Precision and Recall Reject Curves for Classification

For some classification scenarios, it is desirable to use only those classification instances that a trained model associates with a high certainty. To obtain such high-certainty instances, previous work has proposed accuracy-reject curves. Reject curves allow to evaluate and compare the performance of different certainty measures over a range of thresholds for accepting or rejecting classifications. However, the accuracy may not be the most suited evaluation metric for all applications, and instead precision or recall may be preferable. This is the case, for example, for data with imbalanced class distributions. We therefore propose reject curves that evaluate precision and recall, the recall-reject curve and the precision-reject curve. Using prototype-based classifiers from learning vector quantization, we first validate the proposed curves on artificial benchmark data against the accuracy reject curve as a baseline. We then show on imbalanced benchmarks and medical, real-world data that for these scenarios, the proposed precision- and recall-curves yield more accurate insights into classifier performance than accuracy reject curves.Comment: 11 pages, 3 figures. Updated figure label

A two-level structure for advanced space power system automation

The tasks to be carried out during the three-year project period are: (1) performing extensive simulation using existing mathematical models to build a specific knowledge base of the operating characteristics of space power systems; (2) carrying out the necessary basic research on hierarchical control structures, real-time quantitative algorithms, and decision-theoretic procedures; (3) developing a two-level automation scheme for fault detection and diagnosis, maintenance and restoration scheduling, and load management; and (4) testing and demonstration. The outlines of the proposed system structure that served as a master plan for this project, work accomplished, concluding remarks, and ideas for future work are also addressed

STRIPA: A Rule-Based Decision Support System for Medication Reviews in Primary Care

The chronic use of multiple medicinal drugs is growing, partly because individual patients’ drugs have not been adequately prescribed by primary care physicians. In order to reduce these polypharmacy problems, the Systematic Tool to Reduce Inappropriate Prescribing (STRIP) has been created. To facilitate physicians’ use of the STRIP method, the STRIP Assistant (STRIPA) has been developed. STRIPA is a stand-alone web-based decision support system that advices physicians during the pharmacotherapeutic analysis of patients’ health records. In this paper the application’s architecture and rule engine, and the design decisions relating to the user interface and semantic interoperability, are described. An experimental validation of the prototype by general practitioners and pharmacists showed that users perform significantly better when optimizing medication with STRIPA than without. This leads the authors to believe that one process-oriented decision support system, built around a context-aware rule engine, operated through an intuitive user interface, is able to contribute to improving drug prescription practices

Mitigating Concept Drift via Rejection

Göpfert JP, Hammer B, Wersing H. Mitigating Concept Drift via Rejection. In: Kurkova V, Manolopoulos Y, Hammer B, Iliadis L, Maglogiannis I, eds. Artificial Neural Networks and Machine Learning – ICANN 2018. Proceedings, Part I. Lecture Notes in Computer Science. Vol 11139. Cham: Springer; 2018

Scientific progress of design research artefacts

Many existing IT applications exhibit strongly varying demand patterns for resources. Accommodating an ever increasing and highly fluctuating demand requires continuous availability of sufficient resources. To achieve this state at reasonably costs, a high degree of flexibility with respect to the given IT infrastructure is necessary. Facing this challenge the idea of Cloud computing has been gaining interest. In so-called Clouds resources such as CPU, storage and bandwidth can be bundled into a single services, which are offered to Cloud users. These services can be accessed in oblivion of the underlying IT infrastructure. This way Cloud Computing facilitates the introduction of new products and services without large investments in the IT infrastructure. Cloud Computing is a promising approach with a high impact on business models. One aspect of business models is clearly the revenue model, which defines how prices should be set to achieve predefined revenue level. The decision about accepting or denying requests has a high impact on the revenue of the provider. In this paper we analyze two approaches that support the cloud provider in its decision. We show that predefined policies allow increasing revenue compared to widely used technical models such as first-come-first-serve

Proof-of-Concept Application - Annual Report Year 2

This document first gives an introduction to Application Layer Networks and subsequently presents the catallactic resource allocation model and its integration into the middleware architecture of the developed prototype. Furthermore use cases for employed service models in such scenarios are presented as general application scenarios as well as two very detailed cases: Query services and Data Mining services. This work concludes by describing the middleware implementation and evaluation as well as future work in this area. --Grid Computing

A vision system planner for increasing the autonomy of the Extravehicular Activity Helper/Retriever

The Extravehicular Activity Retriever (EVAR) is a robotic device currently being developed by the Automation and Robotics Division at the NASA Johnson Space Center to support activities in the neighborhood of the Space Shuttle or Space Station Freedom. As the name implies, the Retriever's primary function will be to provide the capability to retrieve tools and equipment or other objects which have become detached from the spacecraft, but it will also be able to rescue a crew member who may have become inadvertently de-tethered. Later goals will include cooperative operations between a crew member and the Retriever such as fetching a tool that is required for servicing or maintenance operations. This paper documents a preliminary design for a Vision System Planner (VSP) for the EVAR that is capable of achieving visual objectives provided to it by a high level task planner. Typical commands which the task planner might issue to the VSP relate to object recognition, object location determination, and obstacle detection. Upon receiving a command from the task planner, the VSP then plans a sequence of actions to achieve the specified objective using a model-based reasoning approach. This sequence may involve choosing an appropriate sensor, selecting an algorithm to process the data, reorienting the sensor, adjusting the effective resolution of the image using lens zooming capability, and/or requesting the task planner to reposition the EVAR to obtain a different view of the object. An initial version of the Vision System Planner which realizes the above capabilities using simulated images has been implemented and tested. The remaining sections describe the architecture and capabilities of the VSP and its relationship to the high level task planner. In addition, typical plans that are generated to achieve visual goals for various scenarios are discussed. Specific topics to be addressed will include object search strategies, repositioning of the EVAR to improve the quality of information obtained from the sensors, and complementary usage of the sensors and redundant capabilities

Entrepreneur’s Nightmare – Corporate Failure: Consequences and Probable Solutions

The main objective of this study is to determine the causes, effects and problems that lead to frequent corporate failure in Nigeria and to proffer possible solutions. In effecting this  work, we used questionnaires administered to prospective investors, owners of selected firms in Delta State and a cross section  of customers drawn randomly, interviews with some  key management staff of the selected firms, as well as related published and unpublished data of the firms. We analyzed the data and information obtained using regression and correlation analyses through SPSS statistical software. It was observed that some of the problem militating against production firms that leads to their failure in Nigeria could have been averted through capital restructuring and proper financial portfolio. In view of the findings and outcome of the tested hypotheses we advance as one of the recommendations that Monetary authorities and National Economic Reconstruction Fund (NERFUND) could give lighter conditionality and, fund assistance as well as eligibility for firms enlistment into the Nigeria Stock Market (going public), this would enable entrepreneurs evolve effective growth policies, as well as fund mobilization that would gear up their capital base and help avert possible causes of failure. Keywords:Corporate failure, Capital base, Capital restructuring, Corporate growt