ppxscal/embedding_network huggingface dataset:
Effective decision-theoretic assistance through relational hierarchical models
Authors: Sriraam Natarajan
Venue:  (2007)

Building intelligent computer assistants has been a long-cherished goal of AI. Many intelligent assistant systems were built and fine-tuned to specific application domains. In this work, we develop a general model of assistance that combines three powerful ideas: decision theory, hierarchical task models and probabilistic relational languages. We use the principles of decision theory to model the general problem of intelligent assistance. We use a combination of hierarchical task models and probabilistic relational languages to specify prior knowledge of the computer assistant. The assistant exploits its prior knowledge to infer the user&rsquo;s goals and takes actions to assist the user. We evaluate the decision theoretic assistance model in three different domains including a real-world domain to demonstrate its generality. We show through experiments that both the hierarchical structure of the goals and the parameter sharing facilitated by relational models significantly improve the learning speed of the agent. Finally, we present the results of deploying our relational hierarchical model in a real-world activity recognition task.
Constant-Round Password-Based Authenticated Key Exchange Protocol for Dynamic Groups
Authors: Shuhua Wu, Yuefei Zhu
Venue: Financial Cryptography and Data Security: 12th International Conference, FC 2008, Cozumel, Mexico, January 28-31, 2008. Revised Selected Papers (2008)

In this paper, we extend the work of Abdalla et al. to take into account the notion of dynamicity in the membership and present an improved compiler that transforms any provably secure password-based authenticated 2-party key exchange into a more attractive password-based authenticated group key exchange. The resulting protocol is a provably secure and efficient dynamic password-based authenticated group key exchange protocol in a constant number of rounds. To the best of our knowledge, our proposal is the first solution to design constant-round password-based authenticated group key exchange protocols for dynamic groups. Furthermore, its security result does not assume the Random Oracle model or the ideal cipher model.
A genetic algorithm based strategy for redundancy resolution with multiple criteria
Authors: Cornel Secara
Venue: Proceedings of the 9th WSEAS International Conference on International Conference on Automation and Information (2008)

Redundancy of a serial manipulator means that more joints than necessary are available in order to achieve a specified task of the manipulator end-effector. Manipulators are thus allowed to achieve complex tasks by taking into account additional constraints. This paper presents a genetic algorithm based strategy for redundancy resolution with two performance criteria accomplishment, while the end-effector achieves a number of prescribed configurations. The additional constraints added to the main end-effector task are obstacle avoidance and minimization of the sum of joint displacements. The strategy variables are the manipulator base location and the joint configuration adequate to every prescribed end-effector configuration. The strategy is realized using Matlab program with genetic algorithm tool and the illustrative simulations are obtained for a planar redundant manipulator with four degrees of freedom that achieve five different end-effector configurations, while the two performance criteria are accomplished.
A novel ensemble of classifiers for microarray data classification
Authors: Yuehui Chen, Yaou Zhao
Venue: Applied Soft Computing (2008)

Micorarray data are often extremely asymmetric in dimensionality, such as thousands or even tens of thousands of genes and a few hundreds of samples. Such extreme asymmetry between the dimensionality of genes and samples presents several challenges to conventional clustering and classification methods. In this paper, a novel ensemble method is proposed. Firstly, in order to extract useful features and reduce dimensionality, different feature selection methods such as correlation analysis, Fisher-ratio is used to form different feature subsets. Then a pool of candidate base classifiers is generated to learn the subsets which are re-sampling from the different feature subsets with PSO (Particle Swarm Optimization) algorithm. At last, appropriate classifiers are selected to construct the classification committee using EDAs (Estimation of Distribution Algorithms). Experiments show that the proposed method produces the best recognition rates on four benchmark databases.
Rapid-Response Replication: A Fault Tolerant Algorithm Based on Active Replication
Authors: Lingxia Liu, Jingbo Xia, Zhiqiang Ma, Ruixin Li
Venue: Proceedings of the 7th international conference on Computational Science, Part III: ICCS 2007 (2007)

To the wide area network oriented distributed computing, a slow service is equivalent to an unavailable service. It makes demands of effectively improving the performance of the replication algorithms without damaging the availability. Aim for improving the performance of the active replication algorithm, we propose a new replication algorithm named RRR (Rapid Response Replication). Its basic idea is: all replicas receive request, but only the fastest one sends back the response to the client after it handles the request. Its main advantages are: (1) In the algorithm, the response is sent back directly by the fastest replica after it handles the request; (2) The algorithm avoids agreement; (3) The algorithm avoids the redundant nested invocation problem (the problem may be arisen while using active replication).
Access to Archival Finding Aids: Context Matters
Authors: Junte Zhang, Khairun Nisa Fachry, Jaap Kamps
Venue: Proceedings of the 12th European conference on Research and Advanced Technology for Digital Libraries (2008)

We detail the design of a search engine for archival finding aids based on an XML database system. The resulting system shows results--which can vary in granularity from individual archival items to the whole fonds--within the context of the archive. The presentation preserves the archival structure by providing important contextual information, and all individual results can be "clicked", warping the user to the full finding aid with the selected part in focus.
Brief paper: Further results on input-to-state stability for nonlinear systems with delayed feedbacks
Authors: Frédéric Mazenc, Michael Malisoff, Zongli Lin
Venue: Automatica (Journal of IFAC) (2008)

We consider a class of nonlinear control systems for which stabilizing feedbacks and corresponding Lyapunov functions for the closed-loop systems are available. In the presence of feedback delays and actuator errors, we explicitly construct input-to-state stability (ISS) Lyapunov-Krasovskii functionals for the resulting feedback delayed dynamics, in terms of the available Lyapunov functions for the original undelayed dynamics, which establishes that the closed-loop systems are input-to-state stable (ISS) with respect to actuator errors. We illustrate our results using a generalized system from identification theory and other examples.
Automatic Extraction of Proximal Femur Contours from Calibrated X-Ray Images Using 3D Statistical Models
Authors: Xiao Dong, Guoyan Zheng
Venue: Proceedings of the 4th international workshop on Medical Imaging and Augmented Reality (2008)

Automatic identification and extraction of bone contours from x-ray images is the first essential task for further medical image analysis. In this paper we propose a 3D statistical model based framework for the proximal femur contour extraction from calibrated x-ray images. The initialization is solved by an Estimation of Bayesian Network Algorithm to fit a multiple component geometrical model to the x-ray data. The contour extraction is accomplished by a non-rigid 2D/3D registration between a 3D statistical model and the x-ray images, in which bone contours are extracted by a graphical model based Bayesian inference. Our experimental results demonstrate its performance and efficacy even when part of the images are occluded.
Scheduling in a dynamic heterogeneous distributed system using estimation error
Authors: Andrew J. Page, Thomas M. Keane, Thomas J. Naughton
Venue: Journal of Parallel and Distributed Computing (2008)

In real-world dynamic heterogeneous distributed systems, allocating tasks to processors can be an inefficient process, due to the dynamic nature of the resources, and the tasks to be processed. The information about these tasks and resources is not known a priori, and thus must be estimated online. We utilize the accuracy of these estimates, and when combined with different objectives, such as minimizing makespan and evenly distributing load, naturally gives rise to a family of four different scheduling algorithms. The algorithms have been implemented on a real-world heterogeneous distributed system with up to 90 processors. A set of real-world problems from the areas of cryptography, bioinformatics, and biomedical engineering were used as a test-set to measure the effectiveness of the scheduling algorithms. We have found that considering estimation error when allocating tasks to processors can provide more efficient solutions, than when estimation error is not considered. We have found that using a simple heuristic, combined with estimation error, can in some cases provide solutions approaching the efficiency of complicated well-known evolutionary algorithms.
Fuzzy Support Vector Machine for EMG Pattern Recognition and Myoelectrical Prosthesis Control
Authors: Lingling Chen, Peng Yang, Xiaoyun Xu, Xin Guo, Xueping Zhang
Venue: Proceedings of the 4th international symposium on Neural Networks: Part II--Advances in Neural Networks (2007)

For the optional control to the trans-femoral prosthesis and natural gait, an ongoing investigation of lower limb prosthesis model with myoelectrical control was presented. In this research, the surface electromyographic signals of lower limb were extracted to be switch signal, and translate into movement information. Considering every muscle's different physiologic tendency, fuzzy support vector regression method was applied to establish an intelligent black box that can interpret the physiological signals to accurate information of knee joint angle. It achieves a comparable or better performance than other methods, and provides a more native gait to the prosthesis user.
A model of contingent planning for agent programming languages
Authors: Yves Lespérance, Giuseppe De Giacomo, Atalay Nafi Ozgovde
Venue: Proceedings of the 7th international joint conference on Autonomous agents and multiagent systems - Volume 1 (2008)

In this paper, we develop a formal model of planning for an agent that is operating in a dynamic and incompletely known environment. We assume that both the agent's task and the behavior of the agents in the environment are expressed as high-level nondeterministic concurrent programs in some agent programming language (APL). In this context, planning must produce a deterministic conditional plan for the agent that can be successfully executed against all possible executions of the environment program. We handle actions with nondeterministic effects, as well as sensing actions, by treating them as actions that trigger an environmental reaction that is not under the planning agent's control. Our model of contingent planning is specified for a generic APL with a transition semantics. Within this model, we devise a general procedure for computing the contingent plans. We also show how the model can be instantiated in the situation calculus with programs for the agent and the environment expressed in ConGolog, and we describe an implementation of the planning mechanism in this case.
Topology and arrangement computation of semi-algebraic planar curves
Authors: L. Alberti, B. Mourrain, J. Wintz
Venue: Computer Aided Geometric Design (2008)

We describe a new subdivision method to efficiently compute the topology and the arrangement of implicit planar curves. We emphasize that the output topology and arrangement are guaranteed to be correct. Although we focus on the implicit case, the algorithm can also treat parametric or piecewise linear curves without much additional work and no theoretical difficulties. The method isolates singular points from regular parts and deals with them independently. The topology near singular points is guaranteed through topological degree computation. In either case the topology inside regions is recovered from information on the boundary of a cell of the subdivision. Obtained regions are segmented to provide an efficient insertion operation while dynamically maintaining an arrangement structure. We use enveloping techniques of the polynomial represented in the Bernstein basis to achieve both efficiency and certification. It is finally shown on examples that this algorithm is able to handle curves defined by high degree polynomials with large coefficients, to identify regions of interest and use the resulting structure for either efficient rendering of implicit curves, point localization or boolean operation computation.
Predictive Modeling with Echo State Networks
Authors: Michal Čerňanský, Peter Tiňo
Venue: Proceedings of the 18th international conference on Artificial Neural Networks, Part I (2008)

A lot of attention is now being focused on connectionist models known under the name "reservoir computing". The most prominent example of these approaches is a recurrent neural network architecture called an echo state network (ESN). ESNs were successfully applied in several time series modeling tasks and according to the authors they performed exceptionally well. Multiple enhancements to standard ESN were proposed in the literature. In this paper we follow the opposite direction by suggesting several simplifications to the original ESN architecture. ESN reservoir features contractive dynamics resulting from its' initialization with small weights. Sometimes it serves just as a simple memory of inputs and provides only negligible "extra-value" over much simple methods. We experimentally support this claim and we show that many tasks modeled by ESNs can be handled with much simple approaches.
Spatial Weighed Element Based FEM Incorporating a Priori Information on Bioluminescence Tomography
Authors: Jin Shi, Jie Tian, Min Xu, Wei Yang
Venue: Proceedings of the 11th international conference on Medical Image Computing and Computer-Assisted Intervention - Part I (2008)

Bioluminescence tomography (BLT) is a promising imaging technique which may dynamically and real-timely detect the molecular and cellular activity at the whole-body level in small animal studies. In view of the ill-posedness of the BLT, it is hard to fully reconstruct source density. In addition, the uniqueness theorem on BLT indicates that it is important to employ a priori information for accurate source reconstruction. Hence, we adopt diffuse optical tomography (DOT) technique to provide optical parameters of main tissues as a priori information. Besides, we restrict the range of real source to a permissible region to raise the numerical stability and reduce the ill-posedness of BLT. Next, we forward Spatial Weighed Element based Finite Element Method and compare it's solutions with analytic formula and MOSE. Numerical simulation of homogeneous and heterogeneous phantom demonstrates the source location and density with prior information is better than that not using a priori information.
Real-Time Analysis of Sensory Dissonance
Authors: John Maccallum, Aaron Einbond
Venue: Computer Music Modeling and Retrieval. Sense of Sounds: 4th International Symposium, CMMR 2007, Copenhagen, Denmark, August 27-31, 2007. Revised Papers (2008)

We describe a tool for real-time musical analysis based on a measure of roughness, the principal element of sensory dissonance. While most historical musical analysis is based on the notated score, our tool permits analysis of a recorded or live audio signal in its full complexity. We proceed from the work of Richard Parncutt and Ernst Terhardt, extending their algorithms for the psychoacoustic analysis of harmony to be used for the live analysis of spectral data. This allows for the study of a wider variety of timbrally-rich acoustic or electronic sounds which was not possible with previous algorithms. Further, the direct treatment of audio signal facilitates a wide range of analytical applications, from the comparison of multiple recordings of the same musical work to the real-time analysis of a live performance. Our algorithm is programmed in C as an external object for the program Max/MSP.Taking musical examples by Arnold Schoenberg, Gérard Grisey and Iannis Xenakis, our algorithm yields varying roughness estimates depending on instrumental orchestration or electronic texture, confirming our intuitive understanding that timbre affects sensory dissonance. This is one of the many possibilities this tool presents for analysis and composition of music that is timbrally-dynamic and microtonally-complex.
"More Like This" or "Not for Me": Delivering Personalised Recommendations in Multi-user Environments
Authors: David Bonnefoy, Makram Bouzid, Nicolas Lhuillier, Kevin Mercer
Venue: Proceedings of the 11th international conference on User Modeling (2007)

The television as a multi-user device presents some specificities with respect to personalisation. Recommendations should be provided both per-viewers as well as for a group. Recognising the inadequacy of traditional user modelling techniques with the constraint of television's lazy watching usage patterns, this paper presents a new recommendation mechanism based on anonymous user preferences and dynamic filtering of recommendations. Results from an initial user study indicate this mechanism was able to provide content recommendations to individual users within a multi-user environment with a high level of user satisfaction and without the need for user authentication or individual preference profile creation.
Using fuzzy and grey theory to improve green design in QFD processes
Authors: Chih-Hung Hsu, Tzu-Yuan Lee, Wei-Yin Lu, Jun-Jia Lin, Hai-Fen Lin
Venue: Proceedings of the 9th WSEAS International Conference on Fuzzy Systems (2008)

The green life cycle design is critical issue for improving bicycle design. Quality function deployment has been successfully applied in a number of fields. However, little study has been done in the integrated approach involving grey relational analysis, fuzzy integral, fuzzy theory of analyzing the necessary quality characteristics for the bicycle design in the design process. The proposed method transforms the process design, usage, package, and abortion in different stages into product's design characteristics applying techniques form grey relational analysis, fuzzy integral, fuzzy theory to insight the voices of customers. Questionnaire is used to get the necessary data in this study. The results showed that the important attributes for consumers. Several important and unimportant technical characteristics and customer attributes were identified and analyzed. The results of this study can provide an effective procedure for improving product's design characteristics, enhancing customer satisfaction and green design for bicycle in the marketplace.
Multidimensional upwinding for incompressible flows based on characteristics
Authors: Kamiar Zamzamian, Seyed Esmail Razavi
Venue: Journal of Computational Physics (2008)

In this paper, the multidimensional characteristic based upwind scheme (MCB) which has been recently introduced by the authors is applied to two another benchmark problems namely flow in a channel with a backward facing step and two-dimensional steady and unsteady flows past a circular cylinder. Extension of MCB scheme for calculating convective fluxes on non-Cartesian grids is presented here. For the flow over backward facing step, obtained results were compared against well-known experimental data and the results show high accuracy of MCB scheme and faster convergence rate with respect to conventional CB scheme. In the case of flow over circular cylinder, the flow at steady and transient regimes is investigated by MCB scheme. Again, the results obtained by MCB are compared to the other results in the literature and show good agreement with them. Also, rapid convergence rate of MCB was observed in this case too. It is concluded that, the genuinely multidimensional characteristic based (MCB) scheme, has been introduced earlier by the authors, is a robust and powerful scheme for modeling incompressible viscous flows for achieving the high accuracy and remarkable advantage in convergence rate with respect to conventional characteristic based schemes.
Authentication mechanisms for open distributed systems
Authors: David Mazieres, Victor Shoup
Venue:  (2007)

While authentication within organizations is a well-understood problem, traditional solutions are often inadequate at the scale of the Internet, where the lack of a central authority, the open nature of the systems, and issues such as privacy and anonymity create new challenges. For example, users typically establish dozens of web accounts with independently administered services under a single password, which increases the likelihood of exposure of their credentials; users wish to receive email from anyone who is not a spammer, but the openness of the email infrastructure makes it hard to authenticate legitimate senders; users may have a rightful expectation of privacy when viewing widely-accessed protected resources such as premium website content, yet they are commonly required to present identifying login credentials, which permits tracking of their access patterns. This dissertation describes enhanced authentication mechanisms to tackle the challenges of each of the above settings. Specifically, the dissertation develops: (1) a remote authentication architecture that lets users recover easily in case of password compromise; (2) a social network-based email system in which users can authenticate themselves as trusted senders without disclosing all their social contacts; and (3) a group access-control scheme where requests can be monitored while affording a degree of anonymity to the group member performing the request. The proposed constructions combine system designs and novel cryptographic techniques to address their respective security and privacy requirements both effectively and efficiently.
A rigorous approach towards test case generation
Authors: Zuohua Ding, Kao Zhang, Jueliang Hu
Venue: Information Sciences: an International Journal (2008)

This paper presents a method to generate test cases for sequential programs and concurrent programs written in a flow based program language. Test cases of sequential programs are generated based on condition calculation, and can be combined together to form SYN-sequences for concurrent program testing. Semantics of the language provides an infrastructure for the test case generation, and thus our method may be considered as a rigorous and systematic approach to the program testing. Compared with some formal testing methods, our method can avoid hitting state explosion problem in the test formation. Besides, the complexity analysis reveals that our method is time saving. Our method has been applied to generate test cases for PPP over ATM, a subsystem of IAD that runs data and voice over DSL.