Effects of Direct and Indirect Instructional Strategies on Students‟ Achievement in Mathematics

This is a quasi experimental research designed to determine the effects of Direct and Indirect instructional strategies on Mathematics achievement among junior secondary school students. The population consisted of students in a Public Secondary School in Owerri, Imo State. A sample of 102 students from two (2) intact classes (A & B) was drawn using simple random sampling (Balloting) on class basis. Group A students were taught Mathematics using Direct Instructional strategy, while Group B students were taught using Indirect Instructional strategy. The treatment lasted for 10 weeks of 20 sessions. Three research questions and three null hypotheses guided the study. Mathematics Achievement Test (MAT) was administered on the subjects at the end of treatment. The MAT was validated and its reliability test produced co-efficient of 0.86. Data collected were analyzed with Mean (x), Standard Deviation (SD), t-test analysis. Results got after data analysis indicated that direct instructional strategy has a better effect on students achievement in Mathematics compared to indirect instructional strategy; significant difference existed between direct and indirect instruction on students achievement in Mathematics; and gender is a significant factor in determining the effect of direct and indirect instructional strategy on students‟ achievement in Mathematics, in favour of the males. Based on these results, recommendations were made for the adoption of direct instructional strategy in teaching Mathematics in secondary schools

Can Nigerian RSA’s Beat Inflation?

This paper aims to review and replicate the performance of the funds managed under the 2004 Pension reform act (“Old Act”) of Nigeria and its subsequent repeal. I utilise Ordinary Least Squares (“OLS”) regression analysis in an attempt to replicate the returns on Net Asset Values (“NAV”) published by some of the Licensed Pension Fund Administrators (“PFA”). The Old Act allows for active fund management of both equity and ?xed income instruments on Nigerian assets. I attempt to replicate the published NAV results using four Nigerian ?nancial instruments to ascertain if passive alternatives to active management by the PFA’s at lower cost and transaction fees can be created. The performance of 10 Nigerian PFA’s run by fund managers in the period December 2006 to December 2014 is reviewed and presented.The evidence from this study indicates that the performance of the 10 PFA’s cannot be replicated using four simple financial instruments. Since the Old Act allows for an allocation of up to 80% of assets in bonds, a simple t test is performed to ascertain whether PFA’s mark to market their portfolio’s adequately. Keywords: Pension Funds, Nigeria, PFA’s, T Test, Out-Performance

Heavy Ball with Friction Method for the Elastography Inverse Problem

The primary objective of this thesis is to develop a fast and efficient computational framework for the nonlinear inverse problem of identifying a variable coefficient in a system of partial differential equation modelling the response of an incompressible elastic object under some known body forces and boundary traction. The main novelty of this contribution is to use, for the first time, of the so-called heavy ball with friction method for inverse problems. The heavy ball with friction dynamical system is a nonlinear oscillator with damping. The key idea is to pose the inverse problem as an optimization problem, derive its optimality system, and then seek the solution through a trajectory of a dynamical system. In this work, we will study four different optimization formulations for the nonlinear inverse problem and thoroughly compare their convergence and numerical performance. Since we use a second-order method, we also investigate a general second-order hybrid and a second-order adjoint method for an efficient computation of the hessian of the output least-squares formulation. The stability of the dynamical system approach with respect to the contamination in the data is thoroughly investigate in the context of a simpler elliptic partial differential equation. The mixed finite element approach is used to discretize the direct as well as the inverse problems

Great Recession and Corporate Recovery: Empirical Evidence of the Impact of Firms\u27 Internal Control System

In Previous studies, we are made to understand that recession has a detrimental effect on corporate valves. Hence, I investigate substantial evidence that firms with a good internal control system, even during the financial crisis of 2008, were able to minimize redundancies that could have negatively affected the recovery of their company’s post-recession. Thus, firms with effective internal control systems are able to recover from negative events significantly faster (as measured by the firm’s values) than those without such systems

The January and Monday effect or the lack thereof

This paper assesses the existence of calendar anomalies on 167 stocks listed on the Nigerian stock exchange (“NSE”) between the period 2004 and 2014. These stocks, at different times, also constituted part of the all share index within the review period. The approach taken in this paper differs slightly from most papers where the review has been on indices rather than individual stocks. The simple Ordinary Least Squares (“OLS”) estimation technique and the Generalised Autoregressive Conditional Heteroscedasticity (“GARCH”) model were utilized to test for day of the week effects and any other monthly calendar anomaly that has been reported at different times on the Nigerian Stock Exchange. The evidence from this study indicates that for the Nigerian Stock Exchange All Share Index (“NSE ASI”), and majority of the listed equity instruments, there was no statistically significant day of the week or month of the year effect. There is no evidence of a January effect or any other monthly effects. The constituents of the NSE ASI were employed because as at December 2014, a single stock on the NSE ASI, accounted for over 20% of the index composition. This has been the case since the year 2010. Keywords: Calendar anomalies, Nigeria, January effect, Day of the week effect, OLS, GARCH

The Performance of Nigerian Mutual Funds in the Period 2011 - 2014

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Earnings or Dividends: Which had More Predictive Power?

This paper reviews two important investment strategies employed by value investors; the Price to Earnings Ratio (“PER”) and Dividends yield (“DY”) strategy. In this paper, I review the performance of 16 portfolios formed on listed equity instruments on the Nigerian stock exchange (“NSE”) which were divided into quartiles within the period 2003 and 2014. I utilise various measures; “Jensen Alpha” measure and Sharpe ratio, to assess which portfolio would have earned Nigerian investors above market returns in the period. The evidence from this study indicates that a portfolio formed using a market capitalization weighted approach for the highest quartile of dividend yielding stocks overall outperforms a buy-the-market and-hold policy. Also, equal weighted and market capitalization weighted portfolios based on earnings yield have been unable to outperform the NSE All Share Index in the review period. Put differently, the PER has no predictive power but dividends yields do. The limitations of the study are also discussed. Keywords: Price to Earnings Ratio, Dividends yield, Nigeria, Jensen’s alpha, Sharpe ratio, Risk adjusted returns, Value investin

Conversion Bridge of Sony SubLvds to MIPI CSI-2

Undergraduate Summer Research Outpu

Efficient radio resource management for the fifth generation slice networks

It is predicted that the IMT-2020 (5G network) will meet increasing user demands and, hence, it is therefore, expected to be as flexible as possible. The relevant standardisation bodies and academia have accepted the critical role of network slicing in the implementation of the 5G network. The network slicing paradigm allows the physical infrastructure and resources of the mobile network to be “sliced” into logical networks, which are operated by different entities, and then engineered to address the specific requirements of different verticals, business models, and individual subscribers. Network slicing offers propitious solutions to the flexibility requirements of the 5G network. The attributes and characteristics of network slicing support the multi-tenancy paradigm, which is predicted to drastically reduce the operational expenditure (OPEX) and capital expenditure (CAPEX) of mobile network operators. Furthermore, network slices enable mobile virtual network operators to compete with one another using the same physical networks but customising their slices and network operation according to their market segment's characteristics and requirements. However, owing to scarce radio resources, the dynamic characteristics of the wireless links, and its capacity, implementing network slicing at the base stations and the access network xix becomes an uphill task. Moreover, an unplanned 5G slice network deployment results in technical challenges such as unfairness in radio resource allocation, poor quality of service provisioning, network profit maximisation challenges, and rises in energy consumption in a bid to meet QoS specifications. Therefore, there is a need to develop efficient radio resource management algorithms that address the above mentioned technical challenges. The core aim of this research is to develop and evaluate efficient radio resource management algorithms and schemes that will be implemented in 5G slice networks to guarantee the QoS of users in terms of throughput and latency while ensuring that 5G slice networks are energy efficient and economically profitable. This thesis mainly addresses key challenges relating to efficient radio resource management. First, a particle swarm-intelligent profit-aware resource allocation scheme for a 5G slice network is proposed to prioritise the profitability of the network while at the same time ensuring that the QoS requirements of slice users are not compromised. It is observed that the proposed new radio swarm-intelligent profit-aware resource allocation (NR-SiRARE) scheme outperforms the LTE-OFDMA swarm-intelligent profit-aware resource (LO-SiRARE) scheme. However, the network profit for the NR-SiRARE is greatly affected by significant degradation of the path loss associated with millimetre waves. Second, this thesis examines the resource allocation challenge in a multi-tenant multi-slice multi-tier heterogeneous network. To maximise the total utility of a multi-tenant multislice multi-tier heterogeneous network, a latency-aware dynamic resource allocation problem is formulated as an optimisation problem. Via the hierarchical decomposition method for heterogeneous networks, the formulated optimisation problem is transformed to reduce the computational complexities of the proposed solutions. Furthermore, a genetic algorithmbased latency-aware resource allocation scheme is proposed to solve the maximum utility problem by considering related constraints. It is observed that GI-LARE scheme outperforms the static slicing (SS) and an optimal resource allocation (ORA) schemes. Moreover, the GI-LARE appears to be near optimal when compared with an exact solution based on spatial branch and bound. Third, this thesis addresses a distributed resource allocation problem in a multi-slice multitier multi-domain network with different players. A three-level hierarchical business model comprising InPs, MVNOs, and service providers (SP) is examined. The radio resource allocation problem is formulated as a maximum utility optimisation problem. A multi-tier multi-domain slice user matching game and a distributed backtracking multi-player multidomain games schemes are proposed to solve the maximum utility optimisation problem. The distributed backtracking scheme is based on the Fisher Market and Auction theory principles. The proposed multi-tier multi-domain scheme outperforms the GI-LARE and the SS schemes. This is attributed to the availability of resources from other InPs and MVNOs; and the flexibility associated with a multi-domain network. Lastly, an energy-efficient resource allocation problem for 5G slice networks in a highly dense heterogeneous environment is investigated. A mathematical formulation of energy-efficient resource allocation in 5G slice networks is developed as a mixed-integer linear fractional optimisation problem (MILFP). The method adopts hierarchical decomposition techniques to reduce complexities. Furthermore, the slice user association, QoS for different slice use cases, an adapted water filling algorithm, and stochastic geometry tools are employed to xxi model the global energy efficiency (GEE) of the 5G slice network. Besides, neither stochastic geometry nor a three-level hierarchical business model schemes have been employed to model the global energy efficiency of the 5G slice network in the literature, making it the first time such method will be applied to 5G slice network. With rigorous numerical simulations based on Monte-Carlo numerical simulation technique, the performance of the proposed algorithms and schemes was evaluated to show their adaptability, efficiency and robustness for a 5G slice network