A quickstart tutorial to the IAR Workbench IDE. Learn how to create a project, edit files, build solutions, and use the debugger.
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This module includes the basics and theories of ICT, including types of computer, networks, how, why and who people access information using ICT. This module is the first under the ECDL (AKA ICDL) qualification, written for Windows XP and Office 2003
This collection provides an overview of the 2008-'09 Open Education Cup competition. Contest rules, author resources, and example content are provided. This competition is intended to encourage development of original educational content in the field of parallel computing, with cash prizes awarded to contest winners. Selected modules will be included as part of a new collection available through Connexions.
This subset of the Black Box Software Testing collection includes resources to teach quality cost analysis, combination testing, regression testing, GUI regression automation, high volume test automation, requirements analysis, test documentation, test scripts, and scripted testing and inattentional blindness. Resources include lecture videos, slides, activities, and suggested readings.
The TI TMS320C54x microprocessor provides a number of ways to specify the location of data to be used in calculations. Immediate addressing, direct addressing, and indirect addressing are the three main types. Knowing the basic addressing modes of a mic
" This is a graduate course on the design and analysis of algorithms, covering several advanced topics not studied in typical introductory courses on algorithms. It is especially designed for doctoral students interested in theoretical computer science."
This course will present advanced topics in Artificial Intelligence (AI), including inquiries into logic, artificial neural network and machine learning, and the Turing machine. Upon successful completion of this course, students will be able to: define the term 'intelligent agent,' list major problems in AI, and identify the major approaches to AI; translate problems into graphs and encode the procedures that search the solutions with the graph data structures; explain the differences between various types of logic and basic statistical tools used in AI; list the different types of learning algorithms and explain why they are different; list the most common methods of statistical learning and classification and explain the basic differences between them; describe the components of Turing machine; name the most important propositions in the philosophy of AI; list the major issues pertaining to the creation of machine consciousness; design a reasonable software agent with java code. (Computer Science 408)
This is the final installment of my three part tutorial on the CNXML language. It is currently valid for the most recent release of the 0.3 language. The keywords contain a list of the tags described in this tutorial. Along with the example code in this module there is also an example module that has been growing throughout the tutorial.
Following a brief classroom discussion of relevant principles, each student completes the paper design of several advanced circuits such as multiplexers, sample-and-holds, gain-controlled amplifiers, analog multipliers, digital-to-analog or analog-to-digital converters, and power amplifiers. One of each student's designs is presented to the class, and one may be built and evaluated. Associated laboratory emphasizing the use of modern analog building blocks. Alternate years.
This course will expand upon SQL as well as other advanced topics, including query optimization, concurrency, data warehouses, object-oriented extensions, and XML. Additional topics covered in this course will help you become more proficient in writing queries and will expand your knowledge base so that you have a better understanding of the field. Upon successful completion of this course, the student will be able to: write complex queries, including full outer joins, self-joins, sub queries, and set theoretic queries; write stored procedures and triggers; apply the principles of query optimization to a database schema; explain the various types of locking mechanisms utilized within database management systems; explain the different types of database failures as well as the methods used to recover from these failures; design queries against a distributed database management system; perform queries against database designed with object-relational extensions; develop and query XML files. (Computer Science 410)
Materials covered include: special relativity, electrodynamics of moving media, waves in dispersive media, microstrip integrated circuits, quantum optics, remote sensing, radiative transfer theory, scattering by rough surfaces, effective permittivities, and random media.
This course is a graduate introduction to natural language processing - the study of human language from a computational perspective. It covers syntactic, semantic and discourse processing models, emphasizing machine learning or corpus-based methods and algorithms. It also covers applications of these methods and models in syntactic parsing, information extraction, statistical machine translation, dialogue systems, and summarization. The subject qualifies as an Artificial Intelligence and Applications concentration subject.
Recent results in cryptography and interactive proofs. Lectures by instructor, invited speakers, and students. Alternate years. The topics covered in this course include interactive proofs, zero-knowledge proofs, zero-knowledge proofs of knowledge, non-interactive zero-knowledge proofs, secure protocols, two-party secure computation, multiparty secure computation, and chosen-ciphertext security.
" This course covers concepts and techniques for the design and implementation of large software systems that can be adapted to uses not anticipated by the designer. Applications include compilers, computer-algebra systems, deductive systems, and some artificial intelligence applications. Topics include combinators, generic operations, pattern matching, pattern-directed invocation, rule systems, backtracking, dependencies, indeterminacy, memoization, constraint propagation, and incremental refinement. Substantial weekly programming Assignments and Labs are an integral part of the subject. There will be extensive programming Assignments and Labs, using MIT/GNU Scheme. Students should have significant programming experience in Scheme, Common Lisp, Haskell, CAML or some other "functional" language."
Building on Complex Adaptive Systems theory and basic Agent Based Modeling knowledge presented in SPM4530, the Advanced course will focus on the model development process. The students are expected to conceptualize, develop and verify a model during the course, individually or in a group. The modeling tasks will be, as much as possible, based on real life research problems, formulated by various research groups from within and outside the faculty.
Study Goals The main goal of the course is to learn how to form a modeling question, perform a system decomposition, conceptualize and formalize the system elements, implement and verify the simulation and validate an Agent Based Model of a socio-technical system.
This course focuses on the fundamentals of computer algorithms, emphasizing methods useful in practice. Upon successful completion of this course, the student will be able to: explain and identify the importance of algorithms in modern computing systems and their place as a technology in the computing industry; indentify algorithms as a pseudo-code to solve some common problems; describe asymptotic notations for bounding algorithm running times from above and below; explain methods for solving recurrences useful in describing running times of recursive algorithms; explain the use of Master Theorem in describing running times of recursive algorithms; describe the divide-and-conquer recursive technique for solving a class of problems; describe sorting algorithms and their runtime complexity analysis; describe the dynamic programming technique for solving a class of problems; describe greedy algorithms and their applications; describe concepts in graph theory, graph-based algorithms, and their analysis; describe tree-based algorithms and their analysis; explain the classification of difficult computer science problems as belonging to P, NP, and NP-hard classes. (Computer Science 303)
This is a textbook for first year Computer Science. Algorithms and Data Structures With Applications to Graphics and Geometry.
This course is offered to undergraduates and addresses several algorithmic challenges in computational biology. The principles of algorithmic design for biological datasets are studied and existing algorithms analyzed for application to real datasets. Topics covered include: biological sequence analysis, gene identification, regulatory motif discovery, genome assembly, genome duplication and rearrangements, evolutionary theory, clustering algorithms, and scale-free networks.