Optimization the initial weights of artificial neural networks via genetic algorithm applied to hip bone fracture prediction

This paper aims to find the optimal set of initial weights to enhance the accuracy of artificial neural networks (ANNs) by using genetic algorithms (GA). The sample in this study included 228 patients with first low-trauma hip fracture and 215 patients without hip fracture, both of them were interviewed with 78 questions. We used logistic regression to select 5 important factors (i.e., bone mineral density, experience of fracture, average hand grip strength, intake of coffee, and peak expiratory flow rate) for building artificial neural networks to predict the probabilities of hip fractures. Three-layer (one hidden layer) ANNs models with back-propagation training algorithms were adopted. The purpose in this paper is to find the optimal initial weights of neural networks via genetic algorithm to improve the predictability. Area under the ROC curve (AUC) was used to assess the performance of neural networks. The study results showed the genetic algorithm obtained an AUC of 0.858±0.00493 on modeling data and 0.802 ± 0.03318 on testing data. They were slightly better than the results of our previous study (0.868±0.00387 and 0.796±0.02559, resp.). Thus, the preliminary study for only using simple GA has been proved to be effective for improving the accuracy of artificial neural networks.This research was supported by the National Science Council (NSC) of Taiwan (Grant no. NSC98-2915-I-155-005), the Department of Education grant of Excellent Teaching Program of Yuan Ze University (Grant no. 217517) and the Center for Dynamical Biomarkers and Translational Medicine supported by National Science Council (Grant no. NSC 100- 2911-I-008-001)

Type-2 fuzzy sets applied to multivariable self-organizing fuzzy logic controllers for regulating anesthesia

In this paper, novel interval and general type-2 self-organizing fuzzy logic controllers (SOFLCs) are proposed for the automatic control of anesthesia during surgical procedures. The type-2 SOFLC is a hierarchical adaptive fuzzy controller able to generate and modify its rule-base in response to the controller's performance. The type-2 SOFLC uses type-2 fuzzy sets derived from real surgical data capturing patient variability in monitored physiological parameters during anesthetic sedation, which are used to define the footprint of uncertainty (FOU) of the type-2 fuzzy sets. Experimental simulations were carried out to evaluate the performance of the type-2 SOFLCs in their ability to control anesthetic delivery rates for maintaining desired physiological set points for anesthesia (muscle relaxation and blood pressure) under signal and patient noise. Results show that the type-2 SOFLCs can perform well and outperform previous type-1 SOFLC and comparative approaches for anesthesia control producing lower performance errors while using better defined rules in regulating anesthesia set points while handling the control uncertainties. The results are further supported by statistical analysis which also show that zSlices general type-2 SOFLCs are able to outperform interval type-2 SOFLC in terms of their steady state performance

Thermoelastic Damping in Micro- and Nano-Mechanical Systems

The importance of thermoelastic damping as a fundamental dissipation mechanism for small-scale mechanical resonators is evaluated in light of recent efforts to design high-Q micrometer- and nanometer-scale electro-mechanical systems (MEMS and NEMS). The equations of linear thermoelasticity are used to give a simple derivation for thermoelastic damping of small flexural vibrations in thin beams. It is shown that Zener's well-known approximation by a Lorentzian with a single thermal relaxation time slightly deviates from the exact expression.Comment: 10 pages. Submitted to Phys. Rev.

Cold Nuclear Matter In Holographic QCD

We study the Sakai-Sugimoto model of holographic QCD at zero temperature and finite chemical potential. We find that as the baryon chemical potential is increased above a critical value, there is a phase transition to a nuclear matter phase characterized by a condensate of instantons on the probe D-branes in the string theory dual. As a result of electrostatic interactions between the instantons, this condensate expands towards the UV when the chemical potential is increased, giving a holographic version of the expansion of the Fermi surface. We argue based on properties of instantons that the nuclear matter phase is necessarily inhomogeneous to arbitrarily high density. This suggests an explanation of the "chiral density wave" instability of the quark Fermi surface in large N_c QCD at asymptotically large chemical potential. We study properties of the nuclear matter phase as a function of chemical potential beyond the transition and argue in particular that the model can be used to make a semi-quantitative prediction of the binding energy per nucleon for nuclear matter in ordinary QCD.Comment: 31 pages, LaTeX, 1 figure, v2: some formulae corrected, qualitative results unchange

Using Artificial Neural Network to Predict a Variety of Pathogenic Microorganisms

In this study, an electronic nose is used to record breathing data from healthy patients and pneumonia patients. The electronic nose records resistance data using a micro-array of 11 sensors. The recorded data is fed to Artificial Neural Network (ANN) which is used to train a model for detection of infections. The ANN has performed accurate classification which can be further developed to an online efficient pneumonia detection system. Initially, five patients’ data are used to build up the ANN model. Then, another two patients’ data are used to test the accuracy of the model. The results show that the model predicts the same outcome that is diagnosed by Taipei Medical University Hospital where samples have to be cultured to identify whether patients have pneumonia or not. In this preliminary study, ANN has achieved good results which can be further developed to an online efficient pneumonia detection system in the near future.Taiwan Carbon Nanotube Technology Corporatio

Pressure-induced valence anomaly in TmTe probed by resonant inelastic x-ray scattering

The pressure-induced valence transition in TmTe was investigated by resonant inelastic x-ray scattering at the Tm L(3) edge, a powerful probe of the rare-earth valent state. The data are analyzed within the Anderson impurity model which yields key parameters such as the Tm 4f-5d hybridization. In addition to the general tendency of the f electrons towards delocalization, we find a plateau in both the Tm valence and hybridization pressure dependences between 4.3 and 6.5 GPa which is interpreted in terms of an n-channel Kondo (NCK) screening process. This behavior is at odds with the usually continuous, single-channel Kondo-like f delocalization while being supported by the seminal calculations of the NCK temperature in Tm ion by Saso et al. Our study raises the interesting possibility that an NCK effect realized in a compressed mixed-valent f system could impede the concomitant electron delocalization

Pressure evolution of electronic and crystal structure of non-centrosymmetric EuCoGe3_3

We report on the pressure evolution of the electronic and crystal structures of the noncentrosymmetric antiferromagnet EuCoGe3. Using a diamond anvil cell, we performed high pressure fluorescence detected near-edge x-ray absorption spectroscopy at the Eu L3, Co K, and Ge K edges and synchrotron powder x-ray diffraction. In the Eu L3 spectrum, both divalent and trivalent Eu peaks are observed from the lowest pressure measurement (~2 GPa). By increasing pressure, the relative intensity of the trivalent Eu peak increases, and an average Eu valence continuously increases from 2.2 at 2 GPa to 2.31 at~50 GPa. On the other hand, no discernible changes are observed in the Co K and Ge K spectra as a function of pressure. With the increase in pressure, lattice parameters continuously decrease without changing I4mm symmetry. Our study revealed a robust divalent Eu state and an unchanged crystal symmetry of EuCoGe3 against pressure.Comment: Accepted in PRB https://journals.aps.org/prb/accepted/b2073O6fL9e1ca40307905b1de5bf05de12d8fc1

Pressure-induced structural and electronic transition in KTb(MoO₄)₂ through Raman and optical studies

Raman and optical absorption studies under pressure have been conducted on KTb(MoO4)2 up to 35.5 GPa. A phase transformation occurs at 2.7 GPa when the crystal is pressurized at ambient temperature in a hydrostatic pressure medium. The sample changes to a deep yellow color at the transition and visibly contracts in theα-axis direction. The color shifts to red on further pressure increase. The Raman spectral features and the X-ray powder pattern change abruptly at the transition indicating a structural change. The pressure-induced transition appears to be a property of the layer-type alkali rare earth dimolybdates. However, the color change at the transition in KTb(MoO4)2 is rather unusual and is attributed to a valence change in Tb initiated by the structural transition and consequent intervalence charge transfer between Tb and Mo.In situ high pressure X-ray diffraction data suggest that phase II could be orthorhombic with a unit cell having 3 to 4% smaller volume than that of phase I