CCMAS Course Search

Current and potential future energy systems in Nigeria and globally - resources, extraction, concepts in energy conversion systems; parallels and differences in various conversion systems and end-use technologies, with emphasis on meeting 21st-century national, regional and global energy needs in a sustainable manner. Various energy technologies in each fuel cycle stage for fossil (oil, gas, synthetic), nuclear (fission and fusion) and renewable (solar, biomass, wind, hydro, and geothermal). Energy types, storage, transmission and conservation. Analysis of energy mixes within an engineering, economic and social context. Sustainable energy; emphasise sustainability in general and in the overall concept of sustainable development and the link this has with sustainable energy as the fundamental benefit of renewable energy. Practical Contents Simple measurement of solar radiation, bomb calorimeter determination of calorific value of fuels and biomass; measurement of the velocity of wind, waves and the energy that abound in them; laboratory production of biogas and determination of energy available in it; simple conversion of solar energy to electricity; trans-esterification of edible oil into biodiesel; simulation of geothermal energy; Geiger-Muller or Scintillation Counters’ determination of uranium or thorium energy; simple solid or salt storage of energy; hybrid application of renewable energy. GET 307: Introduction to Artificial Intelligence, Machine Learning and Convergent Technologies (3 Units C: LH 45) Learning Outcomes At the completion of the course, the students are expected to be able: 1. explain the meaning, purpose, scope, stages, applications and effects of artificial intelligence; 2. explain the fundamental concepts of machine learning, deep learning and convergent technologies; 3. demonstrate the difference between supervised, semi-supervised and unsupervised learning; 4. demonstrate proficiency in machine learning workflow and how to implement the steps effectively; 5. explain natural languages, knowledge representation, expert systems and pattern recognition; 6. describe distributed systems, data and information security and intelligent web technologies; 7. explain the concept of big data analytics, purpose of studying it, issues that can arise with a data set and the importance of properly preparing data prior to a machine learning exercise; and 8. explain the concepts, characteristics, models and benefits, key security and compliance challenges of cloud computing. Course Contents Concepts of human and artificial intelligence; artificial/computational intelligence paradigms; search, logic and learning algorithms. Machine learning and nature-inspired algorithms – examples, their variants and applications to solving engineering problems; understanding natural languages; knowledge representation, knowledge elicitation, mathematical and logic foundations of AI; expert systems, automated reasoning and pattern recognition; distributed systems; data and information security; intelligent web technologies; convergent technologies – definition, significance and engineering applications. Neural networks and deep learning. Introduction to python AI libraries.

Current and potential future energy systems in Nigeria and globally - resources, extraction, concepts in energy conversion systems; parallels and differences in various conversion systems and end-use technologies, with emphasis on meeting 21st-century national, regional and global energy needs in a sustainable manner. Various energy technologies in each fuel cycle stage for fossil (oil, gas, synthetic), nuclear (fission and fusion) and renewable (solar, biomass, wind, hydro, and geothermal). Energy types, storage, transmission and conservation. Analysis of energy mixes within an engineering, economic and social context. Sustainable energy; emphasise sustainability in general and in the overall concept of sustainable development and the link this has with sustainable energy as the fundamental benefit of renewable energy. Practical Contents Simple measurement of solar radiation, bomb calorimeter determination of calorific value of fuels and biomass; measurement of the velocity of wind, waves and the energy that abound in them; laboratory production of biogas and determination of energy available in it; simple conversion of solar energy to electricity; transesterification of edible oil into biodiesel; simulation of geothermal energy; Geiger-Muller or Scintillation Counters’ determination of uranium or thorium energy; simple solid or salt storage of energy; hybrid application of renewable energy. GET 307: Introduction to Artificial Intelligence, Machine Learning and Convergent Technologies (3 Units C: LH 45) Learning Outcomes At the completion of the course, the students are expected to be able: 1. explain the meaning, purpose, scope, stages, applications and effects of artificial intelligence; 2. explain the fundamental concepts of machine learning, deep learning and convergent technologies; 3. demonstrate the difference between supervised, semi-supervised and unsupervised learning; 4. demonstrate proficiency in machine learning workflow and how to implement the steps effectively; 5. explain natural languages, knowledge representation, expert systems and pattern recognition; 6. describe distributed systems, data and information security and intelligent web technologies; 7. explain the concept of big data analytics, purpose of studying it, issues that can arise with a data set and the importance of properly preparing data prior to a machine learning exercise; and 8. explain the concepts, characteristics, models and benefits, key security and compliance challenges of cloud computing. Course Contents Concepts of human and artificial intelligence; artificial/computational intelligence paradigms; search, logic and learning algorithms. Machine learning and nature-inspired algorithms – such as their variants and applications to solving engineering problems; understanding natural languages; knowledge representation, knowledge elicitation, mathematical and logic foundations of AI; expert systems, automated reasoning and pattern recognition; distributed systems; data and information security; intelligent web technologies; convergent technologies – definition, significance and engineering applications. Neural networks and deep learning. Introduction to python AI libraries.

Fertilization. Structures of ectodermal, mesodermal and endodermal origins and embryogenesis of different organs. Medical genetics. Physiologic anatomy of male reproductive system. Spermatogenesis. Male sexual act-nervous co-ordination. Male sexual hormones. Cryptochidism. Physiological anatomy of the female reproductive system. The female sex hormones. Oestrous and menstrual cycles. Physiology of pregnancy, parturition and lactation. Pregnancy tests. Contraception and physiological basis of infertility. P10 303: Endocrinology (2 Units C: LH 30) Learning Outcomes On completion of this course, students should be able to: 1. list the hypothalamic factors that control the secretion of each of the anterior pituitary hormones and describe their route of transport from the hypothalamus to the anterior pituitary; 2. list the 3 major families of the anterior pituitary hormones and their biosynthetic and structural relationships; 3. describe the posterior pituitary lobes with respect to cell types, vascular supply, development, and anatomical function relative to the hypothalamus; 4. identify the steps in the biosynthesis, storage, and secretion of tri-iodothyronine (T3) and thyroxine (T4) and their regulation; 5. describe the regulation of parathyroid hormone secretion and the role of the calcium- sensing receptor; 6. identify the major hormones secreted from the endocrine pancreas, their cells of origin, chemical nature and physiological actions; 7. list the functional zones (one medullary and three cortical zones), innervation, blood supply, principal hormones secreted from each zone of the adrenal glands; 8. identify the major physiological actions and therapeutic uses of glucocorticoids; 9. list the major mineralocorticoids and identify their biological actions and target organs or tissues; and 10. identify the chemical nature of catecholamines, their biosynthesis, mechanism of transport within the blood, and how they are degraded and removed from the body. Course Contents Nature of hypothamo-hypophyseal relationship. Synthesis, storage and release of the neurohypophyseal and adenohypophyseal hormones. Functions of the hypothalamus to include regulation of body temperature, thirst appetite and food intake. Regulation of adenophypophyseal function and higher autonomic control. Functions and control of the secretions of the pituitary, thyroid, parathyroid, pancreas and adrenal glands. Abnormalities of endocrine functions. Normal integration in the control of calcium and glucose metabolism.

Identification of donor and recipient; Oestrus cycle; oestrus detection; Synchronisation; and superovulation; Recovery of embryo (surgical methods); Evaluation and storage of embryos; embryo splitting and cloning; Transfer of embryo into recipient; Monitoring and management of recipient; Practical classes using small ruminants

The menstrual cycle and associated disorders. The menstrual cycle. Primary amenorrhoea. Secondary amenorrhoea. Menorrhagia. Dysmenorrhea. Galactorrhoea. Hirsutism. Polycystic 129 ovarian disease. Intermenstrual, postcoital and postmenopausal bleeding. The climacteric. Sexuality. Physiology of coitus. Female sexual dysfunction. Male sexual dysfunction. Rape. Infertility. Epidemiology of infertility. Male infertility. Assisted reproductive techniques.

Pelvic infections, the sexually transmitted diseases. Acute pelvic inflammatory disease, chronic pelvic inflammatory disease, other pelvic infections, spontaneous abortions. Induced abortions, legal and illegal. Population dynamics. Communication issues in family planning. Myths and rumours in family planning. Contraception and family planning. General considerations. Oral hormonal contraception. Intrauterine contraceptive devices. Surgical contraception (female, male), long acting hormonal contraceptives, barrier methods of contraception. Periodic abstinence. Natural methods. Management information system in family planning. Integrating family planning with other reproductive health services. Contraception in special needs. Family planning in adolescent. Post abortal care. Unmet needs in contraception. Gender based violence.

Review of methodologies in Surveying and Geoinformatics. Techniques in research methods. Identification of research problems, review of related literature and justification for the research. Description of data source, acquisition, quality and presentation of data, processing of data. Presentation and analysis of results, research findings, conclusions, recommendations and research contributions to knowledge. Rreferences and appendices.

Definition of research, characteristics of research; types of research; the research process; formulating the research problem; considerations in selecting a research problem; reviewing the literature; procedure for reviewing the literature; formulation of objectives; preparing the research design; consideration for the research design; guidelines to construct a research tool; constructing a questionnaire; piloting the questionnaire; collecting data; ethical issues concerning research participants; ethical issues relating to the researcher; processing and analyzing data; the data processing operations; data analyzing methods; generalization and interpretation of the results; reporting the findings; writing research project report format; general attributes of a research proposal; what distinguishes an engineering research proposal; components of a research proposal; costing an engineering research proposal. The course is designed for final year students who will be required to make seminar presentations. Emphasis here is on how to write an introduction, literature review, methodology, results, and discussion as well as the derivation and/or development of relevant mathematical models and procedures. APA referencing style will also be discussed.

Understanding basic elements of research methods in geography: Selection of a research topic; definition of study problems and objectives; Formulation of research hypotheses; Experimental design for collection and analysis of data; writing a research proposal.

Identifying potential research areas. Literature review: elements, structure, and importance Formulating aims and objectives. Types and sources of data for research in Environmental management: Past projects records; Surveys; Laboratory investigations. Understanding of the role of research in Environmental Management and ways to undertake research. Current methodology of Environmental management research, including: recent paradigm shifts within scientific approach to Environmental research, quantification and classification in Environmental management; theories and models in Environmental management.