ppxscal/embedding_network huggingface dataset:
A biologically inspired mobility control framework for energy conservation in sensor networks
Authors: Jayanthi Rao, Subir Biswas
Venue: International Journal of Communication Systems (2009)

This paper presents a paradigm for extending network life by introducing energy-aware mobility in wireless sensor networks. The concept of controlled mobility for energy saving has been motivated by a natural grouping behavior that is observed in Emperor penguins in the Antarctic region. During the winters, a group of those penguins form a closely huddled group to improve their collective heat insulation. Individual penguins within a group exhibit a local mobility pattern that ensures that each individual spends roughly equal amount of time at the periphery of the group, where heat loss is the maximum. As a result, the total heat loss of the group is thought to be evenly distributed across all the individuals. In this paper, we first draw a parallel between the heat loss of a penguin at the group periphery, and the routing energy burden of sensor nodes near the aggregating base stations in a sensor network. Then we develop a fully distributed and localized mobility control algorithm for collective extension of the network life. Experimental results demonstrate that the proposed controlled mobility paradigm can significantly extend a sensor network's operating life even in situations where the energy cost of physical node movement is modeled as high as up to four orders of magnitude larger than the energy cost for packet transmission. Copyright &copy; 2009 John Wiley & Sons, Ltd. This paper presents a paradigm for extending network life by introducing energy-aware mobility in sensor networks. Controlled mobility for energy saving has been motivated by a natural grouping behavior that is observed in Emperor penguins in the Antarctic. We develop a fully distributed and localized mobility algorithm for collective extension of network lifetime. Experimental results demonstrate that the proposed paradigm can significantly extend a sensor network's operating life even when physical movement energy cost is up to four orders of magnitude larger than packet transmission cost. Copyright &copy; 2009 John Wiley & Sons, Ltd.
The mathematical model of the plywood production
Authors: Andris Buikis, Janis Cepitis, Solvita Kostjukova
Venue: Proceedings of the 13th WSEAS international conference on Applied mathematics (2008)

The mathematical model of the heat and moisture transfer processes for the porous layered media with the intermediate layers is investigated. Particularly this model is employable for the processing of the plywood. The generalized integral parabolic splines are used in order to transform the system of partial differential equation system to the averaged system of the ordinary differential equations with the continuous coefficients. The finite difference scheme for the problem solving of obtained system is offered.
Providing Observability for OpenMP 3.0 Applications
Authors: Yuan Lin, Oleg Mazurov
Venue: Proceedings of the 5th International Workshop on OpenMP: Evolving OpenMP in an Age of Extreme Parallelism (2009)

Providing observability for OpenMP applications is a technically challenging task. Most current tools treat OpenMP applications as native multi-threaded applications. They expose too much implementation detail while failing to present useful information at the OpenMP abstraction level. In this paper, we present a rich data model that captures the runtime behavior of OpenMP applications. By carefully designing interactions between all involved components (compiler, OpenMP runtime, collector, and analyzer), we are able to collect all needed information and keep overall runtime overhead and data volume low.
Spatial prediction of ozone concentration profiles
Authors: Chivalai Temiyasathit, Seoung Bum Kim, Sun-Kyoung Park
Venue: Computational Statistics Data Analysis (2009)

Ground level ozone is one of the major air pollutants in many urban areas. Ozone formation affects ecosystems and is known to be associated with many adverse health issues in humans. Effective modeling of ozone is a necessary step to develop a system to warn residents of high ozone levels. In the present study we propose a statistical procedure that uses multiscale and functional data analysis to improve the spatial prediction of ozone concentration profiles in the Dallas Fort Worth (DFW) area of Texas. This study uses daily eight-hour ozone concentrations and meteorological predictors during a period between 2003 and 2006 at 14 monitoring sites in the DFW area. Wavelet transformation was used as a means of multiscale data analysis, followed by functional modeling to reduce model complexity. Kriging was then used for spatial prediction. The experimental results with real data demonstrated that the proposed procedures achieved acceptable accuracy of spatial prediction.
H∞ structured model reduction algorithms for linear discrete systems via LMI-based optimisation
Authors: Kwan Ho Lee, Biao Huang
Venue: International Journal of Systems Science (2009)

In this article, H∞ structured model reduction is addressed for linear discrete systems. Two important classes of systems are considered for structured model reduction, i.e. Markov jump systems and uncertain systems. The problem we deal with is the development of algorithms with the flexibility to allow any structure in the reduced-order system design, such as the structure of an original system, decentralisation of a networked system, pole assignment of the reduced system, etc. The algorithms are derived such that an associated model reduction error guarantees to satisfy a prescribed H∞ norm-bound constraint. A new condition for the existence of desired reduced-order models preserving a certain structure is presented in a set of linear matrix inequalities (LMI) and non-convex equality constraints. Effective computational algorithms involving LMI are suggested to solve the matrix inequalities characterising a solution of the structured model reduction problem. Numerical examples demonstrate the advantages of the proposed model reduction method.
Structure Optimization Algorithm for Radial Basis Probabilistic Neural Networks Based on the Moving Median Center Hyperspheres Algorithm
Authors: Ji-Xiang Du, Chuan-Min Zhai
Venue: Proceedings of the 6th International Symposium on Neural Networks: Advances in Neural Networks - Part III (2009)

In this paper, a novel structure optimization algorithm for radial basis probabilistic neural networks (RBPNN) is proposed. Firstly, a moving median center hyperspheres (MMCH) algorithm is proposed to heuristically select the initial hidden layer centers of the RBPNN, and then a hybrid optimization algorithm is adopted to further prune the initial structure of the RBPNN. Finally, the effectiveness and efficiency of our proposed algorithm are evaluated through a plant species identification problem and a palmprint recognition task.
SAP ERP HCM Performance Management, 1st edition
Authors: Christos Kotsakis, Jeremy Masters
Venue:  (2007)

Finding and retaining talented employees is critical to every organization's success. But, do you have an effective process for managing employee performance? Are strategic initiatives being met or even tracked? If you're an SAP HCM professional, analyst, or consultant interested in managing employee performance, this indispensable book will help answer these questions. Using the practical information and best practices provided, you'll discover new methods for process improvement, and you'll find detailed guidance on designing, building, and deploying an effective strategy. The book is composed of two parts: "Overview and Process" and "System Functionality and Implementation", which provides both functional and technical insight based on real-world implementation experience. Special attention is given to explaining the common deployment pain points and the mitigation steps to alleviate these issues. The book covers the latest releases, including the R/3 Enterprise Release (4.7), SAP ERP 2004 (ECC 5.0), and SAP ERP 2005 (ECC 6.0). Highlights: Corporate Strategy Goals versus Objectives Development Planning Objective Setting and Appraisal (OSA) module Appraisal Catalog (Transaction PHAP_CATALOG) Security Authorizations Business Add-Ins (BAdIs) Reporting & Business Intelligence SAP Netweaver Integration including iView configuration
Computationally efficient implementation of combustion chemistry in parallel PDF calculations
Authors: Liuyan Lu, Steven R. Lantz, Zhuyin Ren, Stephen B. Pope
Venue: Journal of Computational Physics (2009)

In parallel calculations of combustion processes with realistic chemistry, the serial in situ adaptive tabulation (ISAT) algorithm [S.B. Pope, Computationally efficient implementation of combustion chemistry using in situ adaptive tabulation, Combustion Theory and Modelling, 1 (1997) 41-63; L. Lu, S.B. Pope, An improved algorithm for in situ adaptive tabulation, Journal of Computational Physics 228 (2009) 361-386] substantially speeds up the chemistry calculations on each processor. To improve the parallel efficiency of large ensembles of such calculations in parallel computations, in this work, the ISAT algorithm is extended to the multi-processor environment, with the aim of minimizing the wall clock time required for the whole ensemble. Parallel ISAT strategies are developed by combining the existing serial ISAT algorithm with different distribution strategies, namely purely local processing (PLP), uniformly random distribution (URAN), and preferential distribution (PREF). The distribution strategies enable the queued load redistribution of chemistry calculations among processors using message passing. They are implemented in the software x2f_mpi, which is a Fortran 95 library for facilitating many parallel evaluations of a general vector function. The relative performance of the parallel ISAT strategies is investigated in different computational regimes via the PDF calculations of multiple partially stirred reactors burning methane/air mixtures. The results show that the performance of ISAT with a fixed distribution strategy strongly depends on certain computational regimes, based on how much memory is available and how much overlap exists between tabulated information on different processors. No one fixed strategy consistently achieves good performance in all the regimes. Therefore, an adaptive distribution strategy, which blends PLP, URAN and PREF, is devised and implemented. It yields consistently good performance in all regimes. In the adaptive parallel ISAT strategy, the type and extent of redistribution is determined ''on the fly'' based on the prediction of future simulation time. Compared to the PLP/ISAT strategy where chemistry calculations are essentially serial, a speed-up factor of up to 30 is achieved. The study also demonstrates that the adaptive strategy has acceptable parallel scalability.
Editable Chat Logs: A Concept for Seamless Integration of Chat Conversations and Documents in Shared Workspaces
Authors: Anja Haake
Venue: Proceeding of the 2006 conference on Cooperative Systems Design: Seamless Integration of Artifacts and Conversations -- Enhanced Concepts of Infrastructure for Communication (2006)

This paper introduces the concept of editable chat logs for shared workspace systems. In shared workspaces offering a chat for synchronous communication, editable chat logs allow to keep and archive transcripts of chat conversations as documents in the group memory. As any other document in the shared workspace, the transcript can be subject to future conversations. Moreover, the transcript can be edited to create new documents or to reuse (parts of) the conversation within other documents. In this way, editable chat logs provide for a seamless integration of chat conversations and documents.
Development and Assessment of the “Science Net” e-Learning System for Science Education at the Elementary School Level
Authors: Takeshi Kitazawa, Masahiro Nagai, Hiroshi Kato, Kanji Akahori
Venue: Proceeding of the 2005 conference on Towards Sustainable and Scalable Educational Innovations Informed by the Learning Sciences: Sharing Good Practices of Research, Experimentation and Innovation (2005)

This paper covers the development of the “Science Net”-an e-learning system for science education at the elementary school level. The authors also analyze relationship between the number of students accessing the system and the consequent effectiveness of learning via questionnaire. The results show that the contents of “schedules of lessons” serve not only the purpose of allowing the student to prepare for the next lesson but also provide useful science education. In addition, students report that it is useful to check lessons when they are absent by downloading worksheets and ask questions of a teacher via a bulletin board system (BBS). And then, reflection learning of 'Science Net' has a close relationship with interest in science.
Design and Application of In-Vehicle Terminal for Car Network System Based on ARM9
Authors: Jing Xu, Tao Lu, Lingling Gao
Venue: Proceedings of the 2008 International Workshop on Education Technology and Training & 2008 International Workshop on Geoscience and Remote Sensing - Volume 02 (2008)

A kind of in-vehicle terminal for car network system based on arm9 has been researched and designed in this paper. The main hardware module of the in-vehicle terminal is introduced in detail and the hardware architecture has been presented as well. The software module and its implementation of the terminal have been explained in detail, including CAN(Controller Area Network) bus module, GPRS(General Packet Radio Service) module, GPS(Global Positioning System) module. The software system of the in-vehicle terminal is implemented, and a kind of practical package format and flow chart between the in-vehicle and the server is put forward. The implementation of the system indicates that cars are directed and controlled well through the terminal.
Exploring social tagging graph for web object classification
Authors: Zhijun Yin, Rui Li, Qiaozhu Mei, Jiawei Han
Venue: Proceedings of the 15th ACM SIGKDD international conference on Knowledge discovery and data mining (2009)

This paper studies web object classification problem with the novel exploration of social tags. Automatically classifying web objects into manageable semantic categories has long been a fundamental preprocess for indexing, browsing, searching, and mining these objects. The explosive growth of heterogeneous web objects, especially non-textual objects such as products, pictures, and videos, has made the problem of web classification increasingly challenging. Such objects often suffer from a lack of easy-extractable features with semantic information, interconnections between each other, as well as training examples with category labels. In this paper, we explore the social tagging data to bridge this gap. We cast web object classification problem as an optimization problem on a graph of objects and tags. We then propose an efficient algorithm which not only utilizes social tags as enriched semantic features for the objects, but also infers the categories of unlabeled objects from both homogeneous and heterogeneous labeled objects, through the implicit connection of social tags. Experiment results show that the exploration of social tags effectively boosts web object classification. Our algorithm significantly outperforms the state-of-the-art of general classification methods.
Segmentation of Salient Regions in Outdoor Scenes Using Imagery and 3-D Data
Authors: Gunhee Kim, Daniel Huber, Martial Hebert
Venue: Proceedings of the 2008 IEEE Workshop on Applications of Computer Vision (2008)

This paper describes a segmentation method for extracting salient regions in outdoor scenes using both 3-D laser scans and imagery information. Our approach is a bottom-up attentive process with out any high-level priors, models, or learning. As a mid-level vision task, it is not only robust against noise and outliers but it also provides valuable information for other high-level tasks in the form of optimal segments and their ranked saliency. In this paper, we propose a new saliency definition for 3-D point clouds and we incorporate it with saliency features from color in formation.
Effects of multiple collaborated data streams in wireless sensor networks
Authors: Li Liu, Xiaoyan Hong, Jingyuan Zhang
Venue: Proceedings of the 47th Annual Southeast Regional Conference (2009)

Wireless sensor networks, in our paper, MICAz radio boards with sensors attached to them. Allow us to collect many information around us. When multiple collaborated input streams present, understanding the data with correct data fusion algorithms is important. In this paper, we will present the influences of the thresholds on data from wireless sensors. The hardware used in our project is the Berkeley mote MPR2400 and the MTS310 sensor board. The MIB600 is used as the Ethernet gateway interface for the motes. The MTS310 sensor is used successfully in the project to collect data from passing vehicles. The main topic of this project was to implement a form of machine learning by having the back end computer predict with high confidence that there is a vehicle present. The program MoteView is very efficient in configuring and surveying the motes in real time. This paper is an attempt to demonstrate the abilities of the current wireless sensor network technology.
Trends and issues of regulative support use during inquiry learning: Patterns from three studies
Authors: Sarah Manlove, Ard W. Lazonder, Ton de Jong
Venue: Computers in Human Behavior (2009)

This paper looks across three experimental studies that examined supports designed to assist high-school students (age 15-19) with cognitive regulation of their physics inquiry learning efforts in a technology-enhanced learning environment called Co-Lab. Cognitive regulation involves the recursive processes of planning, monitoring, and evaluation during learning, and is generally thought to enhance learning gains for students. The research synthesis described in this paper examined the usage effects of a support tool called the process coordinator (PC) on learning outcomes. This tool incorporated goal-lists, hints, prompts, cues, and templates to support the cognitive regulation skills of students during a fluid dynamics task. Students were asked to produce two learning outcomes of their investigations: system dynamics models and lab reports. Results from the three studies indicated trends in frequent use of the PC for planning activities, but low usage for monitoring and evaluation. Correlational analysis revealed two trends with regard to how these regulative activities impacted learning outcomes. First, consistent positive correlations were apparent between regulative activities and lab report scores of students and second, consistent negative correlations between the use of supports and model quality scores. Trends with regard to how task complexity, time, and student prior experience impacted these findings are also presented with suggestions for future research.
Visualizing the search process of particle swarm optimization
Authors: Yong-Hyuk Kim, Kang Hoon Lee, Yourim Yoon
Venue: Proceedings of the 11th Annual conference on Genetic and evolutionary computation (2009)

It is a hard problem to understand the search process of particle swarm optimization over high-dimensional domain. The visualization depicts the total search process and then it will allow better understanding of how to tune the algorithm. For the investigation, we adopt Sammon's mapping, which is a well-known distance-preserving mapping. We demonstrate the usefulness of the proposed methodology by applying it to some function optimization problems.
Solution of nonlinear convection-diffusion problems by a conservative Galerkin-characteristics method
Authors: Mohammed Shuker Mahmood
Venue: Numerische Mathematik (2009)

We consider a scheme for nonlinear (degenerate) convection dominant diffusion problems that arise in contaminant transport in porous media with equilibrium adsorption isotherm. This scheme is based on a regularization relaxation scheme that has been introduced by J&#x00e4;ger and Ka&#x010d;ur (Numer Math 60:407&#x2013;427, 1991; M2AN Math Model Numer Anal 29(N5):605&#x2013;627, 1995) with a type of numerical integration by Bermejo (SIAM J Numer Anal 32:425&#x2013;455, 1995) to the modified method of characteristics with adjusted advection MMOCAA that was recently developed by Douglas et&#x00a0;al. (Numer Math 83(3):353&#x2013;369, 1999; Comput Geosci 1:155&#x2013;190, 1997). We present another variant of adjusting advection method. The convergence of the scheme is proved. An error estimate of the approximated scheme is derived. Computational experiments are carried out to illustrate the capability of the scheme to conserve the mass.
Data-Driven Impostor Selection for T-Norm Score Normalisation and the Background Dataset in SVM-Based Speaker Verification
Authors: Mitchell Mclaren, Robbie Vogt, Brendan Baker, Sridha Sridharan
Venue: Proceedings of the Third International Conference on Advances in Biometrics (2009)

A data-driven background dataset refinement technique was recently proposed for SVM based speaker verification. This method selects a refined SVM background dataset from a set of candidate impostor examples after individually ranking examples by their relevance. This paper extends this technique to the refinement of the T-norm dataset for SVM-based speaker verification. The independent refinement of the background and T-norm datasets provides a means of investigating the sensitivity of SVM-based speaker verification performance to the selection of each of these datasets. Using refined datasets provided improvements of 13% in min. DCF and 9% in EER over the full set of impostor examples on the 2006 SRE corpus with the majority of these gains due to refinement of the T-norm dataset. Similar trends were observed for the unseen data of the NIST 2008 SRE.
On Domain Theory over Girard Quantales
Authors: Paweł Waszkiewicz
Venue: Fundamenta Informaticae (2009)

This paper is about a generalization of Scott's domain theory in such a way that its definitions and theorems become meaningful in quasimetric spaces. The generalization is achieved by a change of logic: the fundamental concepts of original domain theory (order, way-below relation, Scott-open sets, continuous maps, etc.) are interpreted as predicates that are valued in an arbitrary completely distributive Girard quantale (a CDG quantale). Girard quantales are known to provide a sound and complete semantics for commutative linear logic, and complete distributivity adds a notion of approximation to our setup. Consequently, in this paper we speak about domain theory based on commutative linear logic with some additional reasoning principles following from approximation between truth values. Concretely, we: (1) show how to define continuous Q-domains, i.e. continuous domains over a CDG quantale Q; (2) study their way-below relation, and (3) study the rounded ideal completion of Q-abstract bases. As a case study, we (4) demonstrate that the domain-theoretic construction of the Hoare, Smyth and Plotkin powerdomains of a continuous dcpo can be straightforwardly adapted to yield corresponding constructions for continuous Q-domains.