Department of Systems Engineering & Engineering Management

Computer-oriented problem solving methods and algorithm development; structured programming concepts; concepts of abstract data types; various commonly used types including vector, list, queue, tree and set; implementation using different data structure such as array, pointer based structure, and linked list etc; illustrative applications. High level programming language such as "C" and "Pascal" will be used. (This course is offered by Department of Computer Science and Engineering.)

The concept of abstract data types and the advantages of data abstraction are introduced. Various commonly used abstract data types including vector, list, stack, queue, tree, and set and their implementations using different data structures (array, pointer based structures, linked list, 2-3 tree, B-tree, etc.) will be discussed. Sample applications such as searching, sorting, etc. will also be used to illustrate the use of data abstraction in computer programming. Analysis of the performance of searching and sorting algorithms. Application of data structure principles. Prerequisite: CSC 1110 or its equivalent.

Basic concepts and techniques of artificial intelligence. Knowledge Representation: predicate logic and inference, semantic networks, scripts and frames, and object-oriented representation. Searching: such as A*, hill-climbing, minimax, and alpha-beta pruning. Planning: the frame problem and the STRIPS formalism, representation schemes, and planning strategies. Neural Networks: learning algorithms, neural architecture and applications. Natural language processing. Knowledge Acquisition and Expert Systems: properties, techniques, and tools of expert systems. Prerequisite: CSC 2100.

This course provides a foundation for understanding and evaluating the design principles incorporated in modern computer systems with particular emphasis on architectural features required to support high-level languages and system software: design methodology and descriptive tools; instruction set design; memory system design; control system design; input/output systems design; parallel processing concepts and future trends. Prerequisite: ERG2020. Not for students who have taken CEG 3420.)

This course is designed for students who wish to communicate effectively in a technical context.Specifically, it will focus on developing research and organizational skill, as well as those needed to present technical information. Course work will consist of writing reports, memos, letters, procedures, and a proposal. It will include work on developing students' oral skills. This course is particularly suitable for Engineering students in their first or second year of attendance. (This course is offered by English Language Teaching Unit.)

Calculus of several variables: partial derivatives, Jacobian matrices, chain rule. Linear algebra: matrices, inverses, vector spaces, basis and dimension, linear independence. Linear transformations: projection, orthogonality, systems of linear equations, Gaussian elimination, LU decomposition, eigenvalues and eigenvectors.

Digital concepts; Number systems; Operations and Codes; Logic Gates; Boolean Algebra and Logic Simplification; Combinational Logic; Functions of Combinational Logic; Flip-Flops and related Devices; Counters; FInite State Machines; Programmable Logic Devices - Programming and Sequential Logic Applications; Memory and Storage; Integrated Circuit Technologies.

This course deals with a number of financial instruments traded in the markets for securities, foarkets for securities, foreign exchange, options and futures. Discussions include intersectoral flow-of-funds analysis, determination of interest rates and analysis of money and capital markets. Prerequisite: FIN 2010 or permission from instructor. (This course is offered by Department of Finance.)

This course discusses basic security valuation theories and portfolio management. Emphasis is placed on fundamental common stock analysis, capital market theory, analysis of portfolio performance, market efficiency, and behavior of stock prices. Prerequisite: FIN 2010 or permission from instructor. (This course is offered by Department of Finance. )

This course aims to discuss the basic operations of the options and futures markets. It analyses option pricing models, investment strategies involving options and futures, and the roles of hedgers and investors in these markets. Other major topics include comparisons of options and futures contracts issued by different exchanges and their trading regulations. Prerequisite: FIN3080.

Topics of this course will include: Basic option theory, forward and futures contracts, model of asset price, Ito’s Lemma, asset price random walk, Black-Scholes model, free boundary problems of options, constrained matrix problems and the projected SOR method, discrete random walk model and the binomial methods. Students taking this course are expected to have knowledge in probability and differential equations.

Principles and techniques of game theory, matrix games, minimax theorem and calculation of optimal strategies, cooperative and non-cooperative solutions of bimatrix games, coalitional games and applications. Students taking this course are expected to have knowledge in linear algebra.

MKT 2010 Marketing Management

This course is devoted to the study of the management of marketing functions, the analysis of external forces affecting marketing decision making, the implementation and control of marketing activities, and an examination of the global impact of marketing. Course objectives include the development of students¡¦ understanding of the fundamental concepts underlying the selection and assessment of markets and the development and delivery of products, an investigation of the role and contribution of marketing to the conduct of successful business operation and to society, and to develop student abilities in identifying marketing opportunities and viable marketing strategies.

Review of linear algebra. Linear programming: simplex methods, duality, and sensitivity analysis. Network flows: transportation and assignment problems, shortest paths, minimum spanning trees, network simplex method, multicommodity flows. Modeling issues in linear programming and network flows applications.

Sample space. Random Variable. Probability and conditional probability. Distribution. Expectation and variance. Characteristic function. Law of large numbers and central limit theorem. Markov chain. Poisson process. Estimation: errors, sample size, maximum likelihood estimation, and consistency. Regression. Time Series.

Principles of engineering economy. Value and cost, cash flows. Economic analysis of alternatives, technological, social, and human factors. Models involving allocation and scheduling of resources. Analytical techniques for evaluating industrial projects. Relationship between economics of technical choice and industrial productivity. Basic financial accounting concepts, accounting cycle, financial statements.

Introduction to Management functions including planning, organizing, influencing, and controlling; project management; team building; corporate knowledge management, strengths and weaknesses of engineers as managers; global issues, and engineering management challenges.Introduction to marketing management including market segmentation, product positioning, pricing strategy, promotion, channels, marketing survey, customer relationship management, and the use of customer relationship management systems. (Not for Students in Engineering & Engineering Management Major)

Introduction to financial and cost analysis: valuation of assets, liabilities, shareholder’s equity; determination of revenues and expenses; cost analysis; allocation of indirect cost; budgeting and performance; use of financial and cost data for planning and control.

Introduction to macroeconomics including national income accounting, aggregate demand and supply models, demand and supply of money, fiscal and monetary policies, balance of payment, exchange rate systems, and business cycle theory. (Not for Students in Engineering & Engineering Management Major)

Overview of financial markets for securities, foreign exchange, options and futures; special emphasis on understanding of the market characteristics; interpretation of financial statements of an organization in terms of liquidity, solvency, profitability, efficiency and growth.

Introduction to Systems Engineering, design and innovation in engineering. Intellectual property rights and other legal issues related to engineering, information technologies and E-commerce. Professional liabilities, engineering ethics and societal impact. Health considerations, safety concerns and environmental impact.

System concept and mathematical models. Model building: parameter estimation, and data analysis. Elementary queueing theory and applications: M/M/S models. Introduction to simulation and simulation languag e. Principles of discrete event simulation. Random number generators and output analysis. Optimization via simulation. Applications to production and manufacturing systems. Prerequisites: CSC 1110, SEG 2430 or their equivalents.

Role of files in data processing. Data organization on secondary storage. Choice of storage media. Blocking and buffering. Design of file parameters and performance computation of file processing. Record clustering and record partitioning. File organizations and access methods for Sequential, Indexed, and Direct file organizations. VSAM files. Static and dynamic hashed files. Hybrid files. Prerequisite: SEG 3460 or its equivalent.

Information system development life cycle, User requirement analysis, Feasibility study, Cost/benefit Analysis, Systems analysis tools such as data flow diagrams, Process specification tools. Real time systems analysis. Transformation from analysis to design. Structured chart. System design quality heuristics such as coupling, cohesion. System design packaging and design optimization: CASE (Computer Aided Software Engineering) Tools. Prerequisite: SEG 3460 or its equivalent.

Non-linear programming: convex sets and functions, local and global optima, Lagrange multipliers, optimality conditions for unconstrained problems, descent methods, constrained optimization, Karush-Kuhn-Tucker conditions, solution methods. Non-differentiable optimization: integer programming models, formulations, cutting-plane methods, branch-and-bound. Dynamic programming: models and formulation, Bellman's equations, solution methods.

Factors that drive continuous creative product innovation. Study of processes of creating, assessing, and pursuing product opportunities. Evaluation of new product ideas and risk assessment of commercialization. Product development strategies in industrial marketing. Understanding the behaviour of buyer. Formulation and implementation of innovative marketing strategy and business plan. Prerequisites: SEG 2440 or SEG 2450 or its equivalent.

Principles of operating system functions. Introduction to assemblers, linkers, loaders, and libraries. Performance analysis of scheduling algorithm. Applications based on systems such as DOS, UNIX and MVS /ESA. Job Control Language, procedures, parameter passing, and utilities. Comparison of programming languages of different levels and their evaluation and selection based on application needs. Prerequisite: CSC 1110 or its equivalent.

Dynamic programming for sequential decision making under uncertainty, optimal control and combinatorial optimization. Applications to network problems (shortest paths, Viterbi algorithm, the travelling salesman problem) and discrete time dynamic optimization problems of finite and infinite horizon (linear-quadratic optimal control, inventory control, portfolio analysis). Numerical solution methods for infinite-time dynamic programming: value iteration, policy iteration, linear programming. Introductory continuous-time optimal control: calculus of variations, Pontryagin principle and the Hamilton-Jacobi-Bellman equation. Prerequisites: SEG 2430 and SEG 3440 or their equivalents.

In depth discussion of the challenges, techniques, and technologies associated with the management of IT in a competitive environment. The linkage of IT to business strategy, and business process reengineering. Type of information systems: MIS, DSS, TPS. Development process. Information system planning. Systems project management and control. IT acquisition, budgeting, and deployment. Performance evaluation, and auditing. Operations management. Privacy and security. Prerequisite: SEG 3430 or its equivalent.

Quality planning, control, and improvement. Sampling theory. Statistical quality control theory applied to production operations. Specification and control charts for monitoring production systems. Quality engineering - The Taguchi Method. Quality control issues of manufacturing and service industry. Case studies of Quality control problems in industry. Use of computer aids. Introduction to ISO 9000. Prerequisite: SEG 2430 or its equivalent

This course provides an introduction to the fast evolving field of human-computer interaction (HCI). HCI is a multidisciplinary subject concerning the design, implementation and evaluation of interactive computing systems for human use, and the study of the major phenomena surrounding them. We will provide a broad overview of the field, including the theory and principles underlying good designs, with emphasis on the interface design process, development and evaluation. We will also sample some state-of-the-art technologies in HCI, such as speech recognition, haptics, virtual reality, software agents, and computer supported cooperative work.

Managerial functions: planning, organizing, influencing and control. Strategic formulation and decision-making. Strategic and operational considerations of technology. Management of research, engineering design, and production functions. Project screening and selection. Project structuring, scheduling and budgeting. Project control.

Basic elements of information systems, their concepts and interrelations. Database systems: database models, relational database, database application programming. Information retrieval: models, indexing, performance evaluation. Expert systems: knowledge and data engineering, expert system shell and application studies.

Review of basic probability. Probabilistic dynamic programming. Stochastic processes and Markov chains. Birth-and-death processes and queuing models. Stochastic inventory models: single and multiple periods. Forecasting and time series. Markov decision processes. Prequisite: SEG 2430 or its equivalent.

Analysis and modeling of market, credit, and operational risks in Financial Engineering. Fundamental financial instruments and derivatives: forward, futures, options, and swaps. Sources and models of market risks: interest rate, foreign exchange rate, equity prices, and commodity prices. Major credit scoring and rating models: Z-score, Logit, and Merton. Major commercial applications and systems, KMV and CreditMetrics. Different approaches to measure Value at Risk (VaR): historical, parametric, and Monte Carlo.

Basic theory of interests, fixed income securities, the term structure of interest rates, valuation of a firm, decision making under uncertainty, mean-variance portfolio theory, capital asset pricing model, models and data, basics of forward and futures contracts, basic options theory.

Evaluation of new product ideas and risk assessment of commercialization. Study of processes of creating, assessing and pursuing product opportunities. Venture launch and growth. Formulation and implementation of innovative marketing strategy and business plan. (This course must be taken concurrently with SEG3810 and is not for students who have taken SEG3450)

This course provides an overview of the technologies that support the development of E-Commerce applications, business models and strategies for E-Commerce, electronic payment and security. (Not for students who have taken SEG3560)

Overview of the operations functions of service organizations. Examination of methods for designing and operating service delivery systems in the health care, financial, hospitality, telecommunication, and logistics industry. Discussion on service strategy, services for individual and corporate customers, service technologies, process and facility design, management of waiting lines, demand forecasting, demand and supply management, service quality, staffing and scheduling.

Introduction to real-time data processing systems and their design and analysis. Reliability and Fault tolerance. Exception and exception handling. Concurrent programming. Shared-memory-based synchronization and communication. Message-passing-based synchronization and communication. Atomic actions and error recovery in concurrent processes environment. Resource control. Real-time facilities of real-time languages. Implementation efficiency. Case studies. Prerequisite: SEG 3460 or its equivalent.

Review of basic decision analysis concepts and methodologies. Single- and multiattribute utility theory under both certainty and uncertainty. Assessment methodologies, strength of preference, risk attitude, and trade-off judgements. Prior information, subjective probability, Bayesian analysis, and sequential analysis. Multiobjective optimization, methods for generating Pareto optimum solutions, methods with prior assessment of preferences, and method with progressive assessment of preferences. Risk sharing and group decisions. Cooperative an non-cooperative game methods. Applications to risk analysis and management. Prerequisites: SEG 2430, SEG 3440 or their equivalents.

Construction and Renovation. Maintenance and Operation. Real Estate Consideration and Planning. Space Planning Layout. Facility Financial Forecasting and Management. General Administrative Services. Successful Facility Management. Industrial Applications. Prerequisite: SEG 2420 or its equivalent.

Client/server theory and practice. Management aspects: vision, priority and transition strategies, operational challenges. Overview of major protocols and distributed system concepts. Prerequisite: SEG 3460 or its equivalent.

Overview of open system standards and protocols. Electronic commerce applications using open system and AI technologies. Application of intelligent agents for the automated transaction processing. Integration of HTML and JAVA with information and communication systems. Prerequisite: SEG 3460 or its equivalent.

Systems analysis and business process re-engineering. Performance variability and measures. Push and pull production systems. Operations planning. Production scheduling. Aggregate and workforce planning. Capacity planning and management. Enterprise resource planning systems.

Introduction to knowledge-based system, neural computing, genetic algorithm, and fuzzy logic. Inference methods and uncertainty management in design and implementation of expert systems. Application of computational intelligence techniques to management decision systems in specific business areas. Prerequisite: CSC 2100 or its equivalent.

System implementation methodology construction, testing, maintenance. Software reengineering and Reverse engineering, Software reliability and program quality assurance; software reusability. Software metrics. Performance engineering. Configuration management. Object oriented system design. Use of computer-aided tools. Prerequisite: SEG 3430 or its equivalent.

This course is designed to investigate and to discuss selected topics of current interests in Systems Engineering and Engineering Management.

The integrated logistics management concept. Customer service. Channels of distribution. Transportation, vehicle routing and scheduling, freight consolidation. Facility location and network planning. Storage and material handling systems. Information systems for order processing and inventory tracking. Purchasing and supply scheduling. Business process re-engineering. Third-party logistics. Global logistics.

Management of moving raw materials, in-process inventory, and finished-goods; transferring information and payment. Topics include: distribution, inventory management, purchasing and supplier management, the value of information and information technology, supply chain integration and strategic partnering, product design for supply chain management.

This course covers various methods of transferring payments over the Internet and compares their functionality. Topics include electronic cash, electronic checks, electronic credit cards, micro-payments, the encryption and digital signature techniques needed to support electronic cash, and the technologies available to support secure transactions on the Internet. Implementations of various payment systems are examined.

This course introduces data mining techniques suitable for E-Commerce applications. It covers the following topics: prediction, association rule mining, rule induction, trend and deviation analysis, pattern visualization, and data mining packages. Emphasis will be placed on employing these techniques to marketing, risk management, business negotiation, and commercial applications.

Review of important concepts in financial decision theory such as utility theory, arbitrage, market efficiency hypothesis, mean-variance analysis, capital asset pricing models, separation theorems, and arbitrage pricing theory and option pricing. Computational techniques such as stochastic programming, binomial trees and the finite difference method. Prerequisites: SEG 2440 or FIN 2010 or their equivalents and SEG 2420.

Overview of purchasing, quality specification and inspection, materials planning and control, price determination and negotiation, contract management, vendor management, international issues, and acquisition of fixed assets and services.

Basics of revenue management: dynamic pricing strategies and product availability decisions, customer segmentation, demand estimation & forecasting, channel management, revenue-based inventory control. Application of optimization tools. Case studies in industries such as airline, hospitality, rental services, and events/ entertainment, with focus on multi-pricing across products, markets, channels and time. Prerequisite: SEG2420 or with the approval of the course instructor.

Dynamic continuous-time systems. Examples, modeling, and classification of optimal control problems. Pontryagin's maximum principle:adjoint equation,Hamiltonian system,and sufficient condition of optimality. Bellman's dynamic programming: principle of optimality, Hamilton-Jacobi-Bellman equation, and verification theorem. Linear quadratic control: Riccati equation and linear matrix inequality. Introduction to numerical methods of solving optimal control problems.

Classification of scheduling and sequencing problems. Sequencing involving capacity expansion. Single machine scheduling involving due dates: problem formulation and applications, complexity, exact solutio ns and approximate solutions. Parallel machine scheduling. Flowshop scheduling. Job shop scheduling. Batch scheduling with set-up times between batches. Prerequisite: SEG 3440 or its equivalent.

Overview of manufacturing systems: resources, constraints, cost, planning horizon, and objective of production planning. Deterministic production planning: parallel machine systems, flowshops and jobshops. Dynamic programming equations, zero-inventory policy. Capacity expansion and HMMS model. Stochastic production planning: unreliable machines, Markov Chains, Akella-Kumar theorem and threshold-type policy. Hierarchical production planning. Prerequisites: SEG 2430, SEG 3440 or their equivalents.

The roles of knowledge systems in problem solving. Automation of commonsense reasoning. Nonmonotonic and Plausible reasoning. Representation and reasoning about quantities, measurements, time, space, and physics. Knowledge systems to represent mind, plans and goal. Prerequisite: CSC 3230 or its equivalent.

The course introduces students to the basics of strategic management. All aspects of strategic planning tools and techniques, strategy formulation and decision making, and implementation and control are covered. Topics include SWOT analysis, forecasting models, decision methodology, project planning, implementation, and evaluation, team building and communication. Integration of business functions such as finance, human resources, marketing, and production and operations is emphasized.

Accounting income. Cash flow modelling. Depreciation and taxation. Overview of utility theory. Analysis of economic risk. Risk simulation. Decision tree analysis. Procedures for replacement analysis. Activity-based costing. Analytical hierarchy process. Economic optimization under constraints. Strategic investment analysis. Prerequisite: SEG 2440 or its equivalent

The course covers the underlying theory and fundamental solution methodologies of mathematical programming: linear programming, unconstrained and constrained non-linear Optimization. Topics include optimality conditions, search methods, descent methods, Lagrange multipliers, penalty functions. Developments of duality theory are presented. Concepts and issues in global optimization and multi-objective optimization are introduced. Applications are drawn from engineering and financial optimization.

Issues in building client/server information systems. Concept, implementation, and management aspects in the development cycle of client/server systems. Advanced technology such as distributed objects, CORBA and COM+, component technology, client/server system management.

The first part of this course covers underlying theory and fundamental solution methodologies of integer programming: optimality, relaxation, and bounds, complexity and problem reductions, branch and bound, cutting plane algorithms, strong valid inequalities and duality theory. The second part of this course covers some of the recent developments in mathematical programming: interior point methodology, conic optimization and semidefinite programming. Various applications in engineering, management, and financial economics are discussed.

This course emphasizes the use of numerical methods for solving financial problems. The numerical methods include: binomial trees, Monte Carlo simulation, stochastic programming, linear/quadratic control models and semidefinite programming techniques. Those techniques will be applied, among other things, to: option pricing, index tracking, portfolio optimization, interest rate models, and asset/liability management. Prerequisite: SEG 5480 or its equivalent.

Poisson process. Birth-and-death process, Markov chain. Martingale. Brownian motion. Renewal and stationary processes. Stochastic integration and Ito's formula. Applications to queueing models, inventory models, and financial investment/hedging models.

Utility theory. Mean-variance model. Capital asset pricing. Asset dynamics, Ito processes. Option pricing, Black-Scholes formula. Term structure, interest-rate derivatives. Introduction to stochastic optimal control model and Hamilton-Jacobi-Bellman equation.

Global logistics management. Facility location models. Network design. Transportation planning: mode selection, routing and scheduling. Transportation and transshipment problems. Vehicle routing models. Fleet management. Less-than-truckload deliveries. Warehouse layout and management. The lotsize/inventory/transportation tradeoff. Enabling technologies for logistics management.

Strategic importance of inventory management. Deterministic and stochastic inventory models. Co-ordinated replenishment for multiple items. Enterprise Resources Planning. Multi-echelon inventory management: constant and time-varying demand models. Push and pull systems. Coordination and incentive issues in a supply chain. The value of information. Strategic partnering and product design for supply chain management.

This course addresses the data and decision aspects of financial information systems. The data aspect includes collection, cleansing, storage, and retrieval of quantitative and qualitative financial data. The decision aspect include on-line analytical processing on financial data and data mining for nontrivial data pattern and knowledge.

Principles and theories underlying the design and implementation of human-computer spoken language systems. Component technologies including multilingual speech recognition, natural language understanding, dialog modeling, speech synthesis. Related topics including acoustic-phonetics in conversational speech. Linguistic features of spoken language, digital signal processing, pattern recognition, machine learning, statistical modeling and artificial intelligence. Software architectures that integrate the various component technologies. Examples of real applications. Students are advised to take ELE3410 before taking this course. Prerequisite: SEG2430 or with the approval of the course instructor.