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Main menu for Browse IS/STAG
Course info
KEP / VP
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Course description
Department/Unit / Abbreviation
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KEP
/
VP
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Academic Year
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2023/2024
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Academic Year
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2023/2024
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Title
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Visual programming for data measurement
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Form of course completion
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Pre-Exam Credit
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Form of course completion
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Pre-Exam Credit
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Long Title
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Visual programming for data measurement and processing
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Accredited / Credits
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Yes,
4
Cred.
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Type of completion
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Combined
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Type of completion
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Combined
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Time requirements
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Lecture
2
[Hours/Week]
Tutorial
2
[Hours/Week]
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Course credit prior to examination
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No
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Course credit prior to examination
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No
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Automatic acceptance of credit before examination
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No
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Included in study average
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NO
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Language of instruction
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Czech, English
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Occ/max
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Automatic acceptance of credit before examination
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No
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Summer semester
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0 / -
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0 / -
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0 / -
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Included in study average
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NO
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Winter semester
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30 / -
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0 / -
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4 / -
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Repeated registration
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NO
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Repeated registration
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NO
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Timetable
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Yes
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Semester taught
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Winter semester
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Semester taught
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Winter semester
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Minimum (B + C) students
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10
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Optional course |
Yes
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Optional course
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Yes
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Language of instruction
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Czech, English
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Internship duration
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0
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No. of hours of on-premise lessons |
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Evaluation scale |
S|N |
Periodicity |
každý rok
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Periodicita upřesnění |
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Fundamental theoretical course |
No
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Fundamental course |
No
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Fundamental theoretical course |
No
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Evaluation scale |
S|N |
Substituted course
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None
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Preclusive courses
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N/A
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Prerequisite courses
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N/A
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Informally recommended courses
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N/A
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Courses depending on this Course
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N/A
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Histogram of students' grades over the years:
Graphic PNG
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XLS
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Course objectives:
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Master the basics of visual programming and use the knowledge in measuring, collecting and processing data in collaboration with DAQ resources. Create applications with analog and discrete signal generators for switching actuators and processing analog signals from sensors of physical quantities. Use timer structures, program management modules, decision structures, block cycles, and cluster data transfer. Learn signal timing and process error channels.
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Requirements on student
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Credits
- knowledge of all materials from lectures and seminars
- writing control tests and obtaining the required number of points
- elaboration of assigned homework
- active participation in exercises
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Content
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1. A basic philosophy of Labview, G language, function of windows and division of work space - concept of two windows. Design of algorithm and model.
2. Constants, variables, links and constraints, data flow issues, definition, and usage of error list and timing.
3. Data flow control, cycle structures, conditions, indicators, signaling, variable types - real, boolean, string and cluster.
4. Cycles, their types, applications and typical deployment. Tunneling, use of internal indexing and initialization, data flow control.
5. Special structures - data feedback in cycle objects, SHIFT register and its use in examples (initialization due to the work).
6. CASE structures and its definitions. FLAT and STACKED sequencer, mutual conversion, specifics and usage.
7. Field Type - 1D, 2D, Usage, Initialization, Foundation and Calculations. Comparison with Matlab. Matrix operations, calculations and applications.
8. Automatic indexing, polymorphism, clusters - creation, function, transfer of virtual and real data, error cluster.
9. Chart types - chart, graph - differences, initialization, typical usage. Waveform chart structures and waveform graph - XY graph and their use.
10. Error handling and cluster error issues. Diagram and data flow control (DATA FLOW) and error signal flow.
11. Various DAQ interfaces and their typical deployment, PC connection and initialization, DAQ addressing, timing.
12. Discrete IN / OUT signals, LED addressing, switch, sampling and filtration.
13. Analog signals of IN / OUT type, examples of signal processing from thermistor, phototransistor, microphone.
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Activities
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Fields of study
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Studentům jsou k dispozici prezentace v el. podobě a videonávody. Tyto obsahují všechny základní informace a doplňující ukázky a příklady. Veškeré poklady jsou přehledně vizualizovány v Google Classroom kurzu předmětu.
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Guarantors and lecturers
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Guarantors:
Doc. Ing. Václav Kotlan, Ph.D. ,
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Lecturer:
Doc. Ing. Václav Kotlan, Ph.D. (100%),
Ing. Karel Slobodník, Ph.D. (100%),
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Tutorial lecturer:
Doc. Ing. Václav Kotlan, Ph.D. (100%),
Ing. Karel Slobodník, Ph.D. (100%),
Ing. Lenka Stachová, Ph.D. (100%),
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Literature
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Recommended:
Hanselman, Duane; Littlefield, Bruce. Mastering MATLAB 6 : a comprehensive tutorial and reference. Upper Saddle River : Prentice Hall, 2001. ISBN 0-13-019468-9.
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Recommended:
Orvis, William J. Microsoft Excel pro vědce a inženýry. 1. vyd. Praha : Computer Press, 1996. ISBN 80-85896-49-4.
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Recommended:
Vlach, Jaroslav; Havlíček, Josef; Vlach, Martin. Začínáme s LabVIEW / Jaroslav Vlach, Josef Havlíček, Martin Vlach. 1. vyd. Praha : BEN - technická literatura, 2008. ISBN 978-80-7300-245-9.
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On-line library catalogues
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Time requirements
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All forms of study
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Activities
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Time requirements for activity [h]
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Contact hours
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52
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Individual project (40)
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32
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Preparation for formative assessments (2-20)
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8
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Preparation for comprehensive test (10-40)
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10
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Total
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102
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Prerequisites
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Knowledge - students are expected to possess the following knowledge before the course commences to finish it successfully: |
to know the basic principles of programming - loops, conditions |
Skills - students are expected to possess the following skills before the course commences to finish it successfully: |
to master the basics from the theory of electrical measurement and the circuit connection |
Competences - students are expected to possess the following competences before the course commences to finish it successfully: |
N/A |
N/A |
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Learning outcomes
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Knowledge - knowledge resulting from the course: |
be familiar with the principles and design of visual programming |
know data processing techniques and their evaluation |
Skills - skills resulting from the course: |
obtain and process measured data |
design algorithm and program for measurement |
Competences - competences resulting from the course: |
N/A |
N/A |
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Assessment methods
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Knowledge - knowledge achieved by taking this course are verified by the following means: |
Test |
Seminar work |
Skills - skills achieved by taking this course are verified by the following means: |
Skills demonstration during practicum |
Test |
Seminar work |
Competences - competence achieved by taking this course are verified by the following means: |
Skills demonstration during practicum |
Seminar work |
Test |
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Teaching methods
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Knowledge - the following training methods are used to achieve the required knowledge: |
Lecture |
Laboratory work |
Task-based study method |
Individual study |
Skills - the following training methods are used to achieve the required skills: |
Laboratory work |
One-to-One tutorial |
Competences - the following training methods are used to achieve the required competences: |
Lecture |
Practicum |
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