Course Introduction

Advanced Information Modeling and Database System แบบจำลองสารสนเทศและระบบฐานข้อมูลขั้นสูง Monday – 16.00?

แบบจำลองสารสนเทศ แนวคิดของระบบฐานข้อมูล สถาปัตยกรรมของระบบฐานข้อมูล การออกแบบฐานข้อมูล ผังเชื่อมโยงเอ็นทิตี้ ภาษายูนิฟายโมเดลลิ่งและกรณีศึกษา การประมวลผลข้อคำถาม การจัดการรายการเปลี่ยนแปลง ความมั่นคงและความบูรณภาพของฐานข้อมูล การบริหาร ฐานข้อมูลขั้นสูง การค้นคว้าวิจัยเกี่ยวกับแบบจำลองข้อมูล เทคโนโลยีฐานข้อมูล Information Modeling, concepts of database systems, database system architecture, database design, entity relationship diagram, unified modeling language and case studies, query processing, transaction management, database integrity and security, advanced data management, research on information modeling, database technology.

Study on any state-of-the-art technology in information technology

Students should: Understand the main concepts of state-of-the-art technologies Be able to apply the knowledge to effectively solve database or any problems. Be able to carry out independent research in the areas of database systems or any other area. This course is designed to train and test your research skill. Self-study is mainly required.

1 13 Aug Lecture 1: Course Introduction - Self-review on database concept - Introduction to MapReduce and ArrayDB 2 20 Aug Lecture 2: EndNote software and academic writing skill 3 27 Aug Lecture 3: Journal manuscript writing 4 3 Sept Independent research presentation 5 10 Sept Independent research presentation 6 17 Sept Independent research presentation 7 24 Sept Independent research presentation 8 1 Oct Confirming topic for main research report *Lecturer is available for consult during independent research

9 8 Oct Independent research Oct Independent research Oct Independent research Oct Independent research 13 5 Nov Independent research Nov Independent research (Lecturer is not available) Nov Research report submission Nov Final Examination (preferred, but negotiable) *Lecturer is available for consult during independent research except for the marked period.

Plagiarism in any assignment -100% In-class Research 20% 4 x 5% Manuscript Review Practice10% Research Report40% Content25% Professional writing10% References5% Final Examination30%

One (good) paper per week for 4 weeks A summary of no more than 2 pages is to be submitted each week together with the original paper You may read a paper and write a summary before class Each student is given 5 minutes to present the paper of a normal length

Approximately 20 pages (including images and references) Font TH SarabunPSK or Browallia New, size 16 Single-line spacing Or approximately 5,000 words in English (use MS Word count) Professionally written Full paper is to be submitted together with EndNote library file on week 16

At least 20 reliable sources, properly cited and listed at the end of the paper Wikipedia is a good place to start but not a good reference Websites are usually not acceptable references except major or official organization websites Books are secondary reference and usually not good references

Any state-of-the-art technology Some keywords NoSQL / NewSQL Spatial database (such as database for GIS) Temporal database Spatiotemporal database MapReduce / Spark Deep Learning

Some keywords Blockchain Mobile cloud computing Crowdsourcing Network hypervisor Urgent computing Social network analysis Internet-of-Things User experience

Be warned, 100% of total score penalty, immediately resulting in the grade “F” What is plagiarism? copy-paste, even from your friends 4 exact same words without quote and citation paraphrasing without citation Google translate General knowledge does not require citation Having more references cited is not bad If you are not sure, ask the lecturer.

Sucha Smanchat, PhD PhD in Information Technology, 2012 Monash University, Australia Master of Science in Information Technology (International Program), 2006 King Mongkut’s University of Technology North Bangkok Master of Information Technology (Minor Thesis), 2005 Monash University, Australia Bachelor of Engineering (Computer Engineering), 2002 King Mongkut’s Institute of Technology Ladkrabang

PhD Topic: Scheduling Parameter Sweep Workflow in the Grid Read posters outside my room Cloud computing Cloud workflow Workflow scheduling Data mining-as-a-service MapReduce / Spark Block chain

Counseling Hour Sucha: 3A05 (third floor) by appointment

Up to your research topic

Cloud Software Engineering Laboratory (CSEL) Members are those working on researches in the Cloud computing and students under my supervision Current research areas: Grid/Cloud workflow scheduling Video encoding on Cloud Data mining on the Cloud VM allocation policy in private cloud using CloudSim Air Drone programming (collective behavior for AR2) MapReduce

“I am still learning”