Pruning GHSOM to create an explainable intrusion detection system

Intrusion Detection Systems (IDS) that provide high detection rates but are black boxes leadto models that make predictions a security analyst cannot understand. Self-Organizing Maps(SOMs) have been used to predict intrusion to a network, while also explaining predictions throughvisualization and identifying significant features. However, they have not been able to compete withthe detection rates of black box models. Growing Hierarchical Self-Organizing Maps (GHSOMs)have been used to obtain high detection rates on the NSL-KDD and CIC-IDS-2017 network trafficdatasets, but they neglect creating explanations or visualizations, which results in another blackbox model.This paper offers a high accuracy, Explainable Artificial Intelligence (XAI) based on GHSOMs.One obstacle to creating a white box hierarchical model is the model growing too large and complexto understand. Another contribution this paper makes is a pruning method used to cut down onthe size of the GHSOM, which provides a model that can provide insights and explanation whilemaintaining a high detection rate

Analysis of topographic maps for recreational purposes using decision trees

pre-printIn this paper we describe a method for predicting the subjective quality of a new mountain bike route for a particular subject based on routes previously ridden and ranked by the subject. GPS tracks of the previously ridden routes are over laid on rasterized topographic maps and topographic features are extracted in the vicinity of the routes using image processing techniques. The subject ranks each previously ridden route segment on four subjective qualities. The extracted topographic features and the subjective rankings are used as input vectors and target vectors to train a series of decision trees. The decision trees are then tested on a series of route segments not used in the decision tree training. The decision trees were able to exactly predict the subjective rankings with over 60% accuracy vs. 20% accuracy for random selection. When close matches are allowed in the prediction of subjective ranking (plus or minus one point vs. actual) the accuracy of the decision trees increased to 90% and above

An analytical model of momentum availability for predicting large wind farm power

Turbine-wake and farm-atmosphere interactions influence wind farm power production. For large offshore farms, the farm-atmosphere interaction is usually the more significant effect. This study proposes an analytical model of the `momentum availability factor' to predict the impact of farm-atmosphere interactions. It models the effects of net advection, pressure gradient forcing and turbulent entrainment, using steady quasi-1D flow assumptions. Turbulent entrainment is modelled by assuming self-similar vertical shear stress profiles. We used the model with the `two-scale momentum theory' to predict the power of large finite-sized farms. The model compared well with existing results of large-eddy simulations (LES) of finite wind farms in conventionally neutral boundary layers. The model captured most of the effects of atmospheric boundary layer (ABL) height on farm performance by considering the undisturbed vertical shear stress profile of the ABL as an input. In particular, the model predicted the power of staggered wind farms with a typical error of 5% or less. The developed model provides a novel way of instantly predicting the power of large wind farms, including the farm blockage effects. A further simplification of the model to analytically predict the 'wind extractability factor' is also presented. This study provides a novel framework for modelling farm-atmosphere interactions. Future studies can use the framework to better model large wind farms.Comment: 22 pages, 12 figures, 4 table

Medication management in community care: using hierarchical task analysis to describe complex systems

This paper presents an investigation into medication management at a UK Community Healthcare Trust. Data were collected at two community in-patient facilities to review practice at the two sites against the Standard Operating Procedures for (1) Medicines Management and (2) Controlled Drugs Management for four key tasks: ordering, transportation, receipt and storage of medicines. The variances in practice were discussed with senior management with the recommendation to simplify the system with a single SOP and provision of in-house pharmacy services at both sites

Aspects of the employment of children in the British coal-mining industry, 1800-1872.

This thesis examines aspects of historiography, legislation, working conditions and welfare relating to the employment of the children who worked in British coal mines between 1800 and 1872. Contemporary views of children's employment in mines are considered in the light of the Children's Employment Commission of 1842. The movement for the abolition of child labour is examined and claims of 'indecent' underground working conditions are investigated. It is argued that the decline in the incidence of children's employment in coal mining came about as a result of the declining economic viability of their labour to the industry. The legislative prohibition of children from the coal industry was a rational process driven largely by improvements in production technology and by safety considerations. The research suggests that the incidence of child employment was lowest in the most technologically advanced coalfields. Computer-aided prosopography was used to analyse ages and occupations of mining children. The physical stature of mining children is discussed as an indicator of their nutritional status and welfare. A number of environmental influences upon the relative shorter stature of mining children are identified and these findings are viewed within the wider debate over the stature of historical populations. Ill-treatment and corporal punishment of children did not arise primarily from the process of coal production. The lowest levels of ill-treatment existed in the most advanced enterprises. The incidence of corporal punishment was greatest in the less developed coalfields and serious ill-treatment was most prevalent among non-parented children. Punishment was an aspect of safety discipline and this issue too is explored

Tripartite Prodrugs of The Anthracycline Anticancer Drug Candidate Doxazolidine: New Methods and Mechanisms Relevant To Their Synthesis

This dissertation describes the development of a new method for the synthesis of tripartiteprodrugs of the anticancer drug candidate doxazolidine, which utilizes, as the keytransformation, the traceless Staudinger ligation (TSL) of an aryl azide. The rationale fordeveloping a new synthetic methodology is presented in juxtaposition to the limitations of thepreexisting route for preparation of prodrugs containing the Katzenellebogan-spacer and thisdiscussion focuses on improving the efficiency with which the chemical space surrounding suchtarget molecules may be explored. A critical limitation to the newly developed method, namely,the inability to stereoselectively esterify C-chiral peptides with 2-(diphenylphosphino)phenol,which ultimately affords a mixture of diastereomeric products and, thereby, complicates thestructural characterization and biological evaluation of the prepared prodrugs, is also discussedalong with possible solutions to the problem. Mechanistic studies provide evidence that the TSLof an aryl azide proceeds via acyl-transfer to a phosphazide intermediate, as opposed to theiminophosphorane intermediate invoked in the putative mechanism of the TSL of an alkyl azide,in a reaction that depends on the concentration of water present in the reaction medium at theoutset of the reaction. A revised mechanism for the TSL of an aryl azide and phosphino phenylester is ultimately presented alongside kinetic analysis of the reaction run under consecutivepseudo-first-order conditions in the presence of an excess of azide and water.</p

Shale Investment Dashboard in Ohio Q1 and Q2 2018

This report presents findings from an investigation into shale-related investment in Ohio. The investment estimates are cumulative from January through June of 2018. Prior investments have previously been reported and are available from Cleveland State University. Subsequent reports will estimate additional investment since the date of this report