Naive Calculations Research Articles

Analysis of Damage Handling in The PT Petrokimia Gresik Factory Conveyor Safety System Using The Naive Bayes Method

In the industrial world, the speed of the production process plays a very important role in influencing industrial profits. One of the factors that determines production speed is the conveyor. PT. Petrokimia Gresik is one of the industries that uses conveyors, which pays great attention to accuracy and control of material speed. The function of the conveyor is to send raw materials from PT Petrokimia Gresik fertilizer to be processed. Three safety devices are installed on this tool, namely the low speed switch, outlying belt and cable pull switch. However, this complex security system makes it difficult for field technicians to handle conveyor problems. Problems that occur with conveyors, especially in the electrical and instrumentation parts, are sometimes difficult to find. Therefore, the author had the idea to conduct research related to conveyor problem solving analysis using the naive Bayes classification method. The results of the calculation between naive Bayes calculations and expert opinion show 100% agreement, which is an optimal result. It is hoped that these results can help field technicians in diagnosing and resolving problems when problems occur with conveyors.

Penentuan Lokasi Fasilitas Kesehatan Strategis Menggunakan Metode Naive Bayes pada RSU Bintang

At present the selection of strategic health facility locations is not easy, to determine the right location and in accordance with the needs of patients must use the right calculation. Bintang General Hospital (RSU Bintang) has difficulties in determining the strategic location of new health facilities. The difficulty is due to the absence of data processing from the current system so that in determining the location of strategic health facilities is not based on data that has been analyzed. Based on the problems experienced by RSU Bintang and to assist in making a decision in establishing a strategic health facility location, a study was made to design a decision support system that can perform calculations to determine the location of the most strategic health facility with the title "Decision Support System. Determining the Location of Strategic Health Facilities Using the Naive Bayes Method at RSU Bintang”. Decision support system that is built will have several functions, such as processing patient register data, user data processing, alternative location data processing, criteria data processing, data processing rules, Naive Bayes calculations and managing several reports that can be used as decision support for the RSU Bintang. in determining the location of the most strategic health facilities. In this system, testing has been done by using blackbox testing which gets the test results in accordance with the system design.

AEP-DLA: Adverse Event Prediction in Hospitalized Adult Patients Using Deep Learning Algorithms

Early prediction of clinical deterioration such as adverse events (AEs), improves patient safety. National Early Warning Score (NEWS) is widely used to predict AEs based on the aggregation of 6 physiological parameters. We took the same parameters as the features for AE prediction using deep learning algorithms (AEP-DLA) among hospitalized adult patients. The aim of this study is to get better performance than traditional naive mathematical calculations by introducing novel vital sign data preprocessing schemes. We retrospectively collected the data from our electronic medical record data warehouse (2007 ~ 2017). AE rate of all 99,861 admissions was 6.2%. The dataset was divided into training and testing datasets from 2007–2015 and 2016–2017 respectively. In real-life clinical care, physiological parameters were not recorded every hour and missed frequently, for example, Glasgow Coma Scale (GCS). The expert domain suggested that missed GCS was rated as 15. We took two strategies (stack series records and align by hour) in the data preprocessing and tripling the values of negative samples for class balancing (CB). We used the last 28 hours’ serial data to predict AEs 3 hours later with Random Forest, XGBoost, Convolutional Neural Network (CNN) and Recurrent Neural Network (RNN). It is shown that CNN with CB and align by hour got the best results comparing to the other methods. The precision, recall and area under curve were 0.841, 0.928 and 0.995 respectively. The performance of the model is also better than those proposed in the published literatures.

Spin-density Wave Assisted Mott Transition at Finite Temperatures

Motivated by the metal–insulator transition in layered organic compound λ-(BETS)2FeCl4, where naive theoretical calculations predict metallic phase after the antiferromagnetic transition, we propos...

The case for a Casimir cosmology.

The cosmological constant, also known as dark energy, was believed to be caused by vacuum fluctuations, but naive calculations give results in stark disagreement with fact. In the Casimir effect, vacuum fluctuations cause forces in dielectric media, which is very well described by Lifshitz theory. Recently, using the analogy between geometries and media, a cosmological constant of the correct order of magnitude was calculated with Lifshitz theory (Leonhardt 2019 Ann. Phys. (New York) 411, 167973. (doi:10.1016/j.aop.2019.167973)). This paper discusses the empirical evidence and the ideas behind the Lifshitz theory of the cosmological constant without requiring prior knowledge of cosmology and quantum field theory.This article is part of a discussion meeting issue ‘The next generation of analogue gravity experiments’.

How to hide a cosmological constant

Naive calculations in quantum field theory suggest that vacuum fluctuations should induce an enormous cosmological constant. What if these estimates are right? I argue that even a huge cosmological constant might be hidden in Planck-scale fluctuations of geometry and topology — what Wheeler called “spacetime foam” — while remaining virtually invisible macroscopically.

Failure of perturbation theory near horizons: the Rindler example

Persistent puzzles to do with information loss for black holes have stimulated critical reassessment of the domain of validity of semiclassical EFT reasoning in curved spacetimes, particularly in the presence of horizons. We argue here that perturbative predictions about evolution for very long times near a horizon are subject to problems of secular growth — i.e. powers of small couplings come systematically together with growing functions of time. Such growth signals a breakdown of naive perturbative calculations of late-time behaviour, regardless of how small ambient curvatures might be. Similar issues of secular growth also arise in cosmology, and we build evidence for the case that such effects should be generic for gravitational fields. In particular, inferences using free fields coupled only to background metrics can be misleading at very late times due to the implicit assumption they make of perturbation theory when neglecting other interactions. Using the Rindler horizon as an example we show how this secular growth parallels similar phenomena for thermal systems, and how it can be resummed to allow late-time inferences to be drawn more robustly. Some comments are made about the appearance of an IR/UV interplay in this calculation, as well as on the possible relevance of our calculations to predictions near black-hole horizons.

A two-stage strategy to accommodate general patterns of confounding in the design of observational studies

Accommodating general patterns of confounding in sample size/power calculations for observational studies is extremely challenging, both technically and scientifically. While employing previously implemented sample size/power tools is appealing, they typically ignore important aspects of the design/data structure. In this paper, we show that sample size/power calculations that ignore confounding can be much more unreliable than is conventionally thought; using real data from the US state of North Carolina, naive calculations yield sample size estimates that are half those obtained when confounding is appropriately acknowledged. Unfortunately, eliciting realistic design parameters for confounding mechanisms is difficult. To overcome this, we propose a novel two-stage strategy for observational study design that can accommodate arbitrary patterns of confounding. At the first stage, researchers establish bounds for power that facilitate the decision of whether or not to initiate the study. At the second stage, internal pilot data are used to estimate key scientific inputs that can be used to obtain realistic sample size/power. Our results indicate that the strategy is effective at replicating gold standard calculations based on knowing the true confounding mechanism. Finally, we show that consideration of the nature of confounding is a crucial aspect of the elicitation process; depending on whether the confounder is positively or negatively associated with the exposure of interest and outcome, naive power calculations can either under or overestimate the required sample size. Throughout, simulation is advocated as the only general means to obtain realistic estimates of statistical power; we describe, and provide in an R package, a simple algorithm for estimating power for a case-control study.

The Effects of Herd Immunity on the Power of Vaccine Trials

We evaluate the effects of herd immunity on the power of vaccine trials. We consider large-scale trials in which persons are individually randomized to either placebo or vaccine. We evaluate the adequacy of naive power calculations that ignore the effects of herd immunity such as those based on the comparison of two independent binomials. We developed a simulation design to evaluate the quantitative effects of herd immunity on power. The simulation design accounted for nonhomogeneous mixing. We found that naive power calculations that ignore the effects of herd immunity can seriously overestimate power. In fact, we found that as sample size increases it is possible for the power to actually decrease. The reason is that herd immunity reduces the overall number of infections. In the situations we considered, power may eventually begin to decrease once the proportion of the population enrolled in the trial exceeds about 25%. We discuss the findings in the context of a pneumococcal vaccine trial for children. Our results serve as a cautionary note that naive sample size calculations for larger scale vaccine trials that ignore the impact of herd immunity can yield underpowered studies. Simulations such as that suggested here can help alert investigators to situations where significant dilution of power could result from ignoring the effects of herd immunity.

Absolute hydration free energies of ions, ion–water clusters, and quasichemical theory

Experimental studies of ion–water clusters have provided insights into the microscopic aspects of hydration phenomena. One common view is that extending those experimental studies to larger cluster sizes would give the single-ion absolute hydration free energies not obtainable by classical thermodynamic methods. This issue is reanalyzed in the context of recent computations and molecular theories of ion hydration, particularly considering the hydration of H+, Li+, Na+, and HO− ions, and thence the hydration of neutral ion pairs. The hydration free energies of neutral pairs computed here are in good agreement with experimental results, whereas the calculated absolute hydration free energies and the excess chemical potentials deviate consistently from some recently tabulated hydration free energies based on ion–water cluster data. We show how the single-ion absolute hydration free energies are not separated from the potential of the phase in recent analyses of ion–water cluster data, even in the limit of large cluster sizes. We conclude that naive calculations of ion–water clusters ought to agree with results obtained from experimental studies of ion–water clusters because both values include the contribution, somewhat extraneous to the local environment of the ion, from the potential of the phase.

Relativistic causality and conservation of energy in classical electromagnetic theory

Causality puts certain constraints on the change of the electromagnetic field due to the change in motion of charged particles. Naive calculations of the electromagnetic energy and the work performed by the electromagnetic fields which take these constraints into account might lead to paradoxes involving the apparent nonconservation of energy. A few paradoxes of this type for the simple motion of two charges are presented and resolved in a quantitative way providing deeper insight into various relativistic effects in classical electromagnetic theory.

A generalized biharmonic equation and its applications to hydrodynamic instability

Problems concerning characterization of eigenvalues of some linear and homogenous differential systems by the Pellew and Southwell method of conjugate eigenfunctions in the domain of hydrodynamic instability are discussed and a general mathematical framework described.In this general survey we look back on and rewrite this work almost in exactly the way it evolved out of a few naive looking calculations in hydrodynamic instability. We show in the process the close relationship that exists between mathematical analysis and its applications with due credit to intuition as the main source of mathematical activity

Influence on Smoothness in Penalized Likelihood Regression for Binary Data

Penalized likelihood is a nonparametric regression technique which can be used to estimate a mean function for binary data. We wish to measure the sensitivity of the smoothing parameter to gross changes in the data when the optimal value of the smoothing parameter is selected using generalized cross-validation. Since penalized likelihood curve fitting requires both a grid search to determine the optimal value of the smoothing parameter and iterative solution for each grid point, naive calculations to determine the change in the optimal value of the smoothing parameter when each data value is modified are computationally intensive and time-consuming. We have developed techniques based on mathematical and numerical approximations for measuring sensitivity in penalized likelihood regression with binary data. These techniques have been applied to selected data sets to compute change in the smoothing parameter resulting from changes in individual data values.

Constraints on ultraviolet-stable fixed points in supersymmetric gauge theories

We consider the possibility that some supersymmetric gauge theories which are not asymptotically free can be governed by ultraviolet-stable fixed points. If this scenario can be realized, gaugino masses will exhibit power-law running with scale, providing a possible solution to the supersymmetric flavor problem. While naive perturbative calculations hint at the appearance of ultraviolet-stable fixed points in certain theories, there are strong constraints following from limits on the scaling dimensions of gauge-invariant operators, positivity of central charges, and Cardy's conjectured constraint on the flow of the Euler coefficient in the stress tensor trace anomaly. Also, we prove that if ultraviolet-stable fixed points do exist, they cannot occur in the perturbative regime of a renormalizable model, and that all-orders results in the limit of large numbers of chiral superfields are necessarily inconclusive. However, we argue that the general idea of ultraviolet-stable fixed points in supersymmetric gauge theories is viable, and exhibit models that can satisfy all known constraints.

The Hard Thermal Loops and the Self-consistent Calculation of the Effective Potential11The project supported in part by National Natural Science Foundation of China.

By developing the “tadpole graph method” including the resummation of the hard thermal loops in the tadpole diagrams, a self-consistent method is proposed in the calculation of effective potential. It is shown that the calculated effective potential at finite temperature in the Higgs model is more self-consistent than the naive calculation. The two difficulties encountered in the naive calculations of the effective potential disappear naturally, The calculated results indicate that the symmetry restoration transition is of the first order.

Curved space quantum scalar field theory with accompanying metric fluctuations.

We show that, in the analysis of quantum-field theory in curved space, taking the simultaneously excited metric fluctuations into account is not only quite feasible but also the results can be regarded as more self-consistent. Although the resulting equations become necessarily somewhat involved, certain simplifications occur such that the analysis becomes simpler and even general solutions are available. We present a minimally coupled scalar field theory in a flat Friedmann-Lema\^{\i}tre-Robertson-Walker background metric. By a "proper" choice of gauge fixing, we are able to produce the same results derived from quantum-field theory in curved space neglecting the metric perturbations in exponential and power-law expansion stages, now supported by the background scalar field. We also show that in the large scale the general integral form solution can be derived for an arbitrary scalar field potential (this is generally possible in any other gauge analysis). The uniform-curvature gauge allows the simplest analysis. Based on these results we are able to provide a firm basis for previous naive calculations of density perturbations generated during inflation. The quantum generation process is treated with full account of the accompanying metric fluctuations, and the analysis is simplified in a coherent manner.

Information on the QCD phase transition and the vacuum permeability from the interquark potential

A method for the calculation of the interquark potential resulting from the instanton induced phase transition in the QCD vacuum is described and it is shown that good agreement is obtained with successful phenomenological potentials for parameter values close to those expected from naive instanton calculations.