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Principles of Computer Science. This is an introductory course for non-CS majors to learn the fundamental concepts and topics of Computer Science CSand how CS is now impacting and changing every person's way of life.

The main topics covered include program design, software development, abstract thinking, information analysis, the Internet, algorithmic methodology.

The course will also discuss other topics including but not limited to modeling real-life phenomena, computing as a creative activity, social uses and abuses of information, and the foundations of cybersecurity. This course has a laboratory component.

Principles of Computer Science Lab. Introduction to Computer Science in Python. An introduction to computation and computational thinking, explored through programming in Python. Python is a scripting programming language that encourages exploration and quick development. This course assumes no prior programming experience and is appropriate for students in any discipline, such as linguistics, biology, business, and art. The student will leave the course with the ability to write clear and well-designed programs that solve interesting problems, and an appreciation of the power and beauty of computation.

Strings, tuples, lists, dictionaries; branching, iteration, abstraction through functions, recursion, higher order programming; insertion sort, binary search, turtle graphics, binary numbers, introduction to classes. Principles of software development are emphasized, including specification, documentation, testing, debugging, exception handling. Introduction to Computer Science in Python Lab.

Introduction to Cyber Security. This course introduces students to the rapidly evolving and critical international arenas of privacy, information security, and critical infrastructure, and is designed to develop knowledge and skills for security of information and information systems at both individual and organizational levels. Stakeholders of information security and privacy.

Framework of information security and privacy. Nature of common information hazards. Common cyber attacks and counter-measures. Operation and limitations of information and system safeguards.

Ethics, privacy, policy and information decisions. Legal aspects, professional practices, and standards for information security and privacy.

Security of national critical infrastructures. Special Topics in Computer Science. Selected topics in Computer Science. This course may or may not have a laboratory component or be taught online. Project oriented hands-on approach lab. Mandatory first day of attendance. A second course in computational thinking, through the lens of object oriented programming.

Fundamental concepts of object oriented programming and basic data structures. Types, classes, objects, inheritance, containers, OO software design, program structure and organization, reflection, generic programming. Lists, trees, stacks, queues, heaps, search trees, hash tables, graphs, complexity analysis.

C] or CS [Min Grade: Fundamental concepts of web development. Client side application development using web languages and technologies. Introduction to application development for mobile devices including those built on Android, iOS and Binary options streaming signals catalog four-letter course codes-undergraduate academic catalogs Phone using a popular mobile application development platform such as Cordova.

Covers unique requirements and constraints of mobile applications, foundations of mobile application development, syntax and semantics of web languages such as HTML, CSS and related frameworks, client side scripting including JavaScript and associated techniques such as jQuery and Ajax, principles for the design and evaluation of mobile user interfaces, storage and sensors.

Mobile Application Development Laboratory. Discrete mathematics for computer science, including elementary propositional and predicate logic, sets, relations, functions, counting, elementary graph theory, proof techniques including proof by induction, proof by contradiction, and proof by construction. Algorithms and Data Structures. Techniques for design and analysis of algorithms; efficient algorithms for sorting, searching, graphs, and string matching; and design techniques such as divide-and-conquer, recursive backtracking, dynamic programming, and greedy algorithms.

Algorithms and Data Structures Laboratory. Syntax, semantics and concepts of programming in Mathematica: Computer Organization and Assembly Language Programming. Register-level architecture of modern digital computer systems, digital logic, machine-level representation of data, assembly-level machine organization, and alternative architectures.

Laboratory emphasizes machine instruction execution, addressing techniques, program segmentation and linkage, macro definition and generation, and computer solution of problems in assembly language. Underlying network technology, including IEEE Interconnecting networks using bridges and routers.

IP addresses and datagram formats. Static and dynamic routing algorithms. Subnet and supernet extensions. E-mail and the World Wide Web. Network address translation and firewalls. Mandatory weekly Linux-based lab. Mandatory first day of class. Finite-state automata and regular expressions, context-free grammars and pushdown automata, computability. Probability and Statistics in Computer Science. Introduction to probability and statistics with applications in computer science. Counting, permutations and combinations.

Probability, conditional probability, Bayes theorem. Measures of central tendency and dispersion. Estimating probabilities by simulation.

Matrix computation is the foundation of data science, of many key areas of computer science machine learning, computer graphics, computer vision, high performance computingand of companies like Google. The main object of study in this course is the matrix, including matrix computation matrix multiplication, null space, solution of linear systems, least squares and applications e. Research project under supervision of faculty sponsor. Selected readings, research and project development under the direction of a faculty member.

CS is a programming language overview course. The course will discuss computability, lexing, parsing, type systems, and ways to formalize a language's semantics. The course will introduce students to major programming paradigms, such as functional programming and logic programming, and their realization in programming languages.

Students will solve problems using different paradigms and study the impact on program design and implementation. The course enables students to assess strengths and weaknesses of different languages for problem solving.

Study the design and implementation of compilers, including front-end lexer, parser, type checkingto mid-end binary options streaming signals catalog four-letter course codes-undergraduate academic catalogs representations, control-flow analysis, dataflow analysis, and optimizations to back-end code generation. Students will get hands-on experience by implementing several compiler components. Introduction to cloud computing architectures and programming paradigms.

Theoretical binary options streaming signals catalog four-letter course codes-undergraduate academic catalogs practical aspects of cloud programming and problem-solving involving compute, storage and network virtualization.

Design, development, analysis, and evaluation of solutions in cloud computing space including machine and container virtualization technologies. Digital media forensics addresses all stored digital evidence types faced by cyber security professionals and Computer Forensics Examiners. Students will learn to analyze character encoding, file formats, and digital media, including hard drives, smartphones, and cloud-hosted evidence, as well as disk acquisition and duplication techniques and how to apply these techniques in typical criminal investigation scenarios.

Relational model of databases, structured query language, relational database design and application development, database normal forms, and security and integrity of databases. Multimedia information processing, multimedia database architecture, multimedia database retrieval, semantic models for multimedia databases.

Database fundamentals, introduction to database security, overview of security models, access control models, covert channels and inference channels, MySQL security, Oracle security, Oracle label security, developing a database security plan, SQL server security, security of statistical databases, security and privacy issues of data mining, database applications security, SQL injection, defensive programming, database intrusion prevention, audit, fault tolerance and recovery, Hippocratic databases, XML security, network security, biometrics, cloud database security, big database security.

Introduction to cyber-investigative techniques involving network forensics. Students will develop and learn to apply new programs and techniques to automatically evaluate digital evidence from network packet captures, emails, server logs, social media, darknets and online forums related to cyber crime cases from both a law enforcement and incident response perspective.

Design and implementation of large-scale software systems, software development life cycle, software requirements and specifications, software design and implementation, verification binary options streaming signals catalog four-letter course codes-undergraduate academic catalogs validation, project management and team-oriented software development.

Advanced Web Application Development. Introduction to web application design and development. Covers responsive design for both mobile and desktop users, as well as hands on server provisioning and configuration. Advanced Web Application Development Laboratory.

Fundamental concepts of mobile application binary options streaming signals catalog four-letter course codes-undergraduate academic catalogs. Hybrid application development using web application technologies. Mobile form factor specific concerns. Conventional network security symmetric and public-key cryptography.

Message encryption and authentication. Theory and practice of metrics for performance and scalability of software systems. The course will introduce students to the principles of queuing theory and statistical analysis relevant to analyzing the performance of software products. Students will use profiling frameworks to identify binary options streaming signals catalog four-letter course codes-undergraduate academic catalogs range of performance problems in existing software.

Why and how binary options streaming signals catalog four-letter course codes-undergraduate academic catalogs fails, characteristics of secure and resilient software, life cycle of secure software development, metrics and models for secure software maturity, design methodology, best practices for secure programming, secure software for mobile computing, cloud computing and embedded systems, methodology for testing and validation.

Software Design and Integration.

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Principles and processes for the development of information technologies: Laboratory for design of hardware and software, and experiments in audio and image processing. Intended for students outside the College of Engineering. Credit is not given to Computer or Electrical Engineering majors. This course satisfies the General Education Criteria for: Introduction to selected fundamental concepts and principles in electrical engineering.

Emphasis on measurement, modeling, and analysis of circuits and electronics while introducing numerous applications. Includes sub-discipline topics of electrical and computer engineering, for example, electromagnetics, control, signal processing, microelectronics, communications, and scientific computing basics.

Lab work incorporates sensors and motors into an autonomous moving vehicle, designed and constructed to perform tasks jointly determined by the instructors and students. Introduction to digital logic, computer systems, and computer languages.

Topics include representation of information, combinational and sequential logic analysis and design, finite state machines, the von Neumann model, basic computer organization, and machine language programming.

Laboratory assignments provide hands-on experience with design, simulation, implementation, and programming of digital systems. Lectures and discussions relating to new areas of interest. May be repeated in the same or separate terms for unlimited hours if topics vary. See class schedule for topics and prerequisites. Discussions of educational programs, career opportunities, and other topics in electrical and computer engineering. For Computer Engineering and Electrical Engineering majors only.

The course includes bi-weekly electronics lab experiments designed to provide students with hands-on experience. Basic principles of circuit analysis and DC circuits; time-domain analysis of 1st and 2nd order linear circuits; complex numbers, phasors, AC steady-state analysis; frequency response; op-amp, diode, and BJT circuits; logic gates and digital logic circuits.

Laboratory experiments in digital logic and controllers; transistor amplifier and switching circuits; DC motor control and voltage regulators; sensors and motion control with feedback; wireless communication.

Analog signal processing, with an emphasis on underlying concepts from circuit and system analysis: Concepts from circuit and system analysis: Information hiding and object-oriented design as commonly implemented in modern software and computer systems programming. Approved written application to department as specified by department or instructors is required.

May be repeated in separate terms to a maximum of 2 hours. Introduction to active and passive photonic devices and applications; optical processes in semiconductor and dielectric materials including electrical junctions, light emission and absorption, and waveguide confinement; photonic components such as light emitting diodes, lasers, photodetectors, solar cells, liquid crystals, and optical fiber; optical information distribution networks and display applications.

Modeling of decisions in engineering work and the analysis of models to develop a systematic approach to making decisions. Fundamental concepts in linear and dynamic programming; probability theory; and statistics. Resource allocation; logistics; scheduling; sequential decision making; siting of facilities; investment decisions; application of financial derivatives; other problems for decision making under uncertainty.

Case studies from actual industrial applications illustrate real-world decisions. Introduction to discrete-time systems and discrete-time signal processing with an emphasis on causal systems; discrete-time linear systems, difference equations, z-transforms, discrete convolution, stability, discrete-time Fourier transforms, analog-to-digital and digital-to-analog conversion, digital filter design, discrete Fourier transforms, fast Fourier transforms, spectral analysis, and applications of digital signal processing.

Probability theory with applications to engineering problems such as the reliability of circuits and systems to statistical methods for hypothesis testing, decision making under uncertainty, and parameter estimation. Topics include sequential hypothesis testing, parameter estimation, confidence intervals, Bloom filters, min hashing, load balancing, inference for Markov chains, PageRank algorithm, vector Gaussian distribution, contagion in networks, principle component method and linear regression for data analysis, investment portfolio analysis.

Ethical issues in the practice of engineering: Philosophical analysis of normative ethical theories. Junior standing is required.

Basic understanding of electrical and computer engineering concepts applicable to technology management. Circuit components; dc fundamentals; ac fundamentals; semiconductors; operational amplifiers; device fabrication; power distribution; digital devices; computer architecture including microprocessors.

Intended for the Business Majors in the Technology and Management program. Electromagnetic fields and waves fundamentals and their engineering applications: Network equivalents; power and energy fundamentals, resonance, mutual inductance; three-phase power concepts, forces and torques of electric origin in electromagnetic and electrostatic systems; energy conversion cycles; principles of electric machines; transducers; relays; laboratory demonstration.

Electric power grid structure and policy; analysis of wind, solar, and fuels as raw resources; wind turbines and parks; solar cells, modules, arrays and systems; fuel cell power plants; energy and financial performance of green energy projects; integration of green energy into power grid; energy project report and presentation. Analysis and design of analog and digital electronic circuits using MOS field effect transistors and bipolar junction transistors, with emphasis on amplifiers in integrated circuits.

Students identify a suitable project, build a team, and explore the feasibility and potential solution space for the selected project area. The intellectual structure of the engineering design process is studied in detail in order to encapsulate the ideation and problem identification aspects of engineering senior design and facilitate student innovation. May be repeated in separate terms to a maximum of 4 hours. Physics and engineering principles associated with x-ray, computed tomography, nuclear, ultrasound, magnetic resonance, and optical imaging, including human visualization and perception of image data.

Concepts and abstractions central to the development of modern computing systems, with an emphasis on the systems software that controls interaction between devices and other hardware and application programs. Input-output semantics; synchronization; interrupts; multitasking; virtualization of abstractions.

Planning, designing, executing, and documenting a microcomputer-based project. Emphasis on hardware but special projects may require an equal emphasis on software. Special project or reading course for James Scholars in engineering. Approved written application to department as specified by department or instructor is required. Subject offerings of new and developing areas of knowledge in electrical and computer engineering intended to augment the existing curriculum.

See Class Schedule or departmental course information for topics and prerequisites. May be repeated in the same or separate terms if topics vary.

Special lecture sequences or discussion groups arranged each term to bring James Scholars in engineering into direct contact with the various aspects of engineering practices and philosophy. For Computer Engineering and Electrical Engineering majors with senior standing. An introduction to signal analysis and processing methods for advanced undergraduates or graduate students in the biological, physical, social, engineering and computer sciences.

Signal analysis methods and their capabilities, weaknesses, and artifacts with an emphasis on their practical application. Resonance and wave phenomena; Acoustics of rooms and transmission lines e. A lab component has been added to measure and model real loudspeakers and enclosures; Topics in digital audio, including AD and DA Sigma-Delta audio converters.

Parallel programming with emphasis on developing applications for processors with many computation cores. Computational thinking, forms of parallelism, programming models, mapping computations to parallel hardware, efficient data structures, paradigms for efficient parallel algorithms, and application case studies.

Basic computer organization and design: Laboratory for computer design implementation, simulation, and layout. Design, construction, and use of a small general-purpose computer with a micro-processor CPU; MSI and LSI circuits used extensively; control panel, peripheral controllers, control logic, central processor, and programming experiments. Underlying engineering principles used to detect small molecules, DNA, proteins, and cells in the context of applications in diagnostic testing, pharmaceutical research, and environmental monitoring.

Biosensor approaches including electrochemistry, fluorescence, acoustics, and optics; aspects of selective surface chemistry including methods for biomolecule attachment to transducer surfaces; characterization of bisensor performance; blood glucose detection; fluorescent DNA microarrays; label-free biochips; bead-based assay methods.

Case studies and analysis of commercial biosensor. Characteristics of speech and image signals; important analysis and synthesis tools for multimedia signal processing including subspace methods, Bayesian networks, hidden Markov models, and factor graphs; applications to biometrics person identification , human-computer interaction face and gesture recognition and synthesis , and audio-visual databases indexing and retrieval.

Concepts and applications in image and video processing; introduction to multidimensional signal processing: Development of real-time digital signal processing DSP systems using a DSP microprocessor; several structured laboratory exercises, such as sampling and digital filtering; followed by an extensive DSP project of the student's choice. Theory and laboratory experimentation with three-phase power, power-factor correction, single- and three-phase transformers, induction machines, DC machines, and synchronous machines; project work on energy control systems; digital simulation of machine dynamics.

Advanced rotating machine theory and practice: Design, application, analysis, and evalution of communication network protocols under both Linux and Windows NT operating systems. Emphasis on identifying problems, proposing alternative solutions, implementing prototypes using available network protocols and evaluating results.

Multiple programming team projects. Hands-on exposure to fundamental technology and practical application of sensors. Capacitive, inductive, optical, electromagnetic, and other sensing methods are examined.

Instrumentation techniques incorporating computer control, sampling, and data collection and analysis are reviewed in the context of real-world scenarios. Overview of wireless network architectures including cellular networks, local area networks, multi-hop wireless networks such as ad hoc networks, mesh networks, and sensor networks; capacity of wireless networks; medium access control, routing protocols, and transport protocols for wireless networks; mechanisms to improve performance and security in wireless networks; energy-efficient protocols for sensor networks.

Advanced concepts including generation-recombination, hot electron effects, and breakdown mechanisms; essential features of small ac characteristics, switching and transient behavior of p-n junctions, and bipolar and MOS transistors; fundamental issues for device modeling; perspective and limitations of Si-devices. This course explores the energy conversion devices from fundamentals to system-levels including electronic structure of semiconductors; quantum physics; compound semiconductors; semiconductor heterostructures and low dimensional quantum structures; energy transfer between photons and electron-hole pairs; photon emission and capture processes; radiative and non-radiative processes; light extraction and trapping; emission and absorption engineering; electrical and optical modelling via numerical and TCAD simulation tools; hands-on characterization of modern light emitting diodes and solar cells.

Fabrication lab emphasizing physical theory and design of devices suitable for integrated circuitry; electrical properties of semiconductors and techniques epitaxial growth, oxidation, photolithography diffusion, ion implantation, metallization, and characterization for fabricating integrated circuit devices such as p-n junction diodes, bipolar transistors, and field effect transistors. Individual design projects in various areas of electrical and computer engineering; projects are chosen by students with approval of instructor.

A professionally kept lab notebook, a written report, prepared to journal publication standards, and an oral presentation required. Interdisciplinary approach to learning principles of experimental research. Presentation methods explored include poster session, conference talk, and journal paper. Open-ended labs and a project reinforce concepts discussed in class. Microwave circuit design of amplifiers, oscillators, and mixers. Manual- and computer-controlled laboratory analysis of circuits at microwave frequencies.

Plane waves at oblique incidence; wave polarization; anisotropic media; radiation; space communications; waveguides. Design of a radio system for transmission of information; modulation, receivers, impedance matching, oscillators, two-port network analysis, receiver and antenna noise, nonlinear effects, mixers, phase-locked loops.

Antenna parameters; polarization of electromagnetic waves; basic antenna types; antenna arrays; broadband antenna design; antenna measurements. Optical beams and cavities; semiclassical theory of gain; characteristics of typical lasers gas, solid state, and semiconductor ; application of optical devices. Engineering and physical principles on which GPS operates, including orbital dynamics, electromagnetic wave propagation in a plasma, signal encoding, receiver design, error analysis, and numerical methods for obtaining a navigation solution.

GPS as a case study for performing an end-to-end analysis of a complex engineering system. Electromagnetic wave propagation, microwave transmission systems, passive components, microwave tubes, solid state microwave devices, microwave integrated circuits, S-parameter analysis, and microstrip transmission lines.