In many areas of research/ production, a lot of factors are combined to obtain a desired product. To be able to analyze which factors (or combinations of factors and at what level) are significant, the experiment has to be replicated. For economic or practical reasons, it may not be feasible to perform the experiment more than once therefore unreplicated factorial designs are often employed. This is especially true in the field of Medicine, Pharmacy and Industrial production units. The traditional method of analysis of variance (ANOVA) cannot be employed in unreplicated factorial designs, therefore many methods have been proposed in literature. In this paper, a new method of analyzing unreplicated factorial designs is proposed and was compared with some of the existing methods. The four existing methods considered were: Lenth, Berk and Picard, Juan and Pena, and Dong. The comparison was performed using Monte Carlo simulation method. The criteria used in evaluating the performances of the methods are Power and Individual Error Rate (IER). Using these criteria of evaluation, the results showed that on overall performance, Dong method is the best among the four existing methods considered and was closely followed by Berk and Picard, Lenth, then Juan and Pena methods in that order. It was also found that not only is the proposed method simpler to compute, it competed favourably with Dong and even performed better than all the others when IER is used for assessment.

Experiment, Factorial, Replication, Significant effects, Power, Individual Error Rate (IER).

Data compression is the process of reducing the size of data. Due to the improvement of Information Technology, there are more data that are being generated nowadays that are transferred from one source to another. This data required higher size and bandwidth to be transferred between two parties. Hence, how to reduce the size of data before transferring from one medium to another has been an important issue. This paper proposed an enhanced method to compress image data file. In this paper, we integrate Chinese Remainder Theorem (CRT) into the Huffman compression algorithm to enhance the speed of compression as against the Traditional Huffman Compression (THC). The experimental analysis was performed in matrix laboratory environment (2015). The experimental results revealed that there is significant reduction in size of image, compression time minimization and data quality retention of original image. The shortcomings of THC are blocky appearance and poor quality reconstructed image after decompressing operation is overcome in our enhanced method with CRT.

Huffman Algorithm, Chinese Remainder Theorem (CRT), compression, Image File.

Math education in the 21st century is facing new real-world problems, nurturing creative thinking skills and effective ways of learning. In an effort to innovate teaching and learning methods to prepare for a new generation for the demands of the new era, many educators have discovered the value of metacognition. The article explores metacognition in the REACT teaching strategy (Relating, Experiencing, Applying, Cooperating, and Transferring) in order to help students solve practical problems based on context, from which, to acquire knowledge.

Teaching strategy, metacognition, REACT Strategy.

The Main Objective of Transport Location Inference Drawing Using Global Positioning System is to help the passengers to track the location of their respective vehicle. Nowadays, it became difficult for passengers to know the exact location of the vehicle for which they are waiting. This application helps the passenger in tracking the vehicle and reach to the boarding point on time. Passengers can greatly use this application since Android mobiles have become common and affordable to all. This will also enhance security since the movement of the vehicles is always available. It is a real-time system as the current location of the bus is updated every moment in the form of latitude and longitude which is received by the passengers through their application on Google maps.

Transport, GPS, User, Administrator, Driver/Rider, Location, Tracking and Android.

This paper examine certain behavior of some permutation statistics on the pattern ω_i defined as: ω_i=(1 (1+i)^modp (1+2i)^modp (1+3i)^modp ...(1+((p−1)i)^modp) for i=1,2,...,p-1. We investigate the permutation statistics that are equidistributed on ω_i ∈ G_p. This to a larger extent helped in identifying ω_i as an Eulerian distribution. The graph permutation of ω_i and the graph of 132-avoiding pattern of ω_i were also studied.

Permutation Pattern, Permutation Statistics and Graph.

The use of mobile technology within the entertainment industry is growing at a fast rate worldwide. In Swaziland, the lack of real time informative platforms has led to several property damages due to an angry audience that did not get all the information or updates about an event on time. This paper presents a system that connects event organizers, artists, and fans. It has been noted that most event mobile applications tend to focus on either uploading information on events updates or information on artists. This system integrates these two ideas into one package in the sense that users have event updates and also get updates on a specific artist all in the same system. Most of the existing applications do not have a platform where users get to comment about a past event that was uploaded in a system.

Mobile apps, event organizers, artists, fans and entertainment.

There are a number of skin diseases like Acne, Eczema, Hives, impetigo, Melanoma, Moles etc. Acne is a disease that affects the skin's oil glands. The small holes in the skin (pores) connect to oil glands under the skin. These glands make a substance called sebum. Eczema, also known as atopic dermatitis, is a long-term skin disease. The most common symptoms are dry and itchy skin, rashes on the face. Hives causes red and sometimes itchy bumps on the skin. Likewise, different skin diseases have different symptoms. Sometimes, it is difficult for the dermatologist to diagnose the skin disease by looking at the disease. This paper aims at spotting the skin disorder by using the template matching algorithm.

Skin disorder, disease, itchy, dry, analysis, diagnose, image processing and disease type.

Mobile Agents (MA) are objects that migrate through the nodes of heterogenous networks to perform intelligent path finding tasks. Prioritizing the metaheuristics algorithms (PSO, ACO, GA and SA) with the best performance in terms of cost value and computational time efficiency for mobile agents path planning has been a major challenge. The performance of these selected meteheuristic algorithms was evaluated. Prototypes of mobile agents were introduced into two dimensional (2-D) workspace of adhoc network consisting of 16 nodes. The PSO, ACO, GA and SA were introduced into the mobile workspace for path planning and encoding. The corresponding path plans from PSO, ACO, GA and SA were later used for finding path and implemented in MATLAB environment. The performance of the metaheuristic techniques was evaluated using Computational Time (CT), Cost Value (CV), Program Effort (PE) and Program Size (PS).

Metaheuristic Algorithms, Mobile Agents, Path Planning, Halstead Complexity Metrics.

The efficiency with which searching is carried out often has significant impact on the overall efficiency of a program. Some of the factors affecting the performance of informed tree based or heuristic search algorithms include high exponential execution time to search, drastic memory or storage usage and number of nodes visited. However, prioritizing each of these factors based on their influence has been a major challenge. Therefore, this research prioritized computational time, memory usage and number of nodes visited based on their influence using factor analysis by principal component.

Heuristic algorithms, Factor analysis, Principal component, computational time, memory usage and number of nodes visited.

Cassava (Manihot esculenta Crantz) like any other crops required high soil nutrients content for quality and quantity yield. When the crop is grown on the land for a number of years in succession or in rotation, the stored nutrients in the soil will be reduced and must therefore be replenished by means of fertilization. This depletion of nutrients is aggravated when a high-yielding cassava variety is planted. Hence, this study investigates to know if NPK fertilizers and genotype have effect on the yield of Cassava, examines at what proportion the trio of Nitrogen, Phosphorus and Potassium are to be applied and which genotype is the best and what would be the optimum yield when NPK is applied correctly to the best genotype. A Split – plot design was adopted in the data analysis. Further test was carried out using LSD, Tukey, Scheffe and Bonferroni to detect which of the levels of NPK fertilizer and Genotype have significance effect on the yield. Multiple regression model was obtained to investigate at what proportion the trio of Nitrogen, Phosphorus and Potassium are to be applied, Response surface methodology was carried out to obtain the optimum yield of Cassava. The result of the Analysis of Variance (ANOVA) carried out showed that NPK Fertilizer and Genotype contribute significantly to the yield of Cassava. A further analysis on the Mean Separation of the Fertilizers at various levels of application and different Genotype shows that fertilizer when applied at N0P50K150 are more significant than any other levels, Genotype B is the best and the best variety is C. Thus, the multiple regression model for Cassava was obtain as Yield=131.5805+4.6462B–4.6462G+4.5803F–0.2127B*G– 0.0179 B*F+0.1140*G*F. Hence, the fixed regression model showed that optimum yield of 181.902 tone / hectare is achievable if NPK fertilizers are applied appropriately at the recommended rate.

Split-plot Designs, Multiple Regression, Surface Response Methodology, Cassava Genotype and Cassava Varieties.

In this study a ratio type estimator of finite population mean has been proposed under simple random sampling without replacement. The properties of the proposed estimator (Bias and Mean Square Error) have been obtained up to first order of approximation using Taylor’s Series Expansion and the condition for its efficiency over some existing estimators have been established. The minimum value of the mean square error of the proposed estimator has also been derived. The efficiency of proposed estimator based on optimal value of the constant, exhibit significant improvement over the existing estimators considered in the study. Empirical studies were conducted with natural populations to demonstrate the performance of the proposed estimator comparing with some existing estimators. The results of the empirical study show that the proposed estimator performs better than the existing estimators.

Auxiliary Variable, Efficiency, Mean Square Error.

Assessment of the view of senior school students on HIV/AIDS was carried out in Offa Local Government Area of Kwara State, Nigeria with the aim of investigating the general views of senior school students on HIV/AIDS. Random sampling technique was employed to select 10 schools comprising both public and private schools while purposive method was used to sample 300 biology students across the selected schools. Sharing of blade, needle or any sharp object with another person had higher risk of contracting HIV account for 89.3% of the respondents, followed by casual sex intercourse with an infected person and prostitutes. It is therefore recommended that HIV/AIDS and sex education should be incorporated into the Biology curriculum of senior secondary school students in Nigeria. Also, more emphasis should be made on abstaining from early sexual activities and parents should be encouraged to talk about sex values to their children.

Private and Public Schools, Student, Biology Subject, Sex Education, Assessment.

Multimodal biometrics has attracted lot of attention in recent days as it provides more reliable scheme for person verification. Multimodal biometrics includes the fusion of information from different biometric modalities. This research work presents a novel method for access control system using ear and tongue images. PCA was employed for feature extraction of ear and tongue images and SOFM was used for training and testing of the system. The proposed method is evaluated using 5000 ear images and tongue images. The images were collected using a digital camera and were fused at the feature extraction level. The fusion results of ear and tongue images showed an improved performance and a huge step closer for user access control.

Multimodal, PCA, SOFM, Fusion, Digital Camera.

Tuberculosis has persisted over the years as a significant contributor to mortality and morbidity counts globally and in particular, Nigeria. This study formulated a continuous-time Markov process model for TB dynamics with the introduction of vaccination impact in the susceptible and exposed classes. Using the Gillespie’s algorithm, we obtained stochastic realizations of the disease behavior using the Kolmogorov equations. Sensitivity analysis on impact of key parameters showed that intervention effort at 50% - 85% effectively reduced TB incidence despite reinfection of recovered individuals.

Continuous-Time Markov Chain, exogenous re-infection, Kolmogorov forward equations, Stochastic Simulation, Tuberculosis, Vaccination.

The focus of this study was to examine the effect of family planning based on the methods of contraceptives on women life span (female life expectancy), using the secondary data collected from the University College Hospital (UCH), Ibadan, Lagos Bureau of Statistics (LBS) and World Bank Statistical database. Analytically, regression model was employed in this study. The data, being a time series data was tested for stationarity using the augmented Dickey- Fuller test and the test indicates that the data were stationary. The results obtained indicate that the method of contraceptives and age are statistically significant for predicting women life span. The coefficient of determination in the regression output also revealed that 93.37% (0.9337) of the total variation in life expectancy was accounted for by the use of contraceptive (injectable, Oral, pills and IUCD) and age with other variables in the expectancy. This study concludes that that the independent variables explain the dependent variable substantially and recommends the need to provide aggressively family planning education, so that people can understand the use, cope with it, take control and develop survival skills. The analyses were done in Minitab and E-views statistical packages to estimate the parameters of the model.

Family planning, Investigation, Regression approach, Women lifespan.

Surface Electromyography (sEMG) signals have been found to be useful in developing methods of recognizing hand gestures using digital signal processing devices or ensemble approaches. In building hand gesture recognition models, it is essential to avoid or reduce computational complications which may result in complex circuit connections while implementing the model. As such, simple but efficient approaches in achieving the desired results are required. A explicable model for hand gesture recognition, using Flexible Neural Trees (FNTs) and sEMG signals is presented in this paper. sEMG is an approach of detecting and documenting the electrical impulses of the muscles, from the surface of the skin. The feed forward Neural Network approach is first used in generating the FNT model before improving it, using predefined simple instruction sets. The FNT model helped to avoid complex computations while building the model and provided a high recognition rate. The experimental outcomes obtained from the developed model shows that the model is capable of classifying six different hand gestures at an accuracy of 92.46%.

Flexible Neural Trees (FNTs); Surface Electromyography (sEMG); Artificial Neural Networks (ANN); Probabilistic Incremental Program Evolution (PIPE); Pattern Recognition.

This study evaluated the effect of atmospheric condition on radio network. Response Surface Methodology was used to develop a signal model in terms of atmospheric condition, analyse and optimize the effect of atmospheric temperature, pressure and relative humidity on signal of a WE-FM radio station based in Abuja. The result shows that atmospheric parameters such as temperature, pressure and relative humidity have inverse relationship with radio signal. The analysis of variance for the model formulated reveals that the atmospheric parameters have significant effect on signal strength. Also, the R – Squared value obtained implies that atmospheric condition have variability of 98.30% on the signal strength. The optimum signal strength of 54.0851 dBuV was obtained with the atmospheric condition of temperature 26.800C, pressure, 24.43inHg, and relative humidity of 78%. The model predicts signal strength with the accuracy of 84.71%. Hence, the approach is efficient for minimizing signal strength degradation in radio network.

Signal strength, Atmospheric condition, WE-FM Station, Frequency, Communication network.

This paper proposes a modified family of ratio estimator of population mean using information on auxiliary attribute and the estimation of population mean in double sampling in ratio form. The proposed modified ratio estimator is a family of estimator which results to different estimators at different value of alpha. For the proposed estimator, when α = 0,0.5 and 1, the estimators of Naik, Gupta, Nirmala Sawan and Sample mean were recovered respectively. When the auxiliary attribute is a variable, the estimator result to that of Subhash et al. When α=0 and the auxiliary attribute is a variable, it results to conventional double sampling. The expression for the Bias, and Mean Square Error of the proposed modified estimator were obtained up to the first order of approximation. An efficiency comparison of both the theoretical and empirical were carried out with some related existing estimators in double sampling. It has been established that the proposed modified ratio estimator is more efficient when compared with the existing ones at optimum value of alpha.

Ratio estimator, bias, mean square error and double sampling.

In addition to traditional teaching methods, project-based teaching method has been introduced to catch up with the modern trend in education in the world towards improving students' self-learning capacity. By understanding the principles of project-based teaching teachers will have more opportunities to promote the self-learning of students, thereby making teaching activities more plentiful and practical. Therefore, in this research I aim to enhance the capacity of Mathematics self-studying of high school students through learning projects. This research was done through studying documents related to capacity and Mathematics self-study ability. In addition, in order to evaluate the results of mathematics self-study capacity of high school students in Vietnam I and the teachers involved in the project designed the assessment tool set including self-studying ladder levels, and a self-assessment note. Fourteen 10-grade students were randomly selected to participate in the project. Research results: The learning project has improved the efficiency, confidence and interest of students in solving practical problems, nurturing creative talents. Students increase their self-study ability. In addition, this study is the basis for teachers, educational researchers and curriculum developers to implement a constructive approach in enabling students to understand the relationship between theory and practice, then improving students' self-studying ability.

Project -based teaching, self-studying ability, solving practical problems.

In this paper, we modified twenty-eight ratio type estimators for estimation of population mean of the study variable earlier suggested by Gupta and Yadav (2017) using product of sample size and population parameter of auxiliary variable. The expressions for the bias and mean square errors of the newly modified ratio type estimators have been obtained up to the first order of approximation. A comparison has been made with the mentioned existing ratio estimators of population mean using the same data set used by Gupta and Yadav for easy justification. The results obtained on the Mean Square Errors shows that the newly modified ratio type estimators perform better vis-à-vis the earlier suggested Gupta and Yadav existing ratio type estimators but the newly modified ratio type Estimator, t^*₂₇, perform better, hence, recommended for usage in Sampling.

Ratio Estimator, Auxiliary information, Sample size, Bias, Mean Squared Error, Efficiency.

The consumer price index (CPI) measure the average change over a time in price of goods and services consumed by people, this study is focus to determine the best smoothing technique, to remove the irregularity in the series and to use the smoothed data to fit the model for future prediction. The data used for this study are monthly data, extracted from the record of CBN via www.cbn .gov.ng. The data spanned from January 1995 to December 2017. The behavioral pattern of the associated time plot exhibits the existence of trend and non-seasonality in the data. In view of this, non-seasonal Exponential Smoothing Techniques were adopted and the Holt’s Smoothing Exponential Technique was proved to be the best techniques to use for this study because, the accuracy measure i.e. MAPE (2.457), MAE (0.9352), MSE (4.5512), are relatively smallest compare with others used smoothing techniques, using the smoothing constant α( 0.933) and β(0.07) The future value of Nigeria CPI for year 2018 was predicted using fitted equation. In view of this study, it was discovered that Nigeria CPI will be gradually increasing over times.

Consumer Price Index, Smoothing Technique, Accuracy Measurement.

Iris recognition is considered as one of the best biometric methods used for human identification and verification; this is because of its unique features that differ from one person to another, and its importance in security. This study proposes a multi-algorithmic feature extraction technique for personal recognition using iris. The proposed framework was implemented on Matlab R2018a. The localization and segmentation techniques are presented using Hough Circular Transform in order to isolate an iris from the whole eye image and for noise detection. The normalization procedure was carried out using Daugman Rubber Sheet Model, while the feature extraction was done using Continuous Wavelet Transform. At the classification stage, Hamming Distance, Nearest Neighbour and Euclidean Distance Classifier was adopted. The system was trained with five hundred iris images while another unregistered one hundred iris image were used for verification of the system. The propose method have the accuracy of 70%, False Acceptance Rate (FAR) of 0.00% and False Rejection Rate of 0.03% with total execution time of approximately 7.00 sec. The present work can be extended by testing more samples of iris images. Since the images in the CASIA database are mainly eyes of Chinese people, the testing could be done among other ethnic groups. It is also recommended that other feature extraction techniques which are capable of handling resolution problem could be used in conjunction with Continuous Wavelet Transform to eradicate resolution problem and to increase the accuracy.

Biometrics, Iris, Feature Extraction, Continuous Wavelet Transform, Classifier.

The increase in growth of communication networks such as internet or intranet over large computer network requires a solution of network routing problem to be addressed in a packet-switched network. In the recent years, researchers have introduced several approaches to solve routing problem in other to maintain continuous network transmission without any loss of packets. Until now a number of studies revealed that the most routing devices get distorted when new nodes are added, shortest path and new direction need to be determined when connections go down in between the network nodes, congestion control and delay factor must be put in mind when finding solution to the problem so as to ensure effective network transmission. This paper applied a natured inspired optimization algorithm called Ant colony optimization (ACO) algorithm to reduce some of the problems encounter during routing process.The experimental results showed the robustness of the enhanced routing system when compared with the existing techniques of routing in a packet-switch network.

Ant Colony Optimizatio, Meta-heuristic Algorithm, Routing, Packet Switched Network.

In Brazil, we are interested in the study of second-order recurrent numerical sequences. Such mathematical content has an enormous potential to provide a differentiated mathematical culture for the math teachers in initial training. However, it becomes important that the teacher in Brazil knows properties beyond the traditional and classic numerical sequences, such as the Fibonacci sequence, Lucas sequence, Pell sequence, Jacobsthal sequence, Narayana sequence, etc. Thus, in the present work, we present a proposal of CAS Maple as technological resources in the study and discovery of new theorems derived from the Mersenne sequence. Throughout the work, we show that the software allows the discovery of theorems from matrix properties derived from the Mersenne sequences and the sequence of Gaussian numbers of Mersenne. The research presented in the paper can stimulate the formation of Mathematics teachers in Brazil.

Mersenne sequence, Gaussian sequence of Mersenne, Theorems, Teacher training, Technology.

In e-commerce, credit card fraud is an evolving challenge. The increase in the number of credit card transactions provides more opportunity for fraudsters to steal credit card numbers and execute fraud. Fraud detection is a continuously evolving discipline to tackle ever changing tactics to commit fraud. Existing techniques of genetic algorithm (GA) and counter propagation neural network (CPNN) have been applied to take credit card fraud detection using different dataset and features. This paper evaluates the performance of GA and CPNN using the same dataset and features. The results show that CPNN outperform GA in terms of accuracy, sensitivity, miss rate, hit rate and prediction time.

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In this paper, the Laplace Homotopy Perturbation Method (LHPM) was utilized to solve some nonlinear partial differential equations. This technique is the mixture of the Laplace transform method and the homotopy perturbation method. Some nonlinear partial differential problems of first and second order were considered which the provide results in terms of transformed variables and the series solution was obtained by applying the inverse properties of the Laplace transform. In this paper, we compared the result obtained with the available Homotopy perturbation and Elzaki transform method solution which was found to be exactly same. The results revealed that the mixture of Laplace transform and Homotopy perturbation method was quite applicable, practically well appropriate for use in such problems.

Laplace transform, Homotopy, Homotopy Perturbation method, nonlinear, partial differential equations.

Efficient speech interface to computer has been drawing the attention of researchers globally because it is more convenient than the traditional methods. The challenge of Speech human computer interaction is a difficult task because human language is complex in nature. Although automatic speech recognition is not a new affair in existing developments of HCI but the showcased facts only provide expected solutions for the two accepted international languages such as English and French . However, very little effort has been made by the scholars in domain of speech processing for African languages like Hausa, thus, the need to extend Hausa speech recognition system in order to include diverse applications based on speech recognition. Hausa as a language is an important indigenous lingua franca in west and central Africa. The speech recognition is a needed model for many applications such as HCI which are very helpful for handicap and aged individuals to live the comfortable life. The study shows MFCC technique for good speech feature extraction in a Hidden Markov Model based recognition approach with 97% recognition accuracy.

ASR, HCI, HMM, MFCC, Hausa.

Recently, there is a rapid growth in the number of students being admitted to various higher institutions across West African countries yearly. This has posed numerous accommodation problems to the stakeholders like school management and students. Some of the problems include the inability to manage student information accurately. This is as a result of the poor information management system that uses manual registers, cumbersome manual allocation system and so on which has resulted in the inability to give accurate information about the occupancy of rooms. This research study addresses problems encountered in the allocation of hostels (space) to students manually in universities. This work proposes and designs a system that is capable of managing a database which will automatically allocate space (Hall and Room) to students. The proposed system will automatically allocate Halls, rooms, and roommates by taking certain criteria into consideration and also keeps proper records of all the vacant lodges and its inhabitants. This automatic allocation method was developed using tools such as HTML, JScript, CSS, PHP, and MySQL. The system has been implemented and evaluated using a Nigeria private institution as a case study.

Allocation Space, Institution, Hostel Management, Student.

In this study, we construct a continuous probability distribution as an improvement of Topp-Leone distribution. However, density function and the cumulative function of the constructed distribution (Burr X-Topp Leone distribution) were obtained. Also, we show the validity of the new distribution.

Burr X G family, Topp-Leone distribution, Probability density function, cumulative density function.

Agriculture is an information intensive sector. Therefore, there is a continuous need for farmers to have access to the right information, at the right time, in the right format and through the right medium, which in turn can improve inclusive development of the agricultural value chains. In Nigeria and sub-Saharan Africa in general, one of the major attendant problems facing farmers is poor access to information on markets, market prices and logistics to enhance productivity and profits. However, providing these information can be challenging, because of the highly localized nature of agriculture, it means that information must be tailored specifically to distinct conditions. These contextual information needs can be fulfilled by the effective use of Information and communication technologies (ICTs) in agriculture often referred to as e-Agriculture. The delivery of agricultural information and knowledge services using modern information and communication tools and technologies for agricultural marketing, products pricing, logistics, trade and financial inclusion that increase agricultural productivity, efficiency and sustainability falls under the definition of e-Agriculture. This paper presents an e-Agriculture framework that offers support services to smallholder farmers by providing a platform for accessing information on markets, market prices, logistics and financial services with the intent to enhance inclusive development of the agricultural value chain of the country.

e-Agriculture, Information and Communications Technology, Framework, Agricultural Value Chain, mobile phone..

The assessment of water pollution in the natural environment is feasible by means of statistical modelling. However, the reliability of results of statistical analysis is largely dependent on the quality of the collected data and efficiency of model calibration. Water is an essential ingredient to healthy living but has become a major threat due to physical and chemical factors associated to it. This work presents studies of measurement of water pollution in Eleyele reservoir. A single factor model is applied to study the hypothetical correlation between the water pollution and physical and chemical factors, which showed that ALK, CA, TH, Ch and DO were significantly and hypothetically related to water pollution. The path diagram of water quality parameters provided in Figure 1 contained the means and error variances to explain the variability of water quality depending on the source of origin of PCF and depth of the Eleyele reservoir. The coefficients obtained in ALK and TH indicated high constituent concentration to water pollution while the results in Table 1 revealed the failure thresholds of PCF against the standard specification limits. Findings in Table 2 showed that ALK, CA, TH, Ch and DO were significantly and hypothetically related to water pollution. This consequently implies that these five Chemical parameters are important in explaining variation in water pollution in Eleyele reservoir. It is evident from the study that pollution in Eleyele reservoir is due to domestic activities around it. This work has contributed to the literature differently using A single factor model.

Hypothetical correlation, Physical and chemical factor, Single factor model, Water pollution.

The generalised mixed ratio-cum-product estimators in Two-phase sampling has been developed and recommended using multi-auxiliary variables for Full Information Case (FIC), Partial Information Case I (PIC-I) and No Information Case (NIC) estimators. However, the PIC-I estimators would not obey the conditions of usage if both the ratio and product estimator components were not in partial information case, simultaneously. Hence, this study has considered two additional PIC (PIC-II and PIC-III) estimators which satisfied two more conditions for any PIC estimator in the family mixed estimator. Theoretical comparison established that the proposed PIC-II and PIC-III estimators were asymptotically efficient than PIC-I estimator. Similarly, the empirical analysis and comparison for thirty three simulated populations, following normal distribution, confirmed the asymptotic efficiency of the proposed estimators. The proposed estimators were recommended not as substitute but as complimentary estimators to the PIC-I estimator, subject to the confirmation of the conditions of usage. Special case estimators were developed based on the settings of the unknown constants in the proposed estimators.

Ratio-cum-product estimator, Multi-auxiliary variables, Two-phase sampling, Partial information case.

N-gram feature is used to represent documents in natural language processing but leads to curse of dimensionality. Sentiment classification based on word embedding to represent document with an incremental method reduce dimensionality with dense vector representation of words. This works focus on the skip-gram model with negative sampling for vector representation. The text class is predicted by maximising the probabilities of embedding vectors of words under the class. However, a Support Vector Machines with an extension of Stochastic Gradient Descent (SVM-SGD) is employed for effective classification of datasets into multiclass. This is achieved by maximising the margin between hyperplane of every two class pair using online learning as well as controlling the constraints and minimise the regularisation error. This reduces the effect of imbalanced classes in training the classifier parameters. Hence, solve a quadratic programming problem while running SGD for chosen iterations and returning the average point in the number of classes in terms of accuracy and computational cost.

SVM, Multiclass, Skip-gram embedding, Stochastic Gradient Descent, Negative sampling.

Climate change has become the foremost global challenge facing human’s existence at the moment and the effect will be multifaceted with respect to social, economy and environmental challenges. This paper built a model to forecast the significant changes in Nigerian rainfall and temperature time series data. The methodology employed in the analysis and modelling of the rainfall and temperature series was Seasonal Autoregressive Integrated Moving Average (SARIMA) model. The identification stage of the model building suggested four models for both series forecast, but SARIMA(1,1,1)×(1,1,1)₁₂ and SARIMA(1,1,2)×(1,1,1)₁₂ were validated in the estimation stage using Akaike Information Criteria (AIC), Schwartz Information Criteria (SIC), Coefficient of determination and Adjusted coefficient of determination. The model was diagnosed and the results showed that the model was adequate and parsimonious. Both models were used to obtain a one ahead out-sample forecast and the results indicated a rapid continuous rise and presence of seasonality in the forecasted rainfall and temperature time series data. In essence, there will be a significant continuous increase in Nigerian rainfall and temperature values. The values of the forecast evaluation’s metrics used for the two models were relatively small and this implied the forecast inaccuracy is low. In conclusion, the significant continuous rise over the months in rainfall and temperature series forecast indicated that there will be rapid climate change in immediate environment in the coming yearly. This may lead to flooding, infrastructural destruction, social and economic challenges and many more. Therefore, Nigerian Government at all levels needs to put in place plans to curtail its effects.

Climate change, Forecasting, Seasonal Autoregressive Integrated Moving Average, Temperature, Rainfall.

A great threat to lives and properties is fire disaster ever since the genesis of human existence. Statistically, over 70% of total loss of properties and about 20% of total loss of lives every year in Nigeria is due to fire disaster. Electric short circuit in faulty electrical wiring, leakage of flammable materials, insufficient fire defense materials, violation of fire safety and most especially, lack of adequate awareness etc. are the major causes of such percentage. Although conventionally, some factories and recent buildings have now incorporated fire extinguishing systems which are not enough to take prompt action during fire to save properties and ultimately save lives. This project is based on the design and implementation of an automatic wireless-based fire monitoring, detection and alarm system using GSM module. Designing a system to alleviate and to detect fire accidents in advance (before its outbreak) by alerting residents of a building and the fire department would really help to combat fire outbreak issues in the nation. The system is able to detect an erupting fire, alert occupants of the building, notify the concerned recipient, extinguish the source of the fire before the occurrence of such hazard, thereby proffering an eventual prevention of fire outbreaks and its fatalities, hence, saving lives and properties. This project basically takes the advantage of the dominating wireless communication network, using a GSM module to alert the concerned occupants remotely via text messages when the sensors sense dangerous gas leakage, heat and fire in order to alleviate the rate at which peoples lose lives and properties due to fire hazards in Nigeria.

Fire, Sensor, Control Panel, Power supply.

In this work, we suggest some variants of Broyden-like algorithm to solve systems of nonlinear equations using various combination of quadrature rules . The proposed methods are three-step in nature whereby the first step is the initial iterate of the Newton’s method and the remaining two steps are the predictor-corrector of Broyden method and quadrature rules. Numerical tests show that these methods give encouraging results with respect to some existing Broyden-like methods in view of Dolan and More performance profile and Bogle and Perkins comparison index.

Broyden-like method, quadrature formulas, predictor- corrector model, systems of nonlinear equations, numerical examples.

Population increase, complex government service expansion and urgency for effective public service delivery to the citizens have made the application of Information and Communication Technologies for development of public service delivery increasingly indispensable to any nation. This is the epoch of e-governance and administration, where Information and Communication Technology innovations powered by the combination of hardware and software technologies to produce ease, accuracy, precision, efficiency and effectiveness in control of human and material management of the public. Hence, the efficacy of a national central database cannot be ignored, as researches from various authors have proven that this fosters e-government. Thus, this study proposed a model for the design, implementation, usage and maintenance of Nigerian National Central Database, which will serve as the driven force for the implementation of unified national identity cards, so as to curtail, if not completely exterminate, data multiplication, fraud and impersonation among host of others.

Data multiplication, Database, Parastatals, National Identity Card, Security.

The article discusses an alternative way of viewing Padovan sequence extensions through Newton fractals using Google Colab to develop these reproductions. Initially, a scientific bibliographic survey is conducted regarding the process of extension of this sequence. Thus, studies are made on this qualitative alternative of visualization for linear and recurrent sequences. Hereafter alternative forms are developed in Google Colab, so each fractal generated from the characteristic polynomial of these numbers is analyzed. Finally, the conclusions about this process are discussed, proposing studies to continue this work in the future and research in Brazil, as well as possible applications in the areas of Physics and the formation of teachers of Natural Sciences in Brazil.

Extension, Fractal, Google Colab, Padovan sequence, Visualization.

Extreme value, in Sample Survey Theory, is termed outlier in General Statistical Theory. Extreme value data analysis would yield over-estimation or under-estimation in statistical estimation process. Non-linear data transformation method and Sarndal’s correction factor method in Sample Survey Theory have been confirmed to correct extreme value effect in an estimate. However, since the two methods work towards the same objective, there is need to ascertain the efficient estimate between the two methods. This study has empirically compared the two extreme value correction methods. Results revealed that non-linear data transformation method, though associated with back transformation challenge, had lower Percentage Coefficient of Variation (PCV) over correction factor method. Hence, non-linear data transformation method proved efficient over correction factor method. It was recommended that Survey Statisticians should improve on the Sarndal’s developed correction factor method and/or developed new improved estimators for the correction of extreme value in Sample Survey Theory.

Extreme value, non-linear data transformation, correction factor, regression estimator, percentage coefficient of variation.

The developments of Information and Communication Technology (ICT) has made education and learning move towards technology-based instruction instead of directed, teacher-centered instruction. It is no longer news that computers today are the main instructional support to the learning and teaching process. As a human, there is an adaptation process of this new development and its implications as well that has to be considered. This research paper examined the attitude of students towards computers for learning and achievement in scientific concepts. Gender difference in attitude towards the use of computer in learning was also examined. A cross-sectional survey design and convenient sampling techniques was carried out among students in north-east Nigeria. Questions were administered to 117 undergraduate students. Data collected were analyzed with SPSS version 20. Findings from this study showed that though students have a negative attitude toward the use of computers for learning scientific concepts, if teachers are trained and favourably disposed, then one does not need to envisage much trouble in getting the students to use computers for learning and achievement in scientific concepts. The findings also revealed a statistically significant difference in attitude between male and female students toward the use of computers in learning scientific concepts.

Teacher-centered instruction, student-centered instruction, computer, technology, scientific concept, learning.

This paper examines Mathematical analysis of the Euler-Bernoulli beam with damping coefficient subjected to moving load was investigated in this project work. The governing partial differential equation of order four was transformed to an ordinary differential equation using a series method. The numerical result was presented and it is found that the dynamic response of the beam increases as the length of the load increases, the same result was also found for the length of the beam and the mass of the load, but the dynamic response of the beam decreases as the length of the load increases.

Euler-Bernoulli Beam, Dynamic Response, Damping Coefficients, Moving Load.

This study aimed at performing a borehole computer experiment via a modified borehole model. An Orthogonal Array Latin Hypercube Design, OA (49, 8) LHD with parameters’ specification N=49 and k=8 was used to develop a borehole computer experiment using the existing borehole model and a modified borehole model with the same assumed ranges of values for the 8 input variables of a borehole model. The borehole model was modified based on the data generated from the existing model and no assumption of a borehole model was relaxed. The modified model has four newly introduced parameters and a nonlinear regression fit in MATLAB (The MathWorks, Inc. 2016) was used to estimate the values of the four parameters. The four parameters β1, β2, β3 and β4 have the estimated values of 0.4538, -0.9986, -0.1176 and 9.2245, respectively. The modified borehole model performs well in developing a borehole computer experiment with the results obtained which are close to those of the existing model as shown in Figure 1.This study concludes that a borehole experiment can be implemented through a modified borehole model which gives a fair representation of the existing borehole model without relaxing the assumptions of the model. This approach on the modification of an existing borehole model is novel in the world of research in this field.

Computer experiment, Existing borehole model, Modified borehole model, orthogonal array Latin hypercube design, Parameters.

The objectives of this article are to show the effectiveness of the mixture of Mahgoub Transform and Homotopy perturbation method in delivering the exact solution of one-dimensional Burger's equation and furthermore to give another technique for solving Burger's equation. A few issues of one-dimensional Burger's equations were considered and used to show the pertinence and unwavering quality of the proposed technique which is combination of Mahgoub transform and Homotopy perturbation method. The analytical solutions gotten with the accessible Laplace decomposition method and Aboodh Homotopy perturbation technique were examined made and the solutions were seen as in great concurrence with one another. The outcomes acquired demonstrated that this method is effective and profoundly encouraging for such sort of challenges. In view of the illustrative models considered, we suggest that this method is increasingly compelling, helpful, efficient and of high precision with lesser computational work.

Mahgoub transform, Homotopy, Homotopy Perturbation Method, Burgers equation, nonlinear, partial differential equation.

This study focused on application of Probability Proportional to Size (PPS) sampling method in two-stage sampling to enhance the efficiency of estimator. Secondary data were used. The first preliminary sample of clusters was selected independently by Simple Random Sampling Without Replacement (SRSWOR). The Lahiri’s method was used to select First Stage Units (FSU) of clusters from the preliminary sample using Probability Proportional to Size with Replacement (PPSWR). Within each selected First stage clusters, sub-samples of Second Stage Units (SSU) were selected with SRSWOR. An estimator under PPS was derived and the expressions for the Bias and Mean Square Error (MSE) were obtained. The results showed that the PPS enhances the efficiency of the derived estimator. The derived estimator is therefore preferred in the estimation of a heterogeneous population parameter.

Probability Proportional to Size, efficiency, Bias and Mean Square Error, estimator.

The study is to assess the rate of knowledge/awareness of HIV/AIDS among secondary school students in related to their Gender, Age-groups and Type of Schools in Jalingo, Taraba State, Nigeria. A 29 item, English-language questionnaire was administered to a sample of 660 students across 8 selected secondary schools in Jalingo. The result revealed that that 49.85% and 50.15% of the respondents were male and female respectively, it also shows that 88.33% know what HIV/AIDS is, and 86.82% believes that the disease is preventable, while 35.46% have misconception that the disease is curable. The data was subjected to cross tabulation using Chi-Square (χ2) statistic which revealed that the knowledge on the mode of transmitting the disease is independent of Age-group and Gender of the respondents but there is relationship between the knowledge on the Mode of transmitting and the type of school the respondents attend. Furthermore, the study also revealed that knowledge on existence and preventability of HIV/AIDS is independent of School types and Age category of the respondents except for the response on curability of the disease which is dependent of Age-group and school type. However, the knowledge of curability and preventability of the disease is independent of the gender of the respondents, but the knowledge of the respondents on existence of the disease depends on the gender of the respondents.

Chi-square, HIV/Aids, Age-group.

In this paper,investigation of two analytical series methods for solving non-linear differential equations is examined. The study is to give a comparison between Picard’s iteration method and Adomian decomposition method in solving non-linear differential equations. The methods will be compared in terms of convergence, accuracy and efficiency.

Adomian decomposition method, Convergence of the Adomian method, Picard’s iteration method, Picard’s Existence and Uniqueness Theorem.

In the research work, (VIM) is used to solve the system of linear differential equations to investigate the effect of transmission coefficient on the model with a permanent immunity.

Permanent immunity, Incidence rate, Transmission Coefficient.

Developing a logically and consistent knowledge representation scheme for narratives across multiple cultural domains raises the question of the components and structure of a framework within which African narratives, particularly Yorùbá narratives can be formalized or standardized. It is a common fact that narratives are often influenced by culture, language and cognition. Thus, our experience working with the representation of narratives texts are challenged by the current state in the domain of knowledge engineering. The aim of this study is to propose a method for the formalizing and standardizing the representation of Yorùbá folktale narrative text in order to make the information content and structure contained in the folktale narrative explicit and shareable. Moreover, two computational approaches known as Ontological-based representation and text-based representation were put forward for the representation of text information. This research is very important with the purpose of analyzing the content and structure of Yorùbá folktale narrative text.

Knowledge representation, Narratives, formalization, Computation, Yorùbá, Folktale.

Energy forecast and engineering designs within the atmosphere requires essential some measurable parameters which can be related to solar radiations. Global solar radiation accounts for the influx of solar radiation received at the ground level. This study presents twelve empirical models with respect to sunshine duration, relative humidity, and temperature using 25 years of observatory data obtained from some stations. The annual and seasonal performance of the models were validated using statistical measure i.e. Mean Bias Error (MBE), Root Mean Square Error (RMSE), Mean Percentage Error (MPE) and Pearsons correlation coefficient. The proposed models show the lowest MBE, RMSE, and MPE for the temperature based models in Sokoto and Ilorin while all models performed favorably for Port -Harcourt. Similar trends were observed in both wet and dry seasons with improvement in the estimated of global solar radiation. The study recommends some of the models for future prediction of Solar Radiation.

Global Solar Radiation; Empirical Models; Seasonal; Sunshine Duration; Temperature.

Users in a ubiquitous work environment desire comfortable interactions with their owned portable smart devices on daily basis, thus demanding the inclusion of their smart devices as an additional means of getting access to organizational systems in a seamless and user friendly manner. In response to these unique challenges, this paper advocates the inclusion of users’ smartphone in achieving a multi-level authentication access in a ubiquitous work environment. This inclusion was achieved by formulating a model that includes combining at least one authentication method each from what the user has, what the user knows and what the user is. In addition, a mobile app called Nomadic App was developed using use case diagrams, HTML5.0, CSS and JavaScript. A justification of the multi-level authentication mechanism based on National Institute of Standard and Technology attained a level three status. The implementation of the developed Nomadic Mobile App improved the ease in including users’ smartphones in the proposed multilevel authentication model.

Ubiquitous Computing, Ubiquitous work environment, Nomadic Mobile App, Multi-level Authentication, UML tools.