ppxscal/embedding_network huggingface dataset:
Insights on identity documents based on the Belgian case study
Authors: Danny De Cock, Koen Simoens, Bart Preneel
Venue: Information Security Tech. Report (2008)

Efficient eGovernment and eCommerce require the ability to authenticate citizens and transactions online, whereas the increasing mobility of citizens demands reliable identification. Identity documents tend to become the most popular form of identity tokens used for these purposes. An important problem, however, is that they can easily be passed on or used by a fraudster. We discuss the use of identity documents and the problem of linking these documents with their genuine holder. We discuss ePassports and eID cards in general using the Belgian identity documents as a reference.
Networking in the land of northern lights: two years of experiences from DTN system deployments
Authors: Anders Lindgren, Avri Doria, Jan Lindblom, Mattias Ek
Venue: Proceedings of the 2008 ACM workshop on Wireless networks and systems for developing regions (2008)

The Sámi Network Connectivity (SNC) project was started to enable Internet connectivity for the Sámi population of reindeer herders in the Laponia region in northern Sweden. In this area, no infrastructure and thus, no Internet connectivity is normally available. Thus, DTN functionality is used to enable connectivity through the use of mobile relays. This paper describes deployments and field tests done within the SNC project and its continuation SNC+1, in which a Delay-Tolerant Networking system was deployed in the target region. During these deployments, the PRoPHET routing protocol, and three different applications were deployed and tested sucessfully.
Distributed and Shared Memory Algorithm for Parallel Mining of Association Rules
Authors: J. Hernández Palancar, O. Fraxedas Tormo, J. Festón Cárdenas, R. Hernández León
Venue: Proceedings of the 5th international conference on Machine Learning and Data Mining in Pattern Recognition (2007)

The search for frequent patterns in transactional databases is considered one of the most important data mining problems. Several parallel and sequential algorithms have been proposed in the literature to solve this problem. Almost all of these algorithms make repeated passes over the dataset to determine the set of frequent itemsets, thus implying high I/O overhead. In the parallel case, most algorithms perform a sum-reduction at the end of each pass to construct the global counts, also implying high synchronization cost. We present a novel algorithm that exploits efficiently the trade-offs between computation, communication, memory usage and synchronization. The algorithm was implemented over a cluster of SMP nodes combining distributed and shared memory paradigms. This paper presents the results of our algorithm on different data sizes experimented on different numbers of processors, and studies the effect of these variations on the overall performance.
Efficient SAT-based bounded model checking for software verification
Authors: Franjo Ivani, Zijiang Yang, Malay K. Ganai, Aarti Gupta, Pranav Ashar
Venue: Theoretical Computer Science (2008)

This paper discusses our methodology for formal analysis and automatic verification of software programs. It is applicable to a large subset of the C programming language that includes pointer arithmetic and bounded recursion. We consider reachability properties, in particular whether certain assertions or basic blocks are reachable in the source code, or whether certain standard property violations can occur. We perform this analysis via a translation to a Boolean circuit representation based on modeling basic blocks. The program is then analyzed by a back-end SAT-based bounded model checker, where each unrolling is mapped to one step in a block-wise execution of the program. The main contributions of this paper are as follows: (1) Use of basic block-based unrollings with SAT-based bounded model checking of software programs. This allows us to take advantage of SAT-based learning inherent to the best performing bounded model checkers. (2) Various heuristics customized for models automatically generated from software, allowing a more efficient SAT-based analysis. (3) A prototype tool called F-Soft has been implemented using our methodology. We present experimental results based on multiple case studies including a C-based implementation of a network protocol, and compare the performance gains using the proposed heuristics.
Computational Geometric Approach to Submodular Function Minimization for Multiclass Queueing Systems
Authors: Toshinari Itoko, Satoru Iwata
Venue: Proceedings of the 12th international conference on Integer Programming and Combinatorial Optimization (2007)

This paper presents an efficient algorithm for minimizing a certain class of submodular functions that arise in analysis of multiclass queueing systems. In particular, the algorithm can be used for testing whether a given multiclass M/M/1 achieves an expected performance by an appropriate control policy. With the aid of the topological sweeping method for line arrangement, our algorithm runs in O(n 2) time, where n is the cardinality of the ground set. This is much faster than direct applications of general submodular function minimization algorithms.
Statistical Static Timing Analysis: A New Approach to Deal with Increased Process Variability in Advanced Nanometer Technologies
Authors: D. Pandini
Venue: Proceedings of the 17th international workshop on Integrated Circuit and System Design. Power and Timing Modeling, Optimization and Simulation (2007)

As process parameter dimensions continue to scale down, the gap between the designed layout and what is really manufactured on silicon is increasing. Due to the difficulty in process control in nanometer technologies, manufacturing-induced variations are growing both in number and as a percent of feature size and electrical parameters. Therefore, characterization and modeling of the underlying sources of variability, along with their correlations, is becoming more and more difficult and costly.
Macroscopic sensor networks: Application issues in healthcare
Authors: Elaine Lawrence, Karla Felix Navarro, Josep Riudavets, Marco Messina
Venue: Journal of Computational Methods in Sciences and Engineering (2006)

Motes (coin-sized sensors) have the potential to transform the way in which people live and work where computing occurs without human interaction so that data may be pre-processed and made available on demand. Motes may potentially transform the workplace into a Mobile Enterprise (m-Enterprise) especially in the healthcare sector. Motes are being trialed for emergency triaging, patient profiling and monitoring and education. Sensor networks could provide healthcare workers with a macroscopic view; they may be able to observe and interact with physical phenomena in real time with a high degree of fidelity. This paper examines the current health areas that are attempting to transform their operations using wireless sensor technology. The researchers report on issues that arose whilst working with Mica2 motes in a test bed environment during 2004, and their efforts to understand how these devices could usefully be adapted to the healthcare sector.
Unique Existence and Computability in Constructive Reverse Mathematics
Authors: Hajime Ishihara
Venue: Proceedings of the 3rd conference on Computability in Europe: Computation and Logic in the Real World (2007)

We introduce, and show the equivalences among, relativized versions of Brouwer's fan theorem for detachable bars (FAN), weak K&ouml;nig lemma with a uniqueness hypothesis (WKL!), and the longest path lemma with a uniqueness hypothesis (LPL!) in the spirit of constructive reverse mathematics. We prove that a computable version of minimum principle: if f is a real valued computable uniformly continuous function with at most one minimum on {0,1}N, then there exists a computable &alpha; in {0,1}N such that $f(\alpha) = \inf f(\{0,1\}^\mathbf{N})$, is equivalent to some computably relativized version of FAN, WKL! and LPL!.
Vote-Based Classifier Selection for Biomedical NER Using Genetic Algorithms
Authors: Nazife Dimililer, Ekrem Varoğlu, Hakan Altınçay
Venue: Proceedings of the 3rd Iberian conference on Pattern Recognition and Image Analysis, Part II (2007)

We propose a genetic algorithm for constructing a classifier ensemble using a vote-based classifier selection approach for biomedical named entity recognition task. Assuming that the reliability of the predictions of each classifier differs among classes, the proposed approach is based on dynamic selection of the classifiers by taking into account their individual votes. During testing, the classifiers whose votes are considered as being reliable are combined using weighted majority voting. The classifier ensemble formed by the proposed scheme surpasses the full object F-score of the best individual classifier and the ensemble of all classifiers by 2.5% and 1.3% respectively.
On Some Method for Intrusion Detection Used by the Multi-agent Monitoring System
Authors: Agnieszka Prusiewicz
Venue: Proceedings of the 8th international conference on Computational Science, Part III (2008)

In this paper an original method for intrusion detection used by the multi-agent monitoring system is proposed. Due to the complexity of the problem of the network security maintaining it is a good idea to apply the multi-agent approach. The multi-agent system is used in the tasks of computer network monitoring in order to detect the security policy violations. In this paper the algorithm for detecting some type of attack is proposed. This algorithm is based on the network traffic analysis. 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
ReMoteCare: Health Monitoring with Streaming Video
Authors: Martin Fischer, Yen Yang Lim, Elaine Lawrence, Leena K. Ganguli
Venue: Proceedings of the 2008 7th International Conference on Mobile Business (2008)

Governments the world over are worried about the increasing costs of providing healthcare to elderly and infirm persons whose numbers are growing rapidly. This paper describes ReMoteCare, a prototype we have developed for remote healthcare monitoring using a Wireless Sensor Network (WSN) Pulse Oximeters, environmental sensors and streaming video to monitor patients. To illustrate the functionality of the prototype we describe three typical remote health monitoring scenarios set in an aged care facility. Finally a series of experimental scenarios were developed and implemented in a laboratory setting to evaluate the reactivity of the monitoring system to a series of physiological conditions that cause the streaming video to alert the observer to potential problems.
The Conformal Monogenic Signal
Authors: Lennart Wietzke, Gerald Sommer
Venue: Proceedings of the 30th DAGM symposium on Pattern Recognition (2008)

The conformal monogenic signal is a novel rotational invariant approach for analyzing i(ntrinsic)1D and i2D local features of two-dimensional signals (e.g. images) without the use of any heuristics. It contains the monogenic signal as a special case for i1D signals and combines scale-space, phase, orientation, energy and isophote curvature in one unified algebraic framework. The conformal monogenic signal will be theoretically illustrated and motivated in detail by the relation of the Radon and the Riesz transform. One of the main ideas is to lift up two-dimensional signals to a higher dimensional conformal space where the signal can be analyzed with more degrees of freedom. The most interesting result is that isophote curvature can be calculated in a purely algebraic framework without the need of any derivatives.
Liquid Computing
Authors: Wolfgang Maass
Venue: Proceedings of the 3rd conference on Computability in Europe: Computation and Logic in the Real World (2007)

This review addresses structural differences between that type of computation on which computability theory and computational complexity theory have focused so far, and those computations that are usually carried out in biological organisms (either in the brain, or in the form of gene regulation within a single cell). These differences concern the role of time, the way in which the input is presented, the way in which an algorithm is implemented, and in the end also the definition of what a computation is. This article describes liquid computing as a new framework for analyzing those types of computations that are usually carried out in biological organisms.
Flow Analysis, Linearity, and PTIME
Authors: David Van Horn, Harry G. Mairson
Venue: Proceedings of the 15th international symposium on Static Analysis (2008)

Flow analysis is a ubiquitous and much-studied component of compiler technology--and its variations abound. Amongst the most well known is Shivers' 0CFA; however, the best known algorithm for 0CFA requires time cubic in the size of the analyzed program and is unlikely to be improved. Consequently, several analyses have been designed to approximate 0CFA by trading precision for faster computation. Henglein's simple closure analysis, for example, forfeits the notion of directionality in flows and enjoys an "almost linear" time algorithm. But in making trade-offs between precision and complexity, what has been given up and what has been gained? Where do these analyses differ and where do they coincide?We identify a core language--the linear ¿-calculus--where 0CFA, simple closure analysis, and many other known approximations or restrictions to 0CFA are rendered identical. Moreover, for this core language, analysis corresponds with (instrumented) evaluation. Because analysis faithfully captures evaluation, and because the linear ¿-calculus is complete for ptime, we derive ptime-completeness results for all of these analyses.
Agent-Based Decision Making through Intelligent Knowledge Discovery
Authors: Marina V. Sokolova, Antonio Fernández-Caballero
Venue: Proceedings of the 12th international conference on Knowledge-Based Intelligent Information and Engineering Systems, Part III (2008)

Monitoring of negative effects of urban pollution and real-time decision making allow to clarify consequences upon human health. Large amounts of raw data information describe this situation, and to get knowledge from it, we apply intelligent agents. Further modeling and simulation gives the new knowledge about the tendencies of situation development and about its structure. Agent-based decision support system can help to foresee possible ways of situation development and contribute to effective management and planning.
SPH simulations of swimming linked bodies
Authors: J. Kajtar, J. J. Monaghan
Venue: Journal of Computational Physics (2008)

In this paper, we describe how the swimming of linked-rigid bodies can be simulated using smoothed particle hydrodynamics (SPH). The fluid is assumed to be viscous and weakly compressible though with a speed of sound which ensures the Mach number is ~0.1 and the density fluctuation (relative to the average density) is typically 0.01. The motion is assumed to be two-dimensional. The boundaries of the rigid bodies are replaced by boundary particles and the forces between these particles and the fluid particles determine the forces and torques on the rigid bodies. The links between the bodies are described by constraint equations which are taken into account by Lagrange multipliers. We integrate the equations by a second-order method which conserves linear momentum exactly and, in the absence of viscosity, is reversible. We test our method by simulating the motion of a cylinder moving in a viscous fluid both under forced oscillation, and when tethered to a spring. We then apply our method to three problems involving three linked bodies. The first of these consists of three linked diamonds in a periodic domain and shows the convergence of the algorithm. The second is the system considered by Kanso et al. [E. Kanso, J.E. Marsden, C.W. Rowley, J.B. Melli-Huber, Locomotion of articulated bodies in a perfect fluid, J. Nonlinear Sci. 15 (2005) 255-289 (referred to in the text as K05)] and our results show similar behaviour for the same gait. The third example clarifies the conservation of angular momentum by simulating the motion of three linked ellipses moving within and through the surface of an initially circular patch of fluid. Our method can be easily extended to linked bodies swimming near surfaces, or to swimming near fixed boundaries of arbitrary shape, or to swimming in fluids which are stratified. Some of these systems have biological significance and others are applicable to the study of undersea vessels which move because of shape changes.
Simulation of thermal fields of sensors supported by an image processing technology
Authors: P. Nevriva, Z. Machacek, J. Krnavek
Venue: Proceedings of the 10th WSEAS International Conference on Automatic Control, Modelling & Simulation (2008)

The accuracy and the reliability of sensors are often influenced by both external and internal thermal sources. In this paper, the analysis of thermal load of sensors is discussed. Physical models incorporating both the analyzed sensors and the ambient conditions similar to the real ones are built. Mathematical models are constructed and calculated to solve tasks described by physical models. Here, temperature fields in sensor are described by the Fourier partial differential equation. Differences between analytical and experimental results are used for adaptive correction of parameters of the mathematical model. At the physical model, sensor's surface temperature is measured by an infrared camera. At the mathematical model, sensor's surface temperature is generated by the ANSYS Workbench graphical generator. To compare the experimental and analytical results, images from both the IR camera and the ANSYS Workbench gg are transformed by a set of image processing functions. Both the general method and the case study results obtained on the tricky problem of the analysis of the heat transfer dynamics of the motor oil level gauge are presented.
Modeling Stroke Diagnosis with the Use of Intelligent Techniques
Authors: S. Lalas, N. Ampazis, Athanasios Tsakonas, Georgios Dounias, K. Vemmos
Venue: Proceedings of the 5th Hellenic conference on Artificial Intelligence: Theories, Models and Applications (2008)

The purpose of this work is to test the efficiency of specific intelligent classification algorithms when dealing with the domain of stroke medical diagnosis. The dataset consists of patient records of the "Acute Stroke Unit", Alexandra Hospital, Athens, Greece, describing patients suffering one of 5 different stroke types diagnosed by 127 diagnostic attributes / symptoms collected during the first hours of the emergency stroke situation as well as during the hospitalization and recovery phase of the patients. Prior to the application of the intelligent classifier the dimensionality of the dataset is further reduced using a variety of classic and state of the art dimensionality reductions techniques so as to capture the intrinsic dimensionality of the data. The results obtained indicate that the proposed methodology achieves prediction accuracy levels that are comparable to those obtained by intelligent classifiers trained on the original feature space.
Knowledge Sharing on the Semantic Web
Authors: Nicholas J. Kings, Caroline Gale, John Davies
Venue: Proceedings of the 4th European conference on The Semantic Web: Research and Applications (2007)

This paper details the design, implementation and evaluation of an ontology-based knowledge sharing tool. The system, "Squidz", automatically classifies browsed web pages against an ontology, and allows users to share comments made about those pages to members of a community. As the user browses web pages, recommendations of relevant documents which have already been shared are produced, based upon both the user's social network as well as the semantic content of the page currently in view. Key to the design of the system has been the requirement, evidenced by earlier studies, that sharing should be easily effected as a side-effect of browsing rather than comprising a separate and distracting task. Another feature of the system is the linkage of a formal ontology with user-provided tags of shared information, thus combining the proven popularity of folksonomy-based systems with the shared and formal domain model provided by an ontology.
Data mining techniques for network scan detection
Authors: Vipin Kumar, Zhi-Li Zhang
Venue:  (2008)

A precursor to many attacks on networks is often a reconnaissance operation, more commonly referred to as a scan. Despite the vast amount of attention focused on methods for scan detection, the state-of-the-art methods suffer from high rate of false alarms and low rate of scan detection. In this thesis, we formalize the problem of scan detection as a data mining problem. We show how a network traffic data set can be converted into a data set that is appropriate for off-the-shelf classifiers. Our method successfully demonstrates that data mining models can encapsulate expert knowledge to create an adaptable algorithm that can substantially outperform state-of-the-art methods for scan detection in both coverage and precision. Specifically, we show that our method is capable of very early detection (in many cases, as early as the first connection attempt on the specific port) without significantly compromising the precision of the detection and is capable of distinguishing P2P and backscatter traffic from scanners. Using off-the-shelf classifiers as scan detectors is very effective but it requires a training data set whose instances are labeled to indicate the correct class assignment. In rapidly changing fields, like computer network traffic analysis, the availability of up-to-date labeled data sets is very limited. This is primarily a consequence of the excessively high cost of an expert manually labeling these large data sets. In this research, we also propose a method, where labeling the data set is carried out in a semi-supervised manner with user-specified guarantees about the quality of the labeling. Thirdly and lastly, we also propose a method for estimating the performance of the classifier (scan detector) when labeled data is unavailable.
Group-Based Key Management for Multicast of Ad Hoc Sensor Network
Authors: Shaobin Cai, Wenbin Yao, Nianmin Yao, Yong Li, Guochang Gu
Venue: Proceedings of the 7th international conference on Computational Science, Part III: ICCS 2007 (2007)

In order to protect communication security among sensor nodes, a cryptographic method are needed by ad hoc sensor networks. According to that most ad hoc sensor networks are deployed in groups, a group-based multicast key management scheme is proposed to extend RPS scheme in this paper. Compared with RPS, our scheme improves the probability that a shared key exists between two sensor nodes, and reduce the probability that the shared key is decrypted.
Assessing the Non-technical Service Aspects by Using Fuzzy Methods
Authors: Andrzej Pieczyński, Silva Robak
Venue: Proceedings of the 9th international conference on Artificial Intelligence and Soft Computing (2006)

The growing expectations for service-oriented applications tailored to the customers needs comprise a definition of the service contract documents, for both, technical and non-technical service elements. The usage of the fuzzy methods and techniques allows for the customized prearrangement of such application systems, which could be developed at the costs of the standard software. In the paper the concepts associated with a service-oriented design of non-technical service aspects especially appropriate for the fuzzy description of them as the requirements destined for Service Level Agreements SLAs, are introduced. The proposed approach is demonstrated on the example of a service accessibility requirement, an important component of a contracted SLA.