Course Gaps at Bauchi State University

This course is designed to explore multiple theoretical approaches to the study of advertising and the digital media vis-à-vis the dynamics of an ever-changing visual ecology. Chosen texts will be developed to examine the messages’ cultural reflections, nature, and characteristics. Students will initially be required to develop an image bank and an in-depth bibliography of critical texts addressing the construction of visual imagery within a defined period of time and/or location.

Introduction to basic programming techniques of artificial intelligence (AI); Domain analysis; representation of Knowledge and strategies; control on inference and search; development of interactive intelligence CAI programs; the role of analogical reasoning; The main contents are symbol manipulations and AI problem solving techniques; Topics include LISP primitives; LISP objects and evaluation; recursion and iteration and data abstraction (association lists; properties and DESTRUCT); macros; object-centred programming; symbolic pattern matching and basic solving methods

Overview of Artificial Intelligence. History of AI. Goals of AI. AI Technique. Types of AI. Branches and applications of AI. Advantages and Disadvantages. Introduction to Intelligent Agents. Agent Performance, Examples of Agents, Agent Faculties, Rationality, Agent Environment. Agent Architectures. Search. General Classes of AI Search Algorithm Problems. Problem Solving by Search. Types of AI Search Techniques and Strategies. Introduction to the types of problems and techniques in AI. Problem-Solving methods. Major structures used in AI programmes. Knowledge Representation. KR and Reasoning Challenges. KR Languages. Knowledge representation techniques such as predicate logic, non-monotonic logic, and probabilistic reasoning. Semantic Network - types of relationships, semantic network inheritance, types and components. Introduction to Frames. Natural Language Processing (NLP). Introduction to natural language understanding and various syntactic and semantic structures. Introduction to Expert Systems - characteristics, components, types, requirements, technology, development. Programming Languages for AI. Introduction to computer image recognition. Lab work: Group practical in (i) Turing test practical - Students can act out their own version of the Turing test (ii) Facial recognition practical to aid in teaching students how machine learning works with students simulating a facial recognition algorithm. Practical applications of NLP in groups – (i) Question Answering focuses on building systems that automatically answer the questions asked by humans in a natural language (ii) Spam detection application for detecting unwanted e-mails getting to a user's inbox (iii) Sentiment analysis/opinion mining should be used on the web to analyse the attitude, behaviour, and emotional state of the sender, implemented through a combination of NLP and statistics (iv) Practical exercise of machine translation used to translate text or speech from one natural language to another natural language such as the Google Translator (v) Developing a model to provide word processor software for the spelling correction (vi) Developing a model for speech recognition for converting spoken words into text (vii) Implementing a Chatbot to provide the staff/student's chat services. OR Group Practical exercise on agents and its environment using simulation of a colony of ants foraging for food; model simulating a message between agents; model simulating the flocking behaviour of birds; model to apply standard search algorithm to the classic search problem of missionaries and cannibals, and how to use communicating agents for searching networks. Some computer AI animation exercises for any branch of AI. Practical exercise on simple robots coupling and programming. Group project of building a lawn robot for trimming grasses, or any simple design and implementation of robotics.

Introduction: Medicines and discovery processes. Initial stages: Target discovery; applications of molecular biology, in silico methods and assays; lead discovery; lead optimization; biomarkers. Measurement of drug properties: assay techniques; agonists (full, partial, inverse and biased); competitive antagonists. In vivo models; pharmacokinetic profiles of compounds; pharmacogenetics and formulations. Pre-clinical safety assessment including acute toxicity evaluation, subacute and chronic toxicity studies, reproductive toxicity, carcinogenicity studies, mutagenicity and mechanistic toxicity studies. Limitations of preclinical studies. Problems associated with drug discovery and development. Later stages: Pharmaceutical development; phases of clinical evaluation; ethics (informed consent, good clinical practice, participation criteria, sponsorship) and concepts in clinical trial design. Pharmacovigilance. e-Learning Activity Links are provided to additional resources (further reading, videos, on-line activities) to support the lecture content. Online self-assessment modules on the course content can be provided for formative feedback. Practical: Experiments are designed to reflect the topics covered including spectrophotometry, chromatography, flow cytometry.

OLS; Gauss-Markov Theorem; MLE; Specification and misspecification test; Predictive and non-predictive tests; Tests of hypothesis for linear model; The likelihood ratio; wald and language multiplier Tests; Multi-collinearity; Specification bias; GLS; Dummy variables and seasonal variations; Inferences based on asymptotic Distribution Theory

Definitions of physical exercise and sport. Energy expenditure during physical exercise. Cardiovascular, respiratory and renal adjustments during physical exercise. Thermoregulatory system in exercise. Water and electrolytes balance in exercise. The integrated neural and hormonal control during physical exercise. The health benefits of physical exercise and the role of exercise in the management of various health conditions. PIO 499: Research Project (5 units C: PH 225) Learning Outcomes On completion of this course, students should be able to: 1. prepare the final write-up of the research project using the appropriate format within the stipulated time frame; and 2. present and defend the write-up of the research project. Course Contents Independent research findings into selected areas/topics of interest to be supervised by an academic staff. Students will be required to carry out literature survey on the topics, perform experiments and produce reports (preferably at the end of second semester). Students will be subjected to both seminar and oral examination on the projects undertaken.

Management decision making. Functions of management planning, organisation, staffing, directing and controlling. Financial management. Principles of extension: diffusion, adoption and rejection of innovations. Communication and leadership in agricultural extension.

Macro and micro economic factors that influence health, illness and health care delivery system. Concept of health economics. Factors that affect demand and supply of health care services. Macroeconomic indices that influence the economy and health. The costing of health and nursing services. Availability and distribution. Cost recovery of services. Healthcare financing and the National Health Insurance Scheme (NHIS). Role of nurses in the National Health Insurance Scheme.

Introduction to sociology, psychology and anthropology. Biological basis for human behaviour– sensation, perception. Motivation and emotion. Describe human development, learning and practices. Role of culture, communication and human relationship and public participation. Importance of indigenous knowledge, belief and health practices. Social, psychological and biological aspect of environmental planning and built-up environment, substance use and abuse. Inequalities in health, psychological disorders, stresses, illness behaviours in relation to social medicine and medical psychology. Role of human behaviours in illness and disease causation. Social determinants of health, social epidemiology and health service utilisation behaviours. Application of social science theories towards understanding behavioural aspects of health and medical care. Considerations of human behavioural dimensions in illness and disease, prophylactic behaviour, the role of culture, role of social institutions, stress and health, compliance behaviours, social epidemiology and many others. Also covers topics in social health including smoking, alcoholism, drug addiction, obesity and nutritional behaviour/disorders, health services utilisation behaviour, emotional health and personality disorders, religion and health.