RoboNetSim: An integrated framework for multi-robot and network simulation

In networked multi-robot systems, communication plays a major role defining system’s dynamics and performance. Unfortunately, existing multi-robot simulators do not provide advanced communication models. Therefore, given the intrinsic unreliability of wireless communications, significant differences might be observed between simulation and real-world results.Addressing these issues, we present RoboNetSim, an integrated simulation framework for communication-realistic simulation of networked multi-robot systems. RoboNetSim integrates multi-robot simulators with network simulators. We present two model implementations based on ARGoS at the robotic side, and NS-2 and NS-3 as network simulators. We evaluate the framework in terms of accuracy and computational performance, showing that it can efficiently simulate systems consisting of hundreds of robots.Using the Stage simulator as an example, we also show the integration of a robotic simulator with RoboNetSim by only adapting robot controllers, without the need to adapt the general code of the simulator.Finally, we demonstrate the effects of communication on mobile multi-robot systems. We consider two different case studies: a distributed coordination and task assignment scenario, and a coordinated mobility scenario. We compare realistic network simulation with simplified communication models and algorithms, and we study the resulting behavior and performance of the multi-robot system and the impact of different parameters.     

AspectC++: An integrated approach for static and dynamic adaptation of system software

Modern computer systems require an enormous amount of flexibility. This is especially the case in low-level system software, from embedded devices to networking services. From literature and practice, various approaches to modularize and integrate adaptations have been investigated. However, most of this work is implemented with dynamic languages that offer extensive run-time support and enable easy integration of such approaches. System software is written in languages like C or C++ in order to minimize utilization of system resources and maximize efficiency. While for these languages highly optimized and reliable compilers are available, the support for static and dynamic adaptation is rather limited. In order to overcome these limitations, we present an adaptation approach that is based on a sophisticated combination of static and dynamic aspect weaving for aspects written in AspectC++. This facilitates the incremental evolution and deployment of system software that has to be “always on”. We demonstrate the feasibility of our approach and its applicability to two pieces of system software, namely the Squid web proxy and the eCos operating system, which is used in the domain of resource-constrained deeply embedded systems.     

ROOT — A C++ framework for petabyte data storage, statistical analysis and visualization

A new stable version (“production version”) v5.28.00 of ROOT [1] has been published [2]. It features several major improvements in many areas, most noteworthy data storage performance as well as statistics and graphics features. Some of these improvements have already been predicted in the original publication Antcheva et al. (2009) [3]. This version will be maintained for at least 6 months; new minor revisions (“patch releases”) will be published [4] to solve problems reported with this version.

New version program summary

Program title: ROOTCatalogue identifier: AEFA_v2_0Program summary URL:http://cpc.cs.qub.ac.uk/summaries/AEFA_v2_0.htmlProgram obtainable from: CPC Program Library, Queen?s University, Belfast, N. IrelandLicensing provisions: GNU Lesser Public License v.2.1No. of lines in distributed program, including test data, etc.: 2 934 693No. of bytes in distributed program, including test data, etc.: 1009Distribution format: tar.gzProgramming language: C++Computer: Intel i386, Intel x86-64, Motorola PPC, Sun Sparc, HP PA-RISCOperating system: GNU/Linux, Windows XP/Vista/7, Mac OS X, FreeBSD, OpenBSD, Solaris, HP-UX, AIXHas the code been vectorized or parallelized?: YesRAM: > 55 MbytesClassification: 4, 9, 11.9, 14Catalogue identifier of previous version: AEFA_v1_0Journal reference of previous version: Comput. Phys. Commun. 180 (2009) 2499Does the new version supersede the previous version?: YesNature of problem: Storage, analysis and visualization of scientific dataSolution method: Object store, wide range of analysis algorithms and visualization methodsReasons for new version: Added features and corrections of deficienciesSummary of revisions: The release notes at http://root.cern.ch/root/v528/Version528.news.html give a module-oriented overview of the changes in v5.28.00. Highlights include

• • 

  File format Reading of TTrees has been improved dramatically with respect to CPU time (30%) and notably with respect to disk space.

• • 

  Histograms A new TEfficiency class has been provided to handle the calculation of efficiencies and their uncertainties, TH2Poly for polygon-shaped bins (e.g. maps), TKDE for kernel density estimation, and TSVDUnfold for singular value decomposition.

• • 

  Graphics Kerning is now supported in TLatex, PostScript and PDF; a table of contents can be added to PDF files. A new font provides italic symbols. A TPad containing GL can be stored in a binary (i.e. non-vector) image file; add support for full-scene anti-aliasing. Usability enhancements to EVE.

• • 

  Math New interfaces for generating random number according to a given distribution, goodness of fit tests of unbinned data, binning multidimensional data, and several advanced statistical functions were added.

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  RooFit Introduction of HistFactory; major additions to RooStats.

• • 

  TMVA Updated to version 4.1.0, adding e.g. the support for simultaneous classification of multiple output classes for several multivariate methods.

• • 

  PROOF Many new features, adding to PROOF?s usability, plus improvements and fixes.

• • 

  PyROOT Support of Python 3 has been added.

• • 

  Tutorials Several new tutorials were provided for above new features (notably RooStats).

A detailed list of all the changes is available at http://root.cern.ch/root/htmldoc/examples/V5.Additional comments: For an up-to-date author list see: http://root.cern.ch/drupal/content/root-development-team and http://root.cern.ch/drupal/content/former-root-developers.The distribution file for this program is over 30 Mbytes and therefore is not delivered directly when download or E-mail is requested. Instead a html file giving details of how the program can be obtained is sent.Running time: Depending on the data size and complexity of analysis algorithms.References:

• [1] 

  http://root.cern.ch.

• [2] 

  http://root.cern.ch/drupal/content/production-version-528.

• [3] 

  I. Antcheva, M. Ballintijn, B. Bellenot, M. Biskup, R. Brun, N. Buncic, Ph. Canal, D. Casadei, O. Couet, V. Fine, L. Franco, G. Ganis, A. Gheata, D. Gonzalez Maline, M. Goto, J. Iwaszkiewicz, A. Kreshuk, D. Marcos Segura, R. Maunder, L. Moneta, A. Naumann, E. Offermann, V. Onuchin, S. Panacek, F. Rademakers, P. Russo, M. Tadel, ROOT — A C++ framework for petabyte data storage, statistical analysis and visualization, Comput. Phys. Commun. 180 (2009) 2499.

• [4] 

  http://root.cern.ch/drupal/content/root-version-v5-28-00-patch-release-notes.

     

An integrated QFD framework with multiple formatted and incomplete preferences: A sustainable supply chain application

Merging sustainable development with the business, and taking goals into account from its three dimensions (i.e., economic, environmental and social) which are derived from customer and stakeholder requirements have been a potential source of competitive differentiation for firms. Academic and corporate interest in sustainable supply chain (SSC) management has also risen considerably in recent years. This paper examines the components and elements of SSC management and how they serve as a foundation for an evaluation framework. By using quality function deployment (QFD) as a product/system planning and improvement tool, an effective SSC structure can be obtained. QFD uses a matrix called the “House of Quality” (HoQ), and constructing the HoQ is a critical step in the application of QFD as it translates customer requirements into engineering characteristics. However, participants of HoQ construction sessions tend to provide information about their individual judgments in multiple formats such as numerically or linguistically depending on their different knowledge, experience, culture and circumstance. Furthermore, they can generate incomplete preferences which are challenging to assess in a consistent way. Therefore, the objective of this study is to apply an extended QFD methodology in SSC by introducing a new group decision making (GDM) approach that takes multiple preference formats and incomplete information into account and fusions different formats of expressions into one uniform group decision by means of the fuzzy set theory. To assess the validity of the proposed approach, a case study conducted at HAVI Logistics-Turkey is also presented in the paper.     

An integrated framework for effective service and repair in the automotive domain: An application of association mining and case-based-reasoning

In this paper, we propose a novel integrated framework combining association rule mining, case-based-reasoning and text mining that can be used to continuously improve service and repair in an automotive domain. The developed framework enables identification of anomalies in the field that cause customer dissatisfaction and performs root cause investigation of the anomalies. It also facilitates identification of the best practices in the field and learning from these best practices to achieve lean and effective service. Association rule mining is used for the anomaly detection and the root cause investigation, while case-based-reasoning in conjunction with text mining is used to learn from the best practices. The integrated system is implemented in a web based distributed architecture and has been tested on real life data.     

An integrated range-sensing, segmentation and registration framework for the characterization of intra-surgical brain deformations in image-guided surgery

Image-guided surgery (IGS) is a technique for localizing anatomical structures on the basis of volumetric image data and for determining the optimal surgical path to reach these structures, by the means of a localization device, or probe, whose position is tracked over time. The usefulness of this technology hinges on the accuracy of the transformation between the image volume and the space occupied by the patient anatomy and spanned by the probe. Unfortunately, in neurosurgery this transformation can be degraded by intra-surgical brain shift, which often measures more than 10 mm and can exceed 25 mm. We propose a method for characterizing brain shift that is based on non-rigid surface registration, and can be combined with a constitutively realistic finite element approach for volumetric displacement estimation. The proposed registration method integrates in a unified framework all of the stages required to estimate the movement of the cortical surface in the operating room: model-based segmentation of the pre-operative brain surface in magnetic resonance image data, range-sensing of the cortex in the OR, range–MR rigid transformation computation, and range-based non-rigid brain motion estimation. The brain segmentation technique is an adaptation of the surface evolution model. Its convergence to the brain boundary is the result of a speed term restricted to white and grey matter voxels made explicit by a classifier, and the final result is post-processed to yield a Closest Point Map of the brain surface in MR space. In turn, this Closest Point Map is used to produce the homologous pairs required to determine a highly efficient, 2D spline-based, Iterative Closest Point (ICP) non-rigid surface registration. The baseline for computing intra-operative brain displacement, as well as the initial starting point of the non-rigid ICP registration, is determined by a very good rigid range–MR transformation, produced by a simple procedure for relating the range coordinate system to that of the probe, and ultimately to that of the MR volume.     

An integrated framework for the analysis of dependable interactive systems (IFADIS): Its tool support and evaluation

This paper discusses a method for the analysis of dependable interactive systems using model checking, and its support by a tool designed to make it accessible to a broader community. The method and the tool are designed to be of value to system engineers, usability engineers and software engineers. It has been designed to help usability engineers by making those aspects of the analysis relevant to them explicit while concealing those aspects of modelling and model checking that are not relevant. The paper presents the results of a user evaluation of the effectiveness of aspects of the tool and how it supports the proposed method. The tool was constructed while both authors worked in the Human Computer Interaction Group. Department of Computer Science, University of York, UK.     

VGE-CUGrid: An integrated platform for efficient configuration,computation, and visualization of MM5

The platform of VGE-CUGrid integrates a computational grid (CUGrid) and a virtual geographic environment (VGE) to enable an efficient life-cycle process of MM5. The CUGrid is used to speed up MM5 computation. The VGE, which is supported by an underlying GIS system and virtual reality, is adopted as the friendly and efficient interface for initiation, computation, and visualization and analysis of MM5.     

An integrated framework of genetic network programming and multi-layer perceptron neural network for prediction of daily stock return: An application in Tehran stock exchange market

Evolutionary algorithms are generally used to find or generate the best individuals in a population. Whenever these algorithms are applied to agent systems, they will lead to optimal solutions. Genetic Network Programming (GNP), which contains graph networks, is one of the developed evolutionary algorithms. When the aim is to forecast the share price or return, ascending and descending trends, volatilities, recent returns, fundamental and technical factors have remarkable impacts on the prediction. This is why technical indicators are used to constitute a set of trading rules. In this paper, we apply an integrated framework consisting of GNP model along with a reinforcement learning and Multi-Layer Perceptron (MLP) neural network to classify data and also time series models to forecast the stock return. Moreover, we utilize rules of accumulation based on the GNP model’s results to forecast the return. The aim of using these models alongside one another is to estimate one-day return. The results derived from 9 stocks with regard to the Tehran Stock Exchange Market. GNP extracts a prodigious number of rules on the basis of 5 technical indicators with 3 times period. Next, MLP network classifies data and finds the similarity between future data and past data concerning a stock (5 sub-period) through classification. Subsequently, a number of conditions are established, in order to choose the best estimation between GNP-RL and ARMA. Distinct comparison with the ARMA–GARCH model, which is operated for return estimation and risk measurement in many researches, demonstrates an extended forecasting power of the proposed model, by the name of GNP–ARMA, reducing error by a mean of 16%.     

An integrated replenishment model with quantity discounts, reentry and downward substitution for control wafers

This paper considers control wafers replenishment problem in wafer fabrication factories. A dynamic lot-sizing replenishment problem with reentry and downward substitution is examined in a pulling control production environment. The objective is to set the inventory level so as to minimize the total cost of control wafers, where the costs include order cost, purchase cost, setup cost, production cost and holding cost, while maintaining the same level of production throughput. In addition, purchase quantity discounts and precise inventory level are considered in the replenishment model. The control wafers replenishment problem is first constructed as a network, and is then transformed into a mixed integer programming model. Lastly, an efficient heuristic algorithm is proposed for solving large-scale problems. A numerical example is given to illustrate the practicality for empirical investigation. The results demonstrate that the proposed mixed integer programming model and the heuristic algorithm are effective tools for determining the inventory level of control wafers for multi-grades in multi-periods.     

An integrated biophysical and socio-economic framework for analysis of climate change adaptation strategies: The case of a New Zealand dairy farming system

The development of effective climate change adaptation strategies for complex, adaptive socio-ecological systems such as farming systems, requires an in-depth understanding of both the dynamic nature of the systems themselves and the changing environment in which they operate.To date, adaptation studies in the New Zealand dairy sector have been either bottom-up, qualitative social research with farmers and communities, or top-down, quantitative biophysical modelling. Each of these approaches has clear benefits as well as significant limitations. This review considers concepts and approaches that support the potential for different disciplines to complement each other in developing a more in-depth understanding of farming systems and their adaptive potential. For this purpose, a Mixed Methods Framework is presented, using examples from a pilot study of a New Zealand dairy farm to illustrate the complementarities between the two current approaches.By presenting this methodology in a specific context, the review provides the theoretical basis for a practical way to integrate quantitative and qualitative research for climate change adaptation research.     

An organic matter and nitrogen dynamics model for the ecological analysis of integrated aquaculture/agriculture systems: I. model development and calibration

A dynamic and mechanistic mass balance model (Integrated Aquaculture/Agriculture System model, or IAAS) for predicting nitrogen and organic matter outputs from aquaculture ponds and their subsequent recycling in conventional agriculture practices has been developed and calibrated using data from Honduras, Thailand and Malawi. The model, developed using Stella™ modeling software (High Performance Systems, Inc. Hanover, New Hampshire), simulates individual fish growth, organic matter, nitrogen (organic, total ammonia and nitrate), dissolved oxygen and phytoplankton, crop growth, soil nitrogen concentrations and soil water balance. Processes included in the model are fish growth, crop biomass growth, allochthonous and autochthonous organic matter production, organic matter decomposition, nitrogen input, nitrogen mineralization, nitrification, denitrification, diffusion, uptake and leaching. The model has been calibrated using literature and observed parameter values from experiments. The calibration procedure involves running the model using inputs from observed data, comparing the model output to observed data, and making appropriate adjustments to parameter values until a general fit between the model and observed values is observed. The structure of the model allows users to modify parameter values to suit different simulation scenarios via a user interface display that also includes graphs and tables for model output.     

An organic matter and nitrogen dynamics model for the ecological analysis of integrated aquaculture/agriculture systems: II. Model evaluation and application

The performance of a model developed to simulate organic matter and nitrogen dynamics in integrated aquaculture/agriculture systems was evaluated using sensitivity analysis and model verification procedures with data from three sites. The model sensitivity analysis results were used to identify parameters that required high accuracy in measurement, and to suggest areas of future research in integrated aquaculture/agriculture systems. Model sensitivity analysis results showed that research on stocking density, sediment processes and water management practices was required, in order to improve the overall understanding of the functioning of the integrated aquaculture/agriculture system. Results from model verification runs showed that the model performance was satisfactory with respect to fish growth, crop growth, pond and terrestrial nitrogen and organic matter simulations. However, the modeling of phytoplankton biomass was less satisfactory and the results suggested the need for more site-specific calibration of exogenous factors and the consideration of phytoplankton species composition in simulating grazing preferences by fish. Application of the model to investigate the effects of different cycling pathways on nitrogen retention and productivity showed that the recycling of plant wastes to aquaculture ponds had a major effect in reducing system nitrogen losses and increasing system productivity. Sediment organic matter processes were identified as the major determinants of system nitrogen retention, as measured by the nitrogen retention index. The modeling study also showed that the number of linkages between the aquaculture and agriculture components was not directly related to nitrogen retention and productivity in the system. The results of the modeling study suggest that the system nitrogen status may be more important than the number of pathways in determining the number and type of cycling pathways that should be incorporated in integrated aquaculture/agriculture system.     

An operational,multi-scale,multi-model system for consensus-based,integrated water management and policy analysis: The Netherlands Hydrological Instrument

Water management in the Netherlands applies to a dense network of surface waters for discharge, storage and distribution, serving highly valuable land-use. National and regional water authorities develop long-term plans for sustainable water use and safety under changing climate conditions. The decisions about investments on adaptive measures are based on analysis supported by the Netherlands Hydrological Instrument NHI based on the best available data and state-of-the-art technology and developed through collaboration between national research institutes. The NHI consists of various physical models at appropriate temporal and spatial scales for all parts of the water system. Intelligent connectors provide transfer between different scales and fast computation, by coupling model codes at a deep level in software. A workflow and version management system guarantees consistency in the data, software, computations and results. The NHI is freely available to hydrologists via an open web interface that enables exchange of all data and tools.