ppxscal/embedding_network huggingface dataset:
The Approach of Chinese Speech Triseme Recognition for Human Mouth Animation
Authors: Jianjun Ouyang, Ming Xu, Yunsen Huang
Venue: Proceedings of the Third International Conference on Natural Computation - Volume 05 (2007)

Different from text driven and phoneme based human mouth synthesis approaches, this paper presents the novel natural speech driven mouth animation approach. To capture the context information of continuously speaking mouth shapes, the triseme based modeling technique is employed for acquiring the trisemic HMMs. To obtain the robust model parameters with the limited training data, the states tying procedure is introduced. Considering the compatibility and ambiguity issues, the visemic questions which assigned in the leaf nodes of decision tree are gen- erated that based on the training data. With the modeled HMM parameters, the viterbi beam searching algorithm is applied to time align the trisemic sequences. Mapping the recognized trisemes to the corresponding MPEG-4 FAPs-represented mouth shapes, the speaking mouth can be finally animated through a smoothing process. In terms of the proposed evaluation criterion, the experimental results illustrate that the recognition accuracy is applicable and also the aligning speed is acceptable in human vision.
Enhancing collaborative synchronous UML modelling with fine-grained versioning of software artefacts
Authors: A. De Lucia, F. Fasano, G. Scanniello, G. Tortora
Venue: Journal of Visual Languages and Computing (2007)

Software development teams are composed of people with different knowledge and skills, who contribute to a project from often widely dispersed locations. Software development in geographically distributed environments creates software engineering challenges due to the interaction among members of distributed teams and the management of consistency and concurrency among project artefacts. In this paper, we propose Synchronous collaborative modelling Tool Enhanced with VErsioning management (STEVE) a collaborative tool supporting distributed Unified Modelling Language (UML) modelling of software systems. The tool provides a communication infrastructure enabling the concurrent editing of the same UML diagram at the same time by distributed developers. Complex UML diagrams are decomposed and managed in a fine-grained hierarchy of sub-artefacts, thus providing change and configuration management functionalities for both the diagram and the graphical objects. Thus, software predefined diagram components can be consistently reused and shared across different diagrams of a given project.
2007 Special Issue: Principles for consciousness in integrated cognitive control
Authors: Ricardo Sanz, Ignacio López, Manuel Rodríguez, Carlos Hernández
Venue: Neural Networks (2007)

In this paper we will argue that given certain conditions for the evolution of biological controllers, they will necessarily evolve in the direction of incorporating consciousness capabilities. We will also see what are the necessary mechanics for the provision of these capabilities and extrapolate this vision to the world of artificial systems.
Function-Based Authorization Constraints Specification and Enforcement
Authors: Wei Zhou, Christoph Meinel
Venue: Proceedings of the Third International Symposium on Information Assurance and Security (2007)

Constraints are an important aspect of role-based access control (RBAC) and its different extensions. They are often regarded as one of the principal motivation behind these access control models. In this paper, we introduce two novel authorization constraint specification schemes named as prohibition constraint scheme and obligation constraint scheme. Both of them can be used for expressing and enforcing authorization constraints. These schemes strongly bind to authorization entity set functions and authorization entity relation functions, so they can provide the system designers a clear view about which functions should be defined in an authorization constraint system. Based on these functions, different kinds of constraint schemes can be easily defined. The security administrators can use these functions to create constraint schemes for their day-to-day operations. The constraint system can be scalable through defining new functions. This approach goes beyond the well known separation of duty constraints, and considers many aspects of entity relation constraints.
Resource Sharing Protocols
Authors: J. D. Day
Venue: Computer (1979)

This report summarizes recent US and European work on conventions for handling two basic types of remote operations: terminal access to remote hosts and file transfer between hosts.
Clairvoyant: a comprehensive source-level debugger for wireless sensor networks
Authors: Jing Yang, Mary Lou Soffa, Leo Selavo, Kamin Whitehouse
Venue: Proceedings of the 5th international conference on Embedded networked sensor systems (2007)

Wireless sensor network (WSN) applications are notoriously difficult to develop and debug. This paper describes Clairvoyant which is a comprehensive source-level debugger for wireless, embedded networks. With Clairvoyant, a developer can wirelessly connect to a sensor network and execute standard debugging commands including break, step, watch, and backtrace, as well as new commands that are specially designed for debugging WSNs. Clairvoyant attempts to minimize its effect on the program being debugged in terms of network load, memory footprint, execution speed, clock consistency, and flash lifetime.
The Complexity of the Descriptiveness of Boolean Circuits over Different Sets of Gates
Authors: Elmar Bohler, Henning Schnoor
Venue: Theory of Computing Systems (2007)

Any Boolean function can be defined by a Boolean circuit, provided we may use sufficiently strong functions in its gates. On the other hand, what Boolean functions can be defined depends on these gate functions: Each set B of gate functions defines the class of Boolean functions that can be defined by circuits over B. Although these classes have been known since the 1920s, their computational complexity was never investigated. In this paper we will study how difficult it is to decide for a Boolean function f and a class B, whether f is in B. Moreover, we will provide such a decision algorithm with additional information: How difficult is it to decide whether or not f is in B, provided we already know a circuit for f, but with gates from another class A? Given such a circuit, we know that f is in A. Is the problem harder if we do not have a concrete representation for f, but still know that it is from A? For nearly all possible combinations, we show that this is not the case, and that the problem is either in P or coNP-complete.
A Novel Performance-Driven Topology Design Algorithm
Authors: Min Pan, Chris Chu, Priyadarshan Patra
Venue: Proceedings of the 2007 Asia and South Pacific Design Automation Conference (2007)

This paper presents a very efficient algorithm for performance-driven topology design for interconnects. Given a net, it first generates A-tree1 topology using table lookup and net-breaking. Then a performance-driven post-processing heuristic not restricting to A-tree topology improves the obtained topology by considering the sink positions, required time and load capacitance to achieve better timing. Experimental results show that our new technique can produce topologies with better timing and is hundreds of times faster than traditional approach.
Proceedings of the 11th conference on Theoretical aspects of rationality and knowledge
Venue: Theoretical Aspects Of Rationality And Knowledge (2007)

The interest in multidisciplinary approaches to the study of rationality and knowledge seems to be as strong as it was twenty-one years ago when the first TARK conference was launched. We see this in the number of submissions to TARK 2007 --- one hundred, which is the second highest for the eleven TARK conferences held since 1986. Thirty two papers were accepted, which is a record high for TARK. In order to accommodate all these papers in three days, 10 of them are presented in a poster session, which is new to TARK.
Reflective and Refractive Variables: A Model for Effective and Maintainable Adaptive-and-Dependable Software
Authors: Vincenzo De Florio, Chris Blondia
Venue: Proceedings of the 33rd EUROMICRO Conference on Software Engineering and Advanced Applications (2007)

We propose a simple and effective tool for the expression of tasks such as cross-layer optimization strategies or sensors-related applications. The approach is based on what we refer to as "reflective and refractive variables". Both types of variables are associated with external entities, e.g. sensors or actuators. A reflective variable is a volatile variable, that is, a variable that might be concurrently modified by multiple threads. A library of threads is made available, each of which interfaces a set of sensors and continuously update the value of a corresponding set of sensors. One such thread is "cpu", which exports the current level of usage of the local CPU as an integer between 0 and 100. This integer is reflected into the integer reflective variable cpu. A refractive variable is a reflective variable that can be modified. Each modification is caught and interpreted as a request to change the value of an actuator. For instance, setting variable "tcp sendrate" would request a cross-layer adjustment to the thread interfacing the local TCP layer entity. This allows express in an easy way complex operations in the application layer of any programming language, e.g. plain old C. We describe our translator and the work we are carrying out within PATS to build simple and powerful libraries of scripts based on reflective and refractive variables, including robotics applications and RFID tags processing.
LH*RS: a highly available distributed data storage
Authors: Witold Litwin, Rim Moussa, Thomas J. E. Schwarz
Venue: Proceedings of the Thirtieth international conference on Very large data bases - Volume 30 (2004)

The ideal storage system is always available and incrementally expandable. Existing storage systems fall far from this ideal. Affordable computers and high-speed networks allow us to investigate storage architectures closer to the ideal. Our demo, present a prototype implementation of LH*RS: a highly available scalable and distributed data structure.
An agent-based decision support system for wholesale electricity market
Authors: Toshiyuki Sueyoshi, Gopalakrishna R. Tadiparthi
Venue: Decision Support Systems (2008)

Application software has been developed for analyzing and understanding a dynamic price change in the US wholesale power market. Traders can use the software as an effective decision-making tool by modeling and simulating a power market. The software uses different features of a decision support system by creating a framework for assessing new trading strategies in a competitive electricity trading environment. The practicality of the software is confirmed by comparing its estimation accuracy with those of other methods (e.g., neural network and genetic algorithm). The software has been applied to a data set regarding the California electricity crisis in order to examine whether the learning (convergence) speed of traders is different between the two periods (before and during the crisis). Such an application confirms the validity of the proposed software.
The Study of the Classification of Chinese Folk Songs by Regional Style
Authors: Yi Liu, JiePing Xu, Lei Wei, Yun Tian
Venue: Proceedings of the International Conference on Semantic Computing (2007)

This paper discusses a method of studying the region style classification of Chinese folk songs with support vector machine (SVM). According to geographical region of China, We have classified Chinese folk songs into 10 major categories, and used 500 Chinese folk songs in our experiment. 74 features have been extracted from audio files of the songs, and classified by an audio classifier on SVM. The experiment results show that sampling rate is not directly proportional to classification accuracy; SVM without feature selection is a very effective classification method for region style classification; the combination of 13-dimension MFCC and 10-dimension LPC features can achieve very similar results as that gained from SVM without feature selection. By using 30-second multi-clip classification and post-processing on classification result, the classification accuracy is improved from 47.4% to 75.2%, which is higher than that professional people got on music clip.
Generation of Representative Functions of the NPN Equivalence Classes of Unate Boolean Functions
Authors: C. R. Baugh
Venue: IEEE Transactions on Computers (1972)

An algorithm is described which generates the set of representative functions of the negation and/or permutation of variables and negation of the function (NPN) equivalence classes of unate Boolean functions. The algorithm is based upon integer programming techniques. The set of representative functions for the NPN equivalence classes of unate functions of six or fewer variables was obtained using this algorithm. The set of pseudothreshold functions of six or fewer variables was also tabulated by using this algorithm as a basis.
Homogeneous Coordinates and Projective Planes in Computer Graphics
Authors: R. F. Riesenfeld
Venue: IEEE Computer Graphics and Applications (1981)

Discrepancies between euclidean three-dimensional space and the projective space modeled by means of homogeneous coordinates account for seemingly paradoxical phenomena in computer graphics.
Sensor-based Training Optimization of a Cyclist Group
Authors: Ankang Le, Thomas Jaitner, Lothar Litz
Venue: Proceedings of the 7th International Conference on Hybrid Intelligent Systems (2007)

Determining the optimal exercise intensity is a crucial factor to increase performance in professional cycling. Novel sensor technologies allow to optimize the training not only for an individual cyclist but also for an entire training group. A sensor-based Assisted Bicycle Trainer (ABT) system with a control algorithm has been developed at the University of Kaiserslautern to optimize the group training in cycling. The focus of this paper is on the development of the control algorithm, a Model Predictive Controller (MPC) for the optimization of the group training. The controller predicts the heart rate of the cyclists based on individualized heart rate models and regulates the group training by advising cyclists to change the position in the group, to adjust the group speed, or to split the group in such a way that each cyclist can meet his training plan as exactly as possible.
View influence analysis and optimization for multiview face recognition
Authors: Won-Sook Lee, Kyung-Ah Sohn
Venue: Journal on Image and Video Processing (2007)

We present a novel method to recognize a multiview face (i.e., to recognize a face under different views) through optimization of multiple single-view face recognitions. Many current face descriptors show quite satisfactory results to recognize identity of people with given limited view (especially for the frontal view), but the full view of the human head has not yet been recognizable with commercially acceptable accuracy. As there are various single-view recognition techniques already developed for very high success rate, for instance, MPEG-7 advanced face recognizer, we propose a new paradigm to facilitate multiview face recognition, not through a multiview face recognizer, but through multiple single-view recognizers. To retrieve faces in any view from a registered descriptor, we need to give corresponding view information to the descriptor. As the descriptor needs to provide any requested view in 3D space, we refer to it as "3D" information that it needs to contain. Our analysis in various angled views checks the extent of each view influence and it provides a way to recognize a face through optimized integration of single view descriptors covering the view plane of horizontal rotation from -90° to 90° and vertical rotation from -30° to 30° The resulting face descriptor based on multiple representative views, which is of compact size, shows reasonable face recognition performance on any view. Hence, our face descriptor contains quite enough 3D information of a person's face to help for recognition and eventually for search, retrieval, and browsing of photographs, videos, and 3D-facial model databases.
Using Software Dependencies and Churn Metrics to Predict Field Failures: An Empirical Case Study
Authors: Nachiappan Nagappan, Thomas Ball
Venue: Proceedings of the First International Symposium on Empirical Software Engineering and Measurement (2007)

Commercial software development is a complex task that requires a thorough understanding of the architecture of the software system. We analyze the Windows Server 2003 operating system in order to assess the relationship between its software dependencies, churn measures and post-release failures. Our analysis indicates the ability of software dependencies and churn measures to be efficient predictors of post-release failures. Further, we investigate the relationship between the software dependencies and churn measures and their ability to assess failure-proneness probabilities at statistically significant levels.
Transport Layer Protocols for the Secoqc Quantum Key Distribution (QKD) Network
Authors: Mehrdad Dianati, Romain Alleaume
Venue: Proceedings of the 32nd IEEE Conference on Local Computer Networks (2007)

Quantum Key Distribution (QKD) is an alternative key distribution technique that, unlike the classical approaches, can provide unconditionally secure keys for data communications over public communication networks. The European projet Secoqc (Secure Communication based on Quantum Cryptography) aims at developing a global network for unconditionally secure key distribution. This paper specifies the major elements of the transport layer protocols of the Secoqc QKD network.
An Attribute-Oriented Ensemble Classifier Based on Niche Gene Expression Programming
Authors: Jiang Wu, Changjie Tang, Jun Zhu, Taiyong Li, Lei Duan, Chuan Li, Li Dai
Venue: Proceedings of the Third International Conference on Natural Computation - Volume 03 (2007)

Ensemble of classifiers is a learning paradigm where a set of classifiers are jointly used to improve the classification accuracy. The main contributions of this paper include: (1) proposing a new concept named attribute selection set based on Gene Expression Programming (GEP), (2) analyzing the principle of classifier ensemble, (3) proposing an Attribute- Oriented Ensemble Classifier Based on Niche Gene Expression Programming (AO-ECNG) to improve the accuracy of sub-classifiers and at the same time maintain the diversity among them, and (4) analyzing the relationship between predictive accuracy and ensemble size. Experimental results on 10 datasets suggest that AO-ECNG increases the predictive accuracy by 2.51%, 1.66%, 1.33% and 1% respectively compared with single GEP-classifiers, Bagging, AdaBoost, and GEFS.
Parameter Estimate by Incomplete Neural Network for MOSFET Life Model with NOME Distribution
Authors: Qiaoling Tong, Xuecheng Zou, Hengqing Tong, Tianzhen Liu
Venue: Proceedings of the Third International Conference on Natural Computation - Volume 03 (2007)

The test of MOSFET life is an important work in semiconductor manufacture. Many studies have been done on modeling the MOSFET life distribution for the reliability of integrated circuits. In this paper, a MOSFET life model is introduced by making use of threshold voltage drift property. A new statistical distribution, whose negative order moment estimator is just the maximum likelihood estimator, is deduced, and we call it NOME distribution. A new method of parameter estimate, F estimate of parameter, is proposed for complete sample test and truncated sample test. A kind of incomplete neural network is used to optimize the parameter in the model. Results show that neural network is a powerful tool for the analysis of MOSFET life model.
Optimal distortion embeddings of distance regular graphs into Euclidean spaces
Authors: Frank Vallentin
Venue: Journal of Combinatorial Theory Series B (2008)

In this paper we give a lower bound for the least distortion embedding of a distance regular graph into Euclidean space. We use the lower bound for finding the least distortion for Hamming graphs, Johnson graphs, and all strongly regular graphs. Our technique involves semidefinite programming and exploiting the algebra structure of the optimization problem so that the question of finding a lower bound of the least distortion is reduced to an analytic question about orthogonal polynomials.
An approach to precisely specifying the problem domain of design patterns
Authors: Dae-Kyoo Kim, Charbel El Khawand
Venue: Journal of Visual Languages and Computing (2007)

The problem domain of a design pattern describes the problem context in which the pattern can be applied. In general, determining the applicability of a pattern to a particular problem heavily relies on the knowledge and experience the developer has with the pattern. This significantly limits the use of patterns. To address this issue, we propose an approach for rigorously specifying the problem domain of patterns. This approach systematically guides one to develop rigorous specifications of a pattern's problem domain using a precise notation. The resulting specifications can be used to develop tool support for automatic evaluation of pattern applicability. We describe the approach using the Visitor pattern, and show how the resulting specification can be used to evaluate pattern applicability for a particular problem model. We also demonstrate tool support for the approach.
Accurate on-line avatar control with collision anticipation
Authors: Manuel Peinado, Daniel Meziat, Damien Maupu, Daniel Raunhardt, Daniel Thalmann, Ronan Boulic
Venue: Proceedings of the 2007 ACM symposium on Virtual reality software and technology (2007)

Interactive control of a virtual character through full body movement has a wide range of applications. However, there is a need for systems that accurately reproduce the motion of a performer while accounting for surrounding obstacles. We propose an approach based on a Prioritized Inverse Kinematics constraint solver. Several markers are placed on the user's body. A set of kinematic constraints make the virtual character track these markers. At the same time, we monitor the instantaneous displacements of a set of geometric primitives, called observers, attached to different parts of the virtual character. When an observer enters the influence area of an obstacle, its motion is damped by means of automatically created preventive constraints. The IK solver satisfies both maker and preventive constraints simultaneously, yielding postures of the virtual character that remain close to those of the user, while avoiding collisions with the virtual environment. Our performance measurements show the maturity of the IK technology for real-time full-body interactions.
Performance Analysis of FFT Algorithms on Multiprocessor Systems
Authors: L. N. Bhuyan
Venue: IEEE Transactions on Software Engineering (1983)

A decimation-in-time radix-2 fast Fourier transform (FFT) algorithm is considered here for implementation in multiprocessors with shared bus, multistage interconnection network (MIN), and in mesh connected computers. Results are derived for data allocation, interprocessor communication, approximate computation time, and speedup of an N point FFT on any P available processing elements (PE's). Further generalization is obtained for a radix-r FFT algorithm. An N X N point two-dimensional discrete Fourier transform (DFT) implementation is also considered when one or more rows of the input data matrix are allocated to each PE.