Search results for: K. A. Adepoju

Authors: K. A. Adepoju, O. I. Shittu, A. U. Chukwu

Abstract:

In this paper, a new four-parameter generalized version of the Fisher Snedecor distribution called Beta- F distribution is introduced. The comprehensive account of the statistical properties of the new distributions was considered. Formal expressions for the cumulative density function, moments, moment generating function and maximum likelihood estimation, as well as its Fisher information, were obtained. The flexibility of this distribution as well as its robustness using cancer remission time data was demonstrated. The new distribution can be used in most applications where the assumption underlying the use of other lifetime distributions is violated.

Keywords: fisher-snedecor distribution, beta-f distribution, outlier, maximum likelihood method

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Authors: Hannah F. Opayinka, Adedayo A. Adepoju

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This study is an extension of a prior study on the modification of the existing m-out-of-n (moon) bootstrap method for heavy-tailed distributions in which modified m-out-of-n (mmoon) was proposed as an alternative method to the existing moon technique. In this study, both moon and mmoon techniques were applied to two real income datasets which followed Lognormal and Pareto distributions respectively with finite variances. The performances of these two techniques were compared using Standard Error (SE) and Root Mean Square Error (RMSE). The findings showed that mmoon outperformed moon bootstrap in terms of smaller SEs and RMSEs for all the sample sizes considered in the two datasets.

Keywords: Bootstrap, income data, lognormal distribution, Pareto distribution

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Authors: Adepoju A. A., Olapade-Ogunwole F., Ganiyu M. O.

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This study examined women's empowerment in cassava production in southwest Nigeria. The contributions of the five domains namely decision about agricultural production, decision-making power over productive resources, control of the use of income, leadership and time allocation to women disempowerment, profiled the women based on their socio-economics features and determined factors influencing women's disempowerment. Primary data were collected from the women farmers and processors through the use of structured questionnaires. Purposive sampling was used to select the LGAs and villages based on a large number of cassava farmers and processors, while cluster sampling was used to select 360 respondents in the study area. Descriptive statistics such as bar charts and percentages, Women Empowerment in Agriculture (WEAI), and the Logit regression model were used to analyze the data collected. The results revealed that 63.88% of the women were disempowered. Lack of decision-making power over productive resources; 36.47% and leadership skills; 33.26% contributed mostly to the disempowerment of the women. About 85% of the married women were disempowered, while 76.92% of the women who participated in social group activities were more empowered than their disempowered counterparts. The findings showed that women with more years of processing experience have the probability of being disempowered while those who engage in farming as a primary livelihood activity, and participate in social groups among others have the tendency to be empowered. In view of this, it was recommended that women should be encouraged to farm and contribute to social group activities.

Keywords: cassava, production, empowerment, southwest, Nigeria

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Authors: Abdulrazaq Adepoju

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Climate change and its negative environmental challenges to humanity has for decades, taken the centre stage globally receiving attention on ways to take care of the menace and keep the damaging effects to manageable and tolerable level. However, noise pollution, another major environmental hazard militating against human habitation particularly in the developing countries of the world, is not receiving enough attention by the concerned authorities at all tiers of governance. A good knowledge of the major sources of environmental noise pollution will go a long way in assisting relevant stakeholders in planning, designing, and management of problems associated with noise pollution. This paper seeks to identify the major sources of noise in the built environment on selected areas of Osogbo, Nigeria. The paper adopted a survey research method of collecting data from surveys carried out on buildings around old Garage-Okefia axis, Old garage-Oja Oba axis, and Okefia-Olaiya junction axis, all within Osogbo metropolis using sound surveying metre. It was discovered that noise from vehicular and pedestrian traffic, commercial activities such as advertising vendors and religious buildings (churches and mosques) constitute major causes of noise in the study area. The paper recommends some measures to the affected stakeholders particularly government agencies on means of reducing noise pollution to a tolerable level in the study areas and places of the same industrial layout.

Keywords: built environment, climate change, environmental pollution, noise

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Authors: Opeyemi Awau Adepoju

Abstract:

The task of nation-building for Nigeria, like other developing nations, has continued to be riddled with audacious challenges that kept threatening to consume the state itself. Among the destabilizing factors that are sometimes mutually reinforcing are poverty and insecurity. Nigeria has been bedeviled with poverty since the onset of the 1980s when the country metamorphosed from an agricultural to an oil-based economy coupled with unbridled political corruption and wasteful management of resources by successive governments. The crippling poverty started manifesting in the scourge of criminalities and a general state of insecurity. Poverty gradually becomes the breeder of insecurity and threats to human life in Nigeria. Interestingly, successive governments tended to recognize the destructive tendencies of poverty and took several interventionist initiatives towards abating or slowing down the spate of poverty so as to reverse the trend of insecurity, but none of those initiatives can be adjudged good or enduring legacies. The emergence of the Buhari administration in 2015 provided a new opportunity to tackle poverty and, in turn, insecurity that had permeated every aspect of national life before that year’s presidential elections. Expectedly, the government took ambitious steps through its innovative ideas of intervention through its National Social Intervention Programmes (NSIP). Therefore, this paper is an assessment of the Buhari administration’s initiatives in poverty eradication in Nigeria as one of its strategies to fight insecurity, and the paper adopted a qualitative approach. The theoretical arguments put up by this paper are with respect to the connection between poverty and insecurity sourced from the theory of Relative Deprivation. The paper found that the Buhari administration has done better than any government since 1999 in inventing a social intervention program and that the poverty of the people has been addressed to a notable extent. However, the problem of politicization of intervention programs has continued to be the practice under the administration, and if this is not abated, the post-Buhari era may as well be like the eras before it. The paper recommends legislation that can make poverty ameliorating programs permanent, at least for some years to come, so as to avoid the usual policy summersault at every instance of political transition, which has limited the sustainability of public policies and indeed hindered nation-building efforts in Nigeria.

Keywords: insecurity, poverty alleviation, public policies, social intervention

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Authors: C. C. Alamanjo, A. O. Adepoju, H. Martin, R. N. Baines

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Peri-urban agriculture in Jos Nigeria serves as a major means of livelihood for both urban and peri-urban poor, and constitutes huge commercial inclination with a target market that has spanned beyond Plateau State. Yet, the sustainability of this sector is threatened by intensive application of urban refuse ash contaminated with heavy metals, as a result of the highly heterogeneous materials used in ash production. Hence, this research aimed to understand the current fertilizer employed by farmers, their perception and acceptability in utilization of household sewage sludge for agricultural purposes and their capacity in mitigating risks associated with such practice. Mixed methods approach was adopted, and data collection tools used include survey questionnaire, focus group discussion with farmers, participants and field observation. The study identified that farmers maintain a complex mixture of organic and chemical fertilizers, with mixture composition that is dependent on fertilizer availability and affordability. Also, farmers have decreased the rate of utilization of urban refuse ash due to labor and increased logistic cost and are keen to utilize household sewage sludge for soil fertility improvement but are mainly constrained by accessibility of this waste product. Nevertheless, farmers near to sewage disposal points have commenced utilization of household sewage sludge for improving soil fertility. Farmers were knowledgeable on composting but find their strategic method of dewatering and sun drying more convenient. Irrigation farmers were not enthusiastic for treatment, as they desired both water and sludge. Secondly, household sewage sludge observed in the field is heterogeneous due to nearness between its disposal point and that of urban refuse, which raises concern for possible cross-contamination of pollutants and also portrays lack of extension guidance as regards to treatment and management of household sewage sludge for agricultural purposes. Hence, farmers concerns need to be addressed, particularly in providing extension advice and establishment of decentralized household sewage sludge collection centers, for continuous availability of liquid and concentrated sludge. Urgent need is also required for the Federal Government of Nigeria to increase commitment towards empowering her subsidiaries for efficient discharge of corporate responsibilities.

Keywords: ash, farmers, household, peri-urban, refuse, sewage, sludge, urban

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Authors: Tayo P. Ogundunmade, Adedayo A. Adepoju

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Terrorist attacks in liberal democracies bring about a few pessimistic results, for example, sabotaged public support in the governments they target, disturbing the peace of a protected environment underwritten by the state, and a limitation of individuals from adding to the advancement of the country, among others. Hence, seeking for techniques to understand the different factors involved in terrorism and how to deal with those factors in order to completely stop or reduce terrorist activities is the topmost priority of the government in every country. This research aim is to develop an efficient deep learning-based predictive model for the prediction of future terrorist activities in Nigeria, addressing low-quality prediction accuracy problems associated with the existing solution methods. The proposed predictive AI-based model as a counterterrorism tool will be useful by governments and law enforcement agencies to protect the lives of individuals in society and to improve the quality of life in general. A Heterogeneous Bayesian Neural Network (HETBNN) model was derived with Gaussian error normal distribution. Three primary transfer functions (HOTTFs), as well as two derived transfer functions (HETTFs) arising from the convolution of the HOTTFs, are namely; Symmetric Saturated Linear transfer function (SATLINS ), Hyperbolic Tangent transfer function (TANH), Hyperbolic Tangent sigmoid transfer function (TANSIG), Symmetric Saturated Linear and Hyperbolic Tangent transfer function (SATLINS-TANH) and Symmetric Saturated Linear and Hyperbolic Tangent Sigmoid transfer function (SATLINS-TANSIG). Data on the Terrorist activities in Nigeria gathered through questionnaires for the purpose of this study were used. Mean Square Error (MSE), Mean Absolute Error (MAE) and Test Error are the forecast prediction criteria. The results showed that the HETFs performed better in terms of prediction and factors associated with terrorist activities in Nigeria were determined. The proposed predictive deep learning-based model will be useful to governments and law enforcement agencies as an effective counterterrorism mechanism to understand the parameters of terrorism and to design strategies to deal with terrorism before an incident actually happens and potentially causes the loss of precious lives. The proposed predictive AI-based model will reduce the chances of terrorist activities and is particularly helpful for security agencies to predict future terrorist activities.

Keywords: activation functions, Bayesian neural network, mean square error, test error, terrorism

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