Studies fundamental spatial concepts, models of spatial information, representation and algorithms, spatial abstract data type, spatial query, computational geometry, and spatial access methods.
Advanced VLSI Designs(3)
This course covers the advanced system-level VLSI design methodology. It includes system-level design specification - VHDL vs graphical HDL, ASIC vs FPGA, simulation-based verification vs emulation-based verification, and HW/SW codesign.
Techniques for discovering valuable knowledge from very large collections of data stored in databases or data warehouses. Issues in data preparation, data reduction, and the statistical and machine learning techniques for extracting important patterns in the data will be discussed.
Advanced Multimedia Systems(3)
This course covers exclusive knowledge about multimedia systems, such as MPEG-II, MPEG-IV, multimedia interface, multimedia OS, multimedia DB.
Advanced Wireless Networking(3)
This course introduces how wireless system works, how mobility is supported, how infrastructure underlies such systems, and what interactions are needed among different functional components. The objective is to make EE and CSE students get the overview from the characteristics of radio propagation to various applications in wireless systems.
Advanced Software Engineering(3)
The objectives of this course are to define what is meant by software engineering, to discuss the knowledge in the most effective way to produce high-quality software systems. This course covers formal methodologies, software process models, software development methods including object-oriented method, software architecture, and software development management, etc.
Advanced Operating Systems(3)
Process synchronization and scheduling; Concurrency and Deadlock control; Virtual memory management; Inter-process communication; Distributed processing; and Security.
Applied Graph Theory(3)
The first part of this course gives an introductory subject of general graph theory. The detail chapters are path, coloring, tree, planarity, network flow. And the following second part explains some topics on Perfect Graph Theory, Matching, Cycle space and bond space. Some application for this graph theory will be introduced, eg., VLSI routing, Network packet routing. New trends in the current graph theory such as hypercube, graph embedding, processor allocation will be discussed. Prerequisites are discrete mathematics, algorithm and data structure.
This course covers the mobile communication techniques. The characteristics of wireless media, FDMA, TDMA, CDMA, PCS, Wireless LAN technique are also covered. Students also study the recent issues in the mobile communication networks.
Advanced Embedded System Design(3)
Advanced Embedded System Design is an advanced graduate level course intended to expose students to the state-of-the-art design and analysis techniques for embedded systems. Fueled by advances in semiconductor technology and consumer demands, many embedded systems have become so complex that the design capability simply prevents such systems to be realized. In the last decades, new research areas targeting at advanced embedded system design have emerged. In this course, major results in this field will be discussed. The main topics include system modeling, performance and power/energy analysis and estimation, system-level partitioning, synthesis and interfacing, co-simulation and emulation, and reconfigurable computing platforms. Research papers with significant impacts on the above topics are studied in detail. Class discussions and research project participation are integral parts of the course.
Advanced Information Retrieval(3)
The primary focus of this course is on viewing information retrieval(IR) in terms of information distribution. This course is designed to provide students with a strong base to learn skills and techniques of large-scale information retrieval and to understand how the methods of information retrieval are changed in today's ever-changing internet environment. Current research in online searching such as Google and other famous IR systems is also covered. This course touches ontologies related to Web 3.0 as well.
Advanced Compiler Construction(3)
Advanced Compiler Construction course introduces general topics to construct the compilers of modern procedural programming languages including scanning, parsing, generating codes (both intermediate codes and target codes). To generate an efficient target code, lots of analyses are required. Some of these analysis methods are also introduced. Further, this course provides the students to have chance to implement a small compiler of their own procedural languages. Some of scanner generators and parser generators (lex/yacc, Java CPU, or JavaCC) are also be introduced to help the students to implement their own compilers. The students will understand the whole procedure of compilation and will be able to co-work with any language implementation project.
Advanced Computer Architectures(3)
This subject researches issues about advancing the performance of computer system architecture.
For example, recent advances of internal processor architecture, I/O system architecture, management of memory devices, inter-connectivity, and so on.
Advanced Computer Networks(3)
Advanced course in computer networks. Through this course, students can learn about the graph theory, queuing theory, and the various network simulation techniques. We also study the designing technique for the various networks such as LAN, PSDN, and the broadband ISDN.
Fundamentals of binary machine vision. Analysis of illumination and texture. Perspective projective geometry and analytic photogrammetry. Shape from X. Image matching and consistent-labeling method. Object models and matching. Knowledge-based vision systems.
This course covers topics related with object-oriented databases. Topics include object-oriented data models, query language, versions, evaluation, authorization, query processing, storage management and indexing
Object-Oriented Software Development Methodology(3)
The objectives of this course are to define what is meant by object-orientation, and to study the pros and cons of object-oriented methodologies in the real world: Object Modeling Techniques (OMT) and Unified Software Development Process, etc. This course covers object-oriented software development concepts, static and dynamic modeling techniques, Unified Modeling Language (UML), and software analysis and design methodologies using UML, etc.
In this course we will investigate the cluster of computers as a computing platform for concurrent computing. By the end of the course, each student should understand, at a deep level, several specific hardware and software tradeoffs for application performance, development, and management on a cluster of computers.
The objective of the course is to introduce students to the issues found in designing and using a cluster for high performance computation. Topics include low latency communication protocols, NIC architecture, cluster and meta-computing, the Computational Grid, shared memory, parallel I/O, data-intensive computation on clusters.
VLSI Testing and Diagnosis(3)
This course covers the testing and diagnosis methodology for VLSI. It includes the fault modeling, combinational deterministic test pattern generation, sequential test pattern generation, scan-based test, built-in self-test, fault simulation, and learning.
Topics in Data Indices(3)
Studies static hashing and dynamic hashing, heap and deap, AVL tree and 2-3-4 tree, red-black tree, B-tree, and trie as advanced data structurs. Includes KDB-tree, R*-tree, grid file, quad-tree for a secondary storage space. Learn to develop cost model and to implement advanced data structures with C++.
Design of Multimedia Systems(3)
Multimedia software systems concepts and architecture. Topics include multimedia retrieval, representations, multimedia databases, geographic information systems. R-tree, video databases, and multimedia operating systems. Design of high performance media servers.
Topics in Multimedia Processing(3)
The course covers current techniques for processing, storage and delivery of media such as speech, audio, images, and video. This requires an in-depth understanding of digital signal processing for 1D signals, as well as the extensions to 2D and 3D cases. The emphasis will be on the theoretical basis as well as efficient implementations. Key components studied in details are digital filters, transforms, quantizers, bit allocators, entropy coders, motion estimation and compensation algorithms.
Technologies for the future networks are covered. We study the technology for personal communication networks, the multimedia networks, and the intelligent networks. Especially, we study the hot technical issues such as PCS, IN, and ATM networks.
Topics in Distributed Database(3)
This course covers topics related with distributed databases. Topics include distributed DBMS architecture database design, query decomposition, optimization, transaction managements, concurrency management.
Advanced Distributed Systems(3)
This subject deals with the concept of distribution processing, distributed operating system, distributed DB, heterogeneous distributed environment and interactive operation.
Topics in Bioinformatics(3)
Bio-informatics is a vast and rapidly growing interdisciplinary area encapsulating the analysis of information present in biological systems as well as the use of bio-molecules in the construction of future information processing systems. It is often projected that Bio-informatics will be to the 21st Century what CS has been to the present one. This seminar course will concentrate on a selection of computational problems of contemporary molecular biology and genomics such as: physical and genetic mapping, protein folding and structure prediction, sequence homology and alignment, evolutionary trees and computational models of development, and DNA computing.
Topics in Software Engineering(3)
This course aims to cover in depth specific topics in software engineering. Typical topics include software design, software testing, and software quality. Students must read several papers relevant to the topics and participate in discussion actively. In addition, more practical techniques and tools as well as fundamental theories are covered.
Software Reuse Methodology(3)
In this course, we discuss the recent research topics in software reuse. There are many existing software reuse techniques. We understand the concepts of software reuse and think about the improvement of those techniques. Specially, component-based software development and maintenance will be covered.
Systems Design Automation(3)
This course covers the all aspects of modern design automation for beyond of VLSI era. It includes synthesis techniques for deep sub-micron, synthesis techniques for ultra-low power, and synthesis techniques for SOC(system on chip).
Advanced Neural Networks(3)
It adjusts and applies the natural language processing ,the image processing, the voice recognition, the detection of cancer and the noise or the transform processing which is difficult to solve in artificial intelligence field by using learning algorithm of neural network.
This subject introduces signal processing which is concerned with image processing, voice recognition and information transmission on computer network. We apply the related application field and new technology.
Topics in Real-Time Systems(3)
Real-time requirements; Real-time scheduling algorithms; Real-time resource management; Real-time file system; and Case studies.
Algorithm engineering includes the implementation, experimental testing, and fine-tuning of theoretically efficient algorithms to the point where they can be usefully applied in practice. Algorithm engineering is a new branch of algorithms research that has grown rapidly in the past few years.
Advanced Image Processing(3)
Basic concept of image interpretation. Image segmentation methods based on intensity discontinuity, region similarity, and motion. Representation of image features and their description. Matching technologies and image interpretation approaches.
This subject deals with the cellular automata(CA). directly, formalize configuration of CA, and rearch the pattern of CA
Ubiquitous Sensor Network(3)
This course covers the wireless sensor network technology such as wireless media characteristics, antenna, network architecture, MAC, routing, middleware, security, various sensor technique, and applications. This course also covers the standards and trends in the wireless sensor networks.
Applied Network Theory(3)
This course presents the fundamental theory concepts for network modeling and provides advanced theories including: (1) optimization techniques based on Markov Process and Markov Decision Processes, (2) Graph theory for network topology design, (3) queueing theory for network performance measurement, and (4) congestion control and QoS (Quality of Service). This course is willing to help graduate students to write and publish more advanced research papers
Advanced Artificial Intelligence(3)
This course provides a broad exposure to the advanced topics in artificial intelligence. Main topics include knowledge representation, intelligent systems, problem solving, planning, uncertainty, probabilistic reasoning, and other topics. The objectives of this course are (1) to instruct algorithms and methods of knowledge representation, knowledge learning and rule extraction for developing an intelligent system, (2) to enable students to apply these techniques in application which are related to their own interests, and (3) to improve the students' ability to solve problems.
Topics in Internet Application Systems(3)
Studies on the communication software such as TCP/IP, X.25, HTTP, RTP, E-mail, FTP, WWW, and API. The course also covers the multimedia application software.
Natural Language Processing(3)
This course gives an overview of main thrusts in natural language processing (NLP) to students, starting with fundamental concepts and ideas, leading into more recent directions of statistics-based probabilistic approaches in this area. The strengths and weaknesses of established systems used in machine translation, information-retrieval, user interface and knowledge extraction will be analyzed in this course, and then the future directions will be provided as well. This course helps students to understand not only the algorithms available for processing linguistic information but also the underlying computational properties of natural languages. Morphological, syntactic, and semantic processing from both linguistic and algorithmic perspectives are considered.
Principles and techniques for building adaptive systems to solve practical problems by employing algorithms based on computational models of natural genetics and evolution. The course first introduces the principles of evolutionary algorithms, and then discusses their applications to search, optimization, scientific modeling, and machine learning. Other meta-heuristic algorithms such as simulated annealing and tabu search will also be discussed for comparative studies.
Advanced Computer Graphics(3)
This course deals the current topics in computer graphics: theory and practice. Main subjects include new techniques of ray tracing, fractal geometry, morphing, animation, particle system. Prerequisites are Calculus, introduction to computer graphics, discrete mathematics. All Attendee should be no difficult to use OpenGL, OpenInventor, C, C++ graphics programming. Term Project will be assigned in the end of this course.
Topics in Computer Network(3)
This course is an advanced course to computer networks, which emphasizes the performance and engineering tradeoffs in the design and implementation of computer networks. The goal is for graduate students to learn not only what computer networks are and how they work today, but also why they are designed the way they are and how they are likely to evolve in the future. Topics to be covered include: wireless networks, sensor networks, ubiquitous networks, congestion/flow/error control techniques, high speed networks, and network optimization.
Computer Security and Cryptology(3)
This course will cover about classic and contemporary topics on cryptology. That is, it will cover about cryptographic primitives such as private key crypto algorithm, public key cryptosystem, security protocols and cryptographic primitives, etc. Also, this course will cover about the crypt-analytic techniques including with the DPA(Differential Power Analysis) and LC(Linear Cryptanalysis). To fully understand about the principles of the cryptosystem, this course will also deal with the discrete mathematics, number theory (prime numbers, factorization, modular arithmetic) and complexity theory, which are known to closely related to the cryptology.
Pattern Recognition uses the neural network and applies the preprocessing and the image processing about various types of characters and images. It researches the method to recognize the real world pattern effectively.
Advanced Programming Languages(3)
This subject introduces principles of functional, imperative, and logic programming languages. Programming experience and background in language implementation required.
Functional Programming course introduces the main concepts of functional programming including pure functions, recursion, and algebraic data structure. One of the algebraic data structure is a list. To handle the lists in a functional style, natural recursion is inevitable. This course focus on the actual programming of the natural recursion, that is mapping the functional concepts into programs. The students will understand the particular concepts of functional languages and will be able to attain the principles of functional programming.