A Gender Recognition System Using Facial Images with High Dimensional Data

Gender recognition has been seen as an interesting research area that plays important roles in many fields of study. Studies from MIT and Microsoft clearly showed that the female gender was poorly recognized especially among dark-skinned nationals. The focus of this paper is to present a technique that categorise gender among dark-skinned people. The classification was done using SVM on sets of images gathered locally and publicly. Analysis includes; face detection using Viola-Jones algorithm, extraction of Histogram of Oriented Gradient and Rotation Invariant LBP (RILBP) features and trained with SVM classifier. PCA was performed on both the HOG and RILBP descriptors to extract high dimensional features. Various success rates were recorded, however, PCA on RILBP performed best with an accuracy of 99.6% and 99.8% respectively on the public and local datasets. This system will be of immense benefit in application areas like social interaction and targeted advertisement

Handcrafted and Transfer Learned Feature Techniques for Vehicle Make and Model Recognition on Nigerian Road

The vehicle makes and model recognition (VMMR) is a challenging task due to the wide range of vehicle categories and similarities between different classes. Studies have shown that works have recognized vehicles of different countries' make and models. Popular vehicles on Nigerian roads may include products like; Toyota, Honda, Peugeot, Benz, Innoson Vehicle Manufacturing (IVM), etc. The VMMR is important in the intelligent transport system hence, this paper presents a handcrafted and transfer learning model to detect stationary vehicles and classify them based on brand, make, and model. A new dataset was introduced consisting of selected images of popular brands of vehicles driven on Nigerian roads. Framework for a vehicle make and model recognition was developed by extracting features using EfficientNet and HOG models and evaluated on the locally gathered datasets. For classification, a linear Support Machine Vector (SVM) was used. Experimental results showed 94.5% on HOG, 97% with EfficientNet, and 98.1% accuracy when HOG and EfficientNet features were concatenation.  The proposed concatenated model outperformed HOG and EfficientNet extracted features by providing higher accuracy and confusion matrix with the highest number of classified images. The study shows the advantages of the proposed model in terms of its accuracy in terms of identifying the vehicle make and model

Perspective on Dark-Skinned Emotion Recognition using Deep-Learned and Handcrafted Feature Techniques

Image recognition has been widely used in various fields of applications such as human—computer interaction, where it can enhance fluency, accuracy, and naturalness in interaction. The need to automate the decision on human expression is high. This paper presents a technique for emotion recognition and classification based on a combination of deep-learned and handcrafted features. Residual Network (ResNet) and Rotation Invariant Local Binary Pattern (RILBP) features were combined and used as features for classification. The aim is to classify, identify, and make judgment on facial images from dark-skinned facial images. Facial Expression Recognition 2013 (FER2013) and self-captured dark-skinned datasets were used for the experiment and validated. The result showed 93.4% accuracy on FER dataset and 95.5% on self-captured dataset, which proved the efficiency of the proposed model

The evolving SARS-CoV-2 epidemic in Africa: Insights from rapidly expanding genomic surveillance

INTRODUCTION Investment in Africa over the past year with regard to severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) sequencing has led to a massive increase in the number of sequences, which, to date, exceeds 100,000 sequences generated to track the pandemic on the continent. These sequences have profoundly affected how public health officials in Africa have navigated the COVID-19 pandemic. RATIONALE We demonstrate how the first 100,000 SARS-CoV-2 sequences from Africa have helped monitor the epidemic on the continent, how genomic surveillance expanded over the course of the pandemic, and how we adapted our sequencing methods to deal with an evolving virus. Finally, we also examine how viral lineages have spread across the continent in a phylogeographic framework to gain insights into the underlying temporal and spatial transmission dynamics for several variants of concern (VOCs). RESULTS Our results indicate that the number of countries in Africa that can sequence the virus within their own borders is growing and that this is coupled with a shorter turnaround time from the time of sampling to sequence submission. Ongoing evolution necessitated the continual updating of primer sets, and, as a result, eight primer sets were designed in tandem with viral evolution and used to ensure effective sequencing of the virus. The pandemic unfolded through multiple waves of infection that were each driven by distinct genetic lineages, with B.1-like ancestral strains associated with the first pandemic wave of infections in 2020. Successive waves on the continent were fueled by different VOCs, with Alpha and Beta cocirculating in distinct spatial patterns during the second wave and Delta and Omicron affecting the whole continent during the third and fourth waves, respectively. Phylogeographic reconstruction points toward distinct differences in viral importation and exportation patterns associated with the Alpha, Beta, Delta, and Omicron variants and subvariants, when considering both Africa versus the rest of the world and viral dissemination within the continent. Our epidemiological and phylogenetic inferences therefore underscore the heterogeneous nature of the pandemic on the continent and highlight key insights and challenges, for instance, recognizing the limitations of low testing proportions. We also highlight the early warning capacity that genomic surveillance in Africa has had for the rest of the world with the detection of new lineages and variants, the most recent being the characterization of various Omicron subvariants. CONCLUSION Sustained investment for diagnostics and genomic surveillance in Africa is needed as the virus continues to evolve. This is important not only to help combat SARS-CoV-2 on the continent but also because it can be used as a platform to help address the many emerging and reemerging infectious disease threats in Africa. In particular, capacity building for local sequencing within countries or within the continent should be prioritized because this is generally associated with shorter turnaround times, providing the most benefit to local public health authorities tasked with pandemic response and mitigation and allowing for the fastest reaction to localized outbreaks. These investments are crucial for pandemic preparedness and response and will serve the health of the continent well into the 21st century

Determination of the Appropriate Time of Relaying Cassava into Pepper in Intercropping System in Nigeria

ABSTRACT: Relay intercropping of cassava (Manihot esculenta Crantz) into pepper (Capsicum annum L.) is a common practice among farmers in Nigeria. However, there is high variation in the time of the relay thus leading to variability in yields of cassava and pepper. Field experiments were conducted to determine the appropriate time to introduce cassava into pepper in a relay intercrop. The experiment was a randomized complete block design replicated three times. Five different planting dates of relaying cassava into pepper were evaluated . Pepper and two cassava varieties were the test crops. Sole pepper was included for comparison. Delayed relay planting of cassava into pepper beyond 1 MAT (Months after transplanting) adversely affected the yield of both cassava varieties while simultaneous planting of pepper and cassava significantly (P 0.05) delayed flowering and maturity of pepper with a resultant effect of significant (P 0.05) reduction in fruit yield of pepper. The most appropriate time to introduce cassava into pepper in a relay intercrop was 1 MAT

Characteristics and Blood Pressure Profile of Goitre Patients in A Tertiary Hospital in South-West Nigeria

Background: Goitre remains endemic in iodine deficient areas of the world despite widespread introduction of iodine fortified food. In Nigeria, it is the second most common condition in endocrinology clinic. There is a therefore a need to document the blood pressure profile and clinical characteristics of this condition.Objective: This study assessed the clinical characteristics, biochemical and blood pressure profile of patients with goitre in the study area and assessed their knowledge and practice of preventive measures against goitre.Methodology: A comparative study of 103 adults with goitres and 103 healthy controls. An interviewer administered questionnaire was used and venous blood samples were obtained for analyses. Variables of interest included socio-demographic, anthropometric, thyroid function, and blood pressure.Results: The mean age of the goitre group was 46.92 ± 13.85 years with 86.4% carrying the swelling for up to 5 years. Anthropometric parameters, social habits, knowledge, and practice of the preventive role of iodized salt were similar between the goitre and control  groups. Forty-six percent of the goitrous subjects were hyperthyroid. Weight and BMI were significantly higher among the hypothyroid subgroup (p<0.001), with subjects in the hyperthyroid subgroup having significantly higher pulse rate and systolic blood pressure  (p<0.001). The hypothyroid subgroup had significantly higher diastolic blood pressure and lower pulse pressure (p< 0.001).Conclusion: This study concluded that patients with hyperthyroidism and hypothyroidism were more likely to have elevated systolic and diastolic blood pressure, respectively. Routine cardiovascular status check is therefore important in goitrous patients

Baseline prevalence of molecular marker of sulfadoxine/pyrimethamine resistance in Ebonyi and Osun states, Nigeria: amplicon deep sequencing of dhps-540.

BACKGROUND: Chemoprevention plays an important role in malaria control strategy. Perennial malaria chemoprevention (PMC) using sulfadoxine/pyrimethamine (SP) is a WHO-approved strategy to combat malaria in young children and may lead to drug pressure. Introducing SP-PMC may therefore be compromised due to the emergence of Plasmodium falciparum resistant to SP, particularly mutation at K540E of the dihydropteroate synthase (dhps) gene. Molecular surveillance of resistance markers can support assessment of antimalarial efficacy and effectiveness. High prevalence of 540E is associated with reduced effectiveness of SP, and areas with more than 50% prevalence are considered unsuitable for intermittent preventative treatment in pregnancy (IPTp) implementation. Assessing 540E prevalence is an important undertaking before implementation of SP-PMC. METHODS: We conducted a rapid surveillance of dhps-540E to assess the suitability of SP as PMC in field studies from Ebonyi and Osun states in Nigeria. We used an in-house developed amplicon deep-sequencing method targeting part of the dhps gene. RESULTS: Our data reveal that 18.56% of individuals evaluated carried the 540E mutation mixed with the WT K540. Mutant variant 540E alone was not found, and 80% of isolates harboured only WT (K540). Clonal analysis of the sequencing data shows a very low proportion of 540E circulating in both states. CONCLUSIONS: Our data show that both states are suitable for SP-PMC implementation and, based on this finding, SP-PMC was implemented in Osun in 2022. Continuous monitoring of 540E will be required to ensure the chemoprevention effectiveness of SP in Nigeria