ppxscal/embedding_network huggingface dataset:
Application of partial mutual information variable selection to ANN forecasting of water quality in water distribution systems
Authors: Robert J. May, Graeme C. Dandy, Holger R. Maier, John B. Nixon
Venue: Environmental Modelling Software (2008)

Recent trends in the management of water supply have increased the need for modelling techniques that can provide reliable, efficient, and accurate representation of the complex, non-linear dynamics of water quality within water distribution systems. Statistical models based on artificial neural networks (ANNs) have been found to be highly suited to this application, and offer distinct advantages over more conventional modelling techniques. However, many practitioners utilise somewhat heuristic or ad hoc methods for input variable selection (IVS) during ANN development. This paper describes the application of a newly proposed non-linear IVS algorithm to the development of ANN models to forecast water quality within two water distribution systems. The intention is to reduce the need for arbitrary judgement and extensive trial-and-error during model development. The algorithm utilises the concept of partial mutual information (PMI) to select inputs based on the analysis of relationship strength between inputs and outputs, and between redundant inputs. In comparison with an existing approach, the ANN models developed using the IVS algorithm are found to provide optimal prediction with significantly greater parsimony. Furthermore, the results obtained from the IVS procedure are useful for developing additional insight into the important relationships that exist between water distribution system variables.
Automated xacml policy reconfiguration for evaluation optimisation
Authors: Philip L. Miseldine
Venue: Proceedings of the fourth international workshop on Software engineering for secure systems (2008)

We present a programmatic approach to the optimisation of XACML policies that specifies how a set of access control rules should be best represented for optimised evaluation. The work assumes no changes to the current XACML specification and methods of interpretation shall be made, so that those who consume XACML are unaffected structurally, and those that generate XACML can provide optimised output. Discussion regarding the flexibility of the XACML specification to describe the same access rules with different policy configurations is presented, and is used to formulate a comprehensive analysis of the evaluation costs the possible policy configurations will produce. This leads to the specification of methods that can be employed to produce optimal forms of policy description. These are implemented and evaluated to show the benefits of the approach proposed.
Regular systems of linear functional equations and applications
Authors: Moulay A. Barkatou, Gary Broughton, Eckhard Pflügel
Venue: Proceedings of the twenty-first international symposium on Symbolic and algebraic computation (2008)

The algorithmic classification of singularities of linear differential systems via the computation of Moser- and super-irreducible forms as introduced in [21] and [16] respectively has been widely studied in Computer Algebra ([8, 12, 22, 6, 10]). Algorithms have subsequently been given for other forms of systems such as linear difference systems [4, 3] and the perturbed algebraic eigenvalue problem [18]. In this paper, we extend these concepts to the general class of systems of linear functional equations. We derive a definition of regularity for these type of equations, and an algorithm for recognizing regular systems. When specialised to q-difference systems, our results lead to new algorithms for computing polynomial solutions and regular formal solutions.
Tools and Products
Authors: Ed Zintel
Venue: IEEE Computer Graphics and Applications (2008)

Department editor Dave Kasik highlights some of the new computer graphics tools and products on the market. In this issue the featured tools and products are a wireless mini trackball keyboard from Adesso, a distribution amplifier from Gefen, a super fast DVD burner from Samsung, an upgrade for photoshop connections from Strata, and a software line for video on-the-go from Pinnacle.
Polynomial time randomised approximation schemes for the Tutte polynomial of dense graphs
Authors: N. Alon
Venue: Proceedings of the 35th Annual Symposium on Foundations of Computer Science (1994)

The Tutte-Grothendieck polynomial T(G; x, y) of a graph G encodes numerous interesting combinatorial quantities associated with the graph. Its evaluation in various points in the (x,y) plane gave the number of spanning forests of the graph, the number of its strongly connected orientations, the number of its proper k-colorings, the (all terminal) reliability probability of the graph, and various other invariants the exact computation of each of which is well known to be P-hard. Here we develop a general technique that supplies fully polynomial randomised approximation schemes for approximating the valve of T(G; x,, y) for any dense graph G, that is, any graph on n vertices whose minimum degree is /spl Omega/(n), whenever x/spl ges/1 and y/spl ges/1, and in various additional points. This region includes evaluations of reliability and partition functions of the ferromagnetic Q-state Potts model. Extensions to linear matroids where T specialises to the weight enumerator of linear codes are considered as well.
Vision platform for mobile intelligent robot based on 81.6 GOPS object recognition processor
Authors: Donghyun Kim, Kwanho Kim, Joo-Young Kim, Seungjin Lee, Hoi-Jun Yoo
Venue: Proceedings of the 45th annual Design Automation Conference (2008)

To enable power-efficient object recognition of mobile intelligent robots, 81.6GOPS object recognition processor is proposed. Based on analysis of Scale Invariant Feature Transform (SIFT) algorithm, architecture of the proposed processor is designed to support both task and data level parallelism. 10 Processing Elements (PEs) are integrated for task parallelism, and each PE is equipped with SIMD instruction for data parallelism as well. In addition, Visual Image Processing memory replaces complex local maximum pixel search operation with a single read operation for further performance gain. With the proposed processor, we also realized vision platform for real-time SIFT computation of mobile robots. The chip operation is tested up to 200MHz and consumes 540mW in the vision platform at 1.8V supply voltage and 100 MHz operation frequency.
Applying consistent fuzzy preference relations to measure user perceived service quality of information presenting web portals
Authors: Tien-Chin Wang, Jia-Ling Liang
Venue: Proceedings of the 10th WSEAS International Conference on APPLIED MATHEMATICS (2006)

The study adopted the method of Herrera-Viedma et al., (2004): consistent fuzzy preference relations (Fuzzy PreRa) to apply the questionnaire which Zhilin Yang et al.(2005) developed. The result shows that the most important of the five-dimension is "Usability" and the most important of the nineteen items is "Relevant information to the customer". Compared to the traditional AHP method, Fuzzy PreRa has the advantages of reducing the comparing times. It is very easy to calculate and improve the inconsistent result. The result provides a useful suggestion for researchers and portal managers.
CS 0.5: a better approach to introductory computer science for majors
Authors: Robert H. Sloan, Patrick Troy
Venue: Proceedings of the 39th SIGCSE technical symposium on Computer science education (2008)

There are often problems when students enter a course with widely different experience levels with key course topics. If the material is covered too slowly, those with greater experience get bored and lose interest. If the material is covered too quickly, those with less experience get lost and feel incompetent. This problem with incoming students of our Computer Science Major led us to create CS 0.5: an introductory Computer Science course to target those CS majors who have little or no background with programming. Our goal is to provide these students with an engaging curriculum and prepare them to keep pace in future courses with those students who enter with a stronger background. Following the lead of Mark Guzdial's work on using media computation for non-majors at Georgia Tech, we use media computation as the tool to provide this engaging curriculum. We report here on our experience to date using the CS 0.5 approach with a media computation course.
Intelligent Multimedia Data Hiding Techniques and Applications
Authors: Hsiang-Cheh Huang, Wai-Chi Fang
Venue: Proceedings of the 2008 International Conference on Information Security and Assurance (isa 2008) (2008)

In this paper, we present the intelligent multimedia data hiding techniques and their possible applications. An introduction on intelligent multimedia data hiding is described which covers backgrounds, recent advances, methodologies, and implementations. The histogram-based reversible data hiding technique is then presented with simulation results and also illustrated by using actual implementations.
Signal propagation, with application to a lower bound on the depth of noisy formulas
Authors: W. Evans, L. J. Schulman
Venue: Proceedings of the 1993 IEEE 34th Annual Foundations of Computer Science (1993)

We study the decay of an information signal propagating through a series of noisy channels. We obtain exact bounds on such decay, and as a result provide a new lower bound on the depth of formulas with noisy components. This improves upon previous work of N. Pippenger (1988) and significantly decreases the gap between his lower bound and the classical upper bound of von Neumann. We also discuss connections between our work and the study of mixing rates of Markov chains.
Biometric Handshake Protocol on Telebiometric System Mechanism for National Infrastructure
Authors: Yong-Nyuo Shin, Yong-Jun Lee, Woochang Shin, Jin-Young Choi
Venue: Proceedings of the 2008 International Conference on Information Security and Assurance (isa 2008) (2008)

The threat of invasion of privacy and of the illegal appropriation of information both increase with the expansion of the biometrics service environment to open systems. However, while certificates or smart cards can easily be cancelled and reissued if found to be missing, there is no way to recover the unique biometric information of an individual following a security breach. For this reason, confidence among service bodies must be guaranteed. In this paper, we suggest nine bio-authentication models that differ according to template storage location, and define the threats and resolutions of these threats for each model. The suggested models can enhance web-based biometric security by providing security from the stage of transmission, and give stable performance by supplying standards-based encryptions. By designing and realizing Biometric Handshake protocols and Biometric Transfer protocols through the extension of TLS (Transport Layer Security), and applying them to each model, these models can be applied to elements of the national infrastructure, such as electronic passports and immigration control systems.
Delay-dependent H∞ filtering of a class of switched discrete-time state delay systems
Authors: Magdi S. Mahmoud
Venue: Signal Processing (2008)

In this paper, the problem of delay-dependent H"~ filtering for a class of discrete-time switched systems with state delays is investigated under arbitrary switching using a parametrized approach. Attention is focused on the design of asymptotically stable filter guaranteeing a prescribed noise attenuation level in the H"~ sense. By using switched Lyapunov functionals, sufficient conditions for the solvability of this problem are obtained in terms of linear matrix inequalities (LMIs), the solution of which constructs the desired H"~ filter under arbitrary switching. Numerical examples are provided to demonstrate the effectiveness of the proposed techniques.
Formal Modeling for Security Behavior Analysis of Computer Systems
Authors: Kamel Adi, Lamia Hamza, Liviu Pene
Venue: Proceedings of the 2008 International MCETECH Conference on e-Technologies (2008)

This paper proposes a formal framework aimed at specifying and verifying computer systems security behavior. In this approach, systems and their interactions are modeled through processes with a new dedicated calculus inspired from the ambient calculus. We demonstrate how, given a network security policy implementation, our dedicated calculus allows to verify that the specification offers or not sufficient protection from a malicious intruder.
Developmental Evaluation in Genetic Programming: A Position Paper
Authors: Tuan-Hao Hoang, R. I. (Bob) McKay, Daryl Essam, Xuan Hoai Nguyen
Venue: Proceedings of the 2007 Frontiers in the Convergence of Bioscience and Information Technologies (2007)

Standard genetic programming genotypes are generally highly disorganized and poorly structured, with little code replication. This is also true of existing developmental genetic programming systems [9, 18], which exploit regularity by using procedures, functional modules, or macros and parameters passing. By contrast, in biological developmental evolution, nature works through code duplication to generate modularity, regularity and hierarchy. Previous developmental approaches have only one level of evaluation for each individual an approach which limits the advantages of modularity to the species rather than the individual, and hence inhibits selection of modularity. We argued in [10, 4] that evaluation during development is necessary for structural regularity to emerge. To confirm the benefits of developmental evaluation and the contribution of code duplication to nature, our new developmental process uses a new representation. Developmental Tree Adjoining Grammar Guided GP (DTAG3P) uses L-systems to encode tree adjoining grammar guided (TAG) derivation trees, and has been investigated in [4]. We have demonstrated scalable solutions to difficult families of problems, and have evidence that this performance is linked to the generation and exploitation of structural regularities in the solutions.
The Theoretical and Empirical Research on Organization Innovation from the Knowledge Management Perspective
Authors: Li He
Venue: Proceedings of the First International Workshop on Knowledge Discovery and Data Mining (2008)

In the knowledge economy era,the organization's existing environment has changed enormously: Innovation becomes the original driving force; knowledge occupies the core position of organizations'resource as strategic resource;the competition of organizations runs to global.In such background,knowledge management as the important sources of the corporations'competition superiority, gradually becomes the focus in enterprise management.On the base of synthetical comment to relevant theories such as knowledge management, organization learning and organization innovation, this article studies organization innovation's connotation,process and mechanism based on knowledge management systematically and thoroughly. It also validates the inner relationship of knowledge management,organization learning and organization innovation through empirical research,as well as organization innovation mechanism based on knowledge management perspective.
Probabilistic Group Nearest Neighbor Queries in Uncertain Databases
Authors: Xiang Lian, Lei Chen
Venue: IEEE Transactions on Knowledge and Data Engineering (2008)

The importance of query processing over uncertain data has recently arisen due to its wide usage in many real-world applications. In the context of uncertain databases, previous work have studied many query types such as nearest neighbor query, range query, top-$k$ query, skyline query, and similarity join. In this paper, we focus on another important query, namely probabilistic group nearest neighbor query (PGNN), in the uncertain database, which also has many applications. Specifically, given a set, Q, of query points, a PGNN query retrieves data objects that minimize the aggregate distance (e.g. sum, min, and max) to query set Q. Due to the inherent uncertainty of data objects, previous techniques to answer group nearest neighbor query (GNN) cannot be directly applied to our PGNN problem. Motivated by this, we propose effective pruning methods, namely spatial pruning and probabilistic pruning, to reduce the PGNN search space, which can be seamlessly integrated into our PGNN query procedure. Extensive experiments have demonstrated the efficiency and effectiveness of our proposed approach, in terms of the wall clock time and the speed-up ratio against linear scan.
Optimized Distributed Data Sharing Substrate in Multi-core Commodity Clusters: A Comprehensive Study with Applications
Authors: K. Vaidyanathan, P. Lai, S. Narravula, D. K. Panda
Venue: Proceedings of the 2008 Eighth IEEE International Symposium on Cluster Computing and the Grid (2008)

Distributed applications tend to have a complex design due to issues such as concurrency, synchronization and communication. Researchers inthe past have proposed simpler abstractions to hide these complexities. However, many of the proposed techniques use messaging protocols which incur high overhead and are not very scalable. To address these limitations, in our previous work, we proposed an efficient Distributed Data Sharing Substrate (DDSS) using the features of high-speed networks. In this paper, we propose several design optimizations for DDSS in multi-core systems such as the combination of shared memory and message queues for inter-process communication, dedicated thread for communication progress and for onloading DDSS operations such as get and put. Our micro-benchmark results not only show a very low latency in DDSS operations but also demonstrate the scalability of DDSS with increasing number of processes. Application evaluations with R-Tree and B-Tree query processing and distributed STORM shows an improvement of up to 56%, 45% and 44%, respectively, as compared to traditional implementations. Evaluations with application checkpointing using DDSS demonstrate the scalability with increasing number of checkpointing applications. Further, in our evaluations, we demonstrate the portability of DDSS across multiple modern interconnects including InfiniBand and iWARP-capable 10-Gigabit Ethernet networks (applicablefor both LAN/WAN environments).
Operational maize yield model development and validation based on remote sensing and agro-meteorological data in Kenya
Authors: O. Rojas
Venue: International Journal of Remote Sensing (2007)

Remote-sensing data acquired by satellite have a wide scope for agricultural applications owing to their synoptic and repetitive coverage. On the one hand, spectral indices deduced from visible and near-infrared remote-sensing data have been extensively used for crop characterization, biomass estimation, and crop yield monitoring and forecasting. On the other hand, extensive research has been conducted using agrometerological models to estimate soil moisture to produce indicators of plant-water stress. This paper reports the development of an operational spectro-agrometeorological yield model for maize using a spectral index, the Normalized Difference Vegetation Index (NDVI) derived from SPOT-VEGETATION, meteorological data obtained from the European Centre for Medium-Range Weather Forecast (ECMWF) model, and crop-water status indicators estimated by the Crop-Specific Water Balance model (CSWB). Official figures produced by the Government of Kenya (GoK) on crop yield, area planted, and production were used in the model. The statistical multiple regression linear model has been developed for six large maize-growing provinces in Kenya. The spectro-agrometerological yield model was validated by comparing the predicted province-level yields with those estimated by GoK. The performance of the NDVI and land cover weighted NDVI (CNDVI) on the yield model was tested. Using CNDVI instead of NDVI in the model reduces 26% of the unknown variance. Of the output indicators of the CSWB model, the actual evapotranspiration (ETA) performs best. CNDVI and ETA in the model explain 83% of the maize crop yield variance with a root square mean error (RMSE) of 0.3298 t ha-1. Very encouraging results were obtained when the Jack-knife re-sampling technique was applied, thus proving the validity of the forecast capability of the model (r 2 = 0.81 and RMSE = 0.359 t ha-1). The optimal prediction capability of the independent variables is 20 days and 30 days for the short and long maize crop cycles, respectively. The national maize production during the first crop season for the years 1998-2003 was estimated with an RMSE of 185 060 t and coefficient of variation of 9%.
Toward Community Sensing
Authors: Andreas Krause, Eric Horvitz, Aman Kansal, Feng Zhao
Venue: Proceedings of the 7th international conference on Information processing in sensor networks (2008)

A great opportunity exists to fuse information from populations of privately-held sensors to create useful sensing applications. For example, GPS devices, embedded in cellphones and automobiles, might one day be employed as distributed networks of velocity sensors for traffic monitoring and routing. Unfortunately, privacy and resource considerations limit access to such data streams. We describe principles of community sensing that offer mechanisms for sharing data from privately held sensors. The methods take into account the likely availability of sensors, the context-sensitive value of sensor information, based on models of phenomena and demand, and sensor owners' preferences about privacy and resource usage. We present efficient and well-characterized approximations of optimal sensing policies. We provide details on key principles of community sensing and highlight their use within a case study for road traffic monitoring.
A Fast Rerouting Approach to Reduce Packet Loss during IP Routing Protocols Convergence
Authors: Fernando Barreto, Emilio C. G. Wille, Luiz Nacamura
Venue: Proceedings of the 22nd International Conference on Advanced Information Networking and Applications (2008)

The link state routing protocols of IP networks, when facing a failure, are reactive approaches and are not able to immediately obtain a new route in due time. They take from hundreds of milliseconds until tens of seconds in order to converge. This period generates instability, especially in high speed networks, causing erroneous forwarding processes and high packet loss rates. This study describes a proactive fast rerouting approach named Fast Emergency Paths, which aims at aiding IP routing protocols to bypass failures. An evaluation of these recovery paths was conducted. Results show that these paths are shorter than the other 100% single-failure recovery approaches and use less extra information added to the forwarding information base per router.