ppxscal/embedding_network huggingface dataset:
RSSI-Based Forwarding for Multihop Wireless Sensor Networks
Authors: Azlan Awang, Xavier Lagrange, David Ros
Venue: Proceedings of the 15th Open European Summer School and IFIP TC6.6 Workshop on The Internet of the Future (2009)

In a multihop Wireless Sensor Network (WSN), a salient point among routing protocols that do not depend on network topology and existence of neighboring nodes is the need to know sensor node's geographical location with respect to the sink node. This is obtained by some means like Global Positioning System (GPS) and localization techniques. In a prior work, we have proposed RSSI-based Forwarding (RBF) protocol that works without knowledge of node's location by using a Received Signal Strength Indicator (RSSI) level of beacon signals transmitted by the sink. Through contention, a next-hop node is determined among the forwarding candidates using a timer-based suppression scheme. We propose an improvement of the suppression scheme in which a contender closer to the sink is favored with a higher probability for being selected as a next-hop node. By means of simulation, it is shown that the performance of RBF is significantly improved using the enhanced mechanism.
Identifying the Dynamic Impact: A Regulatory Perspective on Electronic Money
Authors: Sun Hao, Chai Yue Ting, Liu Yi
Venue: Proceedings of the 2009 Second International Symposium on Electronic Commerce and Security - Volume 01 (2009)

Diversified electronic money products are emerging recently with the rapid growth of e-commerce in China. A hot research topic now is to identify the dynamic impact arising from various uncertainties of e-money evolution, which is essential for an effective regulation. This paper gives e-money a formal definition, and puts it into two categories according to legal tender dependency. Detailed discussion is given about the difference between the two. We recognize the sedimentary money as the key element in the analysis of e-money’s impact on economy. A quantitative model is built to calculate the speed of sedimentary accumulation. Then the dynamic impact is analyzed from typical modes dealing with the sedimentary money. Finally the implications for e-money regulation including the IT architecture are presented based on above analysis.
Spatial Multiplexing Turbo Receiver with Reduced Complexity
Authors: Andrei Nedelcu, Radu Lupoaie, Andrei A. Enescu, Cristian Anghel, Constantin Paleologu
Venue: Proceedings of the 2009 Third International Conference on Sensor Technologies and Applications (2009)

This paper proposes a multi-antenna spatial multiplexing receiver exhibiting very good performances in the presence of fading and low signal-to-noise ratio. These result from the use of a soft-output sphere decoder with reduced complexity and a robust turbo channel decoder affected by log-likelihood ratio quantization and saturation. Fixed-point implementation is targeted, taking in account the receiver throughput and latency.
Online EM for unsupervised models
Authors: Percy Liang, Dan Klein
Venue: Proceedings of Human Language Technologies: The 2009 Annual Conference of the North American Chapter of the Association for Computational Linguistics (2009)

The (batch) EM algorithm plays an important role in unsupervised induction, but it sometimes suffers from slow convergence. In this paper, we show that online variants (1) provide significant speedups and (2) can even find better solutions than those found by batch EM. We support these findings on four unsupervised tasks: part-of-speech tagging, document classification, word segmentation, and word alignment.
Evaluating the Impact of Missing Data Imputation
Authors: Adam Pantanowitz, Tshilidzi Marwala
Venue: Proceedings of the 5th International Conference on Advanced Data Mining and Applications (2009)

This paper presents an impact assessment for the imputation of missing data. The assessment is performed by measuring the impacts of missing data on the statistical nature of the data, on a classifier, and on a logistic regression system. The data set used is HIV seroprevalence data from an antenatal clinic study survey performed in 2001. Data imputation is performed through the use of Random Forests, selected based on best imputation performance above five other techniques. Test sets are developed which consist of the original data and of imputed data with varying numbers of specifically selected missing variables imputed. Results indicate that, for this data set, the evaluated properties and tested paradigms are fairly immune to missing data imputation. The impact is not highly significant, with, for example, linear correlations of 96 % between HIV status probability prediction with a full set and with a set of two imputed variables using the logistic regression analysis.
Selective diffusion for oriented pattern extraction: Application to tagged cardiac MRI enhancement
Authors: A. Histace, M. Ménard, C. Cavaro-Ménard
Venue: Pattern Recognition Letters (2009)

Anisotropic regularization PDE's (Partial Differential Equation) raised a strong interest in the field of image processing. The benefit of PDE-based regularization methods lies in the ability to smooth data in a nonlinear way, allowing the preservation of important image features (contours, corners or other discontinuities). In this article, a selective diffusion approach based on the framework of Extreme Physical Information theory is presented. It is shown that this particular framework leads to a particular regularization PDE which makes the integration of prior knowledge possible within the diffusion scheme. As a proof of feasibility, results of oriented pattern extractions are first presented on ad hoc images and second on a particular medical application: Tagged cardiac MRI (Magnetic Resonance Imaging) enhancement.
Rate Control Improved Algorithm Based on Low Complexity H.264
Authors: Xu Yubin, Sha Xuejun, Jiang Weilin
Venue: Proceedings of the 2009 International Forum on Information Technology and Applications - Volume 01 (2009)

Although Rate control algorithm of TM5 model on MPEG-2 is early classical algorithm, which is able to control rate and complexity lower than Hol7, this algorithm has some insufficiency. This paper analyses rate control algorithm on TM5, Using "virtual buffer" for reference, propose a rate control improved algorithm, which can efficiently control rate, without updating MAD prediction model and R-D model, thus the complication of calculation is decreased greatly, suitable for sensitive situation for computational complexity.
Mining Parsing Results for Lexical Correction: Toward a Complete Correction Process of Wide-Coverage Lexicons
Authors: Lionel Nicolas, Benoît Sagot, Miguel A. Molinero, Jacques Farré, Éric Clergerie
Venue: Human Language Technology. Challenges of the Information Society: Third Language and Technology Conference, LTC 2007, Poznan, Poland, October 5-7, 2007, Revised Selected Papers (2009)

The coverage of a parser depends mostly on the quality of the underlying grammar and lexicon. The development of a lexicon both complete and accurate is an intricate and demanding task. We introduce a automatic process for detecting missing, incomplete and erroneous entries in a morphological and syntactic lexicon, and for suggesting corrections hypotheses for these entries. The detection of dubious lexical entries is tackled by two different techniques; the first one is based on a specific statistical model, the other one benefits from information provided by a part-of-speech tagger. The generation of correction hypotheses for dubious lexical entries is achieved by studying which modifications could improve the successful parse rate of sentences in which they occur. This process brings together various techniques based on taggers, parsers and statistical models. We report on its application for improving a large-coverage morphological and syntacic French lexicon, the Lefff.
Modeling and learning vague event durations for temporal reasoning
Authors: Feng Pan, Rutu Mulkar-Mehta, Jerry R. Hobbs
Venue: Proceedings of the 22nd national conference on Artificial intelligence - Volume 2 (2007)

This paper reports on our recent work on modeling and automatically extracting vague, implicit event durations from text (Pan et al., 2006a, 2006b). It is a kind of commonsense knowledge that can have a substantial impact on temporal reasoning problems. We have also proposed a method of using normal distributions to model Judgments that are intervals on a scale and measure their interannotator agreement; this should extend from time to other kinds of vague but substantive information in text and commonsense reasoning.
HEURISTIC RULES IN GENETIC ALGORITHM FOR FUEL MANAGEMENT OPTIMIZATION: In-Core Fuel Management Optimization for Pressurized Water Reactors - PWRs
Authors: Fatih Alim
Venue:  (2009)

The objective of this study was to develop a unique methodology and a practical tool for designing loading pattern (LP) and burnable poison (BP) pattern for a given Pressurized Water Reactor (PWR) core. Because of the large number of possible combinations for the fuel assembly (FA) loading in the core, the design of the core configuration is a complex optimization problem. It requires finding an optimal FA arrangement and BP placement in order to achieve maximum cycle length while satisfying the safety constraints. To solve this optimization problem, a LP optimization package, GARCO (Genetic Algorithm Reactor Code Optimization) code is developed. This code is applicable for all types of PWR cores having different geometries and structures with an unlimited number of FA types in the inventory. To reach this goal, an innovative GA is developed by modifying the classical representation of the genotype. To obtain the best result in a shorter time, not only the representation is changed but also the algorithm is changed to use in-core fuel management heuristics rules. The improved GA code was tested to demonstrate and verify the advantages of the new enhancements. 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
Lessons Learned from Developing Cognitive Support for Communication, Entertainment, and Creativity for Older People with Dementia
Authors: Norman Alm, Arlene Astell, Gary Gowans, Richard Dye, Maggie Ellis, Phillip Vaughan, Philippa Riley
Venue: Proceedings of the 5th International Conference on Universal Access in Human-Computer Interaction. Addressing Diversity. Part I: Held as Part of HCI International 2009 (2009)

We have developed cognitive support for people with dementia in three areas of activity : communication, entertainment and creativity. In each case the cognitive support was intended to in some way replace an effective working memory. With all three projects our findings have been a mix of expected results and surprises. We are still working out the implications of some of the surprising results. In this paper we set out some key findings from each of these projects, and the lessons learned.
A Library Booking Policy Based on Stocking Theory
Authors: Wensheng Wang
Venue: Proceedings of the 2009 IITA International Conference on Services Science, Management and Engineering (2009)

This paper puts forward a new booking policy based on data mining technology and stocking theory. The main idea is to analysis web logs of the library system by data mining theory to get what kinds of books are students’ interests most and then analysis these books by stocking theory to get the best booking policy. At the last part of this paper, an example is given to illuminate the availability of this new policy.
Spectral clustering for example based machine translation
Authors: Rashmi Gangadharaiah, Ralf Brown, Jaime Carbonell
Venue: Proceedings of the Human Language Technology Conference of the NAACL, Companion Volume: Short Papers on XX (2006)

Prior work has shown that generalization of data in an Example Based Machine Translation (EBMT) system, reduces the amount of pre-translated text required to achieve a certain level of accuracy (Brown, 2000). Several word clustering algorithms have been suggested to perform these generalizations, such as k-Means clustering or Group Average Clustering. The hypothesis is that better contextual clustering can lead to better translation accuracy with limited training data. In this paper, we use a form of spectral clustering to cluster words, and this is shown to result in as much as 29.08% improvement over the baseline EBMT system.
Learning from a tutor: Embodied speech acquisition and imitation learning
Authors: Miguel Vaz, Holger Brandl, Frank Joublin, Christian Goerick
Venue: Proceedings of the 2009 IEEE 8th International Conference on Development and Learning (2009)

This work presents a new developmentally inspired data-driven framework to bootstrap speech perception and imitation abilities in interaction with a tutor. The proposed system architecture extends our work presented in [1], that implements a cascade of interconnected layers to acquire the structure of speech in terms of phones, syllables and words. Here, we show how to couple such a perceptual model with a speech imitation system that is based on an acoustic synthesizer bound to produce speech sounds with a child's voice.
NavBot: the navigational search-and-rescue robot
Authors: Matthew Marge, Ayman Sawas, Juan Carlos Liberato, Murtaza M. Karim, Manish Muttreja, Nader Alrawahi, Brian Fink
Venue: Proceedings of the 20th national conference on Artificial intelligence - Volume 4 (2005)

The Stony Brook Robot Design Team has focused on two main areas of research in the creation of NavBot, our new robot created for the American Association of Artificial Intelligence's (AAAI) Scavenger Hunt Event: navigation and computer vision. The purpose is to create an intelligent machine that is able to navigate the conference floor for specific objects at the AAAI Conference in Pittsburgh, Pennsylvania. To achieve the desirable speeds required in a rescue robot, NavBot utilizes high-rpm servo motors with a manually adjustable gear train. The two 12V servo motors enhance the maneuverability of the robot by providing minor adjustments in the robot's speed as it navigates an area. The manually adjustable gear trains allow NavBot to function in different environments. This is achieved by controlling the force and the speed required for maneuverability in the terrain. NavBot also utilizes a dual-track motion system to handle rough terrain. To enhance the power of NavBot, it was designed with a light aluminum skeleton. In addition to the large space provided for necessary electrical and computer equipment, the skeleton serves as a secure casing that prevent, damage to vital parts.
Research of RBF Neural Networks Algorithm to Fault Diagnosis of Rotary Machinery
Authors: Xiao-yue Wang, Zhong-kui Zhang
Venue: Proceedings of the 2009 IITA International Conference on Control, Automation and Systems Engineering (case 2009) (2009)

In order to overcome the problems of slow rate of convergence, falling easily into local minimum, instability learning performance caused by initial value in BP algorithm, a new diagnosis method based on RBF neural networks was proposed. And the diagnosis method is applied to rotary machinery fault diagnosis. The result shows that the RBF network has very high learning convergence speed and better classifying performance. RBF network has good practicality in the field of equipment fault diagnosis.
The Application of ICTs and Digital Divide in Rural China
Authors: Peng Chen, Jieping Wang, Zuoxian Si, Jie Wang, Ying Liu
Venue: Proceedings of the 3rd International Conference on Internationalization, Design and Global Development: Held as Part of HCI International 2009 (2009)

In this article, we explored rural China's digital divide problem from a social structure perspective, especially regarding the practical process and mechanism of the digital divide forming in different village structures. Traditional village and industrialized village represent two types of rural China's social structure, which provide a good case for studying the digital divide between different types of villages. We consider the gap formed in possessing information and communication technologies(ICTs) as the primary divide, and take the gap formed in using ICTs as the secondary divide. Moreover, a "mutual reproduction" effect exists between the divides formed in the course of possessing and using ICTs. Finally we pointed out that cell phones, as a mobile network, may become the first carrier of the integration of the future information technology and an effective agent weapon helps bridging the digital divide.
A Modified Particle Swarm Optimization and Simulation
Authors: Li Yong, Liao Ruiquan, Zhang Dingxue
Venue: Proceedings of the 2009 Asia-Pacific Conference on Information Processing - Volume 02 (2009)

To overcome premature searching by standard particle swarm optimization (PSO) algorithm, a new modified PSO with information of the closest particle is proposed. In the algorithm, the particle is updated not only by the best previous position and the best position among all the particles in the swarm, but also by the best previous position of the closest particle. To balance the trade-off between exploration and exploitation and convergence to the global optimum solution, a linearly varying acceleration coefficient over the generations was introduced. The simulation results show that the algorithm has better probability of finding global optimum and mean best value than others algorithm, especially for multimodal function.
Mining Short Association Rules from Large Database
Authors: Feiyue Ye, Mingxia Chen, Jin Qian
Venue: Proceedings of the 2009 Asia-Pacific Conference on Information Processing - Volume 01 (2009)

Discovering association rules from existing large databases is an important technique. In this paper, we propose an effective algorithm for mining short association rules on large database. It is experimentally demonstrated presented algorithm has an advantage over existing algorithm for mining association rule, it has better performance and flexibility. By verifying the real transaction data from a supermarket, the short for mining association rules is effective too.
Characteristics on Soil Heavy Metals Pollution around Mine Waste Piles
Authors: Mingliang Zhang, Haixia Wang
Venue: Proceedings of the 2009 International Conference on Environmental Science and Information Application Technology - Volume 02 (2009)

Based on leaching experiment, the leaching of heavy metal in mine waste was brought out. The research showed that Zn, Cr, Pb and Cu concentrations are most in the leachate of weathered coal waste, and the concentration became stable rapidly; only Zn concentrations are found in fresh mine waste leachate in the beginning time. The soil around mine waste also was contaminated by heavy metal, such as Zn, Cr and Pb .The process that heavy metal is leached out is a long time, and heavy metal could be migrated and accumulated. The contents of heavy metals of soil samples decreased with distance. The content of heavy metals decreased with the depth.
Shipping Monitoring System Based on GPS and GPRS Technology
Authors: Zhenhua Zhao, Wei Zhou, Na Wang
Venue: Proceedings of the 2009 WASE International Conference on Information Engineering - Volume 01 (2009)

A scheme of constructing shipping monitoring and control system has been provided: consists of monitor and control center, data communications, ship-borne terminals and user terminals; Hardware Structure of ship-borne terminal has been discussed: consists of central processing unit, GPS module, GPRS module, memory modules, I / O interfaces, keyboard and display modules etc. And the overall structure of ship-borne terminals, two types of memories and their connections with the microprocessor and LCD biasing voltage circuit etc. have been given after introducing related devices and modules; Highlights the initialization statement of GPS module and positioning information acquiring statement in the software design, and the related examples are given to illustrate it. IP is determined for network layer protocol and DUP for application layer protocol for communication after analyzing IP, TCP and DUP communication protocols.
Eye Movement as Indicators of Mental Workload to Trigger Adaptive Automation
Authors: Tjerk Greef, Harmen Lafeber, Herre Oostendorp, Jasper Lindenberg
Venue: Proceedings of the 5th International Conference on Foundations of Augmented Cognition. Neuroergonomics and Operational Neuroscience: Held as Part of HCI International 2009 (2009)

This research describes an approach to objective assessment of mental workload, by analyzing differences in pupil diameter and several aspects of eye movement (fixation time, saccade distance, and saccade speed) under different levels of mental workload. In an experiment, these aspects were measured by an eye-tracking device to examine whether these are indeed indicators for mental workload. Pupil diameter and fixation time both show a general significant increase if the mental workload increases while saccade distance and saccade speed do not show any significant differences. This assessment of mental workload could be a trigger for aiding the operator of an information system, in order to meet operational requirements.
K-RLE: A New Data Compression Algorithm for Wireless Sensor Network
Authors: Eugène Pamba Capo-Chichi, Hervé Guyennet, Jean-Michel Friedt
Venue: Proceedings of the 2009 Third International Conference on Sensor Technologies and Applications (2009)

In the context of the use of Wireless Sensor Network technology for environmental monitoring, the two main elementary activities of Wireless Sensor Network are data acquisition and transmission. However, transmitting/receiving data are power consuming task. In order to reduce transmission-associated power consumption, we explore data compression by processing information locally. In this article, we evaluate and compare compression algorithms on an ultra-low power microcontroller from Texas Instrument within the MSP430 series used for designing Wireless Sensor Network. We propose and evaluate a new data compression algorithm inspired from Run Length Encoding called K-RLE.
The Diversity of Regression Ensembles Combining Bagging and Random Subspace Method
Authors: Alexandra Scherbart, Tim W. Nattkemper
Venue: Advances in Neuro-Information Processing: 15th International Conference, ICONIP 2008, Auckland, New Zealand, November 25-28, 2008, Revised Selected Papers, Part II (2009)

The concept of Ensemble Learning has been shown to increase predictive power over single base learners. Given the bias-variance-covariance decomposition, diversity is characteristic factor, since ensemble error decreases as diversity increases. In this study, we apply Bagging and Random Subspace Method (RSM) to ensembles of Local Linear Map (LLM)-type, which achieve non-linearity through local linear approximation, supplied with different vector quantization algorithms. The results are compared for several benchmark data sets to those of RandomForest and neural networks. We can show which parameters are of major influence on diversity in ensembles and that using our proposed method of LLM combining RSM we are able to achieve results obtained by other reference ensemble architectures.