Difficulty and Discrimination Indices of Logical-Choice Weight and Confidence Scoring Methods on Chemistry Multiple Choice Test in Nigeria Secondary Schools.

This study determined which of the Confidence Scoring Method (CSM) and Logical-choice Weight Method (LWM) of scoring Chemistry objective tests is more reliable and valid. This was with a view in enhancing the Discrimination and Difficulty indices of Chemistry objective test for authentic assessment. The population comprised all Senior Secondary School Students in Osun State. A sample of 280 SSSII Chemistry Students was selected from 14 schools that were selected from the 30 local governments including Modakeke-Ife Area Council in Osun State using multistage sampling technique. The instruments used were Chemistry Multiple-choice Test types A and B (CMTA and CMTB). The 40-items Chemistry multiple-choice test was administered on the students in each school, on two scoring methods group. The students in CSM and LWM were told how they would be scored following their responses to the test items and were accordingly marked and scored. Data collected were analyzed using t-test statistics. Result of the analyses revealed that a significant difference existed between CSM and LWM in the discrimination indices (t = 6.18, p<0.05) with CSM (S = 0.598) better than LWM (S = 0.496). However, there was no significant difference between CSM and LWM in difficulty indices (t =0.06, p>0.05) with CSM (S = 0.768) and LWM (S =0.870). It was concluded that CSM could be used to authentically assess Chemistry student’s performance with a view to identify students with genuine learning difficulties, thereby improving curriculum evaluation and instruction. Key Words: Discrimination Indices, Difficulty indices, Objective test, Learning Difficulties, Confidence Scoring and Logical-choice Weight

Attitude of Health Workers Towards Patients: An Aftermath of Ebola Outbreak in Nigeria

Attitude is a mental and emotional construct that characterizes people. It is formed from a people’s past and present experiences and is instrumental to how people think and behave. This study investigates the attitude of health workers towards patients in some tertiary hospitals in Southwest Nigeria as a result of the aftermath of the last outbreak of Ebola virus disease in Nigeria. 600 consenting participants selected through a two-stage sampling method were involved in the study. Data was retrieved through administration of structured questionnaire designed in five-point Likert-scale format. About two-third of the participants (32.3%) involved in the study were nurses while (22.0%) were doctors. (34.7%) of the participants disagreed that health workers suspect patients have Ebola virus disease at first contact with them while (48.0%) agreed that health workers are afraid when they have contact with patients. In addition, (36.7%) of the participants in the study disagreed that health workers do not move close to patients when examining patients who are febrile while (39.3%) disagreed that health workers are irrational and harsh to patients. In all, the study showed that, (52.7%) of the participants in the study have positive attitude towards patients. This is without prejudice to previous experience of health workers being infected with the deadly disease from patients during the last outbreak in 2014. The study recommended dissemination of adequate information on Ebola virus disease among health workers to forestall future infection of Ebola virus disease from patients. Massive attitudinal change towards patients among health workers in the study population is also strongly recommended.

COMPARATIVE STUDY OF BAYESIAN AND ORDINARY LEAST SQUARES APPROACHES

Frequentist (Classical) and Bayesian are two major approaches to data analysis in statistics, however, the difference is how both see a parameter. Frequentists see a parameter as constant value while the Bayesians see it a random variable. Research work recently has witnessed increase in the application of Bayesian methods to statistical problems and in other fields. For linear regression modelling, frequentists use more often the Ordinary Least Squares (OLS) method despite violation of some assumptions. Bayesian approach can be used when assumptions in linear regression model using OLS are not met. Using two different data sets, an empirical study was performed using both OLS and Bayesian approaches to linear regression modelling. The analysis showed that the resulting linear regression model using OLS does not meet all required assumptions for a good model. The Bayesian approach as an alternative to regression modelling was further established based on results using several criteria such as RMSE, MAPE and MAD. The results showed that linear regression modelling using Bayesian approach is better than Frequentist method using OLS regression modelling

FINANCIAL INTERMEDIATION: INSTITUTIONS AND MARKET OPERATIONS

The book, Financial Intermediation: Institution and market operations encompass a widerange of chapter discourse with emphasis on market operations of financial intermediariesof financial institutions whose operations is a force to reckon with as a result of its major rolein the growth of the country's economy.This book gives a broader view as it relates to financial intermediation and the wholeoperational activity of financial institution in Nigeria. The book comprises of eight articlechapters with topics ranging from Introduction to Financial Intermediation, FinancialInstitutions, Origin, Growth and Development of Banking in Nigeria, Essentials of Bank inthe Economy, Money and Bank, Overview of Nigeria Financial System, The Money Marketand The Capital Market with the aim of enlightening and educating practitioners,researchers, academicians and students of various higher institutions both in Nigeria andabroad.With a deep insight into the concept of financial intermediation, financial institutionoperations, and financial market activities, this book will, therefore, be of great benefits tolecturers and students (undergraduate and postgraduate) of tertiary institutions,professionals and as well broaden the scope of financial organization about activities infinancial market activities within the country.Dr. Ganiyu Olumuyiwa YinusaProf. Godwin Emmanuel OyedokunMayowa Ebenezer Ariyibi</p

A review of dust-induced electromagnetic waves scattering theories and models for 5G and beyond wireless communication systems

Dust particles and sand storms can cause attenuation and cross-polarization of electromagnetic wave propagation, especially at high frequencies above 10 GHz. Dust attenuation has been the focus of many research works, mainly with the deployment of a 5G wireless network in the FR-2 band (mmWave band, 23–53 GHz with TDD). This has led to the development of novel models to accurately predict and estimate attenuation. However, the existing review works have not adequately provided extensive taxonomies for these models to show the state-of-art and future research directions. This paper aims to bridge this gap by providing a comprehensive review of all electromagnetic scattering models in terms of their strengths, weaknesses, and applications. Lessons learned from the detailed survey have been stated and discussed extensively. Key findings from this review indicate that all the models developed were limited to the region where they were developed, with frequency and visibility levels as the two main parameters. The survey across regions showed no model was developed for Region 2, including the Americas, Greenland, and some of the eastern Pacific Islands. Among the dry regions of the globe, where dust and sand storms can occur either occasionally or frequently, it can be seen that only a few parts of these desert regions of Africa (Region 1) and Asia (Region 3) have been considered by authors for the development of prediction models for attenuation due to dust storms. Thus, this also shows the limitations of the overall deterministic models and presents the crucial need to develop new models or modify existing models to accurately predict dust attenuation in other regions, particularly in Africa

A Review on Rain Signal Attenuation Modeling, Analysis and Validation Techniques: Advances, Challenges and Future Direction

Radio waves are attenuated by atmospheric phenomena such as snow, rain, dust, clouds, and ice, which absorb radio signals. Signal attenuation becomes more severe at extremely high frequencies, usually above 10 GHz. In typical equatorial and tropical locations, rain attenuation is more prevalent. Some established research works have attempted to provide state-of-the-art reviews on modeling and analysis of rain attenuation in the context of extremely high frequencies. However, the existing review works conducted over three decades (1990 to 2022), have not adequately provided comprehensive taxonomies for each method of rain attenuation modeling to expose the trends and possible future research directions. Also, taxonomies of the methods of model validation and regional developmental efforts on rain attenuation modeling have not been explicitly highlighted in the literature. To address these gaps, this paper conducted an extensive literature survey on rain attenuation modeling, methods of analyses, and model validation techniques, leveraging the ITU-R regional categorizations. Specifically, taxonomies in different rain attenuation modeling and analysis areas are extensively discussed. Key findings from the detailed survey have shown that many open research questions, challenges, and applications could open up new research frontiers, leading to novel findings in rain attenuation. Finally, this study is expected to be reference material for the design and analysis of rain attenuation