ppxscal/embedding_network huggingface dataset:
A Full First-Order Constraint Solver for Decomposable Theories
Authors: Khalil Djelloul
Venue: Proceedings of the 9th AISC international conference, the 15th Calculemas symposium, and the 7th international MKM conference on Intelligent Computer Mathematics (2008)

Over the last decade, first-order constraints have been efficiently used in the artificial intelligence world to model many kinds of complex problems such as: scheduling, resource allocation, computer graphics and bio-informatics. Recently, a new property called decomposability has been introduced and many first-order theories have been proved to be decomposable: finite or infinite trees, rational and real numbers, linear dense order,...etc. A decision procedure in the form of 5 rewriting rules has also been developed. This latter can decide if a first-order formula without free variables is true or not in any decomposable theory. Unfortunately, this decision procedure is not enough when we want to express the solutions of a first-order constraint having free variables. These kind of problems are generally known as first-order constraint satisfaction problems. We present in this paper, not only a decision procedure but a full first-order constraint solver for decomposable theories. Our solver is given in the form of nine rewriting rules which transform any first-order constraint φ (which can possibly contain free variables) into an equivalent formula ¿ which is either the formula true, or the formula false or a simple solved formula having at least one free variable and being equivalent neither to true nor to false. We show the efficiency of our solver by solving complex first-order constraints over finite or infinite trees containing a huge number of imbricated quantifiers and negations and compare the performances with those obtained using the most recent and efficient dedicated solver for finite or infinite trees. This is the first full first-order constraint solver for any decomposable theory.
The BigLever Software Gears Unified Software Product Line Engineering Framework
Authors: Charles W. Krueger
Venue: Proceedings of the 2008 12th International Software Product Line Conference (2008)

BigLever Software's Unified Software Product Line Engineering (SPLE) Framework enables the integration of tools, assets and processes across the full system and software product line development lifecycle. The Gears framework offers a simple and elegant integrated software product line solution – for requirements engineers, architects, modelers, developers, build engineers, document writers, configuration managers, test engineers and project managers. The unified SPLE framework has enabled mainstream organizations with some of the largest, most sophisticated and complex, safety-critical systems ever built to adopt the SPLE approach.
Improved Kernel Principal Component Analysis and Its Application for Fault Detection
Authors: Chuyao Chen, Daqi Zhu, Qian Liu
Venue: Proceedings of the 4th international conference on Intelligent Computing: Advanced Intelligent Computing Theories and Applications - with Aspects of Theoretical and Methodological Issues (2008)

The kernel principal component analysis (KPCA) based on feature vector selection (FVS) is proposed in this paper for fault detection in nonlinear system. Firstly, the KPCA algorithm is described in detail. Secondly, a feature vector selection (FVS) scheme based on a geometric consideration is adopted to reduce the computational cost of KPCA. Finally, the KPCA and KPCA based on FVS (FVS-KPCA) are applied to a simple nonlinear system. The fault detection results and the comparison confirm the superiority of FVS-KPCA in fault detection.
Formalizing Service-Oriented Architectures
Authors: Khalil A. Abuosba, Asim A. El-Sheikh
Venue: IT Professional (2008)

Service-oriented architecture (SOA) is defined as a paradigm for organizing and using distributed capabilities that might be under the control of different ownership domains. SOA is also known as a methodology for achieving application interoperability and reuse of IT assets in distributed computing environments characterized as transformable by the visibility, interaction, and effect dimensions.
The Design Secret of Kyokusui-no-En's Meandering Channel
Authors: R. Tsubaki, Y. Nakayama, I. Fujita
Venue: Journal of Visualization (2008)

The purpose of this study is to investigate the characteristics of the flow through the Jonangu channel which is used for ceremonial game called as 'Kyokusui-no-En' in Japanese. The geometry of the channel is measured, a visualization technique is used to measure the actual flow characteristics, and then a numerical flow model is used to represent the flow including unsteady flow characteristics. Numerical model of drifting cup is introduced to investigate an interaction between flow and motion of the cup. Finally, the intention of the channel design is interpreted from the viewpoint of fluid mechanics using observed and calculated results.
Prediction and Analysis of Weaning Results of Ventilator-Dependent Patients with an Artificial Neuromolecular System
Authors: Jong-Chen Chen, Shou-Wei Chien, Jinchyr Hsu
Venue: Proceedings of the 8th international conference on Computational Science, Part I (2008)

We have developed a vertical information processing model, motivated from physiological evidence, which integrates intra- and interneuronal information processing. Information processing at the intraneuronal levels is to create a repertoire of pattern processing neurons. Information processing at the interneuronal levels is to group appropriate pattern processing neurons to constitute an effective pattern processing system. The system was applied to a database of the weaning results of ventilator-dependent patients. Ventilator has been used to support the breathing need of patients, and weaning is the gradual process of removing it from ventilator-dependent patients. Experiments with the model show that the integrated system is able to learn to differentiate data in an autonomous manner, separating those patients who have successful weaning results from those who do not. Our parameter analysis shows that most of the parameters identified as significant by the system are the same as those by physicians, but some are not.
Randomized Self-assembly for Approximate Shapes
Authors: Ming-Yang Kao, Robert Schweller
Venue: Proceedings of the 35th international colloquium on Automata, Languages and Programming, Part I (2008)

In this paper we design tile self-assembly systems which assemble arbitrarily close approximations to target squares with arbitrarily high probability. This is in contrast to previous work which has only considered deterministic assemblies of a single shape. Our technique takes advantage of the ability to assign tile concentrations to each tile type of a self-assembly system. Such an assignment yields a probability distribution over the set of possible assembled shapes. We show that by considering the assembly of close approximations to target shapes with high probability, as opposed to exact deterministic assembly, we are able to achieve significant reductions in tile complexity. In fact, we restrict ourselves to constant sized tile systems, encoding all information about the target shape into the tile concentration assignment. In practice, this offers a potentially useful tradeoff, as large libraries of particles may be infeasible or require substantial effort to create, while the replication of existing particles to adjust relative concentration may be much easier. To illustrate our technique we focus on the assembly of n×n squares, a special case class of shapes whose study has proven fruitful in the development of new self-assembly systems.
Advanced front-end electronics to extend the pulse-height spectroscopy range well beyond the ADC analog input range
Authors: G. Pascovici, A. Pullia, F. Zocca, D. Bazzacco
Venue: Proceedings of the 9th WSEAS International Conference on International Conference on Automation and Information (2008)

Using innovative front-end electronics developed for the 36-fold segmented High-Purity Germanium detector of AGATA Array we were able to significantly extend the range of spectroscopic measurements well beyond the fast pipeline ADC limit. To do that above a certain threshold we are automatically switching from a standard pulse height analysis to a Time-over-Threshold [TOT] method (Wilkinson like) and we thus obtain an unprecedented intrinsic dynamic range as large as 100 dB. To achieve that performance the structure of the front-end electronics consists of a very low noise and very high dynamic range charge-sensitive preamplifier followed by a passive pole-zero cancellation circuit including a highly accurate Fast-Reset circuit controlled by a fast comparator and zero crossing detector. With a large AGATA detector we could extend the initial dynamic range measured with a standard pulse height spectroscopic method from 3 keV - 10 MeV up to 180 MeV (equivalent gamma energy, measured with large pulser signal). The intrinsic energy resolution (i.e. electronic noise) is 900 eV @ 39 pF detector capacity. The energy resolution above the comparator threshold measured with the present TOT method is below 0.05 % @ 100 MeV (equivalent gamma energy i.e. pulse signals with amplitudes about 10 times higher than the ADC analog input range). The measured energy resolution is in very good agreement with analytical calculation and with intercomparison measurements with normal pulse height mode only and reduced electronic gain. The new time-variant circuit technique, proposed for nuclear pulse spectroscopy, permits a substantial improvement of the energy measurement dynamic range. This technique can be directly used in many other experimental pulse spectroscopic methods where the sensor is in a first approximation an equivalent capacitor.
Key-Recovery Attacks on Universal Hash Function Based MAC Algorithms
Authors: Helena Handschuh, Bart Preneel
Venue: Proceedings of the 28th Annual conference on Cryptology: Advances in Cryptology (2008)

This paper discusses key recovery and universal forgery attacks on several MAC algorithms based on universal hash functions. The attacks use a substantial number of verification queries but eventually allow for universal forgeries instead of existential or multiple forgeries. This means that the security of the algorithms completely collapses once a few forgeries are found. Some of these attacks start off by exploiting a weak key property, but turn out to become full-fledged divide and conquer attacks because of the specific structure of the universal hash functions considered. Partial information on a secret key can be exploited too, in the sense that it renders some key recovery attacks practical as soon as a few key bits are known. These results show that while universal hash functions offer provable security, high speeds and parallelism, their simple combinatorial properties make them less robust than conventional message authentication primitives.
Inductive Mercury Programming
Authors: Barnaby Fisher, James Cussens
Venue: Inductive Logic Programming: 16th International Conference, ILP 2006, Santiago de Compostela, Spain, August 24-27, 2006, Revised Selected Papers (2007)

We investigate using the Mercury language to implement and design ILP algorithms, presenting our own ILP system IMP. Mercury provides faster execution than Prolog. Since Mercury is a purely declarative language, run-time assertion of induced clauses is prohibited. Instead IMP uses a problem-specific interpreter of ground representations of induced clauses. The interpreter is used both for cover testing and bottom clause generation. The Mercury source for this interpreter is generated automatically from the user's background knowledge using Moose, a Mercury parser generator. Our results include some encouraging results on IMP's cover testing speed, but overall IMP is still generally a little slower than ALEPH.
Notations for Living Mathematical Documents
Authors: Michael Kohlhase, Christine Müller, Florian Rabe
Venue: Proceedings of the 9th AISC international conference, the 15th Calculemas symposium, and the 7th international MKM conference on Intelligent Computer Mathematics (2008)

Notations are central for understanding mathematical discourse. Readers would like to read notations that transport the meaning well and prefer notations that are familiar to them. Therefore, authors optimize the choice of notations with respect to these two criteria, while at the same time trying to remain consistent over the document and their own prior publications. In print media where notations are fixed at publication time, this is an over-constrained problem. In living documents notations can be adapted at reading time, taking reader preferences into account.We present a representational infrastructure for notations in living mathematical documents. Mathematical notations can be defined declaratively. Author and reader can extensionally define the set of available notation definitions at arbitrary document levels, and they can guide the notation selection function via intensional annotations.We give an abstract specification of notation definitions and the flexible rendering algorithms and show their coverage on paradigmatic examples. We show how to use this framework to render OpenMath and Content-MathML to Presentation-MathML, but the approach extends to arbitrary content and presentation formats. We discuss prototypical implementations of all aspects of the rendering pipeline.
The Simulation of Early Vision in Biological Retina and Analysis of Its Performance
Authors: Hui Wei, XuDong Guan
Venue: Proceedings of the 2008 Congress on Image and Signal Processing, Vol. 4 - Volume 04 (2008)

It might be a very effective way for computational vision model to utilize the productions of neurophysiology and biology. Retina does astonishing work in the early vision. In this paper, according to anatomic structure, a multi-layer digital retina model is presented to simulate biological retina and it is placed in a physical visual field of a reduced eye to analyze why the retina can be capable of fulfilling all tasks, and further more, to analyze the characteristics of every layer cell in retina in information processing. The model is designed to achieve a kind of balance among hardware complexity, computing load and performance on the condition of sufficient information collection. This research also contributes to the design and implementation of artificial retina chips to improve perception of visually impaired patients.
Modeling the Bat LSO Tonotopical Map Refinement during Development
Authors: Bertrand Fontaine, Herbert Peremans
Venue: Proceedings of the 10th international conference on Simulation of Adaptive Behavior: From Animals to Animats (2008)

The Lateral Superior Olive (LSO) codes for interaural intensity difference (IID), a cue used for sound localization. Between birth and maturation, the LSO undergoes plasticity driven by input neurons activity. During this developmental phase, a number of inputs are pruned out leading to a refinement of the frequency tuning. The goal of this paper is to show that, using a physiologically plausible network architecture and neuronal model, the activity dependent plasticity of the LSO can be modeled using Spike-Timing Dependent Plasticity (STDP). In particular, we show that the time properties of STDP coupled with the fact that the frequency axis in the LSO can be considered as a delay axis leads to the observed tonotopical map refinement. The response of both the individual neurons as well as population are shown to be in accordance with data taken from physiological analysis.
PAS: probability and sub-optimal distance-based lifetime prolonging strategy for underwater acoustic sensor networks
Authors: Jinfeng Dou, Guangxu Zhang, Zhongwen Guo, Jiabao Cao
Venue: Wireless Communications Mobile Computing (2008)

Lifetime prolonging is one of the most significant issues in the research on underwater acoustic sensor networks (UASNs). Unbalanced energy consumption influences greatly the network lifetime. First this study discusses a probability-based energy balance (PEB) scheme. The sensor nodes report the data to the sink by single-hop direct transmission (DT) or by multi-hop transmission (MT) under the probabilities. A centralized probabilities finding algorithm (PFA) can find a set of transmission probabilities to better balance the energy consumption. Then, a sub-optimal distance (SOD)-based data transmission scheme is proposed which is a distributed scheme and operates on each sensor node. It optimizes the slice width and selects the relays near the optimum transmission range. Simulations show that the two schemes can save more energy and prolong the network lifetime efficiently. Copyright &copy; 2008 John Wiley & Sons, Ltd.
Evaluation of ICT Investments in Public Administrations Based on Business Process Models
Authors: Jörg Becker, Philipp Bergener, Stefan Kleist, Daniel Pfeiffer, Michael Räckers
Venue: Proceedings of the 7th international conference on Electronic Government (2008)

Within the public sector domain there is great potential for business process optimization through ICT. However, until today these possibilities remain largely unexploited. To measure the impact of ICT-investments all processes of a public administration have to be taken into account. The PICTURE modelling method has been proposed as a way to efficiently model the whole process landscape of a public administration. Based on the processes captured, the impact of certain ICT functionalities can be analyzed. ICT investment decisions become more transparent towards the political leadership which are the decision makers in the public sector. This paper has two research objectives: First, an architecture for an semi-automated evaluation of ICT investment decisions is introduced. Second, the practical feasibility of the architecture is shown based on an investment decision for a document management system.
Does a Mammography CAD Algorithm with Varying Filtering Levels of Detection Marks, Used to Reduce the False Mark Rate, Adversely Affect the Detection of Small Masses?
Authors: Isaac Leichter, Richard Lederman, Eli Ratner, Nicolas Merlet, Glenn Fung, Balaji Krishnapuram, Philippe Bamberger
Venue: Proceedings of the 9th international workshop on Digital Mammography (2008)

This study evaluates the performance of an advanced CAD algorithm that is capable of filtering detection marks by level-of-suspicion. The detection of small invasive cancers, which has the greatest impact on breast cancer survival, was investigated. The advanced algorithm (Siemens) permits the radiologist to toggle back and forth between different levels of filtering, and focus on the detection marks that appear or disappear as findings with lower or higher levels of suspicion are displayed. The performance of the algorithm at three levels of filtering was evaluated, by lesion size and breast composition. 149 malignant cases with 151 masses (60 small masses) and 528 normal cases were analyzed. When the highest level of filtering was applied, and only findings most indicative of malignancy were displayed, the number of false masses was markedly reduced by 37.8%, while the detection sensitivity for masses was slightly reduced from 84.8% to 80.1%, and similarly, the detection sensitivity for small masses in dense breast decreased from 69.6% to 65.2%. In conclusion, when using an algorithm with filtering capabilities, designed to draw radiologists' attention to prompts most indicative of malignancy, the substantial reduction in false marks offsets the slight reduction in the detection sensitivity. Reducing the false mark rate by altering the level of filtering of the CAD prompts, does not have a selectively adverse impact on the detection sensitivity of small masses.
Continuous Trend-Based Clustering in Data Streams
Authors: Maria Kontaki, Apostolos N. Papadopoulos, Yannis Manolopoulos
Venue: Proceedings of the 10th international conference on Data Warehousing and Knowledge Discovery (2008)

Trend analysis of time series is an important problem since trend identification enables the prediction of the near future. In streaming time series the problem is more challenging due to the dynamic nature of the data. In this paper, we propose a method to continuously clustering a number of streaming time series based on their trend characteristics. Each streaming time series is transformed to a vector by means of the Piecewise Linear Approximation (PLA) technique. The PLA vector comprises pairs of values (timestamp, trend) denoting the starting time of the trend and the type of the trend (either UP or DOWN) respectively. A distance metric for PLA vectors is introduced. We propose split and merge criteria to continuously update the clustering information. Moreover, the proposed method handles outliers. Performance evaluation results, based on real-life and synthetic data sets, show the efficiency and scalability of the proposed scheme.
Case-Based Troubleshooting in the Automotive Context: The SMMART Project
Authors: Stefania Bandini, Ettore Colombo, Giuseppe Frisoni, Fabio Sartori, Joakim Svensson
Venue: Proceedings of the 9th European conference on Advances in Case-Based Reasoning (2008)

In this paper we present a case---based troubleshooting tool developed in the context of the SMMART project. The application aims at the identification and solution of failures in trucks, exploiting a hybrid approach based on the integration of CBR, model based reasoning and fault trees. The case---based module of the final system allows to identify the most probable part of the truck that is responsible for the failures (e.g. engine, gearbox, and so on): then, model---based reasoning or fault trees can be used to detect the real cause of the problem (e.g. an electric cable in the engine) and to identify the action needed to solve it (e.g. substitute the cable). The project is a collaboration between the University of Milan---Bicocca and Volvo Trucks.
The Impact of Self-similarity on Traffic Shaping in Wireless LAN
Authors: Adam Domański, Joanna Domańska, Tadeusz Czachórski
Venue: Proceedings of the 8th international conference, NEW2AN and 1st Russian Conference on Smart Spaces, ruSMART on Next Generation Teletraffic and Wired/Wireless Advanced Networking (2008)

IEEE 802.11 MAC protocol ist the de facto standard for wireless local area networks (WLANs). In today's Internet, the emerging widespread use of real-time voice, audio, and video applications makes QoS (Quality of Service) a key problem. At the MAC layer, 802.11e defines extensions to enhance the QoS performance of 802.11 WLAN. This MAC layer solution leaves such issues of QoS as QoS guarantee and admission control to the traffic control systems at the higher layers. This article tries to show that implementation of some mechanisms of traffic shaping causes some improvement of the level of QoS in WLANs. First we analyse the influence of the traffic shaping in WLANs stations by the mechanism of token bucket filter. Next the analysis of the behaviour of Access Point with AQM mechanism was carried out. The conducted research has shown that it is possible to achieve certain level of QoS thanks to the implementation of traffic shaping mechanisms. We make our experiments comparatively for the traffic sources with self-similarity and without it. Our results confirm the necessity of taking into account the self-similar character of wireless traffic.