ppxscal/embedding_network huggingface dataset:
Dynamic spectrum access in DTV whitespaces: design rules, architecture and algorithms
Authors: Supratim Deb, Vikram Srinivasan, Ritesh Maheshwari
Venue: Proceedings of the 15th annual international conference on Mobile computing and networking (2009)

In November 2008, the FCC ruled that the digital TV whitespaces be used for unlicensed access. This is an exciting development because DTV whitespaces are in the low frequency range (50-698 MHz) compared to typical cellular and ISM bands, thus resulting in much better propagation characteristics and much higher spectral efficiencies. The FCC has also mandated certain guidelines for short range unlicensed access, so as to avoid any interference to DTV receivers. We consider the problem of WiFi like access (popularly referred to as WiFi 2.0) for enterprizes. We assume that the access points and client devices are equipped with cognitive radios, i.e., they can adaptively choose the center frequency, bandwidth and ower of operation. The access points can be equipped with one or more radios. Our goal is to design a complete system, which (i) does not violate the FCC mandate, (ii) dynamically assigns center frequency and bandwidth to each access point based on their demands and (iii) squeezes the maximum efficiency from the available spectrum. This problem is far more general than prior work that investigated dynamic spectrum allocation in cellular and ISM bands, due to the non-homogenous nature of the whitespaces, i.e., different whitespace widths in different parts of the spectrum and the large range of frequency bands with different propagation characteristics. This calls for a more holistic approach to system design that also accounts for frequency dependent propagation characteristics and radio frontend characteristics. In this paper, we first propose design rules for holistic system design. We then describe an architecture derived from our design rules. Finally we propose demand based dynamic spectrum allocation algorithms with provable worst case guarantees. We provide extensive simulation results showing that (i) the performance of our algorithm is within 94% of the optimal in typical settings and (ii) and the DTV whitespaces can provide significantly higher data rates compared to the 2.4GHz ISM band. Our approach is general enough for designing any system with access to a wide range of spectrum.
Perceptual supports for sensemaking: a case study using multi agent based computational learning environments
Authors: Michelle H. Wilkerson, Pratim Sengupta, Uri Wilensky
Venue: Proceedings of the 8th international conference on International conference for the learning sciences - Volume 3 (2008)

Many studies have examined how learners make sense of the traditionally difficult ideas of levels and emergence in complex systems by interacting with visuospatial multi agent based models. In this poster, we review these findings through the lens of human basic perceptual/representational systems. We argue that many of learners' observed strategies and explanations surrounding the ideas of levels and emergence are supported by visualizations that leverage perceptual systems related to objects, motion, and geometry.
Enabling domain-awareness for a generic natural language interface
Authors: Yunyao Li, Ishan Chaudhuri, Huahai Yang, Satinder Singh, H. V. Jagadish
Venue: Proceedings of the 22nd national conference on Artificial intelligence - Volume 1 (2007)

In this paper, we present a learning-based approach for enabling domain-awareness for a generic natural language interface. Our approach automatically acquires domain knowledge from user Interactions and Incorporates the knowledge learned to improve the generic system. We have embedded our approach in a generic natural language interface and evaluated the extended system against two benchmark datasets. We found that the performance of the original generic system can be substantially improved through automatic domain knowledge extraction and incorporation. We also show that the generic system with domain-awareness enabled by our approach can achieve performance similar to that of previous learning-based domain-specific systems.
Incremental and Adaptive Clustering Stream Data over Sliding Window
Authors: Xuan Hong Dang, Vincent C. Lee, Wee Keong Ng, Kok Leong Ong
Venue: Proceedings of the 20th International Conference on Database and Expert Systems Applications (2009)

Cluster analysis has played a key role in data stream understanding. The problem is difficult when the clustering task is considered in a sliding window model in which the requirement of outdated data elimination must be dealt with properly. We propose SWEM algorithm that is designed based on the Expectation Maximization technique to address these challenges. Equipped in SWEM is the capability to compute clusters incrementally using a small number of statistics summarized over the stream and the capability to adapt to the stream distribution's changes. The feasibility of SWEM has been verified via a number of experiments and we show that it is superior than Clustream algorithm, for both synthetic and real datasets.
The Wrong Analysis of the Price Forecast Model Based on Fractal Theory in Commodity Price Forecasting
Authors: Herui Cui, Li Yang
Venue: Proceedings of the 2009 IITA International Conference on Services Science, Management and Engineering (2009)

The fractal theory is beginning from the 1970s, which take the geometrical morphology with the characteristics of non-regular and self-similar in nature and real life as the research object. Application field of this model is very extensive, and in economic management, as commodity price exhibits the characteristics of non-regular and self-similar to a certain extent, so this model is used as new prediction model in price forecasting of commodity. But this model has some problems, this paper uses empirical analysis to show the shortcomings of this method in commodity price forecast.
Automatic nonverbal analysis of social interaction in small groups: A review
Authors: Daniel Gatica-Perez
Venue: Image and Vision Computing (2009)

An increasing awareness of the scientific and technological value of the automatic understanding of face-to-face social interaction has motivated in the past few years a surge of interest in the devising of computational techniques for conversational analysis. As an alternative to existing linguistic approaches for the automatic analysis of conversations, a relatively recent domain is using findings in social cognition, social psychology, and communication that have established the key role that nonverbal communication plays in the formation, maintenance, and evolution of a number of fundamental social constructs, which emerge from face-to-face interactions in time scales that range from short glimpses all the way to long-term encounters. Small group conversations are a specific case on which much of this work has been conducted. This paper reviews the existing literature on automatic analysis of small group conversations using nonverbal communication, and aims at bridging the current fragmentation of the work in this domain, currently split among half a dozen technical communities. The review is organized around the main themes studied in the literature and discusses, in a comparative fashion, about 100 works addressing problems related to the computational modeling of interaction management, internal states, personality traits, and social relationships in small group conversations, along with pointers to the relevant literature in social science. Some of the many open challenges and opportunities in this domain are also discussed.
Fast-Robust PCA
Authors: Markus Storer, Peter M. Roth, Martin Urschler, Horst Bischof
Venue: Proceedings of the 16th Scandinavian Conference on Image Analysis (2009)

Principal Component Analysis (PCA) is a powerful and widely used tool in Computer Vision and is applied, e.g., for dimensionality reduction. But as a drawback, it is not robust to outliers. Hence, if the input data is corrupted, an arbitrarily wrong representation is obtained. To overcome this problem, various methods have been proposed to robustly estimate the PCA coefficients, but these methods are computationally too expensive for practical applications. Thus, in this paper we propose a novel fast and robust PCA (FR-PCA), which drastically reduces the computational effort. Moreover, more accurate representations are obtained. In particular, we propose a two-stage outlier detection procedure, where in the first stage outliers are detected by analyzing a large number of smaller subspaces. In the second stage, remaining outliers are detected by a robust least-square fitting. To show these benefits, in the experiments we evaluate the FR-PCA method for the task of robust image reconstruction on the publicly available ALOI database. The results clearly show that our approach outperforms existing methods in terms of accuracy and speed when processing corrupted data.
UISK: Supporting Model-Driven and Sketch-Driven Paperless Prototyping
Authors: Vinícius Costa Segura, Simone Diniz Barbosa
Venue: Proceedings of the 13th International Conference on Human-Computer Interaction. Part I: New Trends (2009)

Sketches are often used during user interface design and evaluation as both a design support tool and a communication tool. Despite recent efforts, computational support to user interface sketching has not yet reached its full potential. This paper reports a study comparing two evaluation techniques: paper prototyping and a simulation-based evaluation supported by the UISKEI tool.
Model Analysis and Performance Assessment of Electrical Motorcycles
Authors: P. S. Pa, S. C. Chang
Venue: Proceedings of the 2009 International Conference on Measuring Technology and Mechatronics Automation - Volume 02 (2009)

This study discusses the construction of an electric motorcycle simulation system. It is applicable for children’s toy motorcycles and adults’ motorcycles, and also is a reference for constructing larger electric vehicles. The complete model of the electric motorcycle is established by establishing models of individual components (such as battery, motor, transmission, etc.) based upon their characteristics and properties. Using the Matlab and Simulink software program model to simulate performance, the parameters of the model can be easily changed according to design and demand. To compare simulation results with actual test data, the model can effectively reconstruct the physical properties of the electric motorcycle, such as acceleration, velocity, energy efficiency, etc. By evaluating the simulation results, a simulator can provide valuable data to design and analyze electric motorcycle prototypes. Therefore, rapid prototyping and hardware-in–the-loop can be achieved to speed up the development of new vehicles.
Enabling affordable and efficiently deployed location based smart home systems
Authors: Damian Kelly, Sean McLoone, Terry Dishongh
Venue: Technology and Health Care (2009)

With the obvious eldercare capabilities of smart environments it is a question of "when", rather than "if", these technologies will be routinely integrated into the design of future houses. In the meantime, health monitoring applications must be integrated into already complete home environments. However, there is significant effort involved in installing the hardware necessary to monitor the movements of an elder throughout an environment. Our work seeks to address the high infrastructure requirements of traditional location-based smart home systems by developing an extremely low infrastructure localisation technique. A study of the most efficient method of obtaining calibration data for an environment is conducted and different mobile devices are compared for localisation accuracy and cost trade-off. It is believed that these developments will contribute towards more efficiently deployed location-based smart home systems.
Extending the entity-grid coherence model to semantically related entities
Authors: Katja Filippova, Michael Strube
Venue: Proceedings of the Eleventh European Workshop on Natural Language Generation (2007)

This paper reports on work in progress on extending the entity-based approach on measuring coherence (Barzilay & Lapata, 2005; Lapata & Barzilay, 2005) from coreference to semantic relatedness. We use a corpus of manually annotated German newspaper text (T&uuml;Ba-D/Z) and aim at improving the performance by grouping related entities with the WikiRelate! API (Strube & Ponzetto, 2006).
A Rewriting Logic Approach to Type Inference
Authors: Chucky Ellison, Traian Florin Şerbănuţă, Grigore Roşu
Venue: Recent Trends in Algebraic Development Techniques: 19th International Workshop, WADT 2008, Pisa, Italy, June 13-16, 2008, Revised Selected Papers (2009)

Meseguer and Roşu proposed rewriting logic semantics (RLS) as a programing language definitional framework that unifies operational and algebraic denotational semantics. RLS has already been used to define a series of didactic and real languages, but its benefits in connection with defining and reasoning about type systems have not been fully investigated. This paper shows how the same RLS style employed for giving formal definitions of languages can be used to define type systems. The same term-rewriting mechanism used to execute RLS language definitions can now be used to execute type systems, giving type checkers or type inferencers. The proposed approach is exemplified by defining the Hindley-Milner polymorphic type inferencer $\mathcal{W}$ as a rewrite logic theory and using this definition to obtain a type inferencer by executing it in a rewriting logic engine. The inferencer obtained this way compares favorably with other definitions or implementations of $\mathcal{W}$. The performance of the executable definition is within an order of magnitude of that of highly optimized implementations of type inferencers, such as that of OCaml.
FIR filter optimization using bit-edge equalization in high-speed backplane data transmission
Authors: Lei Zhang, Tadeusz Kwasniewski
Venue: Microelectronics Journal (2009)

A unique bit-edge equalization (BEE) method for mitigating intersymbol interference (ISI) in high-speed backplane applications is presented. Using a least-mean-square (LMS) adaptive algorithm as a receiver (RX) error convergence engine, the proposed BEE method aims to optimize the bit-edge amplitudes by equalizing only the edges of data bits with an adjustment of the sampling points where the error information is collected. This adjustment of sampling points in turn changes the error information and affects filter coefficients for pulse amplitude modulation. As a result, the channel's far-end 3-level bit-edge eye diagrams can be optimized. This proposed BEE method employs transmitter (TX) pre-coding in conjunction with TX pre-emphasis using a symbol-spaced FIR (SSF) filter. In this work, a detailed analytical comparison of the proposed BEE transceiver architecture with the conventional NRZ bit-centre equalization (BCE) and duobinary transceiver architectures is presented. The simulation results demonstrate that at 10+Gbps data rates, the proposed BEE is the most effective method for mitigating ISI in relatively high-loss channels.
Data Mining Using Graphics Processing Units
Authors: Christian Böhm, Robert Noll, Claudia Plant, Bianca Wackersreuther, Andrew Zherdin
Venue: Transactions on Large-Scale Data- and Knowledge-Centered Systems I (2009)

During the last few years, Graphics Processing Units (GPU) have evolved from simple devices for the display signal preparation into powerful coprocessors that do not only support typical computer graphics tasks such as rendering of 3D scenarios but can also be used for general numeric and symbolic computation tasks such as simulation and optimization. As major advantage, GPUs provide extremely high parallelism (with several hundred simple programmable processors) combined with a high bandwidth in memory transfer at low cost. In this paper, we propose several algorithms for computationally expensive data mining tasks like similarity search and clustering which are designed for the highly parallel environment of a GPU. We define a multidimensional index structure which is particularly suited to support similarity queries under the restricted programming model of a GPU, and define a similarity join method. Moreover, we define highly parallel algorithms for density-based and partitioning clustering. In an extensive experimental evaluation, we demonstrate the superiority of our algorithms running on GPU over their conventional counterparts in CPU.
Handling inheritance violation for secure interoperation of heterogeneous systems
Authors: Hejiao Huang, Helene Kirchner, Songyun Liu, Weili Wu
Venue: International Journal of Security and Networks (2009)

In multiple heterogeneous systems, one of key challenges of integrating policies is the conflict detection and resolution while preserving individual policy consistency. In this paper, the inheritance hierarchy of a security policy is formulated with a directed graph. Solving Inheritance Violation Problem (IVP) is formulated as a feedback arc set problem, which is NP-hard. Then some classical approximation algorithms are introduced. The IVP in two interoperating domains is converted into the problem of finding a minimum weight vertex cover problem in a bipartite graph, which is polynomial-time solvable.
Parallel Evidence Propagation on Multicore Processors
Authors: Yinglong Xia, Xiaojun Feng, Viktor K. Prasanna
Venue: Proceedings of the 10th International Conference on Parallel Computing Technologies (2009)

In this paper, we design and implement an efficient technique for parallel evidence propagation on state-of-the-art multicore processor systems. Evidence propagation is a major step in exact inference, a key problem in exploring probabilistic graphical models. We propose a rerooting algorithm to minimize the critical path in evidence propagation. The rerooted junction tree is used to construct a directed acyclic graph (DAG) where each node represents a computation task for evidence propagation. We develop a collaborative scheduler to dynamically allocate the tasks to the cores of the processors. In addition, we integrate a task partitioning module in the scheduler to partition large tasks so as to achieve load balance across the cores. We implemented the proposed method using Pthreads on both AMD and Intel quadcore processors. For a representative set of junction trees, our method achieved almost linear speedup. The execution time of our method was around twice as fast as the OpenMP based implementation on both the platforms.
Study of PID Control System for Ant Colony Algorithm
Authors: Hong He, Fang Liu, Li Li, Jin-Rong Yang, Lei Su, Yi Wu
Venue: Proceedings of the 2009 WRI Global Congress on Intelligent Systems - Volume 01 (2009)

The key of PID control systematic optimization design is PID parameter optimization. Traditional PID controller parametesr adopt experiment to add the way of trying to carry out optimization by man. It is fairly time-consuming, PID controller have no self-adaptive ability, can only rely on artificialoptimization parameter. This paper puts forward a kind of algorithm to select thePID parameters based on the crowd algorithm of ant. Scientists have put forward the crowd algorithm of ant by imitating the ant collective in nature and. Imitation research has shown the validity of this algorithm. this algorithm have surmounted the disadvantages of traditional PID regulator parameter optimization.
Algorithm for Application of Evolution Rules Based on Linear Diofantic Equations
Authors: Alberto Arteta, Luis Fernandez, Javier Gil
Venue: Proceedings of the 2008 10th International Symposium on Symbolic and Numeric Algorithms for Scientific Computing (2008)

Transition P System are a parallel and distributedcomputational model based on the notion of the cellularmembrane structure. Each membrane determines a region thatencloses a multiset of objects and evolution rules. Transition P Systems evolve through transitions between two consecutive configurations. Moreover, transitions between two consecutive configurations are provided by an exhaustive non-deterministic and parallel application of evolution rules inside each membrane of the P system. Hence, rules application is critical for the wholeevolution process efficiency, because it is performed in parallel inside each membrane in each one of the evolution steps. It is known that P systems have a high degree of nondeterminism and parallelism. A transition in such a system consists in applying in parallel a set of atomic actions (e.g.,evolution rules) and this set of atomic actions is randomly chosen from a domain of possiblenext transitions. This paper tries to characterize this domain as the hyperspace defined by a set of diophantine equations and then to develop an algorithm which randomly chooses solutions from this hyperspace. Those solutions are uniquely related to the number of times that certain evolution rules are applied. The work presented here includes an algorithm based on resolving linear systems equations and explain into detail the process that the algorithm must follow
Distribution-free learning of Bayesian network structure in continuous domains
Authors: Dimitris Margaritis
Venue: Proceedings of the 20th national conference on Artificial intelligence - Volume 2 (2005)

In this paper we present a method for learning the structure of Bayesian networks (BNs) without making any assumptions on the probability distribution of the domain. This is mainly useful for continuous domains, where there is little guidance and many choices for the parametric distribution families to be used for the local conditional probabilities of the Bayesian network, and only a few have been examined analytically. We therefore focus on BN structure learning in continuous domains. We address the problem by developing a conditional independence test for continuous variables, which can be readily used by any existing independence-based BN structure learning algorithm. Our test is non-parametric, making no assumptions on the distribution of the domain. We also provide an effective and computationally efficient method for calculating it from data. We demonstrate the learning of the structure of graphical models in continuous domains from real-world data, to our knowledge for the first time using independence-based methods and without distributional assumptions. We also experimentally show that our test compares favorably with existing statistical approaches which use prediscretization, and verify desirable properties such as statistical consistency.
Interactive Object Segmentation System from a Video Sequence
Authors: Guntae Bae, Sooyeong Kwak, Hyeran Byun
Venue: Proceedings of the Symposium on Human Interface 2009 on Human Interface and the Management of Information. Information and Interaction. Part II: Held as part of HCI International 2009 (2009)

In this paper, we present an interactive object segmentation system form video, such as TV products and films, for converting 2D to 3D contents. It is focused on reducing the processing time for the object segmentation, increasing the usability. The proposed system is consist of three steps which are trimap generation based on polygon and object segmentation using Graph Cut algorithm and refinement by a user interfaces (UI) based on rectangle and local features. It makes it easy to get object segmentation rapidly. It is also helpful to create 3D contents.