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Sem # BIO CHEM CS ENG MATH PHYS One 4 papers Two Three Report in E4 1-2 papers in Bio 101 3 lab reports Four 4 lab reports Essays/paper in Chem 52 4 papers Tech report in Phys 53 Lab notebook Exp abstracts 3 reports + paper in 109 Abstracts in CS 110 Proposal & mid-year report OR Project paper in Chem 114 Essay in CS 131 Clinic report IE Paper IE Paper IE Paper IE Paper Proposal Letter of Intro 3 Lab Prog report Proposal + midyear report Proposal + midyear report 1-2 papers in Bio 109 Tech report in Phys 28 Lab notebook & paper in Chem 53 Design doc, Report, & User guide in CS 121 1-2 papers in Bio 108 Five H/SS Exp abstracts Tech report in Phys 54 Term paper in Phys 52 Variable Amount Of Writing 3 lab reports Six 1-2 papers in Bio 113 Tech report in Phys 134 Seminar paper Seven IE Paper IE Paper Seminar Researc h
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Paper Writing Support (Finding Related Work) • • • • • • Help the research paper writing When I am writing a paper, one tedious thing is to compose the related work. Usually, I only have a few competitive or referential papers. But the related work needs a more thorough survey, so as to avoid some unnecessary arguments from the reviewers. It would be good to have a system that I can give it some articles or some paragraphs from the ongoing paper and it can return some typical related works together with a rough organization of them according to research topics. For example, given this note, the system may return some papers about searching in local cached pages, some about email categorization, and some about paper retrieval and summarization. To retrieve related papers, it may need the techniques of content-based information retrieval together with link-based approach on the collection obtained by expanding the citations in the given articles. To give each paper a short summary, we may apply some sort of summarization technique on each paper, or just extract th! ose sentences mentioning the paper in other papers that refer the target paper. To organize the result pagers can be achieved by classification using some welldefined research topic hierachy or by clustering if no such topic information is available in advanced. User: Research paper writers Data: Research papers Function: Given some papers, return some typical related works together with some summarization of each paper as the reference to compose the article and some topical information about each paper that help us to organize those related papers.
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Topic-Specific Paper Rank • • • • • Users always prefer to good papers. Such good papers can be divided into two types: Good survey papers, which include all the good topics of one area, and good technical papers, which set a new direction or address the specific problems thoroughly. However, a paper is good or not is area-dependent. For example, the user would like to get a good paper of Information Retrieval. Another user would like a good paper of Data Mining. The question here is how to rank the paper according to their areas. Such an application may tell people the necessity of writing a new survey paper if he can’t find a good survey paper right now. Users: researchers, scientists, graduate students. Data: literature materials Functions: Paper search and topic-specific rank Challenges: How to identify a paper as a good survey paper, how to identify a paper as a good technical paper and how to classify a paper to a specific domain? How to use the author information in the paper rank?
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CAINE 2013 Call for Papers 26th International Conference on Computer Applications in Industry and Engineering September 25{27, 2013, Omni Hotel, Los Angles, Califorria, USA Sponsored by the International Society for Computers and Their Applications (ISCA) Provides an international forum for presentation and discussion of research on computers and their applications. The conference also includes a Best Paper Award. CAINE{2013 will feature contributed papers as well as workshops and special sessions. Papers will be accepted into oral presentation sessions. The topics will include, but are not limited to, the following areas: Agent-Based Systems Image/Signal Processing Autonomous Systems Information Assurance Big Data Analytics Information Systems/Databases Bioinformatics, Biomedical Systems/Engineering Internet and Web-Based Systems Computer-Aided Design/Manufacturing Knowledge-based Systems Computer Architecture/VLSI Mobile Computing Computer Graphics and Animation Multimedia Applications Computer Modeling/Simulation Neural Networks Computer Security Pattern Recognition/Computer Vision Computers in Education Rough Set and Fuzzy Logic Computers in Healthcare Robotics Computer Networks Fuzzy Logic Control Systems Sensor Networks Data Communication Scientic Computing Data Mining Software Engineering/CASE Distributed Systems Visualization Embedded Systems Wireless Networks and Communication Important Dates Workshop/special session proposal . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .May 2.5,.2.01.3 Full Paper Submission . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .June 5,.2.0.1.3. Notication of Acceptance . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .July.5 , 2013. Pre-registration & Camera-Ready Paper Due . . . . . . . . . . . . . . . . . . . . . .August 5, 2013. Event Dates . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .September 25-27, 2013 The 22nd SEDE Conference is interested in gathering researchers and professionals in the domains of Software Engineering and Data Engineering to present and discuss high-quality research results and outcomes in their fields. SEDE 2013 aims at facilitating cross-fertilization of ideas in Software and Data Engineering, The conference also encourages research and discussions on topics including, but not limited to: . Requirements Engineering for Data Intensive Software Systems. Software Verification and Model of Checking. Model-Based Methodologies. Software Quality and Software Metrics. Architecture and Design of Data Intensive Software Systems. Software Testing. Service- and Aspect-Oriented Techniques. Adaptive Software Systems . Information System Development. Software and Data Visualization. Development Tools for Data Intensive. Software Systems. Software Processes. Software Project Mgnt . Applications and Case Studies. Engineering Distributed, Parallel, and Peer-to-Peer Databases. Cloud infrastructure, Mobile, Distributed, and Peer-to-Peer Data Management . Semi-Structured Data and XML Databases. Data Integration, Interoperability, and Metadata. Data Mining: Traditional, Large-Scale, and Parallel. Ubiquitous Data Management and Mobile Databases. Data Privacy and Security. Scientific and Biological Databases and Bioinformatics. Social networks, web, and personal information management. Data Grids, Data Warehousing, OLAP. Temporal, Spatial, Sensor, and Multimedia Databases. Taxonomy and Categorization. Pattern Recognition, Clustering, and Classification. Knowledge Management and Ontologies. Query Processing and Optimization. Database Applications and Experiences. Web Data Mgnt and Deep Web Submission procedures May 23, 2013 Paper Submission Deadline June 30, 2013 Notification of Acceptance July 20, 2013 Registration and Camera-Ready Manuscript Conference Website: http://theory.utdallas.edu/SEDE2013/ September 25-27, 2013 Omni Hotel, Los Angeles, California, USA The International Conference on Advanced Computing and Communications (ACC-2013) provides an international forum for presentation and discussion of research on a variety of aspects of advanced computing and its applications, and communication and networking systems. ACC-2013 will feature contributed as well as invited papers in all aspects of advanced computing and communications and will include a BEST PAPER AWARD given to a paper presented at the conference. Important Dates May 5, 2013 - Special Sessions Proposal Papers on Current FAUST Cluster (functional gap based) and on revisions to FAUST Classification. June 5, 2013 - Full Paper Submission Who will lead what? July 5, 2013 - Author Notification Aug. 5, 2013 - Advance Registration & Camera Ready Paper Due
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Reflection Papers (throughout notebook) • • • • • Reflection Paper 300-700 Words Brief Summary Analysis and Evaluation (after you finish the placement for classroom management) Possibilities for Application (What can you use, what will you do differently, etc.?)
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Diagram the policies, procedures, rules, laws, authorities, traditions, customs, practices, preferences, attitudes, etc. that influence the Use bubbles to specify all Arrows work. Annotate the Cultural Model Technology/Industry Mo ve q uic kly to ke ep entities (not necessarily people) that influence the work. relevant attitudes of each entity. Your success depends on us, so we do things our way up w ith Move quickly on major projects te c Innovations Business Unit Prioritize the projects – we don’t have time/money/staff to do everything hn olo support collaborative effort in Innovations – keep using that method giWe es We want to make the same products for the same market We like provisional applications – they’re cheaper, less work, and buy us another year The inventions you make should work together and help us monopolize the market Competitors RadTech Legal Inventor i od go s e k h t t boo e pu ly not n o ab We he l t in as de rk wo s thi on indicate the influences that the entities have on each other, including policies, preferences, authority, etc. The amount that bubbles overlap is proportional to the extent to which an influence affects an entity. l wil • I want to find all possible solutions to any problem I’m presented with. You • We can’t risk data • The first idea that works is not necessarily the best one. being stored on • My RadTech Lab Notebook shouldn’t be filled with scribbles or half-baked ideas. individual hard drives • If I’m not confident in my idea, I don’t want to present it to someone to witness. • We don’t blame • I want to develop and document my idea as much as possible before getting a individual inventors witness in case the witness had the same idea before me Customer for problems with • I’m embarrassed about not getting a witness for everything in my RadTech Lab documentation s Notebook How do you use • I could be anywhere when an idea hits me our products? • Documenting is just to cover your tracks, the real magic happens in the invention process • Innovation is a collaborative process • I wish the monetary award for patenting inventions were bigger – a plaque and You should double-check the facts in the patent application that I write $1000 is not enough • If my idea allows us to do something nobody else is able to do, it should go in the I understand the customer’s needs Inventorship must be clear RadTach Lab Notebook It’s up to you to solve problems Document everything in your RadTech Lab Notebook • Lab Notebooks are great for documentation, but it takes time Give us something extra to sell Think outside the box – the patent should be as broad as possible • I tend not to be very good at keeping lab notes, but most people here don’t either • The RadTech Lab Notebook is sacrosanct, almost like folklore Is this a good idea? I’ll I understand the law and need all technical details of your invention • Creating documents is easier on the computer wait to document it until • Sharing ideas, viewing large documents, and searching for concepts by diagram is you tell me We need you to create the patent application – we don’t know how easier on paper • I want my data to be safe and time-stamped Here is allI have for this invention – you know what to do with it • If Legal writes something, I have to double-check the facts, so I’d rather write it I don’t know the status of my Invention Disclosure myself • I share information freely with mu colleagues; everyone in Innovations knows what the others are working on • I like having everything on my hard drive for instant local access You might steal my idea • After I submit an invention disclosure, the rest of the patent application is a “black box” M to ake fit s ou om r n et ee hin ds g Marketing CS 321 Lesson Five Data Analysis Page 5 External Collaborator
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DEN 219/229 Reflection Journal Rubric GRADING Criteria Reflective Student Aware Student Reflective Novice BelowExpectations Clarity Language is clear and expressive. The reader can create a mental picture of the situation being described. Abstract concepts are explained accurately. Explanation makes sense to an uninformed reader. The learning experience being reflected upon is relevant and meaningful to student and course learning goals. Minor, infrequent lapses in clarity and accuracy. There are frequent lapses in clarity and accuracy. Language is unclear and confusing throughout. Concepts are either not discussed or are presented inaccurately. The learning experience being reflected upon is relevant and meaningful to student and course learning goals. Student makes attempts to demonstrate relevance, but the relevance is unclear to the reader. Most of the reflection is irrelevant to student and/ or course learning goals. The reflection demonstrates connections between the experience and material from other courses, but lacks relevance and depth. There is little to no attempt to demonstrate connections between the learning experience and previous other personal and/ or learning experiences. Student makes attempts at applying the learning experience to understanding of self, others, and/ or course concepts but fails to demonstrate depth of analysis. There is some attempt at self-criticism, but the selfreflection fails to demonstrate a new awareness of personal biases, etc. No attempt to demonstrate connections to previous learning or experience. Student’s language is clear and expressive Relevance The learning experience is relevant and meaningful to student. Interconnections The reflection demonstrates connections between the experience and material from The reflection demonstrates other courses; past connections between the experience and material from experience; and/ or personal goals. other courses. Analysis The reflection moves beyond simple description of the experience Self-criticism Ability of the student to question their own biases, stereotypes, preconceptions, and/ or assumptions. The reflection moves beyond simple description of the experience to an analysis of how the experience contributed to student understanding of self, others, and/ or course concepts. The reflection demonstrates student attempts to analyze the experience but analysis lacks depth. The reflection demonstrates ability of the student to question their own biases, stereotypes, preconceptions, and/ or assumptions and define new modes of thinking as a result. The reflection demonstrates ability of the student to question their own biases, stereotypes, preconceptions. Adapted from University of Iowa, Office of Service Learning Reflection does not move beyond description of the learning experience(s). No attempt at selfcriticism.
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