3rd International Workshop on Systems and Computing Inspired by Nature (SCIN) On September 6th-8th, 2024

At Onpa Hotel & Residence Bang Saen, Chonburi, Thailand

นายพิชัย ธรรมเสมา นักศึกษาปริญญาตรีชั้นปีที่ 4 หลักสูตรวิทยาศาสตรบัณฑิต สาขาวิชาวิทยาการสารสนเทศ เพื่อเศรษฐกิจดิจิทัล (หลักสูตรนานาชาติ) ได้ร่วมนำเสนอผลงานเรื่อง An Interactive Graph Website for Generative GraphLearner ในงาน 2024 SCIN

โดยผลงานวิจัยนี้เป็นส่วนหนึ่งของการเข้าร่วมฝึกงานโครงการทุนสหพันธ์สาธารณรัฐเยอรมนี ประจำปีการศึกษา 2566 ของนายพิชัย ธรรมเสมา ระดับปริญญาตรี ตั้งแต่เดือนเมษายนถึงเดือนมิถุนายน 2567 เดือน ณ Department of Communication Networks, FernUniversität, Hagen, Germany

Abstract: The GraphLearner website is focused on creating a seamless website that can both calculate the prediction result and display the graph for the user to observe to gain more insight. The program has functionality that lets users choose which range of data they want to focus on by using the range slider. The graph itself is also intractable, so if the users do not prefer to use a

range slider, they can also interact with the graph directly. For the framework, we utilize Flask for the backend and HTML, CSS, and JavaScript for the frontend. We also implement this program

to be able to convert the numeric data into the form of text and convert the text into numeral data too by using the external program that we created. In the first step, the user will input

the data, such as the root and number of branches. After that, the program will try to generate the next value based on the root value that it got. The data required for prediction comes from reinforcement learning and importing the CSV file into the learners. In the event that there is insufficient data, the GraphLearner will send an error message on the webpage to inform the users. When the program successfully makes predictions, the values will be passed on to the webpage as choices for the user to choose from. Lastly, the chosen node will be combined with the root value to create a sequence that can be used to reinforce learning or convert into text form, as mentioned above.

Systems and Computing Inspired by Nature (SCIN):

Nature has always been a source of inspiration for innovation and problem-solving. This workshop aims to explore the fascinating intersection between natural systems and computing technologies. By understanding and emulating nature's principles, we can design more efficient, sustainable, and adaptive computing systems. Through this workshop, participants will delve into the world of bio-inspired computing evolutionany algorithms, neural networks, and other computational techniques inspired by nature. The event will encourage interdisciplinary collaboration, fostering creativity, and sparking innovative ideas

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