• Journal of The Korean Society of Agricultural Engineers
• /
• v.66 no.4
• /
• pp.27-39
• /
• 2024

Soil texture is determined by the proportions of sand, silt, and clay within the soil, which influence characteristics such as porosity, water retention capacity, electrical conductivity (EC), and pH. Traditional classification of soil texture requires significant sample preparation including oven drying to remove organic matter and moisture, a process that is both time-consuming and costly. This study aims to explore an alternative method by developing an AI model capable of predicting soil texture from images of pre-sorted soil samples using computer vision and deep learning technologies. Soil samples collected from agricultural fields were pre-processed using sieve analysis and the images of each sample were acquired in a controlled studio environment using a smartphone camera. Color distribution ratios based on RGB values of the images were analyzed using the OpenCV library in Python. A convolutional neural network (CNN) model, built on PyTorch, was enhanced using Digital Image Processing (DIP) techniques and then trained across nine distinct conditions to evaluate its robustness and accuracy. The model has achieved an accuracy of over 80% in classifying the images of pre-sorted soil samples, as validated by the components of the confusion matrix and measurements of the F1 score, demonstrating its potential to replace traditional experimental methods for soil texture classification. By utilizing an easily accessible tool, significant time and cost savings can be expected compared to traditional methods.

• Journal of the Korea Society of Computer and Information
• /
• v.29 no.3
• /
• pp.117-125
• /
• 2024

In this paper, implement and propose an Active Electronically Scanned Array (AESA) radar integration analysis system which specialized for radar development by using heterogeneous media. Most analysis systems are used to analyze and improve the cause of defects, so they help the test easier. However, previous log analysis systems that operate only based on text are not intuitive and difficult to find the information user want at once if there is a lot of log information. so when an equipment defect occurs, there are limitations in analyzing the cause of defect. Therefore, the analysis system in this paper utilizes heterogeneous media. The media defined in this paper refers to recording text-based data, displaying data as image or video and visualizing data. The proposed analysis system classifies and stores data that transmitted and received between radar devices, radar target detection and Tracking algorithm data, etc. also displays and visualizes radar operation results and equipment defect information in real time. With this analysis system, it can quickly provide information what user want and assistance in developing high quality radar.

• The Journal of the Convergence on Culture Technology
• /
• v.10 no.2
• /
• pp.453-458
• /
• 2024

Optical Character Recognition is the technology that recognizes text in images and converts them into digital format. Deep learning-based OCR is being used in many industries with large quantities of recorded data due to its high recognition performance. To improve medical services, deep learning-based OCR was actively introduced by the medical industry. In this paper, we discussed trends in OCR engines and medical OCR and provided a roadmap for development of medical OCR. By using natural language processing on detected text data, current medical OCR has improved its recognition performance. However, there are limits to the recognition performance, especially for non-standard handwriting and modified text. To develop advanced medical OCR, databaseization of medical data, image pre-processing, and natural language processing are necessary.

• The Journal of the Institute of Internet, Broadcasting and Communication
• /
• v.24 no.3
• /
• pp.177-182
• /
• 2024

In this paper, the purpose of this paper is to predict and prevent the risk of crowd concentration in advance for possible future crowd accidents based on the Itaewon crush accident in Korea on October 29, 2022. In the case of a single CCTV, the administrator can determine the current situation in real time, but since the screen cannot be seen throughout the day, objects are detected using YOLOv4, which learns images taken with CCTV angle, and safety accidents due to crowd concentration are prevented by notification when the number of clusters exceeds. The reason for using the YOLO v4 model is that it improves with higher accuracy and faster speed than the previous YOLO model, making object detection techniques easier. This service will go through the process of testing with CCTV image data registered on the AI-Hub site. Currently, CCTVs have increased exponentially in Korea, and if they are applied to actual CCTVs, it is expected that various accidents, including accidents caused by crowd concentration in the future, can be prevented.

• Advances in nano research
• /
• v.16 no.3
• /
• pp.217-229
• /
• 2024

This paper presents results of visual analysis of cracks formation and propagation of concretes made of quaternary binders (QBC). A composition of the two most commonly used mineral additives, i.e. fly ash (FA) and silica fume (SF) in combination with nanosilica (nS), has been proposed as a partial replacement of the cement. The principal objective of the present study is to achieve information about the effect of simultaneous incorporation of three pozzolans as partial replacement to the OPC on the fracture processes in concretes made from quaternary binders (QBC). The modern and precise non-contact measurement method (NCMM) via digital image correlation (DIC) technique was used, during the studies. In the course of experiments it was established that the substitution of OPC with three pozzolans including the nanoadditive in FA+SF+nS FA+SF+nS combination causes a clear change of brittleness and behavior during fractures in QBCs. It was found that the shape of cracks in unmodified concrete was quasi-linear. Substitution of the binder by SCMs resulted in a slight heterogeneity of the structure of the QBC, including only SF and nS, and clear heterogeneity for concretes with the FA additive. In addition, as content of FA rises throughout each of QBC series, material becomes more ductile and shows less brittle failure. It means that an increase in the FA content in the concrete mix causes a significant change in fracture process in this composite in comparison to concrete with the addition of silica modifiers only.

• Journal of Korean Physical Therapy Science
• /
• v.31 no.1
• /
• pp.33-45
• /
• 2024

Background: This study aimed to investigate the effect of elastic band-resistive exercise using audio-visual medium on pain, proprioception, and motor function in adults with chronic neck and shoulder pain. Design: One group pretest-posttest follow-up experimental design. Method: Twenty adult women with neck and shoulder pain voluntarily participated in this study. Elastic band-resistive exercise using audio-visual medium including cervical flexion and extension, shoulder external rotation, and scapular retraction-protraction motions was conducted 5 times a week for 3 weeks. The Numerical Rating Scale, pressure threshold tool, CROM goniometer, and Image J software were used to assess subjective pain level, tenderness threshold (pain), joint position sense error (proprioception), joint range of motion, and postural alignment (motor function), respectively. Result:: The pain intensity and threshold and joint position sense error showed significant decreases after the intervention, whereas the joint range of motion angle revealed significant increases. The postural alignment including forward head posture and rounded shoulder revealed significant improvements after the intervention. Conclusions: Therefore, we suggest that elastic band-resistive exercise through audio-visual medium would be helpful in preventing and managing pain and physical dysfunction in individuals with chronic neck and shoulder pain, and then it would support the development of health management-related online education content.

• Journal of Animal Science and Technology
• /
• v.66 no.1
• /
• pp.31-56
• /
• 2024

Pig farming, a vital industry, necessitates proactive measures for early disease detection and crush symptom monitoring to ensure optimum pig health and safety. This review explores advanced thermal sensing technologies and computer vision-based thermal imaging techniques employed for pig disease and piglet crush symptom monitoring on pig farms. Infrared thermography (IRT) is a non-invasive and efficient technology for measuring pig body temperature, providing advantages such as non-destructive, long-distance, and high-sensitivity measurements. Unlike traditional methods, IRT offers a quick and labor-saving approach to acquiring physiological data impacted by environmental temperature, crucial for understanding pig body physiology and metabolism. IRT aids in early disease detection, respiratory health monitoring, and evaluating vaccination effectiveness. Challenges include body surface emissivity variations affecting measurement accuracy. Thermal imaging and deep learning algorithms are used for pig behavior recognition, with the dorsal plane effective for stress detection. Remote health monitoring through thermal imaging, deep learning, and wearable devices facilitates non-invasive assessment of pig health, minimizing medication use. Integration of advanced sensors, thermal imaging, and deep learning shows potential for disease detection and improvement in pig farming, but challenges and ethical considerations must be addressed for successful implementation. This review summarizes the state-of-the-art technologies used in the pig farming industry, including computer vision algorithms such as object detection, image segmentation, and deep learning techniques. It also discusses the benefits and limitations of IRT technology, providing an overview of the current research field. This study provides valuable insights for researchers and farmers regarding IRT application in pig production, highlighting notable approaches and the latest research findings in this field.

• The Journal of the Convergence on Culture Technology
• /
• v.10 no.3
• /
• pp.953-958
• /
• 2024

Recently, there has been growing interest in the Fourth Industrial Revolution, with a particular focus on the advancement of augmented reality (AR) devices. However, there is a shortage of AR content. Augmented reality operates through marker-based and markerless methods. The marker-based approach involves using a camera to capture images that serve as markers, enhancing them through AR principles. To address the scarcity of AR content and improve the quality of character goods, this study proposes integrating AR technology into character goods. The character industry is expanding each year, leading to a diverse range of character goods. Character acrylic stands, among these goods, leverage game, webtoon, and animation character IPs for sales. To enhance the design process, we utilized the character image as a marker, allowing for the creation of content that aligns with the characteristics of the character IP. We selected a webtoon character and developed AR content, incorporating features such as voice, speech bubbles, and an introduction to the webtoon, tailored to the webtoon's characteristics. This study demonstrates the potential of AR to present visual and auditory information, paving the way for a variety of products, including diverse content. We anticipate that utilizing this research will lead to the emergence of products encompassing various contents.

• The Transactions of the Korea Information Processing Society
• /
• v.13 no.7
• /
• pp.311-318
• /
• 2024

As the amount of data increases due to the development of artificial intelligence and the Internet, data management is becoming increasingly important, and the efficient utilization of data retrieval and memory space is crucial. In this study, we investigate how to optimize search speed and memory efficiency by analyzing data structure based on metadata. As a research method, we compared and analyzed the performance of the array, association list, dictionary binary tree, and graph data structures using metadata of photographic images, focusing on temporal and space complexity. Through experimentation, it was confirmed that dictionary data structure performs best in collection speed and graph data structure performs best in search speed when dealing with large-scale image data. We expect the results of this paper to provide practical guidelines for selecting data structures to optimize search speed and memory efficiency for the images data.

• Journal of Information Technology Applications and Management
• /
• v.31 no.4
• /
• pp.139-148
• /
• 2024

This study takes a comprehensive look at how technological advances have changed the way 2D animation is created. Humans are constantly looking for new ways and technologies to express movement, which has led to many changes in the way 2D animation is produced. In this study, we will examine the impact of these changes on 2D animation production and explore the possibilities for future developments. In the early days of 2D animation, the production method was repeatedly changed by the invention of technologies such as celluloid sheets, rotoscopes, and multiplane cameras, while the advent of digital technology has led to revolutionary changes such as the development of CAPS(computer animation production systems), various digital tools, and the combination of 2D and 3D. In addition, the recent introduction of generative AI is rapidly changing the way 2D animation is produced by automatically handling various tasks. These advances have not only streamlined the production of animation, but have also reduced costs by shortening the production period, and greatly improved the quality of animation by making it easier to implement complex and sophisticated visual effects. The introduction of generative AI has pushed the boundaries of what can be represented in 2D animation. On the other hand, the introduction of digital technology has its drawbacks, as the mechanical and uniform style produced by digital tools can reduce originality and individuality, but advances in technology will open up the possibilities for 2D animation to be produced in a variety of ways, as it fosters the creation of new expressions and creative content.