ppxscal/embedding_network huggingface dataset:
Local Path Planning of Mobile Robots in Dynamic Unknown Environment Based on Prediction of Collision
Authors: Yang Gao, Shu-dong Shun
Venue: Proceedings of the 2009 International Conference on Measuring Technology and Mechatronics Automation - Volume 02 (2009)

The velocity and its distribution of obstacles isobserved by an adaptive Unscented Kalman Filter, based onwhich the position of the dangerous region (potential collisionregion) is predicted. And based on its distribution, thedangerous region is expanded to ensure the security. Byfinding the best “Free Road” and estimate the “danger”, a datareduction technique is employed to compress all theinformation needed, with the help of which the efficiency isimproved significantly. Benefit from those the proposedalgorithm gets a better performance in dynamic environment.The results of simulations have proved that.
A Survey of Botnet and Botnet Detection
Authors: Maryam Feily, Alireza Shahrestani, Sureswaran Ramadass
Venue: Proceedings of the 2009 Third International Conference on Emerging Security Information, Systems and Technologies (2009)

Among the various forms of malware, botnets are emerging as the most serious threat against cyber-security as they provide a distributed platform for several illegal activities such as launching distributed denial of service attacks against critical targets, malware dissemination, phishing, and click fraud. The defining characteristic of botnets is the use of command and control channels through which they can be updated and directed. Recently, botnet detection has been an interesting research topic related to cyber-threat and cyber-crime prevention. This paper is a survey of botnet and botnet detection. The survey clarifies botnet phenomenon and discusses botnet detection techniques. This survey classifies botnet detection techniques into four classes: signature-based, anomaly-based, DNS-based, and mining-base. It summarizes botnet detection techniques in each class and provides a brief comparison of botnet detection techniques.
How to Use Spanning Trees to Navigate in Graphs
Authors: Feodor F. Dragan, Yang Xiang
Venue: Proceedings of the 34th International Symposium on Mathematical Foundations of Computer Science 2009 (2009)

In this paper, we investigate three strategies of how to use a spanning tree T of a graph G to navigate in G, i.e., to move from a current vertex x towards a destination vertex y via a path that is close to optimal. In each strategy, each vertex v has full knowledge of its neighborhood N G [v] in G (or, k-neighborhood D k (v,G), where k is a small integer) and uses a small piece of global information from spanning tree T (e.g., distance or ancestry information in T), available locally at v, to navigate in G. We investigate advantages and limitations of these strategies on particular families of graphs such as graphs with locally connected spanning trees, graphs with bounded length of largest induced cycle, graphs with bounded tree-length, graphs with bounded hyperbolicity. For most of these families of graphs, the ancestry information from a BFS-tree guarantees short enough routing paths. In many cases, the obtained results are optimal up to a constant factor.
An accurate, stable and efficient domain-type meshless method for the solution of MHD flow problems
Authors: G. C. Bourantas, E. D. Skouras, V. C. Loukopoulos, G. C. Nikiforidis
Venue: Journal of Computational Physics (2009)

The aim of the present paper is the development of an efficient numerical algorithm for the solution of magnetohydrodynamics flow problems for regular and irregular geometries subject to Dirichlet, Neumann and Robin boundary conditions. Toward this, the meshless point collocation method (MPCM) is used for MHD flow problems in channels with fully insulating or partially insulating and partially conducting walls, having rectangular, circular, elliptical or even arbitrary cross sections. MPC is a truly meshless and computationally efficient method. The maximum principle for the discrete harmonic operator in the meshfree point collocation method has been proven very recently, and the convergence proof for the numerical solution of the Poisson problem with Dirichlet boundary conditions have been attained also. Additionally, in the present work convergence is attained for Neumann and Robin boundary conditions, accordingly. The shape functions are constructed using the Moving Least Squares (MLS) approximation. The refinement procedure with meshless methods is obtained with an easily handled and fully automated manner. We present results for Hartmann number up to 10^5. The numerical evidences of the proposed meshless method demonstrate the accuracy of the solutions after comparing with the exact solution and the conventional FEM and BEM, for the Dirichlet, Neumann and Robin boundary conditions of interior problems with simple or complex boundaries.
The Optimal Application of the Algorithms of Detection and Data Mining in Honeynet
Authors: Dong Nanping, Zhou Guanling, Wang Yuping
Venue: Proceedings of the 2009 IITA International Conference on Control, Automation and Systems Engineering (case 2009) (2009)

This paper puts forward a technical scheme which properly arranges IDS and optimally applies the algorithms of detection and data mining to the Honeynet environment based on a project of building automation system completed by the author recently. In this specific environment, the position of IDS is deployed reasonably and the anomaly and misuse detection algorithm of IDS is designed and selected optimally. Meanwhile, the misuse detection rules are updated dynamically with the combination of data-mining algorithm RIPPER. The design makes the classical and mature algorithms of anomaly detection, misuse detection and RIPPER data mining display their technical characteristics and advantages to the largest extent in the project and enable the honeynet to protect the internal control network as expected.
Decision Support System of Basin Water Allocation Based on HWME
Authors: Tong Jinping, Ma Jianfeng, Wang Gang
Venue: Proceedings of the 2009 International Forum on Information Technology and Applications - Volume 01 (2009)

Constructing decision support system of water allocation is the base of water resources centralization of management in basin. Because water basin is an open complex giant system, water allocation and management would be a so complex process. Faced to open and complex water resources system, the hall for workshop of meta-synthetic engineering (HWME) was referenced, and decision support system of basin water allocation was built, then its participants of HWME, central mission and functional modules were illuminated in detail. The objects to building decision support system of water allocation were to balance the relation of water supply and demand, harmonize the relationship between the beneficial during water allocation, and reach to the aim of reasonable water allocation.
Using semantic authoring for Blissymbols communication boards
Authors: Yael Netzer, Michael Elhadad
Venue: Proceedings of the Human Language Technology Conference of the NAACL, Companion Volume: Short Papers on XX (2006)

Natural language generation (NLG) refers to the process of producing text in a spoken language, starting from an internal knowledge representation structure. Augmentative and Alternative Communication (AAC) deals with the development of devices and tools to enable basic conversation for language-impaired people. We present an applied prototype of an AAC-NLG system generating written output in English and Hebrew from a sequence of Bliss symbols. The system does not "translate" the symbols sequence, but instead, it dynamically changes the communication board as the choice of symbols proceeds according to the syntactic and semantic content of selected symbols, generating utterances in natural language through a process of semantic authoring.
A DE-based approach to no-wait flow-shop scheduling
Authors: B. Qian, L. Wang, R. Hu, D. X. Huang, X. Wang
Venue: Computers and Industrial Engineering (2009)

This paper proposes an effective hybrid differential evolution (HDE) for the no-wait flow-shop scheduling problem (FSSP) with the makespan criterion, which is a typical NP-hard combinational optimization problem. Firstly, a largest-order-value (LOV) rule is presented to transform individuals in DE from real vectors to job permutations so that the DE can be applied for solving FSSPs. Secondly, the DE-based parallel evolution mechanism and framework is applied to perform effective exploration, and a simple but efficient local search developed according to the landscape of FSSP is applied to emphasize problem-dependent local exploitation. Thirdly, a speed-up evaluation method and a fast Insert-based neighborhood examining method are developed based on the properties of the no-wait FSSPs. Due to the hybridization of DE-based evolutionary search and problem-dependent local search as well as the utilization of the speed-up evaluation and fast neighborhood examining, the no-wait FSSPs can be solved efficiently and effectively. Simulations and comparisons based on well-known benchmarks demonstrate the efficiency, effectiveness, and robustness of the proposed HDE.
Pseudorandom Bit Generators That Fool Modular Sums
Authors: Shachar Lovett, Omer Reingold, Luca Trevisan, Salil Vadhan
Venue: Proceedings of the 12th International Workshop and 13th International Workshop on Approximation, Randomization, and Combinatorial Optimization. Algorithms and Techniques (2009)

We consider the following problem: for given n,M, produce a sequence X1,X2,...,Xn of bits that fools every linear test modulo M. We present two constructions of generators for such sequences. For every constant prime power M, the first construction has seed length OM(log(n/¿)), which is optimal up to the hidden constant. (A similar construction was independently discovered by Meka and Zuckerman [MZ]). The second construction works for every M,n, and has seed length O(logn + log(M/¿)log(Mlog(1/¿))).The problem we study is a generalization of the problem of constructing small bias distributions [NN], which are solutions to the M = 2 case. We note that even for the case M = 3 the best previously known constructions were generators fooling general bounded-space computations, and required O(log2 n) seed length.For our first construction, we show how to employ recently constructed generators for sequences of elements of that fool small-degree polynomials (modulo M). The most interesting technical component of our second construction is a variant of the derandomized graph squaring operation of [RV]. Our generalization handles a product of two distinct graphs with distinct bounds on their expansion. This is then used to produce pseudorandom-walks where each step is taken on a different regular directed graph (rather than pseudorandom walks on a single regular directed graph as in [RTV, RV]).
Richness of the base and probabilistic unsupervised learning in optimality theory
Authors: Gaja Jarosz
Venue: Proceedings of the Eighth Meeting of the ACL Special Interest Group on Computational Phonology and Morphology (2006)

This paper proposes an unsupervised learning algorithm for Optimality Theoretic grammars, which learns a complete constraint ranking and a lexicon given only unstructured surface forms and morphological relations. The learning algorithm, which is based on the Expectation-Maximization algorithm, gradually maximizes the likelihood of the observed forms by adjusting the parameters of a probabilistic constraint grammar and a probabilistic lexicon. The paper presents the algorithm's results on three constructed language systems with different types of hidden structure: voicing neutralization, stress, and abstract vowels. In all cases the algorithm learns the correct constraint ranking and lexicon. The paper argues that the algorithm's ability to identify correct, restrictive grammars is due in part to its explicit reliance on the Optimality Theoretic notion of Richness of the Base.
PMCRI: A Parallel Modular Classification Rule Induction Framework
Authors: Frederic Stahl, Max Bramer, Mo Adda
Venue: Proceedings of the 6th International Conference on Machine Learning and Data Mining in Pattern Recognition (2009)

In a world where massive amounts of data are recorded on a large scale we need data mining technologies to gain knowledge from the data in a reasonable time. The Top Down Induction of Decision Trees (TDIDT) algorithm is a very widely used technology to predict the classification of newly recorded data. However alternative technologies have been derived that often produce better rules but do not scale well on large datasets. Such an alternative to TDIDT is the PrismTCS algorithm. PrismTCS performs particularly well on noisy data but does not scale well on large datasets. In this paper we introduce Prism and investigate its scaling behaviour. We describe how we improved the scalability of the serial version of Prism and investigate its limitations. We then describe our work to overcome these limitations by developing a framework to parallelise algorithms of the Prism family and similar algorithms. We also present the scale up results of a first prototype implementation.
Speckle Noise Filtering for Sea SAR Image
Authors: Yongxin Jiang, Xiaotong Wang, Xiaogang Xu, Xiyong Ye
Venue: Proceedings of the 2009 WRI Global Congress on Intelligent Systems - Volume 04 (2009)

The aliasing of the speckle noise and echo information of sea SAR blurs the structure character of sea SAR image. It is difficult that to enhance structure character of sea SAR image. Aiming at this difficulty, we propose a amalgamation frame based on EMD and exponent. The frame can effectively filter the speckle noise and enhance the structure character which finally can be seen by people’s eyes. Using the different frequency character of each level, the content of each level noise and non-noise are analyzed and exponent of each level is adjusted. And the speckle noise of simple SAR image in different scale is filtered. At last, we obtain the new denoised SAR image. The experiment result indicates that speckle noise of our result is substantially decreased and the structure character and texture of the result is clearer. And ours eyes can distinguish the character of sea SAR image. So that it proves that our filtering algorithm is effective to filter the speckle noise of sea SAR image.
Windows Small Business Server 2008
Authors: Craig Zacker
Venue:  (2009)

Portable and precise, this pocket-sized guide delivers ready answers for administering Windows Small Business Server 2008. Zero in on core support tasks and tools using quick-reference tables, instructions, and lists. You ll get the focused information you need to solve problems and get the job done whether at your desk or in the field. Get fast facts to: Plan, install, and configure a small business network Navigate the Windows SBS Console tool Create and administer user and group accounts Manage automatic updates, disk storage, and shared printers Configure mail settings and customize internal Web sites Boost security with authentication, authorization, and permissions Develop a backup and restoration strategy Monitor performance using alerts, notifications, and reports Expand the network by adding a server and accessing remote computers 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
PUTOP: turning predominant senses into a topic model for word sense disambiguation
Authors: Jordan Boyd-Graber, David Blei
Venue: Proceedings of the 4th International Workshop on Semantic Evaluations (2007)

We extend on McCarthy et al.'s predominant sense method to create an unsupervised method of word sense disambiguation that uses automatically derived topics using Latent Dirichlet allocation. Using topic-specific synset similarity measures, we create predictions for each word in each document using only word frequency information. It is hoped that this procedure can improve upon the method for larger numbers of topics by providing more relevant training corpora for the individual topics. This method is evaluated on SemEval-2007 Task 1 and Task 17.
Nonlinear Systems Fault Diagnosis with Differential Elimination
Authors: Zhang Jiafan
Venue: Proceedings of the 2009 International Conference on Computational Intelligence and Natural Computing - Volume 02 (2009)

The differential elimination algorithm is used to eliminate the non-observed variables of the nonlinear systems. By incorporating the algebraic observability and diagnosability concepts and using numerical differentiation algorithms, another approach to the certain classes of nonlinear systems fault diagnosis problem is presented.
Knowledge-driven learning and discovery
Authors: Benjamin Lambert, Scott E. Fahlman
Venue: Proceedings of the 22nd national conference on Artificial intelligence - Volume 2 (2007)

The goal of our current research is machine learning with the help and guidance of a knowledge base (KB). Rather than learning numerical models, our approach generates explicit symbolic hypotheses. These hypotheses are subject to the constraints of the KB and are easily human-readable and verifiable. Toward this end, we have implemented algorithms that hypothesize new relations and new types of entities in a KB by examining structural regularities in the KB that represent implicit knowledge. We evaluate these algorithms on a publications KB and a zoology KB.
Effects of Practice with Foot- and Hand-Operated Secondary Input Devices on Performance of a Word-Processing Task
Authors: Fredrick P. Garcia, Kim-Phuong L. Vu
Venue: Proceedings of the Symposium on Human Interface 2009 on ConferenceUniversal Access in Human-Computer Interaction. Part I: Held as Part of HCI International 2009 (2009)

This study compared the performance of users operating a foot controlled input device (foot mouse) with that of users operating a hand controlled input device (hand trackball). Four different tasks that required (1) direct manipulation of on-screen objects and menu command activation, (2) keyboard entry and direct manipulation, (3) keyboard entry and command activation, and (4) keyboard entry, direct manipulation, and command activation were assessed. Performance on each task was measured both before and after participants practiced computing tasks with one of the devices for 750 trials. For all 4 tasks, practice improved performance with the foot mouse but not the hand trackball. However, overall performance was better with the hand trackball.
Simultaneous heuristic search for conjunctive subgoals
Authors: Lin Zhu, Robert Givan
Venue: Proceedings of the 20th national conference on Artificial intelligence - Volume 3 (2005)

We study the problem of building effective heuristics for achieving cunjunctive goals from heuristics for individual goals. We consider a straightforward method for building conjunctive heuristics that smoothly trades off between previous common methods. In addition to first explicitly formulating the problem of designing conjunctive heuristics. our major contribution is the discovery that this straightforward method substantially outperforms previously used methods across a wide range of domains. Based on a single positive real parameter k, our heuristic measure sums the individual heuristic values for the subgoal conjuncts, each raised to the k'th power. Varying k allows loose approximation and combination of the previous min, max. and sum approaches, while mitigating some of the weaknesses in those approaches. Our empirical work shows that for many benchmark planning domains there exist fixed parameter values that perform well-- we give evidence that these values can be found automatically by training. Our method, applied to top-level conjunctive goals, shows dramatic improvements over the heuristic used in the FF planner across a wide range of planning competition benchmarks. Also, our heuristic, without computing landmarks, consistently improves upon the success ratio of a recently published landmark-based planner FF-L.
Application of Synthetic Neural Network for Fault Diagnosis of Steam Turbine Flow Passage
Authors: Lihua Cao, Yunlong Zhou, Wei Xu, Yong Li
Venue: Proceedings of the 2009 International Conference on Computational Intelligence and Natural Computing - Volume 01 (2009)

It is difficult to determine the normal value for fault diagnosis of steam turbine flow passage, because the flow passage fault or regenerative system fault may result in the decrease of the relative internal efficiency of steam turbine. Based on analyzing the feature of flow passage and regenerative system, the flow passage condition of steam turbine can be evaluated by relative internal efficiency of stage groups. According to various effect factors, the methods to determine the normal value of relative internal efficiency of stage groups is proposed in this paper, which include application of synthetic neural network. Compared the measured values with these normal values, the operating condition of steam turbine flow passage can be evaluated and the detailed reasons of fault can be diagnosed.
Transforming of an existing structural analysis program to the object-oriented framework
Authors: M. V. Sivaselvan, E. Yuksel, K. Winkelmann, A. M. Reinhorn
Venue: Advances in Engineering Software (2009)

The object-oriented philosophy abstracts out the essential immutable qualities of the components of the finite element method into classes of objects. It facilitates easy modification capability without creating a ripple effect on the whole program and reduces the necessity of knowledge of the source code to a minimum level. This paper presents a prototype implementation of the development of a flexible computational platform based on an object-oriented approach and its application in a FORTRAN environment, which facilitates use of previously developed components. IDARC3D which is capable of linear and nonlinear, static as well as dynamic analyses of multistory three-dimensional buildings with, or without, energy dissipation devices developed in FORTRAN with conventional programming practices has been transformed to the object-oriented framework. By using the new object-oriented platform, some representative examples were analysed and the results were compared with the well-known software facilities.
Rotation Invariant Image Description with Local Binary Pattern Histogram Fourier Features
Authors: Timo Ahonen, Jiří Matas, Chu He, Matti Pietikäinen
Venue: Proceedings of the 16th Scandinavian Conference on Image Analysis (2009)

In this paper, we propose Local Binary Pattern Histogram Fourier features (LBP-HF), a novel rotation invariant image descriptor computed from discrete Fourier transforms of local binary pattern (LBP) histograms. Unlike most other histogram based invariant texture descriptors which normalize rotation locally, the proposed invariants are constructed globally for the whole region to be described. In addition to being rotation invariant, the LBP-HF features retain the highly discriminative nature of LBP histograms. In the experiments, it is shown that these features outperform non-invariant and earlier version of rotation invariant LBP and the MR8 descriptor in texture classification, material categorization and face recognition tests.