ppxscal/embedding_network huggingface dataset:
Molecular beam epitaxy passivation studies of Ge and III-V semiconductors for advanced CMOS
Authors: C. Merckling, J. Penaud, D. Kohen, F. Bellenger, A. Alian, G. Brammertz, M. El-Kazzi, M. Houssa, J. Dekoster, M. Caymax, M. Meuris, M. M. Heyns
Venue: Microelectronic Engineering (2009)

Future CMOS technologies will require the use of substrate material with a very high mobility in order to fulfil the performance requirements. Therefore, combination of Ge p-MOS with n-MOS devices made out of high mobility III/V compounds, such as GaAs, has recently received some attention for its possible use in advanced CMOS applications. In this work, the physical, chemical and electrical properties of Al"2O"3 high-@k oxide deposited on Ge and GaAs, using Molecular Beam Deposition (MBD) technique, have been investigated.
Learning Models for Aligning Protein Sequences with Predicted Secondary Structure
Authors: Eagu Kim, Travis Wheeler, John Kececioglu
Venue: Proceedings of the 13th Annual International Conference on Research in Computational Molecular Biology (2009)

Accurately aligning distant protein sequences is notoriously difficult. A recent approach to improving alignment accuracy is to use additional information such as predicted secondary structure. We introduce several new models for scoring alignments of protein sequences with predicted secondary structure, which use the predictions and their confidences to modify both the substitution and gap cost functions. We present efficient algorithms for computing optimal pairwise alignments under these models, all of which run in near-quadratic time. We also review an approach to learning the values of the parameters in these models called inverse alignment. We then evaluate the accuracy of these models by studying how well an optimal alignment under the model recovers known benchmark reference alignments. Our experiments show that using parameters learned by inverse alignment, these new secondary-structure-based models provide a significant improvement in alignment accuracy for distant sequences. The best model improves upon the accuracy of the standard sequence alignment model for pairwise alignment by as much as 15% for sequences with less than 25% identity, and improves the accuracy of multiple alignment by 20% for difficult benchmarks whose average accuracy under standard tools is less than 40%.
Mapping life events: temporal and geographic context for biographical information
Authors: Ray R. Larson, Ryan Shaw
Venue: Proceedings of the 9th ACM/IEEE-CS joint conference on Digital libraries (2009)

Digital Libraries often fail to connect their contents to the wider context of information resources available that are about the same persons, related persons, places, or time periods and the events that happen to those persons, at those places and in a given time period. This demostration will show prototype systems that can perform these tasks, linking the user to relevant contextual information.
Finite difference methods with intrinsic parallelism for parabolic equations
Authors: Bin Zheng, Qinghua Feng
Venue: WSEAS Transactions on Mathematics (2009)

Based on eight saul'yev asymmetry schemes and the concept of domain decomposition, a class of finite difference method (AGE) with intrinsic parallelism for 1D diffusion equations is constructed. Stability analysis for the method is done. We also pay attention to the implementation of the parallel algorithms for 2D convection-diffusion equations. Based on another group of saul'yev asymmetry schemes and the Crank-Nicolson scheme we construct a class of alternating group explicit Crank-Nicolson method(AGEC-N). Both of the present methods are suitable for parallel computation. Stability analysis are also given. In order to verify the methods, we present several numerical examples at the end of the paper. Results of numerical examples show all the methods are of high accuracy.
Topic-link LDA: joint models of topic and author community
Authors: Yan Liu, Alexandru Niculescu-Mizil, Wojciech Gryc
Venue: Proceedings of the 26th Annual International Conference on Machine Learning (2009)

Given a large-scale linked document collection, such as a collection of blog posts or a research literature archive, there are two fundamental problems that have generated a lot of interest in the research community. One is to identify a set of high-level topics covered by the documents in the collection; the other is to uncover and analyze the social network of the authors of the documents. So far these problems have been viewed as separate problems and considered independently from each other. In this paper we argue that these two problems are in fact inter-dependent and should be addressed together. We develop a Bayesian hierarchical approach that performs topic modeling and author community discovery in one unified framework. The effectiveness of our model is demonstrated on two blog data sets in different domains and one research paper citation data from CiteSeer.
Research on current amplifier with current conveyor active loads
Authors: Luiza Grigorescu
Venue: Proceedings of the 3rd WSEAS international symposium on Wavelets theory and applications in applied mathematics, signal processing & modern science (2009)

Based on the translinearity principle there are methods in place to synthesise any nonlinear function by means of translinear circuits. On of these is the Current Amplifier with Current Conveyor Active Loads presented in this paper. The practical implementation of this design allowed the measurement of experimental data showing the gain variation for the amplifier. Several important conclusions have been drawned from these studies and they will be presented.
An intelligent functional link artificial neural network for channel equalization
Authors: Ravi Kumar Jatoth, M. S. B. Saithej Vaddadi, Saladi S. V. K. K. Anoop
Venue: Proceedings of the 8th WSEAS international conference on Signal processing, robotics and automation (2009)

One of the classical signal processing problems is the distortion of the transmitted signal by the channel before reaching the receiver. Channel Equalization is the solution for the so called problem. Practically all channels are non-linear and so there is necessity for non-linear channel equalization. Artificial Neural Network models are more preferable as equalizers because of their capable performance in handling non-linear tasks. In this paper the functional link artificial neural network (FLANN) model of equalizer is trained with biologically inspired soft computing techniques like Standard Genetic Algorithm (SGA) and Particle Swarm Optimization (PSO). The results are thoroughly studied and compared with conventional Least Mean Square (LMS) Algorithm trained FLANN and Multi Layer Perceptron network(MLP) under the headings like Minimum Mean Square Error(MMSE), computational complexity, convergence time and is shown that Particle Swarm Optimization based FLANN performs better than the rest. Comparison between two functional link models trigonometric and chebyschev is also done and is shown that chebyschev equalizers performs better than trigonometric equalizers.
Dependency-aware reordering for parallelizing query optimization in multi-core CPUs
Authors: Wook-Shin Han, Jinsoo Lee
Venue: Proceedings of the 35th SIGMOD international conference on Management of data (2009)

The state of the art commercial query optimizers employ cost-based optimization and exploit dynamic programming (DP) to find the optimal query execution plan (QEP) without evaluating redundant sub-plans. The number of alternative QEPs enumerated by the DP query optimizer can increase exponentially, as the number of joins in the query increases. Recently, by exploiting the coming wave of multi-core processor architectures, a state of the art parallel optimization algorithm [14], referred to as PDPsva, has been proposed to parallelize the "time-consuming" DP query optimization process itself. While PDPsva significantly extends the practical use of DP to queries having up to 20-25 tables, it has several limitations: 1) supporting only the size-driven DP enumerator, 2) statically allocating search space, and 3) not fully exploiting parallelism. In this paper, we propose the first generic solution for parallelizing any type of bottom-up optimizer, including the graph-traversal driven type, and for supporting dynamic search allocation and full parallelism. This is a challenging problem, since recently developed, state of art DP optimizers such as DPcpp [21] and DPhyp [22] are very difficult to parallelize due to tangled dependencies in the join pairs they generate. Unless the solution is very carefully devised, a lot of synchronization conflicts are bound to occur. By viewing a serial bottom-up optimizer as one which generates a totally ordered sequence of join pairs in a streaming fashion, we propose a novel concept of dependency-aware reordering, which minimizes waiting time caused by dependencies of join pairs. To maximize parallelism, we also introduce a series of novel performance optimization techniques: 1) pipelining of join pair generation and plan generation; 2) the synchronization-free global MEMO; and 3) threading across dependencies. Through extensive experiments with various query topologies, we show that our solution supports any type of bottom up optimization, achieving linear speedup for each type. Despite the fact that our solution is generic, due to sophisticated optimization techniques, our generic parallel optimizer outperforms PDPsva tailored to size-driven enumeration. Experimental results also show that our solution is much more robust than PDPsva with respect to search space allocation.
Challenges for Assistive Technology: AAATE 2007, Volume 20 Assistive Technology Research Series
Authors: Gorka Eizmendi, Gorka Eizmendi, Jose Miguel, Azkoitia, Gerald, Craddock
Venue:  (2007)

In the 21st century Assistive Technology (AT) should be defined as a scientific and technologic approach to the development of products and services oriented to support the elderly and people with disabilities in their daily activities, maximizing their personal autonomy, independence, health and quality of life. The AT field should bring this theoretical definition to reality more than ever, in order to counteract one of the main challenges that advanced societies will face during the coming years; the population aging. During the past few years, AT has developed quickly, mainly because of the technological revolution. There are better solutions now than there were 20, 10 or 5 years ago. And furthermore we foresee solutions that were unimaginable a few years ago, such as neuroprosthetics for urinary control in people with spinal cord injury or the cochlear implant for people with hearing impairments. This development is evident in high tech products (e-health, computer-based systems) and also in traditional products such as the wheelchair. The five main challenges identified by AAATE are New Technologies; Socio-Economic Issues, Universal design and its engagement with Assistive Technology, Evidence-based Practice and Aging and disability.IOS Press is an international science, technical and medical publisher of high-quality books for academics, scientists, and professionals in all fields. Some of the areas we publish in: -Biomedicine -Oncology -Artificial intelligence -Databases and information systems -Maritime engineering -Nanotechnology -Geoengineering -All aspects of physics -E-governance -E-commerce -The knowledge economy -Urban studies -Arms control -Understanding and responding to terrorism -Medical informatics -Computer Sciences
Asymmetric Learning for Pedestrian Detection Based on Joint Local Orientation Histograms
Authors: Junfeng Ge, Yupin Luo
Venue: Proceedings of the 6th International Symposium on Neural Networks on Advances in Neural Networks (2009)

We present a cost-sensitive learning framework for pedestrian detection in still images based on the novel Joint Local Orientation Histograms (JLOH) features and the Asymmetric Gentle AdaBoost. The JLOH features capture the co-occurrence of local histograms and make it possible to classify the difficult examples. The proposed Asymmetric Gentle AdaBoost takes account of the situation that the rare positive targets have to be distinguished from enormous negative patterns in practical applications. The quantitative evaluation on the well-defined INRIA data set demonstrates the effectiveness of our methods.
Applying category theory to improve the performance of a neural architecture
Authors: Michael J. Healy, Richard D. Olinger, Robert J. Young, Shawn E. Taylor, Thomas Caudell, Kurt W. Larson
Venue: Neurocomputing (2009)

A recently developed mathematical semantic theory explains the relationship between knowledge and its representation in connectionist systems. The semantic theory is based upon category theory, the mathematical theory of structure. A product of its explanatory capability is a set of principles to guide the design of future neural architectures and enhancements to existing designs. We claim that this mathematical semantic approach to network design is an effective basis for advancing the state of the art. We offer two experiments to support this claim. One of these involves multispectral imaging using data from a satellite camera.
Co-integration Analysis of Multiplexed System Based on VAR
Authors: Zhengping He, Hongtao Zhou, Wei Zeng, Jiang Jiang, Qi Fei
Venue: Proceedings of the 6th International Symposium on Neural Networks on Advances in Neural Networks (2009)

The variation of elements in a compound system is mostly non-stationary. Whether these element variables have long-term mutual connection or balanced relations, is essential to determine the interaction relationships between the subsystems. Co-integration is usually used to describing the long-term balanced relations between these non-stationary variables in a statistical method. In view of the fact that elements of a compound system is mostly non-stationary, this paper gave a method using co-integration analysis to determine the long-term inter-relationship between elements of the compound system or its subsystems, and carried this method on the co-integration analysis of the Guangxi Province compound system, composed of education, economy science and technology system, the result of which indicated that economy growth was the reason of the development of education and technological achievements in Guangxi from 1994 to 2006.
Rapid impingement detection and surface distance measurement system for real-time ball-and-socket joint motion simulation
Authors: Ding Cai, Won-Sook Lee, Chris Joslin, Paul E. Beaule
Venue: International Journal of Advanced Media and Communication (2009)

Detecting the position and the level of joint impingement is often a key to computer-aided surgical plan to normalise joint kinematics. So far for ball-and-socket joint, most of the up-to-date impingement detection methods are not efficient or only consider a few collided points as the detection results. In this paper, we present a real-time impingement detection system with rapid geometry sampling and surface-to-surface distance measurement feature for joint motion simulation. This is an expanded version of a paper presented at the 3rd IEEE International Workshop on Medical Measurements and Applications, 9 10 May 2008, Ottawa, ON, Canada.
Realistic Face Animation for Audiovisual Speech Applications: A Densification Approach Driven by Sparse Stereo Meshes
Authors: Marie-Odile Berger, Jonathan Ponroy, Brigitte Wrobel-Dautcourt
Venue: Proceedings of the 4th International Conference on Computer Vision/Computer Graphics CollaborationTechniques (2009)

Being able to produce realistic facial animation is crucial for many speech applications in language learning technologies. Reaching realism needs to acquire and to animate dense 3D models of the face which are often acquired with 3D scanners. However, acquiring the dynamics of the speech from 3D scans is difficult as the acquisition time generally allows only sustained sounds to be recorded. On the contrary, acquiring the speech dynamics on a sparse set of points is easy using a stereovision recording a talker with markers painted on his/her face. In this paper, we propose an approach to animate a very realistic dense talking head which makes use of a reduced set of 3D dense meshes acquired for sustained sounds as well as the speech dynamics learned on a talker painted with white markers. The contributions of the paper are twofold: We first propose an appropriate principal component analysis (PCA) with missing data techniques in order to compute the basic modes of the speech dynamics despite possible unobservable points in the sparse meshes obtained by the stereovision system. We then propose a method for densifying the modes, that is a method for computing the dense modes for spatial animation from the sparse modes learned by the stereovision system. Examples prove the effectiveness of the approach and the high realism obtained with our method.
Polaris: a system-level roadmapping toolchain for on-chip interconnection networks
Authors: Vassos Soteriou, Noel Eisley, Hangsheng Wang, Bin Li, Li-Shiuan Peh
Venue: IEEE Transactions on Very Large Scale Integration (VLSI) Systems (2007)

Technology trends are driving parallel on-chip architectures in the form of multiprocessor systems-on-a-chip (MPSoCs) and chip multiprocessors (CMPs). In these systems, the increasing on-chip communication demand among the computation elements necessitates the use of scalable, high-bandwidth network-on-chip (NoC) fabrics instead of dedicated interconnects and shared buses. As transistor feature sizes are further miniaturized, more complicated NoC architectures become feasible that can support more demanding applications. Given the myriad emerging software-hardware combinations, for cost-effectiveness, a system designer critically needs to prune this widening NoC design-space to predict the interconnect fabric(s) that best balance(s) cost/performance, before the actual design process begins. This prompted us to develop Polaris, a system-level roadmapping toolchain for on-chip interconnection networks that helps designers predict the most suitable interconnection network design(s) tailored to their performance needs and power/silicon area constraints with respect to a range of applications that the system will run. Polaris explores the plethora of NoC designs based on projections of network traffic, architectures, and process characteristics. While Polaris's toolchain is extensible so new traffic, network designs, and technology processes can be added, the current version already incorporates 7872 NoC design points. Polaris is rapid, efficiently iterating over thousands of NoC design points, while maintaining high relative and absolute accuracies when validated against detailed NoC synthesis results.
Plenary lecture II: annealing hybrid algorithms strategies for NP class problems
Authors: Juan Frausto-Solis
Venue: Proceedings of the 10th WSEAS international conference on Mathematical and computational methods in science and engineering (2008)

One of the main objectives of Computer Science is to develop algorithms for helping human beings to solve their difficult and important problems with speed and quality. Among the more difficult computational problems are those belonging to the NP Hard class; examples of these problems are: Satisfiability Problem (SAT), Scheduling (including the allocation of tasks in operating systems and robotics), planning and most problems related with bioinformatics such as phylogenetic trees construction, Folding problems and many others. There are many stochastic approaches proposed for these problems but none of them is always the best solution. A very good approach is to use Simulated Annealing hybridised (i.e. mixed) with other approaches. Among these approaches we can find the very formal ones as Mechanical Statistical, Markov Models, semi-formal as Support Vector Machines and Neural Networks, and very informal as Golden Ratio. In this presentation the main hybridization approaches, applications and challenges for future research are presented.
Representation of discrete quasi-copulas through non-square matrices
Authors: Isabel Aguiló, Jaume Suòer, Joan Torrens
Venue: Proceeding of the 2008 conference on Artificial Intelligence Research and Development: Proceedings of the 11th International Conference of the Catalan Association for Artificial Intelligence (2008)

In this paper a matrix representation for discrete quasi-copulas defined on a non-square grid In× Im of [0,1]2 with m=kn, k≥1 is given. The special case of irreducible discrete quasi-copulas (those that cannot be expressed as nontrivial convex combination of other ones) is also studied. It is proved that quasi-copulas of minimal range admit a matrix representation through a special class of matrices. In the case of copulas, it is proved that irreducible copulas coincide with those of minimal range. Moreover, an algorithm to express any discrete copula as a convex combination of irreducible ones is given.
A Simple Greedy Algorithm for the k-Disjoint Flow Problem
Authors: Maren Martens
Venue: Proceedings of the 6th Annual Conference on Theory and Applications of Models of Computation (2009)

In classical network flow theory the choice of paths, on which flow is sent, is only restricted by arc capacities. This, however, is not realistic in most applications. Many problems restrict, e.g., the number of paths being used to route a commodity. One idea to increase reliability of routings, e.g., in telecommunication, is to copy a demand and send the copies along disjoint paths. Such problems theoretically result in the k-disjoint flow problem (k-DFP). This problem is a variant of the classical multicommodity flow problem with the additional requirement that the number of paths to route a commodity is bounded by a given parameter. Moreover, all paths used by the same commodity have to be arc disjoint.We present a simple greedy algorithm for the optimization version of the k-DFP where the objective is to maximize the sum of routed demands. This algorithm generalizes a greedy algorithm by Kolman and Scheideler (2002) that approximates the corresponding unsplittable flow problem, in which every commodity may be routed along a single path only. We achieve an approximation factor of $O(k_{\text{max}} \sqrt{m}/k_{\text{min}})$, where m is the number of arcs and $k_{\text{max}}$ ($k_{\text{min}}$) is the maximum (minimum) bound on the number of paths allowed to route any of the commodities. We argue that this performance guarantee is best possible for instances where $k_{\text{max}}/k_{\text{min}}$ is constant, unless $\mathcal{P}=\mathcal{P}\mathcal{N}$. 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
Design of central pattern generators (CPGS) for trajectory tracking of fish-mimetic robots
Authors: Donghee Kim, Seunghee Lee, Jong Hyeon Park
Venue: Proceedings of the 7th WSEAS international conference on Computational intelligence, man-machine systems and cybernetics (2008)

A CPG (Central Pattern Generator) is a biological neural network that generates rhythmic movements for locomotion of animals, such as walking, running, swimming and flying. Also, fish show marvelous ability of autonomous dynamic adaptation for an unsteady fluid dynamic environment or various environments. These biological concepts are utilized to mimic animals in engineering fields. The main objective of this paper is to generate a joint motion of the fish-mimetic robot by CPG, which is biological approach, in order to follow the desired trajectory. We propose a 3-DOF CPG controller to track the trajectory of the fish robot in a plane motion. The conformity of the proposed control algorithm is validated by simulation for a fish robot model with unsteady fluid characteristics.