ppxscal/embedding_network huggingface dataset:
Evolutionary design of single-mode microstructured polymer optical fibres using an artificial embryogeny representation
Authors: Steven Manos, Maryanne C. J. Large, Leon Poladian
Venue: Proceedings of the 2007 GECCO conference companion on Genetic and evolutionary computation (2007)

Polymer microstructured optical fibres are a relatively recent development in optical fibre technology, supporting a wide variety of microstructure fibre geometries, when compared to the more commonly used silica. In order to meet the automated design requirements for such complex fibres, a representation was developed which can describe radially symmetric microstructured fibres of different complexities; from simple hexagonal designs with very few holes, to large arrays of hundreds of holes. This representation uses an embryogeny, where the complex phenotype is 'grown' from a simpler genotype, and the resulting complexity is primarily a feature of the reuse of gene elements that describe the microstructure elements. Most importantly, the growth process results in the automatic satisfaction of manufacturing constraints. In conjunction with a multi-objective genetic algorithm, this formed a robust algorithm for the design of microstructured fibres for particular applications of interest. In this paper the algorithm is used to design one of the most common types of microstructured fibres - single-moded fibres. Various types of single-moded designs that have not been encountered in the literature were discovered, identifying new 'design themes'. One of the designs was subsequently manufactured, the details of which are included.
A scalable association rule visualization towards displaying large amounts of knowledge
Authors: Olivier Couturier, Tarek Hamrouni, Sadok Ben Yahia, Engelbert Mephu Nguifo
Venue: Proceedings of the 11th International Conference Information Visualization (2007)

Providing efficient and easy-to-use graphical tools to users is a promising challenge of data mining (DM). These tools must be able to generate explicit knowledge and to restitute it. Visualization techniques have shown to be an efficient solution to achieve such goal. Even though considered as a key step in the mining process, the visualization step of association rules received much less attention than that paid to the extraction one. Nevertheless, some graphical tools have been developed to extract and visualize association rules. In those tools, various approaches are proposed to filter the huge number of association rules before the visualization step. However both DM steps (association rule extraction and visualization) are treated separately in a one way process. Our approach differs, and uses meta-knowledge to guide the user during the mining process. Standing at the crossroads of DM and Human-Computer Interaction (HCI), we present an integrated framework covering both steps of the DM process. Furthermore, our approach can easily integrate previous techniques of association rule visualization.
A UML 2.0 profile to design Association Rule mining models in the multidimensional conceptual modeling of data warehouses
Authors: Jose Zubcoff, Juan Trujillo
Venue: Data Knowledge Engineering (2007)

By using data mining techniques, the data stored in a Data Warehouse (DW) can be analyzed for the purpose of uncovering and predicting hidden patterns within the data. So far, different approaches have been proposed to accomplish the conceptual design of DWs by following the multidimensional (MD) modeling paradigm. In previous work, we have proposed a UML profile for DWs enabling the specification of main MD properties at conceptual level. This paper presents a novel approach to integrating data mining models into multidimensional models in order to accomplish the conceptual design of DWs with Association Rules (AR). To this goal, we extend our previous work by providing another UML profile that allows us to specify Association Rules mining models for DW at conceptual level in a clear and expressive way. The main advantage of our proposal is that the Association Rules rely on the goals and user requirements of the Data Warehouse, instead of the traditional method of specifying Association Rules by considering only the final database implementation structures such as tables, rows or columns. In this way, ARs are specified in the early stages of a DW project, thus reducing the development time and cost. Finally, in order to show the benefits of our approach, we have implemented the specified Association Rules on a commercial database management server.
Bayesowl: a probabilistic framework for uncertainty in semantic web
Authors: Yun Peng
Venue:  (2005)

To address the difficult but important problem of modeling uncertainty in semantic web, this research takes a probabilistic approach and develops a theoretical framework, named BayesOWL, that incorporates the Bayesian network (BN), a widely used graphic model for probabilistic interdependency, into the web ontology language OWL. This framework consists of three key components: (1) a representation of probabilistic constraints as OWL statements; (2) a set of structural translation rules and procedures that converts an OWL taxonomy ontology into a BN directed acyclic graph (DAG); and (3) a method SD-IPFP based on "iterative proportional fitting procedure" (IPFP) that incorporates available probability constraints into the conditional probability tables (CPTs) of the translated BN. The translated BN, which preserves the semantics of the original ontology and is consistent with all the given probability constraints, can support ontology reasoning, both within and cross ontologies, as Bayesian inferences, with more accurate and more plausible results.SD-IPFP was further developed into D-IPFP, a general approach for modifying BNs with probabilistic constraints that goes beyond BayesOWL. To empirically validate this theoretical work, both BayesOWL and variations of IPFP have been implemented and tested with example ontologies and probabilistic constraints. The tests confirmed theoretical analysis. The major advantages of BayesOWL over existing methods are: (1) it is non-intrusive and flexible, neither OWL nor ontologies defined in OWL need to be modified and one can translate either the entire ontology or part of it into BN depending on the needs; (2) it separates the "rdfs:subClassOf" relations (or the subsumption hierarchy) from other logical relations by using L-Nodes, which makes CPTs of the translated BN smaller and easier to construct in a systematic and disciplined way, especially in a domain with rich logical relations; (3) it does not require availability of complete conditional probability distributions, pieces of probability information can be incorporated into the translated BN in a consistent fashion. One thing to emphasize is that BayesOWL can be easily extended to handle other ontology representation formalisms (syntax is not important, semantic matters), if not using OWL.
d-MUSIC, a real time algorithm for estimating the DOA of coherent sources using a single array snapshot
Authors: R. K. Howell
Venue: Proceedings of the Acoustics, Speech, and Signal Processing, 1999. on 1999 IEEE International Conference - Volume 05 (1999)

d-MUSIC estimates the DOA of two closely spaced sources using a single array snapshot. To overcome the coherent signal problem d-MUSIC utilizes additional information, specifically the derivative of an array snapshot. The combined vector set produces a full rank signal space projector. The algorithm nearly attains the Cramer-Rao bound for typical air traffic control problems. As it does not require a subspace decomposition (e.g., eigenstructure) and all operations are highly vectorized it can be readily implemented in real-time. The algorithm is tested using vertical linear array data with a low flying helicopter. With a spacing of 16% to 35% of a beamwidth between the direct and surface reflected rays, the d-MUSIC RMS error is 9.6% of a beamwidth for the 4 data collections while MUSIC resolved the two rays for 2 of the 4 cases with a RMS error of 18.1%.
Co-evolutionary global optimization algorithm
Authors: M. Iwamatsu
Venue: Proceedings of the Evolutionary Computation on 2002. CEC '02. Proceedings of the 2002 Congress - Volume 02 (2002)

A hybrid global optimization method, the co-evolutionary global optimization algorithm, is proposed, which utilizes the self-organized critical state as a means of diversification of search and the traditional conjugate gradient local minimization method as a means of intensification of search. The former has been recently used by Boettcher and Percus (2000) to solve discrete combinatorial optimization problems. The proposed method has been tested to locate the lowest energy conformation of atomic clusters. It was found that the method was effective not only to locate the lowest energy state but also to enumerate all the low-lying metastable states. 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
Symbolic Model Checking for Channel-based Component Connectors
Authors: Sascha Klüppelholz, Christel Baier
Venue: Electronic Notes in Theoretical Computer Science (ENTCS) (2007)

The paper reports on the foundations and experimental results with a model checker for component connectors modelled by networks of channels in the calculus Reo. The specification formalisms is a branching time logic that allows to reason about the coordination principles of and the data flow in the network. The underlying model checking algorithm relies on variants of standard automata-based approaches and model checking for CTL-like logics. The implementation uses a symbolic representation of the network and the enabled I/O-operations by means of binary decision diagrams. It has been applied to a couple examples that illustrate the efficiency of our model checker.
Characterization of Isothetic Polygons for Image Indexing and Retrieval
Authors: Arindam Biswas, Partha Bhowmick, Bhargab B. Bhattacharya
Venue: Proceedings of the International Conference on Computing: Theory and Applications (2007)

A novel algorithm for two-level indexing of a binary image in a database is proposed. The scheme is based on certain elementary geometric features of the tightly fitting isothetic polygon circumscribing the digital object (and/or those inscribing the holes in the interior of the object). These features, being simple and precise, are used to form a higher level description of the underlying objects present in an image. The edges of an isothetic polygon are classified into three types based on the types of vertices defining an edge. The number of each type of edges is used for first-level of indexing, and the total edge length is used in the second level. The scheme has been tested on two benchmark logo databases, and the retrieval results demonstrate the elegance, robustness, efficiency, and speed of the proposed method.
Long correlation Gaussian random fields: Parameter estimation and noise reduction
Authors: C. F. Caiafa, A. N. Proto, E. E. Kuruoğlu
Venue: Digital Signal Processing (2007)

In this paper, a parametric model for Gaussian random fields (GRFs) with long-correlation feature, namely the long correlation GRF (LC-GRF), is studied. Important properties of the model are derived and used for developing new parameter estimation algorithms and for constructing an optimum noise reduction filter. In particular, a novel iterative maximum likelihood estimation (MLE) algorithm is proposed for estimating the parameters of the model from a sample image, and the expectation-maximization (EM) algorithm is proposed for estimating the signal and noise variances given a noisy image. The optimal Wiener filter is derived making use of the parametric form of the model for the noise reduction under additive white Gaussian noise (WGN). Also the theoretic performance of the filter is obtained and its behavior is analyzed in terms of the long-correlation feature of the model. The effectiveness of the presented algorithms is demonstrated through experimental results on synthetic generated GRFs. An application to the restoration of cosmic microwave background (CMB) images in the presence of additive WGN is also presented.
Semi-unified Caches
Authors: Nathalie Drach, Andre Seznec
Venue: Proceedings of the 1993 International Conference on Parallel Processing - Volume 01 (1993)

The purpose of the semi-unified on-chip cache organization, is to use the data cache (resp. ins truction cache) as an on-chip second-level cache for instructions (resp. data). Thus the associativity de gree of both on-chip caches is artificially increased, and the cache spaces respectively devoted to instruc tions and data are dynamically adjusted. The off-chip miss ratio of a semi-unified cache built with two directmapped caches of size S is equal to the miss ratio of a unified two-way set associative cache of size 2S; yet, the hit time of this semi-unified cache is equal to the hit time of a direct-mapped cache. Trace driven simu lations show that using a direct-mapped semi-unified cache organization leads to higher overall system per formance than using usual split instruction/data cache organization.
Additive and multiplicative abrupt jump detection using the continuous wavelet transform
Authors: M. Chabert
Venue: Proceedings of the Acoustics, Speech, and Signal Processing, 1996. on Conference Proceedings., 1996 IEEE International Conference - Volume 05 (1996)

This paper addresses the problem of additive and multiplicative abrupt jump detection. Two detection algorithms based on the continuous wavelet transform are studied. Additive and multiplicative jumps are compared in the time-scale plane. Considering non-zero mean signals, we show that the same wavelet based algorithms can be used for the detection of additive and multiplicative jumps. However, an analysis of the variance in the time-scale plane allows us to distinguish these two kinds of jump.
Performance Comparison of Chip-Level Equalizers in the HSDPA System
Authors: Minjae Park, Woonsik Lee, Moohong Lee, Hwang Soo Lee
Venue: Proceedings of the 40th Annual Simulation Symposium (2007)

High speed downlink packet access (HSDPA) is devised to enable the current 3G system to accommodate more data throughput for mobile users. The three main features of the HSDPA system are the adaptive modulation and coding (AMC), the hybrid automatic repeat request (HARQ) and the fast scheduling. It would be possible to obtain the downlink speed of up to 14Mbps in HSDPA using these three features. However, the standard describes only about the specification of the Node-B, various kinds of receivers, which may have different internal structures, can be implemented. In general, the common receiver means a rake receiver. Because the equalizer can reduce the Multiple Access Interference (MAI) unlike the rake receiver, it can be an alternative to the rake receiver, especially in the HSDPA system. In this paper, we compare the performance of several equalizers for HSDPA. The simulation results provide the useful information to the receiver designers that which kind of equalizer is appropriate for their design in view of trade-off between performance and complexity.
A heuristic ant algorithm for solving QoS multicast routing problem
Authors: Chao-Hsien Chu, JunHua Gu, Qijun Gu
Venue: Proceedings of the Evolutionary Computation on 2002. CEC '02. Proceedings of the 2002 Congress - Volume 02 (2002)

In this paper, we present an ant colony-based heuristic to solve QoS (quality of service) constrained multicast routing problems. Our algorithm considers multiple QoS metrics, such as bandwidth, delay, delay jitter and packet loss rate, to find the multicast tree that minimizes the total cost. We also explore the scalability of the ant algorithm. Our tests show that the algorithm can find optimal (or near-optimal) solutions quickly and that it has good scalability.
A new method for blind source separation of nonstationary signals
Authors: D. L. Jones
Venue: Proceedings of the Acoustics, Speech, and Signal Processing, 1999. on 1999 IEEE International Conference - Volume 05 (1999)

Many algorithms for blind source separation have been introduced in the past few years, most of which assume statistically stationary sources. In many applications, such as separation of speech or fading communications signals, the sources are nonstationary. We present a new adaptive algorithm for blind source separation of nonstationary signals which relies only on the nonstationary nature of the sources to achieve separation. The algorithm is an efficient, online, stochastic gradient update based on minimizing the average squared cross-output-channel-correlations along with deviation from unity average energy in each output channel. Advantages of this algorithm over existing methods include increased computational efficiency, a simple on-line, adaptive implementation requiring only multiplications and additions, and the ability to blindly separate nonstationary sources regardless of their detailed statistical structure. 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
Efficient resource allocation scheme for real-time MPEG video traffic over ATM networks
Authors: G. Sivaradje, P. Dananjayan
Venue: Proceedings of the The 8th International Conference on Communication Systems - Volume 02 (2002)

ATM networks provide constant bit rate (CBR) services to all the variable bit rate (VBR) sources. In CBR services a fixed value of bandwidth is allocated for each connection at the peak rate. MPEG video is VBR traffic, because of the variable bandwidth requirements; there is potential bandwidth wastage with peak-rate bandwidth assignment. A method to alleviate this situation is proposed. The method dynamically allocates the spare bandwidth to frames whose frame length exceeds the negotiated value for each connection. The smaller the extra number of bandwidth units needed by the input frame, the greater is the priority for the connection to be assigned extra available bandwidth. This bandwidth algorithm when combined with the traffic smoothing technique like usage of buffers gives a good improvement in the quality of service. The benefit of this prioritized order of spare bandwidth assignment for all existing connections is that bandwidth requirements for the largest possible number of connections can be satisfied. The algorithm overcomes the bottleneck of the CBR service and the bandwidth utilization can be increased.
Performance of Switch Blocking on Multithreaded Architectures
Authors: K. Gopinath, Krishna Narasimhan M.K., B. H. Lim, Anant Agarwal
Venue: Proceedings of the 1994 International Conference on Parallel Processing - Volume 01 (1994)

Block multithreaded architectures tolerate large memory and synchronization latencies by switching contexts on every remote-memory-access or on a failed synchronization request. We study the performance of a waiting mechanism called switch-blocking where waiting threads are disabled (but not unloaded) and signalled at the completion of the wait in comparison with switch-spinning where waiting threads poll and execute in a round-robin fashion. We present an implementation of switch-blocking on a simulator for Alewife (a block multithreaded machine) for both remote memory accesses and synchronization operations and discuss results from the simulator. Our results indicate that switch-blocking has the same problems that switch-spinning has under heavy lock contention and that support for switch-blocking for remote memory accesses may not be judicious at current range of memory access times but may be so in the future due to its strong interactions with synchronization operations.
Open source software in higher education: freedom at what price?
Authors: Michael M. Behrmann
Venue:  (2007)

As institutions of Higher Education try to balance limited resources with the rising costs of technology, some institutions are turning to Open Source---software delivered with its computer program source code---for campus-wide applications such as course management systems for teaching and learning, financial systems for institution administration or portals for personalized interfaces to various software applications. The purpose of this research was to determine the extent to which institutions of Higher Education in the United States are seriously considering Open Source to construct a truly integrated learning environment serving the academic and business sides of the institution. Using a mixed methods design, the first phase of this research consisted of a Web-based survey of 772 Chief Academic Officers and Chief Information Officers about their awareness, attitudes and practices surrounding the deployment of Open Source Software. The second phase of the research consisted of 20 one-on-one depth telephone interviews among volunteers from the first phase of the research and probed for the factors informing participant thinking on Open Source, as well as reactions to a concept for providing Open Source deployment services to institutions. The results of the research indicate that Carnegie classification is a key differentiator of awareness, attitudes and adoption of Open Source Software applications, with Associate institutions the least likely to be engaged in activities related to Open Source. The results also question the scope and depth of collaboration between Chief Academic Officers and Chief Information Officers in the selection of enterprise-wide software applications for teaching and learning. Further, the results support anecdotal evidence that uncertainty about the Total Cost of Ownership is the greatest barrier to widespread adoption of Open Source Software applications. Finally, the results of this research indicate that successful adoption of Open Source Software applications requires a willingness to mitigate the support, security, quality and longevity risks associated with Open Source by investing in technology professionals---either by expanding the institution's staff or by outsourcing to commercial support providers---and by early and frequent collaboration between the institution's academic and technical constituents to advance adoption.
A new hybrid solution to boost SAT solver performance
Authors: Lei Fang, Michael S. Hsiao
Venue: Proceedings of the conference on Design, automation and test in Europe (2007)

Due to the widespread demands for efficient SAT solvers in Electronic Design Automation applications, methods to boost the performance of the SAT solver are highly desired. We propose a Hybrid Solution to boost SAT solver performance in this paper, via an integration of local and DPLL-based search approaches. A local search is used to identify a subset of clauses to be passed to a DPLL SAT solver through an incremental interface. In addition, the solution obtained by the DPLL solver on the subset of clauses is fed back to the local search solver to jump over any locally optimal points. The proposed solution is highly portable to the existing SAT solvers. For satisfiable instances, up to an order of magnitude speedup can be obtained via the proposed hybrid solver.