This document discusses different styles of mapping and their uses in instructional design. It identifies key information structures like rhetorical structure, text structure and sentence structure that underlie effective mapping. It analyzes two mapping styles - Novakian mapping and Hunter's infostructure mapping - and their information-related characteristics. It concludes by outlining four types of task constraints that can be used to guide learners' language use when mapping, including constraints on map size, link types, rhetorical devices and degree of abstraction. The constraints are presented as easily manageable elements for instructional design.
The document discusses the concept of "Image Grammar" which uses grammatical structures as tools for writers to create vivid images and depth in their writing. It presents Harry Noden's view that grammar can bridge the world of living to the world of writing when students understand its role in expression. Examples are given of using grammatical structures like absolutes, appositives, participles, inverted adjectives, and vivid verbs to enhance descriptions through "brush strokes" in writing. The goal is to empower students to make purposeful grammatical choices to reinforce meaning.
1) The document discusses how storytelling is an important part of creating empathy and connection in user experience design.
2) Stories can be found in user research, personas, scenarios, and other UX techniques, even if they are not explicitly called stories.
3) Telling stories helps provide a richer understanding of people and contexts, allows for innovation based on real user needs, and creates more persuasive designs by keeping people at the center of the process.
This document provides a checklist of reading comprehension strategies to use before, during, and after reading a text. Some strategies to use before reading include K-W-L charts, previewing text, and activating prior knowledge. During reading, techniques involve thinking maps, content frames, graphic organizers, and highlighting. After reading, students can do activities like retelling, jigsaw, graffiti, and book talks to reinforce comprehension.
- A study examined insects caught in straw mats used to wrap pine trees over four years and found that 55% were beneficial insects while only 4% were harmful.
- The mats contained hundreds of spiders and assassin bugs that prey on harmful insects. However, egger moth caterpillars and nematodes that damage trees remain on the trees after the mats are removed.
- The traditional practice of wrapping trees in winter is thought to provide places for beneficial insects to survive the winter. However, the study found that burning the mats after removal kills both harmful and beneficial insects, so a better approach is needed.
Workshop
[Delivered at joint 8th International Conference on ESP in Asia and 3rd International Symposium on Innovative Teaching and Research in ESP, UEC, Tokyo. August 21, 2016]
In presentations, particularly during conference presentation Q&A, sci-tech EAP learners often prove unable to distil the underlying intentions of their research design or to identify the argument(s) surrounding their claim and the generalizability of their results.
These EAP learners usually have little training in rhetorical orchestration, especially since their research papers are built on the IMRAD structure, a rather poor metaphor for argument. As a result, these learners find spontaneous oral explanation and argument summarization difficult.
This workshop introduces the operation of a structured, low-text approach which has produced consistent, rapid development of the foundation target skills (argument analysis, argument construction) in classroom application (masters and PhD level). The key tool in this approach is the cross-platform freeware CmapTools, now widely adopted in science education. CmapTools automatically generates Novakian maps (maps in which each link is articulated by a relation phrase). Learners find these maps easy to evaluate in terms of correctness of relations and shockingly accessible in terms of structure of information.
This workshop begins with an overview of current styles of concept visualization (and their attendant syntax and information structures) so as to give participants a broad practical overview of mapping practice today. Participants will then be introduced to the use of CmapTools, and will take part in guided model task performance.
The workshop activities will be low-tech (post-its and marker pens) to maximize accessibility.
However, participants who would like to 'lean in' on this skill set are encouraged to download Cmap Tools to their laptops (Mac, Win or Linux) or iPads, familiarize themselves with the basic functions of the software (takes about 15 minutes), and show up equipped for bigger-curve learning.
The document discusses different types of mapping including concept mapping, argument mapping, information structure mapping, syntactic mapping, and association mapping. It provides details on Novakian concept mapping using Cmap Tools and Hunter's information structure mapping using PowerPoint. The document also discusses matching different mapping styles to instructional purposes and considering constraints like architectural, rhetorical, and relational constraints when deciding on a mapping approach.
Visual metaphors as cognitive scalpel: Cutting through the language disguiseLawrie Hunter
The document describes Lawrie Hunter's use of visual metaphors in information structure maps (ISmaps) to display structural relations between bits of information at the sentence level. ISmaps are an information visualization tool created by Hunter that uses metaphors like subordinate, abstract/concrete, passage through time, and cause-effect relationships to link sentences and represent rhetorical flows or arguments. The document provides an example ISmap about salmon survival techniques in response to rising sea temperatures.
03. Introduction to ISmapping (Hunter's information structure mapping)Lawrie Hunter
The document describes Lawrie Hunter's information structure maps (ISmaps) which are used to analyze and represent the structure of information in texts. The ISmaps identify and represent key information structures such as description, classification, comparison, sequence, and cause-effect. Examples are provided of how Hunter's ISmaps can be used to break down texts and diagrams according to these different information structures.
The document discusses the concept of "Image Grammar" which uses grammatical structures as tools for writers to create vivid images and depth in their writing. It presents Harry Noden's view that grammar can bridge the world of living to the world of writing when students understand its role in expression. Examples are given of using grammatical structures like absolutes, appositives, participles, inverted adjectives, and vivid verbs to enhance descriptions through "brush strokes" in writing. The goal is to empower students to make purposeful grammatical choices to reinforce meaning.
1) The document discusses how storytelling is an important part of creating empathy and connection in user experience design.
2) Stories can be found in user research, personas, scenarios, and other UX techniques, even if they are not explicitly called stories.
3) Telling stories helps provide a richer understanding of people and contexts, allows for innovation based on real user needs, and creates more persuasive designs by keeping people at the center of the process.
This document provides a checklist of reading comprehension strategies to use before, during, and after reading a text. Some strategies to use before reading include K-W-L charts, previewing text, and activating prior knowledge. During reading, techniques involve thinking maps, content frames, graphic organizers, and highlighting. After reading, students can do activities like retelling, jigsaw, graffiti, and book talks to reinforce comprehension.
- A study examined insects caught in straw mats used to wrap pine trees over four years and found that 55% were beneficial insects while only 4% were harmful.
- The mats contained hundreds of spiders and assassin bugs that prey on harmful insects. However, egger moth caterpillars and nematodes that damage trees remain on the trees after the mats are removed.
- The traditional practice of wrapping trees in winter is thought to provide places for beneficial insects to survive the winter. However, the study found that burning the mats after removal kills both harmful and beneficial insects, so a better approach is needed.
Workshop
[Delivered at joint 8th International Conference on ESP in Asia and 3rd International Symposium on Innovative Teaching and Research in ESP, UEC, Tokyo. August 21, 2016]
In presentations, particularly during conference presentation Q&A, sci-tech EAP learners often prove unable to distil the underlying intentions of their research design or to identify the argument(s) surrounding their claim and the generalizability of their results.
These EAP learners usually have little training in rhetorical orchestration, especially since their research papers are built on the IMRAD structure, a rather poor metaphor for argument. As a result, these learners find spontaneous oral explanation and argument summarization difficult.
This workshop introduces the operation of a structured, low-text approach which has produced consistent, rapid development of the foundation target skills (argument analysis, argument construction) in classroom application (masters and PhD level). The key tool in this approach is the cross-platform freeware CmapTools, now widely adopted in science education. CmapTools automatically generates Novakian maps (maps in which each link is articulated by a relation phrase). Learners find these maps easy to evaluate in terms of correctness of relations and shockingly accessible in terms of structure of information.
This workshop begins with an overview of current styles of concept visualization (and their attendant syntax and information structures) so as to give participants a broad practical overview of mapping practice today. Participants will then be introduced to the use of CmapTools, and will take part in guided model task performance.
The workshop activities will be low-tech (post-its and marker pens) to maximize accessibility.
However, participants who would like to 'lean in' on this skill set are encouraged to download Cmap Tools to their laptops (Mac, Win or Linux) or iPads, familiarize themselves with the basic functions of the software (takes about 15 minutes), and show up equipped for bigger-curve learning.
The document discusses different types of mapping including concept mapping, argument mapping, information structure mapping, syntactic mapping, and association mapping. It provides details on Novakian concept mapping using Cmap Tools and Hunter's information structure mapping using PowerPoint. The document also discusses matching different mapping styles to instructional purposes and considering constraints like architectural, rhetorical, and relational constraints when deciding on a mapping approach.
Visual metaphors as cognitive scalpel: Cutting through the language disguiseLawrie Hunter
The document describes Lawrie Hunter's use of visual metaphors in information structure maps (ISmaps) to display structural relations between bits of information at the sentence level. ISmaps are an information visualization tool created by Hunter that uses metaphors like subordinate, abstract/concrete, passage through time, and cause-effect relationships to link sentences and represent rhetorical flows or arguments. The document provides an example ISmap about salmon survival techniques in response to rising sea temperatures.
03. Introduction to ISmapping (Hunter's information structure mapping)Lawrie Hunter
The document describes Lawrie Hunter's information structure maps (ISmaps) which are used to analyze and represent the structure of information in texts. The ISmaps identify and represent key information structures such as description, classification, comparison, sequence, and cause-effect. Examples are provided of how Hunter's ISmaps can be used to break down texts and diagrams according to these different information structures.
This document discusses spatial analysis and analysis tools. It begins by defining spatial analysis as techniques for analyzing spatial data where the results depend on object locations. It then describes 7 types of spatial analysis: spatial data analysis, spatial autocorrelation, spatial interpolation, spatial regression, spatial interaction, simulation and modelling, and multiple-point geostatistics. The document also discusses various analysis toolsets including map algebra, math tools, multi-variate tools, neighborhood tools, raster tools, reclassification tools, and solar radiation tools. It emphasizes that spatial analysis is useless without spatial infographics and visualization.
Face Recognition System using Self Organizing Feature Map and Appearance Base...ijtsrd
Face Recognition has develop one of the most effective presentations of image analysis. This area of research is important not only for the applications in human computer interaction, biometric and security but also in other pattern classification problem. To improve face recognition in this system, two methods are used PCA Principal component analysis and SOM Self organizing feature Map .PCA is a subspace projection method is used compress the input face image. SOM method is used to classify DCT based feature vectors into groups to identify if the subject in the input image is "present" or "not present" in the image database. The aim of this system is that input image has to compare with stored images in the database using PCA and SOM method. An image database of 100 face images is evaluated containing 10 subjects and each subject having 10 images with different facial expression. This system is evaluated by measuring the accuracy of recognition rate. This system has been implemented by MATLAB programming. Thaung Yin | Khin Moh Moh Than | Win Tun "Face Recognition System using Self-Organizing Feature Map and Appearance-Based Approach" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-3 | Issue-5 , August 2019, URL: https://www.ijtsrd.com/papers/ijtsrd26691.pdfPaper URL: https://www.ijtsrd.com/computer-science/cognitive-science/26691/face-recognition-system-using-self-organizing-feature-map-and-appearance-based-approach/thaung-yin
Spatially resolved pair correlation functions for structure processing taxono...Tony Fast
Presentation given at the Integrated Computational Materials Engineering conference 2013. This presentation provides a brief survey of what spatial correlation functions can provide for point cloud microstructure datasets. This method is applicable to very large (~1,000,000 datapoints) both experimental and computational microstructure datasets. It is applied to Aluminum molecular dynamics simulations provided by Chandler Becker at NIST, molecular dynamics simulations of mechanical deformation of polymer materials provided by Karl Jacobs and Xin Dong at Georgia Tech, and lastly experimental datasets of the solidfication of Al-Cu alloys generated from X-ray Computed Tomography as provided by Peter Voorhees and John Gibbs at Northwestern University.
PCA and DCT Based Approach for Face Recognitionijtsrd
Recognizing the identity of the target. The research of face recognition has great theoretical value involving subject of pattern recognition, image processing, computer vision, machine learning, and physiology and so on, and it also has a high correlation with other biometrics recognition methods. In recent years, face recognition is one of the most active and challenging problems in the field of pattern recognition and artificial intelligence. Face recognition has a lot of advantages which are not involved in biometrics recognition methods such as nonaggressive, friendly, conveniently, and so on .Therefore, face recognition has a prospective application foreground, such as the criminal identification, security system, file management, entrance guard system, and so on . Research in the field of face recognition knew considerable progress during these last years. Among the most evoked techniques we find those which employ the optimization of the size of the data in order to get a representation which makes it possible to carry out the recognition. For these methods, the images of faces are seen like points in a space of very great dimensions. The face space is defined by Eigen face which are eigenvectors of the set of faces. In the DCT approach we take transform the image into the frequency domain and extract the feature from it. For feature extraction we use two approach. In the 1st approach we take the DCT of the whole image and extract the feature from it. In the 2nd approach we divide the image into sub images and take DCT of each of them and then extract the feature vector from them. Manish Varyani | Pallavi Narware | Lokendra Singh Banafar ""PCA and DCT Based Approach for Face Recognition"" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-3 | Issue-3 , April 2019, URL: https://www.ijtsrd.com/papers/ijtsrd23283.pdf
Paper URL: https://www.ijtsrd.com/engineering/electronics-and-communication-engineering/23283/pca-and-dct-based-approach-for-face-recognition/manish-varyani
Cmap Tools as an essential for teaching academic writingLawrie Hunter
IT tools are great, but they must take their place among other tools, some of them not recognized as technology, e.g. the paragraph is technology - didn't you knowtice?
Academic writing process: Cmaps as an essential tool (JALTCALL 2013, Matsumoto)Lawrie Hunter
The document describes a case study of using concept mapping (Cmaps) with English for Academic Purposes (EAP) students to improve their academic writing. It discusses how the students cycled between mapping texts and analyzing texts using Cmaps and text analysis tools. By mapping introductions to research papers and critiquing and revising the maps, the students were able to produce improved summaries. The case study suggests Cmaps are an effective tool for identifying rhetorical structure and aiding in academic writing.
This document summarizes a presentation on deep image processing and computer vision. It introduces common deep learning techniques like CNNs, autoencoders, variational autoencoders and generative adversarial networks. It then discusses applications including image classification using models like LeNet, AlexNet and VGG. It also covers face detection, segmentation, object detection algorithms like R-CNN, Fast R-CNN and Faster R-CNN. Additional topics include document automation using character recognition and graphical element analysis, as well as identity recognition using face detection. Real-world examples are provided for document processing, handwritten letter recognition and event pass verification.
"FingerPrint Recognition Using Principle Component Analysis(PCA)”Er. Arpit Sharma
Fingerprint recognition is one of the oldest and most popular biometric technologies and it is used in criminal investigations, civilian, commercial applications, and so on. Fingerprint matching is the process used to determine whether the two sets of fingerprints details come from the same finger or not. This work focuses on feature extraction and minutiae matching stage. There are many matching techniques used for fingerprint recognition systems such as minutiae based matching, pattern based matching, Correlation based matching, and image based matching.
A new method based upon Principal Component Analysis (PCA) for fingerprint enhancement is proposed in this paper. PCA is a useful statistical technique that has found application in fields such as face recognition and image compression, and is a common technique for finding patterns in data of high dimension. In the proposed method image is first decomposed into directional images using decimation free Directional Filter bank DDFB. Then PCA is applied to these directional fingerprint images which gives the PCA filtered images. Which are basically directional images? Then these directional images are reconstructed into one image which is the enhanced one. Simulation results are included illustrating the capability of the proposed method.
A Survey of Modern Character Recognition Techniquesijsrd.com
This document summarizes several modern techniques for handwritten character recognition. It discusses common feature extraction methods like statistical, structural and global transformation features. It then summarizes several papers that have proposed different techniques for handwritten character recognition, including using associative memory nets, moment invariants with support vector machines, neural networks, hidden markov models, gradient features, and multi-scale neural networks. The document concludes that neural networks are commonly used for training, and that feature extraction methods continue to be improved, but handwritten character recognition remains an active area of research.
This document summarizes a research paper that revisits the scanpath comparison framework based on string editing. The paper improves upon previous work by substituting k-means clustering with mean shift clustering, and modeling clusters with ellipses to determine overlap between scanpaths. The authors validate the approach by analyzing eye movements recorded during a variant of the Trail Making Test.
The document outlines various skills related to using ArcGIS software. These include querying GIS databases to locate map features, understanding spatial relationships, using analysis tools to create new data, and applying standard approaches to solving geographic problems. Additional skills involve using online resources to create maps, describing data models, evaluating data for mapping projects, exploring and analyzing maps, and preparing maps to share information and analysis results.
IJCER (www.ijceronline.com) International Journal of computational Engineerin...ijceronline
This document summarizes a research paper that proposes a new image interpolation technique to reconstruct high-resolution images from low-resolution counterparts while preserving edge structures. The technique estimates each pixel to be interpolated in two orthogonal directions and fuses the estimates using linear minimum mean square error estimation. This adaptive fusion approach can better discriminate edge directions in the local window compared to interpolating in a single direction. The technique aims to improve on traditional linear interpolation methods by adapting to local image gradients to reduce artifacts while preserving sharp edges. A simplified version is also presented to reduce computational costs with minimal impact on performance. Experiments showed the new technique can better preserve edges and reduce artifacts compared to other methods.
Summary: Graphs are structures commonly used in computer science that model the interactions among entities. I will start from introducing the basic formulations of graph based machine learning, which has been a popular topic of research in the past decade and led to a powerful set of techniques. Particularly, I will show examples on how it acts as a generic data mining and predictive analytic tool. In the second part, I am going to discuss applications of such learning techniques in media analytics: (1) image analysis, where visually coherent objects are isolated from images; (2) social analysis of videos, where actors' social properties are predicted from videos. Materials in this part are based on our recent publications in highly selective venues (papers on https://sites.google.com/site/leiding2010/ ).
Bio: Lei Ding is a researcher making sense of large amounts of data in all media types. He currently works in Intent Media as a scientist, focusing on data analytics and applied machine learning in online advertising. Previously, he has worked in several research institutions including Columbia University, UIUC and IBM Research on digital / social media analysis and understanding. He received a Ph.D. degree in Computer Science and Engineering from The Ohio State University, where he was a Distinguished University Fellow.
This document describes a project using a neural network and MATLAB for handwritten character recognition. The goal is to train a neural network to classify individual handwritten characters. The solution approach involves preprocessing images to extract characters, extracting features from the characters, training the neural network, and creating a graphical user interface application. Image preprocessing includes converting to grayscale, thresholding to binary, connectivity testing, and cropping characters. Feature extraction calculates 17 attributes for each character like position, size, pixel counts and distributions. The neural network is then trained on this dataset to classify characters for the application.
This document discusses convolutional neural networks (CNNs) for graph-structured data. CNNs are traditionally designed for Euclidean data like images but not irregular graph data. The key ideas are:
1) Define convolution on graphs using graph spectral theory by representing signals in the graph Fourier domain.
2) Coarsen graphs using a balanced cut model to extract hierarchical patterns.
3) Perform fast graph pooling using a binary tree of coarsened graphs for downsampling.
This allows generalizing CNNs to any graph data with the same computational efficiency as standard CNNs. Related works on graph CNNs are also discussed.
The document summarizes techniques for finding correspondences between images, including local feature detection, descriptors, and matching. It discusses how local features can be used for large scale image retrieval applications. Local feature detectors aim to find repeatable keypoints that are robust to changes in viewpoint and occlusion. Descriptors are used to represent image patches around keypoints to enable matching. Techniques like bag-of-words models and geometric verification allow matching features across large databases to perform image search and retrieval.
Prediction and planning for self driving at waymoYu Huang
ChauffeurNet: Learning To Drive By Imitating The Best Synthesizing The Worst
Multipath: Multiple Probabilistic Anchor Trajectory Hypotheses For Behavior Prediction
VectorNet: Encoding HD Maps And Agent Dynamics From Vectorized Representation
TNT: Target-driven Trajectory Prediction
Large Scale Interactive Motion Forecasting For Autonomous Driving : The Waymo Open Motion Dataset
Identifying Driver Interactions Via Conditional Behavior Prediction
Peeking Into The Future: Predicting Future Person Activities And Locations In Videos
STINet: Spatio-temporal-interactive Network For Pedestrian Detection And Trajectory Prediction
This document discusses knowledge discovery and machine learning on graph data. It makes three main observations:
1) Graphs are typically constructed from input data rather than given directly, as relationships must be inferred.
2) Graph data management is challenging due to issues like large size, dynamic nature, heterogeneity and attribution.
3) Useful insights and accurate modeling depend on the representation of the data as a graph, such as through decomposition, feature learning or other techniques.
Overview of CPC writing support for G-cube doctoral students 23.01.12Lawrie Hunter
This document describes editing and writing services offered by Lawrie Hunter to G-cube PhD students. It outlines 5 main services: 1) Editing papers and providing coded feedback, 2) Mentoring to improve conformity and readability, 3) Support with presentation skills and materials, 4) Assistance with complexity management using mapping tools, 5) Guidance on academic writing styles. Students can meet with Hunter for an initial assessment and discussion of needs. Examples are provided of Hunter's edited comments and mapping diagrams to illustrate the types of support available.
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This document discusses spatial analysis and analysis tools. It begins by defining spatial analysis as techniques for analyzing spatial data where the results depend on object locations. It then describes 7 types of spatial analysis: spatial data analysis, spatial autocorrelation, spatial interpolation, spatial regression, spatial interaction, simulation and modelling, and multiple-point geostatistics. The document also discusses various analysis toolsets including map algebra, math tools, multi-variate tools, neighborhood tools, raster tools, reclassification tools, and solar radiation tools. It emphasizes that spatial analysis is useless without spatial infographics and visualization.
Face Recognition System using Self Organizing Feature Map and Appearance Base...ijtsrd
Face Recognition has develop one of the most effective presentations of image analysis. This area of research is important not only for the applications in human computer interaction, biometric and security but also in other pattern classification problem. To improve face recognition in this system, two methods are used PCA Principal component analysis and SOM Self organizing feature Map .PCA is a subspace projection method is used compress the input face image. SOM method is used to classify DCT based feature vectors into groups to identify if the subject in the input image is "present" or "not present" in the image database. The aim of this system is that input image has to compare with stored images in the database using PCA and SOM method. An image database of 100 face images is evaluated containing 10 subjects and each subject having 10 images with different facial expression. This system is evaluated by measuring the accuracy of recognition rate. This system has been implemented by MATLAB programming. Thaung Yin | Khin Moh Moh Than | Win Tun "Face Recognition System using Self-Organizing Feature Map and Appearance-Based Approach" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-3 | Issue-5 , August 2019, URL: https://www.ijtsrd.com/papers/ijtsrd26691.pdfPaper URL: https://www.ijtsrd.com/computer-science/cognitive-science/26691/face-recognition-system-using-self-organizing-feature-map-and-appearance-based-approach/thaung-yin
Spatially resolved pair correlation functions for structure processing taxono...Tony Fast
Presentation given at the Integrated Computational Materials Engineering conference 2013. This presentation provides a brief survey of what spatial correlation functions can provide for point cloud microstructure datasets. This method is applicable to very large (~1,000,000 datapoints) both experimental and computational microstructure datasets. It is applied to Aluminum molecular dynamics simulations provided by Chandler Becker at NIST, molecular dynamics simulations of mechanical deformation of polymer materials provided by Karl Jacobs and Xin Dong at Georgia Tech, and lastly experimental datasets of the solidfication of Al-Cu alloys generated from X-ray Computed Tomography as provided by Peter Voorhees and John Gibbs at Northwestern University.
PCA and DCT Based Approach for Face Recognitionijtsrd
Recognizing the identity of the target. The research of face recognition has great theoretical value involving subject of pattern recognition, image processing, computer vision, machine learning, and physiology and so on, and it also has a high correlation with other biometrics recognition methods. In recent years, face recognition is one of the most active and challenging problems in the field of pattern recognition and artificial intelligence. Face recognition has a lot of advantages which are not involved in biometrics recognition methods such as nonaggressive, friendly, conveniently, and so on .Therefore, face recognition has a prospective application foreground, such as the criminal identification, security system, file management, entrance guard system, and so on . Research in the field of face recognition knew considerable progress during these last years. Among the most evoked techniques we find those which employ the optimization of the size of the data in order to get a representation which makes it possible to carry out the recognition. For these methods, the images of faces are seen like points in a space of very great dimensions. The face space is defined by Eigen face which are eigenvectors of the set of faces. In the DCT approach we take transform the image into the frequency domain and extract the feature from it. For feature extraction we use two approach. In the 1st approach we take the DCT of the whole image and extract the feature from it. In the 2nd approach we divide the image into sub images and take DCT of each of them and then extract the feature vector from them. Manish Varyani | Pallavi Narware | Lokendra Singh Banafar ""PCA and DCT Based Approach for Face Recognition"" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-3 | Issue-3 , April 2019, URL: https://www.ijtsrd.com/papers/ijtsrd23283.pdf
Paper URL: https://www.ijtsrd.com/engineering/electronics-and-communication-engineering/23283/pca-and-dct-based-approach-for-face-recognition/manish-varyani
Cmap Tools as an essential for teaching academic writingLawrie Hunter
IT tools are great, but they must take their place among other tools, some of them not recognized as technology, e.g. the paragraph is technology - didn't you knowtice?
Academic writing process: Cmaps as an essential tool (JALTCALL 2013, Matsumoto)Lawrie Hunter
The document describes a case study of using concept mapping (Cmaps) with English for Academic Purposes (EAP) students to improve their academic writing. It discusses how the students cycled between mapping texts and analyzing texts using Cmaps and text analysis tools. By mapping introductions to research papers and critiquing and revising the maps, the students were able to produce improved summaries. The case study suggests Cmaps are an effective tool for identifying rhetorical structure and aiding in academic writing.
This document summarizes a presentation on deep image processing and computer vision. It introduces common deep learning techniques like CNNs, autoencoders, variational autoencoders and generative adversarial networks. It then discusses applications including image classification using models like LeNet, AlexNet and VGG. It also covers face detection, segmentation, object detection algorithms like R-CNN, Fast R-CNN and Faster R-CNN. Additional topics include document automation using character recognition and graphical element analysis, as well as identity recognition using face detection. Real-world examples are provided for document processing, handwritten letter recognition and event pass verification.
"FingerPrint Recognition Using Principle Component Analysis(PCA)”Er. Arpit Sharma
Fingerprint recognition is one of the oldest and most popular biometric technologies and it is used in criminal investigations, civilian, commercial applications, and so on. Fingerprint matching is the process used to determine whether the two sets of fingerprints details come from the same finger or not. This work focuses on feature extraction and minutiae matching stage. There are many matching techniques used for fingerprint recognition systems such as minutiae based matching, pattern based matching, Correlation based matching, and image based matching.
A new method based upon Principal Component Analysis (PCA) for fingerprint enhancement is proposed in this paper. PCA is a useful statistical technique that has found application in fields such as face recognition and image compression, and is a common technique for finding patterns in data of high dimension. In the proposed method image is first decomposed into directional images using decimation free Directional Filter bank DDFB. Then PCA is applied to these directional fingerprint images which gives the PCA filtered images. Which are basically directional images? Then these directional images are reconstructed into one image which is the enhanced one. Simulation results are included illustrating the capability of the proposed method.
A Survey of Modern Character Recognition Techniquesijsrd.com
This document summarizes several modern techniques for handwritten character recognition. It discusses common feature extraction methods like statistical, structural and global transformation features. It then summarizes several papers that have proposed different techniques for handwritten character recognition, including using associative memory nets, moment invariants with support vector machines, neural networks, hidden markov models, gradient features, and multi-scale neural networks. The document concludes that neural networks are commonly used for training, and that feature extraction methods continue to be improved, but handwritten character recognition remains an active area of research.
This document summarizes a research paper that revisits the scanpath comparison framework based on string editing. The paper improves upon previous work by substituting k-means clustering with mean shift clustering, and modeling clusters with ellipses to determine overlap between scanpaths. The authors validate the approach by analyzing eye movements recorded during a variant of the Trail Making Test.
The document outlines various skills related to using ArcGIS software. These include querying GIS databases to locate map features, understanding spatial relationships, using analysis tools to create new data, and applying standard approaches to solving geographic problems. Additional skills involve using online resources to create maps, describing data models, evaluating data for mapping projects, exploring and analyzing maps, and preparing maps to share information and analysis results.
IJCER (www.ijceronline.com) International Journal of computational Engineerin...ijceronline
This document summarizes a research paper that proposes a new image interpolation technique to reconstruct high-resolution images from low-resolution counterparts while preserving edge structures. The technique estimates each pixel to be interpolated in two orthogonal directions and fuses the estimates using linear minimum mean square error estimation. This adaptive fusion approach can better discriminate edge directions in the local window compared to interpolating in a single direction. The technique aims to improve on traditional linear interpolation methods by adapting to local image gradients to reduce artifacts while preserving sharp edges. A simplified version is also presented to reduce computational costs with minimal impact on performance. Experiments showed the new technique can better preserve edges and reduce artifacts compared to other methods.
Summary: Graphs are structures commonly used in computer science that model the interactions among entities. I will start from introducing the basic formulations of graph based machine learning, which has been a popular topic of research in the past decade and led to a powerful set of techniques. Particularly, I will show examples on how it acts as a generic data mining and predictive analytic tool. In the second part, I am going to discuss applications of such learning techniques in media analytics: (1) image analysis, where visually coherent objects are isolated from images; (2) social analysis of videos, where actors' social properties are predicted from videos. Materials in this part are based on our recent publications in highly selective venues (papers on https://sites.google.com/site/leiding2010/ ).
Bio: Lei Ding is a researcher making sense of large amounts of data in all media types. He currently works in Intent Media as a scientist, focusing on data analytics and applied machine learning in online advertising. Previously, he has worked in several research institutions including Columbia University, UIUC and IBM Research on digital / social media analysis and understanding. He received a Ph.D. degree in Computer Science and Engineering from The Ohio State University, where he was a Distinguished University Fellow.
This document describes a project using a neural network and MATLAB for handwritten character recognition. The goal is to train a neural network to classify individual handwritten characters. The solution approach involves preprocessing images to extract characters, extracting features from the characters, training the neural network, and creating a graphical user interface application. Image preprocessing includes converting to grayscale, thresholding to binary, connectivity testing, and cropping characters. Feature extraction calculates 17 attributes for each character like position, size, pixel counts and distributions. The neural network is then trained on this dataset to classify characters for the application.
This document discusses convolutional neural networks (CNNs) for graph-structured data. CNNs are traditionally designed for Euclidean data like images but not irregular graph data. The key ideas are:
1) Define convolution on graphs using graph spectral theory by representing signals in the graph Fourier domain.
2) Coarsen graphs using a balanced cut model to extract hierarchical patterns.
3) Perform fast graph pooling using a binary tree of coarsened graphs for downsampling.
This allows generalizing CNNs to any graph data with the same computational efficiency as standard CNNs. Related works on graph CNNs are also discussed.
The document summarizes techniques for finding correspondences between images, including local feature detection, descriptors, and matching. It discusses how local features can be used for large scale image retrieval applications. Local feature detectors aim to find repeatable keypoints that are robust to changes in viewpoint and occlusion. Descriptors are used to represent image patches around keypoints to enable matching. Techniques like bag-of-words models and geometric verification allow matching features across large databases to perform image search and retrieval.
Prediction and planning for self driving at waymoYu Huang
ChauffeurNet: Learning To Drive By Imitating The Best Synthesizing The Worst
Multipath: Multiple Probabilistic Anchor Trajectory Hypotheses For Behavior Prediction
VectorNet: Encoding HD Maps And Agent Dynamics From Vectorized Representation
TNT: Target-driven Trajectory Prediction
Large Scale Interactive Motion Forecasting For Autonomous Driving : The Waymo Open Motion Dataset
Identifying Driver Interactions Via Conditional Behavior Prediction
Peeking Into The Future: Predicting Future Person Activities And Locations In Videos
STINet: Spatio-temporal-interactive Network For Pedestrian Detection And Trajectory Prediction
This document discusses knowledge discovery and machine learning on graph data. It makes three main observations:
1) Graphs are typically constructed from input data rather than given directly, as relationships must be inferred.
2) Graph data management is challenging due to issues like large size, dynamic nature, heterogeneity and attribution.
3) Useful insights and accurate modeling depend on the representation of the data as a graph, such as through decomposition, feature learning or other techniques.
Similar to Deep Foundations of Concept Mapping (pdf) (20)
Overview of CPC writing support for G-cube doctoral students 23.01.12Lawrie Hunter
This document describes editing and writing services offered by Lawrie Hunter to G-cube PhD students. It outlines 5 main services: 1) Editing papers and providing coded feedback, 2) Mentoring to improve conformity and readability, 3) Support with presentation skills and materials, 4) Assistance with complexity management using mapping tools, 5) Guidance on academic writing styles. Students can meet with Hunter for an initial assessment and discussion of needs. Examples are provided of Hunter's edited comments and mapping diagrams to illustrate the types of support available.
The expanding palette: emergent CALL paradigmsLawrie Hunter
The view from 2006: a presentation at Antwerp CALL, on the need for learning paradigm work for emerging tech society. Largely still relevant, surprisingly, in 2022.
Dimensions of Media Object ComprehensibilityLawrie Hunter
This document discusses dimensions of comprehensibility in media objects. It begins by framing the topic as a pattern language approach for machine-mediated communication (MMC). It notes insights can be drawn from second language learning, where comprehension of partially acquired languages reveals aspects of text and media nature. The document then discusses various parameters that influence the difficulty of comprehending media objects, such as document purpose, content, target behaviors, and lexical items. It provides examples of how knowledge structure maps can link descriptive information about a text. The goal is to develop a pattern language to guide machines in human-like communication by understanding factors affecting media object comprehension.
This is the first of a series of workshops about information structures, which are the framework for two English writing/speaking textbooks:
Greene & Hunter 2002 "Critical Thinking" (Asahi)
Hunter 2007 "Thinking in English" (Cengage)
This workshop introduces the use of concept mapping (not mind mapping!) for identifying structure in complex texts, and for creating structure as you write. Cmap Tools is a freeware that is very suitable for structure work related to your writing. Visit https://cmap.ihmc.us/ to download Cmap Tools freeware and study with their excellent resources.
GRIPS Academic Writing Workshop: process, not crisisLawrie Hunter
This document discusses a workshop on academic writing processes. It outlines that the workshop will teach participants about gradually improving their writing through a process of working with mentors as they write papers and dissertations, rather than seeking help after writing is complete in a state of crisis. The topics covered will include demonstrations of working with a mentor to find weaknesses and develop a style for each paper section. Hands-on exercises will address common writing problems for graduate students and how to overcome them through structured writing processes and mentor feedback.
GRIPS Speech Workshop I: intonation and pausingLawrie Hunter
Using TED talks' interactive transcript, the listen-repeat-record-compare cycle can be enhanced if we focus on particular elements of fluency. Here the emphasis is on two important elements, intonation and pausing.
The document discusses several techniques for improving the readability of academic writing. It covers topics such as subject-verb distance, topic-stress positioning, parallel structure, pronoun reference, word choice, cohesion, joining sentences, vagueness and ambiguity, and nominalization. The workshop aims to help writers identify and address common readability problems in their work in order to make their writing more clear, accessible, and effective for readers.
This is an introduction to the main elements of readability in formal text, e.g. official documents. It reveals how readability in English is very different from readability in Japanese.
The document discusses the concept of "topic-stress", which is a rule for structuring sentences. According to this rule, the topic of the sentence should come near the beginning, while the stress or emphasis should come near the end. Properly applying topic-stress can influence the overall impression or tone conveyed by a sentence. A series of examples are provided to illustrate how moving elements like positive or negative phrases to different parts of the sentence changes the meaning or tone. The document suggests topic-stress is a useful concept for understanding how to structure information in a sentence.
Cohesion for academic writing (sentence-sentence)Lawrie Hunter
The document discusses creating cohesion and readability in writing. Initially, cohesion was established but eventually led to difficulties. The problem was solved by a method, but a weakness remained. That final weakness was then overcome through another technique.
Concept mapping for complexity managementLawrie Hunter
Graduate students are often overwhelmed by the huge amount of information and the numerous ideas that they want to put in their papers. Linear text, paragraph after paragraph, is not the ideal tool for structuring large collections of concepts.
This workshop introduces the use of concept mapping (not mind mapping!) for identifying structure in complex texts, and for creating structure as you write.
Language as a disguise for information 5. make it hard for the readerLawrie Hunter
The document discusses three ways to make reading difficult: 1) Using different words to refer to the same thing, 2) Placing the subject and verb far apart in sentences, and 3) Mismatching a noun and its adjective phrase. Examples are provided to illustrate each technique.
LAND USE LAND COVER AND NDVI OF MIRZAPUR DISTRICT, UPRAHUL
This Dissertation explores the particular circumstances of Mirzapur, a region located in the
core of India. Mirzapur, with its varied terrains and abundant biodiversity, offers an optimal
environment for investigating the changes in vegetation cover dynamics. Our study utilizes
advanced technologies such as GIS (Geographic Information Systems) and Remote sensing to
analyze the transformations that have taken place over the course of a decade.
The complex relationship between human activities and the environment has been the focus
of extensive research and worry. As the global community grapples with swift urbanization,
population expansion, and economic progress, the effects on natural ecosystems are becoming
more evident. A crucial element of this impact is the alteration of vegetation cover, which plays a
significant role in maintaining the ecological equilibrium of our planet.Land serves as the foundation for all human activities and provides the necessary materials for
these activities. As the most crucial natural resource, its utilization by humans results in different
'Land uses,' which are determined by both human activities and the physical characteristics of the
land.
The utilization of land is impacted by human needs and environmental factors. In countries
like India, rapid population growth and the emphasis on extensive resource exploitation can lead
to significant land degradation, adversely affecting the region's land cover.
Therefore, human intervention has significantly influenced land use patterns over many
centuries, evolving its structure over time and space. In the present era, these changes have
accelerated due to factors such as agriculture and urbanization. Information regarding land use and
cover is essential for various planning and management tasks related to the Earth's surface,
providing crucial environmental data for scientific, resource management, policy purposes, and
diverse human activities.
Accurate understanding of land use and cover is imperative for the development planning
of any area. Consequently, a wide range of professionals, including earth system scientists, land
and water managers, and urban planners, are interested in obtaining data on land use and cover
changes, conversion trends, and other related patterns. The spatial dimensions of land use and
cover support policymakers and scientists in making well-informed decisions, as alterations in
these patterns indicate shifts in economic and social conditions. Monitoring such changes with the
help of Advanced technologies like Remote Sensing and Geographic Information Systems is
crucial for coordinated efforts across different administrative levels. Advanced technologies like
Remote Sensing and Geographic Information Systems
9
Changes in vegetation cover refer to variations in the distribution, composition, and overall
structure of plant communities across different temporal and spatial scales. These changes can
occur natural.
Main Java[All of the Base Concepts}.docxadhitya5119
This is part 1 of my Java Learning Journey. This Contains Custom methods, classes, constructors, packages, multithreading , try- catch block, finally block and more.
Strategies for Effective Upskilling is a presentation by Chinwendu Peace in a Your Skill Boost Masterclass organisation by the Excellence Foundation for South Sudan on 08th and 09th June 2024 from 1 PM to 3 PM on each day.
Beyond Degrees - Empowering the Workforce in the Context of Skills-First.pptxEduSkills OECD
Iván Bornacelly, Policy Analyst at the OECD Centre for Skills, OECD, presents at the webinar 'Tackling job market gaps with a skills-first approach' on 12 June 2024
हिंदी वर्णमाला पीपीटी, hindi alphabet PPT presentation, hindi varnamala PPT, Hindi Varnamala pdf, हिंदी स्वर, हिंदी व्यंजन, sikhiye hindi varnmala, dr. mulla adam ali, hindi language and literature, hindi alphabet with drawing, hindi alphabet pdf, hindi varnamala for childrens, hindi language, hindi varnamala practice for kids, https://www.drmullaadamali.com
Temple of Asclepius in Thrace. Excavation resultsKrassimira Luka
The temple and the sanctuary around were dedicated to Asklepios Zmidrenus. This name has been known since 1875 when an inscription dedicated to him was discovered in Rome. The inscription is dated in 227 AD and was left by soldiers originating from the city of Philippopolis (modern Plovdiv).
বাংলাদেশের অর্থনৈতিক সমীক্ষা ২০২৪ [Bangladesh Economic Review 2024 Bangla.pdf] কম্পিউটার , ট্যাব ও স্মার্ট ফোন ভার্সন সহ সম্পূর্ণ বাংলা ই-বুক বা pdf বই " সুচিপত্র ...বুকমার্ক মেনু 🔖 ও হাইপার লিংক মেনু 📝👆 যুক্ত ..
আমাদের সবার জন্য খুব খুব গুরুত্বপূর্ণ একটি বই ..বিসিএস, ব্যাংক, ইউনিভার্সিটি ভর্তি ও যে কোন প্রতিযোগিতা মূলক পরীক্ষার জন্য এর খুব ইম্পরট্যান্ট একটি বিষয় ...তাছাড়া বাংলাদেশের সাম্প্রতিক যে কোন ডাটা বা তথ্য এই বইতে পাবেন ...
তাই একজন নাগরিক হিসাবে এই তথ্য গুলো আপনার জানা প্রয়োজন ...।
বিসিএস ও ব্যাংক এর লিখিত পরীক্ষা ...+এছাড়া মাধ্যমিক ও উচ্চমাধ্যমিকের স্টুডেন্টদের জন্য অনেক কাজে আসবে ...
Philippine Edukasyong Pantahanan at Pangkabuhayan (EPP) CurriculumMJDuyan
(𝐓𝐋𝐄 𝟏𝟎𝟎) (𝐋𝐞𝐬𝐬𝐨𝐧 𝟏)-𝐏𝐫𝐞𝐥𝐢𝐦𝐬
𝐃𝐢𝐬𝐜𝐮𝐬𝐬 𝐭𝐡𝐞 𝐄𝐏𝐏 𝐂𝐮𝐫𝐫𝐢𝐜𝐮𝐥𝐮𝐦 𝐢𝐧 𝐭𝐡𝐞 𝐏𝐡𝐢𝐥𝐢𝐩𝐩𝐢𝐧𝐞𝐬:
- Understand the goals and objectives of the Edukasyong Pantahanan at Pangkabuhayan (EPP) curriculum, recognizing its importance in fostering practical life skills and values among students. Students will also be able to identify the key components and subjects covered, such as agriculture, home economics, industrial arts, and information and communication technology.
𝐄𝐱𝐩𝐥𝐚𝐢𝐧 𝐭𝐡𝐞 𝐍𝐚𝐭𝐮𝐫𝐞 𝐚𝐧𝐝 𝐒𝐜𝐨𝐩𝐞 𝐨𝐟 𝐚𝐧 𝐄𝐧𝐭𝐫𝐞𝐩𝐫𝐞𝐧𝐞𝐮𝐫:
-Define entrepreneurship, distinguishing it from general business activities by emphasizing its focus on innovation, risk-taking, and value creation. Students will describe the characteristics and traits of successful entrepreneurs, including their roles and responsibilities, and discuss the broader economic and social impacts of entrepreneurial activities on both local and global scales.
Communicating effectively and consistently with students can help them feel at ease during their learning experience and provide the instructor with a communication trail to track the course's progress. This workshop will take you through constructing an engaging course container to facilitate effective communication.
Constructing Your Course Container for Effective Communication
Deep Foundations of Concept Mapping (pdf)
1. Information structures:
the essential deep foundation
of concept mapping
Argument mapping
Info-structure mapping
Syntactic mapping
Association mapping
Grammar mapping (pseudo)
Lawrie Hunter
Kochi University of Technology
http://lawriehunter.com
2. No need to take notes (:^0)
All materials can be downloaded
from Hunter’s websites
http://lawriehunter/
http://www.core.kochi-tech.ac.jp/hunter/
or
http://slideshare.net/rolenzo/
9. Uses of mapping
uses of
mapping
mindless witting
principles of
map use?
10. Uses of mapping
uses of
mapping
witting
Information principles of
types map use?
Language
patterns
11. Part 1: the main styles of mapping
Part 2: matching mapping styles to
instructional purposes
(1) Novakian mapping, using Cmap tools
(2) Hunter's infostructure mapping,
using PowerPoint.
Part 3: deciding mode:
electronic vs. hand made
Part 4: using mapping to push the learner
to the use of specific
language forms and patterns
12. Part 1:
the main styles of mapping
Grammar maps (not maps)
Association maps
Syntactic maps
Information structure maps
Argument maps
Rhetorical structure maps
13. Part 1:
the main styles of mapping
Grammar maps (not maps) Argument mapping
Association maps Info-structure mapping
Syntactic maps
Syntactic mapping
Information structure maps
Argument maps Association mapping
Rhetorical structure maps Grammar mapping (pseudo)
25. RST mapping
Bill Mann’s Rhetorical Structure Theory (RST)
uses various sorts of "building blocks" to describe texts.
The principal block type deals with "nuclearity" and "relations"
(often called coherence relations in the linguistic literature.)
www.sil.org/~mannb/rst/
RST links are rhetorical devices.
26. Beyond assocation: Novakian
“The basic Novakian concept map...
usually starts with a general concept
at the top of the map, and then
works its way down ... to more specific concepts.
Concepts are placed in [boxes]...
Lines are drawn from a concept
to a linking word to a concept.
Sequences of concepts and linking words
do not always form grammatically correct sentences.”
Abrams, R. An Overview of Concept Mapping. In
Meaningful Learning: A Collaborative Literature Review of Concept Mapping. Retrieved
March 18, 2008 at http://www2.ucsc.edu/mlrg/clr-conceptmapping.html
28. Novakian maps (Novak & Cañas, 2006)
can be used at any level of abstraction.
Argument mapping
Information structure mapping
Syntactic mapping
Grammatical mapping (pseudo)
Association mapping
Figure: quantum levels of abstraction.
From Hunter (2007)
29. Hunter’s ISmaps
have
graphical
links
ISmaps
ISmaps
correspond to
information
structure
elements syntactic semantic transcend
mapping mapping pragmatic
barriers
pragmatics’
miniworld <
broad
ISmaps’
range
39. Use the ISmap links to map text.
Description Classification
Degree Attribute
comparison comparison
<
big
Contrast
! Sequence Cause-effect
40. Power generating systems
General Boil a Make Rotate Generate
process: liquid steam turbines electricity
seawater fossil or
heat boil boil N-heat
NH3 ! H2O
OTEC older type
steam steam
plants
20C ! 500C
plants
low high
power ! power
zero high
energy cost energy cost
hunter systems
41. Comparison of Novakian and
information structure mapping
Novakian mapping, Hunter's ISmapping,
using Cmap tools, vs. using PowerPoint
a free and very usable software or other graphical software.
with web sharing built in.
Make a Cmap and an ISmap of this text:
Yon sama, a Korean actor,
is younger and more handsome than
Tokoro Joji, a Japanese TV personality.
42. an ISmap of the text:
actor TV personality
Korean Japanese
Tokoro
Yon sama
Joji
>
young
handsome
huntersystems
44. Part 2:
matching mapping styles
to instructional purposes
Representations of the information structures
underlying the witting use of maps:
Writers work with
Rhetorical structure
Argument structure
Information structure
Text structure
Paragraph structure
Sentence structure
45. Part 2:
matching mapping styles
to instructional purposes
Representations of the information structures
underlying the witting use of maps:
Writers work with Mappers make
Rhetorical structure Rhetorical structure maps
Argument structure Argument maps
Information structure Information structure maps
Text structure mystery Association maps
Paragraph structure zone Syntactic maps
Sentence structure Grammar maps (not maps)
46. Mapping decision matrix
Software vs. tangibles
Training
________________________ Mapping type
Training Constraint
-extensive contained warmups
-for Teacher's observation
-L's need support?
-L's need constraint?
-for peer commenting
-look quickly at shapes only
-look carefully at node content and links
47. Mapping decision matrix
Software vs. tangibles
Training
mind maps
Mapping type
relation maps
________________________ Constraint
structure maps
Mapping type
-mind maps
-relation maps (Novakian)
-structure maps
48. Mapping decision matrix
Software vs. tangibles
Training
mind maps
Mapping type
relation maps
________________________ Constraint
structure maps
Mapping type
1. Mind maps
-for amassing 'thoughts'
-relations only by association
-for rearranging, clustering, prioritizing (software good
for this)
49. Mapping decision matrix
Software vs. tangibles
Training
mind maps
________________________ Mapping type
relation maps
Mapping type Constraint
structure maps
2. Relation maps (Novakian maps)
-for relating concepts in articulately related pairs
-CMC debate going on now:declarative reading or not?
50. Mapping decision matrix
Software vs. tangibles
Training
mind maps
________________________ Mapping type
relation maps
Mapping type Constraint
structure maps
3. Structure maps (e.g. ISmaps)
-for representation of syntactic structures at the level of
-sentence
-paragraph
-short technical summary articles
-not necessarily one unified map
-background information may be
-a separate map
-a layer (font color, sidebar, etc.)
-persuasion may be 'picture frames' or title bars or submaps
51. Mapping decision matrix
Software vs. tangibles
Training
mind maps
________________________ Mapping type
relation maps
Mapping type Constraint
structure maps
3. Structure maps (e.g. ISmaps)
-for representation of syntactic structures at the level of
-sentence
-paragraph
-short technical summary articles
-not necessarily one unified map
-background information may be
-a separate map
-a layer (font color, sidebar, etc.)
-persuasion may be 'picture frames' or title bars or submaps
52. Mapping decision matrix
Software vs. tangibles
Training
________________________ Mapping type
structural
Constraint Constraint
rhetorical
relational
1. Architectural constraint
- by size
- by content
2. Rhetorical constraint
-by rhetorical device limitations
3. Relational constraint
-by Novakianism
53. Part 3:
Software vs. tangibles
Training
deciding mode: Mapping type
electronic vs. hand made
Constraint
Software vs. tangibles
-tangibles first
-because quick
-to encourage revisions (paper is cheap)
-software for presentation, sharing, editing, beauty
54. Part 4:
using mapping to push the learner
to the use of
specific language forms and patterns
Using four types of task constraint
which reduce to easily manageable task design elements:
architectural constraint (number of nodes, etc.)
rhetorical constraint (type of links)
relational constraint (nature of links)
degree of abstraction (rhetorical distance) (not today)
55. Pushing the learner
Software vs. tangibles
Training
________________________ Mapping type
architectural
Constraint Constraint
rhetorical
relational
1. Architectural constraint
- by size (number of nodes)
- by content (e.g. only noun phrases)
56. Pushing the learner
Software vs. tangibles
Training
________________________ Mapping type
architectural
Constraint Constraint
rhetorical
relational
2. Rhetorical constraint
-by rhetorical device limitations
-e.g. in a rhetorical structure map,
only allow argument moves as link content
57. Pushing the learner
Software vs. tangibles
Training
________________________ Mapping type
architectural
Constraint Constraint
rhetorical
relational
3. Relational constraint:
-by Novakianism
i.e. restrict linking phrase content
e.g. only verbs
e.g. only action verbs
e.g. only information structure signals
(classification, comparison, sequence, cause-effect)
58. Hunter’s framework
Key content Background Persuasion
Rhetorical
structure
Information
organization
Information
structures
59. Hunter’s framework
Key content Background Persuasion
Rhetorical
structure
Information
organization
Information
structures
60. Thank you for your kind attention,
and thank you in advance
for your feedback and suggestions.
Lawrie Hunter
downloads from
http://lawriehunter.com
view and download at
http://slideshare.net/rolenzo
61. Information structures: The essential deep foundation of concept mapping
Abstract ideals vs. do-able realities
Selected domain for this paper: mapping/concept mapping/argument mapping
Concept mapping and concept mapping software have taken solid hold in many realms of education in many countries, primarily
for use in representing learner and instructor perceptions of the interrelations between concepts. However, it is not so easy to design
effective and motivating mapping tasks, or to choose the appropriate type of mapping for a task/project/curriculum. This paper sets
out a set of conceptual tools for the witting use of mapping in curriculum and materials design.
These central questions are addressed:
(1) Which kind of mapping to use for different instructional purposes;
(2) When to do mapping electronically and when by hand; and
(3) How to create curriculum and materials that go beyond "I do mapping in my class" to lead the learner to the use of the specific
language forms and patterns appropriate to each type of information.
This paper identifies mapping types and information structures underlying the witting use of maps: rhetorical structure, text
structure, paragraph structure and sentence structure. Without incorporating these structures in the framing of task design, the
instructor/designer will not be able to control the form of learner output.
This is followed by an analysis of the information-related character of two salient styles of mapping:
(1) Novakian mapping, which is the most commonly used mapping in science education today; and
(2) Hunter's infostructure mapping, which is a very limited (and thus effective) mapping style for second language learning
technical-oriented tasks.
The conclusion includes a description of four types of task constraint which the author has developed for mapping in the teaching of
entry and upper advanced EFL technical writing. These constraint types, which reduce to easily manageable task design elements,
are: map size; allowable links; rhetorical devices; and degree of abstraction.
Biodata: Lawrie Hunter is a professor at Kochi University of Technology. His infostructure maps provide the underlying structure
of "Critical Thinking" (Greene & Hunter, Asahi Press 2002) and "Thinking in English" (Hunter, Cengage 2008).
http://www.core.kochi-tech.ac.jp/hunter/
62. The age of
GRAPHIC ORGANIZERS
Suggested Reading About Visual Thinking and Learning
Ausubel, D. (1968). Educational psychology: A cognitive view. New York: Holt, Reinhart and Winston.
Buzan, T. & Buzan, B. (1993). The mind map book: How to use radiant thinking to maximize your
brain's untapped potential. New York: Penguin Books USA Inc.
Buzan, T. (1983). Use both sides of your brain: New techniques to help you read efficiently, study
effectively, solve problems, remember more, think clearly. New York: E.P. Dutton.
Jonassen, D.H. (1996). Computers in the classroom: Mindtools for critical thinking. Englewood Cliffs,
NJ. Prentice-Hall, Inc.
Novak, J.D. & Gowin, D.B. (1984). Learning how to learn. New York: Cambridge University Press.
Novak, J.D. (1998). Learning, creating and using knowledge: Concept map® as facilitative tools in
schools and corporations. Mahwah, NJ: Lawrence Erlbaum Associates, Inc.
http://www.inspiration.com/Parents/Visual-Thinking-and-Learning