ppxscal/embedding_network huggingface dataset:
Signal reshaping using dominant harmonic for pitch estimation of noisy speech
Authors: Md. Kamrul Hasan, Shahed Hussain, M. T. Hossain Setu, Md. N. Ibne Nazrul
Venue: Signal Processing (2006)

A simple yet powerful method for pitch estimation of noisy speech is presented in this paper. The basic idea is to use the rectified dominant harmonic for signal reshaping. The main advantage of using the reshaped signal is the enhanced pitch peak as compared to other non-pitch peaks. The normalized autocorrelation function of the processed speech is used for pitch extraction. The performance of the proposed method is tested and compared with those of recent methods using the Keele pitch extraction reference database. Comparative results show that the proposed method can detect pitch with better accuracy in terms of gross and fine pitch errors as compared to other reported techniques.
Enhancing the Dependability of Human-Machine Systems Using Brunswikian Symmetry
Authors: Meike Jipp, Essameddin Badreddin
Venue: Proceedings of the International Conference on Computational Inteligence for Modelling Control and Automation and International Conference on Intelligent Agents Web Technologies and International Commerce (2006)

Brunswikian theory and the symmetry principle of information accessibility and processing are introduced to analyze the interaction between a technical system and their users on the example of an intelligent expert help system for a photocopy machine. To improve the interaction and thus to increase the system's dependability, symmetry must be achieved in information accessibility and processing by generalizing the design-by-contract approach to human-machine interaction. Balancing asymmetry will enable more dependable man-machine systems.
Linguistic group decision-making: opinion aggregation and measures of consensus
Authors: D. Ben-Arieh, Z. Chen
Venue: Fuzzy Optimization and Decision Making (2006)

Group decision-making is a crucial activity, necessary in many aspects of our civilization. In many cases, due to inherent complexity, experts cannot express their opinion or preferences using exact numbers, thus resorting to a qualitative preference such as linguistic labels. Another complicating factor is the fact that very seldom all individuals in a group share the same opinion about the alternatives. This creates the need to aggregate all the differing individual opinions into a group opinion. Moreover, it is desirable to be able to assess the level of agreement among the experts; termed consensus. This paper presents a methodology for aggregating experts' judgements, presented as linguistic labels, into a group opinion with a measure of the group consensus. The aggregation model allows weighted experts to express a degree of optimism or upward bias in their opinions. Then the paper presents two models of calculating the consensus based on the individual expert opinions and the group aggregated opinion.
From HTTP to HTML: Erlang/OTP experiences in web based service applications
Authors: Francesco Cesarini, Lukas Larsson, Michal Ślaski
Venue: Proceedings of the 2006 ACM SIGPLAN workshop on Erlang (2006)

This paper describes the lessons learnt when internally developing web applications in Erlang. On the basis of these experiences, a framework called the Web Platform has been implemented. The Web Platform follows a design pattern separating data processing and formatting, allowing the construction of flexible and maintainable software architectures. It also delivers mechanisms for building dynamic pages and components. On top of the platform and components, web interfaces to commercial Erlang systems have been built.
Global and Componentwise Extrapolation for Accelerating Data Mining from Large Incomplete Data Sets with the EM Algorithm
Authors: Chun-Nan Hsu, Han-Shen Huang, Bo-Hou Yang
Venue: Proceedings of the Sixth International Conference on Data Mining (2006)

The Expectation-Maximization (EM) algorithm is one of the most popular algorithms for data mining from incomplete data. However, when applied to large data sets with a large proportion of missing data, the EM algorithm may converge slowly. The triple jump extrapolation method can effectively accelerate the EM algorithm by substantially reducing the number of iterations required for EM to converge. There are two options for the triple jump method, global extrapolation (TJEM) and componentwise extrapolation (CTJEM). We tried these two methods for a variety of probabilistic models and found that in general, global extraplolation yields a better performance, but there are cases where componentwise extrapolation yields very high speedup. In this paper, we investigate when componentwise extrapolation should be preferred. We conclude that, when the Jacobian of the EM mapping is diagonal or block diagonal, CTJEM should be preferred. We show how to determine whether a Jacobian is diagonal or block diagonal and experimentally confirm our claim. In particular, we show that CTJEM is especially effective for the semi-supervised Bayesian classifier model given a highly sparse data set.
Instruction-coated translation: an approach to restructure directly threaded interpreters with low cohesion
Authors: Fuh-Gwo Chen, Ting-Wei Hou
Venue: ACM SIGPLAN Notices (2006)

A directly threaded interpreter is used to speedup the virtual instruction dispatch. It is composed of translation and interpretation functions. It has low cohesion naturally due to the use of "label as value". This paper presents a restructuring method to envelop the translation function as a new virtual instruction to make the directly threaded interpreter have a single interpreting task and have high cohesion. The reformed translation is named as the instruction-coated translation, a term similar to sugar-coated tablet.
Which Reference View is Effective for Gait Identification Using a View Transformation Model?
Authors: Yasushi Makihara, Ryusuke Sagawa, Yasuhiro Mukaigawa, Tomio Echigo, Yasushi Yagi
Venue: Proceedings of the 2006 Conference on Computer Vision and Pattern Recognition Workshop (2006)

Gait identification is a promising method of individual identification at a distance from a camera and identification of those who observed from various views or those who going to various directions is required in particular for actual use. In this paper, we discuss a selection of reference views for the various-view gait identification using a view transformation model (VTM). In the gait identification process, we first extract frequency-domain gait features from gait silhouette sequences, and then obtain the various-view gait features by transforming a few reference features with the VTM. We made experiments using 736 sequences from 20 subjects of 24 view directions. We evaluate the performance for each single reference and for each combination of two references. In addition, we inspect the relation between the performance and the number of references.
Detection for MIMO systems with imprecise channel knowledge
Authors: Yunnan Wu, S. Y. Kung
Venue: Proceedings of the 2003 International Conference on Multimedia and Expo - Volume 1 (2003)

In this work, we investigate the signal detection for MIMO systems with imprecise channel knowledge. The optimal detector is one which best matches the "total" observation matrix and a "total" signal matrix which has a finite alphabet constraint and a Sylvester structure constraint. An iterative local optimization with interference cancellation (LOIC) algorithm is proposed to achieve low complexity and exploit the finite alphabet constraint. Simulation results show that our proposed algorithms can detect the signals with BER close to the case of perfect channel knowledge, if a rough channel estimate is available initially.
Linearly Constrained Global Optimization and Stochastic Differential Equations
Authors: Panos Parpas, Berç Rustem, Efstratios N. Pistikopoulos
Venue: Journal of Global Optimization (2006)

A stochastic algorithm is proposed for the global optimization of nonconvex functions subject to linear constraints. Our method follows the trajectory of an appropriately defined Stochastic Differential Equation (SDE). The feasible set is assumed to be comprised of linear equality constraints, and possibly box constraints. Feasibility of the trajectory is achieved by projecting its dynamics onto the set defined by the linear equality constraints. A barrier term is used for the purpose of forcing the trajectory to stay within the box constraints. Using Laplace's method we give a characterization of a probability measure (¿) that is defined on the set of global minima of the problem. We then study the transition density associated with the projected diffusion process and show that its weak limit is given by ¿. Numerical experiments using standard test problems from the literature are reported. Our results suggest that the method is robust and applicable to large-scale problems.
MUDABlue: an automatic categorization system for open source repositories
Authors: Shinji Kawaguchi, Pankaj K. Garg, Makoto Matsushita, Katsuro Inoue
Venue: Journal of Systems and Software (2006)

Open Source communities typically use a software repository to archive various software projects with their source code, mailing list discussions, documentation, bug reports, and so forth. For example, SourceForge currently hosts over seventy thousand Open Source software systems. Because of the size of the rich information content, such repositories offer numerous opportunities for sharing information among projects. For example, one would like to know a set of projects that are related or similar to each other, so that the project groups can collaborate and share their work. With thousands of projects in typical repositories, however, manually locating related projects can be difficult. Hence, we propose MUDABlue, a tool that automatically categorizes software systems. MUDABlue has three major aspects: (1) it relies on no other information than the source code, (2) it determines category sets automatically, and (3) it allows a software system to be a member of multiple categories. MUDABlue has a Web interface to visualize determined categories, which eases browsing a software repository. We show the effectiveness of MUDABlue's categorization capability by comparing its generated categories with that of some other existing research tools.
Simulation data mining: a new form of computer simulation output
Authors: Thomas F. Brady, Edward Yellig
Venue: Proceedings of the 37th conference on Winter simulation (2005)

The objective of simulation modeling is to gain insight into the dynamics of complex systems. Simulation models of complex systems consist of numerous input variable, linked together by logical relationships. The process of determining the set of input variable values that produce the optima output has often posed the greatest challenge during simulation studies. In recent years, the ability to integrate optimization technology into simulation models has significantly improved this process. To effectively utilize optimization technology, however, modelers must define optimization variables. In this paper, an approach is developed that provides information concerning the interrelationship between input variables used in a simulation model. This information can then be used as the basis for selecting optimization variables.
On the representation of linear system time-varying half-line maps: Research Articles
Authors: Irwin W. Sandberg
Venue: International Journal of Circuit Theory and Applications (2006)

An expression is given for the most general continuous causal linear input&ndash;output map that takes the space of (Lebesgue) integrable functions into itself. This expression is a function-space limit of an integral. As an application, a representation result is given for an important family of linear maps that take the space of bounded measurable functions into itself and satisfy a certain continuity condition. Some related material concerning engineering education is also given. Copyright &copy; 2006 John Wiley & Sons, Ltd.
Assessing the Usability of a Tool for Developing Adaptive E-learning Processes: an Empirical Analysis
Authors: Gennaro Costagliola, Andrea De Lucia, Filomena Ferrucci, Carmine Gravino, Giuseppe Scanniello
Venue: Proceedings of the Sixth IEEE International Conference on Advanced Learning Technologies (2006)

The correlation between the effort to develop a learning process and early size measures could be used to assess the usability of an employed tool. In particular, when the measures are obtained from the learning process specification and they are relevant effort indicators we can assert that the technical competences of instructional designers are not relevant for the tool usage. We present initial results of applying empirical analysis to confirm a previously usability study performed on the ASCLO-S (Adaptive Self consistent Learning Object SET) editor, a visual language based tool for developing adaptive learning processes.
Multi-modal Scene Reconstruction using Perceptual Grouping Constraints
Authors: Nicolas Pugeault, Florentin Worgotter, Norbert Kruger
Venue: Proceedings of the 2006 Conference on Computer Vision and Pattern Recognition Workshop (2006)

In this work we propose a scheme integrating perceptual grouping into stereopsis to reduce the ambiguity of those early processes. We propose a simple perceptual grouping algorithm that - in addition to the geometric information makes use of a novel multi-modal affinity measure between local primitives. We then use this group information to 1) disambiguate the stereopsis by enforcing that stereo matches preserve groups; and 2) correct the reconstruction error due to the image pixel sampling using a linear interpolation over the groups. We show quantitative and qualitative demonstrations of those processes on a variety of sequences.
Defining the Architectural Design of Frameworks through a Group of Subframeworks Created from Frozen and Hot Spots
Authors: Simone Nasser Matos, Clovis Torres Fernandes
Venue: Proceedings of the International Conference on Software Engineering Advances (2006)

This work presents a contribution to an architectural definition of a framework, which is composed of several subframeworks, subsystems and components, clarifying explicitly its process of reuse. Several approaches for the development of frameworks presented in the literature do not specify which parts of the subframeworks will be flexible and which ones will not vary, thus making the process of reusing subframeworks more difficult. This paper provides a proposal aiming to define the subframeworks from frozen and hot spots obtained in the beginning of a frameworks development process.
Extracting redundancy-aware top-k patterns
Authors: Dong Xin, Hong Cheng, Xifeng Yan, Jiawei Han
Venue: Proceedings of the 12th ACM SIGKDD international conference on Knowledge discovery and data mining (2006)

Observed in many applications, there is a potential need of extracting a small set of frequent patterns having not only high significance but also low redundancy. The significance is usually defined by the context of applications. Previous studies have been concentrating on how to compute top-k significant patterns or how to remove redundancy among patterns separately. There is limited work on finding those top-k patterns which demonstrate high-significance and low-redundancy simultaneously.In this paper, we study the problem of extracting redundancy-aware top-k patterns from a large collection of frequent patterns. We first examine the evaluation functions for measuring the combined significance of a pattern set and propose the MMS (Maximal Marginal Significance) as the problem formulation. The problem is known as NP-hard. We further present a greedy algorithm which approximates the optimal solution with performance bound O(log k) (with conditions on redundancy), where k is the number of reported patterns. The direct usage of redundancy-aware top-k patterns is illustrated through two real applications: disk block prefetch and document theme extraction. Our method can also be applied to processing redundancy-aware top-k queries in traditional database.
A Bi-population-evolution Integrated QoS Multicast Routing Algorithm in NGI
Authors: Xingwei Wang, Shanlin Li, Guangyong An, Min Huang
Venue: Proceedings of the 2006 International Conference on Hybrid Information Technology - Volume 01 (2006)

IP/DWDM optical Internet is one of the main networking technologies for the NGI(Next Generation Internet). QoS multicast routing is one of its basic problems to be solved and is proven to be NP-hard. Thus, a non-NP algorithm is proposed in this paper. It is based on bi-population-evolution to find a costoptimized QoS multicast routing tree with routing and wavelength assignment solved integratedly. Simulation results have shown that the proposed algorithm is both feasible and effective, and is advantageous over its counterpart based on the classical genetic algorithm.
The Optimality of Allocation Methods for Bounded Disagreement Search Queries: The Possible and the Impossible
Authors: Khaled A. S. Abdel-Ghaffar, Amr El Abbadi
Venue: IEEE Transactions on Knowledge and Data Engineering (2006)

Data Allocation on multiple I/O devices manifests itself in many computing systems, both centralized and distributed. Data is partitioned on multiple I/O devices and clients issue various types of queries to retrieve relevant information. In this paper, we derive necessary and sufficient conditions for a data allocation method to be optimal for two important types of queries: partial match and bounded disagreement search queries. We formally define these query types and derive the optimality conditions based on coding-theoretic arguments. Although these conditions are fairly strict, we show how to construct good allocation methods for practical realistic situations. Not only are the response times bounded by a small value, but also the identification of the relevant answer set is efficient.
Adaptive Performance: Implications for Military Logistics
Authors: Charlene K. Stokes, Paul D. Faas
Venue: Proceedings of the International Symposium on Collaborative Technologies and Systems (2006)

The Information Age we are operating in today has created pervasive changes in the basic nature of work. As the foundations of work are being altered, new demands are being placed on the individuals performing the jobs. Although technological innovations to cope with changes in work abound, the implications at the human level have been neglected. Within the military logistics domain, numerous networking technologies have been implemented in an effort to evolve with the new Net-Centric warfare environment. If the evolution is to succeed, a coherent systems approach is needed that also addresses the human component. Starting at the beginning, we must ask what aspects of human performance are imperative in today's warfare environment. As the foundations of work itself are being altered, so are the dimensions of performance; therefore new performance models are needed that address how work is done today. Thus, I propose a study that examines a relatively new model of performance: adaptive performance. Validation of the adaptive performance model and identification of predictors would address the human side of networked logistics by aiding in the selection and training of a workforce suitable to operate within the dynamic and fluid military logistics system that has emerged.
Dynamic Model Learning Using Genetic Algorithm under Adaptive Model Checking Framework
Authors: Zhifeng Lai, S. C. Cheung, Yunfei Jiang
Venue: Proceedings of the Sixth International Conference on Quality Software (2006)

Model-based techniques for reactive systems generally assume the availability of a state machine that describes the behavior of the system under study. However, the assumption may not always hold in reality. Even the assumption holds, the state machine could be invalidated when the system evolves. This triggers the study of adaptive model checking, which necessitates an iterative construction of a state machine for a system. In this paper, we propose a dynamic learning approach based on genetic algorithm to iteratively generate a finite-state automaton from a given system. In view of the fact that modern systems are apt to change, our algorithm postpones expensive equivalence checking until the associated accuracy is required for the verification of some properties. We explain in details the core learning process of our algorithm, including encoding the model and its synthesis from a given training set. Experimental results show that our algorithm is scalable in memory consumption. Dynamic model learning technique helps model checking of evolving reactive system.
Poly-functional intelligent agents for computer generated forces
Authors: Matteo Brandolini, Attilio Rocca, Agostino G. Bruzzone, Chiara Briano, Petranka Petrova
Venue: Proceedings of the 36th conference on Winter simulation (2004)

The authors present the requirement definition and methodological approach for developing a new generation of Computer Generated Forces (CGF) based on Intelligent Agents. The analysis is based on the author initiative (PIOVRA) devoted to the development of High Level Architecture (HLA) components to be integrated for training, planning and operative support. These agents require to act as smart entities in the scenarios reproducing both enemies and/or civil units; their model includes characteristics that are typical of the psychological aspects affecting troops and soldiers on the battlefields as well as operative basic tactics. The authors avoid to create intelligent units in a wide sense due to the fact that Artificial Intelligence (AI) technology is quite far to the creation of an "intelligent virtual strategists or commander"; however their entities are expected to face set of complex situations with realistic cooperative and competitive understanding and reproducing real reactions to the boundary conditions.
Extensive games with possibly unaware players
Authors: Joseph Y. Halpern, Leandro C. Rêgo
Venue: Proceedings of the fifth international joint conference on Autonomous agents and multiagent systems (2006)

Standard game theory assumes that the structure of the game is common knowledge among players. We relax this assumption by considering extensive games where agents may be unaware of the complete structure of the game. In particular, they may not be aware of moves that they and other agents can make. We show how such games can be represented; the key idea is to describe the game from the point of view of every agent at every node of the game tree. We provide a generalization of Nash equilibrium and show that every game with awareness has a generalized Nash equilibrium. Finally, we extend these results to games with awareness of unawareness, where a player i may be aware that a player j can make moves that i is not aware of.
An overview on MEMS-based storage, its research issues and open problems
Authors: Yifeng Zhu
Venue: Proceedings of the international workshop on Storage network architecture and parallel I/Os (2004)

A disruptive new storage technology based on Microelectromechanical Systems (MEMS) is emerging as an exciting complement to the memory hierarchy. This study reviews and summarizes the current research about integrating this new technology into computer systems from four levels: device, architecture, system and application. In addition, several potential research issues in MEMS storage are identified, including (1) exploiting idle read/write tips to perform prefetching, (2) reversal access to save seek time, (3) fault-tolerance design inside storage devices, (4) power consumption modeling, (5) reevaluation of existing disk-type I/O optimization algorithms.