On Some Properties of a Heterogeneous Transfer Function Involving Symmetric Saturated Linear (SATLINS) with Hyperbolic Tangent (TANH) Transfer Functions

For transfer functions to map the input layer of the statistical neural network model to the output layer perfectly, they must lie within bounds that characterize probability distributions. The heterogeneous transfer function, SATLINS_TANH, is established as a Probability Distribution Function (p.d.f), and its mean and variance are shown

On the Level of Precision of a Heterogeneous Transfer Function in a Statistical Neural Network Model

A heterogeneous function of the statistical neural network is presented from two transfer functions: symmetric saturated linear and hyperbolic tangent sigmoid. The precision of the derived heterogeneous model over their respective homogeneous forms are established, both at increased sample sizes hidden neurons. Results further show the sensitivity of the heterogeneous model to increase in hidden neurons

JWH-018 and Selective Serotonin Reuptake Inhibitors: Drug-Drug Interactions and Implications on Toxicity

Drug abuse has expanded from more well-known substances, such as cocaine and marijuana, to relatively new novel psychoactive substances. A group of these substances called synthetic cannabinoids have been increasing in usage throughout the 2000\u27s, and these compounds carry significant and varying risks depending on the dose and composition of the synthetic cannabinoid. Patients have been observed having symptoms associated with high doses of synthetic cannabinoids when they take lower doses of the synthetic cannabinoid in addition to their antidepressant medication. In order to test the effects of co-administration of selective serotonin reuptake inhibitors (SSRis) and synthetic cannabinoids, mice were observed in a marble burying assay under the influence of the different drugs. Mice were given either fluoxetine (10-mg/kg), citalopram (20-mg/kg), or JWH-018 (0.1-mg/kg or 0.3-mg/kg) or a combination of the drugs. Mice without being injected with any of the drugs buried 6.375 marbles on average in the twenty-minute test. Mice injected with fluoxetine or citalopram alone buried 4.25 marbles and 4.0 marbles respectively. The JWH-018 doses were chosen to be ineffective so that the marbles buried at 0.1-mg/kg was 6.125 and the 0.3-mg/kg dose resulted in 6.375 marbles buried. Fluoxetine in combination with JWH-018 resulted in 3.0 marbles being buried for the lower dose and 1.875 marbles were buried with the high dose. Citalopram in combination with JWH-018 resulted in 3.625 marbles buried for the lower dose and 2.875 marbles buried for the high dose. When the SSRis were taken with an ineffective dose of JWH-018 a greater than anticipated drug effect occurred, since it occurred in both combinations it points to a pharmacodynamic effect instead of a pharmacokinetic effect

An Adjusted Network Information Criterion for Model Selection in Statistical Neural Network Models

In this paper, we derived and investigated the Adjusted Network Information Criterion (ANIC) criterion, based on Kullback’s symmetric divergence, which has been designed to be an asymptotically unbiased estimator of the expected Kullback-Leibler information of a fitted model. The ANIC improves model selection in more sample sizes than does the NIC

A DERIVED HETEROGENEOUS TRANSFER FUNCTION FROM CONVOLUTION OF SYMMETRIC HARDLIMIT AND HYPERBOLIC TANGENT SIGMOID TRANSFER FUNCTIONS

This study derived a new heterogeneous transfer function of the Statistical Neural Network from a convolution of two transfer functions: the Symmetric Hard Limit and Hyperbolic Tangent Sigmoid, showing their various mathematical forms. The properties of the derived function were examined. Results show that it is a proper probability distribution with distributional properties shown to exist with mean 0, and variance . Numerical illustrations showed that the derived heterogeneous model is more efficient than its homogeneous forms, as indicated from their respective predictive performances. From the foregoing, the use of homogeneous models of the statistical neural networks in solving empirical problems is encouraged, for effective outcomes

Predicting Performance in an Introductory Programming Course by Logging and Analyzing Student Programming Behavior

The high failure rates of many programming courses means there is a need to identify struggling students as early as possible. Prior research has focused upon using a set of tests to assess the use of a student's demographic, psychological and cognitive traits as predictors of performance. But these traits are static in nature, and therefore fail to encapsulate changes in a student's learning progress over the duration of a course. In this paper we present a new approach for predicting a student's performance in a programming course, based upon analyzing directly logged data, describing various aspects of their ordinary programming behavior. An evaluation using data logged from a sample of 45 programming students at our University, showed that our approach was an excellent early predictor of performance, explaining 42.49% of the variance in coursework marks - double the explanatory power when compared to the closest related technique in the literature

No tests required : comparing traditional and dynamic predictors of programming success.

Research over the past fifty years into predictors of programming performance has yielded little improvement in the identification of at-risk students. This is possibly because research to date is based upon using static tests, which fail to reflect changes in a student's learning progress over time. In this paper, the effectiveness of 38 traditional predictors of programming performance are compared to 12 new data-driven predictors, that are based upon analyzing directly logged data, describing the programming behavior of students. Whilst few strong correlations were found between the traditional predictors and performance, an abundance of strong significant correlations based upon programming behavior were found. A model based upon two of these metrics (Watwin score and percentage of lab time spent resolving errors) could explain 56.3% of the variance in coursework results. The implication of this study is that a student's programming behavior is one of the strongest indicators of their performance, and future work should continue to explore such predictors in different teaching contexts

The metabolic demand of external load carriage in golfers: a comparison of a single versus double-strap golf bag

BACKGROUND: A golf bag filled with a set of clubs provides a substantial load. When carried over distance this can increase the demands placed upon the golfer, leading to discomfort, fatigue and injuries. This study aimed to compare the metabolic demands of 2 methods of golf bag carriage. METHODS: A total of 16 healthy male recreational golfers participated in the study. Participants were given an initial familiarization session in which their self-selected walking speed was determined. This was utilized as the treadmill speed for all subsequent trials. The testing protocol consisted of 3 randomized trials of treadmill walking for 5 minutes in each of three conditions: unloaded, single-strap bag and double-strap bag. Equipment consisted of a double-strap golf bag with a standard set of clubs weighing 12.5kg. For all trials oxygen consumption (L·min-1), VO2 (mL·kg·min-1) respiratory minute volume (VE) (L·min-1), and heart rate (HR) were measured. RESULTS: Results showed that the double-strap bag required significantly less oxygen consumption (1.19±0.19 vs. 1.31±0.16 L·min-1, P<0.01) relative oxygen consumption (14.49±2.06 vs. 15.93±2.25 mL·kg·min-1, P<0.01), reduced respiratory minute volume (29.95±4.19 vs. 32.47±4.26 L·min-1, P<0.05), and lower heart rates (100.14±11.05 vs. 106.96±9.33 BPM, P<0.001) than the single-strap bag. Both methods of carriage showed significantly greater metabolic demands than the unloaded condition (P<0.05). CONCLUSIONS: The decreased metabolic cost of carrying a double-strap golf bag may facilitate a reduction in fatigue and reduced mechanical stress. Golf bag transportation must therefore be recognized as a factor in reducing the risk of injury and improving playing performance

Transmission dynamics of Ebola Virus Disease with vaccine, condom use, quarantine, isolation and treatment drug

Background: Ebola Virus Disease (EVD) has brought the human population, especially the West African race, great losses in so many areas such as economic productivity and human life. During the 2014 Ebola Virus outbreak, the disease devastated and threatened the whole world. EVD symptoms (fever, diarrhea, vomiting, etc) may appear anywhere between two to twenty-one days after infection. Those that recovered from the disease return to being susceptible again and can transmit the virus through semen as research has shown the virus presence in semen even after recovery.Material and Methods: Mathematical modeling method with the combination of vaccine, condom use, quarantine, isolation and treatment drug together as control measures in a population consisting of human and animals. A model system of non-linear differential equations for the control of EVD was formulated and the model effective reproduction number (RE ) was obtained using the next generation matrix method and used in the stability analysis of the model. Center manifold theorem was used in the bifurcation analysis of the model.Results: The result shows that the stability analysis of the model shows that the EVD – Free Equilibrium is locally asymptotically stable when and RE&lt;1EVD - Endemic Equilibrium is locally asymptotically stable when RE&gt;1 . The model was shown to exhibit a forward bifurcation.Conclusions: Numerical simulations and analysis of the model show that EVD could be effectively controlled and eradicated within a short period of time when vaccine, condom use, quarantine, isolation and treatment drug control measures are implemented together