ppxscal/embedding_network huggingface dataset:
On Distributed Cooperative Control for the Manipulation of a Hose by a Multirobot System
Authors: José Manuel López-Guede, Manuel Graña, Ekaitz Zulueta
Venue: Proceedings of the 3rd international workshop on Hybrid Artificial Intelligence Systems (2008)

The manipulation of a hose can be formulated as the motion of a collection of autonomous robots linked by non-rigid elements so that the distance between robot units is not constant. The link may be a random component on the individual robot environment because under some circumstances it will be not known beforehand how the hose will influence the behaviour of the individual robot in response to control commands. We try to state the problem of distributed control of this kind of systems, under a gradation of conditions. We try to highlight the role of Hybrid Intelligent Systems in the development of solutions to this control problem. We have taken the works of Beard on UAV as the framework for the formulation of the system.
Prefetch throttling and data pinning for improving performance of shared caches
Authors: Ozcan Ozturk, Seung Woo Son, Mahmut Kandemir, Mustafa Karakoy
Venue: Proceedings of the 2008 ACM/IEEE conference on Supercomputing (2008)

In this paper, we (i) quantify the impact of compiler-directed I/O prefetching on shared caches at I/O nodes. The experimental data collected shows that while I/O prefetching brings some benefits, its effectiveness reduces significantly as the number of clients (compute nodes) is increased; (ii) identify interclient misses due to harmful I/O prefetches as one of the main sources for this reduction in performance with increased number of clients; and (iii) propose and experimentally evaluate prefetch throttling and data pinning schemes to improve performance of I/O prefetching. Prefetch throttling prevents one or more clients from issuing further prefetches if such prefetches are predicted to be harmful, i.e., replace from the memory cache the useful data accessed by other clients. Data pinning on the other hand makes selected data blocks immune to harmful prefetches by pinning them in the memory cache. We show that these two schemes can be applied in isolation or combined together, and they can be applied at a coarse or fine granularity. Our experiments with these two optimizations using four disk-intensive applications reveal that they can improve performance by 9.7% and 15.1% on average, over standard compiler-directed I/O prefetching and no-prefetch case, respectively, when 8 clients are used.
Distance-Avoiding Sequences for Extremely Low-Bandwidth Authentication
Authors: Michael J. Collins, Scott Mitchell
Venue: Proceedings of the 5th international conference on Sequences and Their Applications (2008)

We develop a scheme for providing strong cryptographic authentication on a stream of messages which consumes very little bandwidth (as little as one bit per message) and is robust in the presence of dropped messages. Such a scheme should be useful for extremely low-power, low-bandwidth wireless sensor networks and "smart dust" applications. The tradeoffs among security, memory, bandwidth, and tolerance for missing messages give rise to several new optimization problems. We report on experimental results and derive bounds on the performance of the scheme.
Framework for Workflow Parallel Execution in Grid Environment
Authors: Lican Huang
Venue: Proceedings of the 7th international conference on Computational Science, Part III: ICCS 2007 (2007)

This paper presents a framework for Web Service based workflow optimisation in Grid environment. In this framework, parallel service is introduced as adaptor and container of parallel block of workflow. In parallel service, workflow is divided into multi sub-workflows, which are dispatched and executed in parallel at different workflow engines in different grid nodes. By this strategy, the performance of workflow can be enhanced greatly. In this paper, we also give a strategy how to guarantee the correctness in complicated network environment by redundant computing.
Information-Theoretic Measures for Meta-learning
Authors: Saddys Segrera, Joel Pinho, María N. Moreno
Venue: Proceedings of the 3rd international workshop on Hybrid Artificial Intelligence Systems (2008)

Information-theoretic measures are suitable to characterize datasets with discrete attributes (or continuous which can be transformed). They can find information that can be decisive in order to analyze the behavior of different learning algorithms with specific datasets. The objective of the work presented in this paper is to study by means of three similar datasets from UCI Repository Machine Learning, the possible reasons for which breast-cancer-wisconsin dataset, in comparison with other 20 datasets, showed in a previous research that Stacking by Meta-Decision Trees (MDT) was significant better than all other multiclassifier models, including Stacking by Multi-Response Linear Regression (MLR). In our experiments the proportion of missing values, among other significant changes in different measure values, provided evidences about the possible origin of the different behaviors presented by these multiclassifier schemes depending on data characteristics.
An efficient hardware design of a system for highly nonstationary signals filtering
Authors: Veselin N. Ivanovic, Srdjan Jovanovski
Venue: Proceedings of the 7th WSEAS International Conference on Applied Computer and Applied Computational Science (2008)

An efficient multicycle hardware design of a time-varying (TV) filtering system, based on time-frequency (TF) analysis, is developed by following the idea of a new method for filter's region of support (FRS) real-tame estimation, also proposed here. Quite general estimation method provides multiple detection of the local filter's regions of support (in observed time-instant) in the practically only important case of a known single noisy signal realization. In this way, a very efficient real-time filtering of mono- and multicomponent nonstationary signals is enabled. By taking different number of clock cycles per frequency point, the proposed design enables application of various (almost all commonly used) TF distributions (TFDs) in the TV filtering research area. Additionally, it allows the implemented filter to share functional kernels within the execution, implying the optimization of the critical design performances and the improvement of the execution time.
T-S Fuzzy Model Identification Based on Chaos Optimization
Authors: Chaoshun Li, Jianzhong Zhou, Xueli An, Yaoyao He, Hui He
Venue: Proceedings of the 5th international symposium on Neural Networks: Advances in Neural Networks (2008)

Nonlinear system identification by fuzzy model has been widely applied in many fields, for fuzzy model has the ability to approximate any nonlinear system to a given accuracy. In this paper, a nonlinear system identification algorithm based on Takagi-Sugeno (T-S) fuzzy model is proposed. Considering that the fuzzy space structure of T-S fuzzy model has great influence upon precision and effect of the final identification result, a new fuzzy clustering method based on chaos optimization, which is believed to be more accurate in data clustering, is adopted to partition the fuzzy space and obtain the fuzzy rules. Based on the fuzzy space partition and the subsequent structure parameters, the least square method is used to identify the conclusion parameters. Typical nonlinear function has been simulated to test the precision and effect of the proposed identification technique, and finally the algorithm has been successfully applied in the boiler-turbine system identification.
Semantics-Based Weaving of UML Sequence Diagrams
Authors: Roy Grønmo, Fredrik Sørensen, Birger Møller-Pedersen, Stein Krogdahl
Venue: Proceedings of the 1st international conference on Theory and Practice of Model Transformations (2008)

In this paper we briefly introduce an aspect language that can define cross-cutting effects on a set of UML 2.0 sequence diagrams. Our main contribution is to weave aspects and sequence diagrams at the model level. By basing the weaving upon a formal trace model for sequence diagrams, we ensure that the weaving is semantics-based. To avoid the intractability of working on complete trace sets, we define a lifeline-based weaving upon trace-based equivalence classes. A major challenge is to handle unbounded loops which produce infinite trace sets. We establish a systematic way to rewrite the original loop definition so that the weaving can be performed on a finite structure. A weaving tool has been implemented to validate the approach.
Recent progress in the production of error-free magnetic computer tape
Authors: J. C. Chapman, W. W. Wetzel
Venue: Papers and discussions presented at the Dec. 8-10, 1953, eastern joint AIEE-IRE computer conference: information processing systems---reliability and requirements (1953)

Signal dropouts arising from magnetic tape are one cause of error in modern digital computers designed to use such tape as a long period storage medium. Noise pulses, which are of sufficient amplitude to act as spurious signals, form a second error source. Both dropouts and noise pulses are traceable to discontinuities in the magnetic coating.
The Alcuin Number of a Graph
Authors: Péter Csorba, Cor A. Hurkens, Gerhard J. Woeginger
Venue: Proceedings of the 16th annual European symposium on Algorithms (2008)

We consider a planning problem that generalizes Alcuin's river crossing problem (also known as: The wolf, goat, and cabbage puzzle) to scenarios with arbitrary conflict graphs. We derive a variety of combinatorial, structural, algorithmical, and complexity theoretical results around this problem.
Implied Set Closure and Its Application to Memory Consistency Verification
Authors: Surender Baswana, Shashank K. Mehta, Vishal Powar
Venue: Proceedings of the 20th international conference on Computer Aided Verification (2008)

Hangal et. al. [3] have developed a procedure to check if an instance of the execution of a shared memory multiprocessor program, is consistent with the Total Store Order (TSO) memory consistency model. They also devised an algorithm based on this procedure with time complexity O(n 5), where n is the total number of instructions in the program. Roy et. al. [6] have improved the implementation of the procedure and achieved O(n 4) time complexity.We have identified the bottleneck in these algorithms as a graph problem of independent interest, called implied-set closure (ISC) problem. In this paper we propose an algorithm for ISC problem and show that using this algorithm, Hangal's consistency checking procedure can be implemented with O(n 3) time complexity. We also experimentally show that the new algorithm is significantly faster than Roy's algorithm.
Learning in the Recurrent Hopfield Network
Authors: Saratha Sathasivam
Venue: Proceedings of the 2008 Fifth International Conference on Computer Graphics, Imaging and Visualisation (2008)

There are two ways to calculate synaptic weights for neurons in logic programming. There are by using Hebbian learning or by Wan Abdullah's method. Hebbian learning for governing events corresponding to some respective program clauses is equivalent with learning using Wan Abdullah's method for the same respective program clauses. We will evaluate experimentally the logical equivalent between these two types of learning (Wan Abdullah's method and Hebbian learning) for the same respective clauses (same underlying logical rules) in this paper. The computer simulation that had been carried out support this theory.
Modeling Modern Social-Network-Based Epidemics: A Case Study of Rose
Authors: Sirui Yang, Hai Jin, Xiaofei Liao, Sanmin Liu
Venue: Proceedings of the 5th international conference on Autonomic and Trusted Computing (2008)

The social-network-based epidemics, such as email-based ones, have been long studied. However, few have noticed some newly emerging epidemics which especially based on portable devices. In this paper, we think of such viruses and take a representative, the Rose epidemic, for case study. We build a model with a system of differential equations and closed-form solutions for three propagation scenes correspondingly. With both theoretical and numerical analysis, we find out that (1) Rose is able to infect hosts as exponentially as the Internet-based worms do;(2) In the Internet cafe scene, it is difficult to contain Rose even with reactive recovery measures; (3) the most influential factors for Rose's propagation are the amount of hosts and portable devices and the lifetime of Internet cafe machines, while the arrival rate of clients and the proportion of immune machines only affect in the print service office scene.
An economic framework for resource management and pricing in wireless networks with competitive service providers
Authors: Mainak Chatterjee
Venue:  (2007)

A paradigm shift from static spectrum allocation to dynamic spectrum access (DSA) is becoming a reality due to the recent advances in cognitive radio, wide band spectrum sensing, and network aware real-time spectrum access. It is believed that DSA will allow wireless service providers (WSPs) the opportunity to dynamically access spectrum bands as and when they need it. Moreover, due to the presence of multiple WSPs in a region, it is anticipated that dynamic service pricing would be offered that will allow the end-users to move from long-term service contracts to more flexible short-term service models. In this research, we develop a unified economic framework to analyze the trading system comprising two components: (i) spectrum owner - WSPs interactions with regard to dynamic spectrum allocation, and (ii) WSP - end-users interactions with regard to dynamic service pricing. For spectrum owner - WSPs interaction, we investigate various auction mechanisms for finding bidding strategies of WSPs and revenue generated by the spectrum owner. We show that sequential bidding provides better result than the concurrent bidding when WSPs are constrained to at most single unit allocation. On the other hand, when the bidders request for multiple units, (i.e., they are not restricted by allocation constraints) synchronous auction mechanism proves to be beneficial than asynchronous auctions. In this regard, we propose a winner determination sealed-bid knapsack auction mechanism that dynamically allocates spectrum to the WSPs based on their bids. As far as dynamic service pricing is concerned, we use game theory to capture the conflict of interest between WSPs and end-users, both of whom try to maximize their respective net utilities. We deviate from the traditional per-service static pricing towards a more dynamic model where the WSPs might change the price of a service almost on a session by session basis. Users, on the other hand, have the freedom to choose their WSP based on the price offered. It is found that in such a greedy and non-cooperative behavioral game model, it is in the best interest of the WSPs to adhere to a price threshold which is a consequence of a price (Nash) equilibrium. We conducted extensive simulation experiments, the results of which show that the proposed auction model entices WSPs to participate in the auction, makes optimal use of the common spectrum pool, and avoids collusion among WSPs. We also demonstrate how pricing can be used as an effective tool for providing incentives to the WSPs to upgrade their network resources and offer better services.
Finite Automata Presentable Abelian Groups
Authors: André Nies, Pavel Semukhin
Venue: Proceedings of the international symposium on Logical Foundations of Computer Science (2007)

We give new examples of FA presentable torsion-free abelian groups. Namely, for every n ¿ 2, we construct a rank n indecomposable torsion-free abelian group which has an FA presentation. We also construct an FA presentation of the group (¿, + )2 in which every nontrivial cyclic subgroup is not FA recognizable.
A Multi-gene-Feature-Based Genetic Algorithm for Prediction of Operon
Authors: Shuqin Wang, Yan Wang, Wei Du, Fangxun Sun, Xiumei Wang, Yanchun Liang, Chunguang Zhou
Venue: Proceedings of the 8th international conference on Adaptive and Natural Computing Algorithms, Part I (2007)

The prediction of operons is critical to reconstruction of regulatory networks at the whole genome level. In this paper, a multi-approach guided genetic algorithm is developed to prediction of operon. The fitness function is created by using intergenic distance of local entropy-minimization, participation of the same metabolic pathway, log-likelihood of COG gene functions and correlation coefficient of microarray expression data, which have been used individually for predicting operons. The gene pairs within operons have high fitness value by using these four scoring criteria, whereas those across transcription unit borders have low fitness value. On the other hand, it is easy to predict operons and makes the prediction ability stronger by using these four scoring criteria. The proposed method is examined on 683 known operons of Escherichia coli K12 and an accuracy of 85.9987% is obtained.
Secure Hybrid Group Key Management for Hierarchical Self-Organizing Sensor Network
Authors: Shu Yun Lim, Meng-Hui Lim, Sang Gon Lee, Hoon Jae Lee
Venue: Proceedings of the 2008 The Fourth International Conference on Information Assurance and Security (2008)

Key management is deemed as the fundamental essential part of any secure communication. A secure sensor network communication protocol relies on the substantial secure, robust and efficient key management system. We put forward a new hybrid group key management scheme for hierarchical self organizing wireless sensor network architecture. By using this approach, multi-level security can be achieved to secure groups of sensors at different levels. We place the cryptographic burden where the resources are less constrained, at the forwarding nodes and the access points. In our proposed scheme, access points and forwarding nodes initially perform a key agreement protocol and each sensor node in a cluster later on establishes a group key with the forwarding node using a key transport scheme dynamically after deployment.
Fuzzy Reasoning Approach for Conceptual Design
Authors: Hailin Feng, Chenxi Shao, Yi Xu
Venue: Proceedings of the 5th international symposium on Neural Networks: Advances in Neural Networks, Part II (2008)

To deal with incomplete quantitative information in configuration design stage, a fuzzy approach is presented for conceptual design. Fuzzy information vector and fuzzy constraint matrices were given for the description of components selected. Fuzzy sign algebra was used to build the reasoning rules and create the configuration branches. The possible reasonable spatial configurations of mechanisms were predicted with the constraint spread rules. Reasoning structure for space configuration was given to determine the configuration matrices and output. The result of reasoning process applied to the spatial configuration inside a mechanism shows that the fuzzy approach is effective for conceptual design with little quantitative information.
An Algorithm for Portfolio Optimization Problem
Authors: Jong Soo Kim, Yong Chan Kim, Ki Young Shin
Venue: Informatica (2005)

Portfolio optimization is to find the stock portfolio minimizing the risk for a required return or maximizing the return for a given risk level. The seminal work in this field is the mean-variance model formulated as a quadratic programming problem. Since it is not computationally practical to solve the original model directly, a number of alternative models have been proposed. In this paper, among the alternative models, we focus on the Mean Absolute Deviation (MAD) model. More specifically, we derive bounds on optimal objective function value. Using the bounds, we also develop an algorithm for the model. We prove mathematically that the algorithm can solve the problem to optimality. The algorithm is tested using the real data from the Korean Stock Market. The results come up to our expectations that the method can solve a variety of problems in a reasonable computational time.
Perturbational Neural Networks for Incremental Learning in Virtual Learning System
Authors: Eiichi Inohira, Hiromasa Oonishi, Hirokazu Yokoi
Venue: Neural Information Processing: 14th International Conference, ICONIP 2007, Kitakyushu, Japan, November 13-16, 2007, Revised Selected Papers, Part I (2007)

This paper presents a new type of neural networks, a perturbational neural network to realize incremental learning in autonomous humanoid robots. In our previous work, a virtual learning system has been provided to realize exploring plausible behavior in a robot's brain. Neural networks can generate plausible behavior in unknown environment without time-consuming exploring. Although an autonomous robot should grow step by step, conventional neural networks forget prior learning by training with new dataset. Proposed neural networks features adding output in sub neural network to weights and thresholds in main neural network. Incremental learning and high generalization capability are realized by slightly changing a mapping of the main neural network. We showed that the proposed neural networks realize incremental learning without forgetting through numerical experiments with a two-dimensional stair-climbing bipedal robot.
Verification of Clinical Guidelines by Model Checking
Authors: Beatriz Pérez, Ivan Porres
Venue: Proceedings of the 2008 21st IEEE International Symposium on Computer-Based Medical Systems (2008)

Clinical guidelines systematically assist practitioners with providing appropriate health care for specific clinical circumstances. However, a significant number of guidelines are lacking in quality. In this paper, we use the UML modeling language to capture guidelines and model checking techniques for their verification. We have established a classification of possible properties to be verified in a guideline and we present an automated approach based on a translation from UML to PROMELA, the input language of the SPIN model checker. Our approach is illustrated with a guideline based on a guideline published by the National Guideline Clearing House (NGC).
A Workflow Engine-Driven SOA-Based Cooperative Computing Paradigm in Grid Environments
Authors: Wanchun Dou, Jinjun Chen, Jianxun Liu, S.C. Cheung, Guihai Chen, Shaokun Fan
Venue: International Journal of High Performance Computing Applications (2008)

The grid has been proposed as a promising service-oriented platform for increasingly complex cooperative computing. The platforms of service-oriented grids are often Web-based where participants collaborate to achieve a common goal by sharing scarce Web-Based Computational/ Computing Resources (WBCR). To share the WBCR effectively is a challenging problem in boundary-spanning grid environments, particularly when these resources are subject to both static and dynamic usage. To set up the certificate-based usage policy described in this paper, we first explore a workflow engine-driven SOA-based resource access control mechanism. Then, aiming at setting up a cooperative computing paradigm from the resource sharing perspective, an infrastructure derived from a specific project of SOA EDSCCE (SOA-Based Engine-Driven Structured Cooperative Computing Environment) is proposed for promoting its cooperative computing in grid environment based on the control disciplines and the WBCR usage policy. The main contributions of this paper are twofold: 1) a workflow engine-driven SOA-based WBCR sharing mechanism is presented in accordance with to the certificate-based usage policy; and 2) a specific infrastructure of cooperative computing is put forward for the collaboration based on the WBCR sharing mechanism.