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.
Interactive Learning through Hands-on Practice using Electronic Mini - Lab (E...Vikas Dongre
- The document describes an "Electronic Mini-Lab (EML)" approach used to teach electronics practical skills through hands-on experience to students in India.
- The EML consists of basic electronic components, tools, and a breadboard that students purchase themselves for about 1000 Rupees. It allows them to perform electronics experiments anywhere by connecting components on the breadboard using a battery as a power supply.
- Using the EML, students design and test digital and analog circuits for their classes. This gives them direct experience handling components, troubleshooting issues, and learning from failures. It also reduces workload in formal labs and allows independent practice.
IRJET- Detection of Writing, Spelling and Arithmetic Dyslexic Problems in...IRJET Journal
The document describes a study that aims to develop a software application to detect dyslexia in children before they begin reading. The researchers acquired data on children's performance on phonological tasks from a previous UK study. They analyzed the data to identify the best phonological tasks for predicting dyslexia, which were oddity and rise time. The researchers then built a prototype application using these tasks. The goal is for the application to be used by parents to predict if a child is at risk for dyslexia before reading instruction begins, in order to intervene early.
IRJET - Visual Question Answering – Implementation using KerasIRJET Journal
This document summarizes a research paper that implements visual question answering using Keras deep learning frameworks. The researchers combine image features extracted from VGG-16 with question vectors from spaCy word embeddings to produce answers to questions about images. A multi-layer perceptron is used to merge the CNN and RNN models and produce categorical classes as answers. The implementation uses Keras with TensorFlow backend to extract image features from VGG-16 and question vectors from spaCy, which are then combined in the multi-layer perceptron to answer questions about the images.
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.
This document summarizes a journal article that evaluates an e-assessment system for automatically scoring short-answer free-text questions. The system uses natural language processing techniques to match student responses to predefined model answers. A study was conducted using this system to assess Open University students. Results found the system could accurately score responses, with accuracy similar to or greater than human markers. The system provides immediate feedback to students to help them learn from mistakes.
Convolutional recurrent neural network with template based representation for...IJECEIAES
Complex Question answering system is developed to answer different types of questions accurately. Initially the question from the natural language is transformed to an internal representation which captures the semantics and intent of the question. In the proposed work, internal representation is provided with templates instead of using synonyms or keywords. Then for each internal representation, it is mapped to relevant query against the knowledge base. In present work, the Template representation based Convolutional Recurrent Neural Network (T-CRNN) is proposed for selecting answer in Complex Question Answering (CQA) framework. Recurrent neural network is used to obtain the exact correlation between answers and questions and the semantic matching among the collection of answers. Initially, the process of learning is accomplished through Convolutional Neural Network (CNN) which represents the questions and answers separately. Then the representation with fixed length is produced for each question with the help of fully connected neural network. In order to design the semantic matching between the answers, the representation of Question Answer (QA) pair is given into the Recurrent Neural Network (RNN). Finally, for the given question, the correctly correlated answers are identified with the softmax classifier.
The document lists 12 thesis projects available for students to undertake, each supervised by faculty members and focusing on various computing technologies and applications such as quantum computing, gesture recognition interfaces, medical image segmentation, and software agent modeling. The projects involve both theoretical research and practical software development. Students must meet certain prerequisites and contact the listed supervisors to express interest in the projects.
This document discusses adaptive and intelligent collaborative learning support systems (AICLS). It provides background on related fields and outlines a classification scheme for AICLS focusing on the target of intervention. It describes work done to model adaptation patterns, develop an AICLS architecture, and implement case studies. Future research directions are proposed, including implementing complete courses with adaptive support at different levels and evolving systems based on assessment. Key publications in the field are also listed.
Interactive Learning through Hands-on Practice using Electronic Mini - Lab (E...Vikas Dongre
- The document describes an "Electronic Mini-Lab (EML)" approach used to teach electronics practical skills through hands-on experience to students in India.
- The EML consists of basic electronic components, tools, and a breadboard that students purchase themselves for about 1000 Rupees. It allows them to perform electronics experiments anywhere by connecting components on the breadboard using a battery as a power supply.
- Using the EML, students design and test digital and analog circuits for their classes. This gives them direct experience handling components, troubleshooting issues, and learning from failures. It also reduces workload in formal labs and allows independent practice.
IRJET- Detection of Writing, Spelling and Arithmetic Dyslexic Problems in...IRJET Journal
The document describes a study that aims to develop a software application to detect dyslexia in children before they begin reading. The researchers acquired data on children's performance on phonological tasks from a previous UK study. They analyzed the data to identify the best phonological tasks for predicting dyslexia, which were oddity and rise time. The researchers then built a prototype application using these tasks. The goal is for the application to be used by parents to predict if a child is at risk for dyslexia before reading instruction begins, in order to intervene early.
IRJET - Visual Question Answering – Implementation using KerasIRJET Journal
This document summarizes a research paper that implements visual question answering using Keras deep learning frameworks. The researchers combine image features extracted from VGG-16 with question vectors from spaCy word embeddings to produce answers to questions about images. A multi-layer perceptron is used to merge the CNN and RNN models and produce categorical classes as answers. The implementation uses Keras with TensorFlow backend to extract image features from VGG-16 and question vectors from spaCy, which are then combined in the multi-layer perceptron to answer questions about the images.
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.
This document summarizes a journal article that evaluates an e-assessment system for automatically scoring short-answer free-text questions. The system uses natural language processing techniques to match student responses to predefined model answers. A study was conducted using this system to assess Open University students. Results found the system could accurately score responses, with accuracy similar to or greater than human markers. The system provides immediate feedback to students to help them learn from mistakes.
Convolutional recurrent neural network with template based representation for...IJECEIAES
Complex Question answering system is developed to answer different types of questions accurately. Initially the question from the natural language is transformed to an internal representation which captures the semantics and intent of the question. In the proposed work, internal representation is provided with templates instead of using synonyms or keywords. Then for each internal representation, it is mapped to relevant query against the knowledge base. In present work, the Template representation based Convolutional Recurrent Neural Network (T-CRNN) is proposed for selecting answer in Complex Question Answering (CQA) framework. Recurrent neural network is used to obtain the exact correlation between answers and questions and the semantic matching among the collection of answers. Initially, the process of learning is accomplished through Convolutional Neural Network (CNN) which represents the questions and answers separately. Then the representation with fixed length is produced for each question with the help of fully connected neural network. In order to design the semantic matching between the answers, the representation of Question Answer (QA) pair is given into the Recurrent Neural Network (RNN). Finally, for the given question, the correctly correlated answers are identified with the softmax classifier.
The document lists 12 thesis projects available for students to undertake, each supervised by faculty members and focusing on various computing technologies and applications such as quantum computing, gesture recognition interfaces, medical image segmentation, and software agent modeling. The projects involve both theoretical research and practical software development. Students must meet certain prerequisites and contact the listed supervisors to express interest in the projects.
This document discusses adaptive and intelligent collaborative learning support systems (AICLS). It provides background on related fields and outlines a classification scheme for AICLS focusing on the target of intervention. It describes work done to model adaptation patterns, develop an AICLS architecture, and implement case studies. Future research directions are proposed, including implementing complete courses with adaptive support at different levels and evolving systems based on assessment. Key publications in the field are also listed.
IRJET - Automatic Lip Reading: Classification of Words and Phrases using Conv...IRJET Journal
This document presents research on developing an automatic lip reading system using convolutional neural networks. The system takes in video frames of a speaker's face without audio and classifies the words or phrases being spoken. The researchers preprocessed the data by detecting faces in video frames and cropping them. They then trained a CNN model on concatenated frames. Their model achieved 80.44% accuracy on the test set in classifying 10 words and 10 phrases from 17 speakers. The researchers concluded the model could be improved by addressing overfitting to unseen speakers with a larger dataset and regularization techniques.
IRJET- Machine Learning V/S Deep LearningIRJET Journal
Machine learning and deep learning are techniques used to implement artificial intelligence. Machine learning uses algorithms to help machines learn from data to make predictions or decisions without being explicitly programmed, while deep learning is a type of machine learning that is inspired by the human brain. The key differences are that machine learning works with moderate amounts of sorted data and produces results more quickly, while deep learning requires large amounts of data, more complex neural networks, and longer training times but can produce more accurate results. Both techniques will continue to be important for developing artificial intelligence and solving real-world problems in fields like computer vision and bioinformatics.
TL;DR: This tutorial was delivered at KDD 2021. Here we review recent developments to extend the capacity of neural networks to “learning to reason” from data, where the task is to determine if the data entails a conclusion.
The rise of big data and big compute has brought modern neural networks to many walks of digital life, thanks to the relative ease of construction of large models that scale to the real world. Current successes of Transformers and self-supervised pretraining on massive data have led some to believe that deep neural networks will be able to do almost everything whenever we have data and computational resources. However, this might not be the case. While neural networks are fast to exploit surface statistics, they fail miserably to generalize to novel combinations. Current neural networks do not perform deliberate reasoning – the capacity to deliberately deduce new knowledge out of the contextualized data. This tutorial reviews recent developments to extend the capacity of neural networks to “learning to reason” from data, where the task is to determine if the data entails a conclusion. This capacity opens up new ways to generate insights from data through arbitrary querying using natural languages without the need of predefining a narrow set of tasks.
Constructed model for micro-content recognition in lip reading based deep lea...journalBEEI
The document describes a proposed model for micro-content recognition in lip reading using deep learning. The model takes micro-contents (the English alphabet) as input from video and recognizes them using a convolutional neural network (CNN). The CNN performs feature extraction and recognition. The model was tested on a dataset containing videos of 11 people pronouncing letters and achieved a high recognition rate of 98%.
The document summarizes a student's project report on developing a tool to calculate indicators that characterize spatial networks. It includes:
1) An overview of the project which involved designing a program to calculate indicators for spatial networks based on a research paper and feedback from supervisors.
2) Details on the motivation, proposed structure, selected indicators to implement (degree, displacement, route factor, binary tree, Strahler index, asymmetry factor) and development of the program code.
3) How the program takes spatial network graph data and text files as input, calculates the selected indicators, and outputs the results to text files after processing and debugging.
This document is a resume for Dr. Parkavi.A that provides information over 3 sentences:
Dr. Parkavi.A is seeking a challenging career that utilizes her engineering knowledge and delivers expected commitments to society, with teaching experience at various institutions and expertise in areas like data analytics, programming languages, databases, and operating systems. She holds a Ph.D in computer science and engineering and has published papers in various international conferences and book chapters on topics related to education technology and data mining. She has also led academic projects focused on areas such as compiler design, networking applications, and maps of cities.
Image classification using convolutional neural networkKIRAN R
For separating the images from a large collection of images or from a large dataset this classifier can be used, Here deep neural network is used for training and classifying the images. The convolutional neural network is the most suitable algorithm for classifier images. This Classifier is a machine learning model, so the more you train it the more will be the accuracy.
This resume summarizes an individual with 12 years of experience in teaching, research, and patents. Some of the key details include:
- He has filed one patent that is currently awaiting examination and is working on a second patent. His education includes an MCA degree and pursuing a PhD.
- His research experience includes 18 published papers, guiding 4 master's students, and leading innovative projects. One of his patents is in an awaiting examination stage.
- His professional experience includes over 12 years as an Associate Professor teaching courses and coordinating online exams for over 500,000 students annually.
- He has received several awards for his research and papers, including two best paper awards and best reviewer awards from international journals
IRJET- Sentiment Analysis to Segregate Attributes using Machine Learning Tech...IRJET Journal
This document discusses sentiment analysis techniques using machine learning. It provides an overview of various supervised and unsupervised machine learning algorithms that can be used for sentiment analysis, including Naive Bayes, SVM, neural networks, decision trees, and BERT. The document also describes the system architecture of a proposed sentiment analysis system that would use a BERT model to identify and classify sentiments in text data as positive, negative, or neutral after preprocessing the data. The system aims to improve sentiment analysis efficiency by taking a holistic approach to attribute identification and classification.
Robotics-Based Learning in the Context of Computer ProgrammingJacob Storer
This document is a project report for research into whether robotics-based learning or simulation-based learning is more effective for teaching programming. It describes the objectives of developing tutorials for both an Arduino robot and visual basic simulation. Programming tasks for moving forwards/backwards and along shapes were developed. Tutorials and programs were implemented to teach these tasks. Surveys were given to test groups after using each method to collect data on their effectiveness for comparison. While results were mixed, all indicated learning was improved with a teacher. Due to the small sample size, no conclusive answer could be provided.
This document provides an overview of a tutorial on machine learning and reasoning for drug discovery.
The tutorial covers several topics: molecular representation and property prediction, including fingerprints, string representations, graph representations, and self-supervised learning; protein representation and protein-drug binding; molecular optimization and generation; and knowledge graph reasoning and drug synthesis.
The introduction discusses the drug discovery pipeline and how machine learning can help with various tasks such as molecular property prediction, target identification, and reaction planning. Neural networks are well-suited for drug discovery due to their expressiveness, learnability, generalizability, and ability to handle large amounts of data.
This document contains the resume of Shubham Vijay Vargiy, who is currently pursuing a B. Tech in Electronics and Communication Engineering at Shri Mata Vaishno Devi University in Jammu and Kashmir, India. Some of his qualifications include graduating high school with 83.38% and 97% in physics, chemistry, and mathematics. His current CGPA is 7.36. He has worked on several projects related to programming and embedded systems and has attended conferences to present papers on his work. He is seeking opportunities in programming and software development where he can apply his skills and contribute to an organization.
PWL Seattle #23 - A Few Useful Things to Know About Machine LearningTristan Penman
A mini-talk prepared for Papers We Love @ Seattle, September 2016, about the paper "A Few Useful Things to Know About Machine Learning". At just over eight pages, this paper by Pedro Domingos delivers an approachable summary of some of the folk knowledge often missed by those new to the field of Machine Learning.
This talk was intended as a high level talk, avoiding the math-heavy approach typical of Machine Learning discussions. The slides include references to other resources that may be useful to students and practitioners alike.
A Few Useful Things to Know about Machine Learningnep_test_account
1. Machine learning algorithms can automatically learn programs from data by generalizing from examples, which is often more feasible and cost-effective than manual programming. However, developing successful machine learning applications requires expertise beyond what textbooks provide.
2. Machine learning consists of three main components: representation, evaluation, and optimization. Choosing appropriate combinations of these components is key to building effective learners.
3. The goal of machine learning is generalization to new examples, not just accuracy on the training data. Strict separation of training and test data is necessary to evaluate generalization performance.
A Survey on Using Artificial Intelligence Techniques in the Software Developm...IJERA Editor
Software engineering and artificial intelligence are the two important fields of the computer science. Artificial Intelligence is about making machines intelligent, while Software engineering is knowledge –intensive activity, requiring extensive knowledge of the application domain and of the target software itself. This study intends to review the techniques developed in artificial intelligence from the standpoint of their application in software engineering. The goal of this research paper is to give some guidelines to use the artificial intelligence techniques that can be applied in solving problems associated with software engineering processes. The aim of this paper is to find out the exact AI technique is likely to be fruitful for particular software development process
Keynote 1: Teaching and Learning Computational Thinking at ScaleCITE
Computational thinking involves problem formulation, pattern recognition, abstraction, and algorithm design. It is an important 21st century skill and countries are incorporating it into curricula. MOOCs can effectively deliver computational thinking education at scale. HKUST offers MOOCs on Java programming, app development, and engineering design that teach computational thinking concepts. Learning analytics provide insights into how students learn from MOOCs.
IRJET- Prediction of Autism Spectrum Disorder using Deep Learning: A SurveyIRJET Journal
This document summarizes research on using deep learning techniques to predict Autism Spectrum Disorder (ASD). It first provides background on ASD, describing it as a developmental disorder that impairs social communication and interaction. It then reviews related work applying machine learning to ASD prediction and diagnosis. The proposed system would use a deep learning model trained on an AQ10 dataset of behavioral questions to predict ASD severity. It would employ a multi-layer feedforward neural network optimized with the Adam gradient descent algorithm. The goal is to develop an accurate, fast and low-cost mobile application to help diagnose ASD at an early stage.
This is the talk given at the Faculty of Information Technology, Monash University on 19/08/2020. It covers our recent research on the topics of learning to reason, including dual-process theory, visual reasoning and neural memories.
This document provides an overview and requirements for the Stat project, an open source machine learning framework for text analysis. It describes the background, motivation, scope, and stakeholders of the project. Key requirements for the framework include being simplified, reusable, and providing built-in capabilities to naturally support text representation and processing tasks.
This document is an introduction to a textbook about logic circuits and logic design using Verilog. It begins with a preface describing the need for a textbook that teaches digital circuits from a bottom-up perspective by first covering fundamental hardware concepts before introducing hardware description languages. The preface outlines how the book is organized to progressively build knowledge and introduce topics only after sufficient prerequisites. It also describes how the book can be used to support both single and multi-course sequences for teaching digital logic and design.
IRJET - Automatic Lip Reading: Classification of Words and Phrases using Conv...IRJET Journal
This document presents research on developing an automatic lip reading system using convolutional neural networks. The system takes in video frames of a speaker's face without audio and classifies the words or phrases being spoken. The researchers preprocessed the data by detecting faces in video frames and cropping them. They then trained a CNN model on concatenated frames. Their model achieved 80.44% accuracy on the test set in classifying 10 words and 10 phrases from 17 speakers. The researchers concluded the model could be improved by addressing overfitting to unseen speakers with a larger dataset and regularization techniques.
IRJET- Machine Learning V/S Deep LearningIRJET Journal
Machine learning and deep learning are techniques used to implement artificial intelligence. Machine learning uses algorithms to help machines learn from data to make predictions or decisions without being explicitly programmed, while deep learning is a type of machine learning that is inspired by the human brain. The key differences are that machine learning works with moderate amounts of sorted data and produces results more quickly, while deep learning requires large amounts of data, more complex neural networks, and longer training times but can produce more accurate results. Both techniques will continue to be important for developing artificial intelligence and solving real-world problems in fields like computer vision and bioinformatics.
TL;DR: This tutorial was delivered at KDD 2021. Here we review recent developments to extend the capacity of neural networks to “learning to reason” from data, where the task is to determine if the data entails a conclusion.
The rise of big data and big compute has brought modern neural networks to many walks of digital life, thanks to the relative ease of construction of large models that scale to the real world. Current successes of Transformers and self-supervised pretraining on massive data have led some to believe that deep neural networks will be able to do almost everything whenever we have data and computational resources. However, this might not be the case. While neural networks are fast to exploit surface statistics, they fail miserably to generalize to novel combinations. Current neural networks do not perform deliberate reasoning – the capacity to deliberately deduce new knowledge out of the contextualized data. This tutorial reviews recent developments to extend the capacity of neural networks to “learning to reason” from data, where the task is to determine if the data entails a conclusion. This capacity opens up new ways to generate insights from data through arbitrary querying using natural languages without the need of predefining a narrow set of tasks.
Constructed model for micro-content recognition in lip reading based deep lea...journalBEEI
The document describes a proposed model for micro-content recognition in lip reading using deep learning. The model takes micro-contents (the English alphabet) as input from video and recognizes them using a convolutional neural network (CNN). The CNN performs feature extraction and recognition. The model was tested on a dataset containing videos of 11 people pronouncing letters and achieved a high recognition rate of 98%.
The document summarizes a student's project report on developing a tool to calculate indicators that characterize spatial networks. It includes:
1) An overview of the project which involved designing a program to calculate indicators for spatial networks based on a research paper and feedback from supervisors.
2) Details on the motivation, proposed structure, selected indicators to implement (degree, displacement, route factor, binary tree, Strahler index, asymmetry factor) and development of the program code.
3) How the program takes spatial network graph data and text files as input, calculates the selected indicators, and outputs the results to text files after processing and debugging.
This document is a resume for Dr. Parkavi.A that provides information over 3 sentences:
Dr. Parkavi.A is seeking a challenging career that utilizes her engineering knowledge and delivers expected commitments to society, with teaching experience at various institutions and expertise in areas like data analytics, programming languages, databases, and operating systems. She holds a Ph.D in computer science and engineering and has published papers in various international conferences and book chapters on topics related to education technology and data mining. She has also led academic projects focused on areas such as compiler design, networking applications, and maps of cities.
Image classification using convolutional neural networkKIRAN R
For separating the images from a large collection of images or from a large dataset this classifier can be used, Here deep neural network is used for training and classifying the images. The convolutional neural network is the most suitable algorithm for classifier images. This Classifier is a machine learning model, so the more you train it the more will be the accuracy.
This resume summarizes an individual with 12 years of experience in teaching, research, and patents. Some of the key details include:
- He has filed one patent that is currently awaiting examination and is working on a second patent. His education includes an MCA degree and pursuing a PhD.
- His research experience includes 18 published papers, guiding 4 master's students, and leading innovative projects. One of his patents is in an awaiting examination stage.
- His professional experience includes over 12 years as an Associate Professor teaching courses and coordinating online exams for over 500,000 students annually.
- He has received several awards for his research and papers, including two best paper awards and best reviewer awards from international journals
IRJET- Sentiment Analysis to Segregate Attributes using Machine Learning Tech...IRJET Journal
This document discusses sentiment analysis techniques using machine learning. It provides an overview of various supervised and unsupervised machine learning algorithms that can be used for sentiment analysis, including Naive Bayes, SVM, neural networks, decision trees, and BERT. The document also describes the system architecture of a proposed sentiment analysis system that would use a BERT model to identify and classify sentiments in text data as positive, negative, or neutral after preprocessing the data. The system aims to improve sentiment analysis efficiency by taking a holistic approach to attribute identification and classification.
Robotics-Based Learning in the Context of Computer ProgrammingJacob Storer
This document is a project report for research into whether robotics-based learning or simulation-based learning is more effective for teaching programming. It describes the objectives of developing tutorials for both an Arduino robot and visual basic simulation. Programming tasks for moving forwards/backwards and along shapes were developed. Tutorials and programs were implemented to teach these tasks. Surveys were given to test groups after using each method to collect data on their effectiveness for comparison. While results were mixed, all indicated learning was improved with a teacher. Due to the small sample size, no conclusive answer could be provided.
This document provides an overview of a tutorial on machine learning and reasoning for drug discovery.
The tutorial covers several topics: molecular representation and property prediction, including fingerprints, string representations, graph representations, and self-supervised learning; protein representation and protein-drug binding; molecular optimization and generation; and knowledge graph reasoning and drug synthesis.
The introduction discusses the drug discovery pipeline and how machine learning can help with various tasks such as molecular property prediction, target identification, and reaction planning. Neural networks are well-suited for drug discovery due to their expressiveness, learnability, generalizability, and ability to handle large amounts of data.
This document contains the resume of Shubham Vijay Vargiy, who is currently pursuing a B. Tech in Electronics and Communication Engineering at Shri Mata Vaishno Devi University in Jammu and Kashmir, India. Some of his qualifications include graduating high school with 83.38% and 97% in physics, chemistry, and mathematics. His current CGPA is 7.36. He has worked on several projects related to programming and embedded systems and has attended conferences to present papers on his work. He is seeking opportunities in programming and software development where he can apply his skills and contribute to an organization.
PWL Seattle #23 - A Few Useful Things to Know About Machine LearningTristan Penman
A mini-talk prepared for Papers We Love @ Seattle, September 2016, about the paper "A Few Useful Things to Know About Machine Learning". At just over eight pages, this paper by Pedro Domingos delivers an approachable summary of some of the folk knowledge often missed by those new to the field of Machine Learning.
This talk was intended as a high level talk, avoiding the math-heavy approach typical of Machine Learning discussions. The slides include references to other resources that may be useful to students and practitioners alike.
A Few Useful Things to Know about Machine Learningnep_test_account
1. Machine learning algorithms can automatically learn programs from data by generalizing from examples, which is often more feasible and cost-effective than manual programming. However, developing successful machine learning applications requires expertise beyond what textbooks provide.
2. Machine learning consists of three main components: representation, evaluation, and optimization. Choosing appropriate combinations of these components is key to building effective learners.
3. The goal of machine learning is generalization to new examples, not just accuracy on the training data. Strict separation of training and test data is necessary to evaluate generalization performance.
A Survey on Using Artificial Intelligence Techniques in the Software Developm...IJERA Editor
Software engineering and artificial intelligence are the two important fields of the computer science. Artificial Intelligence is about making machines intelligent, while Software engineering is knowledge –intensive activity, requiring extensive knowledge of the application domain and of the target software itself. This study intends to review the techniques developed in artificial intelligence from the standpoint of their application in software engineering. The goal of this research paper is to give some guidelines to use the artificial intelligence techniques that can be applied in solving problems associated with software engineering processes. The aim of this paper is to find out the exact AI technique is likely to be fruitful for particular software development process
Keynote 1: Teaching and Learning Computational Thinking at ScaleCITE
Computational thinking involves problem formulation, pattern recognition, abstraction, and algorithm design. It is an important 21st century skill and countries are incorporating it into curricula. MOOCs can effectively deliver computational thinking education at scale. HKUST offers MOOCs on Java programming, app development, and engineering design that teach computational thinking concepts. Learning analytics provide insights into how students learn from MOOCs.
IRJET- Prediction of Autism Spectrum Disorder using Deep Learning: A SurveyIRJET Journal
This document summarizes research on using deep learning techniques to predict Autism Spectrum Disorder (ASD). It first provides background on ASD, describing it as a developmental disorder that impairs social communication and interaction. It then reviews related work applying machine learning to ASD prediction and diagnosis. The proposed system would use a deep learning model trained on an AQ10 dataset of behavioral questions to predict ASD severity. It would employ a multi-layer feedforward neural network optimized with the Adam gradient descent algorithm. The goal is to develop an accurate, fast and low-cost mobile application to help diagnose ASD at an early stage.
This is the talk given at the Faculty of Information Technology, Monash University on 19/08/2020. It covers our recent research on the topics of learning to reason, including dual-process theory, visual reasoning and neural memories.
This document provides an overview and requirements for the Stat project, an open source machine learning framework for text analysis. It describes the background, motivation, scope, and stakeholders of the project. Key requirements for the framework include being simplified, reusable, and providing built-in capabilities to naturally support text representation and processing tasks.
This document is an introduction to a textbook about logic circuits and logic design using Verilog. It begins with a preface describing the need for a textbook that teaches digital circuits from a bottom-up perspective by first covering fundamental hardware concepts before introducing hardware description languages. The preface outlines how the book is organized to progressively build knowledge and introduce topics only after sufficient prerequisites. It also describes how the book can be used to support both single and multi-course sequences for teaching digital logic and design.
This document summarizes a senior capstone project to create mobile applications for chapters of an electrical engineering probability course. A team of three students each created an app for one chapter, with sections on theory, problems, and simulations. While most sections were completed, the simulation for chapter 3 was not finished due to difficulties with the required programming language. The apps were tested by previous students and received positive feedback. The project helped students learn mobile app development and provided a new way for probability concepts to be taught, with the aim of improving student performance and retention in the course.
The STAT technical report provides an introduction to the Stat project, which aims to develop an open source machine learning framework in Java called Stat for text analysis. Stat focuses on facilitating common textual data analysis tasks for researchers and engineers. The report outlines the background, motivation, scope, and stakeholders of the project. It also describes an initial survey conducted to understand potential users and their needs in order to prioritize the framework's design and implementation. Finally, the report analyzes two existing toolkits, Weka and MinorThird, and discusses their strengths and limitations for text analysis tasks.
Crocodile Physics is a simulation software that allows students to model and analyze systems in electrical circuits, mechanics, and optics. It has an intuitive interface that allows students to quickly design systems and observe simulations. The software can operate in both simulation and analysis modes. Teachers can use it as both a hands-on tool for students and to supplement classroom instruction in the sciences and mathematics.
The document describes a proposed web application for automating project management tasks at an engineering institute. The application would allow students to form groups, get project approvals, submit work, and receive feedback and evaluations. It consists of two modules - one for online project work and another to evaluate student and project progress. The goal is to streamline project activities and provide a centralized platform for communication between students and guides.
This document provides an introduction and overview of the Stat project, which aims to create an open source machine learning framework in Java for text analysis. The Stat framework is designed to be simple, extensible, and performant. It aims to simplify common text analysis tasks for researchers and engineers by providing reusable tools and wrappers for existing NLP and machine learning packages. The document outlines the goals, scope, stakeholders and provides an initial requirements analysis for the Stat framework.
Teaching Machine Learning to Design Studentsbutest
The document discusses a course taught at Eindhoven University of Technology that teaches machine learning to industrial design students using an embodied intelligence approach. The course uses Lego Mindstorms kits to teach reinforcement learning and supervised learning concepts. Students build machines with sensors and actuators that learn behaviors through interaction with the real world. This hands-on approach helps design students without strong technical backgrounds better understand machine learning concepts compared to traditional abstract teaching methods. The course structure combines initial theory lessons with practical projects, and evaluations found the embodied approach motivated and helped all students learn the material.
Here is the sequence diagram for the URL shortening process:
User -> UI: Enter username and password
UI -> Authentication Service: Authenticate user (username, password)
Authentication Service -> UI: Authentication response (success/failure)
If authentication success:
UI -> User: Welcome page
User -> UI: Enter long URL to shorten
UI -> URL Shortening Service: Shorten URL (longURL)
URL Shortening Service -> UI: Short URL
UI -> User: Short URL
User -> UI: Click on short URL
UI -> URL Redirect Service: Redirect request (shortURL)
URL Redirect Service -> UI: Redirect response (longURL)
UI -> User
Text Summarization and Conversion of Speech to TextIRJET Journal
This document discusses text summarization and speech to text conversion using deep learning algorithms. It describes how recurrent neural networks can be used for text summarization by identifying key information and semantic meaning from text. Speech recognition uses similar deep learning methods to convert spoken audio to text. The document also provides an overview of the text summarization process, including segmentation, normalization, feature extraction, and modeling steps. It concludes that these models can generate summarized text from extensive documents and meetings.
This document discusses tools for teaching undergraduate computational physics. It begins by explaining how computation has become integral to science. It then discusses how computational physics has been incorporated into Ethiopian university curriculums since 2003. While now required, methodologies and programming languages used vary. The document considers options for languages like Java, Python, and pseudocode. It outlines course content options and factors in language selection. The rest of the document demonstrates uses of computation in physics like simulation and visualization, and explains why the author prefers Java for its platform independence, graphics libraries, and supported library. It provides instructions for installing Java, configuring a development environment, and running sample codes to teach computational physics.
Computational Aptitude of Handheld Calculatormathsmasters
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.
Improved Presentation and Facade Layer Operations for Software Engineering Pr...Dr. Amarjeet Singh
Nowadays, one of the most challenging situations for
software developers is the presence of a mismatch between
relational database systems and programming codes. In the
literature, this problem is defined as "impedance mismatch".
This study is to develop a framework built on innovations
based on the existing Object Relational Mapping technique to
solve these problems. In the study, users can perform
operations for three different database systems such as
MsSQL, MySql and Oracle. In addition, these operations can
be done within the framework of C# and Java programming
languages. In this framework, while the developers can define
database tables in the interface automatically, they can create
relations between tables by defining a foreign key. When the
system performs these operations, it creates tables, views, and
stored procedures automatically. In addition, entity classes in
C# and Java for tables and views, and operation classes for
stored procedures are created automatically. The summary of
the transactions can be taken as pdf file by the framework. In
addition, the project can automatically create Windows
Communication Foundation classes to facilitate the handling
of database elements created and the interfacing operations, as
well. This framework, which supports distributed systems, can
be downloaded at this link.
Phase 2 - Task 1
Task Type:
Discussion Board
Deliverable Length:
400–600 words + 2 responses (100–200 words each)
Points Possible:
75
Due Date:
1/18/2015 11:59:59 PM
Primary Discussion Response is due by Wednesday (11:59:59pm Central), Peer Responses are due by Sunday (11:59:59pm Central).
Primary Task Response: Within the Discussion Board area, write 400–600 words that respond to the following questions with your thoughts, ideas, and comments. This will be the foundation for future discussions with your classmates. Be substantive and clear, and use examples to reinforce your ideas.
Library Research Assignment
Translating detailed requirements into a design is the next very important step. An integrated set of computer-aided software engineering (CASE) tools can be very useful in modeling and documenting a software application or system.
Investigate the library and Internet for information on at least 5 CASE tools such as unified modeling language (UML), functional decomposition diagrams, data flow diagrams, object diagrams, entity-relationship (E-R) diagrams, class diagrams, and structure charts.
· Compare and contrast 5 of the CASE modeling tools by giving a brief description, including strengths and weaknesses.
· Based on your research, which subset or individual CASE modeling tool or tools do you plan to use to develop the design for your project in this class, and why?
Responses to Other Students: Respond to at least 2 of your fellow classmates with a reply of 100–200 words about their Primary Task Response regarding items you found to be compelling and enlightening. To help you with your discussion, please consider the following questions:
· What did you learn from your classmate's posting?
· What additional questions do you have after reading the posting?
· What clarification do you need regarding the posting?
· What differences or similarities do you see between your posting and other classmates' postings?
For assistance with your assignment, please use your text, Web resources, and all course materials.
Course Materials
Phase 2 - Task 2
Task Type:
Individual Project
Deliverable Length:
2–3 new pages
Points Possible:
100
Due Date:
1/19/2015 11:59:59 PM
Weekly tasks or assignments (Individual or Group Projects) will be due by Monday, and late submissions will be assigned a late penalty in accordance with the late penalty policy found in the syllabus. NOTE: All submission posting times are based on midnight Central Time.
At this point, you are ready to execute the next phase in system development life cycle (SDLC), which is the design phase. Exploiting the research that you have performed in this week’s Discussion Board on the set of modeling tools, document the design for the application project that you selected.
Assignment
For this assignment, you will use Visio Software Application to develop the design employing the following computer-aided software engineering (CASE) modeling tools:
· Use case
· Functional decomposition diagr.
Redes de sensores sem fio autonômicas: abordagens, aplicações e desafiosPET Computação
Este curso tem como principal objetivo apresentar aos ouvintes conceitos sobre redes de sensores sem fio (RSSF), protocolos de comunicação para RSSF e conceitos de computação autonômica. Além disso, aplicações focadas nas áreas de monitoramento ambiental, agricultura de precisão, segurança e defesa também serão apresentados.
Fundamentals of data structures ellis horowitz & sartaj sahniHitesh Wagle
This document is the preface to a textbook on data structures. It provides background on how the field of data structures has evolved from list processing languages to an emphasis on algorithm design and analysis. It describes the goals of the textbook as teaching specification of data structures separate from implementation, rigorous analysis of algorithms, and covering topics like sorting and files. It provides examples of how the material could be covered in a one or two semester course.
This document provides module descriptions for the Higher Certificate in Information Systems (Internet Development) program offered by CTI Education Group in South Africa. The modules cover topics like computer literacy, programming logic, program design, software engineering, database design, database management, web design, and creating web pages. The modules introduce fundamental concepts and teach practical skills for areas like word processing, spreadsheets, databases, presentations, programming logic, pseudocode, systems analysis, UML modeling, relational databases, and web development using technologies like HTML, CSS, JavaScript, and Flash.
This document provides an overview and introduction to the book "Software Engineering: A Hands-On Approach" by Roger Y. Lee. The book aims to teach key principles of software engineering through hands-on learning and a project-based approach. It uses common tools like the Unified Modeling Language and object-oriented design patterns. The book is divided into two parts - the first introduces software engineering concepts, and the second guides readers through a software project from requirements to implementation and testing. The goal is to help students bridge the gap between academic learning and real-world practice of software engineering.
1. Four students presented their finalized project title "Education Organizational Governance System" to their guide Dr. Ashish Sharma at GH Raisoni College of Engineering, Nagpur, India in winter 2022.
2. The project aims to develop a simpler method for administering the field of education through e-governance by making the system more user-friendly, time-saving, and cost-saving.
3. The presentation introduced the project title, described the objectives to connect students, mentors, industry and college through the system, and examined technologies like ASP.net and MYSQL that would be used to implement the system.
The document summarizes a workshop on Service-Oriented Programming (SOP). SOP is a new programming methodology that allows developing software applications by connecting and composing existing services, facilitating software reuse. The workshop is divided into two parts: the first part describes SOP concepts and motivation, and the second introduces teaching materials through a demonstration of SOP techniques. The qualifications of the three presenters are also provided, including their research interests and experience in computer science education.
Similar to Development of Computer Aided Learning Software for Use in Electric Circuit Analysis (20)
11(7) 2020 ITJEMAST's published research articlesdrboon
This document summarizes a research study that examined the relationship between positivity, positive affect, negative affect, and perceived stress among cardiac patients. The study hypothesized that perceived stress would mediate the relationship between positivity and positive/negative affect. Researchers surveyed 519 cardiac patients, assessing positivity, perceived stress, and positive/negative affect. The results found that perceived stress mediated the relationship between positive affect and positivity, as well as between negative affect and positivity. Specifically, positivity was negatively correlated with negative affect and perceived stress, while perceived stress was positively correlated with negative affect. The findings suggest that reducing stress and increasing positive emotions can help reduce negative feelings in cardiac patients.
11(4) 2020 ITJEMAST Multidisciplinary Research Articlesdrboon
Research papers 2020 Behavioral finance; Personality traits; Behavioral factors; Overconfidence bias; Locus of control; Decision-making; Biased behavior Carbon (CO2) emissions; Economic Growth; Energy consumption; Trade; ARDL Approach; Granger Causality; Energy use Pedestrian start-up time; Street crosswalk, Pedestrian traffic signals; Pedestrians traffic lights; zebra crossings; Intersection crossings Service Attributes; Relationship quality; Relationship outcomes; Banking services; Electronic Customer Relationship Management; Virtual relationships; eBanking; eCRM College town landscape; College town character; Campus community; Urban identity; College town space; Sense of a place; Public Space; University gardens; Cultural identity; Campus identity; Businesses in college towns Emotional quotient; Self-emotional appraisal; Workplace Advice Network (WAN) Centrality; Service Sector Organizations; Sociometric matrix; Interconnectivity of nodes
11(3) 2020 ITJEMAST Multidisciplinary Research Articles drboon
Non-destructive testing method Heat loss Thermal conductivity Specific heat Know-how Psychological contract breach Employees' Workplace behaviour Workplace spirituality Human resource management (HRM) Power sector Positive classroom Male teachers Classroom management system Public primary schools Private primary school Positive motivation students Quality primary education Grout rheology Construction workings High-precision lining Tunneling complex Cement slurry Reinforcement solutions Smart building systems Green architecture Green roof Green design Sustainable environmental architecture Smart energy management Architecture technology Neo-Functionalism Trade integration CPEC agreement Economic integration Regional cooperation Pak-China relations Pak-Iran relations Central Asia Republics Sino-Pakistan Agreement
11(2)2020 International Transaction Journal of Engineering, Management, & Ap...drboon
Multidisciplinary Management, Journalism and Mass Communication Science (Information and Media Sciences), Political Sciences (International Affairs), Global Studies), Animal Sciences, Feeding Technology, Healthcare Management.
V8(3) 2017:: International Transaction Journal of Engineering, Management, & ...drboon
Research articles published in V8(3) 2017:: International Transaction Journal of Engineering, Management, & Applied Sciences & Technologies ==>
Awareness of Passive Design on Apartment Façade Designs in Putrajaya, Malaysia
127
Comparative Analysis of Low-Cost Housing Policies in Malaysia and Nigeria
139
A Study on Kevin Lynch’s Urban Design Elements: Precinct 9 East Putrajaya
153
Investigating Urban Design Elements of Bandar Baru Sentul, Kuala Lumpur
169
A Study on Sharing Home Ownership Schemes in Malaysia
183
The Impact of Window to Wall Ratio (WWR) and Glazing Type on Energy Consumption in Air-Conditioned Office Buildings
197
Competitiveness Factors of Thai Construction Industry within the AEC Context: A Qualitative Approach
209
Application of Confirmatory Factor Analysis in Government Construction Procurement Problems in Thailand
221
In 3 sentences:
The document discusses the key elements to consider when designing streets for livable cities, including pedestrians, vehicles, parking, and transportation options. It emphasizes the need for a comprehensive approach that considers all users and aspects, such as transportation, safety, the environment, and the economy. The goal is to create streets that are social spaces where people can easily and safely walk, bike, access transit, and spend time, rather than only focus on traffic flow.
Impact of Building Envelope Modification on Energy Performance of High-Rise A...drboon
This document summarizes a research study that investigated the impact of building envelope modifications on the energy performance of high-rise apartments in Kuala Lumpur, Malaysia. Three high-rise apartment buildings were modeled using EnergyPlus software to analyze the effects of thermal insulation and glazing type on potential energy savings. The study found that integrating passive envelope design measures like improved insulation and higher performing glazing could help reduce energy consumption and peak cooling loads in the apartments. Modifying elements of the building envelope, especially the walls and windows, may enable significant energy savings potential for high-rise residential buildings in hot and humid climates.
Enhancement of Space Environment Via Healing Gardendrboon
Green nature, sunlight and fresh air have been known as important component of healing in healthcare facilities. This paper presents the finding of an exploratory study on healing garden elements in healthcare facilities. The purpose of the paper is to find the elements of healing gardens and its healing factors in the existing garden design. In conducting this research study, site observation and informal interview at selected healthcare facilities have been performed. The study reveals the elements of existing garden design, the interactivity and the end users expectation on a garden. The finding shows that lacking some of the elements of garden design lead to less user friendliness and interactivity in the garden. It also shows that the visibility, accessibility, quietness and comfortable condition in the garden give impact to the utilization of the garden.
Design of Quadruped Walking Robot with Spherical Shelldrboon
We propose a new quadruped walking robot with a spherical shell, called "QRoSS." QRoSS is a transformable robot that can store its legs in the spherical shell. The shell not only absorbs external forces from all directions, but also improves mobile performance because of its round shape. In rescue operations at a disaster site, carrying robots into a site is dangerous for operators because doing so may result in a second accident. If QRoSS is used, instead of carrying robots in, they are thrown in, making the operation safe and easy. This paper reports details of the design concept and development of the prototype model. Basic experiments were conducted to verify performance, which includes landing, rising and walking through a series of movements.
Motion Analysis of Pitch Rotation Mechanism for Posture Control of Butterfly-...drboon
We developed a small flapping robot on the basis of movements made by a butterfly with a low flapping frequency of approximately 10 Hz, a few degrees of freedom of the wings, and a large flapping angle. In this study, we clarify the pitch rotation mechanism that is used to control its posture during takeoff for different initial pitch and flapping angles by the experiments of both manufactured robots and simulation models. The results indicate that the pitch angle can be controlled by altering the initial pitch angle at takeoff and the flapping angles. Furthermore, it is suggested that the initial pitch angle generates a proportional increase in the pitch angle during takeoff, and that certain flapping angles are conducive to increasing the tendency for pitch angle transition. Thus, it is shown that the direction of the flight led by periodic changing in the pitch angle can be controlled by optimizing control parameters such as initial pitch and flapping angles.
Analysis of Roll Rotation Mechanism of a Butterfly for Development of a Small...drboon
1) The document analyzes the roll rotation mechanism of a butterfly through computational fluid dynamics simulations using boundary conditions from high-speed camera footage.
2) It finds that during typical pitch rotation flight, differential pressure concentrates at the tip of the forewings, producing roughly matched reaction forces on the left and right wings.
3) During roll rotation flight, differential pressure distributes across the entire wings, with the right reaction force twice as great as the left during the initial downstroke, leading to a large change in roll angle.
Effect of Oryzalin on Growth of Anthurium andraeanum In Vitrodrboon
Apical shoots and lateral buds of Anthurium andraeanum about 0.5 cm grew very well when cultured on MS medium supplemented with NAA, kinetin, sucrose and gelrite. When brought young plantlets (the same sized) of A. andraeanum soaked in various concentrations of oryzalin with different duration times. The A. andraeanum plantlets were subcultured into the same medium every 4 weeks for 3 times. It was found that 5.0 mg/l oryzalin with 24 and 72 hours gave the best average number of leaves per bunch, plant height and diameter of bunch. These parameters were reverse proportion, when increased concentration of oryzalin, the growth rate in each parameter was decreased with thick and pale green leaves.
Role of 2,4-D on Callus Induction and Shoot Formation to Increase Number of S...drboon
Stem node of Miniature Rose with axillary bud were used as explants. These explants cultured on MS medium supplemented with different concentrations of 2,4-D. It was found that MS medium supplemented with 0.5 mg/l 2,4-D gave the highest number of green callus. The callus cultured on MS medium supplemented with different combinations of NAA and BA to form new shoot and root. From the result, we are able to find the highest number of young shoots that were induced from callus when cultured callus on MS medium supplemented with NAA and BA. When subcultured all new shoots with the same size to MS medium supplemented with different concentrations of NAA and BA, and 2,4- D for six weeks. The result was significant difference (P≤0.5) when compared the average height of plant and percentage of root formation, but their duration time for flowering were not significant different.
Seismic Capacity Comparisons of Reinforced Concrete Buildings Between Standar...drboon
Earthquakes are cause of serious damage through the building. Therefore, moment resistant frame buildings are widely used as lateral resisting system. Generally three types of moment resisting frames are designed namely Special ductile frames (SDF), Intermediate ductile frames (IDF) and Gravity load designed (GLD) frames, each of which has a certain level of ductility. Comparative studies on the seismic performance of three different ductility of building are performed in this study. The analytical models are considered about failure mode of column (i.e. shear failure, flexural to shear failure and flexural failure); beam-column joint connection, infill wall and flexural foundation. Concepts of incremental dynamic analysis are practiced to assess the required data for performance based evaluations. This study found that the lateral load capacity of GLD, IDF, and SDF building was 19.25, 27.87, and 25.92 %W respectively. The average response spectrum at the collapse state for GLD, IDF, and SDF are 0.75 g, 1.19 g, and 1.33 g, respectively. The results show that SDF is more ductile than IDF and the initial strength of SDF is close to IDF. The results indicate that all of frames are able to resistant a design earthquake.
ITJEMAST5(2): Latest Research from International Transaction Journal of Engin...drboon
An After-Stay Satisfaction Survey of Residents Living in Prefabricated Concrete Structures in Thailand
Hydrothermal Assisted Microwave Pyrolysis of Water Hyacinth for Electrochemical Capacitors Electrodes
Group Technology Paves the Road for Automation
Effect of Laser Priming on accumulation of Free Proline in Spring Durum Wheat (Triticum turgidum L.) under Salinity Stress
Livable Public Open Space for Citizen’s Quality of Life in Medan, Indonesia
ITJEMAST5(1): Latest Research from International Transaction Journal of Engin...drboon
Latest Research from International Transaction Journal of Engineering, Management, & Applied Sciences & Technologies ITJEMAST5(1):
Effects of Calcination Treatment of Diatomite on Dimethyl Ether Synthesis from Methanol
Effect of Blend Ratio on Cure Characteristics, Mechanical Properties, and Aging Resistance of Silica-filled ENR/SBR Blends
An Efficient Formulation of Off-line Model Predictive Control for Nonlinear Systems Using Polyhedral Invariant Sets
Effect of Modeling Parameters on System Hydrodynamics of Air Reactor in Chemical Looping Combustion Using CFD Simulation
Flow Behavior of Geldart A and Geldart C Particles in a Co-current Downflow Circulating Fluidized Bed Reactor
Optimization of Enzymatic Clarification from Corncob
Synthesis of Alkali Metal/CaO Sorbent for CO2 Capture at Low Temperature
Effect of Exchangeable Cations on Bentonite Swelling Characteristics of Geosy...drboon
1) The study characterized the swelling behavior of bentonite in geosynthetic clay liners (GCLs) using X-ray diffraction and scanning electron microscopy.
2) The X-ray diffraction results showed that bentonite swelling decreased with increasing valence of exchangeable cations and increasing concentration of permeant solutions. Bentonite swelling was highest with deionized water and lowest with calcium chloride solutions.
3) Scanning electron microscopy images showed that bentonite has a flake-like structure when air-dried but becomes more porous and fluffy after permeation. The porous structure decreased with increasing concentration of calcium chloride solutions.
OpenID AuthZEN Interop Read Out - AuthorizationDavid Brossard
During Identiverse 2024 and EIC 2024, members of the OpenID AuthZEN WG got together and demoed their authorization endpoints conforming to the AuthZEN API
Programming Foundation Models with DSPy - Meetup SlidesZilliz
Prompting language models is hard, while programming language models is easy. In this talk, I will discuss the state-of-the-art framework DSPy for programming foundation models with its powerful optimizers and runtime constraint system.
Building Production Ready Search Pipelines with Spark and MilvusZilliz
Spark is the widely used ETL tool for processing, indexing and ingesting data to serving stack for search. Milvus is the production-ready open-source vector database. In this talk we will show how to use Spark to process unstructured data to extract vector representations, and push the vectors to Milvus vector database for search serving.
Unlock the Future of Search with MongoDB Atlas_ Vector Search Unleashed.pdfMalak Abu Hammad
Discover how MongoDB Atlas and vector search technology can revolutionize your application's search capabilities. This comprehensive presentation covers:
* What is Vector Search?
* Importance and benefits of vector search
* Practical use cases across various industries
* Step-by-step implementation guide
* Live demos with code snippets
* Enhancing LLM capabilities with vector search
* Best practices and optimization strategies
Perfect for developers, AI enthusiasts, and tech leaders. Learn how to leverage MongoDB Atlas to deliver highly relevant, context-aware search results, transforming your data retrieval process. Stay ahead in tech innovation and maximize the potential of your applications.
#MongoDB #VectorSearch #AI #SemanticSearch #TechInnovation #DataScience #LLM #MachineLearning #SearchTechnology
Driving Business Innovation: Latest Generative AI Advancements & Success StorySafe Software
Are you ready to revolutionize how you handle data? Join us for a webinar where we’ll bring you up to speed with the latest advancements in Generative AI technology and discover how leveraging FME with tools from giants like Google Gemini, Amazon, and Microsoft OpenAI can supercharge your workflow efficiency.
During the hour, we’ll take you through:
Guest Speaker Segment with Hannah Barrington: Dive into the world of dynamic real estate marketing with Hannah, the Marketing Manager at Workspace Group. Hear firsthand how their team generates engaging descriptions for thousands of office units by integrating diverse data sources—from PDF floorplans to web pages—using FME transformers, like OpenAIVisionConnector and AnthropicVisionConnector. This use case will show you how GenAI can streamline content creation for marketing across the board.
Ollama Use Case: Learn how Scenario Specialist Dmitri Bagh has utilized Ollama within FME to input data, create custom models, and enhance security protocols. This segment will include demos to illustrate the full capabilities of FME in AI-driven processes.
Custom AI Models: Discover how to leverage FME to build personalized AI models using your data. Whether it’s populating a model with local data for added security or integrating public AI tools, find out how FME facilitates a versatile and secure approach to AI.
We’ll wrap up with a live Q&A session where you can engage with our experts on your specific use cases, and learn more about optimizing your data workflows with AI.
This webinar is ideal for professionals seeking to harness the power of AI within their data management systems while ensuring high levels of customization and security. Whether you're a novice or an expert, gain actionable insights and strategies to elevate your data processes. Join us to see how FME and AI can revolutionize how you work with data!
Taking AI to the Next Level in Manufacturing.pdfssuserfac0301
Read Taking AI to the Next Level in Manufacturing to gain insights on AI adoption in the manufacturing industry, such as:
1. How quickly AI is being implemented in manufacturing.
2. Which barriers stand in the way of AI adoption.
3. How data quality and governance form the backbone of AI.
4. Organizational processes and structures that may inhibit effective AI adoption.
6. Ideas and approaches to help build your organization's AI strategy.
AI-Powered Food Delivery Transforming App Development in Saudi Arabia.pdfTechgropse Pvt.Ltd.
In this blog post, we'll delve into the intersection of AI and app development in Saudi Arabia, focusing on the food delivery sector. We'll explore how AI is revolutionizing the way Saudi consumers order food, how restaurants manage their operations, and how delivery partners navigate the bustling streets of cities like Riyadh, Jeddah, and Dammam. Through real-world case studies, we'll showcase how leading Saudi food delivery apps are leveraging AI to redefine convenience, personalization, and efficiency.
Infrastructure Challenges in Scaling RAG with Custom AI modelsZilliz
Building Retrieval-Augmented Generation (RAG) systems with open-source and custom AI models is a complex task. This talk explores the challenges in productionizing RAG systems, including retrieval performance, response synthesis, and evaluation. We’ll discuss how to leverage open-source models like text embeddings, language models, and custom fine-tuned models to enhance RAG performance. Additionally, we’ll cover how BentoML can help orchestrate and scale these AI components efficiently, ensuring seamless deployment and management of RAG systems in the cloud.
How to Get CNIC Information System with Paksim Ga.pptxdanishmna97
Pakdata Cf is a groundbreaking system designed to streamline and facilitate access to CNIC information. This innovative platform leverages advanced technology to provide users with efficient and secure access to their CNIC details.
Full-RAG: A modern architecture for hyper-personalizationZilliz
Mike Del Balso, CEO & Co-Founder at Tecton, presents "Full RAG," a novel approach to AI recommendation systems, aiming to push beyond the limitations of traditional models through a deep integration of contextual insights and real-time data, leveraging the Retrieval-Augmented Generation architecture. This talk will outline Full RAG's potential to significantly enhance personalization, address engineering challenges such as data management and model training, and introduce data enrichment with reranking as a key solution. Attendees will gain crucial insights into the importance of hyperpersonalization in AI, the capabilities of Full RAG for advanced personalization, and strategies for managing complex data integrations for deploying cutting-edge AI solutions.
CAKE: Sharing Slices of Confidential Data on BlockchainClaudio Di Ciccio
Presented at the CAiSE 2024 Forum, Intelligent Information Systems, June 6th, Limassol, Cyprus.
Synopsis: Cooperative information systems typically involve various entities in a collaborative process within a distributed environment. Blockchain technology offers a mechanism for automating such processes, even when only partial trust exists among participants. The data stored on the blockchain is replicated across all nodes in the network, ensuring accessibility to all participants. While this aspect facilitates traceability, integrity, and persistence, it poses challenges for adopting public blockchains in enterprise settings due to confidentiality issues. In this paper, we present a software tool named Control Access via Key Encryption (CAKE), designed to ensure data confidentiality in scenarios involving public blockchains. After outlining its core components and functionalities, we showcase the application of CAKE in the context of a real-world cyber-security project within the logistics domain.
Paper: https://doi.org/10.1007/978-3-031-61000-4_16
Ivanti’s Patch Tuesday breakdown goes beyond patching your applications and brings you the intelligence and guidance needed to prioritize where to focus your attention first. Catch early analysis on our Ivanti blog, then join industry expert Chris Goettl for the Patch Tuesday Webinar Event. There we’ll do a deep dive into each of the bulletins and give guidance on the risks associated with the newly-identified vulnerabilities.
Things to Consider When Choosing a Website Developer for your Website | FODUUFODUU
Choosing the right website developer is crucial for your business. This article covers essential factors to consider, including experience, portfolio, technical skills, communication, pricing, reputation & reviews, cost and budget considerations and post-launch support. Make an informed decision to ensure your website meets your business goals.
HCL Notes und Domino Lizenzkostenreduzierung in der Welt von DLAUpanagenda
Webinar Recording: https://www.panagenda.com/webinars/hcl-notes-und-domino-lizenzkostenreduzierung-in-der-welt-von-dlau/
DLAU und die Lizenzen nach dem CCB- und CCX-Modell sind für viele in der HCL-Community seit letztem Jahr ein heißes Thema. Als Notes- oder Domino-Kunde haben Sie vielleicht mit unerwartet hohen Benutzerzahlen und Lizenzgebühren zu kämpfen. Sie fragen sich vielleicht, wie diese neue Art der Lizenzierung funktioniert und welchen Nutzen sie Ihnen bringt. Vor allem wollen Sie sicherlich Ihr Budget einhalten und Kosten sparen, wo immer möglich. Das verstehen wir und wir möchten Ihnen dabei helfen!
Wir erklären Ihnen, wie Sie häufige Konfigurationsprobleme lösen können, die dazu führen können, dass mehr Benutzer gezählt werden als nötig, und wie Sie überflüssige oder ungenutzte Konten identifizieren und entfernen können, um Geld zu sparen. Es gibt auch einige Ansätze, die zu unnötigen Ausgaben führen können, z. B. wenn ein Personendokument anstelle eines Mail-Ins für geteilte Mailboxen verwendet wird. Wir zeigen Ihnen solche Fälle und deren Lösungen. Und natürlich erklären wir Ihnen das neue Lizenzmodell.
Nehmen Sie an diesem Webinar teil, bei dem HCL-Ambassador Marc Thomas und Gastredner Franz Walder Ihnen diese neue Welt näherbringen. Es vermittelt Ihnen die Tools und das Know-how, um den Überblick zu bewahren. Sie werden in der Lage sein, Ihre Kosten durch eine optimierte Domino-Konfiguration zu reduzieren und auch in Zukunft gering zu halten.
Diese Themen werden behandelt
- Reduzierung der Lizenzkosten durch Auffinden und Beheben von Fehlkonfigurationen und überflüssigen Konten
- Wie funktionieren CCB- und CCX-Lizenzen wirklich?
- Verstehen des DLAU-Tools und wie man es am besten nutzt
- Tipps für häufige Problembereiche, wie z. B. Team-Postfächer, Funktions-/Testbenutzer usw.
- Praxisbeispiele und Best Practices zum sofortigen Umsetzen
Let's Integrate MuleSoft RPA, COMPOSER, APM with AWS IDP along with Slackshyamraj55
Discover the seamless integration of RPA (Robotic Process Automation), COMPOSER, and APM with AWS IDP enhanced with Slack notifications. Explore how these technologies converge to streamline workflows, optimize performance, and ensure secure access, all while leveraging the power of AWS IDP and real-time communication via Slack notifications.
Unlocking Productivity: Leveraging the Potential of Copilot in Microsoft 365, a presentation by Christoforos Vlachos, Senior Solutions Manager – Modern Workplace, Uni Systems
Development of Computer Aided Learning Software for Use in Electric Circuit Analysis
1. 2011 International Transaction Journal of Engineering, Management, & Applied Sciences & Technologies.
2011 International Transaction Journal of Engineering, Management, & Applied Sciences & Technologies.
International Transaction Journal of Engineering,
Management, & Applied Sciences & Technologies
http://www.TuEngr.com, http://go.to/Research
Development of Computer Aided Learning Software for Use
in Electric Circuit Analysis
a* a
Bradley Deken and Chris Cowen
a
Department of Industrial and Engineering Technology, Southeast Missouri State University, USA
ARTICLEINFO ABSTRACT
Article history: Presently, instructors are required to teach more students
Accepted 26 August 2011
Available online with the same resources, thereby reducing the amount of time
01 November 2011 instructors have with their students. Because of this, examples
Keywords: may be omitted to be able to make it through all of the required
Circuit analysis software; material. This can be problematic with electric circuit analysis
Computer aided learning; courses and other courses used as prerequisites. A lack of
Electric circuit analysis; understanding in these classes will likely continue in future
Learning software; classes.
SPICE. 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.
2011 International Transaction Journal of Engineering, Management, &
Applied Sciences & Technologies.
*Corresponding author (B. Deken). Tel/Fax: (573) 651-2659. E-mail addresses:
bdeken@semo.edu. 2011. International Transaction Journal of Engineering, Management, &
Applied Sciences & Technologies. Volume 2 No.5. (Special Issue). ISSN 2228-9860. eISSN
507
1906-9642. Online Available at http://TuEngr.com/V02/507-520.pdf
2. 1. Introduction
As an educator in one of today’s classrooms, I am faced with two problems: an
ever-growing body of knowledge and an educational system that is moving towards larger
classrooms and reduced face-to-face time with students. Electrical circuit analysis courses
(herein referred to as circuit courses) are typically relatively large classes and dense in the
number of topics that are presented. Ideally, for each topic that is presented several examples
would be presented to the class. However, in a traditional lecture environment these are
time-consuming. Moreover, since circuit courses are typically entry-level, students may have a
wide variety of backgrounds. Therefore, some students may understand topics right away while
others may require many different examples. However, because of the number of topics,
providing examples for each topic until each student understands is not a possibility. Equally, it
is not prudent for students to ‘just get through’ a circuits course since it is often a prerequisite
for most of their other courses. Ideally, an instructor or tutor could help any students who get
‘left behind’ by tutoring during their office hours or other help sessions. With the current state
of our education system; however, instructors are required to teach more students with the
same, or even fewer, resources. Software is often touted as a way to increase understanding
outside of the classroom.
While software has its benefits, it is not a panacea for teaching. While software has its
place in the classroom, one must keep in mind the purpose. For instance, SPICE and other
circuit analyzing software are often used but they are designed to analyze, not teach analysis
techniques. While the teaching of this type of software is often justified in circuit courses, the
intent should be to learn the software not to teach analysis concepts. As an analogy, consider
teaching a child arithmetic only using a calculator. They may learn how to use the calculator,
but will neither learn how to perform the arithmetic nor gain insight into how the problems are
solved. Other software does exist for the sole purpose of helping students learn the concepts.
However, many are limited. For example, some have only a present number of problems or
only provide the solution without specifying how it is computed. Others may provide a
‘limitless’ number of problems by changing component values, but each of these end up being
the same basic problem.
This paper will introduce a newly developed, computer-aided, learning software that
addresses these shortcomings. The software provides a practically limitless number of
508 Bradley Deken and Chris Cowen
3. problems by not only varying component values but also the structure of the circuits. Moreover,
the software provides not only an answer to each problem, but an explanation of how the
student could compute it. Finally, the software is designed in such a way that students who need
more help can get it while those who do not can move on. This software and an analysis of its
use in a classroom will be presented in this paper.
2. Types of Electric Circuit Analysis Software
There are three basic types of software packages used in introductory circuits courses:
numerical analysis software, simulation software, and tutoring software. Each has a particular
purpose for being included in a circuits course.
Numerical analysis software enables a user to create complex mathematical functions and
algorithms, and then solve equations using those algorithms. MATLAB (derived from “Matrix
Laboratory”), created by MathWorks, is numerical analysis software designed for engineering
and other math-related fields (Attia, 1996). PTC’s MathCAD and the freely available FreeMat
are both similar to MATLAB in functionality. Each of these software programs have the ability
to perform complex mathematical computations. While these programs simplify the
computations, they do have drawbacks. In lower-level electrical courses, many of the formulas
used do not become complex enough to require computer-based software to analyze.
MATLAB, and similar programs, can calculate diode characteristics, plot transistor response
curves, and so much more (Attia, 1996). However, this is often not needed in low-level circuits
courses. While learning the software may be an objective of the class, learning the numerical
analysis software may not translate into an increased understanding of electric circuit analysis.
Thus the implementation of numerical analysis software to teach electric circuit analysis may
be impractical.
Simulation programs for electrical circuits enable a user to create a schematic of a circuit
on a computer and then run a simulation on the circuit to analyze the behavior. Simulation
Program Integrated Circuits Especially (SPICE) is one of the most common simulation engines
used for electrical circuits (Chamas and Nokali, 2004). SPICE is a simulation engine developed
at the University of California, Berkeley, and serves as a foundation for electronic simulation.
Several programs use it, including XSpice (Georgia Technical Research Institute), PSpice
*Corresponding author (B. Deken). Tel/Fax: (573) 651-2659. E-mail addresses:
bdeken@semo.edu. 2011. International Transaction Journal of Engineering, Management, &
Applied Sciences & Technologies. Volume 2 No.5. (Special Issue). ISSN 2228-9860. eISSN
509
1906-9642. Online Available at http://TuEngr.com/V02/507-520.pdf
4. (MicroSim, now packaged by OrCAD), and MultiSim (Electronics Workbench). Simulating a
circuit involves creating the circuit by placing parts and connecting with wires, running the
simulation for the circuit, and then analyzing the results with probes, oscilloscopes, and meters.
Simulation programs are very useful in the field of electronics. Having a simulation program
eliminates the physical task of placing wires and parts on bread-boards. Simulation software
also makes it possible to construct, test, and analyze a circuit without ever touching real parts,
such as chips or resistors (Hart, 1993). The main benefit of this type of software being used in
the classroom is that it is personalized to the students; they are able to build circuits at their own
pace and with their own design (Lidgey, et al., 1995). With the ability to store circuits on a
computer for future reference, the student can create a portfolio of experiments without
exhausting a supply of parts and space. Ultimately this could save money because the students
do not need to buy this equipment or electronic parts (Castro, 2004). Unfortunately, unless
already present the cost of the software and computers may be more costly than the simple
electronic parts and equipment. Some simulation programs, such as PSpice, utilize a CAD
structure that may not always have a simple user interface (Poole, 1994). If a large amount of
time is needed to train a student on how to use the software, then time will be taken away from
actual learning. For students in lower-level courses it may be easier to just build a circuit on a
breadboard and test it with probes than spending time trying to learn how to do simple tasks
with software. Despite being a good skill to have, learning simulation software does not exactly
translate into learning circuit analysis. This software only provides the analysis; it does not
teach the user how to obtain the results.
Figure 1: DC Circuits Challenge Layout Examples.
Tutoring software enables a user to learn by use of practice and example. Two examples of
tutoring software are Web Tutor and DC Circuits Challenge. DC Circuits Challenge is a
teaching program made by ETCAI that enables students to sharpen their skills on various topics
in electrical circuits. Tutoring software, like DC Circuits Challenge, uses predetermined
circuits for students to practice on (Baser, 2006). In DC Circuits Challenge, the values of the
510 Bradley Deken and Chris Cowen
5. components change allowing students to practice the same type of circuit given various values.
Tutoring software that uses predefined circuits, like DC Circuits Challenge, results in the
student analyzing the same circuit over and over again with just the values of the components
changing (ETCAI, 2008). This may help the student memorize an approach to solving a
particular circuit, but may not help when the circuit changes. Figure 1 shows two examples of
DC Circuits Challenge circuits. Notice that only the component values change between the two
examples.
Web Tutor, developed by Benedykt Rodanski, is a program placed online where students
can practice example exercises to increase knowledge and practice solving electrical circuits
(Rodanski, 2006). Web Tutor generates a circuit within a predefined framework (Rodanski,
2008). Students using software that generates a random circuit will be subjected to many
different circuit layouts. Web Tutor circuits are randomly generated having constraints placed
on the size of the circuit and the orientation (Rodanski, 2008). Figure 2 shows examples of
circuits generated by Web Tutor. While different, the circuits produced are similar visually.
Figure 2: Web Tutor Layout Examples
By having the software itself create the circuit there can be many variations of circuits for
any given topic. Students can learn by practicing as much as they want until they are
comfortable. If a student grasps the concepts of a particular lesson then that student does not
need to practice as much as another student who does not fully understand the lesson. If
software allows for an infinite number of circuits, then students can practice as much as they
need. In some cases tutoring software could replace book work and quizzes completely
(Lidgey, et al., 1995). Rodanski has proved that software tools can supplement a course with
great results (Rodanski, 2006). Tutoring software can be used as a tool that forces students to
*Corresponding author (B. Deken). Tel/Fax: (573) 651-2659. E-mail addresses:
bdeken@semo.edu. 2011. International Transaction Journal of Engineering, Management, &
Applied Sciences & Technologies. Volume 2 No.5. (Special Issue). ISSN 2228-9860. eISSN
511
1906-9642. Online Available at http://TuEngr.com/V02/507-520.pdf
6. look at examples and practice until the concepts become familiar. Tutoring software, however,
does have drawbacks, specifically those found in the programming. The topics are limited by
the amount of programming put into the software package. Some tutoring software may not
cover all the topics covered by the course. Even though the concepts remain the same, the visual
difference in some circuits may be confusing. Therefore, practicing on many different circuits
will prepare the student more effectively (Baser, 2006). Students who practice on software that
can generate any given number (and type) of circuits may have an advantage over the students
who practice on one circuit where only the values of the components change. Therefore, the
type of tutoring software that is used will determine the benefits.
Figure 3: Circuit Tutor Examples
3. Circuit Tutor Software
Tutoring software called Circuit Tutor is the focus of this paper. While it is similar to Web
Tutor and DC Circuits Challenge in many respects, it is significantly different in others. Figure
3 shows examples of Circuit Tutor layouts. While the Circuit Tutor examples are similar to
Web Tutor, the program does allow for more variation. A more significant difference between
the three tutoring software packages is the ways in which they provide help. DC Circuits
Challenge and Web Tutor give help by showing a generic example or by pointing to a specific
theory on which the problem is based. Circuit Tutor, on the other hand, provides customized
text showing step-by-step how a specific problem is solved. Figure 4 shows a problem as
presented to the student.
Figure 5 shows the answers as submitted and the resulting explanation. The full text of this
explanation is shown in Figure 6. This text is customized for each problem.
512 Bradley Deken and Chris Cowen
7. Figure 4: Circuit Tutor Example as Presented to Student
Figure 5: Circuit Tutor Example Once Submitted by Student
*Corresponding author (B. Deken). Tel/Fax: (573) 651-2659. E-mail addresses:
bdeken@semo.edu. 2011. International Transaction Journal of Engineering, Management, &
Applied Sciences & Technologies. Volume 2 No.5. (Special Issue). ISSN 2228-9860. eISSN
513
1906-9642. Online Available at http://TuEngr.com/V02/507-520.pdf
8. Figure 6: Circuit Tutor Example, Explanation Close-up
Figure 7: Circuit Tutor Scoring Example
The software is designed to increase students’ critical thinking abilities. When students see
a circuits question on an exam they must first determine a method to solve the problem. This is
by no means trivial. Even electric circuits that look extremely similar may be analyzed in very
different ways. For this reason, memorizing theories is not enough. Students must comprehend
the theories and determine their applicability to specific circuits. Unfortunately, this
comprehension cannot be ‘taught’. While instructors can provide resources and guide the
students, we are not able to ‘flip the switch’ of understanding. That is up to the students. One
way to get students to ‘see’ the answer is through the use of examples. Most software used in
circuits class will analyze a circuit but not show how it is done. The Circuit Tutor software,
514 Bradley Deken and Chris Cowen
9. however, attempts to do this. This software challenges a student with a problem, checks their
answer, then shows the student how they could approach the problem. Like most other tutor
software, it has a ‘practice mode’ that repeats the same type of problem over and over to build
familiarity with how the specific problem type is solved. A difference with this software is that
it also has a ‘test mode’. In this mode random types of problems are given so students must
learn to recognize the type of problem in addition to knowing how it is solved.
The software developed as a part of this project can be used to supplement topics that
students feel they need more time with. The software currently has 3 topics and each topic has
at least 2 subtopics. The software was designed so that it can easily be expanded with more
topics. Furthermore, students are able to spend as much (or as little) time with a topic as they (or
the instructor) see fit. The software has a special scoring system built in that encourages this. It
scores only the most current problems. Therefore, if a student knows a topic they can work the
minimum number of problems and get a good score. Alternatively, a student who is struggling
can keep doing additional problems until they understand the topic. Since only the most current
problems are used to determine the score, a good score is always possible. An example of this is
shown in Figure 7. For this particular example only 6 problems are used in scoring. Since the
student worked 8 problems the first two are ignored. This method is meant to encourage those
who need extra work to do it while not penalizing those who do not need it.
4. Implementation of Software
The purpose of this project was to find a way to enhance classroom pedagogy in the field of
electrical circuits. This was quantified using test scores and surveys from students. This project
suggested ways to help relieve time strains placed on the educator and increase conceptual
understanding for the students. The key concern of the software is to improve the skills of
students in a time-efficient manner.
This project involved the students in a lower-level electrical course in the School of
Polytechnic Studies at Southeast Missouri State University. The specific course is ET160:
Basic Electricity and Electronics. The class involved has thirty-two students. However, not all
thirty-two students participated in the project. Aside from the thirty-two potential students in
ET160, there was a potential five students from higher-level courses that had already taken
*Corresponding author (B. Deken). Tel/Fax: (573) 651-2659. E-mail addresses:
bdeken@semo.edu. 2011. International Transaction Journal of Engineering, Management, &
Applied Sciences & Technologies. Volume 2 No.5. (Special Issue). ISSN 2228-9860. eISSN
515
1906-9642. Online Available at http://TuEngr.com/V02/507-520.pdf
10. either ET160 or a similar course. These upper-level students were used to provide feedback on
the software. The project relied on student surveys for information regarding the benefits and
opinions of the software when used in the class. A survey was also given to the higher-level
students.
Tests were used to gather data indicating the levels of understanding for students in ET160.
To get a better understanding of the usefulness of the software 4 tests were administered:
pre-test A, post-test A, pre-test B, and post-test B. Both of the pre-tests were given before use of
the software. Both of the post-tests were given after use of the software. The pre-test A and
post-test A both used a randomly generated problem taken verbatim from the Circuit Tutor
software. Pre-test A was given approximately one month before students used the software.
Post-test A was different than the pre-test, but similar. It was given immediately after students
worked with the software. Pre-test B and post-test B both consisted of problems covering the
same concepts as those found in the software. However, the way in which the concept is
presented is significantly different than that found in the software. Pre-test B was given
approximately one month before students used the software. Post-test B was different than the
pre-test, but similar. Post-test B was given a week after students worked with the software.
Test set A was designed to see if the software helped the understanding of a very specific
problem type over a very short time period. Test set B was designed to see if the software could
help with other types of problems (covering the same concepts) over a longer period of time.
While changes were present from the pre-test to the post-test for both test sets, the overall
difficulty of the problem was meant to be consistent. These differences were introduced to
ensure that students didn’t memorize answers without understanding the underlying concept. It
should also be stated that the timing and concepts of both pre-tests were introduced to the
students ahead of time. The concept and timing of the post-test A was also announced. Neither
the timing nor the specific problem type of post-test B was announced ahead of time. The
concepts covered by the software and tests were all covered in lecture before any tests were
given.
5. Results of Software Testing
The test data gathered was analyzed using standard statistical processes. A one-tailed t-test
was used to determine if the students’ grades increased from pre-test to post-test for each test
516 Bradley Deken and Chris Cowen
11. set. While there was over 30 students in the class, not all students participated in all parts of the
project. For example, some students submitted pre-test A, but did not submit post-test A. Some
students also took parts of the pre-test and post-test without using the software. Absent of the
software used, it is assumed that insignificant improvement was made between pre-testing and
post-testing. A limited sample size prevented sub-dividing the group into two parts for control
and experiment. Thus the assumption has been made that all improvement were due to the
software.
Table 1 lists the results for each test set, the sub-questions of each problem set, the overall
results, and the results from 4 students who were not able to use the software because of
absence. The P-values shown are the result of the t-test and provides a measure of the likelihood
that the result could have been achieved through chance. If the P-value is less than the set alpha
level (typically 0.10 or 0.05), the data is considered to be statistically significant. The sample
sizes are also shown. Paired t-tests require a pair of pre- and post-tests. Therefore, if one student
submitted the pre-test but not the post-test then the data was omitted. The table illustrates
whether or not the student achievement, based on grades from pre-tests and post-tests, is
enough to assume that the software has a statistically significant effect on the education of
students. With the alpha level set at 0.05 the overall test results shows significant improvement
since the P-value is less than the alpha level (0.0005 < 0.05). Many of the individual problems
and questions also show a statistically significant improvement. It should be noted, however,
that in Question 2a in Test Set B the average score actually decreased (even if it is statistically
insignificant at a P-value of 0.1641). The improvements made on most of the post-test
questions, however, make the overall test improvement statistically significant.
Because of absences, a small sample of students (4) from ET160 were given pre-test B and
post-test B without using the software. Data from these students is listed in the table as ‘Test Set
B Control’. Although the sample size was small, the data gathered did indicate that the post-test
results showed no improvement over the pre-test results when the students did not use the
software. Thus the assumption that no significant improvement would naturally be made from
pre-test to post-test is supported.
In addition to analyzing test results, students were also given an anonymous survey so that
they could provide feedback on the software. Most of the responses from the survey are
*Corresponding author (B. Deken). Tel/Fax: (573) 651-2659. E-mail addresses:
bdeken@semo.edu. 2011. International Transaction Journal of Engineering, Management, &
Applied Sciences & Technologies. Volume 2 No.5. (Special Issue). ISSN 2228-9860. eISSN
517
1906-9642. Online Available at http://TuEngr.com/V02/507-520.pdf
12. positive regarding the use and benefit of Circuit Tutor. One question, question 10, had a
unanimous response that the program would be beneficial for students taking the course in the
future. Comments made at the end of the survey were mostly positive. Expressions such as
“very helpful,” “very beneficial,” “simple and easy to use,” and “pretty amazing” were all used
to describe the software. Circuit Tutor “supported what was taught in the class well,”
“definitely helped,” was “good practice with immediate feedback,” “helped to better
understand the material,” “enhanced understanding,” and “reinforced the concepts” according
to the surveys. Some of the feedback identified Circuit Tutor to be a “good study tool,” and
“really helpful when studying” as well as “helpful when preparing for tests and understanding
homework.” Not all the comments, however, were positive. Some comments were constructive
and provided suggestions on improvement. Overall there were no negative remarks, just
positive evaluations and helpful suggestions.
Table 1: Statistical Analysis of Test Results
Test Set A, N=25
P-value Pre-Avg Post-Avg
Question 1 0.0159 72.80% 84.00%
Question 2 0.2872 76.00% 79.20%
Total 0.0476 74.40% 81.60%
Test Set B, N=24
P-value Pre-Avg Post-Avg
Question 1a 0.0654 83.33% 92.75%
Question 1b 0.0393 43.48% 59.78%
Total for Q1 0.0162 67.39% 79.57%
Question 2a 0.1641 94.35% 93.04%
Question 2b 0.0363 76.09% 93.48%
Question 2c 0.0928 63.04% 76.09%
Total for Q2 0.0958 87.27% 90.68%
Both Test Sets, N=23
P-value Pre-Avg Post-Avg
Overall Test 0.0005 73.18% 79.88%
Test Set B Control, N=4
P-value Pre-Avg Post-Avg
Overall Test 0.094 98.00% 91.00%
518 Bradley Deken and Chris Cowen
13. Overall the Circuit Tutor software did improve grades by a statistically significant amount.
Not only did Circuit Tutor improve the grades, it also received good reviews by the students
themselves. Although the sample size for the study was small, the results were clear; tutoring
software does have an impact on the level of understanding the students have regarding
electrical circuits.
6. Conclusion
The data gathered from the tests indicate that Circuit Tutor software did have a positive
impact on the level of understanding regarding electrical circuits. The data gathered from the
surveys show that students liked the idea of having tutoring software available to supplement
the lessons as well as replacing homework and quizzes. As a result of the analysis of the data,
the pedagogy in the courses on electrical circuits at Southeast Missouri State University may be
improved.
The software was also found to provide a time savings. The time it takes to assign and
grade homework, assign and grade quizzes, review for tests, and explain how to solve circuits
can be partially eliminated with the use of this tutoring software. The students will be able to
practice as much as needed with unlimited examples and without the assistance of a teacher, be
able to work on homework at their own pace, and be able to study for tests without dedicated
review.
Currently, my students are given access to the software and encouraged to use it, but are
not required to use it. I am currently working on enhancements to the software to make it more
user-friendly. In the future, more topics will be added. Once these modifications are complete, a
second, larger study of Circuit Tutor will be performed. With a larger sample size and more
time another study may compliment this one with improved results. Although Circuit Tutor can
be expanded and improved and more studies performed on the effectiveness of the software,
this project was successful in its examination of enhancing classroom pedagogy in circuit
analysis courses.
7. References
Attia, J. (1996). “Teaching electronics with MATLAB,” Frontiers in Education Conference, 2,
*Corresponding author (B. Deken). Tel/Fax: (573) 651-2659. E-mail addresses:
bdeken@semo.edu. 2011. International Transaction Journal of Engineering, Management, &
Applied Sciences & Technologies. Volume 2 No.5. (Special Issue). ISSN 2228-9860. eISSN
519
1906-9642. Online Available at http://TuEngr.com/V02/507-520.pdf
14. 609-611.
Baser, M. (2006). “Promoting conceptual change through active learning using open source
software for physics simulations,” Australasian Journal of Educational Technology, 22
(3), 336-354.
Castro, M. (2004). “Work in progress - integration of new tools and technologies in electronics
teaching,” Frontiers in Education, 10-11.
Chamas, I. and Nokali, M. (2004). “Automated PSpice simulation as an effective design tool in
teaching power electronics,” IEEE Transactions on Education, 47 (3), 415-421.
ETCAI. (2008). DC circuits challenge, [Computer Program] (5). Ashland, MS: ETCAI
Product.
Hart, D. (1993). “Circuit simulation as an aid in teaching the principles of power electronics,”
IEEE Transactions on Education, 36 (1), 10-16.
Lidgey, F., Rawlinson, M., Pidgeon, M., and Alshahib, I. (1995). “Effective CBL design for
electronics education and student feedback,” IEE Colloquium on Computer-Based
Learning in Electronic Education, 4.1-4.8.
Poole, N. (1994). “The application of simulators in teaching digital electronics,” Engineering
Science and Education Journal, 3, 177-184.
Rodanski, B. (2006), “Dynamic web-based tutorial tool,” Information Technology Based
Higher Education and Training, 67-70.
Rodanski, B. (2008), Web tutor. [Computer Program] (6.5). Sydney, AU: Ben Rodanski.
Dr.B. DEKEN is currently an Assistant Professor in the Industrial and Engineering Technology Department at
Southeast Missouri State University. He has a PhD in Electrical Engineering from Purdue University with a
research focus in machines and power systems. Dr. Deken combines this with an interest in education and
computer programming. He has been a member of IEEE since 2000.
CHRIS COWEN is currently working in the PCB manufacturing industry in Dallas, TX. He has a MS degree
from Southeast Missouri State University in Industrial Management with a focus in Teaching and Training.
Mr. Cowen has a strong drive for education and the utilization of technology.
Peer Review: This article has been internationally peer-reviewed and accepted for publication
according to the guidelines given at the journal’s website. Note: This article
was accepted and presented at IAJC-ASEE International Joint Conference on
Engineering and Related Technologies sponsored by IAJC, ASEE, IEEE, venue
at University of Hartford, USA during April 29-30, 2011.
520 Bradley Deken and Chris Cowen