ppxscal/embedding_network huggingface dataset:
Real-time individualized virtual humans
Authors: Nadia Magnenat-Thalmann, Daniel Thalmann
Venue: ACM SIGGRAPH ASIA 2008 courses (2008)

This tutorial will present the latest techniques to model fast individualized animatable virtual humans for Real-Time applications. As a human is composed of a head and a body, we will analyze how these two parts can be modeled and globally animated as in real-life. More precisely, we will show how we can model and deform human bodies and heads. Facial animation will be also addressed from motion facial capture and voice to the simulation of interactive realistic talking virtual humans, including personality models and complete body gestures. We will describe how we can model crowds in realtime using dynamic meshes, static meshes and impostors. Techniques to introduce variety in crowds including individual animation with accessories will be explained.
Trust-Based Design and Check of FPGA Circuits Using Two-Level Randomized ECC Structures
Authors: Shantanu Dutt, Li Li
Venue: ACM Transactions on Reconfigurable Technology and Systems (TRETS) (2009)

A novel trust-based design method for FPGA circuits that uses error-correcting code (ECC) structures for detecting design tampers (changes, deletion of existing logic, and addition of extradesign logic-like Trojans) is proposed in this article. We determine ECC-based CLB (configuration logic block) parity groups and embed the check CLBs for each parity group in the FPGA circuit. During a trust-checking phase, a Test-Pattern Generator (TPG) and an Output Response Analyzer (ORA), configured in the FPGA, are used to check that each parity group of CLB outputs produce the expected parities. We use two levels of randomization to thwart attempts by an adversary to discover the parity groups and inject tampers that mask each other, or to tamper with the TPG and ORA so that design tampers remain undetected: (a) randomization of the mapping of the ECC parity groups to the CLB array; (b) randomization within each parity group of odd and even parities for different input combinations (classically, all ECC parity groups have even parities across all inputs). These randomizations along with the error-detecting property of the underlying ECC lead to design tampers being uncovered with very high probabilities, as we show both analytically and empirically. We also classify different CLB function structures and impose a parity group selection in which only similarly structured functions are randomly selected to be in the same parity group in order to minimize check function complexity. Using the 2D code as our underlying ECC and its 2-level randomization, our experiments with inserting 1-10 circuit CLB tampers and 1-5 extraneous logic CLBs in two medium-size circuits and a RISC processor circuit implemented on a Xilinx Spartan-3 FPGA show promising results of 100% tamper detection and 0% false alarms, obtained at a hardware overhead of only 7-10%.
EXCEL 2007 MACROS MADE EASY, 1 edition
Authors: Gail Perry
Venue: Made Easy Series (2008)

Get beyond the basics with Excel 2007 macrosNow you can take your Excel skills to the next level with help from this hands-on guide. Excel 2007 Macros Made Easy shows you how to create, run, and revise macros to simplify repetitive tasks and store the instructions for complicated ones. You'll learn to use Visual Basic for Applications (VBA), add macros to the Excel toolbar, and share your macros with other users. Discover how easy it is to develop custom macros, save time, and boost productivity. Record and edit macrosCreate and debug macros in VBASave macros to the Personal Macro Workbook or other workbooksCreate VBA subroutines and functionsDevelop interactive macrosFormat cells using macrosCreate variables and arraysApply logic to macros with If/Then/Else routinesUse loops to process dataAdd controls to your worksheets Table of contentsIntroductionChapter 1. Recording MacrosChapter 2. Editing MacrosChapter 3. Creating Macros in Visual BasicChapter 4. Storing MacrosChapter 5. Understanding Macro CommandsChapter 6. Using Visual Basic Subroutines and Creating FunctionsChapter 7. Creating Interactive MacrosChapter 8. Using Macros to Format CellsChapter 9. Using Variables in MacrosChapter 10. Creating If/Then/Else RoutinesChapter 11. Exploring LoopsChapter 12. Adding Controls to Your WorksheetsIndex
Prediction model building with clustering-launched classification and support vector machines in credit scoring
Authors: Shu-Ting Luo, Bor-Wen Cheng, Chun-Hung Hsieh
Venue: Expert Systems with Applications: An International Journal (2009)

Recently, credit scoring has become a very important task as credit cards are now widely used by customers. A method that can accurately predict credit scoring is greatly needed and good prediction techniques can help to predict credit more accurately. One powerful classifier, the support vector machine (SVM), was successfully applied to a wide range of domains. In recent years, researchers have applied the SVM-based in the prediction of credit scoring, and the results have been shown it to be effective. In this study, two real world credit datasets in the University of California Irvine Machine Learning Repository were selected. SVM and a new classifier, clustering-launched classification (CLC), were employed to predict the accuracy of credit scoring. The advantages of using CLC are that it can classify data efficiently and only need one parameter needs to be decided. In substance, the results show that CLC is better than SVM. Therefore, CLC is an effective tool to predict credit scoring.
A decision support system for detecting products missing from the shelf based on heuristic rules
Authors: Dimitrios Papakiriakopoulos, Katerina Pramatari, Georgios Doukidis
Venue: Decision Support Systems (2009)

The problem of products missing from the shelf is a major one in the grocery retail sector, as it leads to lost sales and decreased consumer loyalty. Yet, the possibilities for detecting and measuring an ''out-of-shelf'' situation are limited. In this paper we suggest the employment of machine-learning techniques in order to develop a rule-based Decision Support System for automatically detecting products that are not on the shelf based on sales and other data. Results up-to-now suggest that rules related with the detection of ''out-of-shelf'' products are characterized by acceptable levels of predictive accuracy and problem coverage.
Real-time anaesthesia diagnosis display system with multi-modal alarms
Authors: Ken Lee, Kyung Jean (Tyler) Yang, Beryl Plimmer, Michael Harrison
Venue: Proceedings of the 20th Australasian Conference on Computer-Human Interaction: Designing for Habitus and Habitat (2008)

Fatal errors during anaesthesia administration are usually preventable human mistakes. It is difficult for anaesthetists to keep monitoring every physiological change and to detect clinically critical events during anaesthesia. Intelligent patient monitoring systems to assist anaesthetists are under investigation. These systems require a distinctive and unique way of conveying alerts and diagnostic information to the anaesthetist in busy and noisy operating theatres. We present here a functional prototype of a multi-modal (audio & visual) alarm system, MMAS.
Plenary lecture II: image denoising: from multiresolution frameworks to variational frameworks
Authors: Sergio Amat
Venue: Proceedings of the 8th conference on Signal, Speech and image processing (2008)

In order to reduce the noise that perturb an image we can find two general approaches: Multiresolution frameworks and Variational frameworks. In the linear case, both frameworks are related. But this is not the best situation in practice. Our goal in this lecture is to review some nonlinear techniques in both framewors and their relations.
Finite mixture of α-stable distributions
Authors: Diego Salas-Gonzalez, Ercan E. Kuruoglu, Diego P. Ruiz
Venue: Digital Signal Processing (2009)

Over the last decades, the @a-stable distribution has proved to be a very efficient model for impulsive data. In this paper, we propose an extension of stable distributions, namely mixture of @a-stable distributions to model multimodal, skewed and impulsive data. A fully Bayesian framework is presented for the estimation of the stable density parameters and the mixture parameters. As opposed to most previous work on mixture models, the model order is assumed unknown and is estimated using reversible jump Markov chain Monte Carlo. It is important to note that the Gaussian mixture model is a special case of the presented model which provides additional flexibility to model skewed and impulsive phenomena. The algorithm is tested using synthetic and real data, accurately estimating @a-stable parameters, mixture coefficients and the number of components in the mixture.
Business failure prediction model based on grey prediction and rough set theory
Authors: Jao-Hong Cheng, Huei-Ping Chen, Kai-Lun Cheng
Venue: WSEAS Transactions on Information Science and Applications (2009)

A lot of methods have been used in the past for the prediction of failure business like Discriminant analysis, Logit analysis, Quadratic Function etc. Although some of these methods lead to models with a satisfactory ability to discriminate between healthy and bankrupt, they endure some limitations, often due to the unrealistic assumption of statistical hypotheses. This is why we have undertaken a hybrid advisable system aiming at weakening these limitations. A hybrid model that predicts the failure firms based on the past financial performance data, combining grey prediction and rough set approach is possible to predict using few data and quickly calculate. The results are very encouraging, compared with original rough set, and prove the usefulness and highlight the effectiveness of the proposed method for firm failure prediction.
Provably secure RSA-type signature based on conic curve
Authors: Xiaolei Dong, Haifeng Qian, Zhenfu Cao
Venue: Wireless Communications Mobile Computing (2009)

In electronic communication and wireless communication, message authentication should be necessary. However, traditional method message authentication code (MAC) employs a symmetric cryptographical technique and it needs to keep a shared private key between two parties. For convenience, people now begins to use public key techniques to provide message authentication. In wireless communication, we shall save more space for message itself because of the limited resources. Therefore, we believe that our proposed digital signature scheme will be more fitful for this kind of communication due to the following merits: (1) in addition to inheriting the merits of RSA signature such as high verification efficiency, the proposed scheme also shows its advantage over RSA by resisting low public key exponent attack; (2) comparing with 1024 bits RSA, our digital signature scheme can sign 2048-bit long message once, and generate a signature with 1025 bits length which doubles the capacity of the 1024-bit RSA signature; (3) the scheme is provably secure and its security is tightly related to the hardness of conic-based (CB)-RSA assumption. Copyright &copy; 2008 John Wiley & Sons, Ltd.
UWB Channel Measurement and Data Analysis in Offshore Oil Platform
Authors: Hong Li, Meng Juan, Li ShuRong, Zhou Zhen
Venue: Proceedings of the 2009 WRI International Conference on Communications and Mobile Computing - Volume 01 (2009)

This paper presents the ultra-wideband (UWB) channel measurements conducted in an offshore oil platform working base of ShenLi oil field. The measurements are done with a vector network analyzer (VNA) in the frequency band of 3-10GHz both in line-of-sight (LOS) and non-line-of-sight (NLOS) scenarios to characterize the path loss and small-scale fading statistics. The multiple scatter clusters are caused by the special nature of the environment, for NLOS with large distance, the maximum of the multipath components is several tens of nanoseconds after the arrival of the first component. The measuement data approximately can be fitted to S-V model, and some modifications are made to provide excellent fit: ray power decay constants depend on delay with a linear relationship,and total power of 50 bins in a cluster fit to an exponential function of delay. Channel characteristics including the distance and frequency dependency of path loss,power delay profile,small-scale fading distribution are examined.The small-scale fading fits to m-Nakagami distribution with m-parameter range from 0.8-1.1. The results are helpful to model the the UWB propagation channel in such environment.
The Future of Software: Adaptation and Dependability
Authors: Paola Inverardi, Massimo Tivoli
Venue: Software Engineering: International Summer Schools, ISSSE 2006-2008, Salerno, Italy, Revised Tutorial Lectures (2009)

Software in the near ubiquitous future (Softure) will need to cope with variability, as software systems get deployed on an increasingly large diversity of computing platforms and operates in different execution environments. Heterogeneity of the underlying communication and computing infrastructure, mobility inducing changes to the execution environments and therefore changes to the availability of resources and continuously evolving requirements require software systems to be adaptable according to the context changes. Softure should also be reliable and meet the users performance requirements and needs. Moreover, due to its pervasiveness and in order to make adaptation effective and successful, adaptation must be considered in conjunction with dependability, i.e., no matter what adaptation is performed, the system must continue to guarantee a certain degree of Quality of Service (QoS). Hence, Softure must also be dependable, which is made more complex given the highly dynamic nature of service provision. Supporting the development and execution of Softure systems raises numerous challenges that involve languages, methods and tools for the systems thorough design and validation in order to ensure dependability of the self-adaptive systems that are targeted. However these challenges, taken in isolation are not new in the software domain. In this paper we will discuss some of these challenges and possible solutions making reference to the approach undertaken in the IST PLASTIC project for a specific instance of Softure focused on software for Beyond 3G (B3G) networks.
Weak-Key Classes of 7-Round MISTY 1 and 2 for Related-Key Amplified Boomerang Attacks
Authors: Eunjin Lee, Jongsung Kim, Deukjo Hong, Changhoon Lee, Jaechul Sung, Seokhie Hong, Jongin Lim
Venue: IEICE Transactions on Fundamentals of Electronics, Communications and Computer Sciences (2008)

In 1997, M. Matsui proposed secret-key cryptosystems called MISTY 1 and MISTY 2, which are 8-and 12-round block ciphers with a 64-bit block, and a 128-bit key. They are designed based on the principle of provable security against differential and linear cryptanalysis. In this paper we present large collections of weak-key classes encompassing 273 and 270 weak keys for 7-round MISTY 1 and 2 for which they are vulnerable to a related-key amplified boomerang attack. Under our weak-key assumptions, the related-key amplified boomerang attack can be applied to 7-round MISTY 1 and 2 with 254, 256 chosen plaintexts and 255.3 7-round MISTY 1 encryptions, 265 7-round MISTY 2 encryptions, respectively.
A 3D Flexible and Tangible Magic Lens in Augmented Reality
Authors: Julian Looser, Raphael Grasset, Mark Billinghurst
Venue: Proceedings of the 2007 6th IEEE and ACM International Symposium on Mixed and Augmented Reality (2007)

The Magic Lens concept is a focus and context technique which facilitates the visualization of complex and dense data. In this paper, we propose a new type of 3D tangible Magic Lens in the form of a flexible sheet. We describe new interaction techniques associated with this tool, and demonstrate how it can be applied in different AR applications.
Load prediction using hybrid model for computational grid
Authors: Yongwei Wu, Yulai Yuan, Guangwen Yang, Weimin Zheng
Venue: Proceedings of the 8th IEEE/ACM International Conference on Grid Computing (2007)

Due to the dynamic nature of grid environments, schedule algorithms always need assistance of a long-time-ahead load prediction to make decisions on how to use grid resources efficiently. In this paper, we present and evaluate a new hybrid model, which predicts the n-step-ahead load status by using interval values. This model integrates autoregressive (AR) model with confidence interval estimations to forecast the future load of a system. Meanwhile, two filtering technologies from signal processing field are also introduced into this model to eliminate data noise and enhance prediction accuracy. The results of experiments conducted on a real grid environment demonstrate that this new model is more capable of predicting n-step-ahead load in a computational grid than previous works. The proposed hybrid model performs well on prediction advance time for up to 50 minutes, with significant less prediction errors than conventional AR model. It also achieves an interval length acceptable for task scheduler.
Multicriteria decisions on interdependent infrastructure transportation projects using an evolutionary-based framework
Authors: Juan Gaytán Iniestra, Javier García Gutiérrez
Venue: Applied Soft Computing (2009)

When evaluating transportation infrastructure projects and determining which of them will be carried out from a set of projects and given a budget constraint, several criteria need to be considered in the decision. Standard evaluation practices imply the aggregation of impacts into one utility function which is later optimized. Nevertheless these techniques used for translation of different measuring units into monetary terms are highly controversial. Multicriteria techniques can explicitly deal with different measuring units, however, they are not suitable to model interdependence relationships of projects that share a common characteristic (same route, location or target population, for instance). In this research we model this transportation planning problem, the multi-objective transportation infrastructure project selection problem (MTIPSP), as a constrained multi-objective optimization problem with quadratic objective functions, using a variation of the multi-objective 0-1 knapsack problem plus some additional constraints. Given the combinatorial nature of the problem, an evolutionary-based framework is used for the identification of Pareto solutions, and later, those with non-attractive properties are filtered using a Knee Identification Procedure. The final selection of the projects portfolio is made using a well known multicriteria decision aid method and including the decision makers' preferences based on the existing context.
Creating a spoken impact: encouraging vocalization through audio visual feedback in children with ASD
Authors: Joshua Hailpern, Karrie Karahalios, James Halle
Venue: Proceedings of the 27th international conference on Human factors in computing systems (2009)

One hallmark difficulty of children with Autism Spectrum Disorder (ASD) centers on communication and speech. Research into computer visualizations of voice has been shown to influence conversational patterns and allow users to reflect upon their speech. In this paper, we present the Spoken Impact Project (SIP), an effort to examine the effect of audio and visual feedback on vocalizations in low-functioning children with ASD by providing them with additional means of understanding and exploring their voice. This research spans over 12 months, including the creation of multiple software packages and detailed analysis of more than 20 hours of experimental video. SIP demonstrates the potential of computer generated audio and visual feedback to encourage vocalizations of children with ASD.
A high-order incompressible flow solver with WENO
Authors: Ju Zhang, Thomas L. Jackson
Venue: Journal of Computational Physics (2009)

A numerical method for solving the incompressible Navier-Stokes equations with a 5th-order weighted essentially non-oscillatory (WENO) scheme is presented. The method is not based on artificial compressibility and is free of tunable parameters such as the artificial compressibility parameter. The method makes use of the fractional-step method in conjunction with the low-dissipation and low-dispersion Runge-Kutta (LDDRK) scheme to improve temporal accuracy of the scheme. The use of a WENO scheme makes it possible to obtain stable solutions for discontinuous initial data and resolve difficult applications with strong shear such as Kelvin-Helmholtz instability or turbulence. Good convergence rate is established for the velocity variables and numerical solutions of the present method compare well with exact solutions and other numerical results.
Towards automating overlay network management
Authors: I. Al-Oqily, A. Karmouch
Venue: Journal of Network and Computer Applications (2009)

Overlay networks are becoming widely used for content delivery because they provide effective and reliable services that are not otherwise available. However, they can negatively affect each other as well as the underlying network. A management system that controls and adapts their behavior is therefore needed. This will meet not only the specific demands of the users but also those of the network and service providers. This paper presents a novel approach to the issue of automating overlay network management. In contrast to existing management approaches which require static a priori policy configurations, policies are created dynamically. A policy layer consists of a set of policy enforcement points and policy decision points. This is used to capture the goals of users, services, and networks into network-level objectives. The behavior of the overlay network is adapted to the changing conditions in its environment. The creation, adaptation, and termination of overlays are achieved through policies. Policies are generated and enforced on the fly from the context information of the user, the network and the service provider. The new approach provides users and applications with more flexibility to dynamically change their quality-of-service requirements while maintaining smooth quality-of-service delivery. We show the advantages of our architecture and provide simulation results to verify its effectiveness.
Analyzing Fixed and Mobile Convergence Services in China
Authors: Yunping Liu, Xiongjian Liang
Venue: Proceedings of the 2009 WRI International Conference on Communications and Mobile Computing - Volume 03 (2009)

Regrouping of China operators gives the light of FMC services. Owing to the technology advantages and competition compelling, all services from mobile and fixed networks together will give new operator competition power growing chance. In this paper, we will give some reasons and analyses.
A Two-Microphone Noise Reduction Method in Highly Non-stationary Multiple-Noise-Source Environments
Authors: Junfeng Li, Masato Akagi, Yôiti Suzuki
Venue: IEICE Transactions on Fundamentals of Electronics, Communications and Computer Sciences (2008)

In this paper, we propose a two-microphone noise reduction method to deal with non-stationary interfering noises in multiple-noise-source environments in which the traditional two-microphone algorithms cannot function well. In the proposed algorithm, multiple interfering noise sources are regarded as one virtually integrated noise source in each subband, and the spectrum of the integrated noise is then estimated using its virtual direction of arrival. To do this, we suggest a direction finder for the integrated noise using only two microphones that performs well even in speech active periods. The noise spectrum estimate is further improved by integrating a single-channel noise estimation approach and then subtracted from that of the noisy signal, finally enhancing the desired target signal. The performance of the proposed algorithm is evaluated and compared with the traditional algorithms in various conditions. Experimental results demonstrate that the proposed algorithm outperforms the traditional algorithms in various conditions in terms of objective and subjective speech quality measures.