DADS: Decentralized (Mobile) Applications Deployment System Using Blockchain

This paper proposes a comprehensive framework using blockchain architecture to create a decentralized applications store, in order to reduce the approval time for apps that are to be deployed on deployment systems i.e. applications stores, and specially for mobile platforms e.g. Apple and Google play stores. This work potentially can solve some of the existing challenges with the current centralized application approval process by Apple and Google. These companies currently charge a flat commission rate of 30% [1] of the total applications revenues from the applications owners. This commission is considered to be very high, especially for applications with revenues in the order of few million dollars. In addition, the length of the review period prior to deployment for any new or revised apps delays the release to the marketplace hence costing economic losses to the app owners. Currently, Apple and Google stores takes around two days and two hours respectively to review and approve the apps on their stores. However, by using decentralized technologies such as the blockchain, the time to review and publish a new or a revised app can be significantly reduced from few days to few minutesIn this paper a novel framework is proposed based on the blockchain architecture incorporating the Ethereum network, Interplanetary Files System (IPFS), VueJS, and a backend database. The framework is experimentally validated, and the results show the reduction in terms of the number of minutes to approve apps by the app stores

Integration of Distributed Generations in Smart Distribution Networks Using Multi-Criteria Based Sustainable Planning Approach

Energy planning has become more complicated in the 21st century of sustainable development due to the inclusion of numerous standards such as techno-economic, and environmental considerations. This paper proposes multi-criteria sustainable planning (MCSP) based optimization approach for identifying DGs’ optimal allocations and rating powers. The main objectives of this paper are the reduction of the network’s total power loss, voltage profile improvement, energy loss saving maximization, and curtailing environmental emissions and water consumption to achieve Sustainable Development Goals (SDGs 3, 6, 7, 13, and 15) by taking the constraints into consideration. Different alternatives are evaluated across four aspects of performance indices; technical, cost-economic, environmental, and social (TEES). In terms of TEES performance evaluations, various multi-criteria decision-making (MCDM) approaches are used to determine the optimal trade-off among the available solutions. These methods are gaining wide acceptance due to their flexibility while considering all criteria and objectives concurrently. Annual energy loss saving is increased by 97.13%, voltage profile is improved to 0.9943 (p.u), and emissions are reduced by 82.45% using the proposed technique. The numerical results of the proposed MCSP approach are compared to previously published works to validate and may be used by researchers and energy planners as a planning tool for ADN schemes

Using models of the ocean's mean dynamic topography to identify errors in coastal geodetic levelling

Identifying errors (blunders and systematic errors) in coastal geodetic levelling networks has often been problematic. This is because (1) mean sea level (MSL) at tide gauges cannot be directly compared to height differences from levelling because the geoid/quasigeoid and MSL are not parallel, being separated by the ocean’s mean dynamic topography (MDT) and (2) the lack of redundancy at the edge of the levelling network. This paper sets out a methodology to independently identify blunders and/or systematic errors (over long distances) in geodetic levelling using MDT models to account for the separation between the geoid/quasigeoid and MSL at tide gauges. This method is then tested in a case study using an oceanographic MDT model, MSL observations, GNSS data and a quasigeoid model. The results are significant because the errors found could not be detected by standard levelling misclosure checks alone, with supplementary data from an MDT model, with cross-validation from GNSS-quasigeoid allowing their detection. In addition, it appears that an oceanographic-only MDT is as effective as GNSS and a quasigeoid model for detecting levelling errors, which could be particularly useful for countries with coastal levelling errors in their levelling networks that cannot be identified by conventional levelling closure checks

Towards Constraining Glacial Isostatic Adjustment in Greenland Using ICESat and GPS Observations

Constraining glacial isostatic adjustment (GIA) i.e. the Earth’s viscoelastic response to past ice changes, is an important task, because GIA is a significant correction in gravity-based ice sheet mass balance estimates. Here, we investigate how temporal variations in the observed and modeled crustal displacements due to the Earth’s response to ongoing ice mass changes can contribute to the process of constraining GIA. We use mass change grids of the Greenland ice sheet (GrIS) derived from NASA’s high resolution Ice, Cloud and land Elevation Satellite (ICESat) data in three overlapping time spans covering the period 2004–2009 to estimate temporal variations in the elastic response due to present day ice mass loss. The modeled crustal displacements (elastic + GIA) are compared with GPS time series from five permanent sites (KELY, KULU, QAQ1, THU2, and SCOR). We find, that the modeled pattern of elastic crustal displacements shows pronounced variation during the observation period, where an increase in elastic displacement is found at the northwest coast of Greenland, while a decrease is found at the southeast coast. This pattern of temporal changes is supported by the GPS observations. We find, that the temporal behavior of the ICESat-based modeled elastic response agrees well with the GPS observations at the sites KELY, QAQ1, and SCOR. This suggests, that our elastic models are able to resolve the temporal changes in the observed uplift, which indicates that the elastic uplift models are reliable at these sites. Therefore, we conclude that these sites are useful for constraining GIA

Variance component estimation uncertainty for unbalanced data: Application to a continent-wide vertical datum

Variance component estimation (VCE) is used to update the stochastic model in least-squares adjustments, but the uncertainty associated with the VCE-derived weights is rarely considered. Unbalanced data is where there is an unequal number of observations in each heterogeneous dataset comprising the variance component groups. As a case study using highly unbalanced data, we redefine a continent-wide vertical datum from a combined least-squares adjustment using iterative VCE and its uncertainties to update weights for each data set. These are: (1) a continent-wide levelling network, (2) a model of the ocean’s mean dynamic topography and mean sea level observations, and (3) GPS-derived ellipsoidal heights minus a gravimetric quasigeoid model. VCE uncertainty differs for each observation group in the highly unbalanced data, being dependent on the number of observations in each group. It also changes within each group after each VCE iteration, depending on the magnitude of change for each observation group’s variances. It is recommended that VCE uncertainty is computed for VCE updates to the weight matrix for unbalanced data so that the quality of the updates for each group can be properly assessed. This is particularly important if some groups contain relatively small numbers of observations. VCE uncertainty can also be used as a threshold for ceasing iterations, as it is shown—for this data set at least—that it is not necessary to continue time-consuming iterations to fully converge to unity