ppxscal/embedding_network huggingface dataset:
Encrypting Algorithm Based on RBF Neural Network
Authors: Kaili Zhou, Yaohong Kang, Yan Huang, Erli Feng
Venue: Proceedings of the Third International Conference on Natural Computation - Volume 01 (2007)

An encrypting algorithm based on RBF neural network is presented. The clear-text is regarded as RBF target vector. RBF network is trained with random input vector, and the trained results are regarded as the cryptograph. With the feature that the input vector of RBF neural network can be any random value, there are the infinite kinds of ways to build the input vector, so the cryptograph cannot be deciphered theoretically. The random seed used to generate the input vector is regarded as the secret-key. The receiver can get the clear-text from the cryptograph by reconstructing RBF neural network and its input vector with the secret-key. The simulation experiments prove the algorithm is feasible and effective.
An Agent-based Policy Aware Framework for Web Services Security
Authors: JIAN-XIN LI, BIN LI, LIANG LI, TONG-SHENG CHE
Venue: Proceedings of the 2007 IFIP International Conference on Network and Parallel Computing Workshops (2007)

The security of Web Services has become one of the important research topics about the application of Web Services. In this paper, we propose an agentbased policy aware framework for Web Services security. In this framework, a policy language called ReiT which is a declarative language based on the rules and ontologies is introduced. The non-structural knowledge is represented by rules and the structural temporal knowledge is represented by ontology. Moreover, we propose a mixed reasoning mechanism to evaluate the ReiT policy. The access control policy including the context of the user and Web Services is evaluated by the reasoner. In addition, we present a policy aware BOID agent to authorize the access control of the Web Services. And we implement the policy aware BOID agent by extending the JADE platform.
Generalisations of the compound trapezoidal rule
Authors: M. Ragulskis, L. Saunoriene
Venue: Applied Numerical Mathematics (2008)

A set of symmetric equidistant quadrature rules with equal internal weights are developed. Some of the rules use the first (and second) derivative(s) in addition to the function values of the integrand. A single unifying concept based on finite element techniques is used to develop this set of quadrature rules. With focus on the quadratures rules' degree of precision we compute the quadrature weights and error estimates for all rules given.
Highly (100)-oriented Pb(Zr0.20Ti0.80)O3/(Pb1-xLax)Ti1-x/4O3 multilayered thin films prepared by RF magnetron sputtering
Authors: Jiagang Wu, Dingquan Xiao, Jiliang Zhu, Jianguo Zhu, Junzhe Tan, Qinglei Zhang
Venue: Microelectronic Engineering (2008)

The Pb(Zr"0"."2"0Ti"0"."8"0)O"3/(Pb"1"-"xLa"x)Ti"1"-"x"/"4O"3 (x=0, 0.10, 0.15, 0.20) (PZT/PLT"x) multilayered thin films were in situ deposited on the Pt(111)/Ti/SiO"2/Si(100) substrates by RF magnetron sputtering technique with a PbO"x buffer layer. With this method, all PZT/PLT"x multilayered thin films possess highly (100) orientation. The PbO"x buffer layer leads to the (100) orientation of the multilayered thin films. The effect of the La content in PLT"x layers on the dielectric and ferroelectric properties of the PZT multilayered thin films was systematically investigated. The enhanced dielectric and ferroelectric properties are observed in the PZT/PLT"x (x=0.15) multilayered thin films. The dielectric constant reaches maximum value of 365 at 1KHz for x=0.15 with a low loss tangent of 0.0301. Along with enhanced dielectric properties, the multilayered thin films also exhibit large remnant polarization value of 2P"r =76.5@mC/cm^2, and low coercive field of 2E"c= 238KV/cm.
Neural Inversion of Flight Guidance Dynamics
Authors: W. C. Lu, R. M. Faye, A. C. Brandao Ramos, J. Slama, F. Mora-Camino
Venue: Proceedings of the Seventh International Conference on Intelligent Systems Design and Applications (2007)

Differential flatness, a property of some dynamic systems which has been recognized only recently, has made possible the development of new tools to control complex nonlinear dynamic systems. Many dynamic non linear systems have been proved to be differentially flat. In this paper, it is shown that the inertial position coordinates of an aircraft can be considered as differential flat outputs for its flight guidance dynamics. Since this differential flatness property is implicit, a neural network is introduced, as a numerical device, to deal with the inversion of the guidance dynamics. Then, once conveniently structured and trained, a neural network is able to generate in real time directives to conventional autopilot systems so that a reference trajectory can be tracked. Numerical results relative to the training of the neural network and to trajectory tracking are displayed and discussed.
Highly efficient techniques for network forensics
Authors: Miroslav Ponec, Paul Giura, Hervé Brönnimann, Joel Wein
Venue: Proceedings of the 14th ACM conference on Computer and communications security (2007)

Given a history of packet transmissions and an excerpt of a possible packet payload, the payload attribution problem requires the identification of sources, destinations and the times of appearance on a network of all the packets that contained such payload. A module to solve this problem has recently been proposed as the core component in a network forensics system. Network forensics provides useful tools for investigating cybercrimes on the Internet, by, for example, tracing the spread of worms and viruses, identifying who has received a phishing email in an enterprise, or discovering which insider allowed an unauthorized disclosure of sensitive information. In general it is infeasible to store and query the actual packets, therefore we focus on extremely compressed digests of the packet activity. We propose several new methods for payload attribution which utilize Rabin fingerprinting, shingling, and winnowing. Our best methods allow data reduction ratios greater than 100:1 while supporting queries with very low false positive rates, and provide efficient querying capabilities given reasonably small excerpts of a payload. Our results outperform current state-of-the-art methods both in terms of false positive rates and data reduction ratio. Finally, these approaches directly allow the collected data to be stored and queried by an untrusted party without disclosing any payload information nor the contents of queries.
Reconstructing relief surfaces
Authors: George Vogiatzis, Philip H. S. Torr, Steven M. Seitz, Roberto Cipolla
Venue: Image and Vision Computing (2008)

This paper generalizes Markov Random Field (MRF) stereo methods to the generation of surface relief (height) fields rather than disparity or depth maps. This generalization enables the reconstruction of complete object models using the same algorithms that have been previously used to compute depth maps in binocular stereo. In contrast to traditional dense stereo where the parametrization is image based, here we advocate a parametrization by a height field over any base surface. In practice, the base surface is a coarse approximation to the true geometry, e.g., a bounding box, visual hull or triangulation of sparse correspondences, and is assigned or computed using other means. A dense set of sample points is defined on the base surface, each with a fixed normal direction and unknown height value. The estimation of heights for the sample points is achieved by a belief propagation technique. Our method provides a viewpoint independent smoothness constraint, a more compact parametrization and explicit handling of occlusions. We present experimental results on real scenes as well as a quantitative evaluation on an artificial scene.
Clustering over Multiple Evolving Streams by Events and Correlations
Authors: Mi-Yen Yeh, Bi-Ru Dai, Ming-Syan Chen
Venue: IEEE Transactions on Knowledge and Data Engineering (2007)

In applications of multiple data streams such as stock market trading and sensor network data analysis, the clusters of streams change at different time because of the data evolution. The information of evolving cluster is valuable to support corresponding online decisions. In this paper, we present a framework for Clustering Over Multiple Evolving sTreams by CORrelations and Events, which, abbreviated as COMETCORE, monitors the distribution of clusters over multiple data streams based on their correlation. Instead of directly clustering the multiple data streams periodically, COMET-CORE applies efficient cluster split and merge processes only when significant cluster evolution happens. Accordingly, we devise an event detection mechanism to signal the cluster adjustments. The coming streams are smoothed as sequences of end points by employing piecewise linear approximation. At the time when end points are generated, weighted correlations between streams are updated. End points are good indicators of significant change in streams, and this is a main cause of cluster evolution event. When an event occurs, through split and merge operations we can report the latest clustering results. As shown in our experimental studies, COMET-CORE can be performed effectively with good clustering quality.
An Experimental Study on Peer Selection in a P2P Network over PlanetLab
Authors: Fatos Xhafa, Leonard Barolli, Raul Fernandez, Thanasis Daradoumis
Venue: Proceedings of the 2007 International Conference on Parallel Processing Workshops (2007)

Peer selection is an important aspect in many P2P applications requiring efficient assignment and execution of jobs to peer nodes and search and file transfer, among others. Due to increasing interest of using P2P systems for distributed computing, peer selection is taking relevance and several models have been proposed in the P2P literature. Yet, there are very few experimental studies for peer selection in P2P networks deployed in real large scale networks. In this work we present an experimental study that aims at revealing empirical information about the efficiency of selecting peer nodes in a P2P network when deployed in a real geographically distributed network. To this end, we have used a JXTA-based P2P platform deployed in Planet- Lab, a planetary scale infrastructure, and have empirically evaluated several peer selection models. Our experimental study showed that in order to achieve efficient P2P applications, appropriate selection model should be used according to the characteristics of the application.
Compile Time Memory Allocation for Parallel Processes
Authors: G. V. Bochmann
Venue: IEEE Transactions on Software Engineering (1978)

This paper discusses the problem of allocating storage for the activation records of procedure calls within a system of parallel processes. A compile time storage allocation scheme is given, which determines the relative address within the memory segment of a process for the activation records of all procedures called by the process. This facilitates the generation of an efficient run-time code. The allocation scheme applies to systems in which data and procedures can be shared among several processes. However, recursive procedure calls are not supported.
Equivalence and Transformations for Post Multivalued Algebras
Authors: R. S. Nutter
Venue: IEEE Transactions on Computers (1974)

Four commonly used multivalued algebras, the disjoint system of Post algebra developed by Epstein, the monotonic system of algebra called Muehldorf by some authors, the free system of algebra introduced by Braddock and Epstein, and the Herrmann system of algebra generalized here from its original three element algebra, are shown to be isomorphic. Transformations are then developed for transforming from one algebra to another. An example problem is presented to illustrate transforming from any of the above to the disjoint system of Post algebra.
FAISC: A Fuzzy Artificial Immune System Clustering Algorithm
Authors: Zhaodong Liu, Xin Jin, Rongfang Bie, Xiaozhi Gao
Venue: Proceedings of the Third International Conference on Natural Computation - Volume 03 (2007)

Clustering is an unsupervised knowledge discovery process that groups a set of data such that the intracluster similarity is maximized and the inter-cluster similarity is minimized. Existing clustering algorithms, such as k-means and PAM, are designed to find clusters that fit static models. In this paper, we describe a clustering algorithm called Fuzzy Artificial Immune System Clustering (FAISC), which is based on Artificial Immune Network and Fuzzy System. Experiments on benchmark datasets show very good qualitative results obtained better than k-means which is one of the widest used clustering algorithm.
Quine&#x2013;McCluskey method for many-valued logical functions
Authors: Milan Petr&#x00ed;k
Venue: Soft Computing - A Fusion of Foundations, Methodologies and Applications (2007)

In this paper we deal with a generalization of the Quine&#x2013;McCluskey method. We show that the generalized method can find a normal form for any finite-valued logical function. Moreover, this normal form is simpler than that found by the intuitive method using the table of values. The method has been successfully implemented and tested on examples.
Request Window: an approach to improve throughput of RDBMS-based data integration system by utilizing data sharing across concurrent distributed queries
Authors: Rubao Lee, Minghong Zhou, Huaming Liao
Venue: Proceedings of the 33rd international conference on Very large data bases (2007)

This paper focuses on the problem of improving distributed query throughput of the RDBMS-based data integration system that has to inherit the query execution model of the underlying RDBMS: execute each query independently and utilize a global buffer pool mechanism to provide disk page sharing across concurrent query execution processes. However, this model is not suitable for processing concurrent distributed queries because the foundation, the memory-disk hierarchy, does not exist for data provided by remote sources. Therefore, the query engine cannot exploit any data sharing so that each process will have to interact with data sources independently: issue data requests and fetch data over the network. This paper presents Request Window, a novel DQP mechanism that can detect and employ data sharing opportunities across concurrent distributed queries. By combining multiple similar data requests issued to the same data source to a common data request, Request Window allows concurrent query executing processes to share the common result data. With the benefits of reduced source burdens and data transfers, the throughput of query engine can be significantly improved. This paper also introduces the IGNITE system, an extended PostgreSQL with DQP support. Our experimental results show that Request Window makes IGNITE achieve a 1.7x speedup over a commercial data integration system when running a workload of distributed TPC-H queries.
The word problem for visibly pushdown languages described by grammars
Authors: Salvatore Torre, Margherita Napoli, Mimmo Parente
Venue: Formal Methods in System Design (2007)

Visibly pushdown languages are an interesting subclass of deterministic context-free languages that can model nonregular properties of interest in program analysis. Such class properly contains typical classes of parenthesized languages such as "parenthesis", "bracketed", "balanced" and "input-driven" languages. It is closed under boolean operations and has decidable decision problems such as emptiness, inclusion and universality. We study the membership problem for visibly pushdown languages, and show that it can be solved in time linear in both the size of the input grammar and the length of the input word. The algorithm relies on a reduction to the reachability problem for game graphs. We also discuss the time complexity of the membership problem for the class of balanced languages which is the largest among those cited above. Besides the intrinsic theoretical interest, we further motivate our main result showing an application to the validation of XML documents against Schema and Document Type Definitions (DTDs).
Letters: An unified EM algorithm for PCA and KPCA
Authors: Haixian Wang, Zilan Hu
Venue: Neurocomputing (2007)

In this note, from another point of view and in a more general situation, we formulate an EM algorithm for finding the leading eigen-system of any positive semi-definite matrix in a very simple derivation. The proposed EM approach can directly compute not only the eigen-system of sample covariance matrix in data space but also that of kernel matrix. Thus, the proposed algorithm provides an unified framework for EM-based principal component analysis (PCA) and kernel PCA (KPCA). Particularly, when it is applied to KPCA, it is a dual form of the commonly used constrained EM algorithm for performing KPCA. And thus it is a beneficial complementarity or dual description of the constrained EM method.
Source preferences in the context of seeking problem-specific information
Authors: Reijo Savolainen
Venue: Information Processing and Management: an International Journal (2008)

The study focuses on the ways in which people define their source preferences in the context of seeking problem-specific information for non-work purposes. The conceptual framework draws on two major concepts, that is, information source horizon and information pathways. The former denotes the ways information sources are mapped in preference order in an imaginary field, while information pathways refers to the sequences in which sources placed on the information source horizon are actually used. The empirical part of the study draws on semi-structured interviews with 18 individuals active in environmental issues. Human sources and the Internet were preferred most strongly in seeking for problem-based information. The major source preferences were content of information, and availability and accessibility. Usability of information sources and user characteristics were mentioned less frequently as preference criteria. Typically, information pathways consisted of the use of 3-4 sources. On average, human and networked sources were favored in the early phases of information seeking. Printed media such as magazines and organizational sources were often used to complement information received from human sources and the Internet. However, the source preferences varied considerably, depending on the requirements of the problem at hand.
Interleaved Traffic Splitting: A promising technique to solve False Timeout
Authors: Shizhong Xu, Kaiyu Zhou, Kwan L. Yeung, Victor O. K. Li
Venue: Computer Communications (2007)

In this paper, we analyze the False Timeout (FTO) problem that TCP flows suffered in OBS networks and propose Interleaved Traffic Splitting (ITS) to solve the problem. We show that the collision loss of ACK bursts may also cause FTO, which has been neglected by previous researchers. As TCP Sack is designed to recover from multiple packet losses, we find that a Sack flow can recover its data transmission without triggering retransmission timeout if packet loss is not too severe. This suggests limiting the number of packets carried by a single burst. In ITS, this is achieved by carrying out a parallel, interleaved burst assembly process at each ingress OBS edge router. We show that ITS tackles the FTO problem caused by the loss of both data and ACK bursts. Unlike other existing approaches, the ITS scheme requires only modification to the assembly/de-assembly mechanisms implemented at the edge routers. It does not add complexities to the network management or the router design. In this paper, both analytical and simulation results are presented to demonstrate the performance improvement of ITS. Our analysis further shows that the use of two parallel bursts is optimum for ITS.
The Training of Radial Basis Function Network Classifier with Cooperative Clustering
Authors: Shaomin Mu, Shengfeng Tian, Chuanhuan Yin
Venue: Proceedings of the Fourth International Conference on Fuzzy Systems and Knowledge Discovery - Volume 02 (2007)

The selection of centers and widths parameter has a strong influence on the performance of radial basis function neural network. In this paper, we present a novel approach of clustering, which we called cooperative clustering, and use it for selection of centers of radial basis function neu- ral network.The experimental results are given to show that the approach could not only effectively improve the training speed, but also keep classification accuracies.
Processes for Random and Sequential Accessing in Dynamic Memories
Authors: S. B. Morris
Venue: IEEE Transactions on Computers (1979)

In a memory using shuffle interconnections, the concept of sequential accessing in unit time has been related to the existence of a sequence of operations, called a tour, that moves each datum through the read/write port. For memories of size 32, it has been stated that for certain operations no tours exist at window 1; moreover, the existence and construction of tours at other windows and for lar
Evolving Connectionist and Hybrid Systems: Methods, Tools, Applications
Authors: Nikola Kasabov
Venue: Proceedings of the 7th International Conference on Hybrid Intelligent Systems (2007)

Evolving Connectionist Systems (ECOS) are neural network systems that develop their structure, functionality and internal representation through continuous learning from data and interaction with the environment. ECOS can also evolve through generations of populations using evolutionary computation, but the focus of the presentation is on: (1) Adaptive learning and improvement of each individual model; (2) Knowledge representation, knowledge adaptation and knowledge extraction. The learning process can be: on-line, off-line, incremental, supervised, unsupervised, active, sleep/dream, etc.
Using Visual Tools to Close the Home Networking Digital Divide
Authors: Erika Shehan Poole
Venue: Proceedings of the IEEE Symposium on Visual Languages and Human-Centric Computing (2007)

As computer networking has moved out of managed environments and into the home, householders - whether they want to or not -- have had to tackle problems of home network maintenance. Unlike in enterprise environments, however, householders often do not plan or manage for network growth. As a result, devices are often added in a haphazard, piecemeal manner [1]. The open-ended nature of home networking protocols has also led to highly dynamic and heterogeneous home networks. The range of possible devices--and possible ways to configure and connect those devices--means that every network likely looks different; one study suggests that highly customized, end-user configured home networks are the norm in many households today [2] . Given the complexity of digital devices, the presence of highly-customized networks, and the technical inexperience of many people, how well do householders understand the structure and function of their home networks? How well can they cope with networking problems when they arise?
Method of Folding a Piecewise Polynomial Function in the Delta Function Integral Representation
Authors: Deok Kyo Lee
Venue: IEEE Transactions on Computers (1978)

A simple procedure is presented for determining the folded form of a piecewise polynomial function in the delta function integral representation. The procedure is useful in evaluating the autocorrelation function by means of the algebraic convolution technique developed by Polge and Hays.