Comparative Analysis of Selected Filtered Feature Rankers Evaluators for Cyber Attacks Detection

An increase in global connectivity and rapid expansion of computer usage and computer networks has made the security of the computer system an important issue with the industries and cyber communities being faced with new kinds of attacks daily The high complexity of cyberattacks poses a great challenge to the protection of cyberinfrastructures Confidentiality Integrity and availability of sensitive information stored on it Intrusion detection systems monitors network traffic for suspicious Intrusive activity and issues alert when such activity is detected Building Intrusion detection system that is computationally efficient and effective requires the use of relevant features of the network traffics packets identified by feature selection algorithms This paper implemented K-Nearest Neighbor and Na ve Bayes Intrusion detection models using relevant features of the UNSW-NB15 Intrusion detection dataset selected by Gain Ratio Information Gain Relief F and Correlation rankers feature selection technique

Design of Machine Learning Framework for Products Placement Strategy in Grocery Store

The well-known and most used support-confidence framework for Association rule mining has some drawbacks when employ to generate strong rules, this weakness has led to its poor predictive performances. This framework predict customers buying behavior based on the assumption of the confidence value, which limits its competent at making good business decision. This work presents a better Association Rule Mining conceptualized framework for mining previous customers transactions dataset of grocery store for the optimal prediction of products placement on the shelves, physical shelf arrangement and identification of products that needs promotion. Sampled transaction records were used to demonstrate the proposed framework. The proposed framework leverage on the ability of lift metric at improving the predictive performance of Association Rule Mining. The Lift discloses how much better an association rule is at predicting products to be placed together on the shelve rather than assuming. The proposed conceptualized framework will assist retailers and grocery stores owners to easily unlock the latent knowledge or patterns in their large day to day stored transaction dataset to make important business decision that will make them competitive and maximized their profit margin

Computational Efficiency Analysis of Customer Churn Prediction Using Spark and Caret Random Forest Classifier

Today’s businesses are buying into technological advancement for productivity, profit maximization and better service delivery. Meanwhile technology as also brought about data coming in at an alarming rate in which businesses need to re-strategize how these data are being handled for them to retain ability to turn them to value. Traditional data mining techniques has proofed beyond doubt that data can be harnessed and turn into value for business growth. But the era of large scale data is posing a challenge of computational efficiency to this traditional approach. This paper therefore address this issue by under-studying a big data analytics tool-Spark with a data mining technique Caret. A churn Telecom dataset was used to analyse both the computational and performance metrics of the two approaches using their Random Forest (RF) classifier. The Classifier was trained with same the train set partitioning and tuning parameters. The result shows that Spark-RF is computational efficient with execution time of 50.25 secs compared to Caret-RF of 847.20 secs. Customer churning rate could be minimized if proper management attention and policy is paid to tenure (ShortTenure), Contract, InternetService and PaymentMethod as the variable importance plot and churn rate count mechanism confirm that. The Classifier accuracy was approximately 80% for both implementation. Keywords: Spark, Caret, Random Forest, Churn, accurac

COVID-19 Pandemic: Perception, Practices and Preparedness in Nigeria

Since Coronavirus disease 19 (COVID-19) pandemic was declared a public health emergency of international concern by the World Health Organization (WHO) on the 30th of January, 2020. Nigeria, with 343 cases and 10 deaths as at April 14, 2020 is classified as one of the countries at high risk of importation of the disease from China. The ability to limit and control local transmission after importation depends on the application and execution of strict measures of detection, prevention and control. The initial response of some percentage of the population was of doubt due to the ignorance of the far-reaching effect of the virus. More than 1,700 leaders of religious groups and communities in all 36 States and FCT were therefore sensitized to increase awareness level and consequences of COVID-19 among the populace. Major response activities were initiated before the first case was reported and were upgraded within weeks after the number of cases began to rise. Based on previous experience of perception, and awareness of other viral disease outbreaks, COVID-19 infection prevention and control interventions recommended by WHO are yet to be fully entrenched in the Nigerian public health system in order to reduce the general risk of contracting SARS-CoV-2 from infected individuals. There is therefore the need to execute strict measures of detection, prevention and control and drive compliance with the Nigeria Centre for Disease Control (NCDC) and WHO guidelines in Nigeria

Factors Associated with Biofilm Persistence on Different Surfaces, Spread and Pathogenicity

The conglomeration of microbial life on a self-produced extracellular polysaccharide (EPS) matrix for mutual co-existence and protection against external aggression and adverse environmental conditions best describe biofilms. This community of microorganisms confers a number of survival and nutritional benefits to members while at the same time portend great ecological and health concern. Biofilms can form on virtually any surface; terrestrial, aquatic, plants, animals and on medical devices and implants. The ability of biofilms to disperse from the parental stalk ensures continuous survival and spread within their ecological niche. Biofilm organisms therefore possess unique survival mechanisms over their plancktonic form and have contributed to our understanding of the mechanisms of pathogenicity of infectious microorganisms. This review highlights trends in the understanding of biofilms and emphasized their health significanc

Nanochitosan derived from marine bacteria

Nanochitosans are polysaccharides produced by the alkalescent deacetylation of chitin and comprise a series of 2‐deoxy‐2 (acetylamino) glucose linked by ß‐(1‐4) glycosidic linkages. These are naturally formed from the deacetylation of shellfish shells and the exoskeleton of aquatic arthropods and crustaceans. Reports of chitosan production from unicellular marine bacteria inhabiting the sea, and possessing distinct animal‐ and plant‐like characteristics abound. This capacity to synthesize chitosan from chitin arises from response to stress under extreme environmental conditions, as a means of survival. Consequently, the microencapsulation of these nanocarriers results in new and improved chitosan nanoparticles, nanochitosan. This nontoxic bioactive material which can serve as an antibacterial agent, gene delivery vector as well as carrier for protein and drug release as compared with chitosan, is limited by its nonspecific molecular weight and higher composition of deacetylated chitin. This chapter highlights the biology and diversity of nanochitosan‐producing marine bacteria, including the factors influencing their activities, survival, and distribution. More so, the applications of marine bacterial nanochitosans in transfection and gene delivery; wound healing and drug delivery; feed supplement development and antimicrobial activity are discussed

Significance of African Diets in Biotherapeutic Modulation of the Gut Microbiome

Diet plays an essential role in human development and growth, contributing to health and well-being. The socio-economic values, cultural perspectives, and dietary formulation in sub-Saharan Africa can influence gut health and disease prevention. The vast microbial ecosystems in the human gut frequently interrelate to maintain a healthy, well-coordinated cellular and humoral immune signalling to prevent metabolic dysfunction, pathogen dominance, and induction of systemic diseases. The diverse indigenous diets could differentially act as biotherapeutics to modulate microbial abundance and population characteristics. Such modulation could prevent stunted growth, malnutrition, induction of bowel diseases, attenuated immune responses, and mortality, particularly among infants. Understanding the associations between specific indigenous African diets and the predictability of the dynamics of gut bacteria genera promises potential biotherapeutics towards improving the prevention, control, and treatment of microbiome-associated diseases such as cancer, inflammatory bowel disease, obesity, type 2 diabetes, and cardiovascular disease. The dietary influence of many African diets (especially grain-base such as millet, maize, brown rice, sorghum, soya, and tapioca) promotes gut lining integrity, immune tolerance towards the microbiota, and its associated immune and inflammatory responses. A fibre-rich diet is a promising biotherapeutic candidate that could effectively modulate inflammatory mediators’ expression associated with immune cell migration, lymphoid tissue maturation, and signalling pathways. It could also modulate the stimulation of cytokines and chemokines involved in ensuring balance for long-term microbiome programming. The interplay between host and gut microbial digestion is complex; microbes using and competing for dietary and endogenous proteins are often attributable to variances in the comparative abundances of Enterobacteriaceae taxa. Many auto-inducers could initiate the process of quorum sensing and mammalian epinephrine host cell signalling system. It could also downregulate inflammatory signals with microbiota tumour taxa that could trigger colorectal cancer initiation, metabolic type 2 diabetes, and inflammatory bowel diseases. The exploitation of essential biotherapeutic molecules derived from fibre-rich indigenous diet promises food substances for the downregulation of inflammatory signalling that could be harmful to gut microbiota ecological balance and improved immune response modulation

Chapter 21 - Utilization of nanochitosan in the sterilization of ponds and water treatment for aquaculture

Water pollution constitutes the leading cause of infant mortality, neonatal deformities, and shrinkage of man’s average life expectancy. Pollutants come from point and nonpoint sources; and water pollution arises from the discharge of wastewater containing undesirable impurities used for domestic, agricultural, and industrial purposes. More so, high nutrient and wastewater runoffs from fish production systems contribute to the fouling and eutrophication of recipient water bodies. Hence, aquaculture which is inextricably linked to the natural environment is challenged by the dearth of appropriate water quantity and quality, militating against fish, and fishery production. Nanochitosans as polysaccharides produced by the alkalescent deacetylation of chitin, comprise a series of 2-deoxy-2 (acetylamino) glucose linked by ß-(1-4) glycosidic linkages. They are naturally formed from the deacetylation of shellfish shells and exoskeletons of aquatic arthropods and crustaceans. The unique attributes of chitin confer a wide range of biotechnological applications on the polymer, observed in flocculation as a wastewater treatment and purification route initiated by chitosan. This chapter highlights nanochitosan properties of aquaculture relevance; and elucidates the purification potentials of nanochitosan, compared to inorganic coagulants and organic polymeric flocculants. Effects of chitosan on contaminants and microorganisms, as well as applications in fish pathogens detection, fish disease diagnosis, and control are discussed

Utilization of nanochitosan for enzyme immobilization of aquatic and animal-based food packages

Studies have identified the properties of enzymes, functionalized molecules, and compounds in food industry applications as edible coatings and encapsulations, that assure prolonged food quality and standards. These molecules present benefits of longer shelf-life by delayed deterioration and inhibition of the proliferation of spoilage and mycotoxigenic microorganisms. However, challenges of reduced nutrient levels, miniaturized size, and low chemical stability remain concerning. Chitosan polymers naturally formed from the deacetylation of shellfish shells and exoskeletons of aquatic arthropods and crustaceans offer improved benefits when functionalized into nanoparticles as nanochitosans. These polysaccharides produced by the alkalescent deacetylation of chitin, comprise a series of 2-deoxy-2 (acetylamino) glucose linked by ß-(1-4) glycosidic linkages. This chapter considers the health impacts and

Comparative Analysis of Selected Filtered Feature Rankers Evaluators for Cyber Attacks Detection

An increase in global connectivity and rapid expansion of computer usage and computer networks has made the security of the computer system an important issue; with the industries and cyber communities being faced with new kinds of attacks daily. The high complexity of cyberattacks poses a great challenge to the protection of cyberinfrastructures, Confidentiality, Integrity, and availability of sensitive information stored on it. Intrusion detection systems monitors’ network traffic for suspicious (Intrusive) activity and issues alert when such activity is detected. Building Intrusion detection system that is computationally efficient and effective requires the use of relevant features of the network traffics (packets) identified by feature selection algorithms. This paper implemented K-Nearest Neighbor and Naïve Bayes Intrusion detection models using relevant features of the UNSW-NB15 Intrusion detection dataset selected by Gain Ratio, Information Gain, Relief F and Correlation rankers feature selection techniques