what is pattern generalisation and abstraction in computational thinking

In Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, Long Beach, CA, USA, 1520 June 2019; pp. 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. Recognising patterns things that are common between problems or programs is one of the key aspects of computational thinking. Identifying patterns means that there is probably an existing solution already out there. Papadakis, S., Kalogiannakis, M., Orfanakis, V., & Zaranis, N. (2019). Learn more about abstraction in computational thinking by downloading our free guide for educators: The Ultimate Guide to Computational Thinking for Educators. In essence, computational thinking is a set of tools or strategies for solving complex problems that relates to mathematical thinking in its use of abstraction, decomposition, measurement and modeling. Based on HAE and DRB, we construct a fast and efficient underwater image enhancement network. What are the patterns we can recognize? Once you have identified a pattern you can speculate whether it can be reused in your existing program, or used in another program. endstream endobj 70 0 obj <> endobj 71 0 obj <> endobj 72 0 obj <>stream Provided by the Springer Nature SharedIt content-sharing initiative, Over 10 million scientific documents at your fingertips, Not logged in In Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, Honolulu, HI, USA, 2126 July 2017; pp. The object detection test was performed before and after the FE-GAN processing. I can communicate the key features of problems and processes to others. Mathematics: Students conduct a survey of peers and analyze the data to note the key findings, create visualizations, present the findings. 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. All rights reserved. The Singapore 2103 primary curriculum uses the term "algorithm" 26 times, and every single time it is in explicit reference to learning or practising the standard arithmetic algorithms. 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. It does not land on any spaces in between these squares. Through structural re-parameterization, we equate complex modules to simple convolutional layers, which accelerates the model during inference while maintaining a good enhancement effect. Data are the raw facts or observations of nature and computation is the manipulation of data by some systematic procedure carried out by some computing agent. I can describe problems and processes as a set of structured steps. As technology continues to become more and Texas schools have big changes on the horizon when it comes to digital skills. Zhang, L.; Li, C.; Sun, H. Object detection/tracking toward underwater photographs by remotely operated vehicles (ROVs). Aggarwal, A.; Mittal, M.; Battineni, G. Generative adversarial network: An overview of theory and applications. The second step of the computational solution, Algorithmic Expression, is the heart of computational problem solving. articles published under an open access Creative Common CC BY license, any part of the article may be reused without Li, H.; Zhuang, P. DewaterNet: A fusion adversarial real underwater image enhancement network. Decomposition and pattern recognition broke down the complex, and abstraction figures out how to work with the different parts efficiently and accurately. In the Aquarium Combined dataset, there are seven types of targets to be detected: fish, jellyfish, penguin, puffin, shark, starfish, and stingray. A Medium publication sharing concepts, ideas and codes. hb```f``*c`e` B@16L< Packed with plugged and unplugged examples, this guide will give you a foundational understanding of computational thinking and the confidence to address this topic with students. [. Akkaynak, D.; Treibitz, T. A revised underwater image formation model. Your alarm on your smart phone wakes you in the morningthats powered by computer science. British Machine Vision Conference (BMVC), London, UK, 47 September 2017; Volume 1. 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. You can even think of it as an alternative definition of critical thinking or evidence-based reasoning where your solutions result from the data and how you think about that data: Data + How to Think about that Data = Computational Thinking. Lulu.com, Griffith University, Gold Coast, Australia, You can also search for this author in 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. This pattern can then be applied to any systems that tracks and monitors student data, including attendance, punctuality and recording homework marks. 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. Editors select a small number of articles recently published in the journal that they believe will be particularly New diseases can also be categorized and have cures, treatments, or preventions identified based on pattern recognition from other corresponding medical complications. In this activity we will engage participants in a text compression exercise. Abstraction means hiding the complexity of something away from the thing that is going to be using it. UIQM is expressed as a linear combination of these three indexes. Cognitive fit: A theory based analysis of the graphs versus tables literature. Of course not, your computer just turns itself on. 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. Beaver neighbourhoods consist of rivers running between ponds. and Y.W. Another system might record, present, planned absence, unplanned absence and late. 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. If youre able to make repeated, precise, quantitative predictions, it implies that whichever model youve used or whichever mode of thinking youve employed, its actually working and should likely be re-employed. We can also generalize to form a big picture that ignores some of the inessential details. 7mNqp6obL -|.g`3~iwnq/d=1An<5a}$eLiYL#iACoF_DM@0uJLSf!i`H>/ 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. Can you identify all the general terms that you would need for this program to securely manage your timetable and your homework? Or if you see a consistent trend upward in a stock for a number of months, you might decide to buy some shares in that stock. 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. These images were taken in a poor light environment, and the overall number of this dataset is small, which brings a certain degree of difficulty to training. 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. UIQM expresses as follows: In the ImageNet dataset, we randomly selected 5500 pairs of images for training and the remaining 628 pairs for testing. In Proceeding 2000 IEEE international symposium on visual languages (pp. 5: 1227. Copyright Learning.com 2023. Feature papers represent the most advanced research with significant potential for high impact in the field. In Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, Salt Lake City, UT, USA, 1823 June 2018; pp. This process occurs through filtering out the extraneous and irrelevant in order to identify whats most important and connects each decomposed problem. Filter out information you do not need and be able to justify this. (2023). For example, when you press the power button on your computer, do you know what is going on? To do this, they type the students surname, click enter, and information is displayed. 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. Abstraction helps students return to the larger problem that prompted this whole computational . School of Information Engineering, Wuhan University of Technology, Wuhan 430070, China, Hubei Key Laboratory of Broadband Wireless Communication and Sensor Networks, Wuhan 430070, China, National Deep Sea Center, Qingdao 266237, China. Cognition and Instruction, 8(4), 293332. Pattern recognition in problem solving is key to determining appropriate solutions to problems and knowing how to solve certain types of problems. Pattern recognition is prominent in medicine, where identifying patterns helps to diagnose and cure diseases as well as to understand and prevent disease. For the Mixed dataset, we selected Test-R90 (90 paired images) and Test-C60 (60 unpaired images) as the test sets of paired and unpaired images respectively and compared them with the same methods in qualitative evaluation. Sun, S.; Wang, H.; Zhang, H.; Li, M.; Xiang, M.; Luo, C.; Ren, P. Underwater image enhancement with reinforcement learning. <> Seeing is understanding: The effect of visualisation in understanding programming concepts. Enhancing underwater imagery using generative adversarial networks. Computational thinking is a problem-solving skill set that is used to tackle problems in computer science. This can be seen further here. Islam, M.J.; Xia, Y.; Sattar, J. As technology continues to become more and Texas schools have big changes on the horizon when it comes to digital skills. It then connects each decomposed problem to establish a complete solution. The pattern recognition in each area provides a scaffold for the total solution. 820827. Next, we will try to optimize more network modules with structural reparameterization to improve the enhancement effect of the model on images with insufficient brightness, and focus on the practical application in underwater object detection and scene analysis. Li, Y.; Lu, H.; Zhang, L.; Li, J.; Serikawa, S. Real-time visualization system for deep-sea surveying. hbbd```b`` 172179). One system might simply record present and absent. 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. In computational thinking, one of the integral steps to the problem-solving process is pattern recognition. In Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, New Orleans, LA, USA, 21 June 2022; pp. [, In recent years, deep learning gradually occupied a leading position in the field of computer vision with its high plasticity and universality. 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. Your home for data science. Like the other elements of computational thinking, abstraction occurs inherently and can be addressed throughout the curriculum with students. Please note, this is not a comprehensive listing but is representative. We will share this in the workshop and discuss under the pattern recognition lens. Another example of abstraction might be creating a summary of a book or movie. Think of your two favourite games. Li, C.; Anwar, S.; Hou, J.; Cong, R.; Guo, C.; Ren, W. Underwater Image Enhancement via Medium Transmission-Guided Multi-Color Space Embedding. Element interactivity and intrinsic, extraneous, and germane cognitive load. If the problem is some complex task, you might break it down into a sequence of simpler sub-tasks. Its very clever.. Through the learning of paired images, FE-GAN achieved end-to-end underwater image enhancement, which effectively improved the image quality. There is not a single reference to "algorithmic thinking" or "computational thinking". 5 0 obj 2023; 12(5):1227. 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. Correspondence to Here are some ideas. All representations of a thing are inherently abstract. Using a Google public data site we ask participants to interpret visualization from the data. Cognitive characteristics of learning Java, an object-oriented programming language. Identify the information required to solve a problem. "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. Sinha, A., & Vessey, I. 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. For 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. Circuits Syst. hko Experiments on different datasets show that the enhanced image can achieve higher PSNR and SSIM values, and the mAP value also achieved significant results in the object detection task. The process of computational thinking typically includes four parts: decomposition, pattern recognition, abstraction and algorithmic thinking. A . Most participants will have navigated their way to this workshop and this is in itself a pattern recognition issues, mostly a transportation problem and an algorithmic design component as well. 67236732. and J.Z. You may or may not be set homework for a particular lesson. 28492857. Its a drawing of a pipe. Any structured thinking process or approach that lets you get to this state would be considered computational thinking. In this paper, we proposed an underwater image enhancement model based on a conditional generative adversarial network. Jaffe, J.S. those of the individual author(s) and contributor(s) and not of MDPI and/or the editor(s). In this sense, being able to represent the data and then manipulate it is itself a computational solution to a computable problem! Abstraction helps students return to the larger problem that prompted this whole computational thinking adventure and identify the most important details from the earlier phases. Berman, D.; Levy, D.; Avidan, S.; Treibitz, T. Underwater single image color restoration using haze-lines and a new quantitative dataset. Zhou, Y.; Yan, K.; Li, X. - 67.227.236.71. Educators use abstraction when looking at vast sets of student data to focus on the most relevant numbers and trends. Cognitive Science, 12(2), 257285. ; Zhao, X.; Cosman, P.C. Can you spot any patterns about the patterns? The materials for this session is slightly different than the the other three sessions and this is intentional. As it sounds, pattern recognition is all about recognizing patterns. What is the best way to present the information. T3Rd2Rz|?&$xALr+(^@0%L9&cKHin)68L;R0#i,)1T8Nm43BfXf!{Wr|W]i}99)>l>cfkWW"Mi%,TrIKO|H Information not needed is gender, age and date of birth as all this will be obtained from the student search. All cats have similar characteristics. https://doi.org/10.3390/electronics12051227, Han, Jie, Jian Zhou, Lin Wang, Yu Wang, and Zhongjun Ding. in [, We used Pytorch 1.8.0 to implement the FE-GAN model. Different loss functions based on texture and content are combined with weights to constrain the generator and discriminator. PSNR is an index used in the image field to measure the quality of reconstructed images, which is defined by taking the logarithm of MSE (mean squared error). Due to the limitation of memory, all pictures were resized to. Pattern recognition is the idea of spotting similarities or trends or regularities of some sort in a problem or some dataset. For example, you might want to search for a student in a school IMS. With the research and application of AUVs (autonomous underwater vehicles) and ROVs (remote operated vehicles), ocean exploration has achieved many breakthrough results. Decision Sciences, 22(2), 219240. The aim is to provide a snapshot of some of the Decomposition breaks down problems into smaller, more manageable parts. Patterns are things that are the same within a problem and between problems. We dont care HOW they do them only that they work. This data will be saved in a database. xJSmSr!@67gQ Ai Ever find yourself saying, 'where have I seen this before', could be a significant step in computational thinking. Here are some ideas. https://doi.org/10.3390/electronics12051227, Han J, Zhou J, Wang L, Wang Y, Ding Z. FE-GAN: Fast and Efficient Underwater Image Enhancement Model Based on Conditional GAN. English Language Arts Students summarize a novel into a book review. What's Next? All cats have a tail, eyes and fur, and also eat fish and meow. You are accessing a machine-readable page. and Z.D. Check out our articles on decomposition, pattern recognition, and algorithmic thinking. Liu, X.; Gao, Z.; Chen, B.M. Computational thinking is a problem-solving skill that develops an algorithm, or series of steps to perform a task or solve a problem. Disclaimer/Publishers Note: The statements, opinions and data contained in all publications are solely In pursuing digital learning communities, she has worked with several hundred educators to tell their stories and share their insights via online publications. Anna is passionate about helping educators leverage technology to connect with and learn from each other. They constitute a way of reasoning or thinking logically and methodically about solving any problem in any area! Arts: Students generalize chord progressions for common musical genres into a set of general principles they can communicate. Using a public data set we will examine patterns in data and visualize or describe the patterns. [V9F oCt;pWtDC;m2VOr(xO RA 6Dlo$Qa& Ve ypW# A2Hl (GuzA /K 44809}$LXz#? Du, Z.; Liu, D.; Liu, J.; Tang, J.; Wu, G.; Fu, L. Fast and Memory-Efficient Network Towards Efficient Image Super-Resolution. Will the data patterns provide a part of the solution to the problem? Zhang, H.; Zhang, S.; Wang, Y.; Liu, Y.; Yang, Y.; Zhou, T.; Bian, H. Subsea pipeline leak inspection by autonomous underwater vehicle. Two different Student IMS systems might have different ways of taking a register. 49524956. 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. In the case of insufficient natural light, the image obtained with the artificial light source itself is extremely distorted. It is mainly composed of three parts: luminance, contrast, and structure contrast. Once you have identified a pattern, you can now start to describe it. 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. This process occurs through filtering out irrelevant information and identifying whats most important. PubMedGoogle Scholar. We conducted feature fusion experiments between the encoder and decoder utilizing concatenate and aggregation, respectively. Fatan, M.; Daliri, M.R. This data will also be output as a Percentage Attendance score for each student. Relating natural language aptitude to individual differences in learning programming languages. Information is the result of processing data by putting it in a particular context to reveal its meaning. [. Several aspects should be taken into consideration, such as FLOPs, number of parameters, and inference time during deploying on resource-limited devices. (1992). Editors Choice articles are based on recommendations by the scientific editors of MDPI journals from around the world. QT%^[g5XM.GTFySXX;S$[+?D@_[6E[jmYWNM~jxIoVx2I#UP$0mq'J"e'i[t4B/vdZciYh;'@3B$u$Wq|"60(puvCU In this lesson, we will learn about the process of identifying common patterns in a Program including: Patterns exist everywhere. Vessey, I. All of these are needed to come up with the eventual computational solution to the problem. 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.