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11251134. The main contributions of this paper are as follows: We present a hierarchical attention encoder (HAE) to fully extract texture detail information, and a dual residual block (DRB) can more efficiently utilize residual learning to accelerate network inference. Under the same experimental conditions, the test results using the aggregation operation method perform better in both PSNR and SSIM values. Using UICM (color measurement index), UISM (sharpness measurement index), UIConM (contrast measurement index) as the evaluation basis. So to summarise what we have learned in this lesson: Pattern Recognition, Generalisation & Abstraction, https://www.tutorialspoint.com/design_pattern/design_pattern_overview.htm, Representing parts of a problem or system in general terms, It will be broken up into a number of lessons of a set length, You will have a lesson with a teacher and the teacher will take a register. It hides the underlying complexity in a programming language, which makes it simpler to implement algorithms and communicate with digital tools. Using the cognitive walkthrough to improve the design of a visual programming experiment. The green and blue light with a shorter wavelength will travel farther [, Many scholars have carried out in-depth research on the scattering phenomenon of light propagating in the medium. Circuits Syst. Pattern generalisation is spotting things that are common between patterns. ; Constants - this will be something that is likely to remain fixed for a while, e.g. Over the last several years, many AUVs and ROVs have been applied to ship hull inspection, underwater target detection and tracking [, Natural light is absorbed and scattered when propagating in seawater. A, Algorithmic Expression: We then need to find an algorithm, a precise sequence of steps, that solves the problem using appropriate data representations. To further verify the generalization ability of FE-GAN, we selected 990 images from the artificially synthesized dataset for testing and compared them with the corresponding ground truth images. Refs. This process occurs through filtering out irrelevant information and identifying whats most important. In Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, Long Beach, CA, USA, 1520 June 2019; pp. It works by establishing a level of complexity on which a person interacts with the system, suppressing the more complex details below the current level. We can represent parts of a system in general terms, including Variables, Constants, Key Processes, repeated Processes, Inputs and Outputs. 797819). We can also codify this information in some knowledge-based system that is curated using knowledge management techniques. This helps the programmer to save time reinventing the wheel when a solution to a given problem may already exist. In: Keane, T., Fluck, A.E. EasyTech Wins Tech & Learning Awards of Excellence: Best of 2022, How One School District is Driving Digital Wellness in Students (& How to Join), What is Digital Literacy: Definition and Uses in Daily Life, Texas Technology Standards: Big Changes Need Big Solutions, Definition of Computer Science, Computational Thinking and Coding, Get Creative with Professional Development for Technology Integration. IEEE Trans. Based on HAE and DRB, we construct a fast and efficient underwater image enhancement network. Students create a personal guide that dictates when to use the formal and informal you in Spanish class or the two to know verbs in French, which, mind you, always confounded me. [V9F oCt;pWtDC;m2VOr(xO RA 6Dlo$Qa& Ve ypW# A2Hl (GuzA /K 44809}$LXz#? captured are operated to obtain the clear images as the desired output [. The task of baking chocolate chip cookies highlights some common elements that you need to know to be . Disclaimer/Publishers Note: The statements, opinions and data contained in all publications are solely All cats have a tail, eyes and fur, and also eat fish and meow. They constitute a way of reasoning or thinking logically and methodically about solving any problem in any area! The One About Abstraction in Computational Thinking. Patterns are pieces or sequences of data that have one or multiple similarities. For them to use technology responsibly, safely and effectively, they need to understand the Digital literacy encompasses the skills required to use technology safely, effectively and responsibly. All rights reserved. enables us to navigate complex problems more effectively while helping to find relevance and clarity at scale. Social Studies: Students coalesce the most important details shared in articles about a specific current event and write a brief about the event. 2023. Recognising patterns things that are common between problems or programs is one of the key aspects of computational thinking. permission is required to reuse all or part of the article published by MDPI, including figures and tables. Disclaimer: correlation does not equal causation; even if you spot a pattern, you might want to confirm or validate that prediction with other analyses before actually putting your money where your pattern is. In which of the following neighbourhoods is Patricia unable to build her dam? Another way to think about abstraction is in the context of those big concepts that inform how we think about the world like Newtons Laws of Motion, the Law of Supply and Demand, or the Pythagorean Theorem. This is a similar problem to bringing utilities to each home, a situation engineers face when building communities. Consider early arithmetic patterns for addition and multiplication using time tables. A sequential network can avoid frequently visiting additional nodes, which is beneficial for speeding up inference and reducing memory consumption. In pursuing digital learning communities, she has worked with several hundred educators to tell their stories and share their insights via online publications. For example, when you press the power button on your computer, do you know what is going on? See further details. Abstraction is an essential part of computational thinking. Learn more about abstraction in computational thinking by downloading our free guide for educators: The Ultimate Guide to Computational Thinking for Educators. https://doi.org/10.1007/978-3-031-21970-2_26, Shipping restrictions may apply, check to see if you are impacted, http://rigaux.org/language-study/diagram.html, Tax calculation will be finalised during checkout. "K/S-M?8 dy"pq!mrb";IRPO^~/.O8`b[8rdjt`` FQ%lf0) SL ]($q_i9 V101gc`M`8*bZA`oae97fL>,v@S2p2BLH3qk3pt)@R y c_ Results on different datasets prove that the model also has good generalization ability. To summarise abstraction is the gathering of the general characteristics we need and the filtering out of the details and characteristics that we do not need.. A website providing comprehensive coverage of computer programming. For I can break down problems and processes into distinct steps. Underwater optical imaging: The past, the present, and the prospects. Problem Specification: We start by analyzing the problem, stating it precisely, and establishing the criteria for the solution. Have a look at the following website about the Gang of Four design patterns https://www.tutorialspoint.com/design_pattern/design_pattern_overview.htm. This paper proposes a fast and efficient underwater image enhancement model based on conditional GAN with good generalization ability using aggregation strategies and concatenate operations to take full advantage of the limited hierarchical features. Two different Student IMS systems might have different ways of taking a register. We intend to develop computational thinking skills and Pattern Recognition is one of the 4 components, however we also want to emphasize that there are many examples where a computer or other devices may not be required. The second step of the computational solution, Algorithmic Expression, is the heart of computational problem solving. 71597165. Electronics 2023, 12, 1227. Pattern recognition is prominent in medicine, where identifying patterns helps to diagnose and cure diseases as well as to understand and prevent disease. Computational Thinking Steps: In order to make predictions using computational thinking, we need to define three steps related to the problem and its solution: I should add a little caveat here: these rules for computational thinking are all well and good but theyre not really rules, per se; instead, think of them more like well-intentioned heuristics, or rules of thumb. Liu, X.; Gao, Z.; Chen, B.M. Abstraction is similar to the selective filtering function in our brains that gates the neural signals with which we are constantly bombarded so we can make sense of our world and focus on whats essential to us. The Search for A Student process does not know that the Student Search Pattern connects to a database and gets a list, all it knows is that it gives the black box a surname, and gets back some results. List of Materials (all materials will be provided during the session). The new primary curriculum (up to Year 3) and the secondary . Now from this general knowledge of patterns in cats, we could draw the general outline of a cat. Tsarava, K., Moeller, K., Romn-Gonzlez, M., Golle, J., Leifheit, L., Butz, M. V., & Ninaus, M. (2022). It does not land on any spaces in between these squares. We apply the FE-GAN model to real and artificially synthesized underwater image datasets, process paired and unpaired distorted images, and compare them with the corresponding ground truth images. Formulas were created after patterns were identified and applied to create a common solution. We conducted feature fusion experiments between the encoder and decoder utilizing concatenate and aggregation, respectively. 49524956. All of these are needed to come up with the eventual computational solution to the problem. These essential principles are also the buzzwords you can put on your rsum or CV so lets first delve into an intuitive understanding of the more important ones, especially decomposition, pattern recognition, and abstraction, as well as its cousin, generalization. In addition, being able to identify the general principles that underly the patterns weve identified allows us to generalize patterns and trends into rules. School of Education, La Trobe University, Victoria, VIC, Australia, School of Education, University of Tasmania, Launceston, TAS, Australia, 2023 The Author(s), under exclusive license to Springer Nature Switzerland AG, Zagami, J. https://doi.org/10.3390/electronics12051227, Han, Jie, Jian Zhou, Lin Wang, Yu Wang, and Zhongjun Ding. Computational thinking is the process of defining a step-by-step solution to a complex problem or to achieve a specific goal. White, G. L. (2001). This data will also be output as a Percentage Attendance score for each student. Computational Thinking is a set of techniques for solving complex problems that can be classified into three steps: Problem Specification, Algorithmic Expression, and Solution Implementation & Evaluation.The principles involved in each step of the Computational Thinking approach are listed above and discussed in detail below. - 67.227.236.71. Abstraction in computational thinking enables us to navigate complexity and find relevance and clarity at scale. In Proceedings of the International Conference on Computer Vision, Venice, Italy, 2229 October 2017; pp. Like the other elements of computational thinking, abstraction occurs inherently and can be addressed throughout curriculum with students. ; Li, K.; Luan, X.; Song, D. Underwater image co-enhancement with correlation feature matching and joint learning. While pattern recognition is most commonly discussed as a step in computational thinking, we automatically use pattern recognition in our everyday lives. 2023; 12(5):1227. As technology continues to become more and Texas schools have big changes on the horizon when it comes to digital skills. Ever find yourself saying, 'where have I seen this before', could be a significant step in computational thinking. In learning, we often look for patterns that would aid in knowledge transfer and solving problems in a variety of subjects including languages, music and chemistry. Abstraction in computational thinking is a technique where we split individual parts of the program down into imaginary black boxes that carry out operations. This will give us a list of students with the specific surname, but the information brought back would include their first, middle and last name, and their year of registration. We will examine this in more detail with the lens of pattern recognition. Once you have identified a pattern, you can now start to describe it. Using a public data set we will examine patterns in data and visualize or describe the patterns. Aggarwal, A.; Mittal, M.; Battineni, G. Generative adversarial network: An overview of theory and applications. Simultaneously, our model conducted qualitative and quantitative analysis experiments on real underwater images and artificial synthetic image datasets respectively, which effectively demonstrates the generalization ability of the model. Underwater image enhancement with a deep residual framework. ; resources, J.Z. Theyre suggestions of ideas youll likely need or require for most efforts but its not some process to pigeonhole your thinking or approach to a solution. ; Wang, Z.; Paul Smolley, S. Least squares generative adversarial networks. But before we implement our solution in a particular programming language, we have to define an algorithmic solution for the problem were examining. Du, Z.; Liu, D.; Liu, J.; Tang, J.; Wu, G.; Fu, L. Fast and Memory-Efficient Network Towards Efficient Image Super-Resolution. That is, she wants to block a single river so that beavers will not be able to travel between all pairs of ponds in the neighbourhood. ; writingoriginal draft preparation, J.H. In the case of the school register, the input will be a Character entered against the student name It could be / or P if the student is present, and N, \ or L if they are not present. x}YaHao=3\u_D(n@2|E?400 F/>Kf9YU`Hldz,yw;?^CO=|~w~{/5n;p;6:6`~N9qs} It might be a new pattern that occurs several times in your own program, or it might exist elsewhere in other programs. IEEE Transactions on Software Engineering, 18(5), 368. It works by establishing a level of complexity on which a person interacts with the system, suppressing the more complex details below the current level. PubMedGoogle Scholar. (1991). Isola et al. Computational thinking is a problem-solving skill that develops an algorithm, or series of steps to perform a task or solve a problem. Pixel-level: Existing research shows that the, The model we proposed uses paired image training, and an objective function is constructed for this purpose to guide. Li, H.; Zhuang, P. DewaterNet: A fusion adversarial real underwater image enhancement network. Zhou, Y.; Yan, K.; Li, X. Abstraction in learning is the process of taking away or removing certain characteristics of a complex problem to reduce it to its most essential components. A couple of examples are iPad apps for junior school, and Blooms Taxonomy. It allows us to thus prioritize information about the system under examination. The results in the second, fifth, and last columns show that the fuzzy target can be detected in the processed image. Students conduct a survey of peers and analyze the data to note the key findings, create visualizations, present the findings. CrossRef When a patient discusses symptoms with a doctor or undergoes a series of tests, the results are compared against known patterns to quickly identify types of infections or injuries that may be causing the symptoms and to apply corresponding solutions to the diagnoses. Cognitive Science, 12(2), 257285. Arjovsky, M.; Chintala, S.; Bottou, L. Wasserstein generative adversarial networks. [. Akkaynak, D.; Treibitz, T. A revised underwater image formation model. [, Peng, Y.T. and J.Z. 2023 Springer Nature Switzerland AG. All of these required the people behind them to think about big, broad, and complex concepts; to break down the problem and to experiment; and to find patterns amongst the experimentations; and to eventually abstract this concrete knowledge to package it into these sterile statements that shelter us from the complexity and difficulty waded through to arrive at this law. Element interactivity and intrinsic, extraneous, and germane cognitive load. However, the training process of GAN is usually unstable. Any structured thinking process or approach that lets you get to this state would be considered computational thinking. The color, brightness, and contrast of the generated image were distinctly improved. These patterns can help solve the larger problem more effectively. The programmer works with an idealized interface (usually well defined . Filter out information you do not need and be able to justify this. Consider the student search system, it can be represented using the following terms: Variables - these are the values that will change - in this case the surname of a student. New diseases can also be categorized and have cures, treatments, or preventions identified based on pattern recognition from other corresponding medical complications. It then connects each decomposed problem to establish a complete solution. Introduction. After the socks have dried, you use pattern recognition in order to pair the socks back together. In software engineering and computer science, abstraction is a technique for arranging complexity of computer systems. Video Technol. In Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, Salt Lake City, UT, USA, 1823 June 2018; pp. It can also expand the difference between the features of different objects in the image, improve the image quality, enrich the amount of information, and strengthen the recognition effect. Incorporating computational thinking into how I think about and plan my design projects helps eliminate unnecessary paths that will not work, which is a time saver. Similar to the EUVP dataset, using the trained CycleGAN [, Due to the lack of real underwater images, Silberman et al. Editors select a small number of articles recently published in the journal that they believe will be particularly Although there is an algorithm where one method may be faster than another, pattern matching is a key to com posing the solution. Enhancing underwater imagery using generative adversarial networks. Through structural re-parameterization, we equate complex modules to simple convolutional layers, which accelerates the model during inference while maintaining a good enhancement effect. As students go through the learning process, they are exposed to many type of patterns and the early recognition of patterns is key to understanding many other more complex problems. "A$n1D2ldfH e/X,r,fAd5Xl>}A`0Y"XMX"Sn)2L@_\8Lw_ O Educators use abstraction when looking at vast sets of student data to focus on the most relevant numbers and trends. Anna is passionate about helping educators leverage technology to connect with and learn from each other. The application scenarios of most existing models are still very restricted, and it is rare to achieve good results in both real and synthetic underwater image datasets. Educational Psychology Review, 22, 123138. The latest iteration of Google Drive call Drive File Streaming is a prime example of how this can be applied to our entire datastore. Example 3: Everyone of us has done laundry, with all your clothes including socks. Copyright Learning.com 2023. I can describe problems and processes as a set of structured steps. 5 0 obj 172179). [, For the existing synthetic and real underwater image datasets, many GAN-based methods have been proven to have achieved good results in underwater image enhancement. "FE-GAN: Fast and Efficient Underwater Image Enhancement Model Based on Conditional GAN" Electronics 12, no. Another way to think about abstraction is in the context of those big concepts that inform how we think about the world like Newtons Laws of Motion, the Law of Supply and Demand, or the Pythagorean Theorem. Understanding abstraction enables students to make sense of problems they encounter, helping them to not be overwhelmed in the face of something complex and to persist, compute, iterate, and ideate. Another system might record, present, planned absence, unplanned absence and late. Please let us know what you think of our products and services. There may be kids running around the classroom or making loud noises, but they can tune that out to focus on what the kid in need is asking until of course it reaches an apex level of rambunctiousness and an intervention must be had. Cognition and Instruction, 8(4), 293332. Abstraction in coding and computer science is used to simplify strings of code into different functions. 27942802. Provided by the Springer Nature SharedIt content-sharing initiative, Over 10 million scientific documents at your fingertips, Not logged in For example, you might want to search for students in a class, or who are being taught by a specific teacher all these involve some form of searching, the only thing that differs is what you are searching for. Can you think of any generalisation of processes between the two? In Proceedings of the Seventh IEEE International Conference on Computer Vision, Kerkyra, Greece, 2027 September 1999; Volume 2, pp. 0 There is similarities to finding a shirt of your size in a clothing store. Draw a series of animals. Retrieved February 24, 2022, from http://rigaux.org/language-study/diagram.html. EasyTech Wins Tech & Learning Awards of Excellence: Best of 2022, How One School District is Driving Digital Wellness in Students (& How to Join), What is Digital Literacy: Definition and Uses in Daily Life, Texas Technology Standards: Big Changes Need Big Solutions, Definition of Computer Science, Computational Thinking and Coding, Get Creative with Professional Development for Technology Integration. % Our web-based curriculum for grades K-12 engages students as they learn keyboarding, online safety, applied productivity tools, computational thinking, coding and more. Our web-based curriculum for grades K-12 engages students as they learn keyboarding, online safety, applied productivity tools, computational thinking, coding and more. If the problem deals with a complex system, you might break the system down into a bunch of smaller sub-components. https://www.mdpi.com/openaccess. Although the brightness and details of the image enhanced by FE-GAN were restored partially, there is still a large gap from the image style under natural light, which is also the focus of future research. These are expressed as follows: UIQM is a non-referenced underwater image quality evaluation metric based on the human visual system excitation, mainly for the degradation mechanism and imaging characteristics of underwater images. This process uses inductive thinking and is needed for transferring a particular problem to a larger class of similar problems. Zhang, H.; Sun, L.; Wu, L.; Gu, K. DuGAN: An effective framework for underwater image enhancement. The elements can be broken down into inputs, processes and outputs. IEEE. Pattern recognition in problem solving is key to determining appropriate solutions to problems and knowing how to solve certain types of problems. Sun, S.; Wang, H.; Zhang, H.; Li, M.; Xiang, M.; Luo, C.; Ren, P. Underwater image enhancement with reinforcement learning. It was proposed by Ref. [. Google Scholar. Nevertheless, our model does not perform well in enhancing darker images, especially in recovering details and textures, which means that it is still challenging in deeper waters, where artificial light sources are needed. Its very clever.. Find support for a specific problem in the support section of our website. The programmer works with an idealized interface (usually well defined) and can add additional levels of functionality that would otherwise be too complex to handle. Lu, H.; Li, Y.; Zhang, L.; Serikawa, S. Contrast enhancement for images in turbid water. All authors have read and agreed to the published version of the manuscript. Cognitive load theory (Sweller, 1988) suggests that we each have a limited capacity to hold different concepts in 'working memory' when problem-solving, with the implication that when programming problems involve too many different elements, this capacity can be exceeded.Students will then have increasing difficulty in solving such problems. It then connects each decomposed problem to establish a complete solution. Pattern recognition in computational thinking uses the identification of similarities within a particular data set or sequence to simplify understanding and resolution of a problem or goal.