AFRICAN JOURNAL OF SCIENCE, TECHNOLOGY AND ENGINEERING (AJSTE)

Heavy Metals in Refinery Wastewater: Assessment and Treatment Using Diatomaceous Earth

Oyugi C. A., Ohowa B., Shee A — Wed, 07 Feb 2024 07:56:37 +0100

In refining crude oil, freshwater is applied in distillation, hydration, desalination, system cooling, firefighting and other cleaning operations. The Kenya Petroleum Refineries Limited consumes huge quantities of freshwater daily for various applications leading to generation of contaminated effluents. The effluents contain a cocktail of contaminants such as aliphatic hydrocarbons, polycyclic aromatic compounds, dissolved gases such as Hydrogen Sulphide like algae, fungi, and heavy metals. Except for heavy metals, the refinery wastewater treatment plant is able to remove most of the other contaminants from the wastewater through a combination of processes including filtration, coagulation, sedimentation, softening, de-aeration, chlorination, desulfurization, bioremediation, and ion-exchange. However, these techniques are expensive, generate huge amounts of sludge, and are also not effective for removal of trace levels of heavy metals. Using inductively coupled plasma coupled with optical emission spectroscopy (ICP-OES), the effluents were found to contain significant levels of Iron, Cadmium, Chromium, Manganese, Nickel, Lead, Vanadium and Zinc. Although the installed wastewater treatment could reduce heavy metals load to trace, effluents storage in the tank farm prior to disposal leads to accumulation of heavy metals over time. Diatomaceous earth (DE) was applied to treat the heavy metals from the tank farm to within allowable limits as recommended by the World Health Organisation. Hence DE should be applied to effluents exiting the wastewater treatment plant prior to storage in the tank farm.

Systematic Literature Review on Application Program Interface -Based Android Malware Detection

Ehoda E., Adebayo O.S., Ismaila I., Ojeniyi J.A., Olalere M — Wed, 07 Feb 2024 08:28:43 +0100

Over the years, various malware detection approaches have been proposed in a bid to address evolving malware threats landscape in android operating system. Systematic literature reviews to analyze these detection approaches have been carried out, but none have been tailored to identifying challenges with android malware detection based on the use of Android program interface (API) features, hence there is no aggregated information on what work has been done by researchers in this area. This research, therefore, presents a systematic literature review on API feature based android malware detection literatures between 2018 to 2022 collected systematically using PRISMA frameworks. This study seeks to identify the challenges faced in android malware detection over the years, methodologies used to address them and limitations of API based feature detection. These useful insights documented in this research will serve as valuable resources which researchers can leverage on to improve the detection of android malware.

Malaria Vector Control: Challenges and Future Strategies

Wed, 07 Feb 2024 00:00:00 +0100

The current demand for the eradication of malaria marks a new-fangled chapter in the antiquity of this illness. This has been brought about by the striking decreases in malaria caused by administration of efficient medications and vector control. However, the emergence of pesticide resistance poses a challenge to this approach. Alternative tools must be developed to continue supporting or potentially replace insecticide-based vector control methods. Long-lasting insecticidal nets (LLINs) and indoor residual spraying (IRS) continue to be the mainstays of the majority of National Malaria Control Programs in Africa, despite the large number of promising control tools tested against mosquitoes. These strategies are not enough to successfully control malaria. While these techniques are successful in lowering malaria incidence, their overall effectiveness in lowering malaria prevalence is often limited. Additionally, efficiency of LLINs and IRS is threatened by the rising rates of pesticide resistance in the targeted mosquito populations. Thus, although larvicidal treatments can be beneficial, using them in rural regions is not advised. To enhance mosquito vector control efforts and improve their quality and delivery, it is important to focus on integrated approaches. Successful malaria eradication requires close collaboration between parasitologists and entomologists, along with a comprehensive evaluation of epidemiological impact of innovative mosquito vector control strategies. This review discusses current malaria vector control strategies and highlights challenges, and promising tools that are expected to contribute to malaria eradication.

Review On Variation In Genetic And Chemical Constituents Of Strychnos Henningsii Populations In Kenya

Wahu K.M. — Wed, 07 Feb 2024 09:27:41 +0100

Strychnos henningsii is an indigenous medicinal plant species widely used in tropical Africa. Studies have revealed that this plant has been used as a remedy for various ailments including rheumatism, gastrointestinal complications, abdominal pains, syphilis, snakebites, diabetes malaria, and arthritis amongst others. Phytochemical and pharmacological studies have identified various compounds such as alkaloids, anthraquinones, cardiac glycosides, chalcones, flavonoids, phenolics, proanthocyanidins, saponins, steroids, tannins and triterpenes from the crude extracts of S. henningsii. These chemical constituents exhibited analgesic, antibacterial, antidiabetic, anti-inflammatory, antioxidant, antiplasmodial, antiprotozoal, antispasmodic as well as cytotoxicity activities. Secondary metabolites are known to aid plants in coping with various environmental stresses. Environmental stress triggers expression of genes for the enzymes involved in biosynthesis of secondary metabolites, many of which have higher medicinal value despite being useful in plant defense mechanisms. This paper is a review on the chemical constituents, pharmacological properties and genetic variation of S henningsii across its geographical range.

Cloud Data Security Audit Report Techniques Using Bat Inspired Algorithm: A Review

Onuja, A. M., Adebayo, O. S, Olalere, M., Aliyu, H. O. — Wed, 07 Feb 2024 09:06:17 +0100

Cloud computing has become an interesting attraction for Information and Communication Technology (ICT) practitioners. It is helping to reduce the cost of procuring computing devices and services. To this end, security attacks have been rising with cloud service providers always having to under-report the prevalence in order not to scare away potential cloud service subscribers. In this review, eighty (80) papers were acquired from reputable academic publications using Google Scholar as the search engine. The eighteen (18) carefully selected from the pool of 80, for review, have a total of seventy-four (74) versions on the internet. Furthermore, the authors agree with the research publications, that there is need to bring on board the client into security breach mitigation strategies, being developed to strengthen cloud data security. Findings from this review, reveals that research interest in cloud data security audit has increased from four (4) papers between 2011 and 2016, to thirteen (13) papers between 2017 and 2022. These existing frameworks and techniques are still being tested to improve performance. This research, therefore, proposed a cloud data security audit report technique using Bat inspired algorithm (CDSART-BA) to improve cloud data security.

Big Data Analytics For Smes' Performance Sustainability In Post-Covid-19 Kenya

Musyoka C., Wanjohi. P. — Wed, 07 Feb 2024 09:20:00 +0100

Small and medium-sized businesses (SMEs) play a critical role in a nation's economy, contributing significantly to its wealth and fostering innovation. Globally, they account for up to half of all jobs and 90% of all businesses. However, SMEs often grapple with limited access to credit from suppliers, compounded by liquidity challenges, decreased sales, and defaults, as supply chains struggle to secure credit. Factors like advance payments, penalties for delayed credit payments, and recurring expenses further exacerbate the vulnerability of Smashing the context of Kenya's post-COVID-19 landscape. This study aimed to explore the potential of Big Data Analytics and Data Science in sustaining SMEs' performance. Drawing from theories such as Complex Adaptive System and Strategic Choice Theory, a descriptive survey design was employed, on a target population of 287 managers of SMEs in each sub County, in Nairobi. Employing a stratified sampling method, a total of 260 respondents were interviewed. Data was analyzed using descriptive statistics, including frequencies, percentages, mean, and standard deviation, while inferential statistics like multiple regression and Pearson correlation were used to examine relationships between variables. The study revealed that Business Intelligence, with a mean score of 3.9 (std. dv = 0.851), and Machine Learning, with a mean of 3.7 (std. dv = 0.928), both had a positive impact on SMEs' sustainability, with an overall average mean of 3.8 (std. dv = 0.8895). Similarly, Data Analytics, comprising Predictive Analytics (mean = 3.73, std. dv = 0.850) and Prescriptive Analytics (mean = 3.85, std. dv = 0.684), positively influenced SMEs' performance, with an average mean of 3.79 (std. dv = 0.767). These findings underscore the potential of Data Science drivers like Business Intelligence and Machine Learning in helping SMEs tackle unforeseen challenges in competitiveness. The study further highlights the importance of implementing a robust legal framework to safeguard data in the context of Data Analytics, particularly in predictive and prescriptive analysis, as a means to enhancing SMEs' performance, survival, and growth in the post-COVID-19 era.