Validating Synthetic Health Datasets for Longitudinal Clustering

This paper appeared at the Australasian Workshop on Health Informatics and Knowledge Management (HIKM 2013), Adelaide, Australia. Conferences in Research and Practice in Information Technology (CRPIT), Vol.142. K. Gray and A. Koronios, Eds. Reproduction for academic, not-for profit purposes permitted provided this text is included.Clustering methods partition datasets into subgroups with some homogeneous properties, with information about the number and particular characteristics of each subgroup unknown a priori. The problem of predicting the number of clusters and quality of each cluster might be overcome by using cluster validation methods. This paper presents such an approach in-corporating quantitative methods for comparison be-tween original and synthetic versions of longitudinal health datasets. The use of the methods is demon-strated by using two different clustering algorithms, K-means and Latent Class Analysis, to perform clus-tering on synthetic data derived from the 45 and Up Study baseline data, from NSW in Australia

Spirality: A Novel Way to Measure Spiral Arm Pitch Angle

We present the MATLAB code Spirality, a novel method for measuring spiral arm pitch angles by fitting galaxy images to spiral templates of known pitch. Computation time is typically on the order of 2 minutes per galaxy, assuming at least 8 GB of working memory. We tested the code using 117 synthetic spiral images with known pitches, varying both the spiral properties and the input parameters. The code yielded correct results for all synthetic spirals with galaxy-like properties. We also compared the code's results to two-dimensional Fast Fourier Transform (2DFFT) measurements for the sample of nearby galaxies defined by DMS PPak. Spirality's error bars overlapped 2DFFT's error bars for 26 of the 30 galaxies. The two methods' agreement correlates strongly with galaxy radius in pixels and also with i-band magnitude, but not with redshift, a result that is consistent with at least some galaxies' spiral structure being fully formed by z=1.2, beyond which there are few galaxies in our sample. The Spirality code package also includes GenSpiral, which produces FITS images of synthetic spirals, and SpiralArmCount, which uses a one-dimensional Fast Fourier Transform to count the spiral arms of a galaxy after its pitch is determined. The code package is freely available online; see Comments for URL.Comment: 19 pages, 9 figures, 3 tables. The code package is available at http://dafix.uark.edu/~doug/SpiralityCode

Computational bounds on polynomial differential equations

In this paper we study from a computational perspective some prop-erties of the solutions of polynomial ordinary di erential equations. We consider elementary (in the sense of Analysis) discrete-time dynam-ical systems satisfying certain criteria of robustness. We show that those systems can be simulated with elementary and robust continuous-time dynamical systems which can be expanded into fully polynomial ordinary diferential equations with coe cients in Q[ ]. This sets a computational lower bound on polynomial ODEs since the former class is large enough to include the dynamics of arbitrary Turing machines. We also apply the previous methods to show that the problem of de-termining whether the maximal interval of defnition of an initial-value problem defned with polynomial ODEs is bounded or not is in general undecidable, even if the parameters of the system are computable and comparable and if the degree of the corresponding polynomial is at most 56. Combined with earlier results on the computability of solutions of poly-nomial ODEs, one can conclude that there is from a computational point of view a close connection between these systems and Turing machines

Pengaruh Model Pembelajaran Talking Stick terhadap Keaktifan Belajar Siswa

[Title: The Effect of a Talking Stick Learning Model on Student Learning Activities]. A fun learning environment, active and meaningful for students need to be created by applying active learning model for students that learning model talking stick. This type of research is quasi-experimental. This research aimed to know there is or no effect of talking stick learning model toward students learning activeness. This research implemented in class VIII SMP Negeri 5 Mataram in academic year 2015/2016 from March to April 2016. The technique of sample using cluster random sampling, in order to obtain first-class VIII I totalling 30 students as an experimental class and class VIII E totalling 30 students as the control class. The results of this research are students' activeness learning showed by using the instrument is activeness of student learning questionnaire. Based on data analysis showed that t-test was 8.28 and t- table was 2.000 (df = 58). So, t-test > t-table (8.28 > 2.000). This means that there is an effect of talking stick learning model toward students learning activeness

Comparison of in-situ delay monitors for use in Adaptive Voltage Scaling

In Adaptive Voltage Scaling (AVS) the supply voltage of digital circuits is tuned according to the circuit's actual operating condition, which enables dynamic compensation to PVTA variations. By exploiting the excessive safety margins added in state-of-the-art worst-case designs considerable power saving is achieved. In our approach, the operating condition of the circuit is monitored by in-situ delay monitors. This paper presents different designs to implement the in-situ delay monitors capable of detecting late but still non-erroneous transitions, called Pre-Errors. The developed Pre-Error monitors are integrated in a 16 bit multiplier test circuit and the resulting Pre-Error AVS system is modeled by a Markov chain in order to determine the power saving potential of each Pre-Error detection approach

Determining the best drought tolerance indices using Artificial Neural Network (ANN): Insight into application of intelligent agriculture in agronomy and plant breeding

In the present study, efficiency of the artificial neural network (ANN) method to identify the best drought tolerance indices was investigated. For this purpose, 25 durum genotypes were evaluated under rainfed and supplemental irrigation environments during two consecutive cropping seasons (2011–2013). The results of combined analysis of variance (ANOVA) revealed that year, environment, genotype and their interaction effects were significant for grain yield. Mean grain yield of the genotypes ranged from 184.93 g plot–1 under rainfed environment to 659.32 g plot–1 under irrigated environment. Based on the ANN results, yield stability index (YSI), harmonic mean (HM) and stress susceptible index (SSI) were identified as the best indices to predict drought-tolerant genotypes. However, mean productivity (MP) followed by geometric mean productivity (GMP) and HM were found to be accurate indices for screening drought tolerant genotypes. In general, our results indicated that genotypes G9, G12, G21, G23 and G24 were identified as more desirable genotypes for cultivation in drought-prone environments. Importantly, these results could provide an evidence that ANN method can play an important role in the selection of drought tolerant genotypes and also could be useful in other biological contexts

Computability with polynomial differential equations

In this paper, we show that there are Initial Value Problems de ned with polynomial ordinary di erential equations that can simulate univer- sal Turing machines in the presence of bounded noise. The polynomial ODE de ning the IVP is explicitly obtained and the simulation is per- formed in real time

Comparison of different algorithms to map hydrothermal alteration zones using ASTER remote sensing data for polymetallic Vein-Type ore exploration: Toroud-Chahshirin Magmatic Belt (TCMB), north Iran

© 2019 by the authors. Polymetallic vein-type ores are important sources of precious metal and a principal type of orebody for various base-metals. In this research, Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) remote sensing data were used for mapping hydrothermal alteration zones associated with epithermal polymetallic vein-type mineralization in the Toroud-Chahshirin Magmatic Belt (TCMB), North of Iran. The TCMB is the largest known goldfield and base metals province in the central-north of Iran. Propylitic, phyllic, argillic, and advanced argillic alteration and silicification zones are typically associated with Au-Cu, Ag, and/or Pb-Zn mineralization in the TCMB. Specialized image processing techniques, namely Selective Principal Component Analysis (SPCA), Band Ratio Matrix Transformation (BRMT), Spectral Angle Mapper (SAM) and Mixture Tuned Matched Filtering (MTMF) were implemented and compared to map hydrothermal alteration minerals at the pixel and sub-pixel levels. Subtle differences between altered and non-altered rocks and hydrothermal alteration mineral assemblages were detected and mapped in the study area. The SPCA and BRMT spectral transformation algorithms discriminated the propylitic, phyllic, argillic and advanced argillic alteration and silicification zones as well as lithological units. The SAM and MTMF spectral mapping algorithms detected spectrally dominated mineral groups such as muscovite/montmorillonite/illite, hematite/jarosite, and chlorite/epidote/calcite mineral assemblages, systematically. Comprehensive fieldwork and laboratory analysis, including X-ray diffraction (XRD), petrographic study, and spectroscopy were conducted in the study area for verifying the remote sensing outputs. Results indicate several high potential zones of epithermal polymetallic vein-type mineralization in the northeastern and southwestern parts of the study area, which can be considered for future systematic exploration programs. The approach used in this research has great implications for the exploration of epithermal polymetallic vein-type mineralization in other base metals provinces in Iran and semi-arid regions around the world

OCEAN: a randomized Phase III study of melflufen + dexamethasone to treat relapsed refractory multiple myeloma

Melflufen is a novel peptide-drug conjugate that rapidly delivers a cytotoxic payload into tumor cells. It has emerged as a potential new multiple myeloma treatment, particularly for late-stage forms of the disease. Here we describe the rationale and design of OCEAN (NCT03151811), a randomized, head-to-head, superiority, open-label, global, Phase III study evaluating the efficacy and safety of melflufen + dexamethasone versus pomalidomide + dexamethasone. Eligible patients with relapsed refractory multiple myeloma have received 2-4 previous treatments and are refractory to both lenalidomide and their last treatment. Patients are excluded if they have previously received pomalidomide. The primary endpoint is progression-free survival, and key secondary endpoints include overall response rate, duration of response and overall survival