ppxscal/embedding_network huggingface dataset:
Possibilistic fusion for landcover mapping using correlated satellite imagery for environmental change
Authors: Shaheera Rashwan, M. A. Ismail, Soheir Fouad
Venue: Proceedings of the 5th WSEAS International Conference on Computational Intelligence, Man-Machine Systems and Cybernetics (2006)

To acquire detection performance required for an operational system in the detection for satellite image for environmental change, it is necessary to use multiple images over years to know the environmental changes over years. This paper describes a method for decision-level fusion technique where the fusion can compensate for correlation among images. The fusion is done using possibilistic combiners based on T-norms families that better represent the correlation of images. This technique was applied to Nile River Delta, Egypt (1973, 1987). These images show the dramatic urban growth within the Nile River delta and the expansion of agriculture into adjoining desert areas.
A runtime architecture-based approach for the dynamic evolution of distributed component-based systems
Authors: Yu Zhou
Venue: Companion of the 30th international conference on Software engineering (2008)

Dynamic evolution of distributed component-based systems (DCS) is an important task in software engineering. Several challenges are posed in this process. For example, how to preserve consistency during evolution and how to reflect the abstract evolution specification in the concrete reconfiguration implementation. Having observed the generality of software architecture, researchers have proposed various architectural description languages (ADLs), enabling evolution techniques, etc. to investigate the problem. These approaches typically employ the formal semantics of dynamic ADLs at the incremental levels of refinement in the design phase or the explicit maintenance of software architecture at runtime. However, different ADLs usually address different concerns and the lack of runtime support for the causal relation between ADLs and the running system easily leads to the mismatch between them, thus inevitably sacrifices their usability. We propose an approach based on a runtime architecture which is visually generated from an attributed type graph meta-model, exists through the lifecycle of DCS, establishes the causal relation between architectural topology and system configuration, and directs the dynamic evolution.
Accessibility and Supporting Technologies in M-Learning Standardization
Authors: Luis Anido-Rifón
Venue: Proceedings of the Third International Conference on Systems (2008)

Accessibility in e-learning in general provides the needed adaptation mechanisms to personalize the delivery of contents and educational tools to the particular needs of each student. Mobile learning supported by ICTs offers an excellent experimentation scenario for accessibility and adaptability research as the environment itself depends on the learner in a high level. This paper presents the initial research works towards the tuning of a mature sets of specifications in the area of accessibility, as ACCLIP and ACCMD, developed by the IMS Global Learning Consortium, to educational environments supported, at least in part, by mobile technologies.
Data Modeling for Kuala Lumpur Composite Index with ANFIS
Authors: Zuriahati Mohd Yunos, Siti Mariyam Shamsuddin, Roselina Sallehuddin
Venue: Proceedings of the 2008 Second Asia International Conference on Modelling & Simulation (AMS) (2008)

Stock market transaction is one of the most popular investments activities. There are many conventional techniques being used and these include technical and fundamental analysis. Recently, AI such as ANN, GA, FL and RS are widely used by the researchers due to their ability to predict the behavior of the stock market efficiently. In this research, a comprehensive preprocessing data modeling of stock market is developed to acquire granular information that represents the behavior of the data that is to be fed to the classifier. The pre-process methodology includes splitting, scaling, normalization, feature selection, and follows by the Ten-Fold Cross Validation method as a benchmark for estimating the predictive accuracy and effectiveness of splitting and selecting the input data. Daily data of KLCI is captured and analyzed, and it is found that the movements of the Indices are unstable; hence the forecasting process becomes difficult. A Hybrid Neurofuzzy with ANFIS is suggested to predict the behavior of the Indices. Four technical indicators are chosen to analyze the data. To verify the effectiveness of the ANFIS model, two experimental have been carried out and the results show that ANFIS method is competent in forecasting the KLCI fabulously compared to ANN.
Quantification of tropical soil attributes from ETM+/LANDSAT-7 data
Authors: J. A. M. Demattê, M. V. Galdos, R. V. Guimarães, A. M. Genú, M. R. Nanni, J. Zullo,  Jr
Venue: International Journal of Remote Sensing (2007)

The characterization of physical and chemical soils attributes is a pressing necessity for the agricultural land management optimization in many countries. Currently, soil analyses are performed by chemical treatments in a laboratory, generating environmental and time-consuming problems. Remote sensing techniques can be faster and cheaper than conventional methods, do not generate chemical residues and are non-destructive to the samples. The objective of the present work was to determine a remote sensing technique to estimate soil physical and chemical attributes in the regions of Paraguaçu Paulista and Rio Brilhante, in the States of São Paulo and Mato Grosso do Sul, respectively, Brazil, using reflectance data obtained by a sensor located in orbit. Fieldwork was performed to validate orbital data. A total of 110 soil samples were collected representing 43,000 h for the development of spectral models. Landsat-7 ETM+images were atmospherically corrected and transformed to reflectance. The soil samples observed in the field were located by GPS and evaluated in the orbital image. The method used consists in a detailed investigation of the spectral data, in which the spectral curve, the position of the data in a graphic dispersion, the colour compositions and the pixel cursor values are evaluated. Spectral models were determined to quantify soil attributes. Soil samples from a different area had their attribute contents determined by the models. The attributes studied were sand, silt, clay, pH (CaCl2), organic matter, phosphorus, potassium, calcium, magnesium, aluminium, hydrogen, cation exchange capacity (CEC), sum of cations (SC) base saturation (BS) and aluminium saturation (AS). The results showed weak correlations with some soil attributes, such as SC, K, Ca, Mg, Al and P. High correlations (reaching 0.86) were obtained with sand, clay, silt, OM, CEC and H. On the other hand, validation procedure indicated that the best attributes for quantification were clearly clay (0.61) and sand (0.5). Therefore, there is strong evidence that these attributes can be predicted in similar landscapes, using the multiple-linear equations developed in this study. This knowledge can be useful in many ways in agriculture, such as soil mapping, determining soil attributes, determining soil information in difficult access regions, and diminishing traditional soil analyses with environmental protection.
Focussed ion beam based fabrication of micro-electro-mechanical resonators
Authors: Daniel Grogg, Nicoleta Diana Badila-Ciressan, Adrian Mihai Ionescu
Venue: Microsystem Technologies (2008)

A simple and fast process to fabricate micro-electro-mechanical (MEM) resonators with deep sub-micron transduction gaps in thin SOI is presented. The proposed process is realized on both 350&#x00a0;nm and 1.5&#x00a0;&#x03bc;m thin silicon-on-insulator (SOI) substrates, evaluating the possibilities for MEMS devices on thin SOI for future co-integration with CMOS circuitry on a single chip. Through the combination of conventional UV-lithography and focused ion beam (FIB) milling the process needs only two lithography steps, achieving &#x223c;100&#x00a0;nm gaps, thus ensuring an effective transduction. Different FIB parameters and etching parameters and their effect on the process are reported.
Domain expert vs. layman: exploring the effect of subject selection in user studies for industrial wearable computing applications
Authors: Hendrik Witt, Ernesto Morales Kluge
Venue: Proceedings of the 4th international conference on mobile technology, applications, and systems and the 1st international symposium on Computer human interaction in mobile technology (2007)

We report on the results of a user study conducted to evaluate three different wearable input devices for menu-selection tasks in aircraft maintenance. Participating subjects were recruited from real maintenance workers (domain experts) and "typical" subjects of scientific studies (layman). An unfamiliar data glove device using gestures was found to outperform natural speech interaction. Besides suffering from handling problems, speech interaction was found inappropriate for domain experts due to lacks in education; laymen did not suffer from this. Further, our evaluation suggests the necessity to include real end-users in studies for industrial applications to get results able to uncover application domain specific constraints. Study outcomes significantly differed between domain experts and laymen; suggesting to take social and educational backgrounds of end-users into account when designing user studies that should impact professional wearable computing applications.
A Neural Network-Based Steam Temperature Control System
Authors: Hang Kuang
Venue: Proceedings of the First International Workshop on Knowledge Discovery and Data Mining (2008)

In this paper the idea of unit control and neural network control are organically integrated and a new control strategy is presented to adopt in superheat steam temperature control. This control strategy has good anti-jamming capability and strong robust, makes the advantage of neural network better manipulate, and then design a control system with better reliability and stronger robust.
A combinatorial construction of almost-ramanujan graphs using the zig-zag product
Authors: Avraham Ben-Aroya, Amnon Ta-Shma
Venue: Proceedings of the 40th annual ACM symposium on Theory of computing (2008)

Reingold, Vadhan and Wigderson [21] introduced the graph zig-zag product. This product combines a large graph and a small graph into one graph, such that the resulting graph inherits its size from the large graph, its degree from the small graph and its spectral gap from both. Using this product they gave the first fully-explicit combinatorial construction of expander graphs. They showed how to construct D-regular graphs having spectral gap 1-O(D-1/3). In the same paper, they posed the open problem of whether a similar graph product could be used to achieve the almost-optimal spectral gap 1-O(D-1/2). In this paper we propose a generalization of the zig-zag product that combines a large graph and several small graphs. The new product gives a better relation between the degree and the spectral gap of the resulting graph. We use the new product to give a fully-explicit combinatorial construction of D-regular graphs having spectral gap 1-D-1/2 + o(1).
Visual analytics apporach to user-controlled evacuation scheduling
Authors: Gennady Andrienko, Natalia Andrienko, Ulrich Bartling
Venue: Information Visualization (2008)

Application of the ideas of visual analytics is a promising approach to supporting decision making, in particular, where the problems have geographic (or spatial) and temporal aspects. Visual analytics may be especially helpful in time-critical applications, which pose hard challenges to decision support. We have designed a suite of tools to support transportation-planning tasks such as emergency evacuation of people from a disaster-affected area. The suite combines a tool for automated scheduling based on a genetic algorithm with visual analytics techniques allowing the user to evaluate tool results and direct its work. A transportation schedule, which is generated by the tool, is a complex construct involving geographical space, time, and heterogeneous objects (people and vehicles) with states and positions varying in time. We apply task-analytical approach to design techniques that could effectively support a human planner in the analysis of this complex information.
ClearShot: Eavesdropping on Keyboard Input from Video
Authors: Davide Balzarotti, Marco Cova, Giovanni Vigna
Venue: Proceedings of the 2008 IEEE Symposium on Security and Privacy (2008)

Eavesdropping on electronic communication is usually prevented by using cryptography-based mechanisms. However, these mechanisms do not prevent one from obtaining private information through side channels, such as the electromagnetic emissions of monitors or the sound produced by keyboards. While extracting the same information by watching somebody typing on a keyboard might seem to be an easy task, it becomes extremely challenging if it has to be automated. However, an automated tool is needed in the case of long-lasting surveillance procedures or long user activity, as a human being is able to reconstruct only a few characters per minute. This paper presents a novel approach to automatically recovering the text being typed on a keyboard, based solely on a video of the user typing. As part of the approach, we developed a number of novel techniques for motion tracking, sentence reconstruction, and error correction. The approach has been implemented in a tool, called ClearShot, which has been tested in a number of realistic settings where it was able to reconstruct a substantial part of the typed information.
A Radiation Hardened Nano-Power 8Mb SRAM in 130nm CMOS
Authors: Mark Lysinger, Francois Jacquet, Mehdi Zamanian, David McClure, Philippe Roche, Naren Sahoo, John Russell
Venue: Proceedings of the 9th international symposium on Quality Electronic Design (2008)

An eight megabit Rad Hard SRAM, implemented in 130nm CMOS technology, uses stacked capacitors within the memory cell for robustness, supply power gating and internally developed array power supplies to achieve very low soft error rates and standby current consumption under 600nA.
A Framework for Detecting Anomalies in VoIP Networks
Authors: Yacine Bouzida, Christophe Mangin
Venue: Proceedings of the 2008 Third International Conference on Availability, Reliability and Security (2008)

This paper introduces a novel system (architecture and techniques) that aims to secure overlay networks by detecting anomalies in Voice over IP networks. It is particularly designed for the signaling protocol SIP. The proposed system mainly consists of two parts. The first one determines the different features that are extracted from the specification of the SIP protocol. In fact, these features should highly characterize the behavior of the signaling traffic so that the evidence of the intrusion is not lost when only these attributes are considered for the attack detection goal. After the attributes extraction step, a detection algorithm is used to classify new SIP profiles in their appropriate class (either as normal, or as an anomaly). Another feature of this system is its adaptability since a feedback from the detected attacks is possible.
Crop surface temperature estimation in irrigated command areas using MODIS satellite data
Authors: S. Jonna, K. V. S. Badrinath, G. Chandrasekhar, E. Amminedu, T. R. Kiran Chand
Venue: International Journal of Remote Sensing (2007)

Crop surface temperature (CST) is an important parameter to monitor crop status. Satellite data in thermal region provide an opportunity to estimate CST over large regions at frequent intervals. In the present study, various split-window algorithms are employed to estimate CST over rice areas in irrigation projects of Krishna basin, South India using multi-resolution MODIS satellite data. NDVI is used to approximate the mean pixel emissivity, by taking known values for emissivity and NDVI for pure vegetation and bare soil pixels. Diurnal ground measurements are made to evaluate satellite-derived CST. CST values obtained using the Sobrino method have been found to be closer to the ground-measured values compared with other algorithms, as it takes into account view angle, atmospheric transmittance, and water vapour corrections. It has been observed that the error in estimating CST is comparatively lower for well-grown crops.
Learning symmetric causal independence models
Authors: Rasa Jurgelenaite, Tom Heskes
Venue: Machine Learning (2008)

Causal independence modelling is a well-known method for reducing the size of probability tables, simplifying the probabilistic inference and explaining the underlying mechanisms in Bayesian networks. Recently, a generalization of the widely-used noisy OR and noisy AND models, causal independence models based on symmetric Boolean functions, was proposed. In this paper, we study the problem of learning the parameters in these models, further referred to as symmetric causal independence models. We present a computationally efficient EM algorithm to learn parameters in symmetric causal independence models, where the computational scheme of the Poisson binomial distribution is used to compute the conditional probabilities in the E-step. We study computational complexity and convergence of the developed algorithm. The presented EM algorithm allows us to assess the practical usefulness of symmetric causal independence models. In the assessment, the models are applied to a classification task; they perform competitively with state-of-the-art classifiers.
Linear information versus function evaluations for L2-approximation
Authors: Aicke Hinrichs, Erich Novak, Jan Vybíral
Venue: Journal of Approximation Theory (2008)

We study algorithms for the approximation of functions, the error is measured in an L"2 norm. We consider the worst case setting for a general reproducing kernel Hilbert space of functions. We analyze algorithms that use standard information consisting in n function values and we are interested in the optimal order of convergence. This is the maximal exponent b for which the worst case error of such an algorithm is of order n^-^b. Let p be the optimal order of convergence of all algorithms that may use arbitrary linear functionals, in contrast to function values only. So far it was not known whether p>b is possible, i.e., whether the approximation numbers or linear widths can be essentially smaller than the sampling numbers. This is (implicitly) posed as an open problem in the recent paper [F.Y. Kuo, G.W. Wasilowski, H. Wozniakowski, On the power of standard information for multivariate approximation in the worst case setting, J. Approx. Theory, to appear] where the authors prove that p>12 implies b>=2p^2/(2p+1)>p-12. Here we prove that the case p=12 and b=0 is possible, hence general linear information can be exponentially better than function evaluation. Since the case p>12 is quite different, it is still open whether b=p always holds in that case.
Design of 3-D FIR digital filters using integral squared error criterion and transformation method
Authors: Guergana Mollova, Wolfgang F. G. Mecklenbräuker
Venue: Proceedings of the 2nd WSEAS International Conference on Circuits, Systems, Signal and Telecommunications (2008)

In this paper, the design of three-dimensional (3-D) FIR filters using McClellan transform method and integral squared error (ISE) criterion is presented. The 3-D filters with cone-shaped characteristics are considered in the approach. By minimizing the ISE function and double integration, a novel closed-form solution for the transform parameters is developed. The new relations for the transform coefficients are expressed in terms of the desired angle of inclination of the cone. The scaling problem of transformation function is also under discussion, as well as the choice of an appropriate cut-off frequency of the 1-D filter prototype. Several design examples are demonstrated to illustrate the merits of the proposed new technique.
Software Architecture Visualization: An Evaluation Framework and Its Application
Authors: Keith Gallagher, Andrew Hatch, Malcolm Munro
Venue: IEEE Transactions on Software Engineering (2008)

In order to characterize and improve software architecture visualization practice, the paper derives and constructs a qualitative framework, with 7 key areas and 31 features, for the assessment of software architecture visualization tools. The framework is derived by the application of the Goal Question Metric paradigm to information obtained from a literature survey and addresses a number of stakeholder issues. The evaluation is performed from multiple stakeholder perspectives and in various architectural contexts. Stakeholders can apply the framework to determine if a particular software architecture visualization tool is appropriate to a given task. The framework is applied in the evaluation of a collection of six software architecture visualization tools. The framework may also be used as a design template for a comprehensive software architecture visualization tool.
An accelerated monotone iterative method for the quantum-corrected energy transport model
Authors: Ren-Chuen Chen, Jinn-Liang Liu
Venue: Journal of Computational Physics (2008)

A non-stationary monotone iterative method is proposed and analyzed for the quantum-corrected energy transport model in nanoscale semiconductor device simulation. For the density-gradient equations, it is analytically and numerically shown that the convergence rate of the method is optimal in the sense of Gummel's decoupling iteration. This is a globally convergent method in the sense that the initial guess can be taken as a lower or an upper solution which is independent of applied voltages. The method integrates the monotone parameters, grid sizes, and Scharfetter-Gummel fitting in an adaptive and automatic way to treat the singularly perturbed nature of the model that incurs boundary, junction, and quantum potential layers in the device.
Simulation Studies of Multi-armed Bandits with Covariates (Invited Paper)
Authors: Nicos G. Pavlidis, Dimitris K. Tasoulis, David J. Hand
Venue: Proceedings of the Tenth International Conference on Computer Modeling and Simulation (2008)

We evaluate the performance of a number of action-selection methods on the multi-armed bandit problem with covariates. We resort to simulations because our primary concern is the speed with which the different methods identify the optimal policy, and not their asymptotic behaviour. The experimental results show that the performance of the ε-greedy methods is robust, while the interval estimation strategies achieve the fastest learning of the optimal policy. We propose a metric to quantify the difficulty of a multi-armed bandit problem with covariates and show that there is a trade-off between the satisfaction of the different performance measures.
Dual convergence of the proximal point method with Bregman distances for linear programming
Authors: J. X. Cruz Neto, O. P. Ferreira, A. N. Iusem, R. D. C. Monteiro
Venue: Optimization Methods Software (2007)

In this article, we consider the proximal point method with Bregman distance applied to linear programming problems, and study the dual sequence obtained from the optimal multipliers of the linear constraints of each subproblem. We establish the convergence of this dual sequence, as well as convergence rate results for the primal sequence, for a suitable family of Bregman distances. These results are obtained by studying first the limiting behavior of a certain perturbed dual path and then the behavior of the dual and primal paths.