Spread the Love, the KSU Writing Center Way ♥
Ahh, Valentines Day.
What a wonderful time for love - for fancy dates - for all those sappy gifts of chocolates, roses, and fluffy teddy bears. But, most of all, what a wonderful time for writing.
It’s true. During this loving time, many people express their love for their significant others through writing. Whether it be a poem, a note, a card, or a scribbled punny joke, people find ways to express their love through written words.
Although many people feel that they can only write a sappy card, poem, note, or punny joke to their significant others (i.e. their boyfriend/girlfriend or girl/boy they have been crushing on for the past five months), this is far from the truth.
In fact, there are many other, non-significant-other people who would love to become significant to you through your written love this Valentine’s day.
And the KSU Writing Center would love to introduce you to some of those people!
For the next two weeks, the KSU Writing Center is hosting “Valentines for Senior Sweethearts,” where you can make valentines for the folks at the Bentley Center for Adult Day Health in Athens, GA.
From February 1-12, stop by the KSU Writing Center on either campus to spread the love!
In addition, at the Kennesaw Campus Carmichael Student Center rotunda on February 4th from 12:30 - 3:30, KSU Writing Center assistants will have card-making supplies available for anyone to stop by to make valentines for the senior sweethearts!
We’ll also have cookies and other goodies to share with those who share their own sweetness by making a valentine.
Here’s a re-cap of the event details:
What: Valentines for Senior Sweethearts
When & Where: February 1-12 @ The KSU Writing Center (Marietta Campus & Kennesaw Campus) & February 4 @ the Carmichael Student Center rotunda from 12:30 - 3:30
Thanks for helping the KSU Writing Center spread the love this Valentines day!
✎ Write on!
New Year, New Writing Habits
Welcome back, KSU Writing Owls!
It’s back to school for the new year, which also means it’s back to writing all of those papers for your new classes!
Never fear though; the KSU Writing Center is also back, ready to help you with any and all of your writing assignments.
In fact, in hopes of inspiring you to prepare for your new writing endeavors this year, a few of the KSU Writing Center Assistants shared some writing habits that you can develop to start the New Year off “write”!
#1. Don’t procrastinate
A good paper requires a lot of thought and consideration, which, despite what many believe, is not possible the night before it is due.
Upon receiving your writing assignment, immediately allow your mind to spin with ideas of what you want to write about. If the ideas do not come so easy to you, don’t wait around until they come to you. After class, take some time to brainstorm, conduct a little (or a lot) of research, and you will have the perfect topic picked out within the first few days it was assigned, which means you will be ready to get started on your paper right away!
#2. Free Write
Remember that thing that your middle and high school teachers always made you do at the beginning of class? When they told you to take out your journals and begin writing? Well, that’s freewriting, and although you may have questioned its purpose back then, I can assure you that it can give you a major advantage now. With freewriting, you can just write continuously without worrying about spelling or grammar. This strategy is known to help writers overcome any blocks and to just get ideas down as soon as they come to mind. Your free write may read like a mess at first, but when you begin to organize your ideas for the paper, you will find that you can use much of these thoughts in your actual paper - which brings us to our next New Year’s Writing Habit, Outlining.
#3. Outline
After you have released all of your ideas from your mind and have them out on your paper, you can begin to organize them in a way that makes sense for your paper. I suggest writing down, on a paper, or on your computer screen, the order in which you would like your thoughts to appear.
Write out:
Introduction
-Hook
-Thesis
Paragraph 1
-Supporting Points 1, 2, 3
Paragraph 2
-Supporting Points 1, 2, 3
–etc. This type of outline will make it easy for you to see exactly how your paper will read.
Whether you organize your paper in a pros/cons format, or a past/present format, there are so many ways to organize a paper, but the best way to begin is by actually writing out the outline so that you may determine how you want your readers to read it.
#4. Read Your Paper Out Loud
If you have ever visited the KSU Writing Center, you know that we will often ask you if we (or you) can read your paper out loud. This is in no way meant to embarrass you, but rather to allow you to hear your own words spoken out loud, so that you can hear how others read your thoughts. If all you do is read your paper to yourself, you will fail to hear the effect that it has on your readers and you will most likely miss multiple grammar errors, such as missing commas and subject-verb disagreement. Reading it out loud can also lead to some helpful feedback from your peers.
#5. Get Feedback
Reading your paper out loud goes hand in hand with getting feedback. It never hurts to have as many eyes on your paper as possible, since everyone reads and interprets messages in different ways, and if you want your paper to be as clear and effective as possible, you will make a point to get feedback from as many people as possible.
Lastly, make it a new (or continued) habit to visit the KSU Writing Center. The KSU Writing Assistants can help you adjust to and build upon these good writing habits so that you may be successful in all of your writing endeavors this year!
✎ Write On!
Imagination Inspiration -- What Leslie Loves to Write About
Although the Fall semester may be coming to a close, bringing Winter back to chill our bones, this does not mean you have to stop falling…🍂 in love with writing. In fact, one of the beauties of writing is that you never have to stop. Whether it be Fall 🍂, Winter ❄, Spring 🌷, or Summer ☀, you can continue to fall in love with writing every single day.
Leslie Goodwin, a KSU Writing Center writing assistant reminds us of the beauty of writing that sprouts from the imagination.
“My favorite things to write about are from my own imagination. Like sure, real world things can be cool. Analysis is fun when you get to argue a point (or at least, I think it’s fun…), but when I can create something from scratch is when I feel like I flourish the most. It’s really awesome to go from having just an idea in your head - say, you want to write about a family of purple aliens - and watching it grow into something more complex. The family of purple aliens lives inside Neptune and they watch Earth movies in their free time. Because they can totally pick up on our satellite signals from Neptune. None of that is real of course. There’s no purple aliens living inside Neptune that I know of. In my opinion, though, that’s the beauty of it. You can make anything you want to. And that’s why I like writing about things from my imagination.”
Like Leslie says, you do not have to write about “real world things.” Instead, you can let your creative mind take over to write a completely original piece. The best part is that everything that you write down comes from your own imagination, so you can make it as crazy, depressing, romantic, serious, or haunting as you like.
This type of free form writing is a great activity to practice your writing, or to just occupy your time over the break!
With that being said, we wish you all a wonderful break and encourage you to ✎ write on!
Science Stimulation -- What Theresa Loves to Write About
As we approach the end of the semester, it is likely that many of you have some major paper deadlines approaching. If you have yet to determine what your final paper topic will be, perhaps words from Theresa, a KSU writing assistant, about her passion for science will give you some ideas.
“I love to write about what I am passionate about, science. Sounds too simple, but I love to write about what I love. Writing is a document of your mind’s explorations. Not only do I value our brain’s endless capability to think, but it’s awesome to be able to look back and evaluate your thought process. If you didn’t write it down, you might have overlooked a brilliant discovery. Also, you may miss what is so brilliant about a discovery that no one knows about. This is where writing and communication comes in. Sharing your thoughts not only benefits you, but society as well. With this said, I enjoy writing research papers, particularly in the science field.”
If you, too, enjoy writing research papers about science, stop by the Writing Center to ask Theresa or any of our other writing assistants to help you brainstorm for your paper!
Also, even though Winter is just around the corner, there is still a few more days of Fall, and with that, more inspirational thoughts from our KSU Writing Center writing assistants who are eager to share how they fall…🍂 in love with writing about their favorite paper topics.
✎ Write On!
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CS 2290 - Special Topics
The course covers special topics at the intermediate level that are not in the regular course offerings.
Prerequisites: Approval of the instructor, major area committee, and department chair.
Credits: 3
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CS 3223 - Computer Architecture
A study of instruction set architectures; basic processor components such as control units, ALU's, and registers; memory; input/output; and performance enhancement using caches and pipelines. Design of the major processor components is discussed in terms of the concepts presented in . Some coverage of assembly language programming is included.
Prerequisites: and CSE 1301
Credits: 3-0-3
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CS 3305L - Data Structures Lab
This laboratory course will cover the implementation of data structures concepts in a contemporary programming language.
Prerequisites: (CSE 1322 and CSE 1322L) and MATH 2345
Credits: 1
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CS 3305 - Data Structures
This course introduces data structures, specification, application, and implementation. The case studies will illustrate how data structures are used in computing applications. The emphasis of the course is on linear and some nonlinear data structures and object oriented principles. Topics include: abstract data types, stacks, queues, lists, binary search trees, priority queues, recursion, algorithm efficiency, trees, heaps, hash tables, and analysis of search and sort algorithms and their performance for implementation and manipulation. The programming language to be used in this course is any standard high-level object-oriented programming language such as C++, Java, and Ada.
Prerequisites: MATH 2345 and (CSE 1322 and CSE 1322L)
Credits: 3
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CS 3410 - Introduction to Database Systems
Introduction to the database management systems, database processing, data modeling, database design, development, and implementation. Contrasts alternative modeling approaches. Includes implementation of current DBMS tools and SQL.
Prerequisites: A grade of B or better in both CSE 1322 and CSE 1322L
Credits: 3
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CS 3502 - Operating Systems
This course introduces the fundamental concepts and principles of operating systems. Topics covered include system performance, processes and threads, multiprogramming, scheduling, memory management, synchronization, deadlocks, file systems, Input/output systems. Additional topics: security and protection, network and distributed OS.
Prerequisites: (CS 3503 and CS 3503L) and (CS 3305 and CS 3305L)
Credits: 3
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CS 3503L - Computer Organization and Architecture Lab
This course will provide the student the opportunity to access some of the physical components of a computer and generate code to manipulate these components.
Prerequisites: CSE 1322 and CSE 1322L
Credits: 1
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CS 3503 - Computer Organization and Architecture
Introduction and overview of basic computer organization. Computer arithmetic: binary, hexadecimal and decimal number conversions, binary number arithmetic and IEEE binary floating point number standard. Basic computer logic: gates, combinational circuits, sequential circuits, adders, ALU, SRAM and DRAM. Basic assembly language programming, basic Instruction Set Architecture (ISA), and the design of single cycle CPU. Hardware security will be introduced.
Prerequisites: CSE 1322 and CSE 1322L
Credits: 3
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CS 4242 - Artificial Intelligence
The primary objective of this course is to provide a introduction to the basic principles and applications of Artificial Intelligence. It covers the basic areas of artificial intelligence including problem solving, knowledge representation, reasoning, decision making, planning, perception and action, and learning -- and their applications. Students will design and implement key components of intelligent agents of modern complexity and evaluate their performance. Students are expected to develop familiarity with current research problems, research methods, and the research literature in AI.
Prerequisites: CS 3305 and CS 3305L
Credits: 3
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CS 4265 - Big Data Analytics
This course covers algorithms and tools that are needed to build MapReduce applications with Hadoop or Spark for processing gigabyte, terabyte, or petabyte-sized datasets on clusters of commodity hardware. A wide range of data algorithms will be discussed in this course.
Prerequisites: A grade of C or better in (CS 3305 and CS 3305L) and CS 3410
Credits: 3
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CS 4267 - Machine Learning
This course covers the-state-of-the-art machine learning techniques. Focuses will be put on deep learning, kernel methods and ensemble learning. Students will learn applying advanced machine learning techniques to solve challenging problems, especially big data problems.
Prerequisites: A grade of C or better in (CS 3305 and CS 3305L) and CS 3410
Credits: 3
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CS 4270 - Intelligent Systems in Bioinformatics
Biological sciences are undergoing a revolution in how they are practiced. In the last decade, a vast amount of biological data has become available, and computational methods are playing a fundamental role in transforming this data into scientific understanding. Bioinformatics involves developing and applying computational methods for managing and analyzing information about the sequence, structure and function of biological molecules and systems. This course covers a wide range of machine learning, data mining, and computational algorithms to solve various bioinformatics research problems.
Prerequisites: A grade of C or better in (CS 3305 and CS 3305L) and CS 3410
Credits: 3
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CS 4305 - Software Engineering
This course provides an overview of the software engineering discipline with emphasis on the development life cycle and UML modeling. It introduces students to the fundamental principles and processes of software engineering, including Unified, Personal, and Team process models. This course highlights the need for an engineering approach to software with understanding of the activities performed at each stage in the development cycle. Topics include software process models, requirements analysis and modeling; design concepts and design modeling; architectural design and styles; implementation; and testing strategies and techniques. The course presents software development processes at the various degrees of granularity.
Prerequisites: CS 3410, CSE 3801, COM 1100
Credits: 3
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CS 4306 - Algorithm Analysis
Advanced algorithm analysis including the introduction of formal techniques and the underlying mathematical theory. Topics include asymptotic analyses of complexity bounds using big-O, little-o, omega, and theta notations. Fundamental algorithmic strategies (brute-force, greedy, divide-and-conquer, backtracking, branch-and-bound, pattern matching, parallel algorithms, and numerical approximations) are covered. Also included are standard graph and tree algorithms. Additional topics include standard complexity classes, time and space tradeoffs in algorithms, using recurrence relations to analyze recursive algorithms, NP-completeness, the halting problem, and the implications of non-computability.
Prerequisites: CS 3305 and CS 3305L
Credits: 3
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CS 4308 - Concepts of Programming Languages
This course covers the fundamental concepts on which programming languages are based and the execution models supporting them. Topics include values, variables, bindings, type systems, control structures, exceptions, concurrency, and modularity. Languages representing different paradigms are introduced.
Prerequisites: (CS 3503 and CS 3503L), and (CS 3305 and CS 3305L)
Credits: 3
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CS 4322 - Mobile Software Development
This course primarily focuses on mobile sensor application development and security of smartphones and mobile telecommunication systems. The goals of the course is to provide students with real world relevant mobile sensor app development and improve their knowledge and skills on mobile application development and mobile security.
Prerequisites: (CS 3305 and CS 3305L) and (CS 3410 or CSE 3153) and SWE 3313
Credits: 3
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CS 4400 - Directed Studies
This course covers special topics of an advanced nature that are not in the regular course offerings. Up to three hours may be applied to the major area.
Prerequisites: Approval of the instructor, major area committee, and department chair.
Credits: 1-3
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CS 4412 - Data Mining
This course covers fundamental data mining concepts and techniques for discovering interesting patterns from data in various applications. Topics include data preprocessing, data warehousing and OLAP, mining frequent patterns, classification, clustering, and tend analysis.
Prerequisites: (CS 3305 and CS 3305L) and CS 3410
Credits: 3
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CS 4491 - Advanced Topics in Computer Science
This course provides the current and relevant topics in an advanced Computer Science area of interest to faculty.
Prerequisites: A grade of C or better in any prerequisite course. Prerequisite course(s) vary depending upon the topic.
Credits: 3
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CS 4504 - Distributed Computing
A course that introduces students to the fundamental principles common to the design and implementation of programs that run on two or more interconnected computer systems. The subtopics, which are based on these principles, include: distributed operating system and network protocols for process communication, synchronization, scheduling, and exception and deadlock resolution; understanding of client-server, web-based collaborative systems; parallel computing; concurrency issues; and API's for distributed application development. Several distributed computing environments, like MPI, PVM, and Java RMI are discussed and used in developing experimental projects in a cluster of networked computers.
Prerequisites: CS 3502
Credits: 3
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CS 4512 - Systems Programming
This course presents an introduction to systems programming in Linux/Unix. Topics include file I/O, process control and communication, threading, and network-aware systems programs.
Prerequisites: (CS 3305 and CS 3305L), and CS 3502
Credits: 3
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CS 4514 - Real-Time Systems
This course covers the software-development life cycle as it applies to real-time systems. Alternatives: • Including labs that involve the use of a real-time operating system and an associated development environment, or • Modeling with UML, and object oriented simulation. Introduction to formal specification of real-time systems. A course project is required to be completed by the end of the semester.
Prerequisites: CS 3502
Credits: 3
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CS 4522 - HPC & Parallel Programming
This course will introduce parallel programming techniques for shared memory and distributed memory systems. Topics include threading, OpenMP, and MPI.
Prerequisites: (CS 3305 and CS 3305L), and CS 3502
Credits: 3
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CS 4523 - Programming Massively Parallel Processors
A study of practical parallel algorithms with an emphasis on implementation and performance issues on massively parallel processors. Design and implement high performance computing applications using CUDA running on Graphics Processing Unit (GPU). Topics include heterogeneous parallel programming, hardware threading models, synchronization, parallel blocking algorithms, register allocations, memory performance, and inter-thread communication.
Prerequisites: (CS 3305 and CS 3305L), and CS 3502
Credits: 3
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CS 4524 - Cloud Computing
This course discusses the fundamental concepts and techniques of cloud computing. Students will develop an understanding of cloud computing architecture, Infrastructure as a Service (IaaS), Platform-as-a-Service (PaaS), Software as a Service (SaaS), Virtualization, and Application Development on Cloud.
Prerequisites: (CS 3305 and CS 3305L) and CS 3502
Credits: 3
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CS 4612 - Secure Software Development
This course covers the design and implementation of secure software. Some of the topics covered are the characteristics of secure software, the role of security in the development lifecycle, designing secure software, and best security programming practices. Security for web and mobile applications will be covered.
Prerequisites: CS 3503 and CS 3503L
Credits: 3
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CS 4622 - Computer Networks
This course covers computer networking and includes software application-related, protocol-related and security-related issues involved in the Internet. Topics include basic network structures, mechanisms for application-to-application communications, protocol layering, Internet addressing, unicast and multicast routing, connection establishment and termination, data flow and congestion control, and error handling. A specific protocol suite will be examined in detail. More advanced topics that build on the student's understanding of network protocols are also introduced, such as network security, mobile networks and the future Internet.
Prerequisites: CS 3503 and CS 3503L
Credits: 3
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CS 4632 - Modeling and Simulation
This course covers the modeling and simulation of the structure and behavior of real-world systems using object-oriented discrete-event simulation techniques. The course emphasizes the modeling and computer programming perspective of simulation; design and implementation of simulation models. The fundamental concepts of object-oriented simulation are introduced. Model implementation will require programming in an object-oriented simulation language such as OOSimL, or in a general purpose programming language (Java or C++). Students will also be exposed to a commercial integrated simulation software tool: Arena.
Prerequisites: CS 3305 and CS 3305L
Credits: 3
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CS 4712 - User Interface Engineering
A comprehensive study of techniques in design and implementation of user interfaces engineering. Topics include the foundation of human-computer interaction and interface related to software lifecycle, building a graphic user interface engineering, interaction devices and technologies, human-computer dialogue, cognitive models, usability, the design and development process, user interface management systems (UIMS), interface style and techniques, user learning, and diversity in interaction styles. Major research and the building of a working graphic user interface are included.
Prerequisites: CSE 1322 and CSE 1322L
Credits: 3
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CS 4720 - Internet Programming
This course introduces current technologies for modeling, designing, implementing, and developing Web applications. Topics include developing for the server and the client, programming frameworks, server administration and integration with databases. Practice will involve platforms and language such as Linux, Python, PHP, Ruby and JavaScript.
Prerequisites: (CS 3305 and CS 3305L) and (CSE 3153 or CS 3410)
Credits: 3
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CS 4722 - Computer Graphics and Multimedia
The basic principles and practices of interactive computer graphics and multimedia systems are covered in this introductory course. The design and implementation of state-of-the-art computer graphic rendering and visual multimedia systems are the main part of the course. The sub-topics of the course deal with specific input/output hardware devices and their technology, software and hardware standards, programming methods for implementing 3-dimensional graphical applications and interactive multimedia applications, and a study and evaluation of the effectiveness of graphic/multimedia communications. A large component of the class is the building of a large-scale application.
Prerequisites: CS 3305 and CS 3305L
Credits: 3
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CS 4732 - Machine Vision
This course introduces concepts and techniques in machine vision. Students successfully completing this course will be able to apply a variety of image processing techniques for the design and analysis of efficient algorithms for real-world applications, such as optical character recognition, face detection and recognition, motion estimation, human tracking, and gesture recognition.
Prerequisites: CS 3305 and CS 3305L
Credits: 3
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CS 4850 - Computer Science Senior Project
The course provides a capstone experience for CS majors to promote a successful transition to the work place or further academic study. Students will have the opportunity to practice essential project management skills and work with current software tools and technologies. Student teams will develop a project scope, project plan, document functional specifications, develop a design document, implement specified functions, provide weekly progress reports, give project presentations to the class, conduct final project presentation to the instructor and/or project sponsor, and provide a complete final report that includes documentation of all class activities. Each team will designate a team leader who is responsible for coordinating work tasks, team meetings, communications with the instructor and/or project sponsor, and team effort.
Prerequisites: CS 3502 and CS 4305
Credits: 3
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