ghanaopendata/ghanaian-research-english huggingface dataset:
Analysis of the Drug-Alcohol Crime Nexus at the Central Police Narcotic Unit and the Central Prison in Kumasi

This study explored the drug-alcohol crime nexus. The connection that exists between substance use and crime does not include only dependent users who commit crimes in order to support their habits, but also drug manufacturing, trafficking, trading, possession and other drug related offences resulting from the behavioral and psychological effects on the user. The setting was at the Central Prison and Central Police Narcotic Unit, both in Kumasi. In all, two groups of participants with sample size (n=206) were involved. The group includes Prison Inmates (n=160) and Police officers (n=46). Semi-structured questionnaires and interviews were used to elicit responses for both qualitative and quantitative data. Urine samples were collected from male prison inmates and immunochemical test performed for cannabis, cocaine and morphine. TLC procedure was used to confirm the presence of cannabis metabolites following the immunochemical test. The response rates were (Inmates=85% and Police=75%). Majority of the inmates were between the ages of 18-35 years (>60%). From the interview, 27.5% of the inmates confessed using cannabis only and this confirms the urine test results where 6.67% of the inmates tested positive for cannabis only while 0.6% tested for both cannabis and morphine. Those who used tramadol and cannabis only were 11.88% with cocaine and cannabis only making 5%. A significant number of the inmates and police believed that drug use can influence one to commit crime (78.13% of inmates and 95.65% of police officers). About 40% out of the 160 inmates said their incarceration was due to drug offence. From the outcome, it can be concluded that drug/substance use has a significant relation with crime.

Source: KNUST
Application of Count Data Models for HIV Testing and Counselling Programe

The study focused on the mean prevalence across gender and to compare identically most appropriate model that best fits selected indicators in the cases of the National HIV Testing and Counseling Units given the gender and time in years. Classical Poisson regression without no doubt a popular method of modeling count data, but its underlying assumption limits its use. That affect many real applications with excess or dispersed data. To deal with a wide range of dispersion levels, poisson regression, Negative Binomial Regression, Hurdle Poisson, hurdle negative Binomial, Zero inflated Poisson and Zero Inflated Negative Binomial were used as alternative regression models. Data were analyzed using these six methods, the results from the models are compared using vuong’s test and the Akaike Information Criterion (AIC) with the Generalized Poisson Regression having the smallest AIC values determines best model for the data. As indicated in the study, the average number of people who have been tested as HIV+ were approximately twenty (_x = 20; SD = 11). The estimated model to fit the data gathered is; log (_i) = 2:5736 􀀀 0:2341Gender + 0:0316Tuberculois and the estimated beta (_ > 0. Overdispersion is an important concept in the analysis of discrete data that is used to determine the best model to fit a given dataset, with Z 􀀀 value test results of 1,1609 and a large p 􀀀 value of 0,1228, which means that there is no overdispersion problem, so the poison regression model should be used instead of the negative binomial. The Vuong test was used in determination of the best model and the hurdle poisson has the minimum AIC value of 721.081, then the best count data technique that could be used to model the data gathered is Hurdle Poisson technique. Based on the appropriate model selected, the key predictor that is HIV+ that contribute significantly and also have a high effect on the mean of thefemale visiting for Testing and Counselling Program.

Source: KNUST
Application Of Count Data Models For HIV Testing And Counselling Programe

The study focused on the mean prevalence across gender and to compare identically most appropriate model that best fits selected indicators in the cases of the National HIV Testing and Counseling Units given the gender and time in years. Classical Poisson regression without no doubt a popular method of modeling count data, but its underlying assumption limits its use. That affect many real applications with excess or dispersed data. To deal with a wide range of dispersion levels, poisson regression, Negative Binomial Regression, Hurdle Poisson, hurdle negative Binomial, Zero inflated Poisson and Zero Inflated Negative Binomial were used as alternative regression models. Data were analyzed using these six methods, the results from the models are compared using vuong’s test and the Akaike Information Criterion (AIC) with the Generalized Poisson Regression having the smallest AIC values determines best model for the data. As indicated in the study, the average number of people who have been tested as HIV+ were approximately twenty (_x = 20; SD = 11). The estimated model to fit the data gathered is; log (_i) = 2:5736 􀀀 0:2341Gender + 0:0316Tuberculois and the estimated beta (_ > 0. Overdispersion is an important concept in the analysis of discrete data that is used to determine the best model to fit a given dataset, with Z 􀀀 value test results of 1,1609 and a large p 􀀀 value of 0,1228, which means that there is no overdispersion problem, so the poison regression model should be used instead of the negative binomial. The Vuong test was used in determination of the best model and the hurdle poisson has the minimum AIC value of 721.081, then the best count data technique that could be used to model the data gathered is Hurdle Poisson technique. Based on the appropriate model selected, the key predictor that is HIV+ that contribute significantly and also have a high effect on the mean of the female visiting for Testing and Counselling Program.

Source: KNUST
Application of count data models for HIV testing and Counselling programe

The study focused on the mean prevalence across gender and to compareidentically most appropriate model that best fits selected indicators in the cases of the National HIV Testing and Counseling Units given the gender and time in years. Classical Poisson regression without no doubt a popular method of modeling count data, but itsunderlying assumption limits its use. That affect many real applications with excess or dispersed data. To deal with a wide range of dispersion levels, poisson regression, Negative Binomial Regression, Hurdle Poisson, hurdle negative Binomial, Zero inflated Poisson and Zero Inflated Negative Binomial were used as alternative regression models. Data were analyzed using these six methods, the results from the models are compared using vuong’s test and the Akaike Information Criterion (AIC) with the Generalized Poisson Regression having the smallest AIC values determines best model for the data. As indicated in the study, the average number of people who have been tested as HIV+ were approximately twenty (_x = 20; SD = 11). The estimated model to fit the data gathered is; log (_i) = 2:5736 􀀀 0:2341Gender + 0:0316Tuberculois and the estimated beta (_ > 0. Overdispersion is an important concept in the analysis of discrete data that is used to determine the best model to fit a given dataset, with Z 􀀀 value test results of 1,1609 and a large p 􀀀 value of 0,1228, which means that there is no overdispersion problem, so the poison regression model should be used instead of the negative binomial. The Vuong test was used in determination of the best model and the hurdle poisson has the minimum AIC value of 721.081, then the best count data technique that could be used to model the data gathered is Hurdle Poisson technique. Based on the appropriate model selected, the key predictor that is HIV+ that contribute significantly and also have a high effect on the mean of the female visiting for Testing and Counselling Program

Source: KNUST
APPLICATION OF QUEUING THEORY IN THE EFFECTIVE MANAGEMENT OF TIME IN MONEY DEPOSIT BANKS-A STUDY OF GHANA COMMERCIAL BANK IN OBUASI MUNICIPAL

Waiting for services is a phenomenon in Ghana. We wait to eat in restaurants, we queue to board buses, we line up for service in post o_ce and in banks either to deposit or withdraw money. The waiting phenomenon is not an experience limited to human beings only but objects too. Jobs wait to be processed on a machine, planes circle in stack before getting permission to land at an airport and cars stop at traffic lights waiting for their turn. Waiting cannot be elimi- nated entirely without incurring inordinate expenses and the goal is to reduce its adverse impact to a tolerable levels. The objective of this study is to use already available systems to identify and also make known the effects and rami_cations of keeping customers waiting in the queue and also the cost banks had to bear if idle facilities are not put into good use, with special emphasis on Obuasi branch of GCB. The queuing char- acteristics at the bank were analyzed using a Multi-server single-queue Model to achieve this major objective. Data for this study was collected by direct obser- vation with the help of research assistants, a stop watch to record the number of hours/minutes spent by each customer at the bank. The data collected from the bank showed that 28th of June, from an hour of 9:30am-10:30am recorded the highest number of customers in the waiting line(113) whiles the least num- ber of customers (17) in the waiting line was recorded on 18th of July hour of 9:00am-10:00am. customers had to wait an average of 0.0165 hours in the queue and 0.0183 hours in the system before leaving the bank. We _nally suggested that, queuing theory is worth studying; the _ndings of it can be used by managers of banks to determine and install the optimum service facilities or in other words put in place the appropriate technologies to help deal with long queues in their banks.

Source: KNUST
Applying blended learning at the SHS level – implications on Students’ performance: the case of Suhum Senior High Technical School

With the rapid proliferation of ICT devices in every field of endeavor and their usage becoming increasingly easier and more affordable, using blended learning in all levels of education becomes very imperative. However, classroom practices continue to be dominated by instructor led teaching. This study sought to unearth how blended learning can be applied as a teaching and learning approach at the SHS level and its implications if any on students’ academic performance, considering that traditional face-to-face technique has been used over the years with its antecedent problems at that level and below. Two main research objectives were set. Action Case study and subsequently a formative experiment were conducted at the Suhum Senior High Technical School where ICT as a subject is taught to all students in the various SHS levels. Opportunity sampling was employed in sampling two hundred (200) SHS 3 students as research participants according to preselected criteria relevant to the research objectives. Qualitative data gathered was analyzed with Computer Assisted Qualitative Data Analysis Software (CAQDAS), specifically Nvivo. The study found out that the BL environment made learning last - longer and easy for students and further provided a different point of view for students and propelled the desire to take other subjects with the blended approach; although not without converse opinions. Results of this study are discussed and recommendations given in light of implications for further research and policy planning.

Source: KNUST
Assessing Land Degradation in Amansie West District: A Surface Mined Area in Ghana

The Amansie West District is characterized by extensive land degrading activities. The district has become a nexus for vast illegal small-scale mining activities, thus affecting the sustainability of other land uses. It is thus imperative, that the land use land cover (LULC) trends over the years be monitored. This would aid assessment of changes over time and their future impacts on resources in the district. The study examined the LULC changes in the district with surface mining as a driver of change. Landsat images of 30m resolution for 1986, 2004, and 2015 were taken for Amansie West District in the Ashanti Region of Ghana. The images were classied using the Maximum Likelihood Classication. Verication was done using 200 ground truth points collected on-site and from Google Earth. The results showed changes in the Spatio-temporal distribution of LULC in the District over 30 years (1986–2015). The dominant LULC changes are from forest to farmland and farmland to mines for 30 years. In addition, there were losses from farmland to mines from 2004–2015. Farmland and forest were the dominant LULC types of the study area which made up 54.6% and 43.6% respectively for 1986, and likewise 54.4% and 22.3% for 2015. However, the forest cover was reduced drastically by 21.3% in 2015. The main drivers of land degradation were farmland from 1986–2004 and mines from 2004–2015. The study emphasizes the need for local-level studies by exposing the extent of the damage for effective future land use management.

Source: KNUST
Assessing the ecosystem services in the Monkey Hill Reserve Area in Takoradi and the Ankasa Conservation Area in the Jomoro district, Ghana UNE, 2019

A Contingent Valuation Method (CVM) was adopted to elicit values of ecosystem services among sampled households in Monkey Hills, Takoradi and Ankasa conservation, in the Jomoro district. The aim was to assess household’s willingness to pay for biodiversity conservation of forest ecosystems in the mist of prevalent destructive socio-economic activities taking place in the areas; and how it differs along the geographical location and across users groups. Simple random sampling techniques were used to select respondents in the two study areas. Data were collected from 150 respondents in each area using a structured questionnaire. Findings showed that most of the household’s WTP per month ranged from GHȼ 1 to GHȼ 20 in the both Ankasa Conservation Area and Monkey Forest Area. In the Ankasa conservation area age and Gender of the head of household were the factors that had statistically significant effects on household’s willingness to pay as determined by the logistic regression analysis. In the Takoradi Monkey reserve area, none of the demographic characteristics had a significant influence of willingness to pay. The survey showed that majority of households aspired to conserve the biodiversity of the forest ecosystem for the survival of mankind and for future generations. However, the only way they could fulfil this was through increased involvement in decision making on forest ecosystem management and other alternative livelihoods made available to them. The results can be used to mobilize support for conservation and sustainable use of these Forest ecosystems.

Source: KNUST
Assessing the effectiveness of FDA regulation of energy drinks

Energy drinks which contain stimulant drugs chiefly caffeine and are marketed as providing mental and physical stimulation are fast becoming the most popular drink worldwide targeted at the youth. There is a growing concern about its impact on the health of young people due to some adverse effects linked to it. It is therefore no surprise that many countries are calling for tighter control and regulation of energy drinks. Some countries have issued limits for caffeine in such drinks, introduced special tax on them, demanded for the display of caution statements on product labels and restricted its sale. This study was therefore conducted to assess the effectiveness of the Food and Drugs Authority (FDA) regulation of energy drinks. A mixed methods approach was adopted which includes survey, interviews, sampling and testing using HPLC to determine knowledge, perception, effects and actual level of caffeine in some energy drinks on the local market. Results indicated relatively poor regulation of energy drinks in the country. Some products in trade were not registered and the country has no limits set for caffeine. Majority of billboards (87.5%) have not been approved by the FDA. Most consumers of the product had exceeded the maximum daily intake and others were mixing these drinks with alcohol, tramadol and codeine containing cough syrups. The way forward is for better and tighter control and regulation of energy drinks by the Food and Drugs Authority and the education of the public on the adverse effects of excessive consumption of the product and the dangers in mixing it with alcohol, tramadol etc.

Source: KNUST
Assessing the Efficacy of High-Dose Rifampicin plus Albendazole against Onchocerciasis

The dataset provides de identified participant data from the ASTAWOL clinical trial (https://kccr-ghana.org/research-impact/research-groups/filariasis-2/), a phase II pilot study investigating the efficacy and safety of high-dose rifampicin (RIF) plus albendazole (ALB) in treating onchocerciasis. The trial was conducted in the Sefwi Akontombra District, Ghana – an area endemic for this parasitic disease. Study Design: Participants (adults aged 18–55 with confirmed onchocercomata and microfilaria) were randomized into four treatment arms: RIF+ALB (7 or 14 days), ALB alone (14 days), and No Treatment, alongside six-month ivermectin administration. Data Included: The dataset encompasses comprehensive clinical data including demographic characteristics, treatment allocation, adverse events, laboratory safety parameters, skin microfilarial densities, Wolbachia depletion measurements via qPCR, and detailed immunohistology analysis of surgically removed onchocercomata tissue to assess embryogenesis and worm viability. Access and Use: Access to this dataset is subject to reasonable requests to the corresponding author, obtaining relevant institutional ethics approval, and proper acknowledgement and citation of the original study.

Source: KNUST
Assessment of physics parameterization scheme combinations of the Weather Research and Forecasting model (WRF) in replicating Onset, Cessation and Duration of the Rainy Season over Ghana

Rainy season modulates many socio-economic activities of Ghana’s economy (health, energy, agriculture, water and disaster management) and as such quantitative knowledge of the rainfall characteristics becomes essential for effective planning. The study evaluated the performance of eight (8) physics parameterization scheme combinations of the Weather Research and Forecasting (WRF) model. The goal of this study is to obtain an optimal scheme combination capable of determining onset, cessation and duration dates of the rainy season over Ghana. The onset and cessation dates were determined from cumulative percentage mean rainfall method using rainfall values. The WRF simulations was forced by ERA-Interim, a reanalysis data, using a double nested configuration approach. The internal domain covers Ghana (the study area) at 10 km resolution whereas the external domain extends over the entire West Africa at 50 km resolution. The assessment of the WRF configurations were carry out for two distinct years, a dry (2001) and a wet (2008) using Global Precipitation Climatological Center data as the observed field. The results obtained show that the method is effectual in determining rainfall onset and cessation dates over Ghana. In general, the combination of WRF Single-Moment 5-class (WSM5) microphysics scheme, Grelli-Devenyi (GD), ensemble cumulus parameterization Scheme and Asymmetric Convective Model (ACM2), planetary boundary layer scheme simulated best the observed data with least biases over Ghana as a unit, the Southern sector and the Northern sector in both dry (2001) and wet years (2008). On the other hand, the schemes combination of WSM5, BMJ and YSU performed worst in both years.

Source: KNUST
Assessment of Three Problematic Texts in the Synoptic Gospels of the New Testament of the Dangme Bible

Three texts in the Dangme Bible (BSG/UBS 1999) generated a lot of discussions during a field survey of the eight Dangme speaking areas. The texts are: Ngôô wa tômi ômâ kâ pa wô... [Lend us our wrong-doings…] (Matt 6:12); … Mumi Klôuklôu ô tsε e yi se …[ the Holy Spirit pushed the head from behind…] (Mark 1:12); and Kεkε nε Yesu de mε ke, “Kuasiahi …” [Then Jesus said to them, “Fools…] (Luke 24:25). Exegesis of the Greek texts; and semantic analysis of the texts in Dangme, found out that: An alternative translation of Matt 6:12 in the Dangme as Ne o kâ wa tômi ômâ nâ ke wô [And let go our wrong-doings] will help readers understand forgiveness as “letting go” the offence of an offender, without keeping any record of the offence. The rendering of Mark 1:12 as Mumi Klôuklôu ha nε e ho nga a nô ya [The Holy Spirit permitted him to go to the wilderness], will clear the confusion in the minds of Dangme Bible readers who do not understand how the Holy Spirit could “push” Jesus into the wilderness. The alternative translation of Luke 24:25 with the phrase Oo nyâ juâmi he jô, (your mind has become cold) reduces the degrading tone of kuasia which etymology means “a good for nothing person”, “an un respected person”, “a worthless person.” The significance of the research is that it has evolved alternative translations and interpretations of Matt 6:12, Mark 1:12, and Luke 24:25 for the Dangme Bible reading communities; the researcher has thus started a discussion that other scholars will join.

Source: KNUST
Attention-based drivers, operational resilience, and operational efficiency: model development and empirical analysis

Developing knowledge of drivers and outcomes of operational resilience is important for building resilient societies as societal welfare depends on the sustenance of business operations. However, such knowledge will not only be incomplete but also misleading if the operational resilience construct remains ambiguous. This study first develops the conceptual domain of operational resilience, and second combines insights from the attention-based view of the firm, the contingency theory, and the resource-based view to propose a model to investigate how attention to threats, uniquely, and in interaction with strategic mission rigidity and disruption orientation, affect operational resilience and how operational resilience affects operational efficiency. The proposed conceptual model is tested on survey data from 259 firms in a major Sub-Sahara African economy - Ghana. The measurement and the structural parts of the model are analysed using confirmatory factor analysis and three-stage least squares estimator respectively. Results support the arguments that operational resilience consists of two distinct theoretical components: disruption absorption and recoverability; and that attention to threats positively relates to operational resilience. Additional analysis, however, shows that there is a limit to the operational resilience benefit of attention to threats: extreme levels of attention to threats are associated with low levels of operational resilience. Further results support the arguments that strategic mission rigidity and disruption orientation negatively and positively moderate the attention to threats-operational resilience relationship respectively and that operational resilience is positively related to operational efficiency. The study demonstrates that contingency-based models can be useful for investigating the drivers and outcomes of operational resilience. A key practical implication from the study is that managers' ability to match emphasis on attention to threats with relevant attention structures may boost operational resilience, and accordingly operational efficiency.

Source: KNUST