Computing and Information Sciences Dr' Virgil Wallentine http:www'cis'ksu'edu

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Computing and Information SciencesDr. Virgil
Wallentinehttp//www.cis.ksu.edu

• What is computing?
• Why is computing important?
• How do I get a degree in CS, SE, or IS?
• What will I do as a computing professional?
• How can I get involved with CIS research projects?

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Definition of Computing

• Systematic study of algorithmic processes that
  describe and transform information theory,
  analysis, design, efficiency, implementation, and
  application
• What can be (efficiently) automated?

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Areas in Computer Science

• Algorithms and data structures
• Programming languages
• Computer Architecture
• Operating Systems
• Networking
• cybersecurity

• Software engineering
• Data and knowledge base systems
• Artificial intelligence and robotics
• Human-computer interface

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C.S. is more than programming

• Programming is the essential mechanism that
  permits computing professionals to make things
  come alive on the screen, in the robot, in the
  car, in the plane, etc.
• But it is a small part of the study of computing

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Computing Profession

• Computing is a challenging curriculum but it is
• a rewarding profession
• computing affects all of society
• jobs are creative, not repetitive
• software is a team sport
• lots of exciting jobs
• and the pay is very good

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Contribution of Computing to Society

• Medicine telemedicine, medical informatics,
  bioinformatics, diagnosis and treatment,
  complementary and supplementary devices
  (pacemaker, diabetes sensing and control)
• Entertainment movie animation, video games,
  theatre
• Homeland Defense smart weapons, search and
  rescue, cybersecurity, intelligence, safe
  soldiers
• Embedded Real-time control robotics, precision
  agriculture, car brakes, airliner control,
  pacemakers, prosthetics, infusion pumps,
  networking, manufacturing, smart buildings

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Computing and Society

• Employment telecommuting, hazardous jobs
• Sensor Systems spread of disease, tracking
  systems
• Graphic Arts marketing, websites, mass
  communication
• Digital Media sounds, movement, human interface
• Security fighting terrorism, identity theft

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Ubiquitous Computing and Society

• Design industrial, apparel, architectural,
  virtual reality
• Environment air, soil, water modeling and
  monitoring
• Government administration, citizen services, law
  enforcement, taxes
• Education learning aids, access to information,
  virtual environments
• Ecommerce efficient operation, secure
  transactions, access to information, banking,
  retail, business processes, inter-corporate
  operations

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Video Game Creation Teamwork

• Art
• Theatre and story-telling
• Creative Writing
• Architecture
• Physics and Math of Games
• Music and Sound
• Programming and Games frameworks
• Programming Languages
• Software Engineering
• Artificial Intelligence and machine learning
• 3D graphics
• Human/computer interface
• Real-time embedded systems
• Database systems

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Games Programming Tasks

• Simulation Programmer
• Script Programmer
• AI Programmer
• Graphics Programmer
• User Interface Programmer
• Tool Programmer
• Sound Programmer
• Database Programmer
• Web Programmer
• BuildMeister
• BugMeister
• Quality Assurance
• Multiplayer parallel and distributed programmer

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Virtual Worlds

• Virtual Reality
• Retraining stroke victims
• Video Games
• Pain reduction
• Movie Animations
• Training
• Car and airplane simulators, war gaming, etc.
• Medical training (surgery, diagnosis, caregiver)

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What does a computing professional do?

• Types of jobs
• Build software systems
• Software engineering processes
• Managing systems development
• Managing data and/or computing systems
• Managing people and projects
• Integrating software
• Entrepreneur
• Problem-solving

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Research in Real-time Embedded Systems

• Pervasive computing
• Planes ,trains, cars, tractors, ships,
  pacemakers, etc.
• Response time critical
• Sensor Systems
• New RESL Lab
• CAN protocols, development boards, Java cards,
  etc.
• Design methodology
• Patterns for verifiable real-time parallel code
• Scheduling
• Collaborators and Funding
• NSF, DARPA, Rockwell-Collins, IFR, John Deere,
  Wind River, Trimble, Navy, U of Ill.

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Real-Time Embedded Systems Coursework

• Certification sequence (with EECE).
• RT OS, networking, I/O
• Capstone design e.g., optical weed controller

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High Assurance Software

• NASA robots, Avionics software
• Collaborators and Funding
• NSF, ARO, DARPA, Honeywell, Rockwell-Collins,
  Microsoft, IBM, NASA, CMU, Stanford, Nebraska,
  FDA, etc.

• Massive testing is fruitless
• Need tools to explore all relevant states
• Program Analysis Tools
• Parallel Java code slicing
• Underlying model-checking
• Explore all states

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Mobile Robotics

• Software engineering and AI approach
• KSU won AAAI contest in 1997 and 2006
• Navigation and learning
• sonar, infrared, touch sensors
• Object recognition (video)
• Object retrieval (slides and grippers)
• Robotics Roadshow
• Search and rescue
• Collaborators and Funding
• NSF, Rockwell-Collins, Cargill, and Nomad

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Database Data Mining

• Database Research
• Internet-compatible technologies
• Data Mining
• Mathematical tools for finding patterns
• Visualization
• Artificial intelligence and machine learning
• Bioinformatics
• Collaborators and Funding
• Wal-Mart, NCR, Raytheon, Navy, NCSA

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Software Engineering

• Software Development Technologies
• Methods, processes, metrics, costing
• Tool building
• Testing
• Integration
• Verification
• Project development management
• Collaborators and Funding
• Rockwell-Collins, Lucent, NSF

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Parallel and Distributed Systems

• Control of parallel, interacting, asynchronous
  systems
• Network protocols
• Operating systems
• Parallel programming systems
• Web technologies
• Collaborators and Funding
• NSF, Cargill, Rockwell-Collins

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Major Cyber-security Research AreasinCIS_at_K-State

• Enterprise-network security
• Security analysis
• Intrusion alerts correlation
• Web application security
• Software security

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Enterprise-network Security
Internet
Firewall 1
buffer overrun
Demilitarized zone (DMZ)
webServer
Firewall 2
NFS shell
sharedBinary
Trojan horse
workStation
Corporation
webPages
fileServer
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Misconfiguration Problem
Information about data assets
Linux security behavior Windows security
behavior Common attack techniques
Information about users
potential attack paths
Security expert
System admin
Network configuration
Host configuration
CERT advisory
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Intrusion Alerts Correlation
Correlation Engine
Attack Graph
System Logs
Network IDS alerts
Host-based IDS alerts
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Web Security
webServer
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Software Security

• Protecting consumers who have to run untrusted
  codes.
• Have you ever wondered whether it is safe to run
  a piece of code you downloaded from the Web?
• Wouldnt it be nice if it can be formally proved
  that the code is safe to run?
• Is this possible?

With years of research in proof-carrying code and
certified compilation, we are not ready to
conduct research on how to prove various program
properties (including safety) down to the
machine-code level!
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Home ComputersEvaluate AIDS Drugs

• Community
• 1000s of home computer users
• Philanthropic computing vendor (Entropia)
• Research group (Scripps)
• Common goal advance AIDS research

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Virtual Data Grid Laboratory
U.S. PIs Avery, Foster, Gardner, Newman, Szalay
www.ivdgl.org
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Andresen Web to World
DHARMA
REAPER
Distributed hydrology simulation
Veterinary telemedicine
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Sensor application design A multidisciplinary
exercise
Sensor networking - energy aware communication
- data analysis - safety critical/high
assurance - secure data flow,.
Materials Research - sensitivity - power -
size - durability,.
Sensor design - reliability - power -
ruggedness - packaging,.
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Goals of the Center
Sensor Development
MaterialsResearch
Sensor Networking
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Current Efforts in Sensor Networks

• Software tool development research
• Development of sensor applications in various
  application areas
• Veterinary Telemedicine
• Precision Agriculture
• Radiation Surveillance
• Environmental Monitoring
• Target Tracking
• Sensor Network Education

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Sensor Software Research Challenges

• Remote programming of sensors deployed in the
  field/remote areas.
• Remote data collection and control
• Design of large scale systems (1000s of sensors)
  
• Issues
• Correctness (for safety critical systems)
• Energy efficiency (sensors are battery operated)

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Cadena design environment
Automated Code Generation

• Cadena analysis tools enable
• Development of high assurance systems
• Automated code generation
• Model-driven design of efficient systems

Deployed Systems
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Applications Radiation Surveillance

• Possible deployment fields
• Urban areas
• Nuclear facilities
• Dockyards

Issues and requirements - Large scale -
Real-time response - Reliable - Secure
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Applications Tracking time critical targets
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Applications Precision Agriculture
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Summary

• Research in developing tools for programming and
  configuring sensor systems.
• Development of Sensor Infrastructure to support
  applications in diverse application areas.
• Develop relationships with industry and National
  Laboratories

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Overview

• Methodologies
• Multiagent Systems Engineering (MaSE) (1999)
  methodology for developing multiagent systems
• Organization-based Multiagent Systems Engineering
  (O-MaSE) (2005, 2007) extended MaSE to focus on
  developing artificial organizations using
• agentTool development environment to support
  O-MaSE

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Agents and Robotics

• Models for adaptive, cooperative teams
• Organizational Model for Adaptive Computational
  Systems (OMACS) treat teams of agents (robots)
  like human organizations
• Goal Model for Adaptive Computational Systems
  (GMoDS) provides the ability to model team
  goals and the ability to create and remove goals
  based on events that occur during operation

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O-MaSE Process Framework

• O-MaSE is actually a family of processes that are
  engineered for a specific use based on common
  concepts, techniques, and tasks

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ExampleImprovised Explosive Device Detection

• Route Reconnaissance and Security Sweep
• Working with US Marine Corp
• Robots search designated roads for changes that
  may be suspicious
• Team of robots work with human operators

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Example Improvised Explosive Detection

• Details
• Given a map, the team automatically divides the
  search area among themselves
• Robots are heterogeneous and have the capability
  to move, detect suspicious objects, classify
  suspicious object (IED, inert), and communicate
  with operator
• Team must adapt to
• Changes in the environment
• New robots entering the team
• Loss of existing robots or robot capabilities

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Improvised Explosive Device Displays
IED disguised as curb
IED disguised as debris
Remote detonator
Motion detonator in box
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Real World Robots

• Currently working to implement simulation on
  real, all terrain robots

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What is Bioinformatics?

• Wikipedia
• Bioinformatics computational biology involve
  the use of techniques from applied mathematics,
  informatics, statistics, computer science,
  artificial intelligence, chemistry, and
  biochemistry to solve biological problems usually
  on the molecular level.

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Genomes

• Each cell of an individual contains identical
  DNA
• Genome totality of DNA in cell of an organism
• E.g. Humans about 3 billion base pairs
• E.g. Bacteria few million base pairs
• In eukaryotes, genome split into chromosomes,
  which are packed pieces of DNA

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DNA as Code

• Genomic DNA contains
• Fragments called genes that code for proteins
• Signals recognized by regulatory molecules
• control information
• Challenges
• Identify genes in a genome
• Identify signals in a genome

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Project Find genes in a genome based on EST data
analysis
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Project Gene Structure Prediction for Insects
(e.g., red flour beetle)

• Predict exons, introns and boundaries between
  them
• Find genes that undergo alternative splicing
  (using EST to genome alignments and machine
  learning)
• Find new genes, correct old genes
• Find pseudogenes and non-coding RNA genes

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Project Prediction of Signals in Insect Genomes
(e.g., red flour beetle)

• Promoters and Transcription Start Sites (TSS)
• Transcription Termination (TT)
• Transcription Factor Binding Sites (TFBS)

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Genomic-scale data Expression

• Gene expression data using microarray technology
  measure mRNA expression level for 10,000s of
  genes in a sample
• Functional genomics discover groups of genes
  that are up/down- regulated under various
  conditions, understand mechanisms of
  transcriptional regulation

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Project Gene Regulatory Networks (GRNs)

• GRNs typically model interactions between genes

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Project Structural Interactions

• Prediction of protein-protein interactions
• Prediction of protein-protein interaction sites

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Summary

• Talk to your mentor and advisor
• Impress your instructors
• Get involved
• Programming contest, open house, ACM, etc.
• Career fair
• Be aware of research programs in CIS
• Study hard
• Take responsibility
• Have fun