CCMAS Course Search

pSpice simulation; Design of BJT-based amplifier systems; Design of FET-based amplifier systems; Current-series feedback design; Current-series feedback design; Voltage-shunt feedback design; Differential amplifier; Op-amp IC applications; Positive feedback and oscillator circuits; Advanced electronic laboratory skills (design, analysis, construction, and measurement of advanced analog electronic circuits using discrete devices (diodes, bipolar junction transistors, MOSFETs).

Review of Microelectronic Devices: Diode, BJT, JFET, and MOSFET; Large-signal behaviour and Small-signal models; Single-Transistor Amplifiers: Common-emitter/source, common- base/gate, and common-collector/drain; Biasing, small-signal gain, input resistance, and output resistance; Circuit simulation using pSpice; Multi-Transistor Amplifiers: Cascade, differential, and cascade; Biasing, small-signal gain, input resistance, and output resistance; Frequency Response, Gain/phase plots and Analysis; Negative Feedback: Effects on gain, input resistance, output resistance, noise, distortion, and bandwidth; Inverting and non- inverting op amps; Passive Filters and Active Filters: Low-pass, high-pass, band-pass, and band-reject, First-, second-, and higher-order; Non-linear Circuits: Rectifiers and peak detectors, Sinusoidal oscillators, Mono and bi-stable multivibrators, Waveform generators.

Fundamental concepts: Electric fields, charges, magnetic fields. current, B-H curves Kirchhoff’s laws, superposition. Thevenin, Norton theorems, Reciprocity, RL, RC, RLC circuits. DC, AC bridges, Resistance, Capacitance, Inductance measurement, Transducers, Single phase circuits, Complex j - notation, AC circuits, impedance, admittance, susceptance.

Introduction to Artificial Intelligence: Intelligent Agents and Applications of Artificial Intelligence. Knowledge Representation and Reasoning: Propositional logic, Theory of first order logic, Inference in First order logic, Forward and Backward chaining, Resolution, Probabilistic reasoning, Utility theory, Hidden Markov Models (HMM), Bayesian Networks. Machine Learning: Supervised and unsupervised learning, Decision trees, Statistical learning models, Learning with complete data – Naive Bayes models, Learning with hidden data – EM algorithm, Reinforcement learning. Pattern Recognition: Introduction, Design principles of pattern recognition system, Statistical Pattern recognition, Parametre estimation methods – Principle Component Analysis (PCA) and Linear Discriminant Analysis (LDA), Classification Techniques – Nearest Neighbour (NN) Rule, Bayes Classifier, Support Vector Machine (SVM), K – means clustering.

Three-phase balanced circuits and power; mutual inductance; Linear transformer, ideal transformer, autotransformer; Frequency response, transfer function, Bode plots; Series and parallel resonance in the frequency domain; Series and parallel resonance in the time domain; Fourier series in circuit analysis; Two-port parameters; Laplace transform circuit analysis.

Sounds and sound patterns in English Language (vowels and consonants, phonetics and phonology); English word classes (lexical and grammatical words, definitions, forms, functions, usages, collocations); major word formation processes; the sentence in English (types: structural and functional); grammar and usage (tense, concord and modality). Reading and types of reading, comprehension skills, 3RsQ. Logical and critical thinking; reasoning methods (logic and syllogism, inductive and deductive argument, analogy, generalisation and explanations). Ethical considerations, copyright rules and infringements. Writing activities (pre-writing[brainstorming and outlining], writing [paragraphing, punctuation and expression]. post- writing [ editing and proofreading]. Types of writing (summary, essays, letter, curriculum vitae, report writing, note-making) etc. Mechanics of writing. Information and Communication Technology in modern language learning. Language skills for effective communication. The art of public speaking.

Introduction to computers and computing; computer organisation – data processing, memory, registers and addressing schemes; Boolean algebra; floating-point arithmetic; representation of non-numeric information; problem-solving and algorithm development; coding (solution design using flowcharts and pseudo codes). Data models and data structures; computer software and operating system; computer operators and operators precedence; components of computer programs; introduction to object oriented, structured and visual programming; use of MATLAB in engineering applications. ICT fundamentals, Internet of Things (IoT). Elements of software engineering.

Introduction: network edge, end systems, access networks, links, network core, packet switching, circuit switching, network structure, delay, loss, throughput in networks, protocol layers, service models, Application Layer, Web and HTTP, Electronic mail, Domain Name System, video streaming and content distribution networks, Socket programming with UDP and TCP*, Transport Layer, multiplexing and demultiplexing, connectionless transport: UDP, principles of reliable data transfer, connection-oriented transport: TCP, principles of congestion control, TCP congestion control, Network layer: The Data Plane, control plane, Router architecture, IP: Internet Protocol, Generalized Forward and SDN, Network Layer: The Control Plane, routing protocols, intra-AS routing in the Internet: OSPF, routing among the ISPs: BGP, The SDN control plane, Link Layer and LANs, error detection, correction, multiple access protocols, data center networking, Wireless Networking, Wireless links, characteristics, IEEE 802.11 wireless LANs (Wi-Fi), Network Security, Message integrity, authentication, Securing e-mail, securing TCP connections: SSL, Firewalls and IDS.

Introduction to Computing Systems; Switch Design; Boolean Algebra; Gate Design and Simplification; Building Blocks; Number Systems and Arithmetic; Latches and Registers; Counters; State Machines; Memory; Datapaths; Introductory Assembly Programming. Laboratory projects will include use of PC-based CAD environment that supports schematic capture, logic simulation, and HDL-based logic synthesis on FPGAs (field-programmable gate arrays). Small-scale integrated circuits will be used for early labs; HDL-based logic synthesis on FPGA-based design boards will be used for more advanced design implementations. ELE 324 : Communication Principles (3 Units C: LH 45) Learning Outcomes On the successful completion of this course, students will be able to: 1. analyse communication systems in both the time and frequency domains; 2. describe the principles of amplitude modulated and angle modulated communication systems, and be able to analyse their performance in the presence of noise; 3. explain source coding and its relations to information theory, citing Shannon’s theorem; 4. describe the principles of various digital modulation systems and their properties, including bandwidth, channel capacity, transmission over bandlimited channels, inter-symbol interference (ISI), demodulation methods, and error performance in the presence of noise; and 5. explain engineering fundamentals of photogeneration, photodetection and lightwave propagation for optical communications. Course Contents Models of telecommunication system. The concept of information volume. Characteristics of analogue audio and video signals. Analogue modulation techniques and their implementation: amplitude and angle modulation, Frequency Division Multiplexing. Digitization of analogue signals. Binary system. Arithmetic operations on binary numbers. Modulo 2 arithmetic. Pulse code modulation (PCM), sampling, quantization, coding. Delta and differential pulse code modulation. Synchronous and asynchronous, static and dynamic time division multiplexing. Plesio-synchronous digital hierarchy, primary group, secondary group, groups of higher levels. Synchronous digital hierarchy. Multiplexing PDH signals into SDH STM-1 transport module. Transmission media. Optical fibres: single mode, multimode. Optical cables. Wavelength division multiplexing (WDM): Dense wavelength division multiplexing (DWDM) 400 Level GET 402 Engineering Project I (2 Units: C; PH 90) Learning Outcomes At the end of this course, the students should be able to: 1. Complete the design phase of a complex engineering problem sourced from industry or community during the SIWES III programme. 2. Demonstrate the connection between engineering product-making and the theoretical courses they have learned following the applicable industry best practices. Course Contents In the second semester of the 400-level students, preferably in groups, work from the university on the identified industry or organization to tackle industry complex engineering problems. Theoretical issues may be provided by the department faculty or industry experts. During the vacation, students will now work full time with the organisation/industry on the project as part of the SIWES III. The students can also go beyond the department and engage in multidisciplinary undertakings. Literature survey, review of existing systems etc. must be achieved to a satisfactory extent. GET 404 Engineering Valuation and Appraisal (2 Units: C; LH 30) Learning Outcomes At the end of this course, the students should be able to: 1. Identify at least three (3) objectives of engineering valuation work, valuer's primary duty and responsibility and valuation terminologies. 2. Describe at least four (4) Valuer's obligation to his or her client, to other valuers, and to the society. 3. Demonstrate with example the engineering valuation methods, valuation standards, and practices. 4. Prepare engineering valuation and appraisal reports and review 5. Discuss expert witnessing and ethics in valuation. 6. Determine price, cost, value, depreciation and obsolescence in real property, personal property, personal property, machinery and equipment, oil, gas, mines, and quarries valuation.

Review of discrete-time signals and systems with emphasis on sampling and quantization. Introduction to DSP hardware architecture, including fixed-point vs. floating-point processors and the multiply-accumulate unit. Convolution and spectral analysis using the discrete-time Fourier transform. The discrete Fourier transform, the fast Fourier transform (FFT), and use of the FFT for convolution and spectral analysis. Z- transforms, pole-zero analysis of discrete-time systems, and pole-zero-based digital filter design. Analysis of FIR and IIR discrete-time systems with emphasis on phase response. Design and implementation of FIR digital filters. Design and implementation of IIR digital filters. Introduction to multi-rate signal processing and filter banks.