ppxscal/embedding_network huggingface dataset:
Hybrid adaptive neural control for flexible manipulators
Authors: Amin Riad Maouche, Mokhtar Attari
Venue: International Journal of Intelligent Systems Technologies and Applications (2009)

This article describes a hybrid control strategy to deal with the problem of controlling flexible link manipulators. The motion control of a planar manipulator with two flexible arms is studied. Dynamics is developed in Lagrange's formulation. A novel control system structure is proposed to control the joint position and velocity as well as the deflection of the tip for each arm. First, a non-linear control law based on the dynamic motion equation of the robot is presented and the stability analysis is studied. Then, an adaptive neural controller is implemented to compensate errors due to structured and unstructured uncertainties. Efficiency of the new controller obtained by combining the two control laws is tested facing an important variation of the dynamic parameters of the flexible manipulator and compared to the non-linear control taken solely. Simulation results show the effectiveness of the control strategy proposed.
Identifying Activities of Daily Living Using Wireless Kinematic Sensors and Data Mining Algorithms
Authors: Anthony F. Dalton, Gearóid OLaighin
Venue: Proceedings of the 2009 Sixth International Workshop on Wearable and Implantable Body Sensor Networks (2009)

The objective of this study was to compare base-level and meta-level classifiers on the task of activity recognition.Five wireless kinematic sensors were attached to 25 subjects with each subject asked to complete a range of basic activities in a controlled laboratory setting. Subjects were then asked to carry out similar self-annotated activities in a random order and in an unsupervised environment. A combination of time-domain and frequency-domain features were calculated using a sliding window segmentation technique. A reduced feature set was generated using a wrapper subset evaluation technique with a linear forward search.The meta-level classifier AdaBoostM1 with C4.5 Graft as its base-level classifier achieved an overall accuracy of 95%. Equal sized datasets of subject independent data and subject dependent data were used to train this classifier and it was found that high recognition rates can be achieved without the need of user specific training.
Financial Analysis with Microsoft Excel 2007, 5th edition
Authors: Timothy R. Mayes, Todd M. Shank
Venue:  (2009)

Master the tool that finance professionals depend upon everyday as you perfect your skills in Excel 2007 while establishing a strong understanding of contemporary corporate finance. Mayes/Shank's "Financial Analysis with Microsoft Excel 2007, 5E, International Edition" shows today's reader how to tap into some of Excel 2007's most powerful tools to solve real financial problems. The book's solid content covers all of the topics from today's corporate finance course, including financial statements, budgets, the Market Security Line, pro forma statements, cost of capital, equities, and debt. A reader-friendly, self-directed learning approach and numerous study tools help you build upon basic skills or transfer skills from other spreadsheet programs for the Excel skills and solid finance knowledge today's developing business professionals need for success.
Proceedings of the Workshop on Comparing Corpora
Venue: ACL Workshops (2000)

Anyone who has worked with corpora will be all too aware of differences between them. Depending on the differences, it may, or may not, be reasonable to expect results based on one corpus to also be valid for another. It may, or may not, be appropriate for a grammar, or parser, based on one to perform well on another. It may, or may not, be straightforward to port an application from a domain of the first text type to a domain of the second. Currently, characterisations of corpora are mostly textual and informal. A corpus is described as "Wall Street Journal" or "transcripts of business meetings" or "foreign learners' essays (intermediate grade)". It would be desirable to be able to place a new corpus in relation to existing ones, and to be able to quantify similarities and differences.
Relaxed Transfer of Different Classes via Spectral Partition
Authors: Xiaoxiao Shi, Wei Fan, Qiang Yang, Jiangtao Ren
Venue: Proceedings of the European Conference on Machine Learning and Knowledge Discovery in Databases: Part II (2009)

Most existing transfer learning techniques are limited to problems of knowledge transfer across tasks sharing the same set of class labels. In this paper, however, we relax this constraint and propose a spectral-based solution that aims at unveiling the intrinsic structure of the data and generating a partition of the target data, by transferring the eigenspace that well separates the source data. Furthermore, a clustering-based KL divergence is proposed to automatically adjust how much to transfer. We evaluate the proposed model on text and image datasets where class categories of the source and target data are explicitly different, e.g., 3-classes transfer to 2-classes, and show that the proposed approach improves other baselines by an average of 10% in accuracy. The source code and datasets are available from the authors.
TreeTime
Authors: Lin Himmelmann, Dirk Metzler
Venue: Bioinformatics (2009)

Motivation: For the estimation of phylogenetic trees from molecular data, it is worthwhile to take prior paleontologic knowledge into account, if available. To calibrate the branch lengths of the tree with times assigned to geo-historical events or fossils, it is necessary to select a relaxed molecular clock model to specify how mutation rates can change along the phylogeny. Results: We present the software TreeTime for Bayesian phylogeny estimation. It can take prior information about the topology of the tree and about branching times into account. Several relaxed molecular clock models are implemented in TreeTime. TreeTime is written in C++ and designed to be efficient and extensible. Availability: TreeTime is freely available from http://evol.bio.lmu.de/statgen/software/treetime under the terms of the GNU General Public Licence (GPL, version 3 or later). Contact:lin@linhi.de; metzler@bio.lmu.de
Radar Signal Automatic Classification Based on PCA
Authors: Zhibin Yu, Chunxia Chen, Weidong Jin
Venue: Proceedings of the 2009 WRI Global Congress on Intelligent Systems - Volume 03 (2009)

This paper introduces an efficient approach to radar signal automatic classification by extracted fusion feature entropy. In this approach, wavelet packet reconstruct coefficient features are extracted from given radar signals in frequency domain based on wavelet packet decomposition. Then, these features are fused with the principal component analysis and a single characteristic feature vector which can effectively represent difference radar signals is obtained. Aiming at the single fusion feature, its energy entropy and symbolization probability entropy are extracted and extracted fusion feature entropy are used to classify emitter radar signal with fuzzy c-mean clustering algorithm. Simulation experiment show that the proposed approach is verified to be highly accurate and robust even in the low SNR, and the classification algorithm needs only very small memory space to store the reference information and can fast implement radar signal classification.
A four-stage algorithm for updating a Burrows-Wheeler transform
Authors: M. Salson, T. Lecroq, M. Léonard, L. Mouchard
Venue: Theoretical Computer Science (2009)

We present a four-stage algorithm that updates the Burrows-Wheeler Transform of a text T, when this text is modified. The Burrows-Wheeler Transform is used by many text compression applications and some self-index data structures. It operates by reordering the letters of a text T to obtain a new text bwt(T) which can be better compressed. Even though recent advances are offering this structure new applications, a major bottleneck still exists: bwt(T) has to be entirely reconstructed from scratch whenever T is modified. We study how standard edit operations (insertion, deletion, substitution of a letter or a factor) that transform a text T into T^' impact bwt(T). Then we present an algorithm that directly converts bwt(T) into bwt(T^'). Based on this algorithm, we also sketch a method for converting the suffix array of T into the suffix array of T^'. We finally show, based on the experiments we conducted, that this algorithm, whose worst-case time complexity is O(|T|log|T|(1+log@s/loglog|T|)), performs really well in practice and replaces advantageously the traditional approach.
A framework for data mining on combinatorial game theory
Authors: David Hooks, Qin Ding
Venue: Journal of Computational Methods in Sciences and Engineering (2009)

Combinatorics is the study of discrete, finite spaces. Combinatorial games are games that can be studied through the use of combinatorics. They are typically, but not necessarily, two-player games with a finite set of possible states and a well-defined winning condition. The search space in combinatorial games is typically very large. In this paper, we proposed a framework to apply data mining techniques such as Bayesian classification to the combinatorial game theory, in particular, a game called "Audacity". Our experimental results show that the Bayesian classification is effective for discovering classification rules in combinatorial games, such as the "Audacity" game.
High abstraction level CAD tool implementation of MOS drain current models
Authors: William Prodanov, Maurizio Valle
Venue: Microelectronics Journal (2009)

This paper presents a toolbox in which a compact high abstraction level formulation of the MOS drain current was implemented. The formulation is based on the popular ACM compact MOS model: the approximations introduced in the model preserve the drain-to-source device symmetry and the continuity between all regions of operation (i.e. weak, moderate and strong inversion). The technological parameters involved in the formulation are obtained by means of a fully automatic extraction procedure. Finally, a detailed case study, in which a behavioural analysis of sample-and-hold circuits using the proposed toolbox is performed, is presented. The ATMEL^(R)0.24@mm CMOS process was used as reference for the case study. The MATLAB^(R) environment was used to implement the drain current model formulation, the technological parameters extraction and the case study as well.
Dynamic Compartments in the Imperative Π-Calculus
Authors: Mathias John, Cédric Lhoussaine, Joachim Niehren
Venue: Proceedings of the 7th International Conference on Computational Methods in Systems Biology (2009)

Dynamic compartments with mutable configurations and variable volumes are of basic interest for the stochastic modeling of biochemistry in cells. We propose a new language to express dynamic compartments that we call the imperative Π -calculus. It is obtained from the attributed Π -calculus by adding imperative assignment operations to a global store. Previous approaches to dynamic compartments are improved in flexibility or efficiency. This is illustrated by an appropriate model of osmosis and a correct encoding of bioambBioAmbients.
The Preliminary Process of Modeling in Deep Web Information Fusion System
Authors: Hao Liang, Fei Ren, Wanli Zuo
Venue: Proceedings of the 2009 International Forum on Information Technology and Applications - Volume 01 (2009)

The Web has become the largest information source, which includes all aspect of human's life. The myriad information is believed to be hidden behind the Deep Web, which the search engines and crawlers can't access directly. To extend the human's physical limitation of accessing information, the information fusion system is introduced. The Web is very different from the traditional database community, the nature of which is more dynamic, heterogeneous, dispersed and hyper-linked. The query interfaces of the Deep Web are the only clue to disclose the hidden schemas. However, to get schemas of the local databases through the query interfaces is a great challenge, which is deserved dramatically concern. The key aspect of the Deep Web information fusion is the source modeling problem, which is about the specification of the correspondence between the data at the sources and those in the global schema. The first step is to parse the query interfaces and extracting attributes and semantic relationships which reflect the hidden schemas. There are two approaches of source modeling: global as view (GAV) and local as view (LAV). In this paper, we choose the method of LAV and present an attributes extraction method utilizing Ontology.
Zero quiescent current startup circuit with automatic turning-off for low power current and voltage reference
Authors: Andre Mansano, Andre Vilas Boas, Alfredo Olmos, Jefferson Soldera
Venue: Proceedings of the 22nd Annual Symposium on Integrated Circuits and System Design: Chip on the Dunes (2009)

A zero quiescent current startup circuit with automatic turning-off for low power current and voltage reference is presented. The proposed startup uses positive feedback to sense an internal bias voltage of the main current/voltage reference circuit and guarantees it properly achieves its desired steady state condition. After that, the start-up circuitry automatically turns off itself. Hence, there is no power consumption on start-up circuitry after start-up process. Also, its very robust architecture is compatible with standard CMOS processes and is able to operate down to sub-1V making it ideal for single battery applications. The circuit has been integrated in a 45nA current source implemented in TSMC 0.25um process. Transient response of the start-up circuitry has been measured as well as supply voltage variation has been evaluated to prove start-up operation.
WiMAX Network Planning and Optimization, 1st edition
Authors: Yan Zhang
Venue:  (2009)

This book offers a comprehensive explanation on how to dimension, plan, and optimize WiMAX networks. The first part of the text introduces WiMAX networks architecture, physical layer, standard, protocols, security mechanisms, and highly related radio access technologies. It covers system framework, topology, capacity, mobility management, handoff management, congestion control, medium access control (MAC), scheduling, Quality of Service (QoS), and WiMAX mesh networks and security. Enabling easy understanding of key concepts and technologies, the second part presents practical examples and illustrative figures to explain planning techniques and optimization algorithms. The author provides both theoretical and practical information to ensure in-depth, realistic results. 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
Identification of Hammerstein Models Based on Support Vector Regression
Authors: Zhiyong Du, Xianfang Wang
Venue: Proceedings of the 2009 IITA International Conference on Control, Automation and Systems Engineering (case 2009) (2009)

This paper presents a method for the identification of Hammerstein models based on Support Vector Regression (SVR). First, the intermediate linear model was established through converting the nonlinear equations of Hammerstein to a class of linear one by the function expansion. Second, training samples for intermediate linear model were obtained by operating measured data synthetically, and coefficients of the intermediate model were obtained by the SVR algorithm. Then, through the relations of the coefficients of intermediate model and that of Hammerstein model, the nonlinear static part and linear dynamic part were identified simultaneously. Finally, The efficiency of the proposed algorithm was demonstrated by simulation examples.
A Brain-Machine Interface Based on EEG: Extracted Alpha Waves Applied to Mobile Robot
Authors: Mufti Mahmud, David Hawellek, Aleksander Valjamae
Venue: Proceedings of the 2009 Advanced Technologies for Enhanced Quality of Life (2009)

The increasing number of signal processing tools for highly parallel neurophysiological recordings opens up new avenues for connecting technologies directly to neuronal processes. As the understanding is taking a better shape, lot more work to perform is coming up. A simple brain-machine interface may be able to reestablish the broken loop of the persons with motor dysfunction. With time the brain-machine interfacing is growing more complex due to the increased availability of instruments and processes for implementation. In this work, as a proof-of-principle we established a brain-machine interface through a few simple processes to control a robotic device using the alpha wave’s event-related synchronization and event-related de-synchronization extracted from EEG.
A Fault-Tolerant Target Location Detection Algorithm in Sensor Networks
Authors: Chiu-Kuo Liang, Chih-Shiuan Li
Venue: Proceedings of the 2009 Third International Conference on Sensor Technologies and Applications (2009)

This paper focuses on the fault-tolerant target detection and localization in sensor networks. Typical applications include the habitat monitoring and roadway safety warning. We propose an algorithm for target detection and localization to improve the target position accuracy. Our algorithm is purely localized and thus is suitable for large scale of sensor networks. The computational overhead is low since the detection algorithm is based on a simple clustering technique which only simple numerical operations are involved. Simulation results show that our algorithm can decrease the false alarm rate and improve the target localization accuracy when as many as 30% sensors become faulty. Therefore, our algorithm achieves a great improvement over the previous algorithms.
MARM: Multiscale Adaptive Regression Models for Neuroimaging Data
Authors: Hongtu Zhu, Yimei Li, Joseph G. Ibrahim, Weili Lin, Dinggang Shen
Venue: Proceedings of the 21st International Conference on Information Processing in Medical Imaging (2009)

We develop a novel statistical model, called multiscale adaptive regression model (MARM), for spatial and adaptive analysis of neuroimaging data. The primary motivation and application of the proposed methodology is statistical analysis of imaging data on the two-dimensional (2D) surface or in the 3D volume for various neuroimaging studies. The existing voxel-wise approach has several major limitations for the analyses of imaging data, underscoring the great need for methodological development. The voxel-wise approach essentially treats all voxels as independent units, whereas neuroimaging data are spatially correlated in nature and spatially contiguous regions of activation with rather sharp edges are usually expected. The initial smoothing step before the voxel-wise approach often blurs the image data near the edges of activated regions and thus it can dramatically increase the numbers of false positives and false negatives. The MARM, which is developed for addressing these limitations, has three key features in the analysis of imaging data: being spatial, being hierarchical, and being adaptive. The MARM builds a small sphere at each location (called voxel) and use these consecutively connected spheres across all voxels to capture spatial dependence among imaging observations. Then, the MARM builds hierarchically nested spheres by increasing the radius of a spherical neighborhood around each voxel and combine all the data in a given radius of each voxel with appropriate weights to adaptively calculate parameter estimates and test statistics. Theoretically, we first establish that the MARM outperforms classical voxel-wise approach. Simulation studies are used to demonstrate the methodology and examine the finite sample performance of the MARM. We apply our methods to the detection of spatial patterns of brain atrophy in a neuroimaging study of Alzheimer's disease. Our simulation studies with known ground truth confirm that the MARM significantly outperforms the voxel-wise methods.
An Improved and Efficient Tool for Analyzing Industrial Security Protocols
Authors: Nan Liu, Yuefei Zhu, Zhongquan Mao, Wei Xu
Venue: Proceedings of the 2009 IITA International Conference on Control, Automation and Systems Engineering (case 2009) (2009)

Formal methods and automatic tools are always necessary for analyzing security protocols, and model checking has become a hot spot of research for its ability of verifying finite-state concurrent system automatically. In this paper, we propose a model of security protocols based on MSR (multi-set rewriting), coupled with PLTL describing security properties. Based on the model, a series of key automatic analysis algorithms close to the implementation are designed for our own tool. By using the tool, we illustrate the method’s effectiveness with some typical protocols and give the experimental results.
An Adaptive Technique for Accurate Feature Extraction from Regular and Irregular Image Data
Authors: Sonya Coleman, Shanmuglingam Suganthan, Bryan Scotney
Venue: Proceedings of the 15th International Conference on Image Analysis and Processing (2009)

We present a single multi-scale gradient-based feature extraction algorithm that can be directly applied to irregular or regular image data and hence can be used on both range and intensity images. We illustrate the accuracy of this approach using the Figure of Merit evaluation technique on real images, demonstrating that the application of this approach to both range and intensity images is more accurate than the equivalent approach of applying a gradient operator, such as Sobel, to an intensity image and, separately, the scan-line approximation approach to range images.
Efficient Non-malleable Commitment Schemes
Authors: Marc Fischlin, Roger Fischlin
Venue: Journal of Cryptology (2009)

Non-malleability protects against man-in-the middle attacks on cryptographic protocols. Non-malleable commitment schemes, for example, assure that a commitment of a message does not help to produce a commitment of a related message. Here we present efficient constructions of such commitment schemes in the common reference string model, based on standard assumptions such as RSA, factoring or discrete logarithm. Our protocols require only three rounds and a few modular exponentiations, and provide statistical or even perfect secrecy of committed values. We also discuss differences between the notion of non-malleable commitment schemes used in previous works by Dolev, Dwork and Naor and by Di&#x00a0;Crescenzo, Ishai and Ostrovsky. The former definition requires that it is infeasible to find a commitment such that there exists an encapsulated message which is related to another committed value (non-malleability with respect to commitment). The second approach allows the existence of such messages, but then it is hard to find them and to output them in the opening phase (non-malleability with respect to opening). We note that our solutions are of the second type.
Multi-Ant-Colony Based Multi-Path Routing Algorithm for Overlay Network
Authors: Shen Ling, Wu Wei
Venue: Proceedings of the 2009 WRI Global Congress on Intelligent Systems - Volume 01 (2009)

Network topology always changes randomly during the communication. This paper presented a Multi-Ant colony based Multi-Path routing algorithm (MACMPR). Comparing with the conventional ant colony based route protocols, MACMPR extended the basic ant colony to multiple ones with dynamic pheromone release design. Each ant Colony searches one path and repulses other ant Colonies. Ants deposit pheromones depends on the situation of network and nodes capability, which provides a new method to avoid the congestion. MACMPR constructs multi-path for every destination and source nodes and allocate the traffic load of network to the different paths to avoid traffic congestion. It is robust and applies backup path to deliver data packets when link failure occurs.