MACRO-MICRO FEEDBACK LINKS OF IRRIGATION WATER MANAGEMENT IN TURKEY

Agricultural production is heavily dependent on water availability in Turkey, where half the crop production relies on irrigation. Irrigated agriculture consumes about 75 percent of total water used, which is about 30 percent of renewable water availability. This study analyzes the likely effects of increased competition for water resources and changes in the Turkish economy. The analysis uses an economy-wide Walrasian Computable General Equilibrium model with a detailed account of the agricultural sector. The study investigated the economy-wide effects of two external shocks, namely a permanent increase in the world prices of agricultural commodities and climate change, along with the impact of the domestic reallocation of water between agricultural and non-agricultural uses. It was also recognized that because of spatial heterogeneity of the climate, the simulated scenarios have differential impact on the agricultural production and hence on the allocation of factors of production including water. The greatest effects on major macroeconomic indicators occur in the climate change simulations. As a result of the transfer of water from rural to urban areas, overall production of all crops declines. Although production on rainfed land increases, production on irrigated land declines, most notably the production of maize and fruits. The decrease in agricultural production, coupled with the domestic price increase, is further reflected in net trade. Agricultural imports increase with a greater decline in agricultural exports.Computable General Equilibrium; Feedback links; Irrigation Water; Turkey

OWL-POLAR : semantic policies for agent reasoning

The original publication is available at www.springerlink.comPostprin

OntoMathPROOntoMath^{PRO} Ontology: A Linked Data Hub for Mathematics

In this paper, we present an ontology of mathematical knowledge concepts that covers a wide range of the fields of mathematics and introduces a balanced representation between comprehensive and sensible models. We demonstrate the applications of this representation in information extraction, semantic search, and education. We argue that the ontology can be a core of future integration of math-aware data sets in the Web of Data and, therefore, provide mappings onto relevant datasets, such as DBpedia and ScienceWISE.Comment: 15 pages, 6 images, 1 table, Knowledge Engineering and the Semantic Web - 5th International Conferenc

Patterns of older and younger prisoners' primary healthcare utilization in Switzerland

Purpose The purpose of this paper is to identify primary health concerns prompting older and younger prisoners in Switzerland to consult a nurse or a general practitioner (GP) within the prison healthcare setting, and explores if these reasons for visits differ by age group (49 years and younger vs 50 years and older). The authors used 50 years and older as the benchmark for older prisoners in light of literature indicating accelerated aging among prisoners. Design/methodology/approach Retrospective information from medical records of 406 prisoners were collected for a period of six months. This study analyzed the reasons for which prisoners visited the nurses and GPs available to them through the prison healthcare service. These reasons were coded using the International Classification of Primary Care-version 2. Data were analyzed descriptively and four generalized linear models were built to examine whether there was an age group difference in reasons for visiting nurses and GPs. Findings The health reasons for visiting nurses and GPs by 380 male prisoners from 13 Swiss prisons are presented. In the six month period, a total of 3,309 reasons for visiting nurses and 1,648 reasons for visiting GPs were recorded. Prisoner participants' most common reasons for both visits were for general and unspecified complaints and musculoskeletal problems. Older prisoners sought significantly more consultations for cardiovascular and endocrine problems than younger prisoners. Research limitations/implications Nurses play an important role in addressing healthcare demands of prisoners and coordinating care in Swiss prisons. In light of age-related healthcare demands, continuing education and training of both nurses and GPs to adequately and efficiently address the needs of this prisoner group is critical. Allowing prisoners to carry out some care activities for minor self-manageable complaints will reduce the demand for healthcare. Originality/value This study presents unique data on healthcare concerns for which prisoners visit prison nurses and GPs. It highlights the varied needs of older prisoners as well as how these needs are addressed based on the availability of the primary healthcare provider within the prison

Flexible provisioning of Web service workflows

Web services promise to revolutionise the way computational resources and business processes are offered and invoked in open, distributed systems, such as the Internet. These services are described using machine-readable meta-data, which enables consumer applications to automatically discover and provision suitable services for their workflows at run-time. However, current approaches have typically assumed service descriptions are accurate and deterministic, and so have neglected to account for the fact that services in these open systems are inherently unreliable and uncertain. Specifically, network failures, software bugs and competition for services may regularly lead to execution delays or even service failures. To address this problem, the process of provisioning services needs to be performed in a more flexible manner than has so far been considered, in order to proactively deal with failures and to recover workflows that have partially failed. To this end, we devise and present a heuristic strategy that varies the provisioning of services according to their predicted performance. Using simulation, we then benchmark our algorithm and show that it leads to a 700% improvement in average utility, while successfully completing up to eight times as many workflows as approaches that do not consider service failures

How Can Reasoner Performance of ABox Intensive Ontologies Be Predicted?

Reasoner performance prediction of ontologies in OWL 2 language has been studied so far from different dimensions. One key aspect of these studies has been the prediction of how much time a particular task for a given ontology will consume. Several approaches have adopted different machine learning techniques to predict time consumption of ontologies already. However, these studies focused on capturing general aspects of the ontologies (i.e., mainly the complexity of their TBoxes), while paying little attention to ABox intensive ontologies. To address this issue, in this paper, we propose to improve the representativeness of ontology metrics by developing new metrics which focus on the ABox features of ontologies. Our experiments show that the proposed metrics contribute to overall prediction accuracy for all ontologies in general without causing side-effects

Analytic Metaphysics versus Naturalized Metaphysics: The Relevance of Applied Ontology

The relevance of analytic metaphysics has come under criticism: Ladyman & Ross, for instance, have suggested do discontinue the field. French & McKenzie have argued in defense of analytic metaphysics that it develops tools that could turn out to be useful for philosophy of physics. In this article, we show first that this heuristic defense of metaphysics can be extended to the scientific field of applied ontology, which uses constructs from analytic metaphysics. Second, we elaborate on a parallel by French & McKenzie between mathematics and metaphysics to show that the whole field of analytic metaphysics, being useful not only for philosophy but also for science, should continue to exist as a largely autonomous field

SADI, SHARE, and the in silico scientific method

<p>Abstract</p> <p>Background</p> <p>The emergence and uptake of Semantic Web technologies by the Life Sciences provides exciting opportunities for exploring novel ways to conduct <it>in silico</it> science. Web Service Workflows are already becoming first-class objects in “the new way”, and serve as explicit, shareable, referenceable representations of how an experiment was done. In turn, Semantic Web Service projects aim to facilitate workflow construction by biological domain-experts such that workflows can be edited, re-purposed, and re-published by non-informaticians. However the aspects of the scientific method relating to explicit discourse, disagreement, and hypothesis generation have remained relatively impervious to new technologies.</p> <p>Results</p> <p>Here we present SADI and SHARE - a novel Semantic Web Service framework, and a reference implementation of its client libraries. Together, SADI and SHARE allow the semi- or fully-automatic discovery and pipelining of Semantic Web Services in response to <it>ad hoc</it> user queries.</p> <p>Conclusions</p> <p>The semantic behaviours exhibited by SADI and SHARE extend the functionalities provided by Description Logic Reasoners such that novel assertions can be automatically added to a data-set without logical reasoning, but rather by analytical or annotative services. This behaviour might be applied to achieve the “semantification” of those aspects of the <it>in silico</it> scientific method that are not yet supported by Semantic Web technologies. We support this suggestion using an example in the clinical research space.</p

Ambient-aware continuous care through semantic context dissemination

Background: The ultimate ambient-intelligent care room contains numerous sensors and devices to monitor the patient, sense and adjust the environment and support the staff. This sensor-based approach results in a large amount of data, which can be processed by current and future applications, e. g., task management and alerting systems. Today, nurses are responsible for coordinating all these applications and supplied information, which reduces the added value and slows down the adoption rate. The aim of the presented research is the design of a pervasive and scalable framework that is able to optimize continuous care processes by intelligently reasoning on the large amount of heterogeneous care data. Methods: The developed Ontology-based Care Platform (OCarePlatform) consists of modular components that perform a specific reasoning task. Consequently, they can easily be replicated and distributed. Complex reasoning is achieved by combining the results of different components. To ensure that the components only receive information, which is of interest to them at that time, they are able to dynamically generate and register filter rules with a Semantic Communication Bus (SCB). This SCB semantically filters all the heterogeneous care data according to the registered rules by using a continuous care ontology. The SCB can be distributed and a cache can be employed to ensure scalability. Results: A prototype implementation is presented consisting of a new-generation nurse call system supported by a localization and a home automation component. The amount of data that is filtered and the performance of the SCB are evaluated by testing the prototype in a living lab. The delay introduced by processing the filter rules is negligible when 10 or fewer rules are registered. Conclusions: The OCarePlatform allows disseminating relevant care data for the different applications and additionally supports composing complex applications from a set of smaller independent components. This way, the platform significantly reduces the amount of information that needs to be processed by the nurses. The delay resulting from processing the filter rules is linear in the amount of rules. Distributed deployment of the SCB and using a cache allows further improvement of these performance results