Missing Observations in Split-Plot Central Composite Designs: The Loss in Relative A-, G-, and V- Efficiency

The trace (A), maximum average prediction variance (G), and integrated average prediction variance (V) criteria are experimental design evaluation criteria, which are based on precision of estimates of parameters and responses. Central Composite Designs(CCD) conducted within a split-plot structure (split-plot CCDs) consists of factorial (), whole-plot axial (), subplot axial (), and center () points, each of which play different role in model estimation. This work studies relative A-, G- and V-efficiency losses due to missing pairs of observations in split-plot CCDs under different ratios (d) of whole-plot and sub-plot error variances. Three candidate designs of different sizes were considered and for each of the criteria, relative efficiency functions were formulated and used to investigate the efficiency of each of the designs when some observations were missing relative to the full one. Maximum A-efficiency losses of 19.1, 10.6, and 15.7% were observed at = 0.5, due to missing pairs , , and , respectively, indicating a negative effect on the precision of estimates of model parameters of these designs. However, missing observations of the pairs- , , , , and did not exhibit any negative effect on these designs' relative A-efficiency. Maximum G- and Vefficiency losses of 10.1,16.1,0.1% and 0.1, 1.1, 0.2%, were observed, respectively, at = 0.5, when the pairs- , , , were missing, indicating a significant increase in the designs' maximum and average variances of prediction. In all, the efficiency losses become insignificant as d increases. Thus, the study has identified the positive impact of correlated observations on efficiency of experimental designs. Keywords: Missing Observations, Efficiency Loss, Prediction varianc

Modeling the Effect of Bank Specific Factors on Financial Performance of Commercial Banks in Nigeria: Panel Data Regression Approach

Periodic checking and evaluation of financial performance of the banking sector is a way of sustaining the development of a nation’s economy. The key indicators of the banks’ financial performance are their return on assets (ROA) and return on equity (ROE). A bank’s financial performance is affected by some specific factors like capital adequacy ratio (CAR), credit risk (CRISK), management quality, liquidity ratio (LIQ.RAT.) and bank size. This work first compares average financial performance of some sampled commercial banks in Nigeria (UBA, GTB, ZENITH, FIRST, and ACCESS banks) based on the key indicators and the bank specific factors. It then models the effect of these factors on the overall financial performance of the sampled banks using panel data regression approach. The results showed that the GTB had the highest average ROA, ROE and CAR throughout the period under review while Zenith bank was the best in terms of credit risk, management quality and liquidity ratio. The fitted ROA model accounted for 83% of the total variability in the data and revealed that CAR, CRISK, and LIQ.RAT were significant at both 1% and 5% levels while the ROE model accounted for 69% and revealed that CRISK and LIQ.RAT were significant. Keywords: Financial Performance, Commercial Banks, Evaluation, Panel Data, Econom

Split-Plot Central Composite Designs Robust to a Pair of Missing Observations

This study constructs robust split-plot central composite designs against missing pairs of observations. Split-plot central composite designs (CCD) consist of factorial (f), whole-plot axial (α), subplot axial (β), and center (c) points. A loss function in terms of determinant (D) criterion was formulated based on two different configurations of the factorial and axial parts; losses due to missing pairs of observations of these different categories of points were investigated. Robust split-plot central composite designs against missing pairs of observations were then developed under each of the two configurations. It was observed that the losses, Lff, Lββ, and Lfβ, due respectively, to missing pairs of observations of the factorial, subplot axial, and, factorial and subplot axial points, were higher than the losses due to missing pairs of observations of the whole-plot axial and center points given by Lαα and Lcc respectively. Thus the factorial (f) and the subplot axial (β) points were found to be the most influential points in these designs while the whole-plot axial (α) and the center (c) points were less influential. This work has therefore identified and properly classified the losses due to missing design points in the split-plot CCD portions. In this way, the practitioner can avoid the experimental points having less influence from the full CCD experiments and this could lead to a possible increase in design efficiency.Keywords: Robustness, Split-plot Central Composite Designs, Missing observations, loss functio

Appraisal of ANN and ANFIS for Predicting Vertical Total Electron Content (VTEC) in the Ionosphere for GPS Observations

Positional accuracy in the usage of GPS receiver is one of the major challenges in GPS observations. The propagation of the GPS signals are interfered by free electrons which are the massive particles in the ionosphere region and results in delays in the transmission of signals to the Earth. Therefore, the total electron content is a key parameter in mitigating ionospheric effects on GPS receivers. Many researchers have therefore proposed various models and methods for predicting the total electron content along the signal path. This paper focuses on the use of two different models for predicting the Vertical Total Electron Content (VTEC). Artificial Neural Network (ANN) and Adaptive Neuro Fuzzy Inference System (ANFIS) algorithms have been developed for the prediction of VTEC in the ionosphere.  The developed ANN and ANFIS model gave Root Mean Square Error (RMSE) of 1.953 and 1.190 respectively.  From the results it can be stated that the ANFIS is more suitable tool for the prediction of VTEC. Keywords: Artificial Neural Network, Adaptive Neuro Fuzzy Inference System, Vertical Total Electro

Analysis of Methods for Ellipsoidal Height Estimation – The Case of a Local Geodetic Reference Network

Ghana’s local geodetic reference network is based on the War Office 1926 ellipsoid with data in latitude, longitude and orthometric height  without the existence of ellipsoidal height. This situation makes it difficult to apply the standard forward transformation equation for direct conversion of curvilinear geodetic coordinates to its associated cartesian coordinates (X, Y, Z) in the Ghana local geodetic reference network. In order to overcome such a challenge, researchers resort to various techniques to obtain the ellipsoidal height for a local geodetic network. Therefore, this paper evaluates, compares, and discusses different methods for estimating ellipsoidal height for a local geodetic network. The investigated methods are the Abridged Molodensky transformation model, Earth Gravitational Model, and the Orthometric Height approach. To evaluate these methods, their estimated local ellipsoidal height values were implemented in the seven-parameter similarity transformation model of Bursa-Wolf. The performance of each of the methods was assessed based on statistical indicators of Mean Square Error (MSE), Mean Absolute Error (MAE), Horizontal Position Error (HE) and Standard Deviation (SD). The statistical findings revealed that, the Abridged Molodensky model produced more reliable transformation results compared with the other methods. It can be concluded that for Ghana’s local geodetic network, the most practicable method for estimating ellipsoidal height is the Abridged Molodensky transformation model.  Keywords: Abridged Molodensky Model, Earth Gravitational Model, Orthometric Height, Geodetic Networ

Urine Burn Dermatitis in a Two Year-Old Sudanese Ewe

Nigerian Veterinary Journal, Vol. 32(3): 2011; 238 - 24

Effect of neem fertilizer rates and weed control methods on the growth and yield of soybeans (Glycine max (L.) merrill) in north Central Nigeria

Two field experiments were conducted at the Research Farm of the Ibrahim Badamasi Babangida University, Lapai, Niger State during the 2018 and 2019 rainy seasons to determine the effect of neem fertilizer rates and weed control methods on the growth and yields of soybeans. The experimental treatments were made up of four neem fertilizer rates (0, 50, 100 and 150 kg ha-1) and six weed control methods (pendimethalin at 1.5 kg a.i ha-1 followed by one hoe weeding, pendimethalin at 2.0 kg a.i. ha-1 followed by diuron at 1.5 kg a.i ha-1, weeding once at 3 WAS, weeding twice at 3 and 6 WAS, weed free and weedy check. The experiment was a 3 × 3 factorial experiment laid out in a Randomize complete block design replicated three times. TGX 1448 – 2E variety of soybean was used for the study. Result showed that weed control efficiency was better with the use of 150 kg ha-1 of neem fertilizer, while decrease in weed dry matter was obtained at 50 kg ha-1. Increase in number of leaves and leaf area were encouraged with 150 kg ha-1 of neem fertilizer. Weed free treatments recorded the highest grain yield and 100 seed weight of soybean. Pendimethalin at 1.5 or 2.0 kg a.i ha-1 supplemented with one hoe weeding or diuron at 1.5 kg a.i ha-1 respectively can be an alternative for better control of weeds to obtain greater yield of soybean in the study area

Split-plot Central Composite Experimental Design Method for Optimization of Cake Height to Achieve desired Texture

In many industrial experimental situations, the levels of certain factors under investigation are much harder to change than others due to time and/or cost constraints. An appropriate approach to such situations is to restrict the randomization of the hard-to-change (HTC) factors, which leads to a split-plot structure. This work designs and conducts a split-plot central composite experiment for optimizing cake height using oven temperature(Factor A) as the HTC factor, amount of flour (B), baking powder (C), and amount of milk (D) as the easy-to-change (ETC) factors. A second-order split-plot central composite design (CCD) model was fit to the generated data and analyzed using generalized least squares (GLS). A stationary point, which gives optimum cake height, was then determined. The results show that main effects of oven temperature, flour, baking powder, and milk were highly significant on the cake height . Their quadratic effects were also significant except that of the flour. The flower/baking powder interaction effect was significant. The fitted model  accounted for about 95% of the total variability in the cake height data. The observed optimum cake height was ̂ at a stationary point: A . This study has established the potentials of response surface experiments in optimizing products in food industries. Keywords: Experiment, split-plot CCD, Cake height, Design, Stationary point.&nbsp

Binary logistic regression methods for modeling broncho-pneumonia status in infants from tertiary health institutions in north central Nigeria

Acute respiratory tract infections, predominantly bronchopneumonia, are one of the leading causes of infant deaths in developing countries and around the world. This work models the effects of the significant risk factors on infants’ bronchopneumonia status and also fits some reduced models and determines the best model with minimum number of parameters. The data for this study consist of a random sample of 433 births to women seen in the obstetrics clinic of two sampled tertiary health institutions in north-central Nigeria. These include University Teaching Hospital (UTH) Abuja, and Federal Medical Center (FMC) Keffi, Nasarawa State. Binary logistic regression was used to identify and model the effects of the various risk factors while stepwise regression technique was used to fit some reduced logistic regression models. Then the best fitting model with minimum number of parameters was identified using likelihood ratio statistic. It was observed that baby’s weight at birth, baby’s weight four weeks since birth, and mother’s occupation have significant effects on infant’s bronchopneumonia status. Additionally, among the four fitted reduced models, model4 is the best predictor of infants’ bronchopneumonia status, followed by model3 and then model2. Therefore, community service like home visiting for health education, supplementation of vitamin A, etc., would be an advantage if provided for teenaged pregnant women as it would, in turn, reduce incidence of low birth weight and thereby reduce bronchopneumonia infection among these children.Keywords: Bronchopneumonia, Multiple Logistic Regression Model, Fitness, likelihood ratio tes

Determination of thermal sensation on transient conditions

The objective of this study is to investigate the difference in thermal environment and human response between air-conditioned closed space and a semi-open space. The thermal response of the subjects in transitional space as they experienced step changes in temperature when moving from outdoor environment to indoor air-conditioned and back to outdoor was examined. The thermal sensation was investigated using a questionnaire and a comprehensive package of micro-metrological instruments. Experiment was conducted to examine the immediate thermal sensation of the subjects when walking from one set of thermal condition to another. Subjects were exposed to three different environmental conditions for 5 to 20 minutes (semi-outdoor, indoor and semi-outdoor). Skin temperature, subjective thermal sensation and comfort were recorded throughout the experiment. Results showed that there is variation in skin temperature as observed in sensation scores between the sequences. The predicted mean vote overshoot all through the sequence as the subjects move from one location to another. Since PMV is widely used as a tool to predict thermal comfort in steady-state environment, it may not be applied to predict thermal sensation in a transient environment. The result of this study can help to improve the PMV model to be applied in a transient environment. This outcome would be suitable in circumstances such as movement in a lobby which is semi-outdoor to predict thermal sensation