The Impact of some Meteorological Variables on the Estimation of Global Solar Radiation in Kano, North Western, Nigeria

This study examines the impact of measured monthly average daily global solar radiation, sunshine duration, wind speed, maximum and minimum temperatures, rainfall, cloud cover and relative humidity parameters on the estimation of global solar radiation during the period of thirty one years (1980 – 2010) for Kano, Nigeria (Latitude 12.030N, Longitude 08.120E and altitude 472.5 m above sea level) using different selected proposed empirical models. The accuracy of the proposed models are tested using statistical indicator; Mean Bias Error (MBE), Root Mean Square Error (RMSE), Mean Percentage Error (MPE), t – test, correlation coefficient (R) and coefficient of determination (R2). The developed models are based on one variable correlation, two variable correlations, three variable correlations, four variable correlations, five variable correlations and six variable correlations, in each case one or two empirical models has been recommended based on their outstanding performance in line with the statistical test subjected to. The model (Eqn. 36) with the highest values of R and R2 and lowest values of MBE, RMSE, MPE and t – test as compared with other developed model is considered the best performing model. It was observed that the newly recommended developed models (Eqns. 13, 17, 21, 26, 27, 31, 35 and 36) can be used for estimating daily values of global solar radiation with higher accuracy and has good adaptability to highly changing climatic conditions for Kano and regions of similar climatic information. Keywords: global solar radiation, sunshine duration, wind speed, rainfall and coefficient of determination

A Comparative Study of some Meteorological Parameters for Predicting Global Solar Radiation in Kano, Nigeria Based on Three Variable Correlations

In this present study, twenty empirical regression equations based on three variable correlations were developed and used to estimate the monthly average daily global solar radiation on a horizontal surface using measured monthly average daily global solar radiation, sunshine duration, wind speed, maximum and minimum temperatures, rainfall, cloud cover and relative humidity parameters during the period of thirty one years (1980 – 2010) for Kano, Nigeria (Latitude 12.030N, Longitude 08.120E and altitude 472.5 m above sea level). The comparative performance of the developed models has been evaluated on the basis of statistical parameters using Mean Bias Error (MBE), Root Mean Square Error (RMSE), Mean Percentage Error (MPE), t – test and Nash – Sutcliffe Equation (NSE). The values of the correlation coefficient (R) and coefficient of determination (R2) were also obtained for each of the developed models. The MPE values for all the developed models lie within the acceptable range . The t – test produces perfect model performance at 95% and 99% confidence level for all the developed models. Three equations were recommended from this study, firstly, the model (Eqn. 20) with the highest value of R and R2, secondly, the model (Eqn. 24) with the least value of RMSE and the highest value of NSE and thirdly, the model (Eqn. 31) with the least values of MPE and t – test. These developed models can be used for estimating monthly average daily global solar radiation for Kano, North – Western, Nigeria and other locations with similar weather conditions where the solar radiation data is unavailable. Keywords: global solar radiation, Kano, variable correlation, Mean Bias Error (MBE) and coefficient of determination

Ebola virus disease and pregnancy outcome: A review of the literature

Introduction: Ebola virus disease (EVD) is a disease of humans and other primates caused by Ebola viruses. The most widespread epidemic of EVD in history occurred recently in several West African countries. The burden and outcome of EVD in pregnant women remains uncertain. There are few reports to date on maternal and fetal outcomes among pregnant women with EVD, hence the justification for this comprehensive review of these published studies.Materials and Methods: Published literature in Englishthat reported on maternal and or fetal outcome among pregnant women with EVD up to May 2016 were searched in electronic databases (Google Scholar, Medline, Embase, PubMed, AJOL, and Scopus). Studies that did not meet the inclusion criteria were excluded. We extracted the following variables from each study: Geographical location, year of the study, settings of the study, participants, maternal and fetal outcome.Results: A total of 12 studies reported on 108 pregnant women and 110 fetal outcomes. Six of the studies were case reports, three retrospective studies, two cross‑sectional studies, and one was a technical report. There were 91 (84.3%) deaths out of the 108 pregnant women, while only one (0.9%) fetal survival was reported out of 110. The survival rate among the 15 patients that had spontaneous abortion/stillbirth or induced delivery was 100%.Conclusion: There was a poor maternal and fetal outcome among pregnant women with EVD, and fetal evacuation significantly improves maternal survival.Key words: Africa; Ebola; fetal; maternal; outcome

Effects of vaccination on the prevalence of Peste Des Petits Ruminants (PPR) in small ruminants in Taraba State, Nigeria

An investigation was conducted in order to determine the distribution of Peste Des Petits Ru'minants (PPR) and vaccination efforts in Taraba State of Nigeria using data collected from the Veterinary Services Department of the State's Ministry of Agriculture and Rural Development between 1992 and 1998. The results showed that the disease is most prevalent during the cold months of the year (Hamattan) and beginning of the rainy season. Similarly, outbreaks increased with the relaxation of vaccination campaign programmes. It was observed that the number of outbreak was low when a vaccination using Tissue-Culture-Rinderpest Vaccine (TCRV) was intensified and it increases when the vaccination was relaxed. It was concluded from this study that intensive vaccination campaign of small ruminants against the PPR through provision of adequate facilities, TCRV vaccines, training offield workers and mass enlightenment campaign in the villages are paramount to control menace of the disease in Nigeria

Effects of Rainfall Variability on Cassava Yield in Owerri North Local Government Area of Imo State, Nigeria

Agriculture in Nigeria is the main source of food and major employer of labour with about 60% of the Nigerian population engaged in Agriculture. It is predominantly ran-fed and hence vulnerable to climate change. This study assessed the effects of rainfall and temperature variation on cassava in Owerri North Local Government Area of Imo State, Nigeria. Data for the study were collected from the Imo State Agricultural Development Programme for the period of 22years (1995-2017). The data were analyzed statistically and the results revealed that there was minimal variation in rainfall and temperature characteristics, which translates into proportional variability in cassava yield in Owerri North Local Government Area, during the period of study. The study also revealed poor yield with non-significant positive effect of rainfall, maximum and minimum temperature in cassava yield. With reference to the study outcome, it was recommended that weather information should be disseminated to crop farmers to equip them with proper timing, adaptation and mitigation strategies for agricultural practice in the region. This would reduce the adverse effects of climate variability on crop production. Also, it was recommended that since rainfall and temperature do not account for one hundred percent of the determinants of crop yield, other factors such as soil fertility and farm management practices should be explored in order to ensure maximum yield of crops in Owerri, Imo State of Nigeria. Keywords: Effect, Rainfall, Variability, Cassava yield DOI: 10.7176/JEES/9-3-12 Publication date:March 31st 201

Effects of Rainfall and Temperature Variability on Yam Production in Lafia Local Government Area, Nasarawa State, Nigeria

The study assesses the effects of rainfall and temperature variability on yam production in lafia Local Government Area of Nasarawa State, Nigeria. The research data were collected from secondary data from the existed literatures such as textbooks, journals, articles, seminar papers, encyclopedia which are most pertinent to this study. The rainfall and temperature data of the fourteen years (2001-2014) were collected from synoptic weather station of NIMET archives Lafia sub station where rain gauge and thermometer are used. The Statistics Package for Social Science (SPSS) software was used for the analysis. The derivatives of these data were computed and used for further analysis such as average of number of rainy and temperature variations of months of years under study. The yam data was collected in metric tons as unit of measurement per year for the fourteen years under study which shows that there is an upward increase trend in yam production in the area of study over the time span in gradual and steady state which has a variation in production, across the years under consideration of 0.843%. It is also indicated the effect of 0.186 (19%) of the variation in yam production was explained by the variation in rainfall, maximum and minimum temperature between the study periods. It’s further stated that the magnitude of effect by the predictors (rainfall, minimum and maximum temperature) on the dependent variable (yam) varies. Rainfall had a non-significant (P-value > 0.05) effect of -0.269 and a coefficient value of -0.438. This by extension implies that for every unit (mm) decrease in rainfall over the period of time under investigation, yam production decreases by -0.438mt. The relationship between rainfall, temperature and yam using Pearson correlation shows that a weak negative relationship (-0.041) between rainfall and yam yield, a weak positive relationship (0.160) between maximum temperature and yam yield and there is a weak positive relationship (0.322) between minimum temperature and yam yield. The study identified increased production with non-significant positive effect of rainfall, maximum and minimum temperature on yam production. Since the study focused on the effects of rainfall and temperature variability on yam production in Lafia Local Government Area of Nasarawa state, without taking into consideration of other parameters like land use patterns and since rainfall and temperature are not the only parameters that affects yam production. the following recommendations are made: Agricultural Extension Officers (AEOs) should be deployed to guide farmers through routine visits, regular access to weather information to farmers by NIMET, application of irrigation  for growing of crops,  study of land use pattern should be considered and there is need for modern farm inputs and price control by government and Non Governmental organization. Keywords: Effects, Rainfall, Temperature, Variability, Yam Production DOI: 10.7176/JEES/9-3-13 Publication date:March 31st 201

Grupiranje zasnovano na skupljanju dokaza s vjerojatnosno-neizrazitim C-means pristupom za dijagnozu bolesti

Traditionally, supervised machine learning methods are the first choice for tasks involving classification of data. This study provides a non-conventional hybrid alternative technique (pEAC) that blends the Possibilistic Fuzzy C-Means (PFCM) as base cluster generating algorithm into the ‘standard’ Evidence Accumulation Clustering (EAC) clustering method. The PFCM coalesces the separate properties of the Possibilistic C-Means (PCM) and Fuzzy C-Means (FCM) algorithms into a sophisticated clustering algorithm. Notwithstanding the tremendous capabilities offered by this hybrid technique, in terms of structure, it resembles the hEAC and fEAC ensemble clustering techniques that are realised by integrating the K-Means and FCM clustering algorithms into the EAC technique. To validate the new technique’s effectiveness, its performance on both synthetic and real medical datasets was evaluated alongside individual runs of well-known clustering methods, other unsupervised ensemble clustering techniques and some supervised machine learning methods. Our results show that the proposed pEAC technique outperformed the individual runs of the clustering methods and other unsupervised ensemble techniques in terms accuracy for the diagnosis of hepatitis, cardiovascular, breast cancer, and diabetes ailments that were used in the experiments. Remarkably, compared alongside selected supervised machine learning classification models, our proposed pEAC ensemble technique exhibits better diagnosing accuracy for the two breast cancer datasets that were used, which suggests that even at the cost of none labelling of data, the proposed technique offers efficient medical data classification.Tradicionalno, metode nadziranog strojnog učenja predstavljaju prvi izbor za zadatke koji uključuju klasifikaciju podataka. Ovo istraživanje prikazuje nekonvencionalnu hibridnu alternativnu (pEAC) tehniku koja kombinira vjerojatnosno-neizraziti C-Means (PFCM) kao osnovni algoritam grupiranja u standardno grupiranje korištenjem grupiranja zasnovanog na skupljanju dokaza (EAC). PFCM objedinjuje zasebna svojstva vjerojatnosnog C-Means (PCM) i neizrazitog C-Means (FCM) algoritama u sofisticirani algoritam grupiranja. Usprkos ogromnim mogućnostima koje nudi ova tehnika, u smislu strukture, ona je nalik cjelovitim hEAC i fEAC tehnikama grupiranja realiziranim integracijom K-Means i FCM algoritama grupiranja u EAC tehniku.Kako bi se validirala učinkovitost, njeno ponašanje je ispitano na sintetičkim i stvarnim medicinskim podacima te su provedene usporedbe s pojedinačnim široko rasprostranjenim metodama, drugim nenadziranim tehnikama grupiranja i nekim nadziranim metodama učenja. Rezultat prikazuje kako predložena pEAC tehnika nadmašuje pojedine metode grupiranja i druge tehnike nenadziranog učenja u smislu točnosti u dijagnozi hepatitisa, kadiovaskularnih bolesti, raka dojke i dijabetesa, korištenih u eksperimentu.Značajno, u usporedbi s odabranim nadziranim modelima klasifikacije, predložena pEAC tehnika pokazuje bolju točnost dijagnoze na dvama korištenim bazama podataka za rak dojke, što ukazuje na to da čak i bez označenih podataka predložena tehnika nudi efikasnu klasifikaciju medicinskih podataka