ppxscal/embedding_network huggingface dataset:
The importance of a match in a tournament
Authors: Philip A. Scarf, Xin Shi
Venue: Computers and Operations Research (2008)

A quantitative measure of ''match importance'' is useful in a number of decision problems, for example: as a metric in tournament design; for selecting matches for broadcasting; for scheduling matches in a tournament; and for assigning referees. To date measures of match importance used in such analyses have been relatively naive. We discuss a general measure that considers the effect of a particular match on the end of tournament position, given the results of all other matches, some played, some predicted. We use logistic regression to predict matches and Monte Carlo simulation to compute the match importance measure, and apply these to soccer matches in the English Football Association Premier League.
Modeling of Switched Reluctance Motor Based on GA Optimized T-S Type Fuzzy Logic
Authors: Jie Xiu, Chang-Liang Xia
Venue: Proceedings of the Fourth International Conference on Fuzzy Systems and Knowledge Discovery - Volume 04 (2007)

Flux linkage of switch reluctance motor (SRM) is in nonlinear function of both rotor position and phase current. Establishing this nonlinear mapping is the basis of computing the mathematical equations of SRM accurately. In this paper, the Takagi-Sugeno (T-S) type fuzzy logic is employed to develop the nonlinear model of SRM. By taking advantage of the benefit of T-S type fuzzy logic inference, the T-S type fuzzy logic based model of SRM has a simple structure, less training epoch, fast computational speed and characteristics of robustness. In order to get a high precision, the parameters of T-S type fuzzy logic based model of SRM should be optimized. For there is no derivative information available, the conventional optimal method, such as steepest gradient decent optimization method, is hard to be used to optimize the parameters of the T-S type fuzzy logic. In this paper, genetic algorithm (GA) is used to optimize the parameters of the proposed model. GA is an optimization technique that performs a parallel, stochastic, but directed search to evolve the most fit population and it do not relay on computing local derivatives to guide the search process. Compared with the training data and generalization test data, the output data of the developed model are in good agreement with those data. The simulated current wave is also in good agreement with the measured current wave. This proves that the model developed in this paper has high accuracy, strong generalization ability, fast computation speed and characteristics of robustness.
Speech and Song Search on the Web: System Design and Implementation
Authors: Yuichi Yaguchi, Yoshiyuki Watanabe, Keitaro Naruse, Ryuichi Oka
Venue: Proceedings of the 7th IEEE International Conference on Computer and Information Technology (2007)

This paper proposes a novel search system for speech and song segments. The amount of accumulated video data in the World Wide Web is expanding and its content is varied. Video content includes natural voices and singing voices, and these differ in their phoneme lengths. Our system uses frame-wise phoneme recognition and Continuous Dynamic Programming (CDP). First, each target and query waveform is divided into fixed short-time frames; second, each frame of the waveform is used to estimate a phoneme label using Bayes estimation; third, the query sequences of phoneme labels are searched from target sequences by time-robustness CDP; and, finally, this system gets candidate answers. This method is robust along the time dimension, and thus has a great advantage for natural voice as well as song. This paper also introduces an implementation of this system, which is published on the Web, as a secondary search engine for Youtube data.
Principles of Program Design Induced from Experience with Small Public Programs
Authors: D. Comer
Venue: IEEE Transactions on Software Engineering (1981)

The art of programming is taught, learned, and often practiced as if programs are disposable, personal objects owned, solely by the programmer. This paper uses examples to illustrate why real software is neither personal nor disposable; it shows how even simple programs are shared by others. From the examples, the paper extracts four principles for program development. Finally, it draws conclusions about programming practices and the education of programmers.
A mean–variance bound for a three-piece linear function
Authors: Karthik Natarajan, Zhou Linyi
Venue: Probability in the Engineering and Informational Sciences (2007)

In this article, we derive a tight closed-form upper bound on the expected value of a three-piece linear convex function E[max(0, X, mX − z)] given the mean μ and the variance σ2 of the random variable X. The bound is an extension of the well-known mean–variance bound for E[max(0, X)]. An application of the bound to price the strangle option in finance is provided.
Partial-Disjoint Multipath Routing for Wireless Ad-hoc Networks
Authors: Haseeb Zafar, David Harle, Ivan Andonovic, Mahmood Ashraf
Venue: Proceedings of the 32nd IEEE Conference on Local Computer Networks (2007)

On-demand multipath routing in wireless ad-hoc networks can be effective in achieving load balancing over the network and in providing a degree of resilience to route failures. A Shortest Multipath Source Routing (SMS) protocol is proposed - a multipath extension to DSR - supporting multimedia applications. The protocol has two novel aspects compared to other on-demand multipath routing protocols: it achieves shorter multiple partial-disjoint paths and allows rapid recovery of route breaks Simulation results show that SMS outperforms the competing protocols with respect to a number of key performance metrics.
Preference Articulation in Evolutionary Multiobjective Optimisation
Authors: Carlos M. Fonseca
Venue: Proceedings of the 7th International Conference on Hybrid Intelligent Systems (2007)

Real-world optimisation problems often involve a number of conflicting criteria, or objectives. Such problems usually admit multiple Pareto-optimal solutions, i.e. solutions, which cannot be improved upon in all objectives simultaneously. In practice, however, acceptable solutions must perform sufficiently well with respect to all objectives, which means that not all Pareto-optimal solutions may be satisfactory. Evolutionary approaches to multiobjective optimisation have concentrated mainly on the task of approximating the set of Pareto-optimal solutions of a given problem as well as possible, by generating diverse sets of non-dominated alternatives. Subjective information concerning how different combinations of objective values influence the relative quality of a solution is not required, but this approach tends to become impractical as the number of objectives grows. In practice, however, there are many situations in which such preference information is either available a priori or may be acquired during the initial steps of an optimisation run, even if not in a complete form. Incorporating preference information in evolutionary multiobjective optimisation (EMO) algorithms allows the search to concentrate on, and to better approximate, the relevant regions of the Pareto-optimal front. In this talk, a number of ways in which preference information may be combined with evolutionary search, in order to improve the relevance and the quality of the optimisation results will be discussed, and application examples will be presented. Important aspects of the discussion will include the form in which preference information is initially available, the impact of preference articulation techniques on the optimisation problems to be solved, the quality of the final solutions obtained, and user-related issues, such as visualisation and interaction. The talk will conclude with the identification of some opportunities for future work.
Slow messaging: intimate communication for couples living at a distance
Authors: Simon King, Jodi Forlizzi
Venue: Proceedings of the 2007 conference on Designing pleasurable products and interfaces (2007)

Technology increasingly mediates communication between people, particularly when they live at a distance. For couples in long-distance relationships, these technologies are a primary means of exchanging not only information but also emotions. This one-year project explores the communication needs of couples living at a distance to design an intimate and emotional means of interaction specifically for this context. A user-centered design process revealed opportunities for interactions that show time and effort or those that connect people through a shared sense of place. These observed needs were used to develop concepts which where validated by representative users.
Finite element analysis of welded beam-to-column joints in aluminium alloy EN AW 6082 T6
Authors: T. Wang, O. S. Hopperstad, O. -G. Lademo, P. K. Larsen
Venue: Finite Elements in Analysis and Design (2007)

Shell elements are used to model welded beam-to-column joints in alloy EN AW 6082 T6, and the results are compared with experimental data from the literature. The textured alloy is modelled using an anisotropic plasticity model and the inhomogeneous work-hardening properties of the heat-affected zone (HAZ) are accounted for in the material modelling. In order to represent the geometry as accurately as possible, a varying thickness of the shell elements is used in the various parts of the joints. It is found that the numerical results are strongly mesh dependent. To obtain reliable results for both strength and ductility, it is proposed to introduce non-local plastic thinning in the HAZ. This procedure reduces the mesh dependence of the strain localization, at the cost of introducing one additional parameter, namely the radius of the non-local domain.
Webquest improvement of the chemical equilibrium study
Authors: Carla Susana Lopes Morais, João C. Paiva, José Luis Silva Barros
Venue: Proceedings of the sixth conference on IASTED International Conference Web-Based Education - Volume 2 (2007)

The study of Chemical Equilibrium is a central and inevitable point for knowledge acquiring in Chemistry. However, it is here where students do present more alternative conceptions becoming more difficult for them to understand it and thus a great challenge for the teaching. As something abstract, that includes non observable events, multiple factors, advanced reasoning and complex microscopic interpretation, this is one of the topics in the Chemistry curriculum that appeals more to the use of computational simulations for its teaching. We have carried out studies using a computer programme for the teaching of chemical equilibrium which confirm the usefulness of these digital tools. Computational simulations are very useful and rich context educational resources. Webquests may be supporting material in the exploration of a computational simulation: they are a kind of an "exploration guide" and at the same time a way of creating students' nearby contexts. There are several advantages that come from the use of this work dynamic using the Web.
Genetic forma recombination in permutation flowshop problems
Authors: Carlos Cotta, José M. Troya
Venue: Evolutionary Computation (1998)

This paper analyzes different representations for permutation flowshop problems. This is done using forma analysis to assess the quality of these representations with respect to makespan optimization. Classical recombination operators are studied and empirically evaluated in this context. It is shown that the best operators work on representations in which absolute positions of tasks are relevant. Subsequently, some new operators operating on these representations are proposed. These new operators are designed to exhibit specific properties regarding implicit mutation and forma transmission. Their performance is shown to be competitive with traditional operators.
Development and evaluation of a foreign-word learning system by iPods
Authors: Satoko Amemiya, Kazunori Hasegawa, Keiichi Kaneko, Haruko Miyakoda, Wataru Tsukahara
Venue: Proceedings of the sixth conference on IASTED International Conference Web-Based Education - Volume 2 (2007)

In learning the vocabulary of a foreign language, it is effective to increase the time and frequency of learning the novel words. Hence, in our study, we developed a foreign-word learning system based on a popular mobile device, the iPod, that enables its users to make good use of his/her free time. Compared to other mobile devices, the iPod has a larger storage capacity. Furthermore, the user can easily replay the moving image files. These advantages can be put to good use in language learning. In our system, the users first select the foreign words that they want to learn using their personal computers, then download the corresponding contents into their iPods. The contents that are downloaded into the iPod consist of the pronunciation of each word together with a series of either still or moving images corresponding to these foreign words. In addition, we conducted an evaluation experiment in which we compared the learning method based on our system against the conventional paper-and pencil method. The result indicated that the method based on our system showed as 1.5 times as better ratio of memorization after two weeks, thus verifying the effectiveness of our system.
Study on Chaos Immune Network Algorithm for Multimodal Function Optimization
Authors: Jia Lv
Venue: Proceedings of the Fourth International Conference on Fuzzy Systems and Knowledge Discovery - Volume 03 (2007)

Multimodal function optimization problem, which requires finding out the global optimum and the utmost number of local optima, has important applications in the field of engineering. When solving multimodal function optimization problem with artificial immune network algorithm, problems such as premature convergence phenomena and unsatisfying searching precision may arise. Under such circumstances, improved chaos immune network algorithm was put forward in this paper. In the improved algorithm, the stopping criterion was improved and some relevant measures taken to avoid premature convergence; and chaos variable was used to simulate proliferation mode of immune cells to enhance searching precision. Based on simulation tests on some benchmark functions, conclusions were drawn that this algorithm can fast optimize the antibodies, strengthen the searching ability and enhance the searching precision. Index Terms: Multimodal function optimization, artificial immune network algorithm, chaos immune network algorithm
Voltage-mode driver preemphasis technique for on-chip global buses
Authors: Liang Zhang, John M. Wilson, Rizwan Bashirullah, Lei Luo, Jian Xu, Paul D. Franzon
Venue: IEEE Transactions on Very Large Scale Integration (VLSI) Systems (2007)

This paper demonstrates that driver preemphasis technique can be used for on-chip global buses to increase signal channel bandwidth. Compared to conventional repeater insertion techniques, driver preemphasis saves repeater layout complexity and reduces power consumption by 12%-39% for data activity factors above 0.1. A driver circuit architecture using voltage-mode preemphasis technique was tested in 0.18-µm CMOS technology for 10-mm long interconnects at 2 Gb/s.
CountTorrent: ubiquitous access to query aggregates in dynamic and mobile sensor networks
Authors: Abhinav Kamra, Vishal Misra, Dan Rubenstein
Venue: Proceedings of the 5th international conference on Embedded networked sensor systems (2007)

We study the problem of aggregate querying over sensor networks where the network topology is continuously evolving. We develop scalable data aggregation techniques that remain efficient and accurate even as nodes move, join or leave the network. We present a novel distributed algorithm called CountTorrent, that enables fast estimation of certain classes of aggregate queries such as COUNT and SUM. CountTorrent does not require a static routing infrastructure, is easily implemented in a distributed setting, and can be used to inform all network nodes of the aggregate query result, instead of just the query initiator as is done in traditional query aggregation schemes. We evaluate its robustness and accuracy compared to previous aggregation approaches through simulations of dynamic and mobile sensor network environments and experiments on micaz motes. We show that in networks where the nodes are stationary, CountTorrent can provide 100% accurate aggregate results even in the presence of lossy links. In mobile sensor networks where the nodes constantly move and hence the network topology changes continuously, CountTorrent provides a close (within 10 -- 20%) estimate of the accurate aggregate query value to all nodes in the network at all times.
Visualization of Cosmological Particle-Based Datasets
Authors: Paul Navratil
Venue: IEEE Transactions on Visualization and Computer Graphics (2007)

We describe our visualization process for a particle-based simulation of the formation of the first stars and their impact on cosmic history. The dataset consists of several hundred time-steps of point simulation data, with each time-step containing approximately two million point particles. For each time-step, we interpolate the point data onto a regular grid using a method taken from the radiance estimate of photon mapping. We import the resulting regular grid representation into ParaView, with which we extract isosurfaces across multiple variables. Our images provide insights into the evolution of the early universe, tracing the cosmic transition from an initially homogeneous state to one of increasing complexity. Specifically, our visualizations capture the build-up of regions of ionized gas around the first stars, their evolution, and their complex interactions with the surrounding matter. These observations will guide the upcoming James Webb Space Telescope, the key astronomy mission of the next decade.
Selecting and Implementing a Turnkey Graphics System
Authors: F. W. Bliss
Venue: IEEE Computer Graphics and Applications (1981)

If carefully planned for and managed, turnkey graphics can boost the productivity of design and drafting departments.
Assessment on Fault-tolerance Performance Using Neural Network Model Based on Ant Colony Optimization Algorithm for Fault Diagnosis in Distribution Systems of Electric Power Systems
Authors: Zhisheng Zhang, Yaming Sun
Venue: Proceedings of the Eighth ACIS International Conference on Software Engineering, Artificial Intelligence, Networking, and Parallel/Distributed Computing - Volume 02 (2007)

This paper presents a model based on neural network optimized by the ant colony optimization algorithm (ACOA) for fault section diagnosis in distribution systems of electric power systems, and the simulation results show that it can effectively improve the fault-tolerance ability of fault section diagnosis. It had better fault-tolerance ability in contrast with the BP-NN model and the DGA-NN model. It must be pointed out that the improvement degree is correlative with the space distribution of samples, and it isn't the essential improvement, but it is the potential mining of neural network.
Software Quality Assurance for Maintenance
Authors: J. S. Collofello
Venue: IEEE Software (1987)

Maintenance plays a vital role in protecting quality as a system evolves. The results of this study pinpoit this study pinpoint how to make maintenance a part of SQA.
Analysis and optimization of service availability in a HA cluster with load-dependent machine availability
Authors: Chee-Wei Ang, Chen-Khong Tham
Venue: IEEE Transactions on Parallel and Distributed Systems (2007)

Calculations of service availability of a High- Availability (HA) cluster are usually based on the assumption of load-independent machine availabilities. In this paper, we study the issues and show how the service availabilities can be calculated under the assumption that machine availabilities are load-dependent. we present a Markov chain analysis to derive the steady-state service availabilities of a load-dependentmachine- availability HA cluster. We show that, with loaddependent machine-availability, the attained service availability is now policy-dependent. After formulating the problem as a Markov Decision Process, we proceed to determine the optimal policy to achieve the maximum service availabilities using the method of policy iteration. Two greedy assignment algorithms are studied: least-load and FDL-based, where leastload corresponds to some load-balancing algorithms.We carry out analysis and simulations on two cases of load profiles: in the first profile, a single machine has the capacity to host all services in the HA cluster; in the second profile, a single machine does not have enough capacity to host all services. We show that the service availabilities achieved under the first load profile are the same, while the service availabilities achieved under the second load profile are different. Since the service availabilities achieved are different in the second load profile, we proceed to investigate how the distribution of service availabilities across the services can be controlled by adjusting the rewards vector.
A Novel Complex Orthogonal Design for Space---Time Coding in Sensor Networks
Authors: Tai-Kuo Woo
Venue: Wireless Personal Communications: An International Journal (2007)

In this paper, we propose a complex orthogonal design based on the theory of Finite projective plane. As most of the orthogonal designs incur low ratio of time diversity, the proposed complex orthogonal design has a relatively high ratio of time diversity. In addition, the proposed scheme has the following characteristics: (1) full spatial diversity (2) low rate $$({\leq}\frac{1}{3})$$ (3) linear processing. We compare the proposed scheme with another complex design to show the tradeoffs. The proposed scheme can be of use for certain applications such as sensor networks and deep space exploration where there might be an imposed limit on the peak transmit power.
Reduced bootstrap aggregating of learning algorithms
Authors: Rafael Pino-Mejías, María-Dolores Jiménez-Gamero, María-Dolores Cubiles-de-la-Vega, Antonio Pascual-Acosta
Venue: Pattern Recognition Letters (2008)

Bagging is based on the combination of models fitted to bootstrap samples of a training data set. There is considerable evidence that such ensemble method can significantly reduce the variance of the prediction model. However, several techniques have been proposed to achieve a variance reduction in the proper bootstrap resampling process, as in our reduced bootstrap methodology, where the generated bootstrap samples are forced to have a number of distinct original observations between two appropriate values k"1 and k"2. In this paper, we first describe the reduced bootstrap and consider possible values for k"1 and k"2. Secondly, we propose to employ the reduced bootstrap for bagging unstable learning algorithms as decision trees and neural networks. An empirical comparison over classification and regression problems shows a tendency to reduce the variance of the test error. We have also performed a theoretical analysis for learning algorithms that can be approximated by a quadratic expansion, obtaining expressions for the relative gain in efficiency for the reduced bootstrap aggregating procedure.
A Data Collection Algorithm Using Energy Maps in Sensor Networks
Authors: Abdelmorhit El Rhazi, Samuel Pierre
Venue: Proceedings of the Third IEEE International Conference on Wireless and Mobile Computing, Networking and Communications (2007)

The main challenge when deploying sensor networks pertains to optimizing the energy consumption for data collection from sensor nodes. This paper proposes a new data collection mechanism based on a distributed clustering method. It uses sensor network energy maps and applies QoS requirements in order to reduce energy consumption. Simulation results show that this new data collection algorithm consumes less energy than the TAG algorithm.