ppxscal/embedding_network huggingface dataset:
Discussion of Search Strategy for Multi-objective Genetic Algorithm with Consideration of Accuracy and Broadness of Pareto Optimal Solutions
Authors: Tomoyuki Hiroyasu, Masashi Nishioka, Mitsunori Miki, Hisatake Yokouchi
Venue: Proceedings of the 7th International Conference on Simulated Evolution and Learning (2008)

In multi-objective optimization, it is important that the obtained solutions are high quality regarding accuracy, uniform distribution, and broadness. Of these qualities, we focused on accuracy and broadness of the solutions and proposed a search strategy. Since it is difficult to improve both convergence and broadness of the solutions at the same time in a multi-objective GA search, we considered to converge the solutions first and then broaden them in the proposed search strategy by dividing the search into two search stages. The first stage is to improve convergence of the solutions, and a reference point specified by a decision maker is adopted in this search. In the second stage, the solutions are broadened using the Distributed Cooperation Scheme. From the results of the numerical experiment, we found that the proposed search strategy is capable of deriving broader solutions than conventional multi-objective GA with equivalent accuracy.
Sequent calculi and abstract machines
Authors: Zena M. Ariola, Aaron Bohannon, Amr Sabry
Venue: ACM Transactions on Programming Languages and Systems (TOPLAS) (2009)

We propose a sequent calculus derived from the &lambda;&horbar;&mu;&mu;&tilde;-calculus of Curien and Herbelin that is expressive enough to directly represent the fine details of program evaluation using typical abstract machines. Not only does the calculus easily encode the usual components of abstract machines such as environments and stacks, but it can also simulate the transition steps of the abstract machine with just a constant overhead. Technically this is achieved by ensuring that reduction in the calculus always happens at a bounded depth from the root of the term. We illustrate these properties by providing shallow encodings of the Krivine (call-by-name) and the CEK (call-by-value) abstract machines in the calculus.
Analyzing trust in technology strategies
Authors: Jennifer Horkoff, Eric Yu, Lin Liu
Venue: Proceedings of the 2006 International Conference on Privacy, Security and Trust: Bridge the Gap Between PST Technologies and Business Services (2006)

As technology design becomes increasingly motivated by business strategy, technology users become wary of vendor intentions. Conversely, technology producers must determine what strategies they can employ to gain the trust of consumers in order to acquire and retain their business. As a result, both parties have a need to understand how business strategies shape technology design, and how such designs alter relationships among stakeholders. In this work, we use the Trusted Computing domain as an example. Can the technology consumer trust the advertised intentions of Trusted Computing Technology? Can the providers of Trusted Computing gain the trust of consumers? We use the i* Modeling Framework to analyze the links between strategies and technologies in terms of a network of social intentional relationships. By applying the qualitative i* evaluation procedure, we probe the intentions behind the strategies of technology providers, facilitating an analysis of trust.
On Negative Unfolding in the Answer Set Semantics
Authors: Hirohisa Seki
Venue: Logic-Based Program Synthesis and Transformation: 18th International Symposium, LOPSTR 2008, Valencia, Spain, July 17-18, 2008, Revised Selected Papers (2009)

We study negative unfolding for logic programs from a viewpoint of preservation of the answer set semantics. To this end, we consider negative unfolding in terms of nested expressions by Lifschitz et al., and regard it as a combination of the replacement of a literal by its definition (called "pre-negative unfolding") and double negation elimination. We give sufficient conditions for preserving the answer set semantics. We then consider a framework for unfold/fold transformation of locally stratified programs, which, besides negative unfolding, contains replacement rules, allowing a more general form than those proposed by Pettorossi and Proietti. A new folding condition for the correctness proof is identified, which is not required either for definite or stratified programs, but becomes necessary only in case of locally stratified programs. An extension of the framework beyond the class of locally stratified programs is also discussed.
Continuous variance estimation in video surveillance sequences with high illumination changes
Authors: Pedro Gil-Jiménez, Hilario Gómez-Moreno, Javier Acevedo-Rodríguez, Saturnino Maldonado Bascón
Venue: Signal Processing (2009)

Continuous estimation of signal statistics is an important issue in many video processing systems, such as motion detection in surveillance applications. In this paper we demonstrate how results of classical expressions for variance estimation decrease in accuracy when dealing with sequences containing high illumination variations. The paper also proposes a new estimation method, and shows how, under such conditions, the accuracy of the proposed method produces better results whilst maintaining performance in scenarios with smaller changes, thus improving the motion detection stage of a video surveillance system.
Model reduction in state identification problems with an application to determination of thermal parameters
Authors: Janne M. J. Huttunen, Jari P. Kaipio
Venue: Applied Numerical Mathematics (2009)

Large-dimensional parameter estimation problems are often computationally unstable and are therefore characterized as ill-posed inverse problems. Inverse problems tolerate measurement and modelling errors poorly which usually calls for accurate computational implementations of the underlying models. These implementations often turn out to be computationally too demanding for a specific application, especially in case of time-varying problems. The so-called approximation error approach has recently been developed to cope with both modelling and numerical discretization errors. This approach has been applied to both stationary (time-invariant) and nonstationary problems. Given a fixed available computational capacity, the employment of the approximation error approach usually yields significantly better estimates than with a conventional error model. In addition, the error estimates are more feasible than with a conventional error model. In this paper we extend the previous results and provide computationally efficient forms for the extended Kalman filters for large-dimensional state identification problems. We apply the approach to the determination of distributed thermal parameters of tissue. In the measurement setting the tissue is heated with focused ultrasound and the temperature evolution is observed through magnetic resonance imaging.
Transmission Disequilibrium Test (TDT) for a pair of linked marker loci
Authors: P. Narain
Venue: Computational Statistics Data Analysis (2009)

A general theory of the Transmission Disequilibrium Test for two linked flanking marker loci used in interval mapping of a disease gene with an arbitrary mode of inheritance based on the genotypic relative risk model is presented from first principles. The expectations of all the cells in a contingency table possible with four marker haplotypes (transmitted vs. not transmitted) are derived. Although algebraic details of the six possible linkage tests are given, only the test involving doubly heterozygous parents has been considered in detail. Based on a test of symmetry of a square contingency table, chi-square tests are proposed for the null hypothesis of no linkage between the markers and the disease gene. The power of the tests is discussed in terms of the corresponding non-centrality parameters for each of the four modes of inheritance viz. additive, recessive, dominant and multiplicative. Sample sizes required for 80% power at the significance level of 0.05 have also been computed in each case. The results have been presented both for the case when the pair of markers is at the disease susceptibility locus as well as for the case when it is not so. In addition to the marker gene frequencies, recombination probabilities, and various association parameters, etc., it is found that the results depend on a composite parameter involving the genotypic relative risk of the homozygous disease genotype and the disease gene frequency instead of its constituents individually. The power increases with the decrease in the recombination probability in general but their magnitudes differ across the modes of inheritance. Additive and multiplicative modes of inheritance, in general, are found to give almost similar sample sizes. The sample sizes are found to be higher when the marker haplotype is not at the disease susceptibility locus than when the markers are there, indicating loss of power of the tests in the former case. But these are lower than the sample sizes required in the single marker case, thereby showing the superiority of the strategy in adopting the two marker loci for the transmission disequilibrium test. The use of linkage information between the markers seems to improve matters when this strategy is adapted for disease gene identification. The computations for sample sizes required for 80% power at the significance level of 5x10^-^8 used in TDT for fine mapping and genome-wide association studies indicate that the sample sizes needed could be several times larger than those for the traditional significance level of 0.05.
Optimally computing all solutions of Stackelberg with parametric prices and of general monotonous gain functions on a tree
Authors: J. Spoerhase, H. -C. Wirth
Venue: Journal of Discrete Algorithms (2009)

This paper considers Hotelling's duopoly model on a tree with parametric service prices. Two competitors, the leader and the follower, sequentially place a server in a network. Users decide for a server according to the sum of distance and server price. The goal of the competitors is to maximize their profit induced by the total demand served. Garcia and Pelegrin (2003) develop an algorithm with O(n^3logn) running time to compute the Stackelberg set, i.e., the set of all optimal leader positions. In this paper we first provide an algorithm to compute the Stackelberg set and the relaxed Simpson set with worst case running time O(n). Second we suggest an algorithm to compute the optimal set for general monotonous gain functions. Its running time is O(nlogn) and we prove that this bound is tight even for computing the security set.
Distributed similarity search in high dimensions using locality sensitive hashing
Authors: Parisa Haghani, Sebastian Michel, Karl Aberer
Venue: Proceedings of the 12th International Conference on Extending Database Technology: Advances in Database Technology (2009)

In this paper we consider distributed K-Nearest Neighbor (KNN) search and range query processing in high dimensional data. Our approach is based on Locality Sensitive Hashing (LSH) which has proven very efficient in answering KNN queries in centralized settings. We consider mappings from the multi-dimensional LSH bucket space to the linearly ordered set of peers that jointly maintain the indexed data and derive requirements to achieve high quality search results and limit the number of network accesses. We put forward two such mappings that come with these salient properties: being locality preserving so that buckets likely to hold similar data are stored on the same or neighboring peers and having a predictable output distribution to ensure fair load balancing. We show how to leverage the linearly aligned data for efficient KNN search and how to efficiently process range queries which is, to the best of our knowledge, not possible in existing LSH schemes. We show by comprehensive performance evaluations using real world data that our approach brings major performance and accuracy gains compared to state-of-the-art.
Novel Approaches for Exclusive and Continuous Fingerprint Classification
Authors: Javier A. Montoya-Zegarra, João P. Papa, Neucimar J. Leite, Ricardo Silva Torres, Alexandre X. Falcão
Venue: Proceedings of the 3rd Pacific Rim Symposium on Advances in Image and Video Technology (2009)

This paper proposes novel exclusive and continuous approaches to guide the search and the retrieval in fingerprint image databases. Both approaches are useful to perform a coarse level classification of fingerprint images before fingerprint authentication tasks. Our approaches are characterized by: (1) texture image descriptors based on pairs of multi-resolution decomposition methods that encode effectively global and local fingerprint information, with similarity measures used for fingerprint matching purposes, and (2) a novel multi-class object recognition method based on the Optimum Path Forest classifier. Experiments were carried out on the standard NIST-4 dataset aiming to study the discriminative and scalability capabilities of our approaches. The high classification rates allow us demonstrate the feasibility and validity of our approaches for characterizing fingerprint images accurately.
On self-selected pairing in CS1: who pairs with whom?
Authors: Vincent A. Cicirello
Venue: Journal of Computing Sciences in Colleges (2009)

In recent years, we have seen an increased use of pair programming in CS-1 courses. Widespread evidence shows pair programming as beneficial at all levels of programming skill. During three academic years, we studied what students in CS-1 choose when given the option to either pair program or to program independently. We explore which students choose to pair and how often, and examine the majors and academic years of the self-selected pairs. Among our objectives is to learn about student pair preferences to help guide the assignment of partners when mandatory pair programming is used. We show that Math majors are more likely than Computer Science/Information Systems (CS/IS) majors to prefer pair programming in CS-1. Math majors prefer pairing with Math majors. CS/IS majors more often choose to pair with non-majors, perhaps indicating self-chosen mentoring roles.
MIC(0) preconditioning of 3D FEM problems on unstructured grids: Conforming and non-conforming elements
Authors: Svetozar Margenov, Nikola Kosturski
Venue: Journal of Computational and Applied Mathematics (2009)

In this study, the topics of grid generation and FEM applications are studied together following their natural synergy. We consider the following three tetrahedral grid generators: NETGEN, TetGen, and Gmsh. After that, the performance of the MIC(0) preconditioned conjugate gradient (PCG) solver is analyzed for both conforming and non-conforming linear FEM problems. If positive off-diagonal entries appear in the corresponding matrix, a diagonal compensation is applied to get an auxiliary M-matrix allowing a stable MIC(0) factorization. The presented numerical experiments for elliptic and parabolic problems well illustrate the similar PCG convergence rate of the MIC(0) preconditioner for both, structured and unstructured grids.
Quantitative measures of MIS quality assurance during hardware conversion
Authors: John W. Center
Venue: Proceedings of the May 4-7, 1981, national computer conference (1981)

The management information systems (MIS) department of Medtronic converted their applications from running on the computer of one hardware vendor to another. A quality assurance (QA) program was instituted to monitor, validate, and assist in the conversion process. Several quantitative measures were developed to determine the status and progress of the conversion from the QA viewpoint. Objective measures included learning curve position, rejection delay, and costs. Subjective measures included problem solution impact, confidence of conversion personnel, and confidence of management. Analysis and evaluation of the measures indicated that the QA program was able to pay for itself.
A class-based scheme for E-commerce web servers: Formal specification and performance evaluation
Authors: D. R. W. Holton, I. Nafea, M. Younas, I. Awan
Venue: Journal of Network and Computer Applications (2009)

This paper is an investigation into the performance of E-commerce applications. E-commerce has become one of the most popular applications of the web as a large population of web users is now benefiting from various on-line services including product searches, product purchases and product comparison. E-commerce provides users with 24-7 shopping facilities. However, the consequence of these benefits and facilities is the excessive load on E-commerce web servers and the performance degradation of E-commerce (eCom) requests they process. This paper addresses this issue and proposes a class-based priority scheme which classifies eCom requests into high and low priority requests. In E-commerce, some requests (e.g. payment) are generally considered more important than others (e.g. search or browse). We believe that by assigning class-based priorities at multiple service levels, E-commerce web servers can perform better and can improve the performance of high priority eCom requests. In this paper, we formally specify and implement the proposed scheme and evaluate its performance using multiple servers. Experimental results demonstrate that the proposed scheme significantly improves the performance of high priority eCom requests.
Low-temperature preparation of amorphous-shell/nanocrystalline-core nanostructured TiO2electrodes for flexible dye-sensitized solar cells
Authors: Dongshe Zhang, Hengyao Hu, Laifeng Li, Donglu Shi
Venue: Journal of Nanomaterials (2008)

An amorphous shell/nanocrystalline core nanostructured TiO2 electrode was prepared at low temperature, in which the mixture of TiO2 powder and TiCl4 aqueous solution was used as the paste for coating a film and in this film amorphous TiO2 resulted from direct hydrolysis of TiCl4 at 100°C sintering was produced to connect the particles forming a thick crack-free uniform nanostructured TiO2 film (12 µm), and on which a photoelectrochemical solar cell-based was fabricated, generating a short-circuit photocurrent density of 13.58mA/cm2, an open-circuit voltage of 0.647 V, and an overall 4.48% light-to-electricity conversion efficiency under 1 sun illumination.
Simple games and weighted games: A theoretical and computational viewpoint
Authors: Josep Freixas, Xavier Molinero
Venue: Discrete Applied Mathematics (2009)

It is a well-known result in the theory of simple games that a game is weighted if and only if it is trade robust. In this paper we propose a variant of trade robustness, that we call invariant-trade robustness, which is enough to determine whether a simple game is weighted. To test whether a simple game is invariant-trade robust we do not need to consider all winning coalitions; a reduced subset of minimal winning coalitions is enough. We make a comparison between the two methods (trade robustness and invariant-trade robustness) to check whether a simple game is weighted. We also provide by means of algorithms a full classification using both methods, for simple games with less than 8 voters according to the maximum level of (invariant-)trade robustness they achieve.
The Modeling and the Sensor Fault Diagnosis of a Continuous Stirred Tank Reactor with a Takagi-Sugeno Recurrent Fuzzy Neural Network
Authors: Li Shi, Lijia Wang, Zhizhong Wang
Venue: International Journal of Distributed Sensor Networks (2009)

In this paper, a novel Takagi-Sugeno recurrent fuzzy neural network (TSRFNN) is constructed for modeling and sensor fault diagnosis of a Continuous Stirred Tank Reactor (CSTR), a nonlinear dynamic system. The TSRFNN is composed of 9 layers, including premise network and consequence network. The temporal information is embedded in the TSRFNN by adding the feedback connections between the output layer and the input layer of the fuzzy neural network (FNN). It is assumed that the inputs are Gaussian membership functions; the product operation is utilized for the premise and implication, and the weighted center-average method is adopted for defuzzification. The network is a Fuzzy Basis Function(FBF). The general approximation characteristic of the network was proven by the theory reasoning. The identification of the TSRFNN consists of two steps: structure identification and parameter identification. Unsupervised clustering is used to determine the structure of the fuzzy system, the number of fuzzy rules, and the membership functions of the premise using the input-output data of a system. Then in the parameter identification, the Dynamic Backpropagation (DBP) is adopted to determine the membership functions of the conclusion of the fuzzy system. Then the network is applied to the modeling and diagnosis of a CSTR system. The network is applied to set up the sensors models of a CSTR system, including the models of the temperature sensor faults and the models of concentration sensor faults. To set up a high performance diagnosis model, a persistent signal was chosen to sufficiently activate the plant. Finally an Adaptive Threshold Algorithm based on statistics is used to fault diagnose. If there are sensor faults in the CSTR, the bias between the actual output of the plant and the output of the network surpasses the threshold and the faults are detected on-line according to it. The effectiveness of the modeling and diagnosis approach proposed was verified by the simulation results with Matlab. Therefore, the proposed network and the fault diagnosis approach can be employed to a CSTR system successfully and be extended to the modeling and fault detection of other nonlinear systems.
Deformation Techniques for Sparse Systems
Authors: Gabriela Jeronimo, Guillermo Matera, Pablo Solern&#x00f3;, Ariel Waissbein
Venue: Foundations of Computational Mathematics (2009)

We exhibit a probabilistic symbolic algorithm for solving zero-dimensional sparse systems. Our algorithm combines a symbolic homotopy procedure, based on a flat deformation of a certain morphism of affine varieties, with the polyhedral deformation of Huber and Sturmfels. The complexity of our algorithm is cubic in the size of the combinatorial structure of the input system. This size is mainly represented by the cardinality and mixed volume of Newton polytopes of the input polynomials and an arithmetic analogue of the mixed volume associated to the deformations under consideration.
Integrating Thermodynamic and Observed-Frequency Data for Non-coding RNA Gene Search
Authors: Scott F. Smith, Kay C. Wiese
Venue: Transactions on Computational Systems Biology X (2008)

Among the most powerful and commonly used methods for finding new members of non-coding RNA gene families in genomic data are covariance models. The parameters of these models are estimated from the observed position-specific frequencies of insertions, deletions, and mutations in a multiple alignment of known non-coding RNA family members. Since the vast majority of positions in the multiple alignment have no observed changes, yet there is no reason to rule them out, some form of prior is applied to the estimate. Currently, observed-frequency priors are generated from non-family members based on model node type and child node type allowing for some differentiation between priors for loops versus helices and between internal segments of structures and edges of structures. In this work it is shown that parameter estimates might be improved when thermodynamic data is combined with the consensus structure/sequence and observed-frequency priors to create more realistic position-specific priors.