Analysis of multilateral service conversations in global business networks

The rapid growth of services available on the Internet and exploited through ever globalizing business networks poses new challenges for service interoperability. New services, from consumer “apps”, enterprise suites, platform and infrastructure resources, are vying for demand with quickly evolving and overlapping capabilities, and shorter cycles of extending service access from user interfaces to software interfaces. Services, drawn from a wider global setting, are subject to greater change and heterogeneity, demanding new requirements for structural and behavioral interface adaptation. In this paper, we analyze service interoperability scenarios in global business networks, and propose new patterns for service interactions, above those proposed over the last 10 years through the development of Web service standards and process choreography languages. By contrast, we reduce assumptions of design-time knowledge required to adapt services, giving way to run-time mismatch resolutions, extend the focus from bilateral to multilateral messaging interactions, and propose declarative ways in which services and interactions take part in long-running conversations via the explicit use of state.

Vehicle-to-vehicle real-time relative positioning using 5.9 GHz DSRC media

Vehicular accidents are one of the deadliest safety hazards and accordingly an immense concern of individuals and governments. Although, a wide range of active autonomous safety systems, such as advanced driving assistance and lane keeping support, are introduced to facilitate safer driving experience, these stand-alone systems have limited capabilities in providing safety. Therefore, cooperative vehicular systems were proposed to fulfill more safety requirements. Most cooperative vehicle-to-vehicle safety applications require relative positioning accuracy of decimeter level with an update rate of at least 10 Hz. These requirements cannot be met via direct navigation or differential positioning techniques. This paper studies a cooperative vehicle platform that aims to facilitate real-time relative positioning (RRP) among adjacent vehicles. The developed system is capable of exchanging both GPS position solutions and raw observations using RTCM-104 format over vehicular dedicated short range communication (DSRC) links. Real-time kinematic (RTK) positioning technique is integrated into the system to enable RRP to be served as an embedded real-time warning system. The 5.9 GHz DSRC technology is adopted as the communication channel among road-side units (RSUs) and on-board units (OBUs) to distribute GPS corrections data received from a nearby reference station via the Internet using cellular technologies, by means of RSUs, as well as to exchange the vehicular real-time GPS raw observation data. Ultimately, each receiving vehicle calculates relative positions of its neighbors to attain a RRP map. A series of real-world data collection experiments was conducted to explore the synergies of both DSRC and positioning systems. The results demonstrate a significant enhancement in precision and availability of relative positioning at mobile vehicles.

Low cost localisation for agricultural robotics

This paper presents a pose estimation approach that is resilient to typical sensor failure and suitable for low cost agricultural robots. Guiding large agricultural machinery with highly accurate GPS/INS systems has become standard practice, however these systems are inappropriate for smaller, lower-cost robots. Our positioning system estimates pose by fusing data from a low-cost global positioning sensor, low-cost inertial sensors and a new technique for vision-based row tracking. The results first demonstrate that our positioning system will accurately guide a robot to perform a coverage task across a 6 hectare field. The results then demonstrate that our vision-based row tracking algorithm improves the performance of the positioning system despite long periods of precision correction signal dropout and intermittent dropouts of the entire GPS sensor.

Aircraft dynamic navigation for unmanned aerial vehicles

This thesis describes the investigation of an Aircraft Dynamic Navigation (ADN) approach, which incorporates an Aircraft Dynamic Model (ADM) directly into the navigation filter of a fixed-wing aircraft or UAV. The result is a novel approach that offers both performance improvements and increased reliability during short-term GPS outages. This is important in allowing future UAVs to achieve routine, unconstrained, and safe operations in commercial environments. The primary contribution of this research is the formulation Unscented Kalman Filter (UKF) which incorporates a complex, non-linear, laterally and longitudinally coupled, ADM, and sensor suite consisting of a Global Positioning System (GPS) receiver, Inertial Measurement Unit (IMU), Electronic Compass (EC), and Air Data (AD) Pitot Static System.

Development of an inter-vehicle communications & positioning platform for transport safety applications

This project is a breakthrough in developing new scientific approaches for the design, development and evaluation of inter-vehicle communications, networking and positioning systems as part of Cooperative Intelligent Transportation Systems ensuring the safety of both roads and rail networks. This research focused on the elicitation, specification, analysis and validation of requirements for Vehicle-to-Vehicle communications and networking, and Vehicle-to-Vehicle positioning, which are accomplished with the research platform developed for this study. A number of mathematical models for communications, networking and positioning were developed from which simulations and field experiments were conducted to evaluate the overall performance of the platform. The outcomes of this research significantly contribute to improving the performance of the communications and positioning components of Cooperative Intelligent Transportation Systems.

Real-time wind speed estimation and compensation for improved flight

This paper presents the development and experimental validation of a prototype system for online estimation and compensation of wind disturbances onboard small Rotorcraft unmanned aerial systems (RUAS). The proposed approach consists of integrating a small pitot-static system onboard the vehicle and using simple but effective algorithms for estimating the wind speed in real time. The baseline flight controller has been augmented with a feed-forward term to compensate for these wind disturbances, thereby improving the flight performance of small RUAS in windy conditions. The paper also investigates the use of online airspeed measurements in a closed-loop for controlling the RUAS forward motion without the aid of a global positioning system (GPS). The results of more than 80 flights with a RUAS confirm the validity of our approach.

The importance of grasslands for animal production and other functions: a review on management and methodological progress in the tropics

The global importance of grasslands is indicated by their extent; they comprise some 26% of total land area and 80% of agriculturally productive land. The majority of grasslands are located in tropical developing countries where they are particularly important to the livelihoods of some one billion poor peoples. Grasslands clearly provide the feed base for grazing livestock and thus numerous high-quality foods, but such livestock also provide products such as fertilizer, transport, traction, fibre and leather. In addition, grasslands provide important services and roles including as water catchments, biodiversity reserves, for cultural and recreational needs, and potentially a carbon sink to alleviate greenhouse gas emissions. Inevitably, such functions may conflict with management for production of livestock products. Much of the increasing global demand for meat and milk, particularly from developing countries, will have to be supplied from grassland ecosystems, and this will provide difficult challenges. Increased production of meat and milk generally requires increased intake of metabolizable energy, and thus increased voluntary intake and/or digestibility of diets selected by grazing animals. These will require more widespread and effective application of improved management. Strategies to improve productivity include fertilizer application, grazing management, greater use of crop by-products, legumes and supplements and manipulation of stocking rate and herbage allowance. However, it is often difficult to predict the efficiency and cost-effectiveness of such strategies, particularly in tropical developing country production systems. Evaluation and on-going adjustment of grazing systems require appropriate and reliable assessment criteria, but these are often lacking. A number of emerging technologies may contribute to timely low-cost acquisition of quantitative information to better understand the soil-pasture-animal interactions and animal management in grassland systems. Development of remote imaging of vegetation, global positioning technology, improved diet markers, near IR spectroscopy and modelling provide improved tools for knowledge-based decisions on the productivity constraints of grazing animals. Individual electronic identification of animals offers opportunities for precision management on an individual animal basis for improved productivity. Improved outcomes in the form of livestock products, services and/or other outcomes from grasslands should be possible, but clearly a diversity of solutions are needed for the vast range of environments and social circumstances of global grasslands.

Development and evaluation of a spatial decision support system for malaria elimination in Bhutan

Background: Bhutan has reduced its malaria incidence significantly in the last 5 years, and is aiming for malaria elimination by 2016. To assist with the management of the Bhutanese malaria elimination programme a spatial decision support system (SDSS) was developed. The current study aims to describe SDSS development and evaluate SDSS utility and acceptability through informant interviews. Methods: The SDSS was developed based on the open-source Quantum geographical information system (QGIS) and piloted to support the distribution of long-lasting insecticidal nets (LLINs) and indoor residual spraying (IRS) in the two sub-districts of Samdrup Jongkhar District. It was subsequently used to support reactive case detection (RACD) in the two sub-districts of Samdrup Jongkhar and two additional sub-districts in Sarpang District. Interviews were conducted to ascertain perceptions on utility and acceptability of 11 informants using the SDSS, including programme and district managers, and field workers. Results: A total of 1502 households with a population of 7165 were enumerated in the four sub-districts, and a total of 3491 LLINs were distributed with one LLIN per 1.7 persons. A total of 279 households representing 728 residents were involved with RACD. Informants considered that the SDSS was an improvement on previous methods for organizing LLIN distribution, IRS and RACD, and could be easily integrated into routine malaria and other vector-borne disease surveillance systems. Informants identified some challenges at the programme and field level, including the need for more skilled personnel to manage the SDSS, and more training to improve the effectiveness of SDSS implementation and use of hardware. Conclusions: The SDSS was well accepted and informants expected its use to be extended to other malaria reporting districts and other vector-borne diseases. Challenges associated with efficient SDSS use included adequate skills and knowledge, access to training and support, and availability of hardware including computers and global positioning system receivers.

Localização colaborativa em robótica de enxame.

Diversas das possíveis aplicações da robótica de enxame demandam que cada robô seja capaz de estimar a sua posição. A informação de localização dos robôs é necessária, por exemplo, para que cada elemento do enxame possa se posicionar dentro de uma formatura de robôs pré-definida. Da mesma forma, quando os robôs atuam como sensores móveis, a informação de posição é necessária para que seja possível identificar o local dos eventos medidos. Em virtude do tamanho, custo e energia dos dispositivos, bem como limitações impostas pelo ambiente de operação, a solução mais evidente, i.e. utilizar um Sistema de Posicionamento Global (GPS), torna-se muitas vezes inviável. O método proposto neste trabalho permite que as posições absolutas de um conjunto de nós desconhecidos sejam estimadas, com base nas coordenadas de um conjunto de nós de referência e nas medidas de distância tomadas entre os nós da rede. A solução é obtida por meio de uma estratégia de processamento distribuído, onde cada nó desconhecido estima sua própria posição e ajuda os seus vizinhos a calcular as suas respectivas coordenadas. A solução conta com um novo método denominado Multi-hop Collaborative Min-Max Localization (MCMM), ora proposto com o objetivo de melhorar a qualidade da posição inicial dos nós desconhecidos em caso de falhas durante o reconhecimento dos nós de referência. O refinamento das posições é feito com base nos algoritmos de busca por retrocesso (BSA) e de otimização por enxame de partículas (PSO), cujos desempenhos são comparados. Para compor a função objetivo, é introduzido um novo método para o cálculo do fator de confiança dos nós da rede, o Fator de Confiança pela Área Min-Max (MMA-CF), o qual é comparado com o Fator de Confiança por Saltos às Referências (HTA-CF), previamente existente. Com base no método de localização proposto, foram desenvolvidos quatro algoritmos, os quais são avaliados por meio de simulações realizadas no MATLABr e experimentos conduzidos em enxames de robôs do tipo Kilobot. O desempenho dos algoritmos é avaliado em problemas com diferentes topologias, quantidades de nós e proporção de nós de referência. O desempenho dos algoritmos é também comparado com o de outros algoritmos de localização, tendo apresentado resultados 40% a 51% melhores. Os resultados das simulações e dos experimentos demonstram a eficácia do método proposto.

Function propagation through nested systems

Concepts of function are central to design but statements about a device's functions can be interpreted in different ways. This raises problems for researchers trying to clarify the foundations of design theory and for those developing design support-tools that can represent and reason about function. By showing how functions relate systems to their sub-systems and super-systems, this article illustrates some limitations of existing function terminology and some problems with existing function statements. To address these issues, a system-relative function terminology is introduced. This is used to demonstrate that systems function not only with respect to their most local super-system, but also with respect to their more global super-systems. © 2012 Elsevier Ltd. All rights reserved.

An asymmetric MOSFET-C band-pass filter with on-chip charge pump auto-tuning

An asymmetric MOSFET-C band-pass filter(BPF)with on chip charge pump auto-tuning is presented.It is implemented in UMC (United Manufacturing Corporation)0.18μm CMOS process technology. The filter system with auto-tuning uses a master-slave technique for continuous tuning in which the charge pump OUtputs 2.663 V, much higher than the power supply voltage, to improve the linearity of the filter. The main filter with third order low-pass and second order high-pass properties is an asymmetric band-pass filter with bandwidth of 2.730-5.340 MHz. The in-band third order harmonic input intercept point(HP3) is 16.621 dBm,wim 50 Ω as the source impedance. The input referred noise iS about 47.455μVrms. The main filter dissipates 3.528 mW while the auto-tuning system dissipates 2.412 mW from a 1.8 V power supply. The filter with the auto-tuning system occupies 0.592 mm~2 and it can be utilized in GPS (global positioning system)and Bluetooth systems.

基于GIS的高速公路养护管理信息系统的设计与开发

China is experiencing a rapid development of highway ever since 1990s. By the end of 2004, the total length of the highway summed up to 33 thousand kilometers, ranking 2n in the world. After the open of highway, the accumulation of time and traffic causes the decrease of its capability. To ensure its good quality, security and operation functions, we should take some reasonable measures to maintain it periodically. At present, a big problem is that the traditional maintain measures can no longer meet the increasing requirements. Due to the characters of highway, the relationship of various maintenance data and geographic positions is even closer than any others. If we wan to improve the quality and efficiency of the maintenance work, particularly when there is need for decision-making, a great number of data that is related to geographic positions are absolutely necessary. Evidently, Geographical Information System (GIS) has incomparably advantages in dealing with these spatial information. As a result, a management system for highway maintenance work based on GIS became inevitable for the development of the maintenance of highway. The purpose of this paper is to establish a management system for highway maintenance work base on Geographical Information System (GIS), Global Positioning System (GPS) and spatial database, to manage all kinds of problems encountered in the work, and to provide support on information and methods. My study mainly includes: (1) Analysis on the current status of the maintenance and management work; overview on the history of domestic and international highway maintenance management systems; identifying the necessity and importance for establishing a management system for highway maintenance work based on GIS. (2) Based on the requirement analysis, I proposed a general design for this management system, and discussed the objective, design principles, framework, systematical structure and function design. (3) Outdoor data collection is not only a prime way to understand the current situation of the road, but also an important method for data update after the system is put into use. This paper also intends to establish a set of plan to collect data efficiently and precisely which is based on GIS and GPS technologies. (4) The maintenance management database is a supporting platform for various maintenance decision-makings. Such decisions need the support of a great amount of data, which would cause other problems, such as the diversity of the data source, difference of data formats. This paper also discussed how to deal with these problems and establish such a database. (5) To propose an approach to assess the condition of pavement, based on GIS and related maintenance models. Among all the maintenance models, the two for assessing and forecasting pavement condition are the most important and mature. This paper also analyzed these two models and introduced them in terms of the integration of models. (6) This paper took the Guangshen Highway for example, explaining how to realize a GIS for management of highway maintenance work.

Automatically Recovering Geometry and Texture from Large Sets of Calibrated Images

Three-dimensional models which contain both geometry and texture have numerous applications such as urban planning, physical simulation, and virtual environments. A major focus of computer vision (and recently graphics) research is the automatic recovery of three-dimensional models from two-dimensional images. After many years of research this goal is yet to be achieved. Most practical modeling systems require substantial human input and unlike automatic systems are not scalable. This thesis presents a novel method for automatically recovering dense surface patches using large sets (1000's) of calibrated images taken from arbitrary positions within the scene. Physical instruments, such as Global Positioning System (GPS), inertial sensors, and inclinometers, are used to estimate the position and orientation of each image. Essentially, the problem is to find corresponding points in each of the images. Once a correspondence has been established, calculating its three-dimensional position is simply a matter of geometry. Long baseline images improve the accuracy. Short baseline images and the large number of images greatly simplifies the correspondence problem. The initial stage of the algorithm is completely local and scales linearly with the number of images. Subsequent stages are global in nature, exploit geometric constraints, and scale quadratically with the complexity of the underlying scene. We describe techniques for: 1) detecting and localizing surface patches; 2) refining camera calibration estimates and rejecting false positive surfels; and 3) grouping surface patches into surfaces and growing the surface along a two-dimensional manifold. We also discuss a method for producing high quality, textured three-dimensional models from these surfaces. Some of the most important characteristics of this approach are that it: 1) uses and refines noisy calibration estimates; 2) compensates for large variations in illumination; 3) tolerates significant soft occlusion (e.g. tree branches); and 4) associates, at a fundamental level, an estimated normal (i.e. no frontal-planar assumption) and texture with each surface patch.

Global value Chains, rising power firms and economic and social upgrading

© Emerald Group Publishing Limited.Purpose – The purpose of this paper is to introduce the global value chain (GVC) approach to understand the relationship between multinational enterprises (MNEs) and the changing patterns of global trade, investment and production, and its impact on economic and social upgrading. It aims to illuminate how GVCs can advance our understanding about MNEs and rising power (RP) firms and their impact on economic and social upgrading in fragmented and dispersed global production systems. Design/methodology/approach – The paper reviews theGVCliterature focusing on two conceptual elements of the GVC approach, governance and upgrading, and highlights three key recent developments in GVCs: concentration, regionalization and synergistic governance. Findings – The paper underscores the complicated role of GVCs in shaping economic and social upgrading for emerging economies, RP firms and developing country firms in general. Rising geographic and organizational concentration in GVCs leads to the uneven distribution of upgrading opportunities in favor of RP firms, and yet economic upgrading may be elusive even for the most established suppliers because of power asymmetry with global buyers. Shifting end markets and the regionalization of value chains can benefit RP firms by presenting alternative markets for upgrading. Yet, without further upgrading, such benefits may be achieved at the expense of social downgrading. Finally, the ineffectiveness of private standards to achieve social upgrading has led to calls for synergistic governance through the cooperation of private, public and social actors, both global and local. Originality/value – The paper illuminates how the GVC approach and its key concepts can contribute to the critical international business and RP firms literature by examining the latest dynamics in GVCs and their impacts on economic and social development in developing countries.

Space-based lidar measurements of global ocean carbon stocks

Global ocean phytoplankton biomass (C-phyto) and total particulate organic carbon (POC) stocks have largely been characterized from space using passive ocean color measurements. A space-based light detection and ranging (lidar) system can provide valuable complementary observations for C-phyto and POC assessments, with benefits including day-night sampling, observations through absorbing aerosols and thin cloud layers, and capabilities for vertical profiling through the water column. Here we use measurements from the Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) to quantify global C-phyto and POC from retrievals of subsurface particulate backscatter coefficients (b(bp)). CALIOP b(bp) data compare favorably with airborne, ship-based, and passive ocean data and yield global average mixed-layer standing stocks of 0.44 Pg C for C-phyto and 1.9 Pg for POC. CALIOP-based C-phyto and POC data exhibit global distributions and seasonal variations consistent with ocean plankton ecology. Our findings support the use of spaceborne lidar measurements for advancing understanding of global plankton systems.