Modelling the system behaviour of wet snow avalanches using an expert system approach for risk management on high alpine traffic roads

The presented approach describes a model for a rule-based expert system calculating the temporal variability of the release of wet snow avalanches, using the assumption of avalanche triggering without the loading of new snow. The knowledge base of the model is created by using investigations on the system behaviour of wet snow avalanches in the Italian Ortles Alps, and is represented by a fuzzy logic rule-base. Input parameters of the expert system are numerical and linguistic variables, measurable meteorological and topographical factors and observable characteristics of the snow cover. Output of the inference method is the quantified release disposition for wet snow avalanches. Combining topographical parameters and the spatial interpolation of the calculated release disposition a hazard index map is dynamically generated. Furthermore, the spatial and temporal variability of damage potential on roads exposed to wet snow avalanches can be quantified, expressed by the number of persons at risk. The application of the rule base to the available data in the study area generated plausible results. The study demonstrates the potential for the application of expert systems and fuzzy logic in the field of natural hazard monitoring and risk management.

Sleep and wakefulness disturbances in Swiss pharmacy customers

BACKGROUND AND OBJECTIVE: Sleep disturbances are prevalent but often overlooked or underestimated. We suspected that sleep disorders might be particularly common among pharmacy customers, and that they could benefit from counselling. Therefore, we described the prevalence and severity of symptoms associated with sleep and wakefulness disorders among Swiss pharmacy customers, and estimated the need for counselling and treatment. METHODS: In 804 Swiss pharmacies (49% of all community pharmacies) clients were invited to complete the Stanford Sleep Disorders Questionnaire (SDQ), and the Epworth Sleepiness Scale (EPW). The SDQ was designed to classify symptoms of sleep and wakefulness into the four most prevalent disorders: sleep apnoea syndrome (SAS), insomnia in psychiatric disorders (PSY), periodic leg movement disorders/restless legs (RLS) and narcolepsy (NAR). Data were entered into an internet-linked database for analysis by an expert system as a basis for immediate counselling by the pharmacist. RESULTS: Of 4901 participants, 3238 (66.1%) were female, and 1663 (33.9%) were male. The mean age (SD) of females and males was 52.4 (18.05), and 55.1 (17.10) years, respectively. The percentages of female and male individuals above cut-off of SDQ subscales were 11.4% and 19.8% for sleep apnoea, 40.9% and 38.7% for psychiatric sleep disorders, 59.3% and 46.8% for restless legs, and 10.4% and 9.4% for narcolepsy respectively. The prevalence of an Epworth Sleepiness Scale score >11 was 16.5% in females, and 23.9% in males. Reliability assessed by Cronbach's alpha was 0.65 to 0.78 for SDQ subscales, and for the Epworth score. CONCLUSIONS: Symptoms of sleep and wakefulness disorders among Swiss pharmacy customers were highly prevalent. The SDQ and the Epworth Sleepiness Scale score had a satisfactory reliability to be useful for identification of pharmacy customers who might benefit from information and counselling while visiting pharmacies. The internet-based system proved to be a helpful tool for the pharmacist when counselling his customers in terms of diagnostic classification and severity of symptoms associated with the sleeping and waking state.

International horse movements and spread of equine diseases: Equine Infectious Anaemia and Glanders - two examples

International trade with horses is important and continuously increasing. Therefore the risk of spread of infectious diseases is permanently present. Within this context the worldwide situation of equine vector-borne diseases and of other diseases which are notifiable to the World Organisation of Animal Health (OIE), is described. Furthermore it provides estimates of the numbers of horse movements between these countries, as well as information on import requirements and preventive measures for reducing the risk of disease spread. According to TRACES (Trade Control and Expert System of the European Union) data from 2009 and 2010 81 horses per week were imported from North America into Europe, 42 horses per week from South America, 11 horses per week from the North of Africa and the African horse sichness free-zone of South Africa, 28 per week from the Middle East and the rest of Asia and approximately 4 horses per week from Australia / Oceania. Trade within the European Union resulted amongst others in the introduction of Equine Infectious Anaemia (EIA) from Roma- nia into other European countries. Another example is the suspected case of glanders which occurred after importation of horses from Leb- anon via France and Germany into Switzerland in July 2011.

A Conceptual Model to Combine Creativity Techniques with Fuzzy Cognitive Maps for Enhanced Knowledge Management

This chapter introduces a conceptual model to combine creativity techniques with fuzzy cognitive maps (FCMs) and aims to support knowledge management methods by improving expert knowledge acquisition and aggregation. The aim of the conceptual model is to represent acquired knowledge in a manner that is as computer-understandable as possible with the intention of developing automated reasoning in the future as part of intelligent information systems. The formal represented knowledge thus may provide businesses with intelligent information integration. To this end, we introduce and evaluate various creativity techniques with a list of attributes to define the most suitable to combine with FCMs. This proposed combination enables enhanced knowledge management through the acquisition and representation of expert knowledge with FCMs. Our evaluation indicates that the creativity technique known as mind mapping is the most suitable technique in our set. Finally, a scenario from stakeholder management demonstrates the combination of mind mapping with FCMs as an integrated system.

An insulin infusion advisory system based on autotuning nonlinear model-predictive control

This paper aims at the development and evaluation of a personalized insulin infusion advisory system (IIAS), able to provide real-time estimations of the appropriate insulin infusion rate for type 1 diabetes mellitus (T1DM) patients using continuous glucose monitors and insulin pumps. The system is based on a nonlinear model-predictive controller (NMPC) that uses a personalized glucose-insulin metabolism model, consisting of two compartmental models and a recurrent neural network. The model takes as input patient's information regarding meal intake, glucose measurements, and insulin infusion rates, and provides glucose predictions. The predictions are fed to the NMPC, in order for the latter to estimate the optimum insulin infusion rates. An algorithm based on fuzzy logic has been developed for the on-line adaptation of the NMPC control parameters. The IIAS has been in silico evaluated using an appropriate simulation environment (UVa T1DM simulator). The IIAS was able to handle various meal profiles, fasting conditions, interpatient variability, intraday variation in physiological parameters, and errors in meal amount estimations.

The FORA Framework - A Fuzzy Grassroots Ontology for Online Reputation Management

Online reputation management deals with monitoring and influencing the online record of a person, an organization or a product. The Social Web offers increasingly simple ways to publish and disseminate personal or opinionated information, which can rapidly have a disastrous influence on the online reputation of some of the entities. This dissertation can be split into three parts: In the first part, possible fuzzy clustering applications for the Social Semantic Web are investigated. The second part explores promising Social Semantic Web elements for organizational applications,while in the third part the former two parts are brought together and a fuzzy online reputation analysis framework is introduced and evaluated. Theentire PhD thesis is based on literature reviews as well as on argumentative-deductive analyses.The possible applications of Social Semantic Web elements within organizations have been researched using a scenario and an additional case study together with two ancillary case studies—based on qualitative interviews. For the conception and implementation of the online reputation analysis application, a conceptual framework was developed. Employing test installations and prototyping, the essential parts of the framework have been implemented.By following a design sciences research approach, this PhD has created two artifacts: a frameworkand a prototype as proof of concept. Bothartifactshinge on twocoreelements: a (cluster analysis-based) translation of tags used in the Social Web to a computer-understandable fuzzy grassroots ontology for the Semantic Web, and a (Topic Maps-based) knowledge representation system, which facilitates a natural interaction with the fuzzy grassroots ontology. This is beneficial to the identification of unknown but essential Web data that could not be realized through conventional online reputation analysis. Theinherent structure of natural language supports humans not only in communication but also in the perception of the world. Fuzziness is a promising tool for transforming those human perceptions intocomputer artifacts. Through fuzzy grassroots ontologies, the Social Semantic Web becomes more naturally and thus can streamline online reputation management.

Prometheus – Fuzzy Information Retrieval for Semantic Homes and Environments

This paper introduces a novel vision for further enhanced Internet of Things services. Based on a variety of data – such as location data, ontology-backed search queries, in- and outdoor conditions – the Prometheus framework is intended to support users with helpful recommendations and information preceding a search for context-aware data. Adapted from artificial intelligence concepts, Prometheus proposes user-readjusted answers on umpteen conditions. A number of potential Prometheus framework applications are illustrated. Added value and possible future studies are discussed in the conclusion.

Verbalization of Dependencies Between Concepts Built Through Fuzzy Cognitive Maps

The new computing paradigm known as cognitive computing attempts to imitate the human capabilities of learning, problem solving, and considering things in context. To do so, an application (a cognitive system) must learn from its environment (e.g., by interacting with various interfaces). These interfaces can run the gamut from sensors to humans to databases. Accessing data through such interfaces allows the system to conduct cognitive tasks that can support humans in decision-making or problem-solving processes. Cognitive systems can be integrated into various domains (e.g., medicine or insurance). For example, a cognitive system in cities can collect data, can learn from various data sources and can then attempt to connect these sources to provide real time optimizations of subsystems within the city (e.g., the transportation system). In this study, we provide a methodology for integrating a cognitive system that allows data to be verbalized, making the causalities and hypotheses generated from the cognitive system more understandable to humans. We abstract a city subsystem—passenger flow for a taxi company—by applying fuzzy cognitive maps (FCMs). FCMs can be used as a mathematical tool for modeling complex systems built by directed graphs with concepts (e.g., policies, events, and/or domains) as nodes and causalities as edges. As a verbalization technique we introduce the restriction-centered theory of reasoning (RCT). RCT addresses the imprecision inherent in language by introducing restrictions. Using this underlying combinatorial design, our approach can handle large data sets from complex systems and make the output understandable to humans.

Synchronizing Mind Maps with Fuzzy Cognitive Maps for Decision-Finding in Cognitive Cities

Synchronizing mind maps with fuzzy cognitive maps can help to handle complex problems with many involved stakeholders by taking advantage of human creativity. The proposed approach has the capacity to instantiate cognitive cities by including cognitive computing. A use case in the context of decision-finding (concerning a transportation system) is presented to illustrate the approach.