The case for validating ADDIE model as a digital forensic model for peer to peer network investigation

Rapid technological advancement can substantially impact the processes of digital forensic investigation and present a myriad of challenges to the investigator. With these challenges, it is necessary to have a standard digital forensic framework as the foundation of any digital investigation. State-of-the-art digital forensic models assume that it is safe to move from one investigation stage to the next. It guides the investigators with the required steps and procedures. This brings a great stride to validate a non-specific framework to be used in most digital investigation procedures. This paper considers a new technique for detecting active peers that participate in a peer-to-peer (P2P) network. As part of our study, we crawled the μTorrent P2P client over ten days in different instances while logging all participating peers. We then employed digital forensic techniques to analyse the popular users and generate evidence within them with high accuracy. We evaluated our approach against the standard Analysis, Design, Development, Implementation, and Evaluation (ADDIE) model for the digital investigation to achieve the credible digital evidence presented in this paper. Finally, we presented a validation case for the ADDIE model using the United States Daubert Test and the United Kingdom’s Forensic Science Regulator Guidance – 218 (FSR-G-218) and Forensic Science Regulator Guidance – 201 (FSR-G-201) to formulate it as a standard digital forensic model

Labour and Labour Crisis in Nigerian: The Implication of the Structural Adjustment Programme

This Paper Labour and Labour Crises in Nigeria: The implication of structural adjustment programme, its aims at analyzing the effects of the structural adjustment programme (SAP) on the Labour and Labour crises in Nigeria. Through the economic policy programme, which among other objectives of the programmes includes, the privatization of public investment, retrenchment of Staffs, devaluation of the naira, deregulation of interest rates, reduction on government expenditure and Labour market adjustment. This paper also examine the Nigerian economy before the introduction of the Structural adjustment programme (SAP) which also give an insight about the Nigerian drawing rights from 1970 where the 90 percent of the nation foreign exchange earnings and more than 80 percent of the country’s population (53 million) were gaily employed by the agricultural sector. However, with discovery of Oil in the 70s Agricultural contribution to GDP started to decline from about 40 percent, GDP in the early 1970s to 20 percentage in the early 1980s. This decline resulted into untold sequences such as increased dependence on food imports. Now the government source of income solidly depend on Oil with 90 percent of the country exports earnings. As such revenue fell from $27.4 billion in 1950 to$ 11.1 billion in 1982. In the same vein, external reserve dropped from $757 billion to$5.5 billion. These effects resulted into external debt and massive borrowing. In order to find a solution to the problems the government decided to adopt the Structural adjustment programme so that it will dealth with the economic problems as at that time. This also brought about the idea of shifting the resources from undesired sector to more desire ones. Labour in particular is required to shift accordingly from Urban to Rural areas. Government intends to pursue this by applying relative price instrument like devaluation, freeing of urban wages and removal of subsidy. But unfortunately, this result was could not be achieved because of implicit model in pursuing the said objective is defective in many ways. The consequence of these leads to retrenchment of workers where this is not possible, workers were denied their basic pay for months, the Nigeria wage earner was left to fend foe his survival in order to sustain his life and those of his dependents. As such this leads to strike and counter strike which the Labour Union sought to be the only means of obtaining Union rights. Even though this was not effective, since the industries can not affords the exchange rate for their raw materials etc

Enhancing the Performance of Heart Disease Prediction from Collecting Cleveland Heart Dataset using Bayesian Network

Cardiovascular diseases are diseases affecting the general well-being of the heart. It is responsible for many deaths annually. Consequently, this paper focuses on improving the performance of heart disease prediction by collecting Cleveland heart datasets from the University of California Irvine machine learning repository. Different feature subset selection is performed on the dataset and modeled using machine learning models such as logistic regression, K-Nearest neighbor, Naïve Bayes and Bayesian Network. The proposed method achieved an accuracy of 88.53%. Based on the results obtained, we observed feature reduction on the Cleveland dataset could enhance the performance of the Bayesian network

Kawasaki disease associated with streptococcal infection and facial nerve palsy: a case report

Kawasaki disease (mucocutaneous lymph node syndrome), an acute febrile vasculitis of childhood that affects medium and small-sized arteries, is uncommonly reported in the West African sub[1]region. Its diagnosis relies on the presence of a constellation of clinical signs which could mimic or coexist with infectious viral or bacterial agents, thereby requiring a high index of suspicion. Case presentation: We report a two-year, ten months-old boy who presented with prolonged high-grade fever for over 3 three weeks; non-purulent conjunctivitis, unilateral cervical lymphadenopathy, cracked lips, reddish tongue, diffuse oedema, erythema of his palms and soles; skin desquamation over the tips of his digits and left-sided facial nerve palsy. He had leukocytosis, thrombocytopenia, and elevated inflammatory markers. Throat swab yielded Streptococcus pyogenes species; however, serial echocardiography was unrevealing. He was managed with aspirin, steroids, bed rest, and antibiotics (based on culture sensitivity), but intravenous immunoglobulin (IVIG) was not readily available and therefore was not administered. His inpatient clinical course showed fever persisting into the second week of inpatient management that gradually became undulating by the third week before lysing. Conclusion: The rare complication of facial nerve palsy is highlighted, while the evidence for acute bacterial infection posed further diagnostic challenges in this child with clinical features of Kawasaki disease. The unavailability of IVIG also portends a prolonged course for the acute stages, which are largely unresponsive to antipyretics and antibiotics. The importance of long-term follow-up for potential coronary artery aneurysms in the face of risk factors is further emphasized

Structural Characterization of Lithium Doped Nzp Na1-xLixZr(PO4)3(x=0.00-0.75)

Sodium zirconium phosphate (NZP) of composition Na1-xLixZr2(PO4)3 (x=0.0-0.75) have been synthesized using solid state reaction, with a view to minimizing the ZrO2 second phase normally present .The compositions have been characterized by XRD and SEM for phase composition, lattice parameters and density. No ZrO2 second phase was detected in some of the compositions, rather NasZr(PO4)3 and the density showed a systematic decrease with increase of Li. All The compositions belong to the rhombohedral crystal system and were indexed based on hexagonal lattice structure. The density of the composition x=0.00 as calculated from the XRD data is 3.02g/cm3.The grain sizes of the compositions are in the range 1-2&#956m, 2-5&#956m, 3-7 &#956m and 2&#956m for x=0,0.25,0.5 and 0.75, respectively. Keywords: solid state synthesis, NZP, XR

Comprehensive analysis of security issues in cloud-based Internet of Things: A survey

The Internet of Things (IoT )has emerged as the largest computing platform, enabling IoT devices to sense real-world conditions such as temperature, humidity, pressure, and cloud prediction. However, the security of IoT systems is crucial due to their direct impact on human life. With the expansion of processing and communication capabilities to numerous devices, IoT has become a vast network where connectivity is ubiquitous. This paper focuses on the security issues of cloud-based IoT, specifically access control, network security, data security, and privacy, which are the four main components of cloud-based IoT. By analyzing and comparing existing research papers on security in cloud IoT and IoT in general, we identify proposed solutions. Most researchers have concentrated on a single component, while only a few have addressed two components. Consequently, our research aims to bridge the gap in Cloud IoT security by focusing on more than two components. We propose the utilization of methods such as Machine Learning and blockchain to enhance security, drawing on the strengths highlighted in previous works. Our future focus will involve exploring potential attacks in cloud IoT and developing a comprehensive method that encompasses atleast three security components of cloud IoT security

Adaptive Load Frequency Control of Nigerian Hydrothermal System Using Unsupervised and Supervised Learning Neural Networks

This work presents a novel load frequency control design approach for a two-area power system that relies on unsupervised and supervised learning neural network structure. Central to this approach is the prediction of the load disturbance of each area at every minute interval that is uniquely assigned to a cluster via unsupervised learning process. The controller feedback gains corresponding to each cluster center are determined using modal control technique. Thereafter, supervised learning neural network (SLNN) is employed to learn the mapping between each cluster center and its feedback gains. A real time load disturbance in either or both areas activates the appropriate SLNN to generate the corresponding feedback gains. The effectiveness of the control framework is evaluated on the Nigerian hydrothermal system. Several far-reaching simulation results obtained from the test system are presented and discussed to highlight the advantages of the proposed approach

Workflow for building and calibrating 3D pre-injection and 4D geomechanics modelling to assess caprock and fault integrity for geologic CO2 storage

Carbon capture and storage (CCS) has been established as a viable technology for the mitigation of climate change caused mainly by anthropogenic greenhouse gas emissions into the atmosphere. Ever since the publication of the special report on CCS by the Intergovernmental Panel on Climate Change in 2005, there has been an increased research and development in all areas of CCS. Some of these research involves use of numerical methods and models for optimizing storage and ensuring effective long term containment. In this paper, we propose a workflow for building and calibrating 3D preinjection and 4D geomechanics modelling to assess caprock and fault integrity for geologic carbon dioxide storage. The workflow presented here describes a seamless end -to-end process which combines a transparent flow of data with an easy-to-use graphical user interface. The workflow can conduct 3D static and 4D flow-, pressure-, and temperature-coupled calculations for rock deformations, failure and stresses. In highly heterogeneous and complex models, the workflow is capable of modelling multiple hundred faults, and multiple thousand discrete fractures. It allows the geological model, despite its high degree of complexity to be maintained throughout the geomechanical analyses process

Vaccination with newcastle disease vaccines strain i2 and lasota in commercial and local chickens in Plateau State Nigeria

Vaccination trials and comparative immunogenicity study using Newcastle disease vaccine strain I2 (NDVI2) and NDV La Sota administered to commercial and local chickens through intraocular (i/o), intramuscular (i/m), drinking water (dw), untreated sorghum, parboiled sorghum, sorghum coated with gum Arabic or commercial chick mash feed as vaccine carriers was conducted. Newcastle disease vaccine strain I2 and NDV La Sota vaccines provided protection to commercial and local chickens vaccinated through i/o, i/m or dw. No significant difference (P.0.05) was observed in the antibody titre of commercial or local chickens vaccinated with either NDVI2 or NDV La Sota vaccines administered via commercial feed, parboiled sorghum, parboiled sorghum coated with gum Arabic and untreated sorghum. NDVI2 or NDV La Sota vaccines administered through commercial feed, parboiled sorghum, parboiled sorghum coated with gum Arabic and untreated sorghum gave no or limited protection (0-22%) to the birds when challenged with a local strain of velogenic viscerotropic Newcastle disease virus Kudu 113 strain. It was concluded that the vaccine carriers used in this study were not suitable for delivery of NDVI2 or NDVS La Sota vaccines to local or commercial chickens

Prevalence of gastrointestinal parasitic helminths among school-aged children from two selected primary schools in Mubi-north L.G.A., Adamawa State, Nigeria.

Infections involving parasitic helminths constitute a major health challenge especially as it affects children from rural and sub-urban communities of developing countries. It is also reported to be an influential cause of morbidity in children of school age who harbour the peak burden and the damaging effect of the worm invasion. Objectives: This was a cross-sectional institutional-based study aimed at investigating the prevalence of gastrointestinal parasitic helminths from two selected primary schools in Mubi-North LGA, Adamawa State. Methodology: Faecal samples were collected from 150 pupils of Staff Primary School, Federal Polytechnic Mubi, and Mubi I Primary School Lokuwa and were examined for eggs/larvae of intestinal helminths using direct smear and formal ether concentration methods. Results: The results showed an overall prevalence of 22.0% consisting of four species of helminthic parasites which includes Ascaris lumbricoides, Ancylostoma duodenale, Taenia solium, and Schistosoma mansoni. Staff Primary School had the highest occurrence of S. mansoni (5.3%), while Mubi I Primary School had the highest occurrence of A. duodenale (10.7%), A. lumbricoides(8.0%), and T. solium (5.3%). On the overall, Ancylostoma duodenale (10.0%) was the most predominant parasite, while the least was T. solium (3.3%). The result of the odd ratio and chi-square (OR=1.263, CI=0.582-2.742, P=0.554) showed that pupils in Mubi I Primary School are 1.263 times more likely to be infected with gastrointestinal helminths than pupils of Staff Primary School, Federal Polytechnic Mubi, but with no statistical difference. The relationship between gender and infection with gastrointestinal helminthic parasites (OR =1.017, 95% CI = 0.456-2.269, P=0.967) showed that females stand a higher chance of being infected with gastrointestinal helminths than their male counterparts, but the difference is not significant. The highest prevalence of A. lumbricoides and S. mansoni was observed among males, while the highest prevalence of Ancylostoma duodenale and T. Solium was observed among females. The age group 8-10 years had the highest prevalence of gastrointestinal parasites, but with no statistical difference from other age brackets (P=0.514). Conclusion: Despite low prevalence, there is, the need for urgent development of high-quality preventive and control measures that is compliant with the endemic or highly prevalent communities