn) lower bound for computing the sum of even-raked elements
Authors: Marc Mörig, Dieter Rautenbach, Michiel Smid, Jan Tusch
Venue: Information Processing Letters (2009)

Given a sequence A of 2n real numbers, the EvenRankSum problem asks for the sum of the n values that are at the even positions in the sorted order of the elements in A. We prove that, in the algebraic computation-tree model, this problem has time complexity @Q(nlogn). This solves an open problem posed by Michael Shamos at the Canadian Conference on Computational Geometry in 2008.
On the Integration of Unicast and Multicast Cell Scheduling in Buffered Crossbar Switches
Authors: Lotfi Mhamdi
Venue: IEEE Transactions on Parallel and Distributed Systems (2009)

Internet traffic is a mixture of unicast and multicast flows. Integrated schedulers capable of dealing with both traffic types have been designed mainly for Input Queued (IQ) buffer-less crossbar switches. Combined Input and Crossbar Queued (CICQ) switches, on the other hand, are known to have better performance than their buffer-less predecessors due to their potential in simplifying the scheduling and improving the switching performance. The design of integrated schedulers in CICQ switches has thus far been neglected. In this paper, we propose a novel CICQ architecture that supports both unicast and multicast traffic along with its appropriate scheduling. In particular, we propose an integrated round-robin-based scheduler that efficiently services both unicast and multicast traffic simultaneously. Our scheme, named Multicast and Unicast Round robin Scheduling (MURS), has been shown to outperform all existing schemes under various traffic patterns. Simulation results suggested that we can trade the size of the internal buffers for the number of input multicast queues. We further propose a hardware implementation of our algorithm for a 16 \times 16 buffered crossbar switch. The implementation results suggest that MURS can run at 20 Gbps line rate and a clock cycle time of 2.8 ns, reaching an aggregate switching bandwidth of 320 Gbps.
A New Fake Iris Detection Method
Authors: Xiaofu He, Yue Lu, Pengfei Shi
Venue: Proceedings of the Third International Conference on Advances in Biometrics (2009)

Recent research works have revealed that it is not difficult to spoof an automated iris recognition system using fake iris such as contact lens and paper print etc. Therefore, it is very important to detect fake iris as much as possible. In this paper, we propose a new fake iris detection method based on wavelet packet transform. First, wavelet packet decomposition is used to extract the feature values which provide unique information for discriminating fake irises from real ones. Second, to enhance the detecting accuracy of fake iris, Support vector machine (SVM) is used to characterize the distribution boundary based on extracted wavelet packet features, for it has good classification performance in high dimensional space and it is originally developed for two-class problems. The experimental results indicate the proposed method is to be a very promising technique for making iris recognition systems more robust against fake iris spoofing attempts.
Adaptive play in Texas Hold'em Poker
Authors: Raphaël Maîtrepierre, Jérémie Mary, Rémi Munos
Venue: Proceeding of the 2008 conference on ECAI 2008: 18th European Conference on Artificial Intelligence (2008)

We present a Texas Hold'em poker player for limit headsup games. Our bot is designed to adapt automatically to the strategy of the opponent and is not based on Nash equilibrium computation. The main idea is to design a bot that builds beliefs on his opponent's hand. A forest of game trees is generated according to those beliefs and the solutions of the trees are combined to make the best decision. The beliefs are updated during the game according to several methods, each of which corresponding to a basic strategy. We then use an exploration-exploitation bandit algorithm, namely the UCB (Upper Confidence Bound), to select a strategy to follow. This results in a global play that takes into account the opponent's strategy, and which turns out to be rather unpredictable. Indeed, if a given strategy is exploited by an opponent, the UCB algorithm will detect it using change point detection, and will choose another one. The initial resulting program, called Brennus, participated to the AAAI'07 Computer Poker Competition in both online and equilibrium competition and ranked eight out of seventeen competitors.
Efficient construction of maximal and minimal representations of motifs of a string
Authors: François Nicolas, Veli Mäkinen, Esko Ukkonen
Venue: Theoretical Computer Science (2009)

Two substrings of a given text string are called synchronous (occurrence-equivalent) if their sets of occurrence locations are translates of each other. Linear time algorithms are given for the problems of finding a shortest and a longest substring that is synchronous with a given substring. We also introduce approximate variants of the motif discovery problem and give polynomial time algorithms for finding longest and shortest substrings whose suitably translated occurrence location set contains or, respectively, is contained in a given set of locations. The FFT technique used here also leads to an O(nlogn) algorithm for finding the maximum-content gapped motif that is synchronous with a given set of locations; the previously known algorithm for this problem is only quadratic.
Classifying Biomedical Abstracts Using Committees of Classifiers and Collective Ranking Techniques
Authors: Alexandre Kouznetsov, Stan Matwin, Diana Inkpen, Amir H. Razavi, Oana Frunza, Morvarid Sehatkar, Leanne Seaward, Peter O'Blenis
Venue: Proceedings of the 22nd Canadian Conference on Artificial Intelligence: Advances in Artificial Intelligence (2009)

The purpose of this work is to reduce the workload of human experts in building systematic reviews from published articles, used in evidence-based medicine. We propose to use a committee of classifiers to rank biomedical abstracts based on the predicted relevance to the topic under review. In our approach, we identify two subsets of abstracts: one that represents the top, and another that represents the bottom of the ranked list. These subsets, identified using machine learning (ML) techniques, are considered zones where abstracts are labeled with high confidence as relevant or irrelevant to the topic of the review. Early experiments with this approach using different classifiers and different representation techniques show significant workload reduction.
Collision Attack on Boole
Authors: Florian Mendel, Tomislav Nad, Martin Schläffer
Venue: Proceedings of the 7th International Conference on Applied Cryptography and Network Security (2009)

Boole is a hash function designed by Gregory Rose and was submitted to the NIST Hash competition. It is a stream cipher based hash function which produces digests up to 512 bits. Different variants exist, namely Boole16, Boole32 and Boole64 where the number refers to word size in bits. Boole64 is considered as the official submission. In this paper we demonstrate a collision attack with complexity 265 for the 64-bit variant and 233 for the 32-bit variant. The amount of memory required is negligible. Since the attack on Boole32 is practical, we present an example for a collision.
New algorithms for block segregated multiple key search strategy
Authors: Ahmed Tarek
Venue: Proceedings of the international conference on Computational and information science 2009 (2009)

In this paper, two new algorithms for list segregated multiple key search strategies are discussed. In block search, a given list of elements, which are in sorted order is subdivided into a number of equal sized blocks, and the given key element is compared to the upper bounding element in each block until a bounding element is found, which is either equal to or greater than the key. If the bounding element is greater, then the search is confined in the corresponding block to locate the correct key position. In the proposed algorithms, the block search effort is confined to identify multiple key elements in a given list. The search efforts are optimized after identifying each individual key position by discarding a part of the search space (a portion of the list elements). Here, the list of keys are assumed to be sorted in ascending order, though it is possible to consider a descending list of keys with an ascending list of elements. Once a key index position is identified, the successive keys are searched for at the same or at the higher level blocks containing larger elements. This strategy considerably reduces the search efforts with multiple keys with increasing number of keys in the list. To search for the current key element, the algorithm simply discards the blocks containing the previous smaller keys, and starts at the bounding element of the latest block holding the immediately preceding key. Computational complexity of the proposed algorithms are also considered. Another modification uses the binary search instead of the linear search to identify the correct key position within the block, since the list is in sorted order. With large block sizes, this strategy considerably improves the search time. Therefore, the performance issues of the proposed algorithms are also taken into consideration.
Pervasive Healthcare Computing: EMR/EHR, Wireless and Health Monitoring, 1st edition
Authors: Upkar Varshney
Venue:  (2009)

Pervasive healthcare is the conceptual system of providing healthcare to anyone, at anytime, and anywhere by removing restraints of time and location while increasing both the coverage and the quality of healthcare. Pervasive Healthcare Monitoring is at the forefront of this research, and presents the ways in which mobile and wireless technologies can be used to implement the vision of pervasive healthcare. This vision includes prevention, healthcare maintenance and checkups; short-term monitoring (home healthcare monitoring), long-term monitoring (nursing home), and personalized healthcare monitoring; and incidence detection and management, emergency intervention, and transportation and treatment. The pervasive healthcare applications include pervasive health monitoring, intelligent emergency management system, pervasive healthcare data access, and ubiquitous mobile telemedicine. Pervasive Healthcare Monitoring fills the need for a research-oriented book on the wide array of emerging healthcare applications and services, including the treatment of several new wireless technologies and the ways in which they will implement the vision of pervasive healthcare. This book is written primarily for university faculty and graduate students in the field of healthcare technologies, and industry professionals involved in healthcare IT research, design, and development.
Online optimization for variable selection in data streams
Authors: Christoforos Anagnostopoulos, Dimitris Tasoulis, David J. Hand, Niall M. Adams
Venue: Proceeding of the 2008 conference on ECAI 2008: 18th European Conference on Artificial Intelligence (2008)

Variable selection for regression is a classical statistical problem, motivated by concerns that too many covariates invite overfitting. Existing approaches notably include a class of convex optimisation techniques, such as the Lasso algorithm. Such techniques are invariably reliant on assumptions that are unrealistic in streaming contexts, namely that the data is available off-line and the correlation structure is static. In this paper, we relax both these constraints, proposing for the first time an online implementation of the Lasso algorithm with exponential forgetting. We also optimise the model dimension and the speed of forgetting in an online manner, resulting in a fully automatic scheme. In simulations our scheme improves on recursive least squares in dynamic environments, while also featuring model discovery and changepoint detection capabilities.
Automated motion capture segmentation using laban movement analysis
Authors: Norman I. Badler
Venue:  (2008)

Many applications that utilize motion capture data require small, discrete, semantic segments of data, but most motion capture collection processes produce long sequences of data. The smaller segments are often created from the longer sequences manually. This segmentation process is very laborious and time consuming. An automatic motion capture segmentation method based on movement qualities derived from Laban Movement Analysis (LMA) is presented. LMA provides a good compromise between high-level semantic features, which are difficult to extract for general motions, and low-level kinematic features, which often yield unsophisticated segmentations. The LMA features are computed using a collection of neural networks trained with temporal variance in order to create a classifier that is more robust with regard to input boundaries. The actual segmentation points are derived through simple time series analysis of the LMA features. Segmentations produced using LMA features are more similar to manual segmentations, both at the frame and segment level, than are several other automatic segmentation methods. The LMA based segmentation method has the added benefit of improving the performance classifiers for which it segments the input. This has implications in many areas that utilize motion capture analysis including human-computer interaction and computer animation.
Towards context-aware propagators: language constructs for context-aware adaptation dependencies
Authors: Engineer Bainomugisha, Wolfgang De Meuter, Theo D'Hondt
Venue: International Workshop on Context-Oriented Programming (2009)

A context-aware system needs to reason about its current context of use and select applicable adaptations to activate or deactivate. This process is complex as often multiple contexts are available and improper interpretation of adaptation dependencies may lead to inconsistent or annoying system behaviour. This paper proposes a programming language support for defining context-aware dependencies between adaptations. Our model is based on the ideas of the propagator computational model to provide support for multiple dependencies that can coexist even if they contradict. Our proposed model is analogous to relationships and multiplicities in the modelling approaches. In addition, rather than fixed dependencies between adaptations, our model allows these dependencies to change depending on the context of use.
Resolving bridging references in unrestricted text
Authors: Massimo Poesio, Renata Vieira, Simone Teufel
Venue: Proceedings of a Workshop on Operational Factors in Practical, Robust Anaphora Resolution for Unrestricted Texts (1997)

Our goal is to develop a system capable of treating the largest possible subset of definite descriptions in unrestricted written texts. A previous prototype resolved anaphoric uses of definite descriptions and identified some types of first-mention uses, achieving a recall of 56%. In this paper we present the latest version of our system, which handles some types of bridging references, uses WordNet as a source of lexical knowledge, and achieves a recall of 65%.
Linear Data Structures for Fast Ray-Shooting amidst Convex Polyhedra
Authors: Haim Kaplan, Natan Rubin, Micha Sharir
Venue: Algorithmica (2009)

We consider the problem of ray shooting in a three-dimensional scene consisting of k (possibly intersecting) convex polyhedra with a total of n facets. That is, we want to preprocess them into a data structure, so that the first intersection point of a query ray and the given polyhedra can be determined quickly. We describe data structures that require preprocessing time and storage (where the $ notation hides polylogarithmic factors), and have polylogarithmic query time, for several special instances of the problem. These include the case when the ray origins are restricted to lie on a fixed line ℓ 0, but the directions of the rays are arbitrary, the more general case when the supporting lines of the rays pass through ℓ 0, and the case of rays orthogonal to some fixed line with arbitrary origins and orientations. We also present a simpler solution for the case of vertical ray-shooting with arbitrary origins. In all cases, this is a significant improvement over previously known techniques (which require Ω(n 2) storage, even when k ≪ n).
Learning effective and engaging strategies for advice-giving human-machine dialogue
Authors: Martijn Spitters, Marco De boni, Jakub Zavrel, Remko Bonnema
Venue: Natural Language Engineering (2009)

We describe a system that automatically learns effective and engaging dialogue strategies, generated from a library of dialogue content, using reinforcement learning from user feedback. Besides the more usual clarification and verification components of dialogue, this library contains various social elements like greetings, apologies, small talk, relational questions and jokes. We tested the method through an experimental dialogue system that encourages take-up of exercise and shows that the learned dialogue policy performs as well as one built by human experts for this system.
The Research and Implementation of Grid Based Data Mining Architecture
Authors: Jingwen Gong, Yu Wang, Haigang Song, Xueguang Chen, Qihua Zhang
Venue: Proceedings of the 6th International Symposium on Neural Networks: Advances in Neural Networks - Part II (2009)

Nowadays E-Business and E-Science are generating plenty of datasets. These datasets are heterogeneous and geographically distributed. There are major challenges involved in the efficient extracting useful knowledge from the datasets. This paper proposes a Grid based data mining architecture for Grid based Urban Public Transport Decision Support System (GUPTDSS). It discusses three main topics: process of parallel algorithm; deployment, invoking and scheduling of Grid based data mining service; data sources distribution scenarios and data access. To evaluate the efficiency of the proposed system, an example of traffic flow classification is presented.
An Ontology Learning and Reasoning Framework
Authors: Hele-Mai Haav
Venue: Proceeding of the 2006 conference on Information Modelling and Knowledge Bases XVII (2006)

Most of current ontology languages and methodologies lack of learning support combined with reasoning mechanisms. This motivates us creating an ontology learning and reasoning framework in order to guarantee accuracy, transparency and consistency of ontology representation by automatic or semiautomatic methods of ontology learning and reasoning. Novelty of our approach is in combining ontology learning and reasoning into one framework. For ontology extraction and learning, we use Formal Concept Analysis. For ontology reasoning purposes, we require that learned ontology should be automatically mapped to some logic language. We use predicate logic as a target ontology language in this paper.
A dynamic erasure code for multicasting live data
Authors: Erik M. Ferragut
Venue: Proceedings of the 5th Annual Workshop on Cyber Security and Information Intelligence Research: Cyber Security and Information Intelligence Challenges and Strategies (2009)

Digital fountains, a class of erasure codes, have been used for multicasting stream data and for robust distributed data storage. These methods produce a potentially endless sequence of packets from a fixed (static) message. The dynamic erasure code problem is to extend the digital fountains concept to a message generated simultaneously with the transmission (i.e., live data). Solution of this problem provides a means for robust multicasting or one-way transmission of live data on a computer network. It also gives a method for robust distributed storage of log data, or other serially generated data. A new erasure code is proposed as a solution to the dynamic erasure code problem. It is analytically shown to have a fast decoding algorithm and to be highly bandwidth-efficient.
Reflectance of floodplain waterbodies using EO-1 Hyperion data from high and receding flood periods of the Amazon River
Authors: C. M. Rudorff, L. S. Galvao, E. M. L. M. Novo
Venue: International Journal of Remote Sensing (2009)

The potential of Hyperion images acquired on September 2001 (receding flood period of the Amazon River) and June 2005 (high flood) was investigated for reflectance characterization of selected Amazon floodplain waterbodies using a linear spectral mixture model. The results show the ability of Hyperion to measure adequately the major variation in water reflectance spectral features in response to the annual flood pulse of the Amazon River. Mixture model fraction values were correlated with measured inorganic suspended solids (ISS) but not with chlorophyll (Chl) in the high flood period. Inspection of the fractions across the two images revealed variation in water composition. Small changes in ISS-and Chl-bearing water fractions between the images indicated relatively stable spectral conditions for low (Tapajos River and Lake Juruparipucu) and high (Amazon River) turbidity waterbodies. Large changes indicated reflectance variation in some lakes when the water receded due to algal blooms (Lake Curumu) and sediment resuspension in shallow regions (Lake Aritapera). Although not all water constituents were modelled adequately for quantification purposes, spectral mixture modelling is still an interesting approach for spectral-temporal reflectance characterization of Amazonian floodplains with hyperspectral data.
Formation of Ge nanocrystals in a silicon dioxide layer using pulsed plasma-immersion ion implantation
Authors: Young Min Kim, Min-Kyu Jeong, Ki-Heung Park, Sang-Goo Jung, Sung-Ho Bae, Jong-Ho Lee
Venue: Microelectronic Engineering (2009)

Pulsed plasma-immersion ion implantation (PIII) or Pulsed PLAsma Doping (P^2LAD) is known as a cost effective solution for ultra shallow junction formation due to its capability to implant doping species at ultra-low energies (0.05-5keV), the advantages of P^2LAD, high concentration and sharp distribution of the implanted species, also make this technique a good candidate to fabricate nanocrystals (NCs) within silicon dioxide (SiO"2) layer. In this work, we report Ge NC fabrication within a SiO"2 layer by using the pulsed PIII technique for the first time. GeH"4 (4sccm) and He (100sccm) gases were flown to the plasma chamber, and a voltage of 4.5kV was applied. After pulsed PIII process, furnace annealing was performed at 900^oC in nitrogen atmosphere for Ge agglomeration. By using such a process, we fabricated non-volatile memory devices and obtained relevant program/erase, retention, and cycling characteristics.