Automatic Adaptation of SOA Systems Supported by Machine Learning

Part 3: Service OrientationInternational audienceRecent advances in the development of information systems have led to increased complexity and cost in terms of the required maintenance and management. On the other hand, systems built in accordance with modern architectural paradigms, such as Service Oriented Architecture (SOA), posses features enabling extensive adaptation, not present in traditional systems. Automatic adaptation mechanisms can be used to facilitate system management. The goal of this work is to show that automatic adaptation can be effectively implemented in SOA systems using machine learning algorithms. The presented concept relies on a combination of clustering and reinforcement learning algorithms. The paper discusses assumptions which are necessary to apply machine learning algorithms to automatic adaptation of SOA systems, and presents a machine learning-based management framework prototype. Possible benefits and disadvantages of the presented approach are discussed and the approach itself is validated with a representative case study

Assessing the suitability of GlobeLand30 for mapping land cover in Germany

Global land cover (LC) maps have been widely employed as the base layer for a number of applications including climate change, food security, water quality, biodiversity, change detection, and environmental planning. Due to the importance of LC, there is a pressing need to increase the temporal and spatial resolution of global LC maps. A recent advance in this direction has been the GlobeLand30 dataset derived from Landsat imagery, which has been developed by the National Geomatics Center of China (NGCC). Although overall accuracy is greater than 80%, the NGCC would like help in assessing the accuracy of the product in different regions of the world. To assist in this process, this study compares the GlobeLand30 product with existing public and online datasets, that is, CORINE, Urban Atlas (UA), OpenStreetMap, and ATKIS for Germany in order to assess overall and per class agreement. The results of the analysis reveal high agreement of up to 92% between these datasets and GlobeLand30 but that large disagreements for certain classes are evident, in particular wetlands. However, overall, GlobeLand30 is shown to be a useful product for characterizing LC in Germany, and paves the way for further regional and national validation efforts

Co-Design of Business and IT Services – a Tool-Supported Approach

Service modeling is an important step in designing service-oriented systems. There are multiple levels of design because service sci-ence includes both the business rationale and the IT implementation ofthe services. As business and IT perspectives differ, the modeling tech-niques are different, and often the respective modeling languages aredisconnected or ad-hoc. We propose a new service-modeling approachfor connecting the business modeling and the web service modeling bypresenting these two perspectives in a single model. We present a multi-stage modeling process for capturing different perspectives and creatingmodels iteratively by working with levels of abstraction from higher tolower. The model is then used as an input in order to generate a RESTAPI specification in the OpenAPI format to feed the next stages of theservice life-cycle

The global governance of human cloning: the case of UNESCO

Since Dolly the Sheep was cloned in 1996, the question of whether human reproductive cloning should be banned or pursued has been the subject of international debate. Feelings run strong on both sides. In 2005, the United Nations adopted its Declaration on Human Cloning to try to deal with the issue. The declaration is ambiguously worded, prohibiting “all forms of human cloning inasmuch as they are incompatible with human dignity and the protection of human life”. It received only ambivalent support from UN member states. Given this unsatisfactory outcome, in 2008 UNESCO (the United Nations Educational, Scientific and Cultural Organization) set up a Working Group to investigate the possibility of a legally binding convention to ban human reproductive cloning. The Working Group was made up of members of the International Bioethics Committee, established in 1993 as part of UNESCO’s Bioethics Programme. It found that the lack of clarity in international law is unhelpful for those states yet to formulate national regulations or policies on human cloning. Despite this, member states of UNESCO resisted the idea of a convention for several years. This changed in 2015, but there has been no practical progress on the issue. Drawing on official records and first-hand observations at bioethics meetings, this article examines the human cloning debate at UNESCO from 2008 onwards, thus building on and advancing current scholarship by applying recent ideas on global governance to an empirical case. It concludes that, although human reproductive cloning is a challenging subject, establishing a robust global governance framework in this area may be possible via an alternative deliberative format, based on knowledge sharing and feasibility testing rather than the interest-based bargaining that is common to intergovernmental organizations and involving a wide range of stakeholders. This article is published as part of a collection on global governance

Impact analysis of accidents on the traffic flow based on massive floating car data

The wide usage of GPS-equipped devices enables the mass recording of vehicle movement trajectories describing the movement behavior of the traffic participants. An important aspect of the road traffic is the impact of anomalies, like accidents, on traffic flow. Accidents are especially important as they contribute to the the aspects of safety and also influence travel time estimations. In this paper, the impact of accidents is determined based on a massive GPS trajectory and accident dataset. Due to the missing precise date of the accidents in the data set used, first, the date of the accident is estimated based on the speed profile at the accident time. Further, the temporal impact of the accident is estimated using the speed profile of the whole day. The approach is applied in an experiment on a one month subset of the datasets. The results show that more than 72% of the accident dates are identified and the impact on the temporal dimension is approximated. Moreover, it can be seen that accidents during the rush hours and on high frequency road types (e.g. motorways, trunks or primaries) have an increasing effect on the impact duration on the traffic flow

The Financial Burden of Non-Communicable Chronic Diseases in Rural Nigeria: Wealth and Gender Heterogeneity in Health Care Utilization and Health Expenditures

Objectives Better insights into health care utilization and out-of-pocket expenditures for non-communicable chronic diseases (NCCD) are needed to develop accessible health care and limit the increasing financial burden of NCCDs in Sub-Saharan Africa. Methods A household survey was conducted in rural Kwara State, Nigeria, among 5,761 individuals. Data were obtained using biomedical and socio-economic questionnaires. Health care utilization, NCCD-related health expenditures and distances to health care providers were compared by sex and by wealth quintile, and a Heckman regression model was used to estimate health expenditures taking selection bias in health care utilization into account. Results The prevalence of NCCDs in our sample was 6.2%. NCCD-affected individuals from the wealthiest quintile utilized formal health care nearly twice as often as those from the lowest quintile (87.8% vs 46.2%, p = 0.002). Women reported foregone formal care more often than men (43.5% vs. 27.0%, p = 0.058). Health expenditures relative to annual consumption of the poorest quintile exceeded those of the highest quintile 2.2-fold, and the poorest quintile exhibited a higher rate of catastrophic health spending (10.8% among NCCD-affected households) than the three upper quintiles (4.2% to 6.7%). Long travel distances to the nearest provider, highest for the poorest quintile, were a significant deterrent to seeking care. Using distance to the nearest facility as instrument to account for selection into health care utilization, we estimated out-of-pocket health care expenditures for NCCDs to be significantly higher in the lowest wealth quintile compared to the three upper quintiles. Conclusions Facing potentially high health care costs and poor accessibility of health care facilities, many individuals suffering from NCCDs—particularly women and the poor—forego formal care, thereby increasing the risk of more severe illness in the future. When seeking care, the poor spend less on treatment than the rich, suggestive of lower quality care, while their expenditures represent a higher share of their annual household consumption. This calls for targeted interventions that enhance health care accessibility and provide financial protection from the consequences of NCCDs, especially for vulnerable populations

Quality assessment of OpenStreetMap data using trajectory mining

OpenStreetMap (OSM) data are widely used but their reliability is still variable. Many contributors to OSM have not been trained in geography or surveying and consequently their contributions, including geometry and attribute data inserts, deletions, and updates, can be inaccurate, incomplete, inconsistent, or vague. There are some mechanisms and applications dedicated to discovering bugs and errors in OSM data. Such systems can remove errors through user-checks and applying predefined rules but they need an extra control process to check the real-world validity of suspected errors and bugs. This paper focuses on finding bugs and errors based on patterns and rules extracted from the tracking data of users. The underlying idea is that certain characteristics of user trajectories are directly linked to the type of feature. Using such rules, some sets of potential bugs and errors can be identified and stored for further investigation