Evolving temporal fuzzy association rules from quantitative data with a multi-objective evolutionary algorithm

A novel method for mining association rules that are both quantitative and temporal using a multi-objective evolutionary algorithm is presented. This method successfully identifies numerous temporal association rules that occur more frequently in areas of a dataset with specific quantitative values represented with fuzzy sets. The novelty of this research lies in exploring the composition of quantitative and temporal fuzzy association rules and the approach of using a hybridisation of a multi-objective evolutionary algorithm with fuzzy sets. Results show the ability of a multi-objective evolutionary algorithm (NSGA-II) to evolve multiple target itemsets that have been augmented into synthetic datasets

Development of black ice prediction model using GIS-based multi-sensor model validation

Fog, freezing rain, and snow (melt) quickly condense on road surfaces, forming black ice that is difficult to identify and causes major accidents on highways. As a countermeasure to prevent icing car accidents, it is necessary to predict the amount and location of black ice. This study advanced previous models through machine learning and multi-sensor-verified results. Using spatial (hill shade, river system, bridge, and highway) and meteorological (air temperature, cloudiness, vapour pressure, wind speed, precipitation, snow cover, specific heat, latent heat, and solar radiation energy) data from the study area (Suncheon–Wanju Highway in Gurye-gun, Jeollanam-do, South Korea), the amount and location of black ice were modelled based on system dynamics to predict black ice and then simulated with a geographic information system in units of square metres. The intermediate factors calculated as input factors were road temperature and road moisture, modelled using a deep neural network (DNN) and numerical methods. Considering the results of the DNN, the root mean square error was improved by 148.6 % and reliability by 11.43 % compared to a previous study (linear regression). Based on the model results, multiple sensors were buried at four selected points in the study area. The model was compared with sensor data and verified with the upper-tailed test (with a significance level of 0.05) and fast Fourier transform (freezing does not occur when frequency = 0.00001 Hz). Results of the verified simulation can provide valuable data for government agencies like road traffic authorities to prevent traffic accidents caused by black ice

Construction of radial basis function networks with diversified topologies

In this review we bring together some of our recent work from the angle of the diversified RBF topologies, including three different topologies; (i) the RBF network with tunable nodes; (ii) the Box-Cox output transformation based RBF network (Box-Cox RBF); and (iii) the RBF network with boundary value constraints (BVC-RBF). We show that the modified topologies have some advantages over the conventional RBF topology for specific problems. For each modified topology, the model construction algorithms have been developed. These proposed RBF topologies are respectively aimed at enhancing the modelling capabilities of; (i)flexible basis function shaping for improved model generalisation with the minimal model;(ii) effectively handling some dynamical processes in which the model residuals exhibit heteroscedasticity; and (iii) achieving automatic constraints satisfaction so as to incorporate deterministic prior knowledge with ease. It is shown that it is advantageous that the linear learning algorithms, e.g. the orthogonal forward selection (OFS) algorithm based leave-one-out (LOO) criteria, are still applicable as part of the proposed algorithms

Restriction fragment mass polymorphism (RFMP) analysis based on MALDI-TOF mass spectrometry for detecting antiretroviral resistance in HIV-1 infected patients

AbstractViral genotype assessment is important for effective clinical management of HIV-1 infected patients, especially when access and/or adherence to antiretroviral treatment is reduced. In this study, we describe development of a matrix-assisted laser desorption/ionization-time of flight mass spectrometry-based viral genotyping assay, termed restriction fragment mass polymorphism (RFMP). This assay is suitable for sensitive, specific and high-throughput detection of multiple drug-resistant HIV-1 variants. One hundred serum samples from 60 HIV-1-infected patients previously exposed to nucleoside reverse transcriptase inhibitors (NRTIs), non-nucleoside reverse transcriptase inhibitors (NNRTIs) and protease inhibitors (PIs) were analysed for the presence of drug-resistant viruses using the RFMP and direct sequencing assays. Probit analysis predicted a detection limit of 223.02 copies/mL for the RFMP assay and 1268.11 copies/mL for the direct sequencing assays using HIV-1 RNA Positive Quality Control Series. The concordance rates between the RFMP and direct sequencing assays for the examined codons were 97% (K65R), 97% (T69Ins/D), 97% (L74VI), 97% (K103N), 96% (V106AM), 97% (Q151M), 97% (Y181C), 97% (M184VI) and 94% (T215YF) in the reverse transcriptase coding region, and 100% (D30N), 100% (M46I), 100% (G48V), 100% (I50V), 100% (I54LS), 99% (V82A), 99% (I84V) and 100% (L90M) in the protease coding region. Defined mixtures were consistently and accurately identified by RFMP at 5% relative concentration of mutant to wild-type virus while at 20% or greater by direct sequencing. The RFMP assay based on mass spectrometry proved to be sensitive, accurate and reliable for monitoring the emergence and early detection of HIV-1 genotypic variants that lead to drug resistance

Cosmic Rays during BBN as Origin of Lithium Problem

There may be non-thermal cosmic rays during big-bang nucleosynthesis (BBN) epoch (dubbed as BBNCRs). This paper investigated whether such BBNCRs can be the origin of Lithium problem or not. It can be expected that BBNCRs flux will be small in order to keep the success of standard BBN (SBBN). With favorable assumptions on the BBNCR spectrum between 0.09 -- 4 MeV, our numerical calculation showed that extra contributions from BBNCRs can account for the $^7$Li abundance successfully. However $^6$Li abundance is only lifted an order of magnitude, which is still much lower than the observed value. As the deuteron abundance is very sensitive to the spectrum choice of BBNCRs, the allowed parameter space for the spectrum is strictly constrained. We should emphasize that the acceleration mechanism for BBNCRs in the early universe is still an open question. For example, strong turbulent magnetic field is probably the solution to the problem. Whether such a mechanism can provide the required spectrum deserves further studies.Comment: 34 pages, 21 figures, published versio

Predicting microbial water quality with models: Over-arching questions for managing risk in agricultural catchments

The application of models to predict concentrations of faecal indicator organisms (FIOs) in environmental systems plays an important role for guiding decision-making associated with the management of microbial water quality. In recent years there has been an increasing demand by policy-makers for models to help inform FIO dynamics in order to prioritise efforts for environmental and human-health protection. However, given the limited evidence-base on which FIO models are built relative to other agricultural pollutants (e.g. nutrients) it is imperative that the end-user expectations of FIO models are appropriately managed. In response, this commentary highlights four over-arching questions associated with: (i) model purpose; (ii) modelling approach; (iii) data availability; and (iv) model application, that must be considered as part of good practice prior to the deployment of any modelling approach to predict FIO behaviour in catchment systems. A series of short and longer-term research priorities are proposed in response to these questions in order to promote better model deployment in the field of catchment microbial dynamics

Spin dependent scattering of a domain-wall of controlled size

Magnetoresistance measurements in the CPP geometry have been performed on single electrodeposited Co nanowires exchange biased on one side by a sputtered amorphous GdCo layer. This geometry allows the stabilization of a single domain wall in the Co wire, the thickness of which can be controlled by an external magnetic field. Comparing magnetization, resistivity, and magnetoresistance studies of single Co nanowires, of GdCo layers, and of the coupled system, gives evidence for an additional contribution to the magnetoresistance when the domain wall is compressed by a magnetic field. This contribution is interpreted as the spin dependent scattering within the domain wall when the wall thickness becomes smaller than the spin diffusion length.Comment: 9 pages, 13 figure

Modification of argon impurity transport by electron cyclotron heating in KSTAR H-mode plasmas

Experiments with a small amount of Ar gas injection as a trace impurity were conducted in the Korea Superconducting Tokamak Advanced Research (KSTAR) H-mode plasma (BT  = 2.8 T, IP = 0.6 MA, and PNBI = 4.0 MW). 170 GHz electron cyclotron resonance heating (ECH) at 600 and 800 kW was focused along the mid-plane with a fixed major radial position of R  =  1.66 m. The emissivity of the Ar16+ (3.949 Å) and Ar15+ (353.860 Å) spectral lines were measured by x-ray imaging crystal spectroscopy (XICS) and a vacuum UV (VUV) spectrometer, respectively. ECH reduces the peak Ar15+ emission and increases the Ar16+ emission, an effect largest with 800 kW. The ADAS-SANCO impurity transport code was used to evaluate the Ar transport coefficients. It was found that the inward convective velocity found in the plasma core without ECH was decreased with ECH, while diffusion remained approximately constant resulting in a less-peaked Ar density profile. Theoretical results from the NEO code suggest that neoclassical transport is not responsible for the change in transport, while the microstability analysis using GKW predicts a dominant ITG mode during both ECH and non-ECH plasmas

Small Open Chemical Systems Theory and Its Implications to Darwinian Evolutionary Dynamics, Complex Self-Organization and Beyond

The study of biological cells in terms of mesoscopic, nonequilibrium, nonlinear, stochastic dynamics of open chemical systems provides a paradigm for other complex, self-organizing systems with ultra-fast stochastic fluctuations, short-time deterministic nonlinear dynamics, and long-time evolutionary behavior with exponentially distributed rare events, discrete jumps among punctuated equilibria, and catastrophe.Comment: 15 page