Mobile Facial Recognition System for Patient Identification in Medical Emergencies for Developing Economies

Medical emergencies are part of the common daily lives of people in developing and under-developed economies. Frequently, some of these medical emergencies end up tragically for many people in these countries due to many reasons, among which is the delivery of medical treatment when the patient is uncommunicative or unresponsive. The ability of the attending medical personnel to access a patient’s medical history is critical for the quality of the treatment rendered. Unfortunately, today many lives are lost in low income economies during medical emergencies due to lack or inaccessibility of a patient’s medical information. One of the major contributing factors of this paucity in records is attributable to the absence of reliable and cost-efficient healthcare delivery systems that support patient identification and verification. Due to the current ubiquity of mobile devices with their concomitant digital cameras, this paper explores the feasibility and practicability of using mobile platform and facial recognition technology as a means to deploying a cost-efficient system for reliable patient identification and verification

Mobile Facial Recognition System for Patient Identification in Medical Emergencies for Developing Economies

Medical emergencies are part of the common daily lives of people in developing and under-developed economies. Frequently, some of these medical emergencies end up tragically for many people in these countries due to many reasons, among which is the delivery of medical treatment when the patient is uncommunicative or unresponsive. The ability of the attending medical personnel to access a patient’s medical history is critical for the quality of the treatment rendered. Unfortunately, today many lives are lost in low income economies during medical emergencies due to lack or inaccessibility of a patient’s medical information. One of the major contributing factors of this paucity in records is attributable to the absence of reliable and cost-efficient healthcare delivery systems that support patient identification and verification. Due to the current ubiquity of mobile devices with their concomitant digital cameras, this paper explores the feasibility and practicability of using mobile platform and facial recognition technology as a means to deploying a cost-efficient system for reliable patient identification and verification

Multi-Objective Optimization in Metabolomics/Computational Intelligence

The development of reliable computational models for detecting non-linear patterns encased in throughput datasets and characterizing them into phenotypic classes has been of particular interest and comprises dynamic studies in metabolomics and other disciplines that are encompassed within the omics science. Some of the clinical conditions that have been associated with these studies include metabotypes in cancer, in ammatory bowel disease (IBD), asthma, diabetes, traumatic brain injury (TBI), metabolic syndrome, and Parkinson's disease, just to mention a few. The traction in this domain is attributable to the advancements in the procedures involved in 1H NMR-linked datasets acquisition, which have fuelled the generation of a wide abundance of datasets. Throughput datasets generated by modern 1H NMR spectrometers are often characterized with features that are uninformative, redundant and inherently correlated. This renders it di cult for conventional multivariate analysis techniques to e ciently capture important signals and patterns. Therefore, the work covered in this research thesis provides novel alternative techniques to address the limitations of current analytical pipelines. This work delineates 13 variants of population-based nature inspired metaheuristic optimization algorithms which were further developed in this thesis as wrapper-based feature selection optimizers. The optimizers were then evaluated and benchmarked against each other through numerical experiments. Large-scale 1H NMR-linked datasets emerging from three disease studies were employed for the evaluations. The rst is a study in patients diagnosed with Malan syndrome; an autosomal dominant inherited disorder marked by a distinctive facial appearance, learning disabilities, and gigantism culminating in tall stature and macrocephaly, also referred to as cerebral gigantism. Another study involved Niemann-Pick Type C1 (NP-C1), a rare progressive neurodegenerative condition marked by intracellular accrual of cholesterol and complex lipids including sphingolipids and phospholipids in the endosomal/lysosomal system. The third study involved sore throat investigation in human (also known as `pharyngitis'); an acute infection of the upper respiratory tract that a ects the respiratory mucosa of the throat. In all three cases, samples from pathologically-con rmed cohorts with corresponding controls were acquired, and metabolomics investigations were performed using 1H NMR technique. Thereafter, computational optimizations were conducted on all three high-dimensional datasets that were generated from the disease studies outlined, so that key biomarkers and most e cient optimizers were identi ed in each study. The clinical and biochemical signi cance of the results arising from this work were discussed and highlighted

Multimedia Object Modelling and Storage Allocation Strategies for Heterogeneous Parallel Access Storage Devices in Real Time Multimedia Computing Systems

The improvements in disk speeds have not kept up with improvements in processor and memory speeds. Conventional storage techniques, in the face of multimedia data, are inefficient and/or inadequate. Here, an efficient multimedia object allocation strategy is presented. We describe a multimedia object model, the object and storage device characteristics, and the fragmentation strategy. A bipartite graph approach is used for mapping fragments to storage devices and a cost function is used to determine an efficient allocation of an object and to balance the loads on the devices

Chemical Pesticides and Food Safety

Pesticides are usually applied to protect crops against insects and other pests. These pesticides of synthetic origin are potentially toxic to humans and can have both acute and chronic health effects, depending on the quantity and ways in which a person is exposed. They play significant roles in food production as they protect or increase yields due to less attack by insect pests. This is particularly important in countries that face food security challenges. The general population—who are not in the area where pesticides are used—is exposed to significantly lower levels of chemical insecticide residues through food and water. Chemical pesticides are among the leading causes of death by self-poisoning, in particular in low- and middle-income countries. Adverse effects from these synthetic pesticides occur only above a certain safe level of exposure. When people come into contact with large quantities of it in food, it may cause acute poisoning or long-term health effects, including cancer and adverse effects on reproduction. Production, distribution, and use of pesticides require strict regulation and control. Regular monitoring of residues in food and the environment is also required. Best among all is the promotion and adoption of bio-insecticides as a better alternative to chemical insecticides

Predicting the Concentration Characteristics of Itakpe Iron Ore for cut-off Grade Estimation

Concentration characteristics of an ore are very critical to the estimation of cut-off grade of a deposit. A mathematical model that can lead to their quick prediction will significantly enhance ore reserve estimation, mine planning and the economy of the mining venture as a whole. In this paper attempts have been made to establish a functional relationship between ore grades and concentration characteristics of Itakpe Iron ore. The Wilcoxon signed rank test has been used to establish a significant level of correspondence between actual values and values obtained from the model. The model has shown that the performance characteristics of the processing plant and the grade of the ore both play vital roles in deciding the concentration characteristics of an ore. \ua9JASE

Coping strategies and academic engagement of part-time undergraduate student teachers in Nigeria

Empirical evidence is inadequate in Nigeria to understand the link between the coping strategies and academic engagement of part-time student teachers who face challenges that might impede their academic success. This study adopted the quantitative research paradigm to ascertain part-time undergraduate student teachers’ coping strategy and their academic engagement. One hundred and fifty-five (155) undergraduate part-time student teachers of Nnamdi Azikiwe University formed the sample size. Major findings showed that respondents adopted more of problem- focused coping than emotion-focused coping strategies and were academically engaged. Significant mean differences did not occur based on gender and marital status in the dimensions of coping strategies and academic engagement except in extra- curricular engagement but occurred in coping efficacy, emotional support coping and disengagement coping dimensions affective liking for school, extra-curricular engagement and cognitive engagement based on students’ specialty. Significant positive relationships occurred in almost all the dimensions of coping and academic engagement and the predictive powers of the independent variables on the dependent variables were ascertained. Demographic variables did not significantly moderate the relationship between problem-focused coping dimensions and the academic engagement while they did on emotion-focused coping and academic engagement. Conclusions were drawn and recommendations made based on the findings

Infant Feeding Practices Among Mothers and Their Infants Attending Maternal And Child Health In Enugu, Nigeria.

Inappropriate feeding of infants has long been observed in our society and it is one of the global problems responsible for about one-third of the cases of malnutrition world wide. The study assessed the Infant feeding Practices among mothers and their infants attending Maternal and child health in Enugu, Nigeria. Samples of 410 infants (0-12 months) and mother pair, were randomly selected from these hospitals: Institute of Child Health University of Nigeria Teaching Hospital, Poly Clinic Asata, Christ Specialist Hospital Ogui and ESUT Teaching Hospital (Parklane) all in Enugu State of Nigeria. These four hospitals were purposefully selected because of their involvement in maternal and child health. Information  on infant feeding practices, demographic data, socio-economic data, were obtained from the mothers with a structured and pre-tested questionnaire. The data obtained were analyzed with the use of Statistical Package for Social Sciences (SPSS) version 16 to percentages, frequences and reprensented in a descriptive statistic in tables and charts. Results showed that most (43%) mothers were within the age of 26–30 years, 92.2% were married, 41% had secondary education, 45.1% were civil servants, 36.8% earned a monthly salary of less than ?10,000 per month. Majority (97.5%) of the infants were Breastfed, 53% initiated breastfeeding within one hour after birth, 65.3% breastfed on-demand, 62.2% of the infants were exclusive breastfed, only 34.5% were breastfed exclusively for a duration of 5–6 months, 38.8% of mothers practiced prelacteal feeding on their infants, 44% were fed on breastmilk substitute, 72.4% were fed on complementary food, 48.3% initiate complementary feeding at the age of 5 to 6 months, 70% were fed on Pap (Akamu, Ogi) as a complementary food. This study depicted high prevalence of inapropriate infant feeding practices among mothers despite all the nutrition education and promotion of optimal breastfeeding and adequate complementary feeding practices in our maternal and child care institute. Key Word: Infant, Breastfeeding, Exclusive breastfeeding, Complementary Feeding