A Manuscript entitled "Computational Aptitude of Handheld Calculator" can be found at:
This is useful for solving problems in:
Thermodynamics, Mass and Heat Transfer, Engineering Analysis, Accounting and Economics and so on. It has been found useful in Undergraduate and Post graduate level courses. Kindly share with your younger ones.
This document discusses computer simulation and its use in education. It defines computer simulation as a computer model that attempts to simulate a system. Computer simulations can model natural and human systems. They provide hands-on learning and allow students to experiment with inaccessible phenomena. Simulations help develop 21st century skills and support different learning styles. The document outlines the history and development of computer simulations and discusses strategies for adopting their use in education, including teacher training, free software, and competitions. It also examines factors influencing adoption such as complexity, observability, and compatibility.
This document provides an overview of machine learning presented by Preetam from R.E.C. Sonbhadra. It defines machine learning as a field that allows computers to learn without being explicitly programmed and discusses traditional programming versus machine learning approaches. The document outlines key machine learning concepts like generalization, popular algorithms like decision trees and logistic regression, and applications such as image and speech recognition. It concludes that machine learning will allow machines to perform increasingly complex tasks autonomously.
The document is a laboratory manual for the Design and Analysis of Algorithms course at Jawaharlal Nehru National College of Engineering. It includes the vision, mission, program educational objectives, program specific outcomes, and program outcomes of the Computer Science and Engineering department. It also outlines the syllabus and 12 experiments to be performed in the laboratory covering topics like sorting algorithms, graph algorithms, dynamic programming, and more. Students will design, develop and implement algorithms in Java to solve various problems and analyze their time complexities.
Incorporating Prior Domain Knowledge Into Inductive Machine ...butest
This document discusses incorporating prior domain knowledge into inductive machine learning. It introduces concepts of inductive machine learning such as consistency, generalization, and convergence. Incorporating prior domain knowledge can help improve performance in these three key areas. The document proposes analyzing how domain knowledge can be incorporated while balancing risks. It also presents a new hierarchical modeling method called VQSVM and tests it on imbalanced datasets.
IRJET- Syllabus and Timetable Generation SystemIRJET Journal
The document describes a proposed system called the Syllabus and Timetable Generation System that aims to automatically generate timetables and syllabi for educational institutions. It uses an algorithm that takes inputs like number of classes, subjects, days in a week, and lectures per day to randomly generate timetables for multiple classes without clashes. The algorithm employs recursion to prevent clashes across class timetables. It also includes a static faculty assignment method. The proposed system was able to automatically generate timetables and syllabi for 4 classes with 10 subjects, demonstrating the effectiveness of the algorithm in solving the complex task of timetable scheduling.
This document provides an introduction to machine learning techniques presented by Dr. Radhey Shyam. It begins with definitions of machine learning and discusses when machine learning is applicable. The document then covers types of learning problems, designing learning systems, the history of machine learning, function representation techniques, search algorithms, and evaluation parameters. It also introduces several machine learning approaches and discusses common issues in machine learning.
Draft Two:
This report looks at one approach to the standard scheduling problem by constructing a model for use by high schools and small colleges/universities. This iteration of the model builds up an integer programming optimization model, aiming to maximize credit hours following constraints: 1) required class hours per course-week; 2) instructor preference for teaching-free days; 3) restricting group-room assignments to Integer: (0,1); 4) restricting number of instructors per group-room to Integer:(0,1); and other constraints. The model searches through two thousand variable fields: 1) ten instructors; with potential to occupy: 2) eight group-room assignments; over 3) five potential course time slots per day; over five days each week – vis. 10 X 8 X 5 X 5. But the model has capability beyond the two thousand variables. For instance, if the system limits a department teaching hours to two time slots per day (or different days), the system could accommodate several departments to minimize scheduling conflicts while maximizing satisfaction for instructors and students.
This project uses the robust solver mechanism in OpenSolver, an open source project developed by Andrew Mason in the Department of Engineering Science at the University of Auckland. The standard solver issued with Microsoft Excel is limited to only 200 variable fields. The OpenSolver mechanism does not impose artificial limits to the number of potential variable fields.
This document discusses computer simulation and its use in education. It defines computer simulation as a computer model that attempts to simulate a system. Computer simulations can model natural and human systems. They provide hands-on learning and allow students to experiment with inaccessible phenomena. Simulations help develop 21st century skills and support different learning styles. The document outlines the history and development of computer simulations and discusses strategies for adopting their use in education, including teacher training, free software, and competitions. It also examines factors influencing adoption such as complexity, observability, and compatibility.
This document provides an overview of machine learning presented by Preetam from R.E.C. Sonbhadra. It defines machine learning as a field that allows computers to learn without being explicitly programmed and discusses traditional programming versus machine learning approaches. The document outlines key machine learning concepts like generalization, popular algorithms like decision trees and logistic regression, and applications such as image and speech recognition. It concludes that machine learning will allow machines to perform increasingly complex tasks autonomously.
The document is a laboratory manual for the Design and Analysis of Algorithms course at Jawaharlal Nehru National College of Engineering. It includes the vision, mission, program educational objectives, program specific outcomes, and program outcomes of the Computer Science and Engineering department. It also outlines the syllabus and 12 experiments to be performed in the laboratory covering topics like sorting algorithms, graph algorithms, dynamic programming, and more. Students will design, develop and implement algorithms in Java to solve various problems and analyze their time complexities.
Incorporating Prior Domain Knowledge Into Inductive Machine ...butest
This document discusses incorporating prior domain knowledge into inductive machine learning. It introduces concepts of inductive machine learning such as consistency, generalization, and convergence. Incorporating prior domain knowledge can help improve performance in these three key areas. The document proposes analyzing how domain knowledge can be incorporated while balancing risks. It also presents a new hierarchical modeling method called VQSVM and tests it on imbalanced datasets.
IRJET- Syllabus and Timetable Generation SystemIRJET Journal
The document describes a proposed system called the Syllabus and Timetable Generation System that aims to automatically generate timetables and syllabi for educational institutions. It uses an algorithm that takes inputs like number of classes, subjects, days in a week, and lectures per day to randomly generate timetables for multiple classes without clashes. The algorithm employs recursion to prevent clashes across class timetables. It also includes a static faculty assignment method. The proposed system was able to automatically generate timetables and syllabi for 4 classes with 10 subjects, demonstrating the effectiveness of the algorithm in solving the complex task of timetable scheduling.
This document provides an introduction to machine learning techniques presented by Dr. Radhey Shyam. It begins with definitions of machine learning and discusses when machine learning is applicable. The document then covers types of learning problems, designing learning systems, the history of machine learning, function representation techniques, search algorithms, and evaluation parameters. It also introduces several machine learning approaches and discusses common issues in machine learning.
Draft Two:
This report looks at one approach to the standard scheduling problem by constructing a model for use by high schools and small colleges/universities. This iteration of the model builds up an integer programming optimization model, aiming to maximize credit hours following constraints: 1) required class hours per course-week; 2) instructor preference for teaching-free days; 3) restricting group-room assignments to Integer: (0,1); 4) restricting number of instructors per group-room to Integer:(0,1); and other constraints. The model searches through two thousand variable fields: 1) ten instructors; with potential to occupy: 2) eight group-room assignments; over 3) five potential course time slots per day; over five days each week – vis. 10 X 8 X 5 X 5. But the model has capability beyond the two thousand variables. For instance, if the system limits a department teaching hours to two time slots per day (or different days), the system could accommodate several departments to minimize scheduling conflicts while maximizing satisfaction for instructors and students.
This project uses the robust solver mechanism in OpenSolver, an open source project developed by Andrew Mason in the Department of Engineering Science at the University of Auckland. The standard solver issued with Microsoft Excel is limited to only 200 variable fields. The OpenSolver mechanism does not impose artificial limits to the number of potential variable fields.
The document describes the development of a mobile scientific calculator application. It will allow students to solve mathematical problems and view the step-by-step solutions on their mobile phones. The application will be created using Java programming on the NetBeans platform to ensure it can run on mobile devices. An iterative development process will be used to analyze requirements, design interfaces, code functions, test the application, and repeat the process to continuously improve the software. The goal is to provide students with an affordable alternative to physical scientific calculators that displays solutions to help learning.
Solution manual fundamentals of fluid mechanics (4th edition)Guilherme Gonçalves
This document provides solutions to problems presented in the 4th edition of the textbook "Fundamentals of Fluid Mechanics". It contains over 1220 problem solutions organized by chapter in a clear, step-by-step format. The problems cover key concepts in fluid mechanics and many are designed to be solved using computer programs, spreadsheets, or programmable calculators. The document also provides the code for standard computer programs used in multiple solutions.
Development of Computer Aided Learning Software for Use in Electric Circuit A...drboon
Presently, instructors are required to teach more students with the same resources, thereby reducing the amount of time instructors have with their students. Because of this, examples may be omitted to be able to make it through all of the required material. This can be problematic with electric circuit analysis courses and other courses used as prerequisites. A lack of understanding in these classes will likely continue in future classes. While software is often used in these classes, often it is analysis software not meant to teach concepts. Teaching software does exist, but may have only a preset number of problems or only provide the solution. Others provide a ‘limitless’ number of problems by changing component values, but each ends up being the same basic problem. This paper introduces new learning software that addresses these shortcomings. The software provides a practically limitless number of problems by varying component values and circuit structure. Moreover, it provides both an answer and an explanation. Finally, it is designed so that students who need more help can get it, while those who do not can move on.
In the last few decades the field of Information and Communication Technology (ICT) has made a swift progress. The growing role of computers in education is beyond doubt and has become essential for higher educational institutions for teaching and instructional purposes to improve the quality and efficiency of both teaching and learning
vtu data structures lab manual bcs304 pdfLPSChandana
The document contains a preface and index for a lab manual on data structures. It discusses how C programming offers facilities to group data into convenient packages called data structures. The preface emphasizes abstract concepts of data structures and how they are useful for problem solving using structures like queues, arrays, linked lists, stacks, trees and graphs. The index lists 11 programs to be developed related to various data structure operations and applications including strings, stacks, queues, linked lists, polynomials and more.
A Generic Tool For Generating And Assessing Problems Automatically Using Spre...Tony Lisko
This document describes a new tool called ACME_Spreadsheet that can automatically generate, assign, correct, provide feedback, and grade spreadsheet exercises for educational purposes. Spreadsheets are commonly used in fields like mathematics, statistics, economics, and business. While other systems exist for automatically grading spreadsheets, ACME_Spreadsheet improves on previous approaches through its end-to-end workflow from exercise design to feedback and grading, and its low technical requirements for instructors. The tool allows instructors to assign individualized spreadsheet exercises to students that are then automatically graded. It provides feedback to support student learning. ACME_Spreadsheet is part of a broader platform called ACME that aims to continuously improve higher education through automated assessment tools.
SOFTWARE BASED CALCULATION OF CAPACITY OUTAGE OF GENERATING UNITSvivatechijri
The main theme of the project is to develop software for calculating the reliability & capacity outage table for generation purposes. The method for the calculation is quite lengthy, complex & a high possibility to get a human error during the calculation. The methods used to calculate reliability & capacity outage are Digital Method, Partial Binomial Method & Recursive Method, this method is highly recommended, but can be complex during the actual calculation. To justify the need for this method & also to remove the human error factor during quicker & better calculation, the software is made with the help of the python software. The python-based website will be easily accessible to use to any sort of user, choosing python program was a better option as it does not compile but interprets the calculation are in constant runtime with the input of values, this program helps in developing highly complex calculation which is up to many decimal points.
1. The document describes an ICT project created by students using Visual Basic 6.0 to develop calculators for math, science, and health subjects.
2. The programs include calculations for molar mass, moles, water requirements, and conversions between units. A percentage/rate calculator is also included.
3. The programs are intended to help students in their studies by simplifying complex calculations and conversions between units.
Technology in maths and maths in technologyshajunisha
Technology has greatly expanded the role of mathematics beyond traditional academic uses. New fields like operations research, control theory, and signal processing now rely on both mathematics and technology. A variety of technologies are commonly used in classrooms today, including computers, online study tools, blogs/wikis, microphones, mobile devices, interactive whiteboards, and digital games. These tools enhance teaching and learning by making lessons more interactive, visual, and engaging for students. Calculators like graphing, scientific, and matrix calculators also provide hands-on experience with mathematical concepts.
Robotic hand prototype as a didactic model.IRJET Journal
This document describes the development of a robotic hand prototype designed to be used as a didactic (teaching) model for students. The prototype was designed using 3D CAD software and 3D printed. It is controlled using an ATmega 328P microcontroller and flex sensors to read finger positions and servo motors to drive finger movement. The prototype was tested with students through classroom lessons focusing on electronics, microcontrollers, programming and robotics concepts. Students then programmed a binary counting sequence using the hand. The prototype was able to execute the programmed sequence but some fingers had slower movement times than desired due to the weight and flexibility of the 3D printed material. The robotic hand prototype was intended to motivate students and support their learning of robotics
LabVIEW - Teaching tool for control design subjectIOSR Journals
This document discusses using LabVIEW as a teaching tool for control design subjects. It allows students to simulate experimental results, analyze comparisons between different systems, and validate modeling and controller design. Students can visualize the effects of changing system parameters. This makes the learning process more active compared to traditional lectures. LabVIEW provides tools like root locus analysis, Bode plots, and step responses to analyze system performance. Examples are given of modeling a DC motor and analyzing its frequency response and root locus. LabVIEW is concluded to improve engineering education by allowing students to validate theory with working prototypes.
This document outlines the syllabus for the Analog and Digital Electronics Laboratory course for the third semester Computer Science students. It includes the vision, mission, objectives, and outcomes of both the institution and department. The syllabus covers both analog and digital circuits through 9 experiments involving components like timers, operational amplifiers, adders/subtractors, multiplexers, flip-flops, and counters. Students will design, simulate, implement, and test the circuits both in hardware and HDL. The goal is for students to apply design skills and gain practical experience with electronic components and tools.
This document discusses the role of computers in petroleum engineering. It begins by defining what a computer is and its basic components. It then outlines several applications of computers in petroleum engineering, including using handheld computers for field operations, various petroleum engineering software for tasks like reservoir modeling and production analysis, and making classrooms more effective through multimedia presentations. Online education enabled by computers is also discussed. Common Microsoft office applications like Word, Excel and PowerPoint are described and their relevance to petroleum engineering work explained.
This paper introduces a programming course which provides second year mechanical engineering students the opportunity to develop engineering-oriented software and Graphical User Interface (GUI) using the principles of software engineering. Two object-oriented languages, C# and MATLAB) were taught in this course to make the students familiar with different types of programming languages. Methods used in teaching this course such as topics, class/laboratory schedule, and evaluation instruments are explained. The course objectives were well met according to the student learning outcomes and several Mechanical Engineering B.Sc. program objectives were also supported by this course. This course was taught by the author at University of Louisville and will be offered in University of Louisiana at Lafayette.
The document discusses the role of computers in chemical engineering education. It identifies four main areas of computer application: process modelling, programming, computer-based process control, and computer-interactive mathematics tuition. It also examines challenges students face with mathematics and how computer-assisted learning can help address skills gaps while promoting independent study. Overall, the document argues that computers are useful educational tools when they reinforce learning and don't oversimplify concepts, and that teaching programming and modelling can develop valuable problem-solving skills.
The document provides information on the K to 12 Creative Technologies curriculum for junior high school students in the Philippines. It outlines the conceptual framework, key stage standards, grade level standards, and sample lessons for the subject. The curriculum aims to develop students' technological proficiency through a project-based approach involving theoretical learning and hands-on laboratory work developing ideas and projects that apply to different fields. It is designed to equip students with skills for lifelong learning and an entrepreneurial spirit.
Calculus is used extensively in software engineering and related fields for several purposes:
1) In computer graphics, calculus is used to simulate light bouncing and rendering objects smoothly as well as powering physics engines.
2) In programming language design and semantics, calculus provides a functional predicate calculus to support formal reasoning about programs.
3) Calculus allows the creation of mathematical models to arrive at optimal solutions and is used in many areas of physics that relate to software such as motion, heat, and dynamics.
4) Fields like signal analysis, scientific computing, financial modeling, and robotics also employ calculus for tasks like examining functions, simulating systems, and modeling optimization.
The document provides information on the K to 12 Creative Technologies Curriculum Guide for junior high school students in the Philippines. It outlines the conceptual framework, key stage standards, grade level standards, and sample lessons for the subject. The curriculum aims to develop students' technological proficiency through a project-based approach involving theoretical learning and hands-on laboratory work developing ideas and projects in different fields. It is designed to equip students with skills for lifelong learning and entrepreneurship.
The document describes the development of a mobile scientific calculator application. It will allow students to solve mathematical problems and view the step-by-step solutions on their mobile phones. The application will be created using Java programming on the NetBeans platform to ensure it can run on mobile devices. An iterative development process will be used to analyze requirements, design interfaces, code functions, test the application, and repeat the process to continuously improve the software. The goal is to provide students with an affordable alternative to physical scientific calculators that displays solutions to help learning.
Solution manual fundamentals of fluid mechanics (4th edition)Guilherme Gonçalves
This document provides solutions to problems presented in the 4th edition of the textbook "Fundamentals of Fluid Mechanics". It contains over 1220 problem solutions organized by chapter in a clear, step-by-step format. The problems cover key concepts in fluid mechanics and many are designed to be solved using computer programs, spreadsheets, or programmable calculators. The document also provides the code for standard computer programs used in multiple solutions.
Development of Computer Aided Learning Software for Use in Electric Circuit A...drboon
Presently, instructors are required to teach more students with the same resources, thereby reducing the amount of time instructors have with their students. Because of this, examples may be omitted to be able to make it through all of the required material. This can be problematic with electric circuit analysis courses and other courses used as prerequisites. A lack of understanding in these classes will likely continue in future classes. While software is often used in these classes, often it is analysis software not meant to teach concepts. Teaching software does exist, but may have only a preset number of problems or only provide the solution. Others provide a ‘limitless’ number of problems by changing component values, but each ends up being the same basic problem. This paper introduces new learning software that addresses these shortcomings. The software provides a practically limitless number of problems by varying component values and circuit structure. Moreover, it provides both an answer and an explanation. Finally, it is designed so that students who need more help can get it, while those who do not can move on.
In the last few decades the field of Information and Communication Technology (ICT) has made a swift progress. The growing role of computers in education is beyond doubt and has become essential for higher educational institutions for teaching and instructional purposes to improve the quality and efficiency of both teaching and learning
vtu data structures lab manual bcs304 pdfLPSChandana
The document contains a preface and index for a lab manual on data structures. It discusses how C programming offers facilities to group data into convenient packages called data structures. The preface emphasizes abstract concepts of data structures and how they are useful for problem solving using structures like queues, arrays, linked lists, stacks, trees and graphs. The index lists 11 programs to be developed related to various data structure operations and applications including strings, stacks, queues, linked lists, polynomials and more.
A Generic Tool For Generating And Assessing Problems Automatically Using Spre...Tony Lisko
This document describes a new tool called ACME_Spreadsheet that can automatically generate, assign, correct, provide feedback, and grade spreadsheet exercises for educational purposes. Spreadsheets are commonly used in fields like mathematics, statistics, economics, and business. While other systems exist for automatically grading spreadsheets, ACME_Spreadsheet improves on previous approaches through its end-to-end workflow from exercise design to feedback and grading, and its low technical requirements for instructors. The tool allows instructors to assign individualized spreadsheet exercises to students that are then automatically graded. It provides feedback to support student learning. ACME_Spreadsheet is part of a broader platform called ACME that aims to continuously improve higher education through automated assessment tools.
SOFTWARE BASED CALCULATION OF CAPACITY OUTAGE OF GENERATING UNITSvivatechijri
The main theme of the project is to develop software for calculating the reliability & capacity outage table for generation purposes. The method for the calculation is quite lengthy, complex & a high possibility to get a human error during the calculation. The methods used to calculate reliability & capacity outage are Digital Method, Partial Binomial Method & Recursive Method, this method is highly recommended, but can be complex during the actual calculation. To justify the need for this method & also to remove the human error factor during quicker & better calculation, the software is made with the help of the python software. The python-based website will be easily accessible to use to any sort of user, choosing python program was a better option as it does not compile but interprets the calculation are in constant runtime with the input of values, this program helps in developing highly complex calculation which is up to many decimal points.
1. The document describes an ICT project created by students using Visual Basic 6.0 to develop calculators for math, science, and health subjects.
2. The programs include calculations for molar mass, moles, water requirements, and conversions between units. A percentage/rate calculator is also included.
3. The programs are intended to help students in their studies by simplifying complex calculations and conversions between units.
Technology in maths and maths in technologyshajunisha
Technology has greatly expanded the role of mathematics beyond traditional academic uses. New fields like operations research, control theory, and signal processing now rely on both mathematics and technology. A variety of technologies are commonly used in classrooms today, including computers, online study tools, blogs/wikis, microphones, mobile devices, interactive whiteboards, and digital games. These tools enhance teaching and learning by making lessons more interactive, visual, and engaging for students. Calculators like graphing, scientific, and matrix calculators also provide hands-on experience with mathematical concepts.
Robotic hand prototype as a didactic model.IRJET Journal
This document describes the development of a robotic hand prototype designed to be used as a didactic (teaching) model for students. The prototype was designed using 3D CAD software and 3D printed. It is controlled using an ATmega 328P microcontroller and flex sensors to read finger positions and servo motors to drive finger movement. The prototype was tested with students through classroom lessons focusing on electronics, microcontrollers, programming and robotics concepts. Students then programmed a binary counting sequence using the hand. The prototype was able to execute the programmed sequence but some fingers had slower movement times than desired due to the weight and flexibility of the 3D printed material. The robotic hand prototype was intended to motivate students and support their learning of robotics
LabVIEW - Teaching tool for control design subjectIOSR Journals
This document discusses using LabVIEW as a teaching tool for control design subjects. It allows students to simulate experimental results, analyze comparisons between different systems, and validate modeling and controller design. Students can visualize the effects of changing system parameters. This makes the learning process more active compared to traditional lectures. LabVIEW provides tools like root locus analysis, Bode plots, and step responses to analyze system performance. Examples are given of modeling a DC motor and analyzing its frequency response and root locus. LabVIEW is concluded to improve engineering education by allowing students to validate theory with working prototypes.
This document outlines the syllabus for the Analog and Digital Electronics Laboratory course for the third semester Computer Science students. It includes the vision, mission, objectives, and outcomes of both the institution and department. The syllabus covers both analog and digital circuits through 9 experiments involving components like timers, operational amplifiers, adders/subtractors, multiplexers, flip-flops, and counters. Students will design, simulate, implement, and test the circuits both in hardware and HDL. The goal is for students to apply design skills and gain practical experience with electronic components and tools.
This document discusses the role of computers in petroleum engineering. It begins by defining what a computer is and its basic components. It then outlines several applications of computers in petroleum engineering, including using handheld computers for field operations, various petroleum engineering software for tasks like reservoir modeling and production analysis, and making classrooms more effective through multimedia presentations. Online education enabled by computers is also discussed. Common Microsoft office applications like Word, Excel and PowerPoint are described and their relevance to petroleum engineering work explained.
This paper introduces a programming course which provides second year mechanical engineering students the opportunity to develop engineering-oriented software and Graphical User Interface (GUI) using the principles of software engineering. Two object-oriented languages, C# and MATLAB) were taught in this course to make the students familiar with different types of programming languages. Methods used in teaching this course such as topics, class/laboratory schedule, and evaluation instruments are explained. The course objectives were well met according to the student learning outcomes and several Mechanical Engineering B.Sc. program objectives were also supported by this course. This course was taught by the author at University of Louisville and will be offered in University of Louisiana at Lafayette.
The document discusses the role of computers in chemical engineering education. It identifies four main areas of computer application: process modelling, programming, computer-based process control, and computer-interactive mathematics tuition. It also examines challenges students face with mathematics and how computer-assisted learning can help address skills gaps while promoting independent study. Overall, the document argues that computers are useful educational tools when they reinforce learning and don't oversimplify concepts, and that teaching programming and modelling can develop valuable problem-solving skills.
The document provides information on the K to 12 Creative Technologies curriculum for junior high school students in the Philippines. It outlines the conceptual framework, key stage standards, grade level standards, and sample lessons for the subject. The curriculum aims to develop students' technological proficiency through a project-based approach involving theoretical learning and hands-on laboratory work developing ideas and projects that apply to different fields. It is designed to equip students with skills for lifelong learning and an entrepreneurial spirit.
Calculus is used extensively in software engineering and related fields for several purposes:
1) In computer graphics, calculus is used to simulate light bouncing and rendering objects smoothly as well as powering physics engines.
2) In programming language design and semantics, calculus provides a functional predicate calculus to support formal reasoning about programs.
3) Calculus allows the creation of mathematical models to arrive at optimal solutions and is used in many areas of physics that relate to software such as motion, heat, and dynamics.
4) Fields like signal analysis, scientific computing, financial modeling, and robotics also employ calculus for tasks like examining functions, simulating systems, and modeling optimization.
The document provides information on the K to 12 Creative Technologies Curriculum Guide for junior high school students in the Philippines. It outlines the conceptual framework, key stage standards, grade level standards, and sample lessons for the subject. The curriculum aims to develop students' technological proficiency through a project-based approach involving theoretical learning and hands-on laboratory work developing ideas and projects in different fields. It is designed to equip students with skills for lifelong learning and entrepreneurship.
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1. Computational Aptitude of Handheld Calculator
USE OF HANDHELD CALCULATORS AS SUPPORTIVE TOOLS IN
ENGINEERING EDUCATION
BY
ADEWOLE J. K . and OSUNLEKE A. S2.
Department of Chemical Engineering
1
King Fahd University of Petroleum & Minerals
2
Obafemi Awolowo University,
Ile Ife, Nigeria
1
ABSTRACT
The computational capability of a handheld non – programmable calculator as a supportive tool in effective teaching of softcomputing skill is demonstrated in this work. Seven engineering problems were solved using some of its essential in-built
scientific functions and accessories. The results obtained compared favourably well with those from sophisticated algebraic
software packages such as MATLAB and MS Excel in terms of numerical accuracy. The percentage error obtained for all the
seven problems are 0%. Acquiring skills in the use of this calculator will therefore not only enhance the learning of modern
computing software, thereby preparing students and engineers for solving real-time world problems but will also serve as an
affordable alternative to the available algebraic software packages in situations where these software are out reach. It is hoped
that this new effort will pave way for a more pragmatic approach of teaching and assessing computing skills in our higher
institutions.
Keywords: sustainable development; engineering education; computing skills; simulation software; technical competencies.
1.0
INTRODUCTION
Effective teaching in engineering education is an
important tool for sustainable industrial development. The
act of teaching the principles of engineering to produce
well baked products has been described as the most
innovative and continually evolving challenges (1). With
the emergence of many different technologies, students
need to be taught the basic knowledge required for them
to be relevant in this jet age. Globally, engineering
environment today demands both technical competencies
and excellent computing skills. Engineers and scientists
are expected to be skilful in simulation software. Gone are
the days when computer applications were consigned to
the ranks of senior staff. The emerging proliferation of
personal computers has greatly transformed application
software into common tools for problem solving.
Numerous sophisticated mathematics processing software
packages are now available. It has been observed by Foley
(2) that students in engineering and science have been
using this software but often without good results. The
author disagreed with teaching analysis in one place
(course) and computing in another place (another course),
when the two can be taught concurrently. In an attempt to
solve this problem, Hill and Rajeev et al (3, 4) wrote on
fundamentals for getting accurate simulation results.
In most schools (especially in the developing countries
where the MDGs are expected to be met by 2015), the
opportunities for hands-on practice with process
simulators may have been nonexistent or underutilised.
This is due to the fact that adequate method of teaching
computing skills has not been put in place. Students
population combined with the cost of sophisticated
software have contributed to this problem. Millions of
dollars is spent on acquiring licences for software with
little or nothing to show for it. It is quite clear that once
people are oblivious of the basics underlying the use of
this software, then it becomes difficult to use them. Also,
it has been observed that students are not interested in
learning whatever will not come out in their examinations.
The end result of this is that if a lecturer attempts to teach
them software skills, the first question they will ask is
whether it will come in the examinations or not. Of course
students know quite well that it is very difficult for them
to be asked questions that will entail real time use of
computer in the examination halls. With this in mind, the
only alternative for the lecturers is to give assignment
which majority will not do personally. All these factors
coupled with other social distractions have really
J. K. Adewole & A. S. Osunleke, 2011
2. Computational Aptitude of Handheld Calculator
contributed to lack of student’s interest and hence little or
no understanding of the basic knowledge of technical
computing. In essence, there is the need to inculcate the
use of affordable, accessible and efficient methods that
will give room for real time use of computer in the
examination halls. Accessibility in the sense that it is not
necessary to use thousands of dollars to procure the tools
needed to implement this method. We need not to have
students to queue up to practise what they have learnt.
The tool should be efficient such that moderate problems
can be solved and analysed using these tools and results
obtained are comparable with those from expensive
software packages. While the use of calculator can never
be a substitute for the available mathematical software, it
can be used, at the initial stage of learning computing
skills, to boost student morale and make computing more
interesting.
This paper is written to demonstrate the use of handheld
calculator in solving engineering problems. It discusses its
application as a supportive tool in teaching computing
skills. In justifying the use of handheld calculator,
engineering problems were solved using 1 Casio fx –
991MMS calculator and results obtained compared with
those using software like 2 Matlab and MS Excel. The
paper will present a step by step procedure of using the
available built in Functions and Modes in the handheld
calculator. The choice of this calculator is due to its
abundance and the fact that it is not programmable. It will
therefore not give room for examination malpractice.
Deep familiarization with such a calculator will give
student good background skills in using simulation
software applications.
2.1
Computer and Handheld Calculators
The history of computer can be traced back to abacus
which was developed as a calculating device in the
ancient kingdom of Babylonia in SW Asia and widely
used in early Greek and Roman times (5). The first
general purpose electronic digital calculator that was the
prototype of most computers used today was invented by
J. P. Eckert and co-invented with J. W. Mauchly in 1946.
In about four years later, Eckert and Mauchly produced a
Binary Automatic Computer (BINAC) which is capable
1
Casio is a registered trademark of the Casio Computer Co., Ltd
Matlab is a registered trademark of the Math Works Inc. and MS Excel
is a registered trademark of Microsoft Inc
2
of storing information on magnetic tape rather the than
earlier punched cards. An all transistor calculator was
introduced in 1965 by Sharp in Japan. Further research on
calculator ushered in Scientific Calculator produced by
Hewlett-Packard (HP) in 1972. Comparison between
computer and calculator can further be illustrated
graphically as shown in Fig 2.1. Details relating the
common features regarding the design and development
of the software can be found in any standard Computer
Science and Engineering Texts.
Display
Screen
Key Board
Fig. 2.1: Common Features of a Computer and
a Handheld Calculator
3.0 APPLICATIONS OF AVAILABLE FUNCTIONS
TO ENGINEERING PROBLEMS
3.1 CALC Function
Problem: One of the mathematical models proposed by
Taiwo and Adewole (6) for predicting dynamic liquid
hold up can be expressed as:
P1 = 0.0323Q – 0.0003XF + 0.0249 ed – 0.0116 (3.1)
for 0 d 0.12, where XF is the feed composition, Q
(KJ/s) is the heat flow rate and d (in m) is the distance of
the point of measurement from the top. This can be
implemented using the CALC Function
Representation: Let Q, XF, d and P1 be represented as A, B,
C and D respectively.
J. K. Adewole & A. S. Osunleke, 2011
3. Computational Aptitude of Handheld Calculator
Algorithm: ALPHA D ALPHA = 0.0323 x ALPHA A –
0.0003 x B + 0.0249 x SHIFT ex (C) - 0.0116 CALC
For the first calculations press 0.195 = 0.1 = 0 = and the
answer will be displayed as 0.01957. The complete results
are as shown below in Table 3.1
Table 3.1: Results obtained using CALC Function
Q
XF
d
P1 (CALC) P1 (MS %
(A)
(B)
(C)
(D)
EXCEL) ERROR
0.0001
1
2.51
0.86 ln
0.
100000 f
f
3.7
Let
f = F.
Algorithm: (1 ÷
ALPHA F + 0.86 × ln (0.0001 ÷ 3.7
0.195
0.1
0
0.01957
0.01957
0
+ 2.51 ÷ (100000 ×
0.235
0.1
0.02
0.02136
0.02136
0
SHIFT CALC SHIFT CALC
0.195
0.2
0.04
0.02055
0.02055
0
0.2
0.06
0.02237
0.02237
0
Results: F = 0.01885.
0.235
0.195
0.4
0.08
0.02155
0.02155
0
0.235
0.4
0.1
0.02339
0.02339
0
0.195
0.6
0.12
0.02259
0.02259
0
3.2
ALPHA F))) ALPHA CALC 0
Table 3.2: Results Obtained using SOLVE Function to
Solve Colebrook Equation
f (CALCULATOR)
f (Text) % ERROR
(F)
0.0189
SOLVE Function
The SOLVE Function employs the Newton’s method to
find approximations to more complex equations. It can be
used to find the roots of non – linear equations such as
f (x) = 2x – x2
0.0189
0
The same answer was obtained as in ref 7 using a ten page
Matlab code. However the matlab program used was an
interactive one with graphical display making it more
robust. The above algorithm can also be made interactive
for various values of
D
and
N Re by defining them as
and
variables (say X and Y).
y (t ) (1 exp( t )[cos(t ) sin(t )]) 0.5
where , and are constants.
Problem 2: The boiling of an equimolar mixture of
benzene and toluene at 101.3KN/m2 (760mm Hg) can also
be computed using the SOLVE Function. Given Antoine
constant for Benzene as
Problem 1: Colebrook equation relating the friction factor
( f ) for a turbulent flown of an incompressible fluid in a
pipe with the roughness ( ) and the diameter (D) of the
pipe is given by the non – linear expression
1
2.51
0.86 ln D
3.7 N Re f
f
0
Representation:
Given
that
D
Antoine constant for Toluene is
K1B=6.95334, K2B = 1343.943 K3B = 219.377
(3.2)
Representation: At the boiling point
y A yB 1
f using the CALC
This equation can be solved for
function.
K1A= 6.90565, K2A = 1211.033 K3A = 220.79
0.0001 and
N Re 100000 , the equation can be rewritten as
(3.3)
For equimolar mixture
xA o
PA PBo 1
P
J. K. Adewole & A. S. Osunleke, 2011
x A x B 0.5
(3.4)
4. Computational Aptitude of Handheld Calculator
i.
ii.
From Antoine equation
P 10
o
k1
k2
T k3
(3.5)
Substituting (3.5) into (3.4), with A representing Benzene
and B Toluene, we have
k2 A
k1 B 2 B
T k3 B
x A k1 A T k3 A
10
10
P
k
1
Substituting for the constants and let T = X, we have
.033
6.95334
6.90565 1211220.7
X 219.377
X
10
10
1343
1520
Algorithm:
The function of the variable
The point at which the differentiation is
calculated
The change in Δx or step size
iii.
The general expression for solving such problem is
SHIFT
d
expression , a , b , Δx )
dx
Problem 1: Determine the first derivative of the
expression f ( x ) x exp( x ) at x = 0 using a step size
of h = 0.1
Representation: Let x = X
Algorithm: SHIFT
d
dx
ALPHA X x SHIFT ln ( -
ALPHA X ) , 0 , 0.1 )
Results: X = 1
( SHIFT log ( 6.90565 – (1211.033 ÷ ( ALPHA X + 220.7
) ) ) + SHIFT log ( 6.95334 – ( 1343 ÷ (ALPHA X +
219.377 ) ) ) ALPHA CALC 1520 SHIFT CALC SHIFT
CALC
The result obtained from the above is 92.1058 oC
(365.1058K). This result compares favourably with that in
ref (8) which uses trial and error to determine at which
temperature PB +PT =101.3 KN/m2 (Table 3.3).
Table 3.3: Results from Trial and Error
T (K)
PBo
PTo
PB
PT
PB PT
373
180.006
74.152
90.003
37.076
127.079
353
100.988
38.815
50.494
77.631
128.125
3.4 Integration Calculation Function
The integration function is used to solve moderate
integration problems. To use this Function, four inputs are
required
The function with variable x
The boundary a and b which define the
integration range of the definite integral
The number of partition n.
The general expression for solving such problem is
dx expression, a , b , n )
Problem
1:
2
I ( x)
0
sin x
1 0.25 sin 2 x
363
136.087
24.213
68.044
27.106
95.150
365
144.125
57.810
772.062
28.905
100.967
Algorithm:
365.1
144.534
57.996
72.267
28.998
101.265
(sin ALPHA X )
3.3 Differential Calculation Function
This solver can be used to obtain a numerical derivative of
explicit expressions such as f ( x ) x cos(x) . To solve
such problem, three inputs are needed
Solve
for
I(x)
given
that
dx (3.3)
dx (( sin ALPHA X ) ÷ (
( 1 – 0.25 x
x 2 ) ) , 0 , ÷ 2 , 4)
Table 3.4: Results obtained using Integration Function
and Analytical Method
I (x) (CALCULATOR) I (x) (Analytical) % ERROR
1.09861
J. K. Adewole & A. S. Osunleke, 2011
1.098612
0
5. Computational Aptitude of Handheld Calculator
The analytical solution was obtained from (9). It should
be noted that the calculator must be in radian mode to
solve this problem. The function can also be used to solve
integrals such as
150
(i)
CpdT
D
Cp 0.235 exp[0.0473T
1
2
x 3 exp( x 2 )
(ii) I (0,1)
dx
2
0 2 cos(ln(1 x )
1
dx (
2
0 1 x
0
1
4 x2
60,000
470,000
465,000
477,000
C K 1 D n( K 2 K 3 D )
n QD
I (0,2)
40,000
Representation: Given
1
2
20,000
C
]
1
(iv)
Table 3.5: Variation of Diameter with the Manufacturing
Costs
given that
1800
(iii) I (0,1)
(ii) Estimate the optimum value of C
(take Q = 100, 000 and use Table 3.5)
C K1 D
dx
exp[sin(x)]dx
D opt
150
U ( KJ Kg )
K 2Q
K 3Q
D
(3.8)
Differentiating (3.6) and equating to zero, the optimum
diameter can be expressed as
1
(vi)
(3.7)
Substitution (3.7) into (3.6) we have,
1
(v) I (1,1)
(3.6)
(0.855 9.42 x10
4
T )dT
20
K 2Q
K1
(3.9)
The simplified form of (3.8) is given as
C K1 D 100000
for n 5
[ANS (i) -1731.12cal/g (ii) 0.04585 (iii) 0.785398
(iv) 0.8813736 (v) 2.532132 (vi) 121.5591 KJ/Kg]
3.5 Matrix Calculations
In MAT Mode, the calculator can be used to create
maximum of three matrices each with up to three rows
and three columns. Matrices operations such as addition,
subtraction, multiplication, transpose, inverse, and
determinant can be performed on the matrices created.
Problem: The annual manufacturing cost for a specialty
chemical is
C K 1 D n( K 2 K 3 D) and n Q D
K2
100000 K 3
D
(3.10)
Using the values from Table 3.4, a matrix structure can be
obtained as follows
D1
C1
C D
2 2
C 3
D3
100000
100000
D1
K1
100000
100000 K 2
D2
K3
100000
100000
D3
Rearranging (3.11) gives
Where K1, K2, K3 and Q are constants
(i) Obtain an expression for optimum D
J. K. Adewole & A. S. Osunleke, 2011
(3.11)
6. Computational Aptitude of Handheld Calculator
D1
K1
K D
21 2
K3
D3
1
100000
100000
D1
C1
100000
100000 C 2 (3.12)
D2
C3
100000
100000
D3
By using values from Table 3.4, K1, K2 and K3 can be
obtained as follows:
1
5 100000 470000
K 1 20000
K 40000 2.5 100000 465000
2
K 3 60000 1.67 100000 477000
3.6 Regression Calculations
The REG Mode can be used to perform linear,
logarithmic, exponential, power, inverse and quadratic
regressions. This mode is very useful in data analysis,
mathematical modelling and in solving optimization
problems.
Problem: Table 3.7 shows experimental data in which the
independent variable x is the mole percentage of a
reactant and the dependent variable y is the yield (in
percent). Determine the value of x that maximises the
yield.
Table 3.7: Experimental Data on Percentage Reactant and
Yield
X
20
20
30
40
40
50
50
50
60
70
For the ease of computing K1, K2 and K3, let
Y
73
78
85
90
91
87
86
91
75
65
K1
K A1 B
2
K3
Representation: The data is first fit with a quadratic model
of the form
Algorithm:
MODE MODE MODE 2 SHIFT 4 1 1 3 = 3 = 20000 5
100000 40000 2.5 100000 60000 1.67 100000 SHIFT 4 1
2 3 = 1 = 470000 465000 477000 SHIFT 4 3 1 X-1 x
SHIFT 4 3 2 =
The results are shown in Table 3.6.
Table 3.6:Comparison of results obtained using Excel
Link in Matlab and Matrix Function in Calculator
MS Excel
%
CALCULATOR Link/Matlab ERROR
K1
1.022
1.022
0
K2
10179.641
10179.641
0
K3
3.987
3.987
0
y A Bx Cx 2
(3.13)
Algorithm: MODE MODE 2 ► 3 20,73 M+ 20,78 M+
30,85 M+ 40,90 M+ 40,91 M+ 50,87 M+ 50,86 M+
50,91 M+ 60,75 M+ 70,65 M+ SHIFT 2 ► ► 1 SHIFT 2
► ► 2 = SHIFT 2 ► ► 3
The figure that shows on the screen after pressing M+ is
the number of data that has been entered. It is strongly
recommended that the calculator memory is cleared
before initiating a new set of calculations. This can be
done by pressing SHIFT MODE 3 = =
Results:
Table 3.8: Comparison of results obtained using MS
Excel and REG Mode in Calculator
CALCULATOR MS Excel
%ERROR
K 1 1.022 1.0
K 10179.641 10000
2
K 3 3.987 4
A
D opt 31622.78 and C opt 463245.55
The values for the MS Excel ware obtained from (10)
35.66
35.66
0
B
2.63
2.63
0
C
-0.032
-0.032
0
3.7 Equation Calculations
J. K. Adewole & A. S. Osunleke, 2011
7. Computational Aptitude of Handheld Calculator
The EQN Mode can be used to solve equations up to three
degrees and simultaneous linear equations with up to three
unknowns. The Mode can be applied in various field of
engineering including but not limited to Thermodynamics,
Mass Transfer, Optimization and Process Control.
the ladder of their academic pursuit. With the better
understanding of the use of this important tool, the
assessment of teaching of computing skills can now easily
be done even in the examination hall so as to inject the
spirit of speed and accuracy into the students.
Problem: Consider the function
Dedication: To my mother “Obinrin rere” and other
lovely mothers around the world. “Gbogbo yin le o jere
omo o” (ameen).
f ( x) 5 x 6 36 x 5 165 x 4 60 x 3 36
2
Determine the minimum point
Representation: The first derivative of this equation is
f ' ( x) 30 x 5 180 x 4 330 x 3 180 x 2 0 (3.14)
The optimum points can be obtained from (3.14) as
follows
30 x 2 ( x 3 6 x 2 11x 6) 0
3
2
Thus x 0 and x 6 x 11x 6 0
Algorithm: MODE MODE MODE 1 ► 3 1 = -6 = 11 = 6=
Continuous pressing of the = key will display the values
of X1 = 3, X2 = 1 and X3 = 2
Other functions and Modes in this calculator are Complex
Number, Base n, Statistical Calculations, Vector
Calculations, Metric Conversions, and Scientific
Constants.
Conclusion and Recommendation
In this work, we have demonstrated the capability of using
handheld calculator to perform some seemingly difficult
scientific computations with same level of numerical
accuracy as with commonly known sophisticated
algebraic software packages. From the outcome of this
work, we have shown that the hitherto familiar handheld
calculators have so far been under-utilized because of lack
of knowledge of its functional capabilities. It can be
concluded that calculator can be used as a supportive tool
in effective teaching of soft computing skills. It is
therefore recommended that the use of calculator be
introduced in courses related to some high level
computing. Students can later build on this basic
knowledge with the use of computer as they climb higher
Acknowledgement: My profound appreciation to my
favourite secondary school maths teacher, Engr Atoyebi
and other individuals (too numerous to mention) for their
contributions to this manuscript.
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J. K. Adewole & A. S. Osunleke, 2011