Radioactivity of the Pre-Cambrian section of the Bourbon, Missouri, well core by measurement of the total hard gamma radiation

In December of 1947 Mr. Robert Van Nostrand and the writer became interested in the problem of the distribution of natural radioactivity and the applications of radioactivity to geology. A cooperative survey of the literature on the subject was undertaken. Later the writer decided to follow up the survey with a research project. Consultations with Dr. Z. V. Harvalik of the Missouri School of Mines Physics Department, and Dr. E. L. Clark and Mr. O. M. Bishop of the Missouri Geological Survey, followed. The nature of the project was evolved when Dr. Clark, with the consent of the U. S. Bureau of Mines, offered to loan the writer the igneous section of the Bourbon, Missouri, well core. The equipment was designed and built, samples prepared and measurements taken during the summer months, June through September, 1948 --Preface, page iii

Nietzsche, Unconscious Processes, and Non-Linear Individuation

This thesis attempts to create an ontology of the self using Nietzsche’s concept of will-to-power forces, which operate in the individual unconsciously, leading to non-linear individuation resulting from responding or participating in chance events. Individuation results non-linearly because of Nietzsche’s claim that the “Deed has no doer” and that subjects and thoughts rely on fictitiously created causal chains, but that in actuality there are nothing but chance events and competing forces of nature which shape the individual into non-linear directions. The individual can only respond as creatively as possible to moments which arise, once loss of ultimate control is embraced. The main original points in this thesis are the interpretations that Nietzsche’s will-to-power acts as unconscious processes in individuals, and that non-linear individuation results from the directions which are taken during the participation and mastery of chance events

A Community-Consensus Approach to Knowledge Interoperability Within Heterogeneous Earth System Science Based Observational Systems

Within complex domains - such as Earth System Science - knowledge is constantly evolving. Observational systems used to observe Earth’s complex processes are often built in isolation, and data representations are not adequately designed for secondary use and higher order knowledge generation. Cross-community sharing of computable information is therefore difficult to achieve. Barriers to interoperability of information means that specialists cannot fully exploit the data that may be available. Much of the work done to date within the Information Science community has been to enable interoperability through standardisation, particularly at the syntactic level. The Open Geospatial Consortium’s (OGC) Observations & Measurements (O&M) standard [1] is a good example of the ongoing work towards enabling interoperability among observational systems. However, standards have a codifying and constraining effect on information. Object-oriented approaches commonly employed assume a static understanding of entities or classes of information. Therefore, these design methodologies cannot represent the true nature of knowledge within an evolving domain. Standards such as O&M avoid over constraining information objects by allowing variability. Where variability exists, interoperability is often compromised for individual use-cases. The Health domain also faces similar challenges to representing complex and evolving domain concepts. Within complex domains two categories or levels of domain concepts exist. Those concepts that remain stable over a long period of time, and those concepts that are prone to change, as the domain knowledge evolves. Health informaticians have developed a sophisticated two-level systems design approach for electronic health documentation over many years, and with the use of archetypes, have shown how knowledge interoperability among heterogeneous systems can be achieved [2]. The authors are currently engaged in translating two-level modelling approaches to geo-observational based systems [3][4]. A key differentiator of two-level modelling compared to other approaches is that it allows domain experts to be the primary drivers of digital artefacts, while also ensuring that technical validity is maintained in one highly accessible and integrated process; leading to a managed and interoperable extensibility mechanism to standards such as O&M. This presentation will highlight this ongoing work and demonstrate the tools under development to allow domain practitioners to define and manage a set of Earth System Science community defined archetypes to enable interoperability, beyond the syntactic level of observational systems. [1] S. Cox, Observations and measurements, Open Geospatial Consortium Best Practices Document. Open Geospatial Consortium, 2006. [2] T. Beale, Archetypes: Constraint-based domain models for future-proof information systems, in OOPSLA 2002 Workshop on Behavioral Semantics, 2002. [3] P. Stacey, D. Berry, “Applying two-level modelling to remote sensor systems design to enable future knowledge generation,” in IEEE YP Conference in Remote Sensing Abstracts, Barcelona, 2015. [4] P. Stacey, D. Berry, “Design and Implementation of an Archetype Based Interoperable Knowledge EcoSystem for Data Buoys” [in press] to appear in proceedings of IEEE/MTS Oceans conference, Aberdeen, June 2017

Extending Two-level Information Modeling to the Internet of Things

Interoperability is a major challenge for the Internet of Things (IoT). The real potential of the IoT lies in facilitating largescale sharing of high-quality context-rich information through systems-of-IoT-systems, rather than IoT systems that operate as isolated technology silos. Real large-scale interoperability requires layers of standards, and each layer addresses different interoperability challenges. The SensorThings API data model seeks to tackle data interoperability at the data and informational layers of IoT platforms. SensorThings API is aligned to the ISO/OGC O&M data standard, and like O&M it is semistructured. Semi-structured models allow for variance within implementations for different use-cases, which is both necessary and detrimental to systems interoperability. In this paper we propose that the SensorThings API data model should be defined as a set of archetypes, used to capture extensible domain concepts using a two-level modeling IoT systems design approach. Extending two-level modeling to the IoT using the SensorThings API as a base for domain concepts definition allows for a powerful framework to manage variance within systems implementation and maintaining semantic interoperability within systems-of-IoT-systems across diverse use-cases

Towards a Digital Earth: Using Archetypes to Enable Knowledge Interoperability within Geo-Observational Sensor Systems Design

Earth System Science (ESS) observational data are often inadequately semantically enriched by geo-observational information systems in order to capture the true meaning of the associated data sets. Data models underpinning these information systems are often too rigid in their data representation to allow for the ever-changing and evolving nature of ESS domain concepts. This impoverished approach to observational data representation reduces the ability of multi-disciplinary practitioners to share information in a computable way. Object oriented techniques typically employed to model data in a complex domain (with evolving domain concepts) can unnecessarily exclude domain specialists from the design process, invariably leading to a mismatch between the needs of the domain specialists, and how the concepts are modelled. In many cases, an over simplification of the domain concept is captured by the computer scientist. This paper proposes that two-level modelling methodologies developed by Health Informaticians to tackle similar problems of specific domain use-case knowledge modelling can be re-used within ESS Informatics. A proposed methodology to re-use two-level modelling within geo-observational sensor systems is described. We show how the Open Geospatial Consortium’s (OGC) Observations & Measurements (O&M) standard can act as a pragmatic solution for a stable reference-model (necessary for two-level modelling), and upon which more volatile domain specific concepts can be defined and managed using archetypes. A use-case is presented, followed by a worked example showing the implementation methodology and considerations leading to an O&M based, two-level modelling design approach, to realise semantically rich and interoperable Earth System Science based geo-observational sensor systems

Fun-Defense: Games that Teach Fundamental Martial-Arts and Build Self-Esteem.

Associations have been made among having a low self-esteem and both being a bully and being bullied. With bullying and its victimization being a common problem in today’s schools, increasing students’ self-esteem could benefit schools with this dilemma. Learning martial arts has been shown to increase students’ self-esteem. However, training in martial arts can take considerable time, usually more time than can be allotted in a typical middle school physical education unit. This paper provides teachers a way to increase students’ self-esteem and confidence by quickly teaching and reinforcing fundamental martial arts skills through a game series known as “Fun-Defense.

Interoperable Ocean Observing Using Archetypes: A Use-case Based Evaluation

This paper presents a use-case based evaluation of the impact of two-level modeling on the automatic federation of ocean observational data. The goal of the work is to increase the interoperability and data quality of aggregated ocean observations to support convenient discovery and consumption by applications. An assessment of the interoperability of served data flows from publicly available ocean observing spatial data infrastructures was performed. Barriers to consumption of existing standards-compliant ocean-observing data streams were examined, including the impact of adherence to agreed data standards. Historical data flows were mapped to a set of archetypes and a backward integration experiment was performed to assess the incremental benefit of using two level models to federate data streams. The outcome of the evaluation demonstrates the feasibility of building a two-level model based ocean observing system using a combination of existing open source components, the adaptation of existing standards and the development of new software tools. The automatic integration of data flows becomes possible. This technique also allows real-time applications to automatically discover and federate newly discovered data flows and observations

Design and Implementation of an Archetype Based Interoperable Knowledge Eco-system for Data Buoys

This paper describes the ongoing work of the authors in translating two-level system design techniques used in Health Informatics to the Earth Systems Science domain. Health informaticians have developed a sophisticated two-level systems design approach for electronic health documentation over many years, and with the use of archetypes, have shown how knowledge interoperability among heterogeneous systems can be achieved. Translating two-level modelling techniques to a new domain is a complex task. A proof-of-concept archetype enabled data buoy eco-system is presented. The concept of operational templates-as-a service is proposed. Design recommendations and implementation experiences of re-working the proposed architecture to run on ultra-resource constrained data buoy platforms using templates-as-service are described

Applying Two-Level Modelling to Remote Sensor Systems Design to Enable Future Knowledge Generation

Geographical Information Scientists have a need to combine data from many sources and in various ways to synthesize new understanding, producing new knowle­dge [1]. Remote sensor deployments, monitoring environmental phenomena, are a huge provider of valuable data. Often, observation systems are built in isolation, and the data representations are not adequately designed for re-use and higher order knowledge generation. There are many standards that allow syntactic interoperability and sharing of remote sensor systems observational data, such as the OGC’s suite of standards [2]. However, semantic interoperability remains a work in progress [3] [4]. This presentation describes how system design techniques used in the health informatics domain [5] to tackle similar problems of how data, information and knowledge concepts are modelled and managed can be applied to remote sensing applications. Much like the health domain, remotely sensed data is traditionally modelled from a computer science perspective. Traditional object-oriented techniques typically used to model complex data are insufficient in a geographical data context, as they are too stringent during the early stages of knowledge acquisition. Standards such as O&M on their own precipitate a codifying effect as systems are developed, constraining rapidly evolving information [6]. The authors have investigated the OGC’s O&M standard as a reference model to underpin a two-level modelling approach. An augmented O&M model has been developed and is presented along with a worked example of how a two-level modelling approach using O&M as the reference model can be applied to modelling a marine data buoy. [1] M. Gahegan and W. Pike, A situated knowledge representation of geographical information, Transactions in GIS, vol. 10, pp. 727-749, 2006. [2] M. Botts, G. Percivall, C. Reed and J. Davidson, OGC® sensor web enablement: Overview and high level architecture, in GeoSensor Networks Springer, 2008, pp. 175-190. [3] S. Cox, An explicit OWL representation of ISO/OGC observations and measurements. in Ssn@ Iswc, 2013, pp. 1-18. [4] A. M. Leadbetter, R. K. Lowry and D. O. Clements, Putting meaning into NETMAR–the open service network for marine environmental data, International Journal of Digital Earth, pp. 1-18, 2013. [5] T. Beale, Archetypes: Constraint-based domain models for future-proof information systems, in OOPSLA 2002 Workshop on Behavioural Semantics, 2002. [6] M. F. Goodchild, GIScience ten years after Ground Truth, Transactions in GIS, vol. 10, pp. 687-692, 2006

Re-Annotation of Cough Events in the AMI Corpus

Cough sounds act as an important indicator of an individual\u27s physical health, often used by medical professionals in diagnosing a patient\u27s ailments. In recent years progress has been made in the area of automatically detecting cough events and, in certain cases, automatically identifying the ailment associated with a particular cough sound. Ethical and sensitivity issues associated with audio recordings of coughs makes it more difficult for this data to be made publicly available. However, without the public availability of a reliable database of cough sounds, developments in the area of audio event detection are likely to be hampered. The purpose of this paper is to spread awareness of a database containing a large amount of naturally occurring cough sounds that can be used for the implementation, evaluation, and comparison of new machine learning algorithms that allow for audio event detection associated with cough sounds. Using a purpose built GUI designed in MATLAB, the re-annotation procedure followed a reusable methodology that allowed for quick and efficient importing and marking of audio signals, resulting in a re-annotated version of the Augmented Multi-party Interaction (AMI) corpus\u27 cough location annotations, with 1369 individual cough events. All cough annotations and the re-annotation tool are made available for download and public use