ppxscal/embedding_network huggingface dataset:
3D virtual simulator for breast plastic surgery
Authors: Youngjun Kim
Venue: Computer Animation and Virtual Worlds (2008)

We have proposed novel 3D virtual simulation software for breast plastic surgery. Our software comprises two processes: a 3D torso modeling and a virtual simulation of the surgery result. First, image-based modeling is performed in order to obtain a female subject's 3D torso data. Our image-based modeling method utilizes a template model, and this is deformed according to the patient's photographs. For the deformation, we applied procrustes analysis and radial basis functions (RBF). In order to enhance reality, the subject's photographs are mapped onto a mesh. Second, from the modeled subject data, we simulate the subject's virtual appearance after the plastic surgery by morphing the shape of the breasts. We solve the simulation problem by an example-based approach. The subject's virtual shape is obtained from the relations between the pair sets of feature points from previous patients' photographs obtained before and after the surgery. Copyright &copy; 2008 John Wiley & Sons, Ltd.
Los Angeles Cooperative Compiler Project Policy Committee Minutes
Venue: IEEE Annals of the History of Computing (1983)

This is a copy of the minutes of the first meeting of the Los Angeles Computer Project Policy Committee on November 16, 1954. [The editor] has always thought that this meeting, along with the activity of the Digital Computer Association (DCA), led directly to the formation of SHARE. The ACM Portal is published by the Association for Computing Machinery. Copyright © 2010 ACM, Inc. Terms of Usage Privacy Policy Code of Ethics Contact Us Useful downloads: Adobe Acrobat QuickTime Windows Media Player Real Player
Research on Integrated and Flexible MES Based on Agency and SOA
Authors: Ruixue Fu, Ming Song, Zhanhong Xin, Jianzhang Wu, Hongying Li
Venue: Proceedings of the 2008 International Symposiums on Information Processing (2008)

To develop integrated and flexible MES (Manufacturing Execution Systems) based on Agency and SOA (Service Oriented Architecture), after the definition of agent, the hierarchical structure of manufacturing management-control system with three layers has been presented. The core layer is the MES layer which includes nine Function Agencies. Each Function Agency consists of four types of agents with different functionalities. In this architecture, the Web Service is adopted to realize the communication between agents and the Market Mechanism is adopted to serve as control for interaction behavior among agents. The objectives of this paper is to illustrate the architecture of integrated and flexible MES with the purposes of integrating legacy systems together with MES, response rapid to a fluctuating market, flexibility and reconfiguration of the MES, the function of detailed planning, and the approach how a web services-based SOA supports our MES.
Provably Secure Convertible User Designating Confirmer Partially Blind Signatures
Authors: Zhenjie Huang, Kefei Chen, Yumin Wang
Venue: Informatica (2006)

This paper introduces a new concept of convertible user designating confirmer partially blind signature, in which only the designated confirmer (designated by the user) and the user can verify and confirm the validity of given signatures and convert given signatures into publicly verifiable ones. We give a formal definition for it and propose a concrete provably secure scheme with a proof of security and a brief analysis of efficiency. Assuming the intractabilities of the Discrete Logarithm Problem and the ROS-Problem, the proposed scheme is unforgeable under adaptive chosen-message attack.
Web-Based System for Advanced Heart Disease Identification Using Grid Computing Technology
Authors: Chang Hee Han, Chan-Hyun Youn, Wooram Jung
Venue: Proceedings of the 2008 21st IEEE International Symposium on Computer-Based Medical Systems (2008)

Heart disease is one of the most serious medical problems which threaten human life. Now there are several methods for detecting heart disease and ECG (Electrocardiogram) signal analysis is one of the typical solutions. The other method such as MCG (Magnetocardiogram) is also recommended for heart disease detection. In computer society, the e-Health systems using these diagnosis methods have been developed. However, each diagnosis method has their own weak points and also limitations in system performance according to the increase of data in quantity. Therefore, in order to improve each diagnosis method and conventional e-Health system, we propose and implement a novel integrated-diagnosis system combining grid technologies which is termed as a Physio-Grid system. We present the experimental and evaluation data in order to show our system capability in diagnosis and system performance. The results indicate that the proposed e-Health system can provide the plausible medical services and also it guarantees high reliability and system performance in data management and in diagnosis.
Towards Building Robust Natural Language Interfaces to Databases
Authors: Michael Minock, Peter Olofsson, Alexander Näslund
Venue: Proceedings of the 13th international conference on Natural Language and Information Systems: Applications of Natural Language to Information Systems (2008)

We seek to give everyday technical teams the capability to build robust natural language interfaces to their databases, for subsequent use by casual users. We present an approach to the problem which integrates and streamlines earlier work based on light annotation and authoring tools. We model queries in a higher-order version of Codd's tuple calculus and we use synchronous grammars extended with lambda functions to represent semantic grammars. The results of configuration can be applied directly to SQL based databases with general n-ary relations. We have fully implemented our approach and we present initial empirical results for the Geoquery 250 corpus.
Search Space Reduction for Constraint Optimization Problems
Authors: Kenil C. Cheng, Roland H. Yap
Venue: Proceedings of the 14th international conference on Principles and Practice of Constraint Programming (2008)

In a constraint optimization problem (COP), many feasible assignments have the same objective value. This usually means huge search space and poor propagation among the objective variables (which appear in the objective function) and the problem variables (which do not). In this paper, we investigate a search strategy that focuses on the objective function, namely, the objective variables are assigned before the problem variables. Despite the larger search space, we may indeed solve a COP faster, provided that the constraint propagation is strong -- the search can reach the optimal objective value faster in the objective space, and by strong propagation it knows if the constraints are unsatisfiable with little search in the problem space. To obtain strong propagation, we study the use of dual encoding [1] for COPs. Our COP formulation and search strategy are general and can handle any dual COPs.
Research on the Privacy Preserving Algorithm of Association Rule Mining in Centralized Database
Authors: Shaofei Wu, Hui Wang
Venue: Proceedings of the 2008 International Symposiums on Information Processing (2008)

The recent advance of data mining technology to analyze vast amount of data has played an important role in marketing business, despite its benefits in such areas, data mining also opens new threats to privacy and information security if not done or used properly. The main problem is that from non-sensitive data, one is able to infer sensitive information, including personal information, fact or even patterns that are not supposed to be disclosed. In order to focusing on privacy preserving association rule mining, the simplistic solution to address the problem of privacy is presented. The solution is to implement a filter after the mining phase to weed out or hide the restricted discovered association rules. Before implementing the algorithms, the data structure of database and sensitive association rule mining set have been analyzed to build the more effective model. This new algorithm can be used to balance privacy preserving and knowledge discovery in association rule mining.
Value-based observation compression for DEC-POMDPs
Authors: Alan Carlin, Shlomo Zilberstein
Venue: Proceedings of the 7th international joint conference on Autonomous agents and multiagent systems - Volume 1 (2008)

Representing agent policies compactly is essential for improving the scalability of multi-agent planning algorithms. In this paper, we focus on developing a pruning technique that allows us to merge certain observations within agent policies, while minimizing loss of value. This is particularly important for solving finite-horizon decentralized POMDPs, where agent policies are represented as trees, and where the size of policy trees grows exponentially with the number of observations. We introduce a value-based observation compression technique that prunes the least valuable observations while maintaining an error bound on the value lost as a result of pruning. We analyze the characteristics of this pruning strategy and show empirically that it is effective. Thus, we use compact policies to obtain signicantly higher values compared with the best existing DEC-POMDP algorithm.
A Machine-Learning Based Load Prediction Approach for Distributed Service-Oriented Applications
Authors: Jun Wang, Yi Ren, Di Zheng, Quan-Yuan Wu
Venue: Proceedings of the 7th international conference on Computational Science, Part I: ICCS 2007 (2007)

By using middleware, we can satisfy the urgent demands of performance, scalability and availability in current distributed service-oriented applications. However to the complex applications, the load peak may make the system suffer extremely high load and the response time may be decreased for this kind of fluctuate. Therefore, to utilize the services effectively especially when the workloads fluctuate frequently, we should make the system react to the load fluctuate gradually and predictably. Many existing load balancing middleware use the dampening technology to make the load to be predicative. However, distributed systems are inherently difficult to manage and the dampening factor cannot be treated as static and fixed. The dampening factor should be adjusted dynamically according to different load fluctuate. So we have proposed a new technique based on machine learning for adaptive and flexible load prediction mechanism based on our load balancing middleware.
Modelling of Modular Robot Configurations Using Graph Theory
Authors: José Baca, Ariadna Yerpes, Manuel Ferre, Juan A. Escalera, Rafael Aracil
Venue: Proceedings of the 3rd international workshop on Hybrid Artificial Intelligence Systems (2008)

Modular robots are systems that can change its geometry or configuration when connecting more modules or when rearranging them in a different manner to perform a variety of tasks. Graph theory can be used to describe modular robots configurations, hence the possibility to determine the flexibility of the robot to move from one point to another. When the robot's configurations are represented in a mathematical way, forward kinematics can be obtained.
Improvement of genetic algorithm performance for identification of cultivation process models
Authors: Olympia Roeva
Venue: Proceedings of the 9th WSEAS International Conference on Evolutionary Computing (2008)

In the genetic algorithms, there are many parameters and settings that can be implemented differently in various problems. There is no general theory about tuning the genetic algorithm parameters. In this paper some adjustments of genetic parameters, according to the identification problem of cultivation process models, are done to improve the genetic algorithm performance. Based on the proposed procedure for genetic parameters tuning and series of experiments a successful adjustment of the algorithm is done. The results show that the identification procedure leads to higher order of accuracy of the obtained parameter estimations and to 2.5 times decrease of the computation time. In order to validate the proposed genetic algorithm two experimental data sets of a recombinant E. coli BL21(DE3)pPhyt109 cultivation process are used. Based on the regarded genetic algorithm successful identification is done and fulfilled model verification shows the model adequateness.
Operational Semantics for Positive Relevant Logics Without Distribution
Authors: Ying Gao, Jingde Cheng
Venue: Proceedings of the 3rd conference on Computability in Europe: Computation and Logic in the Real World (2007)

This paper investigates operational semantics for various positive relevant logics without distribution after the work of Kit Fine in Models for Entailment. To invalidate the law of distribution of conjunction over disjunction, we use different types of states to model conjunction and disjunction, respectively. The implication &rarr; is interpreted by three operations &oplus; , &otimes; , ⊖, instead of one operation `&middot;' as in Fine's work.
Analysis of User Perceived QoS in Ubiquitous UMTS Environments Subject to Faults
Authors: Andrea Bondavalli, Paolo Lollini, Leonardo Montecchi
Venue: Proceedings of the 6th IFIP WG 10.2 international workshop on Software Technologies for Embedded and Ubiquitous Systems (2008)

This paper provides a QoS analysis of a dynamic, ubiquitous UMTS network scenario in the automotive context identified in the ongoing EC HIDENETS project. The scenario comprises different types of mobile users, applications, traffic conditions, and outage events reducing the available network resources. Adopting a compositional modeling approach based on Stochastic Activity Networks formalism, we analyze the Quality of Service (QoS) both from the users' perspective and from the mobile operator's one. The classical QoS analysis is enhanced by taking into account the congestion both caused by the outage events and by the varying traffic conditions.
Numerical Simulation of Flow in a Screw-Type Blood Pump
Authors: M. I. Kilani, Y. S. Haik, S.-Y. Jaw, C.-J. Chen
Venue: Journal of Visualization (2005)

This study presents a numerical investigation of the flow field in a screw pump designed to circulate biological fluid such as blood. A simplified channel flow model is used to allow analysis using a Cartesian set of coordinates. Finite analytic (FA) numerical simulation of the flow field inside the channel was performed to study the influence of Reynolds number and pressure gradient on velocity distribution and shear stresses across the channel cross-section. Simulation results were used to predict flow rates, circulatory flow and the shear stresses, which are known to be related to the level of red blood cell damage (hemolysis) caused by the pump. The study shows that high shear levels are confined to small regions within the channel cross-section, but the circulatory nature of the flow causes an increased percentage of blood elements to pass through the high shear regions, and increases the likelihood of cell damage.
Building Medium-Vocabulary Isolated-Word Lithuanian HMM Speech Recognition System
Authors: Gailius Raškinis, Danutė Raškinienė
Venue: Informatica (2003)

In this paper, the opening work on the development of a Lithuanian HMM speech recognition system is described. The triphone single-Gaussian HMM speech recognition system based on Mel Frequency Cepstral Coefficients (MFCC) was developed using HTK toolkit. Hidden Markov model's parameters were estimated from phone-level hand-annotated Lithuanian speech corpus. The system was evaluated on a speaker-independent <750 distinct isolated-word recognition task. Though the speaker adaptation and language modeling techniques were not used, the system was performing at 20% word error rate.
Local Similarity Solutions for Laminar Boundary Layer Flow along a Moving Cylinder in a Parallel Stream
Authors: Anuar Ishak, Roslinda Nazar, Ioan Pop
Venue: Computer Mathematics: 8th Asian Symposium, ASCM 2007, Singapore, December 15-17, 2007. Revised and Invited Papers (2008)

The present paper deals with a numerical method to analyze the axisymmetric boundary layer flow of a viscous and incompressible fluid along a static or moving cylinder, using local similarity approximation. Both parallel and reverse moving boundary to the free stream are considered. Local similarity solutions are obtained to show the effects of the velocity ratio parameter and the curvature parameter on the surface shear stress. The numerical results are comparable very well with the existing results available in the literature for some particular cases of the present problem. Moreover, the results indicate that dual solutions exist when the cylinder and the free stream move in opposite directions.
A study on different fault characteristics using wavelet and fast Fourier transforms
Authors: E. E. Ngu, K. Ramar, R. Montano, V. Cooray
Venue: Proceedings of the 7th WSEAS International Conference on Application of Electrical Engineering (2008)

An investigation on different types of faults namely: open-circuit (OC), short-circuit (SC), high impedance fault (HIF) and the fault caused by direct lightning strike (LS) on the transmission line has been done using Alternative Transient Program/ Electromagnetic Transient Program (ATP/EMTP) and MATLAB Toolbox. The characteristic of the faults in terms of their corresponding frequency spectrum, the polarity of incident- and reflected-wave from fault point, and the neighboring and/or remote end busbar signals has been studied and verified for the possibility to differentiate the type of fault occurred. For this purpose, the fault point on the wave has been created at the moment when the voltage signal reaches its peak and also when it is close to zero. Both, Wavelet Transform (WT) and Fast Fourier Transform (FFT) methods have been implemented in the study to extract and analyze the information associated with transient signal generated by the fault simulated at both, sending and receiving end busbars. Model of the network used in this study is taken from [1].
Analog Power Modelling
Authors: C. Svensson
Venue: Proceedings of the 17th international workshop on Integrated Circuit and System Design. Power and Timing Modeling, Optimization and Simulation (2007)

Digital power modelling is well developed today, through many years of active research. However analog power modelling lags behind. The aim of this paper is to discuss possible fundamentals of analog power modelling. Modelling is based on noise, precision, linearity, and process constraints. Simple elements as samplers, amplifiers and comparators are discussed. Analog-to-digital converters are used to compare predicted minimum power constraints with real circuits.
A New Method for Financial Performance Evaluation of Listed Power Enterprise
Authors: Dongxiao Niu, Weijun Wang, Zilong Qiu
Venue: Proceedings of the 2008 Second International Conference on Genetic and Evolutionary Computing (2008)

In order to evaluate the financial performance of listedpower enterprise, a new method is put forward based onthe fuzzy matter-element analysis and combined with themembership function of normal distribution, the conceptof Euclid approach degree, the theory of informationentropy. Regarding the listed power enterprise as theobjects of matter-element, and the compound fuzzymatter-element is constructed by the evaluation factorsand their fuzzy value of the object. Through calculatingEuclid approach degree between the fuzzy matter-elementand the standard fuzzy matter-element, so the level oflisted power enterprise’s financial achievement can bededuced. Finally, the feasibility and the effectiveness ofthe proposed method are verified by an empirical study.
A Workflow for the Networked Ontologies Lifecycle: A Case Study in FAO of the UN
Authors: Óscar Muñoz-García, Asunción Gómez-Pérez, Marta Iglesias-Sucasas, Soonho Kim
Venue: Current Topics in Artificial Intelligence: 12th Conference of the Spanish Association for Artificial Intelligence, CAEPIA 2007, Salamanca, Spain, November 12-16, 2007. Selected Papers (2007)

This document shows a preliminary framework for editing networked ontologies in the context of the NeOn project. The goal is to manage, in a collaborative way, multiple networked ontologies for large-scale semantic applications. This paper shows the main concepts on the editorial workflow and several lifecycle use cases. The ontologies produced with this framework will be used by the Food and Agriculture Organization of the United Nations (FAO) in many different large applications such the Fisheries Stock Depletion Assessment System[4]. Therefore a major goal for FAO is to have a strong and reliable ontology management system for editing the networked ontologies that applications will use as a basis. This framework for editing networked ontologies is being developed in the context of the NeOn Project. What we present here is a brief summary of the activities carried out in this project regarding user requirements and subsequent use case analysis.
Differential MFCC and Vector Quantization Used for Real-Time Speaker Recognition System
Authors: Chen Wang, Zhenjiang Miao, Xiao Meng
Venue: Proceedings of the 2008 Congress on Image and Signal Processing, Vol. 5 - Volume 05 (2008)

This paper makes some improvements on MFCC feature extraction and proposes a quick MFCC algorithm which is used for Real-Time Speaker Recognition System. Based on the quick MFCC algorithm, the paper uses Differential MFCC for feature extraction and Vector Quantization plus GMM model for classification to achieve a better result. It can meet the requirements of real-time system in case of the high precision. By comparing with the traditional MFCC algorithm, the quick MFCC algorithm reduces the run time greatly while maintaining recognition accuracy of the system. To prove it, this paper compares the quick MFCC algorithm with LPC and FFT. The experiment indicates that the EER of LPC is 14.4% and the EER of FFT is 12.5%, but by using the Quick MFCC the EER is 9.4% and the differential MFCC is only 6.9%.
A Facial Expression Recognition Approach Based on Novel Support Vector Machine Tree
Authors: Qinzhen Xu, Pinzheng Zhang, Luxi Yang, Wenjiang Pei, Zhenya He
Venue: Proceedings of the 4th international symposium on Neural Networks: Advances in Neural Networks, Part III (2007)

Automatic facial expression recognition is the kernel part of emotional information processing. This paper dedicates to develop an automatic facial expression recognition approach based on a novel support vector machine tree, which performs feature selection at each internal node, to improve recognition accuracy and robustness. After the Pseudo-Zernike moment features were extracted, they were used to train a support vector machine tree for automatic recognition. The structure of a support vector machine enables the model to divide the facial recognition problem into sub-problems according to the teacher signals, so that it can solve the sub-problems in decreased complexity in different tree levels. In the training phase, those sub-samples assigned to two internal sibling nodes perform decreasing confusion cross, thus, the generalization ability for recognition of facial expression is enhanced. The compared results on Cohn-Kanade facial expression database also show that the proposed approach appeared higher recognition accuracy and robustness than other approaches.