ppxscal/embedding_network huggingface dataset:
BMPGA: A Bi-objective Multi-population Genetic Algorithm with Applications to Multi-modal Optimization Problems
Authors: Jie Yao
Venue:  (2009)

This dissertation presents a novel Bi-objective Multi-population Genetic Algorithm (BMPGA) for multimodal optimization problems. BMPGA is distinguished by its use of two separate but complementary fitness objectives designed to enhance the diversity of the overall population and exploration of the search space. This is coupled with a multi-population strategy and a clustering scheme, both of which together focus selection pressure within sub-populations, resulting in improved exploitation of promising optimum areas as well as effective identification and retention of potential optima. The practical value of BMPGA is demonstrated in several applications including optimization of benchmark multimodal functions and detection of imagery ellipses. BMPGA is compared with widely used algorithms and exhibits solid advantages over them. BMPGA is also extended to the segmentation of microscopic cells, which is a necessary first step of many automated biomedical image processing procedures. 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
NFC-Based Mobile Interactions with Direct-View Displays
Authors: Khoovirajsingh Seewoonauth, Enrico Rukzio, Robert Hardy, Paul Holleis
Venue: Proceedings of the 12th IFIP TC 13 International Conference on Human-Computer Interaction: Part I (2009)

Two NFC-based interactions are described in the paper. The first interaction technique is referred to as Touch Connect: a process by which an NFC tag is used to rapidly pair a mobile device with a computer. The second interaction technique is referred to as Touch Select, and considerably extends the Touch Connect concept by allowing the use of an NFC-enabled mobile phone to directly touch at, and select, an object on the computer screen. We achieve this by attaching a grid of NFC tags to the back of the screen. A picture browsing application has been developed in order to compare Touch Connect and Touch Select with the currently available Bluetooth-based approach. Our most salient findings show a considerable task time decrease for Touch-and-Connect (31%) and Touch-and-Select (43%) over the standard Bluetooth approach for picture browsing tasks.
A Topology Based Approach for Context-Awareness in Smart Environments
Authors: Antonio Coronato, Giuseppe Pietro
Venue: Proceedings of the 9th International Conference on Smart Spaces and Next Generation Wired/Wireless Networking and Second Conference on Smart Spaces (2009)

This paper presents logic models and mechanisms to achieve context awareness and future context awareness. The proposed approach relies on handling the topology of the physical environment. We describe methods and tools to specify and implement topology services that can provide mechanisms for both rapid prototyping application services and handling context awareness information. Finally, we report some case studies and applications of the proposed approach.
Speaking without knowing what to say&hellip;or when to end
Authors: Anna Hjalmarsson
Venue: Proceedings of the 9th SIGdial Workshop on Discourse and Dialogue (2008)

Humans produce speech incrementally and on-line as the dialogue progresses using information from several different sources in parallel. A dialogue system that generates output in a stepwise manner and not in preplanned syntactically correct sentences needs to signal how new dialogue contributions relate to previous discourse. This paper describes a data collection which is the foundation for an effort towards more human-like language generation in DEAL, a spoken dialogue system developed at KTH. Two annotators labelled cue phrases in the corpus with high inter-annotator agreement (kappa coefficient 0.82).
Cross-Domain Interoperability: A Case Study
Authors: Jukka Honkola, Hannu Laine, Ronald Brown, Ian Oliver
Venue: Proceedings of the 9th International Conference on Smart Spaces and Next Generation Wired/Wireless Networking and Second Conference on Smart Spaces (2009)

We describe a case study of the behaviour of four agents using a space based communication architecture. We demonstrate that interoperability may be achieved by the agents merely describing information about themselves using an agreed upon common ontology. The case study consists of an exercise logger, a game, a mood rendered attached to audio player and phone status observing agents. The desired scenario emerges from the independent actions of the agents.
A reversible information hiding scheme using left-right and up-down chinese character representation
Authors: Zhi-Hui Wang, Chin-Chen Chang, Chia-Chen Lin, Ming-Chu Li
Venue: Journal of Systems and Software (2009)

Techniques for text data hiding are different from image data hiding, video data hiding and audio data hiding. To break through the difficulty of text data hiding, Sun, Lou and Huang proposed a novel Chinese text data hiding scheme called the L-R scheme. In the L-R scheme, Sun et al. embedded secrets into Chinese characters that can be divided into left and right components. This paper describes how our proposed scheme extends the component concept to incorporate the up and down components of Chinese characters rather than the left and right components only, to significantly enhance hiding capacity. In addition, this paper adds a reversible function to Sun et al.'s L-R scheme to make it possible for receivers to obtain the original cover text and use it repeatedly for later transmission of secrets after the initial hidden secrets have been extracted. Finally, the extended scheme simplifies the extracting procedure and efficiently reduces the memory required on the receiver side during the secret extracting phase by using a new comparison method. Experimental results confirm the improved functions offered by the proposed scheme.
Tolerant Linearity Testing and Locally Testable Codes
Authors: Swastik Kopparty, Shubhangi Saraf
Venue: Proceedings of the 12th International Workshop and 13th International Workshop on Approximation, Randomization, and Combinatorial Optimization. Algorithms and Techniques (2009)

We study tolerant linearity testing under general distributions. Given groups G and H, a distribution μ on G, and oracle access to a function f:G ¿H, we consider the task of approximating the smallest μ-distance of f to a homomorphism h:G¿H, where the μ-distance between f and h is the probability that $f(x) \ne h(x)$ when x is drawn according to the distribution μ. This question is intimately connected to local testability of linear codes.In this work, we give a general sufficient condition on the distribution μ for linearity to be tolerantly testable with a constant number of queries. Using this condition we show that linearity is tolerantly testable for several natural classes of distributions including low bias, symmetric and product distributions. This gives a new and simple proof of a result of Kaufman and Sudan which shows that sparse, unbiased linear codes over are locally testable.
Information-theoretic feature selection for functional data classification
Authors: Vanessa Gómez-Verdejo, Michel Verleysen, Jérôme Fleury
Venue: Neurocomputing (2009)

The classification of functional or high-dimensional data requires to select a reduced subset of features among the initial set, both to help fighting the curse of dimensionality and to help interpreting the problem and the model. The mutual information criterion may be used in that context, but it suffers from the difficulty of its estimation through a finite set of samples. Efficient estimators are not designed specifically to be applied in a classification context, and thus suffer from further drawbacks and difficulties. This paper presents an estimator of mutual information that is specifically designed for classification tasks, including multi-class ones. It is combined to a recently published stopping criterion in a traditional forward feature selection procedure. Experiments on both traditional benchmarks and on an industrial functional classification problem show the added value of this estimator.
Password Cracking Using Probabilistic Context-Free Grammars
Authors: Matt Weir, Sudhir Aggarwal, Breno de Medeiros, Bill Glodek
Venue: Proceedings of the 2009 30th IEEE Symposium on Security and Privacy (2009)

Choosing the most effective word-mangling rules to use when performing a dictionary-based password cracking attack can be a difficult task. In this paper we discuss a new method that generates password structures in highest probability order. We first automatically create a probabilistic context-free grammar based upon a training set of previously disclosed passwords. This grammar then allows us to generate word-mangling rules, and from them, password guesses to be used in password cracking. We will also show that this approach seems to provide a more effective way to crack passwords as compared to traditional methods by testing our tools and techniques on real password sets. In one series of experiments, training on a set of disclosed passwords, our approach was able to crack 28% to 129% more passwords than John the Ripper, a publicly available standard password cracking program.
Research on Environment Investment Management System Based on WebGIS
Authors: Deng Hongbing, Wen Yuyuan
Venue: Proceedings of the 2009 International Conference on Environmental Science and Information Application Technology - Volume 02 (2009)

This text studied the problem of designing the investment environment management information system which is based on the WebGIS, The text probed into the systematic target from 6 aspects and analyzed the problem of system design form database management information system, the visualization of investment environment evaluation and management, and analyzed the constraction and function of the system and the way of realizing and the key technology.
Mind your left: Spatial bias in subcortical fear processing
Authors: Tali Siman-Tov, David Papo, Natan Gadoth, Tom Schonberg, Avi Mendelsohn, Daniella Perry, Talma Hendler
Venue: Journal of Cognitive Neuroscience (2009)

Hemispheric lateralization of emotional processing has long been suggested, but its underlying neural mechanisms have not yet been defined. In this functional magnetic resonance imaging study, facial expressions were presented to 10 right-handed healthy adult females in an event-related visual half-field presentation paradigm. Differential activations to fearful versus neutral faces were observed in the amygdala, pulvinar, and superior colliculus only for faces presented in the left hemifield. Interestingly, the left hemifield advantage for fear processing was observed in both hemispheres. These results suggest a leftward bias in subcortical fear processing, consistent with the well-documented leftward bias of danger-associated behaviors in animals. The current finding highlights the importance of hemifield advantage in emotional lateralization, which might reflect the combination of hemispheric dominance and asymmetric interhemispheric information transfer.
Research of Automatic Recognition Algorithm of Chinese-sensible Code
Authors: Sun Ming, Fang Zhenkun, Fu Longsheng, Zhang Shuhuai
Venue: Proceedings of the 2009 WRI Global Congress on Intelligent Systems - Volume 04 (2009)

For the collected barcode image, an image processing method with the ability of locating, segmenting, correcting and recognizing the Chinese-sensible code is introduced. In order to meet the real-time demands and obtain the optimal thresholding under various lighting conditions, we proposed the improved adaptive thresholding algorithm, which is proved both high efficiency and high stability. The ratios of each module in the finder pattern are used to obtain the functional information and determine the structure of barcode. For the distorted barcode images, the relative locations of finder patterns, alignment patterns and auxiliary alignment patterns are taken advantage of to divide the barcode image into several sub-regions. And then, the affine transformation is employed to correct sub-regions into normal. The results showed that this method can correct the distortion of symbols effectively.
Dynamic liquid association: Complex learning without implausible guidance
Authors: Anthony Morse, Malin Aktius
Venue: Neural Networks (2009)

Simple associative networks have many desirable properties, but are fundamentally limited by their inability to accurately capture complex relationships. This paper presents a solution significantly extending the abilities of associative networks by using an untrained dynamic reservoir as an input filter. The untrained reservoir provides complex dynamic transformations, and temporal integration, and can be viewed as a complex non-linear feature detector from which the associative network can learn. Typically reservoir systems utilize trained single layer perceptrons to produce desired output responses. However given that both single layer perceptions and simple associative learning have the same computational limitations, i.e. linear separation, they should perform similarly in terms of pattern recognition ability. Further to this the extensive psychological properties of simple associative networks and the lack of explicit supervision required for associative learning motivates this extension overcoming previous limitations. Finally, we demonstrate the resulting model in a robotic embodiment, learning sensorimotor contingencies, and matching a variety of psychological data.
Discrete Driver Assistance
Authors: Reinhard Klette, Ruyi Jiang, Sandino Morales, Tobi Vaudrey
Venue: Proceedings of the 9th International Symposium on Mathematical Morphology and Its Application to Signal and Image Processing (2009)

Applying computer technology, such as computer vision in driver assistance, implies that processes and data are modeled as being discretized rather than being continuous. The area of stereo vision provides various examples how concepts known in discrete mathematics (e.g., pixel adjacency graphs, belief propagation, dynamic programming, max-flow/min-cut, or digital straight lines) are applied when aiming for efficient and accurate pixel correspondence solutions. The paper reviews such developments for a reader in discrete mathematics who is interested in applied research (in particular, in vision-based driver assistance). As a second subject, the paper also discusses lane detection and tracking, which is a particular task in driver assistance; recently the Euclidean distance transform proved to be a very appropriate tool for obtaining a fairly robust solution.
Parallelization Strategies for Mixed Regular-Irregular Applications on Multicore-Systems
Authors: Gudula Rünger, Michael Schwind
Venue: Proceedings of the 8th International Symposium on Advanced Parallel Processing Technologies (2009)

Scientific simulation codes often exhibit a mixed structure of regular and irregular data accesses. Since the organization of data accesses has a large influence on the overall performance of parallel code, a careful planning of parallelism is required. In this article, we consider a mixed regular-irregular particle simulation code and investigate several parallelization strategies for multicore architectures consisting of several multicore processors in a shared memory system. The interaction of irregular and regular data accesses are the specific challenge for a cache optimized parallel multicore-code. We present performance experiments on three different multicore systems and show that a mixture of parallelization techniques for irregular and regular applications leads to the best performance.
Fuzzy Self-Adaptive PID Controller for Freeway Ramp Metering
Authors: Tao Jiang, Xinrong Liang
Venue: Proceedings of the 2009 International Conference on Measuring Technology and Mechatronics Automation - Volume 02 (2009)

Aiming at the nonlinear and time-varying characteristics of freeway traffic system, a fuzzy self-adaptive PID controller is designed and applied to freeway ramp metering in this paper. A traffic flow model to describe the freeway flow process is firstly built. Based on the model and in conjunction with nonlinear feedback theory, a fuzzy-PID ramp controller is then designed. The ramp metering rate is determined by the PID controller whose parameters are tuned by fuzzy logic according to the density tracking error and error variation. Gauss and triangle curves are used for the membership functions of the fuzzy variables. The rule base including 49 fuzzy rules is also established. Finally, the control system is simulated in MATLAB software. The results show that this controller designed has fast response, good dynamic and steady-state performance. It can achieve a desired traffic density along the mainline of a freeway, and can make vehicles travel more efficiently and safely. This approach is quite effective to freeway ramp metering.
On Yen's Path Logic for Petri Nets
Authors: Mohamed Faouzi Atig, Peter Habermehl
Venue: Proceedings of the 3rd International Workshop on Reachability Problems (2009)

In [13], Yen defines a class of formulas for paths in Petri nets and claims that its satisfiability problem is expspace-complete. In this paper, we show that in fact the satisfiability problem for this class of formulas is as hard as the reachability problem for Petri nets. Moreover, we salvage almost all of Yen's results by defining a fragment of this class of formulas for which the satisfiability problem is expspace-complete by adapting his proof.
Essential Graphs and Bayesian Networks
Authors: Angel Garrido
Venue: Proceedings of the 2008 First International Conference on Complexity and Intelligence of the Artificial and Natural Complex Systems. Medical Applications of the Complex Systems. Biomedical Computing (2008)

Our purpose in this paper is to show how it is possible to obtain improved tools, in a computational sense, for Learning Bayesian Networks (LBNs). And also give a more mathematically consistent and complete formulation.First, by the partition in equivalence classes, and then selecting a graph as representative of each one of them, the so called Essential Graph.Second, analyzing the asymptotical behavior of the ratio among the cardinal of equivalence classes (therefore, of essential graphs) and the cardinal of Directed Acyclic Graphs (DAGs) of order n, and reciprocally, when this number of nodes tends to infinity. This study is made in both algebraic and geometrical ways. Finally, we describe the future research lines, in LBNs and Probabilistic Graphical Models (PGMs), by new algebraic and geometrical tools.
An adaptive field rule for non-parametric MRI intensity inhomogeneity estimation algorithm
Authors: Maite García-Sebastián, Ana Isabel González, Manuel Graña
Venue: Neurocomputing (2009)

A widely accepted magnetic resonance imaging (MRI) model states that the observed voxel intensity is a piecewise constant signal intensity function corresponding to the tissue spatial distribution, corrupted with multiplicative and additive noise. The multiplicative noise is assumed to be a smooth bias field, it is called intensity inhomogeneity (IIH) field. Our approach to IIH correction is based on the definition of an energy function that incorporates some smoothness constraints into the conventional classification error function of the IIH corrected image. The IIH field estimation algorithm is a gradient descent of this energy function relative to the IIH field. We call it adaptive field rule (AFR). We comment on the likeness of our approach to the self-organizing map (SOM) learning rule, on the basis of the neighboring function that controls the influence of the neighborhood on each voxel's IIH estimation. We discuss the convergence properties of the algorithm. Experimental results show that AFR compares well with state of the art algorithms. Moreover, the mean signal intensity corresponding to each class of tissue can be estimated from the image data applying the gradient descent of the proposed energy function relative to the intensity class means. We test several variations of this gradient descent approach, which embody diverse assumptions about available a priori information.
Harmonic Gait under Primitive DOF for Biped Robot
Authors: Shigeki Sugiyama
Venue: Proceedings of the 2nd International Conference on Digital Human Modeling: Held as Part of HCI International 2009 (2009)

Here argues about an effective and an energy less-consuming walking for a humanoid type of robot. There are many humanoid types of robots in the world that can walk, run, dance, and get up, etc. Those are mostly used and enjoyed in the field of entertainment for kids' pleasures. For any other usages, humanoid types of robots are not practical enough in a daily life usage or in factory usages or in any others. Because the robotics movements are not smooth enough and not effective enough for doing things in them, that is to say, the stable biped walking and the energy optimization biped walking (series of those walking figures) could not meet the necessary conditions for the expected usages or for other purposes. So here introduces a new idea of humanoid type of harmonic gait, which makes a robot move more effectively and an energy less-consuming walking.
A Journey to the Core of the Blogosphere
Authors: Darko Obradovic, Stephan Baumann
Venue: Proceedings of the 2009 International Conference on Advances in Social Network Analysis and Mining (2009)

Blogs are popular communication instruments in today's web and altogether, they form the so-called blogosphere. This blogosphere has repeatedly been subject to structural analyses, and one of the findings has been the discovery of the A-List phenomenon, a cohesive group of influential blogs in the center of the blogosphere, whose exact identification remained an open issue. We use four language-specific subsets of the blogosphere, for which we aggregated the blogroll-based networks. We adapt core theory to analyse and compare the cohesion in these four data-sets, and provide a new scalable method for the identification of core-periphery structures in blog networks, which can contribute to identify A-List blogs more reliably.
Owner-Centric Networking (OCN): Toward a Data Pollution-Free Internet
Authors: Claude Castelluccia, Mohamed Ali Kaafar
Venue: Proceedings of the 2009 Ninth Annual International Symposium on Applications and the Internet (2009)

In this paper, we propose OCN (Owner-Centric Networking), a new Internet architecture that provides individuals control over their contents. We argue that this architecture would considerably improve privacy on the Internet by limiting data pollution.
Mathematics of FuzzinessBasic Issues, 1st edition
Authors: Xuzhu Wang, Da Ruan, Etienne E. Kerre
Venue: Studies In Fuzziness And Soft Computing (2009)

"Mathematics of Fuzziness: Basic Issues" introduces a basic notion of 'fuzziness' and provides a conceptual mathematical framework to characterize such fuzzy phenomena in "Studies in Fuzziness and Soft Computing". The book systematically presents a self-contained introduction to the essentials of mathematics of fuzziness ranging from fuzzy sets, fuzzy relations, fuzzy numbers, fuzzy algebra, fuzzy measures, fuzzy integrals, and fuzzy topology to fuzzy control in a strictly mathematical manner. It contains most of the authors' research results in the field of fuzzy set theory and has evolved from the authors' lecture notes to both undergraduate and graduate students over the last three decades. A lot of exercises in each chapter of the book are particularly suitable as a textbook for any undergraduate and graduate student in mathematics, computer science and engineering. The reading of the book will surely lay a solid foundation for further research on fuzzy set theory and its applications.