Assessing Neural Network Prediction in Kidney Disease Data

Neural networks can be used as a potential way to predict continuous and binary outcomes. With their ability to model complex non-linear relationships between variables and outcomes, they may be better at prognosis than more traditional regression methods such as logistic regression. In this thesis, the prognostic abilities of neural networks will be assessed using data from the Consortium for Radiological Imaging Studies of Polycystic Kidney Disease (CRISP) using clinically significant variables such as BMI, Blood Urea Nitrogen (BUN), Height Adjusted Total Kidney Volume (htTKV), baseline estimated glomeruler filtration rate (eGFR), and type of PKD. Both a logisitic regression and variations of neural networks were modeled. The neural networks had hidden units from 2 to 10, and weight decays from 0.01 to 0.05. Each of these models was assessed by looking at Receiver Operator Characteristic (ROC) curves, specifically the area under the curve (AUC). The complexity of these models was also looked at by calculating the degrees of freedom for each model. More complex models could lead to an overfitting of the data, and were therefore examined in this study. The study showed that neural networks have the capability to predict the outcome of stage 3 kidney disease better than a more traditional logistic regression, however, the models become increasingly complex as the predictive ability increases. These findings could have a great impact on public health in the future. They could greatly impact the methods that are used for prognosis. The use of neural networks might lead to better prognosis and earlier treatment for kidney disease based on an individuals baseline measurements of the aforementioned variables, or any other new biomarkers that are discovered in the future

The Method-specific Certification of the Cholesterol and Triglyceride Contents of a Pure and an Adulterated Butter Fat Reference Material.

Abstract not availableJRC.D-Institute for Reference Materials and Measurements (Geel

Tradespace Exploration of Distributed Propulsors for Advanced On-Demand Mobility Concepts

Combustion-based sources of shaft power tend to significantly penalize distributed propulsion concepts, but electric motors represent an opportunity to advance the use of integrated distributed propulsion on an aircraft. This enables use of propellers in nontraditional, non-thrust-centric applications, including wing lift augmentation, through propeller slipstream acceleration from distributed leading edge propellers, as well as wingtip cruise propulsors. Developing propellers for these applications challenges long-held constraints within propeller design, such as the notion of optimizing for maximum propulsive efficiency, or the use of constant-speed propellers for high-performance aircraft. This paper explores the design space of fixed-pitch propellers for use as (1) lift augmentation when distributed about a wing's leading edge, and (2) as fixed-pitch cruise propellers with significant thrust at reduced tip speeds for takeoff. A methodology is developed for evaluating the high-level trades for these types of propellers and is applied to the exploration of a NASA Distributed Electric Propulsion concept. The results show that the leading edge propellers have very high solidity and pitch well outside of the empirical database, and that the cruise propellers can be operated over a wide RPM range to ensure that thrust can still be produced at takeoff without the need for a pitch change mechanism. To minimize noise exposure to observers on the ground, both the leading edge and cruise propellers are designed for low tip-speed operation during takeoff, climb, and approach

Flexible aggregation in multiple attribute decision making: Application to the Kuranda Range Road Upgrade

The conventional method of aggregating the satisfaction of transport projects with respect to multiple attributes is commonly some variant of Simple Additive Weighting (SAW), which involves the sum of products of standardized outcomes of projects with respect to attributes and attribute importance weights. It is suggested that alternative forms of aggregation might be more useful, in particular, the Ordered Weighted Averaging (OWA) operator introduced by Yager (1988). Attribute importance weights and satisfaction of attributes by projects may be aggregated prior to aggregation via an OWA operator. In this case OWA operator weights may be based on the "attitudinal character of the decision maker expressed in terms of the degree of "orness and "andness of the aggregation. A well-known approach is maximum entropy aggregation, in which weights are derived to be as "even (or as minimally dispersed) as a possible subject to satisfying a given "orness or "andness constraint. Recently, aggregation processes have been proposed by Larsen (199920022003) which have several desirable properties and also may be considered as alternative forms of aggregation. An example is given relating to the Kuranda Range Road upgrade (Queensland, Australia) which is limited by grade, poor overtaking opportunities, poor horizontal alignment, and other constraints, and the road is expected to become increasingly congested over the next few years. A more flexible Multiple Attribute Decision Making is used to identify a "best project from a set of four alternative projects

A multiobjective model for passive portfolio management: an application on the S&P 100 index

This is an author's accepted manuscript of an article published in: “Journal of Business Economics and Management"; Volume 14, Issue 4, 2013; copyright Taylor & Francis; available online at: http://dx.doi.org/10.3846/16111699.2012.668859Index tracking seeks to minimize the unsystematic risk component by imitating the movements of a reference index. Partial index tracking only considers a subset of the stocks in the index, enabling a substantial cost reduction in comparison with full tracking. Nevertheless, when heterogeneous investment profiles are to be satisfied, traditional index tracking techniques may need different stocks to build the different portfolios. The aim of this paper is to propose a methodology that enables a fund s manager to satisfy different clients investment profiles but using in all cases the same subset of stocks, and considering not only one particular criterion but a compromise between several criteria. For this purpose we use a mathematical programming model that considers the tracking error variance, the excess return and the variance of the portfolio plus the curvature of the tracking frontier. The curvature is not defined for a particular portfolio, but for all the portfolios in the tracking frontier. This way funds managers can offer their clients a wide range of risk-return combinations just picking the appropriate portfolio in the frontier, all of these portfolios sharing the same shares but with different weights. An example of our proposal is applied on the S&P 100.García García, F.; Guijarro Martínez, F.; Moya Clemente, I. (2013). A multiobjective model for passive portfolio management: an application on the S&P 100 index. Journal of Business Economics and Management. 14(4):758-775. doi:10.3846/16111699.2012.668859S758775144Aktan, B., Korsakienė, R., & Smaliukienė, R. (2010). TIME‐VARYING VOLATILITY MODELLING OF BALTIC STOCK MARKETS. Journal of Business Economics and Management, 11(3), 511-532. doi:10.3846/jbem.2010.25Ballestero, E., & Romero, C. (1991). A theorem connecting utility function optimization and compromise programming. Operations Research Letters, 10(7), 421-427. doi:10.1016/0167-6377(91)90045-qBeasley, J. E. (1990). OR-Library: Distributing Test Problems by Electronic Mail. Journal of the Operational Research Society, 41(11), 1069-1072. doi:10.1057/jors.1990.166Beasley, J. E., Meade, N., & Chang, T.-J. (2003). An evolutionary heuristic for the index tracking problem. European Journal of Operational Research, 148(3), 621-643. doi:10.1016/s0377-2217(02)00425-3Canakgoz, N. A., & Beasley, J. E. (2009). Mixed-integer programming approaches for index tracking and enhanced indexation. European Journal of Operational Research, 196(1), 384-399. doi:10.1016/j.ejor.2008.03.015Connor, G., & Leland, H. (1995). Cash Management for Index Tracking. Financial Analysts Journal, 51(6), 75-80. doi:10.2469/faj.v51.n6.1952Corielli, F., & Marcellino, M. (2006). Factor based index tracking. Journal of Banking & Finance, 30(8), 2215-2233. doi:10.1016/j.jbankfin.2005.07.012Derigs, U., & Nickel, N.-H. (2004). On a Local-Search Heuristic for a Class of Tracking Error Minimization Problems in Portfolio Management. Annals of Operations Research, 131(1-4), 45-77. doi:10.1023/b:anor.0000039512.98833.5aDose, C., & Cincotti, S. (2005). Clustering of financial time series with application to index and enhanced index tracking portfolio. Physica A: Statistical Mechanics and its Applications, 355(1), 145-151. doi:10.1016/j.physa.2005.02.078Focardi, S. M., & Fabozzi 3, F. J. (2004). A methodology for index tracking based on time-series clustering. Quantitative Finance, 4(4), 417-425. doi:10.1080/14697680400008668Gaivoronski, A. A., Krylov, S., & van der Wijst, N. (2005). Optimal portfolio selection and dynamic benchmark tracking. European Journal of Operational Research, 163(1), 115-131. doi:10.1016/j.ejor.2003.12.001Hallerbach, W. G., & Spronk, J. (2002). The relevance of MCDM for financial decisions. Journal of Multi-Criteria Decision Analysis, 11(4-5), 187-195. doi:10.1002/mcda.328Jarrett, J. E., & Schilling, J. (2008). DAILY VARIATION AND PREDICTING STOCK MARKET RETURNS FOR THE FRANKFURTER BÖRSE (STOCK MARKET). Journal of Business Economics and Management, 9(3), 189-198. doi:10.3846/1611-1699.2008.9.189-198Roll, R. (1992). A Mean/Variance Analysis of Tracking Error. The Journal of Portfolio Management, 18(4), 13-22. doi:10.3905/jpm.1992.701922Rudolf, M., Wolter, H.-J., & Zimmermann, H. (1999). A linear model for tracking error minimization. Journal of Banking & Finance, 23(1), 85-103. doi:10.1016/s0378-4266(98)00076-4Ruiz-Torrubiano, R., & Suárez, A. (2008). A hybrid optimization approach to index tracking. Annals of Operations Research, 166(1), 57-71. doi:10.1007/s10479-008-0404-4Rutkauskas, A. V., & Stasytyte, V. (s. f.). Decision Making Strategies in Global Exchange and Capital Markets. Advances and Innovations in Systems, Computing Sciences and Software Engineering, 17-22. doi:10.1007/978-1-4020-6264-3_4Tabata, Y., & Takeda, E. (1995). Bicriteria Optimization Problem of Designing an Index Fund. Journal of the Operational Research Society, 46(8), 1023-1032. doi:10.1057/jors.1995.139Teresienė, D. (2009). LITHUANIAN STOCK MARKET ANALYSIS USING A SET OF GARCH MODELS. Journal of Business Economics and Management, 10(4), 349-360. doi:10.3846/1611-1699.2009.10.349-36

The Narrative Frame of Daniel: A Literary Assessment

This paper presents a fuzzy multicriteria group decision making approach for evaluating and selecting information systems projects. The inherent subjectiveness and imprecision of the evaluation process is modeled by using linguistic terms characterized by triangular fuzzy numbers. A new algorithm based on the concept of the degree of dominance is developed to avoid the complex and unreliable process of comparing fuzzy numbers usually required in fuzzy multicriteria decision making. A multicriteria decision support system is proposed to facilitate the evaluation and selection process. An information systems project selection problem is presented to demonstrate the effectiveness of the approach

TRY plant trait database - enhanced coverage and open access

Plant traits-the morphological, anatomical, physiological, biochemical and phenological characteristics of plants-determine how plants respond to environmental factors, affect other trophic levels, and influence ecosystem properties and their benefits and detriments to people. Plant trait data thus represent the basis for a vast area of research spanning from evolutionary biology, community and functional ecology, to biodiversity conservation, ecosystem and landscape management, restoration, biogeography and earth system modelling. Since its foundation in 2007, the TRY database of plant traits has grown continuously. It now provides unprecedented data coverage under an open access data policy and is the main plant trait database used by the research community worldwide. Increasingly, the TRY database also supports new frontiers of trait-based plant research, including the identification of data gaps and the subsequent mobilization or measurement of new data. To support this development, in this article we evaluate the extent of the trait data compiled in TRY and analyse emerging patterns of data coverage and representativeness. Best species coverage is achieved for categorical traits-almost complete coverage for 'plant growth form'. However, most traits relevant for ecology and vegetation modelling are characterized by continuous intraspecific variation and trait-environmental relationships. These traits have to be measured on individual plants in their respective environment. Despite unprecedented data coverage, we observe a humbling lack of completeness and representativeness of these continuous traits in many aspects. We, therefore, conclude that reducing data gaps and biases in the TRY database remains a key challenge and requires a coordinated approach to data mobilization and trait measurements. This can only be achieved in collaboration with other initiatives

Broad band variability of SS433: Accretion disk at work?

We present broad band power spectra of variations of SS433 in radio, optical and X-ray spectral bands. We show that at frequencies lower than 1e-5 Hz the source demonstrates the same variability pattern in all these bands. The broad band power spectrum can be fitted by one power law down to frequencies ~1e-7 Hz with flattening afterwards. Such a flattening means that on time scales longer than ~1e7 sec the source variability becomes uncorrelated. This naturally leads to the appearance of quasi-poissonian flares in the source light curve, which have been regularly observed in radio and optical spectral bands. The radio flux power spectrum appears to have a second break at Fourier frequencies ~1e-5 Hz which can be caused by the smearing of the intrinsic radio variability on timescale of the light-crossing time of the radio emitting region. We find a correlation of the radio and optical fluxes of SS433 and the radio flux is delayed by about ~2 days with respect to the optical one. Power spectra of optical and X-ray variabilities continue with the same power law from 1e-7 Hz up to ~0.01-0.05 Hz. The broad band power spectrum of SS433 can be interpreted in terms of self-similar accretion rate modulations in the accretion disk proposed by Lyubarskii (1997) and elaborated by Churazov et al. (2001). We discuss a viscous time-scale in the accretion disk of SS433 in implication to the observed broad band power spectrum.Comment: 8 pages, 2 figures. Submitted to A&