Leveraging Data Mining and Data Warehouse to Improve Prison Services and Operations in Nigeria

Crimes are social nuisance and cost our society dearly in several ways. In Nigeria, any research geared towards helping to solve crimes faster will be beneficial to the society at large. It has been observed that the major challenge facing all law-enforcement and intelligence-gathering organizations in Nigeria is how to accurately and efficiently analyze the growing volume of crime data. As the volume of this crime data becomes enormously large, new techniques have to be used to turn this data into valuable information and actionable knowledge so that appropriate actions can be taken accordingly. Sometimes it is usual to find that the data needed to be analyzed to produce report are scattered throughout different operational States and jurisdictions of Nigeria and must first be carefully integrated. Moreover, observations show that the process required to extract the existing data from each operational system demand so much of the system resources such that the IT professional must wait until nonoperational hours before running targeted queries required for producing operational reports. These delays are not only time-consuming and frustrating for both the IT professionals and the decision-makers they are dangerous for the sector whose primary task is to control crime spread and explosion. It should be noted that when such operational reports are finally produced, they may not be relied upon, because the data use in producing them many a times are inconsistent, inaccurate, or obsolete. This paper therefore highlights the increasing growing need for Data integration, Data warehouse and Data mining as ways to improve the operations of principal actors within the prisons sector of Nigeria. The paper explains what these Data management techniques mean and entail, and furthermore suggests ways to effectively leverage the techniques to help detect existing crime patterns and speed up the process of solving crimes. Keywords: Crime-data, data mining, data mining techniques, data warehouse, data integratio

A Phase Approach for Adopting Private Clouds as a Collaborative Platform for Nigerian Universities

Cloud computing is creating a new era for information technology by providing a set of services that appears to have infinite capacity, immediate deployment and high availability at trivial cost. It is the result of the evolution of computing and communications technology from a high-value asset to a simple commodity. In this evolution, the focus shifts from the concept of computing as a physical thing to computing as a service, like electricity, that is accessible from the nearest network connection. An organization, which is under increasing pressure to provide computing services at the lowest possible cost, can choose either public or private clouds to meet these needs. However, driven by concerns over security, regulatory compliance, control over quality of service, and long-term costs, many organizations choose internal private clouds. Private clouds provide the same cost and flexibility benefits as public clouds and also enable an organization to control the quality of service delivered to their users. In addition, private clouds allow an organization to better secure data and meet governance regulations which is usually a major concern when using public clouds. Many universities spend huge amount of money yearly on ICT infrastructure.  About ninety percent of ICTs budgets are consumed by computing requirements that can be centralized and standardized enabling one to do more with less resource. This paper tries to make a ca se for the private cloud as a better platform for collaboration among the Nigerian universities and to propose a safe strategy for migration into the private cloud. Keywords: Cloud Computing, Private Cloud, Public Cloud, Cloud Service Models, Cloud Characteristic

Algorithmic Framework for Frequent Pattern Mining with FP-Tree

The FP-tree algorithm is currently one of the fastest approaches to frequent item set mining. Studies have also shown that pattern-growth method is one of the most efficient methods for frequent pattern mining. It is based on a prefix tree representation of the given database of transactions (FP-tree) and can save substantial amounts of memory for storing the database. The basic idea of the FP-growth algorithm can be described as a recursive elimination scheme which is usually achieved in the preprocessing step by deleting all items from the transactions that are not frequent. In this study, a simple framework for mining frequent pattern is presented with FP-tree structure which is an extended prefix-tree structure for mining frequent pattern without candidate generation, and less cost for better understanding of the concept for inexperienced data analysts and other organizations interested in association rule mining. Keywords: Association Rule, Frequent Pattern Mining, Apriori Algorithm, FP-tre

Pre-operative pulmonary assessment and risk factors for post-operative pulmonary complications in elective abdominal surgery in Nigeria

Background and Objectives: Post-operative pulmonary complications (PPCs) are recurring causes of rising morbidity and mortality in surgeries. This study sought to evaluate pre-operative risk factors for PPCs in abdominal surgerypatients in Nigeria.Methodology: This was a prospective study in patients booked for surgery in 2014. Biodata, medical his tory, pre-operative respiratory and cardiovascular examination findings, body mass index, serum albumin, serum urea, ventilatory function, chest x-rays and oxygen saturation were obtained. The association between pre-operative variables and PPCs was determined.Results: The pre-operative spirometry was predominantly restrictive (62%). Overall, the prevalence of PPCs was 52%. This included non-productive cough (14%), isolated productive cough (10%), productive cough with abnormal chest finding (16%), pneumonia (8%), pleural effusion (5%), ARDS (2%). Percentage predicted FEV1 and FVC were lower in participants with PPCs. (p= 0.03 and p=0.01respectively). Pre-operative cough, shortness of breath and consolidation were associated with PPCs (p< 0.05). Post-operative respiratory rate and pulse rate in participants with PPCs were higher than the values in those without PPCs (p=0.03 and p=0.05).Conclusion: The prevalence of PPCs was high in this study. Pre-operative cough, shortness of breath, consolidation, abnor- mally low percentage predicted FEV1 and FVC were associated with PPCs.Keywords: Post-operative pulmonary complications, pre-operative assessment, risk factors, cough, shortness of breath, consol- idation, pneumonia, elective abdominal surgeries, Nnewi, Nigeria

Pre-operative pulmonary assessment and risk factors for post-operative pulmonary complications in elective abdominal surgery in Nigeria

Background and Objectives: Post-operative pulmonary complications (PPCs) are recurring causes of rising morbidity and mortality in surgeries. This study sought to evaluate pre-operative risk factors for PPCs in abdominal surgerypatients in Nigeria. Methodology: This was a prospective study in patients booked for surgery in 2014. Biodata, medical his tory, pre-operative respiratory and cardiovascular examination findings, body mass index, serum albumin, serum urea, ventilatory function, chest x-rays and oxygen saturation were obtained. The association between pre-operative variables and PPCs was determined. Results: The pre-operative spirometry was predominantly restrictive (62%). Overall, the prevalence of PPCs was 52%. This included non-productive cough (14%), isolated productive cough (10%), productive cough with abnormal chest finding (16%), pneumonia (8%), pleural effusion (5%), ARDS (2%). Percentage predicted FEV1 and FVC were lower in participants with PPCs. (p= 0.03 and p=0.01respectively). Pre-operative cough, shortness of breath and consolidation were associated with PPCs (p<0.05). Post-operative respiratory rate and pulse rate in participants with PPCs were higher than the values in those without PPCs (p=0.03 and p=0.05). Conclusion: The prevalence of PPCs was high in this study. Pre-operative cough, shortness of breath, consolidation, abnormally low percentage predicted FEV1 and FVC were associated with PPCs. DOI: https://dx.doi.org/10.4314/ahs.v19i1.51 Cite as: Ufoaroh CU, Ele PU, Anyabolu AE, Enemuo EH, Emegoakor CD, Okoli CC, et al. Pre-operative pulmonary assessment and risk factors for post-operative pulmonary complications in elective abdominal surgery in Nigeria. Afri Health Sci. 2019;19(1). 1745-1756. https:// dx.doi. org/10.4314/ ahs. v19i1.5

Population pharmacokinetic analysis and pharmacogenetics of raltegravir in HIV-positive and healthy individuals

The objectives of this study were to characterize raltegravir (RAL) population pharmacokinetics in HIV-positive (HIV(+)) and healthy individuals, identify influential factors, and search for new candidate genes involved in UDP glucuronosyltransferase (UGT)-mediated glucuronidation. The pharmacokinetic analysis was performed with NONMEM. Genetic association analysis was performed with PLINK using the relative bioavailability as the phenotype. Simulations were performed to compare once- and twice-daily regimens. A 2-compartment model with first-order absorption adequately described the data. Atazanavir, gender, and bilirubin levels influenced RAL relative bioavailability, which was 30% lower in HIV(+) than in healthy individuals. UGT1A9*3 was the only genetic variant possibly influencing RAL pharmacokinetics. The majority of RAL pharmacokinetic variability remains unexplained by genetic and nongenetic factors. Owing to the very large variability, trough drug levels might be very low under the standard dosing regimen, raising the question of a potential relevance of therapeutic drug monitoring of RAL in some situations

Prospective observational cohort study on grading the severity of postoperative complications in global surgery research

Background The Clavien–Dindo classification is perhaps the most widely used approach for reporting postoperative complications in clinical trials. This system classifies complication severity by the treatment provided. However, it is unclear whether the Clavien–Dindo system can be used internationally in studies across differing healthcare systems in high- (HICs) and low- and middle-income countries (LMICs). Methods This was a secondary analysis of the International Surgical Outcomes Study (ISOS), a prospective observational cohort study of elective surgery in adults. Data collection occurred over a 7-day period. Severity of complications was graded using Clavien–Dindo and the simpler ISOS grading (mild, moderate or severe, based on guided investigator judgement). Severity grading was compared using the intraclass correlation coefficient (ICC). Data are presented as frequencies and ICC values (with 95 per cent c.i.). The analysis was stratified by income status of the country, comparing HICs with LMICs. Results A total of 44 814 patients were recruited from 474 hospitals in 27 countries (19 HICs and 8 LMICs). Some 7508 patients (16·8 per cent) experienced at least one postoperative complication, equivalent to 11 664 complications in total. Using the ISOS classification, 5504 of 11 664 complications (47·2 per cent) were graded as mild, 4244 (36·4 per cent) as moderate and 1916 (16·4 per cent) as severe. Using Clavien–Dindo, 6781 of 11 664 complications (58·1 per cent) were graded as I or II, 1740 (14·9 per cent) as III, 2408 (20·6 per cent) as IV and 735 (6·3 per cent) as V. Agreement between classification systems was poor overall (ICC 0·41, 95 per cent c.i. 0·20 to 0·55), and in LMICs (ICC 0·23, 0·05 to 0·38) and HICs (ICC 0·46, 0·25 to 0·59). Conclusion Caution is recommended when using a treatment approach to grade complications in global surgery studies, as this may introduce bias unintentionally