Toward the regulation of ubiquitous mobile government: a case study on location-based emergency services in Australia

Mobile alerts, notifications and location-based emergency warning systems are now an established part of mobile government strategies in an increasing number of countries worldwide. In Australia the national emergency warning system (NEWS) was instituted after the tragic Black Saturday Victorian Bushfires of February 2009. NEWS has enabled the provision of public information from the government to the citizen during emergencies anywhere and any time. Moving on from traditional short message service (SMS) notifications and cell broadcasting to more advanced location-based services, this paper explores the major issues faced by government, business and society at large, toward the realization of a fully fledged emergency system for personal mobile devices. This qualitative study contains two phases: phase 1 gathered issues from the general public via an open-ended survey question, and phase 2 gathered issues from key informant interviews. The data was analyzed using qualitative content analysis techniques. The results are presented in a narrative form granting detailed insight into the main challenges faced in the deployment of a mobile government application. The complex interplay between government agencies, telecommunications carriers and the Australian public is presented, ultimately leading down a path of regulation. By using a qualitative approach it is hoped that the intimate lessons learnt in the Australian landscape can be applied to other nations considering mobile government applications. The outcome of the paper is predominantly practical providing a series of recommendations toward the successful deployment of mobile government applications.     

Estimated global nitrogen deposition using NO2 column density

Global nitrogen deposition has increased over the past 100 years. Monitoring and simulation studies of nitrogen deposition have evaluated nitrogen deposition at both the global and regional scale. With the development of remote-sensing instruments, tropospheric NO₂ column density retrieved from Global Ozone Monitoring Experiment (GOME) and Scanning Imaging Absorption Spectrometer for Atmospheric Chartography (SCIAMACHY) sensors now provides us with a new opportunity to understand changes in reactive nitrogen in the atmosphere. The concentration of NO₂ in the atmosphere has a significant effect on atmospheric nitrogen deposition. According to the general nitrogen deposition calculation method, we use the principal component regression method to evaluate global nitrogen deposition based on global NO₂ column density and meteorological data. From the accuracy of the simulation, about 70% of the land area of the Earth passed a significance test of regression. In addition, NO₂ column density has a significant influence on regression results over 44% of global land. The simulated results show that global average nitrogen deposition was 0.34 g m^?2 yr^?1 from 1996 to 2009 and is increasing at about 1% per year. Our simulated results show that China, Europe, and the USA are the three hotspots of nitrogen deposition according to previous research findings. In this study, Southern Asia was found to be another hotspot of nitrogen deposition (about 1.58 g m^?2 yr^?1 and maintaining a high growth rate). As nitrogen deposition increases, the number of regions threatened by high nitrogen deposits is also increasing. With N emissions continuing to increase in the future, areas whose ecosystem is affected by high level nitrogen deposition will increase.     

Capability representation model for heterogeneous remote sensing sensors: Case study on soil moisture monitoring

Sensor capability information can be used as a basis for the integrated management of vast and heterogeneous remote sensing sensors in Global Earth Observation System of Systems environment. However, the existing representation of this information shows an inconsistent pattern, incomplete capability aspects, and casual expression forms, resulting in information silos among different systems. A sensor capability representation model (SCRM) is proposed in this study. Based on the Meta Object Facility architecture, a five-tuple hierarchical SCRM framework is formulated. Five specific representation element collections for typical remote sensing sensor types are developed to satisfy the requirements of detailed capability expression. The Open Geospatial Consortium Sensor Model Language is used as the expression form of the proposed SCRM. A prototype system is developed and a case study is conducted for a soil moisture monitoring application in Baoxie Town. The SCRM can also be extensively utilised for other environmental monitoring and modelling situations.     

A global 1° by 1° NDVI data set for climate studies derived from the GIMMS continental NDVI data

A nine-year (1982–1990) global normalized difference vegetation index (NDVI) data set with a spatial resolution of 1° by 1° and a temporal resolution of one month was compiled for use in climate studies. This data set was derived from higher resolution (5–8 km) monthly continental NDVI data sets that have been processed and archived by the Global Inventory Monitoring and Modelling Studies (GIMMS) group at NASA/Goddard Space Flight Center. The continental GIMMS NDVI data sets were calculated from Global Area Coverage (GAC) data collected at daily intervals by the Advanced Very High Resolution Radiometer (AVHRR) onboard the NOAA-7, -9 and -11 satellites

The global 1° by 1° NDVI data set was produced to calculate land surface parameters for use within general circulation model J of the atmosphere (GCM). In view of this quantitative application, an evaluation is given of the representation by the NDVI data of the spectral properties of vegetation at the landsurface. Errors are defined as deviations from measurements obtained under standard conditions, i.e., conditions at the-top-of-the-atmosphere with no clouds, clear atmosphere, near-nadir viewing angles, overhead Sun, and invariant soil background. The discussion includes an assessment of (1) the data collected and processed onboard the AVHRR; (2) processing of the AVHRR data into the continental GIMMS NDVI data sets; (3) resampling of the continental data sets to a 1° by 1° data set; and (4) propagation of inconsistencies and biases from (1), (2) and (3) into the 1° by 1° global NDVI data. Examples are shown of the temporal and spatial variations in spectral properties of vegetation contained in the 1° by 1° NDVI data, and these are compared with the dynamics of biophysical parameters derived from land cover classes that were used in previous climate studies.     

Global Positioning System (GPS) Time Dissemination for Real-Time Applications

This paper presents an overview of the Global Positioning System (GPS) for the potential precise time and time interval user with special reference to real-time systems. An overview of GPS operation is presented, and GPS error sources are described as they relate to the timing user. A review of receiver types and receiver tasks provides the basis for understanding GPS time transfer techniques. The accuracies provided by different techniques are reviewed and the special requirements for GPS time and frequency receivers as well as modern timing receiver enhancements are described. The precise time standard provided by GPS is traced through its path from global standards to the user application. GPS time dissemination failure modes that result from control problems, space craft failures, and receiver failures are outlined.     

Instance based personalized multi-form image browsing and retrieval

It is important to adapt and personalize image browsing and retrieval systems based on users’ preferences for improved user experience and satisfaction. In this paper, we present a novel instance based personalized multi-form image representation with implicit relevance feedback and adaptive weighting approach for image browsing and retrieval systems. In the proposed system, images are grouped into forms, which represent different information on images such as location, content etc. We conducted user interviews on image browsing, sharing and retrieval systems for understanding image browsing and searching behaviors of users. Based on the insights gained from the user interview study we propose an adaptive weighting method and implicit relevance feedback for multi-form structures that aim to improve the efficiency and accuracy of the system. Statistics of the past actions are considered for modeling the target of the users. Thus, on each iteration weights of the forms are updated adaptively. Moreover, retrieval results are modified according to the users’ preferences on iterations in order to improve personalized user experience. The proposed method has been evaluated and results are illustrated in the paper. It is shown that, satisfactory improvements can be achieved with proposed approaches in the multi-form scheme.     

Design of a distributed CODASYL database system

A general model for distributed database systems based on the three-level architecture is presented. How concrete architectural forms can be derived from the general model is illustrated by means of the CODASYL database model. A new language is introduced, the data partition language, in which all distribution specific statements are concentrated. The application of distribution predicates in the data partition language to form distribution units leads to the concept of a “distribution graph”—it is a subset of the schema graph and defines the validity scope of a distribution predicate. Global database keys, global currency indicators and multiple record access are suggested to manipulate distributed CODASYL databases.     

Self-managed topologies in P2P networks

The problem of efficient resource location is an important open issue in P2P systems. This paper introduces DANTE, a self-adapting P2P system that changes its peer links to form topologies where resources are located in an efficient manner via random walks. Additionally, this same self-adaptation capacity makes DANTE capable of reacting to events like changes in the system load or attacks on well-connected nodes by adjusting the topology to the new scenario. This adaptive behavior emerges as the global result of the individual work of nodes, without the intervention of any central entity or the need for global knowledge. Simulations show that this adaptation process makes the system scalable, resilient to attacks, and tolerant to a high transitivity of peers. Simulations are also used to compare this solution with other well-known self-adapting P2P system. From these results it can be concluded that the topologies achieved by DANTE offer better performance.     

Global exponential stability analysis of cellular neural networks with multiple time delays

Global exponential stability problems are investigated for cellular neural networks （CNN） with multiple time-varying delays. Several new criteria in linear matrix inequality form or in algebraic form are presented to ascertain the uniqueness and global exponential stability of the equilibrium point for CNN with multiple time-varying delays and with constant time delays. The proposed method has the advantage of considering the difference of neuronal excitatory and inhibitory effects, which is also computationally efficient as it can be solved numerically using the recently developed interior-point algorithm or be checked using simple algebraic calculation. In addition, the proposed results generalize and improve upon some previous works. Two numerical examples are used to show the effectiveness of the obtained results.     

Global exponential stability analysis of cellular neural networks with multiple time delays

Global exponential stability problems are investigated for cellular neural networks (CNN) with multiple time-varying delays. Several new criteria in linear matrix inequality form or in algebraic form are presented to ascertain the uniqueness and global exponential stability of the equilibrium point for CNN with multiple time-varying delays and with constant time delays. The proposed method has the advantage of considering the difference of neuronal excitatory and inhibitory effects, which is also computationally efficient as it can be solved numerically using the recently developed interior-point algorithm or be checked using simple algebraic calculation. In addition, the proposed results generalize and improve upon some previous works. Two numerical examples are used to show the effectiveness of the obtained results.     

Liar liar,pants on fire; or how to use subjective logic and argumentation to evaluate information from untrustworthy sources

This paper presents a non-prioritized belief change operator, designed specifically for incorporating new information from many heterogeneous sources in an uncertain environment. We take into account that sources may be untrustworthy and provide a principled method for dealing with the reception of contradictory information. We specify a novel Data-Oriented Belief Revision Operator, that uses a trust model, subjective logic, and a preference-based argumentation framework to evaluate novel information and change the agent’s belief set accordingly. We apply this belief change operator in a collaborative traffic scenario, where we show that (1) some form of trust-based non-prioritized belief change operator is necessary, and (2) in a direct comparison between our operator and a previous proposition, our operator performs at least as well in all scenarios, and significantly better in some.     

A new global tree-cover percentage map using MODIS data

Global tree-cover percentage is an important parameter used to understand the global environment. However, the available global percentage tree-cover products are few. Producing a new global-scale data set facilitates comparison analysis among maps. Our study was undertaken to map tree-cover percentage on a global scale with better accuracy than previous studies. In this study, we estimated the tree-cover percentage on a global scale at a pixel size of 500 m using a modified supervised regression tree algorithm from the Moderate Resolution Imaging Spectroradiometer (MODIS) data of 2008. Training data were derived from high-resolution images displayed in Google Earth and created by linear mixture simulation. The estimation model was modified to fit the reference data, which were randomly collected from the global area. The estimation result was validated at 1106 random sample points. The root mean square error (RMSE) between estimated and observed tree cover was 13.8%. The produced map was also compared with existing global data sets. The RMSE of our result was better than that of two existing global percentage tree-cover data sets (about 1.8% and 9.2% lower than Vegetation Continuous Fields MOD44B data set and Global Map – Percent Tree Cover data set, respectively). In our result and all other data sets, the accuracy was lower for forests than for other areas. When the produced map was compared with the Vegetation Continuous Fields MOD44B data set, the low agreement between them was concentrated in closed forests of Colombia, India, and Indonesia, and closed to open forests of Central Africa.     

Visualization of Large Amount of Spectra in Virtual Observatory Environment

This paper presents overview of new features so far prepared for new version of spectral analysis tool SPLAT-VO that allows to retrieve a large amount of spectra(and other data) based on its characteristics by detailed querying a virtual observatory s resources. The overview is focused on enhancements of user experience, work with simple application messaging protocol(SAMP) and other interoperability that improves work with global list of spectra, plot window and analysis menu.     

Ubiquitous computing: connecting Pervasive computing through Semantic Web

Ubiquitous computing refers to building a global computing environment where seamless and invisible access to computing resources is provided to the user. Pervasive computing deals with acquiring context knowledge from the environment and providing dynamic, proactive and context-aware services to the user. A Ubiquitous computing environment is created by sharing knowledge and information between Pervasive computing environments. In this paper we propose a framework that uses the potential of the Semantic Web to weave Pervasive computing environments into a Ubiquitous computing environment. We discuss how the collaboration of these Pervasive environments can create an effective Ubiquitous computing environment referred herein as the Integrated Global Pervasive Computing Framework (IGPF). We test the effectiveness of the Ubiquitous environment through a small scenario from a prototype system that we have implemented over this framework to handle medical emergency scenario.     

A Comprehensive and Adaptive Trust Model for Large-Scale P2P Networks

Based on human psychological cognitive behavior, a Comprehensive and Adaptive Trust (CAT) model for large-scale P2P networks is proposed. Firstly, an adaptive trusted decision-making method based on HEW (Historical Evidences Window) is proposed, which can not only reduce the risk and improve system efficiency, but also solve the trust forecasting problem when the direct evidences are insufficient. Then, direct trust computing method based on IOWA (Induced Ordered Weighted Averaging) operator and feedback trust converging mechanism based on DTT (Direct Trust Tree) are set up, which makes the model have a better scalability than previous studies. At the same time, two new parameters, confidence factor and feedback factor, are introduced to assign the weights to direct trust and feedback trust adaptively, which overcomes the shortage of traditional method, in which the weights are assigned by subjective ways. Simulation results show that, compared to the existing approaches, the proposed model has remarkable enhancements in the accuracy of trust decision-making and has a better dynamic adaptation capability in handling various dynamic behaviors of peers.     

Global adaptive control of nonlinearly parametrized systems

In this paper, we consider global adaptive control of nonlinearly parametrized systems in parametric-strict-feedback form. Unlike previous results, we do not require a priori bounds on the unknown parameters, which is as in the linear parametrization case. We also allow unknown parameters to be time-varying provided they are bounded. Our proposed adaptive controller is a switching type controller, in which the controller parameter is tuned in a switching manner via a switching logic. Global stability results of the closed-loop system have been proved.     

In silico design: Extended molecular dynamic simulations of a new series of dually acting inhibitors against EGFR and HER2

Based on the hit structures that have been identified in our previous studies against EGFR and HER2, new potential inhibitors that share the same scaffold of the hit structures are designed and screened in silico. Insights into understanding the potential inhibitory effect of the new inhibitors against both EGFR and HER2 receptors is obtained using extended molecular dynamics (MD) simulations and different scoring techniques. The binding mechanisms and dynamics are detailed with respect to two approved inhibitors against EGFR (lapatinib) and HER2 (SYR127063). The best scoring inhibitor (T9) is chosen for additional in silico investigation against both the wild-type and T790M mutant strain of EGFR and the wild-type HER2. The results reveal that certain substitution patterns increase the stability and assure stronger binding and higher H-bond occupancy of the conserved water molecule that is commonly observed with kinase crystal structures. Furthermore, the new inhibitor (T9) forms stable interactions with the mutant strain as a direct consequence of the enhanced ability to form additional hydrogen bonding interactions with binding site residues.     

卫星全球普查任务调度系统的设计与实现

卫星全球普查任务是指利用星载遥感设备,周期性地对全球表面进行覆盖监测和数据采集。论文针对卫星全球普查任务需求的特点和卫星资源能力,建立了卫星全球普查任务调度系统。卫星全球普查任务调度系统主要包括想定管理模块、资源管理模块、场景管理模块、调度模块与仿真评估模块等功能模块,文中重点分析了系统核心的场景管理模块、调度模块与仿真评估模块的实现。     

Development of a global land cover characteristics database and IGBP DISCover from 1 km AVHRR data

Researchers from the U.S. Geological Survey, University of Nebraska-Lincoln and the European Commission's Joint Research Centre, Ispra, Italy produced a 1 km resolution global land cover characteristics database for use in a wide range of continental-to global-scale environmental studies. This database provides a unique view of the broad patterns of the biogeographical and ecoclimatic diversity of the global land surface, and presents a detailed interpretation of the extent of human development. The project was carried out as an International Geosphere-Biosphere Programme, Data and Information Systems (IGBP-DIS) initiative. The IGBP DISCover global land cover product is an integral component of the global land cover database. DISCover includes 17 general land cover classes defined to meet the needs of IGBP core science projects. A formal accuracy assessment of the DISCover data layer will be completed in 1998. The 1 km global land cover database was developed through a continent-by-continent unsupervised classification of 1 km monthly Advanced Very High Resolution Radiometer (AVHRR) Normalized Difference Vegetation Index (NDVI) composites covering 1992-1993. Extensive post-classification stratification was necessary to resolve spectral/temporal confusion between disparate land cover types. The complete global database consists of 961 seasonal land cover regions that capture patterns of land cover, seasonality and relative primary productivity. The seasonal land cover regions were aggregated to produce seven separate land cover data sets used for global environmental modelling and assessment. The data sets include IGBP DISCover, U.S. Geological Survey Anderson System, Simple Biosphere Model, Simple Biosphere Model 2, Biosphere-Atmosphere Transfer Scheme, Olson Ecosystems and Running Global Remote Sensing Land Cover. The database also includes all digital sources that were used in the classification. The complete database can be sourced from the website: http://edcwww.cr.usgs.gov/landdaac/glcc/glcc.html.