ppxscal/embedding_network huggingface dataset:
An adaptive middleware for supporting time-critical event response
Authors: Qian Zhu, Gagan Agrawal
Venue: Cluster Computing (2009)

There are many applications where a timely response to an important event is needed. Often such response can require significant computation and possibly communication, and it can be very challenging to complete it within the time-frame the response is needed. At the same time, there could be application-specific flexibility in the computation that may be desired.This paper presents the design, implementation, and evaluation of a middleware that can support such applications. Each of the services in our target applications could have one or more service parameters, which can be modified, within the pre-specified ranges, by the middleware. The middleware enables the time-critical event handling to achieve the maximum benefit, as per the user-defined benefit function, while satisfying the time constraint. Our middleware is also based on the existing Grid infrastructure and Service-Oriented Architecture (SOA) concepts. We have evaluated our middleware and its support for adaptation using a volume rendering application and a Great Lake forecasting application. The evaluation shows that our adaptation is effective, and has a very low overhead.
Self-calibrated visual servoing with respect to axial-symmetric 3D objects
Authors: Duccio Fioravanti, Carlo Colombo, Benedetto Allotta
Venue: Robotics and Autonomous Systems (2009)

A self-calibrated approach to visual servoing with respect to non-planar targets modeled through a pair of coaxial circles plus one point is discussed. Full calibration data (fixed internal parameters) are obtained from two views, and used to recover the Euclidean structure of an auxiliary virtual plane associated to the target, together with the relative pose of the camera. Pose disambiguation is achieved without requiring any real third view of the target. The approach benefits of an off-line planning strategy by which the camera follows a 3D helicoidal path around an arbitrarily chosen axis. A convenient choice for the helicoidal axis is found to be that of the target axis itself. Simulation results demonstrate that the approach is robust with respect to noise both in the off-line and on-line control phases.
Supporting transitions in work: informing large display application design by understanding whiteboard use
Authors: Anthony Tang, Joel Lanir, Saul Greenberg, Sidney Fels
Venue: Proceedings of the ACM 2009 international conference on Supporting group work (2009)

In this paper, we explore the practice of using a whiteboard for multiple tasks, and specifically how users employ whiteboards to smoothly transition between related sets of tasks. Our study underscores several basic, but important affordances of whiteboards that support this practice, including visual persistence, flexibility of interaction primitives, and their situated physicality. We discuss the implications of these findings for the design of large display applications.
A Framework for Component Categories
Authors: Emmanuel Haucourt
Venue: Electronic Notes in Theoretical Computer Science (ENTCS) (2009)

This paper provides further developments in the study of the component categories which have been introduced in [Fajstrup, L., E. Goubault, E. Haucourt and M. Rauszen, Component categories and the fundamental category, APCS 12 (2004), pp. 81-108]. In particular, the component category functor is seen as a left adjoint hence preserves the pushouts. This property is applied to prove a Van Kampen like theorem for component categories. This last point is very important to make effective calculations. The original purpose of component categories is to suitably reduce the size of the fundamental categories which are the directed counterpart of classical fundamental groupoids (see [Higgins, P.J., ''Categories and Groupoids,'' Mathematical Studies 32, Van Nostrand Reinhold, 1971, libre d'accs sur internet l'adresse http://www.tac.mta.ca/tac/reprints/]). In concrete examples, the fundamental category is as ''big'' as R while the component category is ''finitely generated''. We take advantage of this fact to define the cohomology of a directed geometrical shape as the cohomology of its component category. The cohomology of small categories is defined in [Baues, H.J. and G. Wirsching, Cohomology of small categories, Journal of Pure and Applied Algebra 38 (1985)] and [Baues, H.J., ''Combinatorial Homotopy and 4-Dimensional Complexes,'' De Gruyter expositions in Mathematics 2, Walter de Gruyter, 1991]. Still, in the recent paper [Husainov, A.A., On the homolgy of small categories and asynchronous transition systems, Homology, Homotopy and Applications 6 (2004), pp. 439-471], the homology of small categories is defined in a very similar way and applied to the study of asynchronous transition systems.
A clustering framework for task partitioning based on function-level data usage analysis
Authors: S. Arash Ostadzadeh, Roel J. Meeuws, Kamana Sigdel, Koen Bertels
Venue: Proceeding of the ACM/SIGDA international symposium on Field programmable gate arrays (2009)

Recently, reconfigurable computing has received a great deal of attention due to its ability to increase an application performance with hardware execution, while possessing the flexibility of software solution. One of the major requirements for such systems is to identify which application or part of the application can be implemented as software and which can be mapped onto reconfigurable devices. Grouping the tasks within an application can intensify coarse-grained partitioning of the application, which can eventually improve the performance of the system. In this work, we introduce a clustering framework along with a flexible multipurpose clustering algorithm that initiates task clustering at the functional level based on dynamic profiling information. The clustering framework can be used as the basic step to modify the granularity of tasks in the hardware/software partitioning and scheduling phases. As a result, an elaborate mapping onto the system resources and possibly a higher degree of task parallelism can be obtained. In an initial attempt, the framework addresses two primary objectives to create workload-balanced and loosely-coupled clusters. The experimental results show that the clustering complies with the desired metrics, which were defined through the objectives.
Aspects of modelling in computer aided geometric design
Authors: Richard F. Riesenfeld
Venue: Proceedings of the May 19-22, 1975, national computer conference and exposition (1975)

This paper identifies some problems of modelling free-form geometry in a computer, and discusses attributes of a good model and good parameters for a model. In particular, we are interested in representing arbitrary shape information, shapes that may not have special names and may not be well defined except at particular points (or curves) of interest occasionally referred to as "hard points" or "hard constraints." There may remain considerable freedom in modelling the "soft points" or "soft constraints." Paradigms of this problem include modelling an automobile fender, a shoe last, or a boat hull. This is an aspect of an area that Forrest calls computational geometry.
A Sketch of a Complete Scheme for Tabled Execution Based on Program Transformation
Authors: Pablo Chico Guzmán, Manuel Carro, Manuel V. Hermenegildo
Venue: Proceedings of the 24th International Conference on Logic Programming (2008)

Tabled evaluation has proved to be an effective method to improve several aspects of goal-oriented query evaluation, including termination and complexity. "Native" implementations of tabled evaluation offer good performance, but also require significant implementation effort, affecting compiler and abstract machine. Alternatively, program transformation-based implementations, such as the original continuation call (CCall) technique, offer lower implementation burden at some efficiency cost. A limitation of the original CCall proposal is that it limits the interleaving of tabled and non-tabled predicates and thus cannot be used for arbitrary programs. In this work we present an extension of the CCall technique that allows the execution of arbitrary tabled programs, as well as some performance results. Our approach offers a useful tradeoff that can be competitive with state-of-the-art implementations, while keeping implementation effort relatively low.
Neurological Foundation of Image Processing
Authors: Andrzej W. Przybyszewski
Venue: Proceedings of the 2009 Seventh International Conference on Advances in Pattern Recognition (2009)

A popular computation approach is to process visual images by dividing them into crisp (winner-takes-all) parts in analog to properties of neurophysiological receptive fields. Problem with such symbolic representation is that in a real environment object attributes are seldom invariant. We propose to divide images into rough parts using hierarchical, multi-valued processes. The bottom-up computation (BUC) is related to prediction where object attributes are approximated by different granules with properties similar to different brain areas: by dots as in the thalamus, by oriented lines as in the primary visual cortex, and by elementary shapes as in V4. There are a large number of possible combinations of elementary granules; therefore objects in BUC are overrepresented. The top-down computation (TDC) fits prediction to hypothesis posed by more complex properties (higher brain areas). If the hypothesis check is positive, TDC verifies the object and eliminates other possible patterns. Such classifications take place in parallel at many functional units. We show an example of such hierarchical system computation on experimentally recorded data from monkey visual area (V4).
Adaptive threshold determination method for the dynamic filtering in wireless sensor networks using fuzzy logic
Authors: Sang Jin Lee, Hae Young Lee, Tae Ho Cho
Venue: Proceedings of the 3rd International Conference on Ubiquitous Information Management and Communication (2009)

Nodes in sensor networks can be easily compromised by an adversary because of hostile environments. An adversary may use compromised nodes to inject false reports into the network. The dynamic en-route scheme can detect and drop such false reports during the forwarding phase. In this scheme, choosing a threshold value is important, as it trades off between security power and energy consumption. Thus, we should choose a threshold value such that it provides sufficient resilience, yet is small enough to conserve energy. This paper presents a fuzzy-based threshold determination method for the dynamic en-route scheme to filter false reports in wireless sensor networks. The base station periodically determines the threshold value using a fuzzy rule-based system. The resilience and energy efficiency of the proposed method against false data injection attacks are shown by simulation.
Scalable satisfiability checking and test data generation from modeling diagrams
Authors: Yannis Smaragdakis, Christoph Csallner, Ranjith Subramanian
Venue: Automated Software Engineering (2009)

We explore the automatic generation of test data that respect constraints expressed in the Object-Role Modeling (ORM) language. ORM is a popular conceptual modeling language, primarily targeting database applications, with significant uses in practice. The general problem of even checking whether an ORM diagram is satisfiable is quite hard: restricted forms are easily NP-hard and the problem is undecidable for some expressive formulations of ORM. Brute-force mapping to input for constraint and SAT solvers does not scale: state-of-the-art solvers fail to find data to satisfy uniqueness and mandatory constraints in realistic time even for small examples. We instead define a restricted subset of ORM that allows efficient reasoning yet contains most constraints overwhelmingly used in practice. We show that the problem of deciding whether these constraints are consistent (i.e., whether we can generate appropriate test data) is solvable in polynomial time, and we produce a highly efficient (interactive speed) checker. Additionally, we analyze over 160 ORM diagrams that capture data models from industrial practice and demonstrate that our subset of ORM is expressive enough to handle their vast majority.
Characteristics-based effective applause detection for meeting speech
Authors: Yan-Xiong Li, Qian-Hua He, Sam Kwong, Tao Li, Ji-Chen Yang
Venue: Signal Processing (2009)

Applause frequently occurs in multi-participants meeting speech. In fact, detecting applause is quite important for meeting speech recognition, semantic inference, highlight extraction, etc. In this paper, we will first study the characteristic differences between applause and speech, such as duration, pitch, spectrogram and occurrence locations. Then, an effective algorithm based on these characteristics is proposed for detecting applause in meeting speech stream. In the algorithm, the non-silence signal segments are first extracted by using voice activity detection. Afterward, applause segments are detected from the non-silence signal segments based on the characteristic differences between applause and speech without using any complex statistical models, such as hidden Markov models. The proposed algorithm can accurately determine the boundaries of applause in meeting speech stream, and is also computationally efficient. In addition, it can extract applause sub-segments from the mixed segments. Experimental evaluations show that the proposed algorithm can achieve satisfactory results in detecting applause of the meeting speech. Precision rate, recall rate, and F1-measure are 94.34%, 98.04%, and 96.15%, respectively. When compared with the traditional algorithm under the same experimental conditions, 3.62% improvement in F1-measure is achieved, and about 35.78% of computational time is saved.
A method of run-time detecting DDos attacks
Authors: Muhai Li, Ming Li
Venue: Proceedings of the 12th WSEAS international conference on Computers (2008)

Distribution denial-of-service (DDoS) constitutes one of the major threats and among the hardest security problems in today's Internet. However, DDoS detection techniques, such as signature-based detection, anomaly-based detection, and wavelet-based signal analysis, face the considerable challenge of determining network-based flooding attacks from sudden increases in legitimate activity or flash events. In this paper, we study the basic characteristic of network traffic, and propose a method for meeting the challenge. By taking full advantage of known traffic in normal state, we design a detection algorithm for dealing with DDoS attacks. We have carried out experiments with actual data to evaluate the algorithm. The results show that it can recognize DDoS attacks.
GestureBar: improving the approachability of gesture-based interfaces
Authors: Andrew Bragdon, Robert Zeleznik, Brian Williamson, Timothy Miller, Joseph J. LaViola,  Jr.
Venue: Proceedings of the 27th international conference on Human factors in computing systems (2009)

GestureBar is a novel, approachable UI for learning gestural interactions that enables a walk-up-and-use experience which is in the same class as standard menu and toolbar interfaces. GestureBar leverages the familiar, clean look of a common toolbar, but in place of executing commands, richly discloses how to execute commands with gestures, through animated images, detail tips and an out-of-document practice area. GestureBar's simple design is also general enough for use with any recognition technique and for integration with standard, non-gestural UI components. We evaluate GestureBar in a formal experiment showing that users can perform complex, ecologically valid tasks in a purely gestural system without training, introduction, or prior gesture experience when using GestureBar, discovering and learning a high percentage of the gestures needed to perform the tasks optimally, and significantly outperforming a state of the art crib sheet. The relative contribution of the major design elements of GestureBar is also explored. A second experiment shows that GestureBar is preferred to a basic crib sheet and two enhanced crib sheet variations.
A clustering algorithm using particle swarm optimization for DNA chip data analysis
Authors: Minsoo Lee, Yoonkyoung Lee, Boyeon Meang, Okju Choi
Venue: Proceedings of the 3rd International Conference on Ubiquitous Information Management and Communication (2009)

As DNA chips are becoming increasingly popular as a convenient way to perform vast amounts of experiments related to genes on a single chip, the importance of analyzing the data that is provided by such DNA chips is becoming significant. A very important analysis on DNA chip data would be clustering genes to identify gene groups which have similar properties. Clustering data for DNA chips usually deal with a large search space and has a very fuzzy characteristic. This task can be achieved by applying a clustering technique that mimics the biological world. One such algorithm is the Particle Swarm Optimization algorithm which was recently proposed as a very good candidate to solve such problems. In this paper, we propose a clustering mechanism that is based on the Particle Swarm Optimization algorithm. Our experiments show that the PSO-based clustering algorithm developed can efficiently cluster DNA chip data, and thus be used to extract valuable information from DNA chip data in an accurate yet timely manner.
Motion Detection with Entropy in Dynamic Background
Authors: Yu-Kumg Chen, Tung-Yi Cheng, Shuo-Tsung Chiu
Venue: Proceedings of the 2009 International Asia Conference on Informatics in Control, Automation and Robotics (2009)

The traditional automatic smart image surveillance system can usually be used in the environment with still background. That is, the background image must not contain the moving objects. If there is waving ocean, waving tree, floating cloud, or raining in the background image, the traditional methods do not work well. In order to improve this problem, a new motion detection method based on the theory of entropy and combined a multi-periods Sigma-Delta background estimation algorithm is developed in this paper. Based on the theory of moving average, a moving thresholding method is designed in this paper to obtain a sequence of alarm announcements. Experiments are carried out for some samples with dynamic backgrounds to demonstrate the computational advantage of the proposed method.
PAT: A pattern classification approach to automatic reference oracles for the testing of mesh simplification programs
Authors: W. K. Chan, S. C. Cheung, Jeffrey C. F. Ho, T. H. Tse
Venue: Journal of Systems and Software (2009)

Graphics applications often need to manipulate numerous graphical objects stored as polygonal models. Mesh simplification is an approach to vary the levels of visual details as appropriate, thereby improving on the overall performance of the applications. Different mesh simplification algorithms may cater for different needs, producing diversified types of simplified polygonal model as a result. Testing mesh simplification implementations is essential to assure the quality of the graphics applications. However, it is very difficult to determine the oracles (or expected outcomes) of mesh simplification for the verification of test results. A reference model is an implementation closely related to the program under test. Is it possible to use such reference models as pseudo-oracles for testing mesh simplification programs? If so, how effective are they? This paper presents a fault-based pattern classification methodology called PAT, to address the questions. In PAT, we train the C4.5 classifier using black-box features of samples from a reference model and its fault-based versions, in order to test samples from the subject program. We evaluate PAT using four implementations of mesh simplification algorithms as reference models applied to 44 open-source three-dimensional polygonal models. Empirical results reveal that the use of a reference model as a pseudo-oracle is effective for testing the implementations of resembling mesh simplification algorithms. However, the results also show a tradeoff: When compared with a simple reference model, the use of a resembling but sophisticated reference model is more effective and accurate but less robust.
Event-Driven Metamorphoses of P Systems
Authors: Thomas Hinze, Raffael Faßler, Thorsten Lenser, Naoki Matsumaru, Peter Dittrich
Venue: Membrane Computing: 9th International Workshop, WMC 2008, Edinburgh, UK, July 28-31, 2008, Revised Selected and Invited Papers (2009)

Complex reaction systems in molecular biology are often composed of partially independent subsystems associated with the activity of external or internal triggers. Occurring as random events or dedicated physical signals, triggers effect transitions from one subsystem to another which might result in substantial changes of detectable behavior. From a modeling point of view, those subsystems typically differ in their reaction rules or principle of operation. We propose a formulation of trigger-based switching between models from a class of P systems with progression in time employing discretized mass-action kinetics. Two examples inspired by biological phenomena illustrate the consecutive interplay of P systems towards structural plasticity in reaction rules: evolutionary construction of reaction networks and artificial chemistries with self-reproducible subunits.
The digital hourglass
Authors: Fabian Hemmert, Susann Hamann, Reto Wettach
Venue: Proceedings of the 3rd International Conference on Tangible and Embedded Interaction (2009)

This paper presents the Digital Hourglass, an alarm clock that focuses on the amount of sleep, rather than wake-up times. It follows a simple approach, lighting one LED for each hour of sleep, and physically resembles the interaction with a conventional hourglass: Tilting the hourglass moves 'time' between its chambers, placing it in an upright position activates it, turning it by 180&deg; snoozes it and placing it horizontally on a surface turns it off.
Collective robotic search using hybrid techniques: Fuzzy logic and swarm intelligence inspired by nature
Authors: Ganesh K. Venayagamoorthy, Lisa L. Grant, Sheetal Doctor
Venue: Engineering Applications of Artificial Intelligence (2009)

This paper presents two new strategies for navigation of a swarm of robots for target/mission focused applications including landmine detection and firefighting. The first method presents an embedded fuzzy logic approach in the particle swarm optimization (PSO) algorithm robots and the second method presents a swarm of fuzzy logic controllers, one on each robot. The framework of both strategies has been inspired by natural swarms such as the school of fish or the flock of birds. In addition to the target search using the above methods, a hierarchy for the coordination of a swarm of robots has been proposed. The robustness of both strategies is evaluated for failures or loss in swarm members. Results are presented with both strategies and comparisons of their performance are carried out against a greedy search algorithm.
Monotonicity and stratification
Authors: Gang Zhao, Pirooz Vakili
Venue: Proceedings of the 40th Conference on Winter Simulation (2008)

In utilizing the technique of stratification, the user needs to first partition/stratify the sample space; the next task is to determine how to allocate samples to strata. How to best perform the second task is well understood and analyzed and there are effective and generic recipes for sample allocation. Performing the first task, on the other hand, is generally left to the user who has limited guidelines at her/his disposal. We review explicit and implicit stratification approaches considered in the literature and discuss their relevance to simulation studies. We then discuss the different ways in which monotonicity plays a role in optimal stratification.