Hematocrit and Slip Velocity Influence on Third Grade Blood Flow and Heat Transfer through a Stenosed Artery

A theoretical investigation concerning hematocrit and slip velocity influence on the flow of blood and heat transfer by taking into account the externally applied magnetic field has been carried out. The mathematical models considered in this work treated blood as a non-Newtonian fluid obeying the third grade fluid model. A suitable geometry of the stenosis is taken into account. Galerkin weighted residual and Newton Raphson methods are used to solve the equations that govern the flow of blood and heat transfer. Analytical expression for the velocity profile, temperature profile, volume flow rate, wall shear stress and resistance to flow were obtained. Graphical representation of results shows that the flow velocity, volumetric flow rate and shear stress increase while resistance to flow and heat transfer rate decrease when the slip velocity increases. Also, flow velocity and volume flow rate decrease while shear stress, heat transfer rate, and resistance to flow increase when the hematocrit parameter increases. Finally, increases in magnetic field parameter lead to decrease in flow velocity, flow rate and shear stress but increase the flow resistance.

Spatial and Temporal Variation in Water Quality of River Benue, Nigeria

The study investigates the spatial and temporal variation in water quality parameters at ten different locations along River Benue for twelve consecutive months. In order to explore the spatial variation among different stations and seasonal changes, multivariate analysis of variance (MANOVA) was used to group these on the basis of spatial similarities. MANOVA on season and station shows that there is no significant difference between the stations investigated while there is for the seasons. This could be viewed as a resulting from the narrow spatial sampling interval (12 km at 0.7% total length of River Benue). However, discriminate analysis identified all the parameters to discriminate between the three seasons with 99.2% correct assignations. Two discriminate functions were found and the total variance cumulative was 100% between seasons. The first function explained 64.8% of the total variance between the seasons while the second function explained 35.2%. Total solids (TS) were the highest contributor in discriminate functions 1 and 2. Therefore, discriminate function analysis would enable us to predict the likely season a water sample from metropolitan Makurdi was collected given the values of the water quality parameters. It also enables us to conclude that all the parameters were responsible for significant seasonal variations in River Benue water quality.

A Well-Built Hybrid Recommender System for Agricultural Products in Benue State of Nigeria

Benue State of Nigeria is tagged the Food Basket of the country due to its heavy production of many classes of food. Situated in the North Central Geo-Political area of the country, its food production ranges from root crops, fruits to cereals. Recommender systems (RSs) allow users to access products of interest, given a plethora of interest on the Internet. Recommendation techniques are content-based and collaborative filtering. Recommender systems based on collaborative filtering outshines content-based systems in the quality of their recommendations, but suffers from the cold start problem, i.e., not being able to recommend items that have few or no ratings. On the other hand, content-based recommender systems are able to recommend both old and new items but with low recommendation quality in relation to the user’s preference. This work combines collaborative filtering and content based recommendation into one system and presents experimental results obtained from a web and mobile application used in the simulation. The work solves the problem of serendipity associated with content based (RS) as well as the problem of ramp-up associated with collaborative filtering. The results indicate that the quality of recommendation is promising and is competitive with collaborative technique recommending items that have been seen before and also effective at recommending cold-start products.

A Glorious Literature on Linear Goal Programming Algorithms

In the last several years, there has been a marked improvement in the development of new algorithms for solving Linear Goal programming (LGP). This paper presents a survey of current methods for LGP.

Beta-Exponentiated Ishita Distribution and Its Applications

This article develops a beta-exponentiated Ishita distribution that extends the exponentiated Ishita distribution. Expansions for the cumulative distribution and probability density functions are given. Various properties of the new distribution such as hazard function, moments, cumulants, skewness, kurtosis, mean deviations, Bonferroni and Lorenz curves, Rényi and Tsallis entropies, and stress-strength reliability are discussed. Moment generating function and characteristic function of the new model were derived. Distribution and the moment of order statistic have been derived. The method of maximum likelihood was used for estimation of parameters. The new model is quite flexible in analysing positively skewed data. Two real datasets are used to demonstrate the flexibility of the new distribution.

A Modified Replacement Model for Items That Fail Suddenly with Variable Replacement Costs

Several researches have been done to provide better alternative to the existing replacement models, but the research works did not adequately address the replacement problem for items that fail suddenly. Hence, a modified replacement model for items that fail suddenly has been proposed using the knowledge of probability distribution of failure times as well as that of variable replacement cost. The modified cost functions for implementing both individual and group replacements were derived. The modified cost functions were minimized using the principle of classical optimization in order to find the age at which replacement of items would be appropriate. Conditions under which the individual and group replacement policies should be adopted were derived. Two real data sets on failure time of LED bulbs and their replacement costs were used to validate the theoretical claims of this work. In essence, goodness-of-fit test was used to select appropriate probability distribution of failure times as well as that of replacement costs for data sets I and II respectively. The goodness-of-fit results showed that failure times of LED bulbs follow the Smallest Extreme Value and Laplace distributions for data sets I and II respectively. Similarly, it was observed that individual replacement cost followed the two-parameter Gamma and Largest Extreme Value distributions for data sets I and II respectively. Further, the group replacement cost was found to follow the log-normal and two-parameter Weibull distributions for data sets I and II respectively. Based on the empirical study, we observed that individual replacement policy is better than group replacement policy in terms of cost minimization for both existing model and the proposed model. In view of the results, the proposed replacement policy was recommended over the existing one because it yielded lower replacement costs than the existing replacement model.

A Review of Activity Time Distributions in Risk Analysis

Project Evaluation and Review Technique (PERT) alongside recent modifications is a popular and useful tool in project risk analysis. Over the past seven decades, there have been some modifications in PERT owing to the shift from beta distributed activity times to other activity time distributions. This paper presents a review of activity time distributions in risk analysis as found in literature up to date.

Analysis of Pulsatile Magnetohydrodynamic (MHD) Third Grade Blood Flow in a Stenosed Artery

In this research, we modeled MHD third grade blood flow in a stenosed artery. The blood viscosity and the density have been modeled into the shear thinning/thickening parameters, the most important rheological properties of blood. We used regular perturbation method and obtained the flow characteristics such as the flow velocity, the volume flow rate, the shear stress and the resistance to the flow considering a single layered stenosed artery. The results however showed that there is significant increase in volume flow rate and the velocity with increase in the magnetic field intensity H and the shear thinning Λ and reduces with increase in the shear thickening Ω.

A Neural Based Experimental Fire-Outbreak Detection System for Urban Centres

Incessant fire-outbreak in urban settlements has remained intractable especially in developing countries like Nigeria. This is often characterized by grave socio-economic aftermath effects. Urban fire outbreak in Nigerian cities has been on increase in recent times. The major problem faced by fire fighters in Nigerian urban centres is that there are no mechanisms to detect fire outbreaks early enough to save lives and properties. They often rely on calls made by neighbours or occupants when an outbreak occurs and this accounts for the delay in fighting fire outbreaks. This work uses Artificial Neural Networks (ANN) with backpropagation method to detect the occurrence of urban fires. The method uses smoke density, room temperature and cooking gas concentration as inputs. The work was implemented using Java programming language and results showed that it detected the occurrence of urban fires with reasonable accuracy. The work is recommended for use to minimize the effect of urban fire outbreak.