• Title/Summary/Keyword: AI 개발

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Implementation of Acceleration Sensor-based Human activity and Fall Classification Algorithm (가속도 센서기반의 인체활동 및 낙상 분류를 위한 알고리즘 구현)

  • Hyun Park;Jun-Mo Park;Yeon-Chul, Ha
    • Journal of the Institute of Convergence Signal Processing
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    • v.23 no.2
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    • pp.76-83
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    • 2022
  • With the recent development of IT technology, research and interest in various biosignal measuring devices is increasing. As an aging society is in full swing, research on the elderly population using IT-related technologies is continuously developing. This study is about the development of life pattern detection and fall detection algorithm, which is one of the medical service areas for the elderly, who are rapidly developing as they enter a super-aged society. This study consisted of a system using a 3-axis accelerometer and an electrocardiogram sensor, collected data, and then analyzed the data. It was confirmed that behavioral patterns could be classified from the actual research results. In order to evaluate the usefulness of the human activity monitoring system implemented in this study, experiments were performed under various conditions, such as changes in posture and walking speed, and signal magnitude range and signal vector magnitude parameters reflecting the acceleration of gravity of the human body and the degree of human activity. was extracted. And the possibility of discrimination according to the condition of the subject was examined by these parameter values.

The Development of Biodegradable Fiber Tensile Tenacity and Elongation Prediction Model Considering Data Imbalance and Measurement Error (데이터 불균형과 측정 오차를 고려한 생분해성 섬유 인장 강신도 예측 모델 개발)

  • Se-Chan, Park;Deok-Yeop, Kim;Kang-Bok, Seo;Woo-Jin, Lee
    • KIPS Transactions on Software and Data Engineering
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    • v.11 no.12
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    • pp.489-498
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    • 2022
  • Recently, the textile industry, which is labor-intensive, is attempting to reduce process costs and optimize quality through artificial intelligence. However, the fiber spinning process has a high cost for data collection and lacks a systematic data collection and processing system, so the amount of accumulated data is small. In addition, data imbalance occurs by preferentially collecting only data with changes in specific variables according to the purpose of fiber spinning, and there is an error even between samples collected under the same fiber spinning conditions due to difference in the measurement environment of physical properties. If these data characteristics are not taken into account and used for AI models, problems such as overfitting and performance degradation may occur. Therefore, in this paper, we propose an outlier handling technique and data augmentation technique considering the characteristics of the spinning process data. And, by comparing it with the existing outlier handling technique and data augmentation technique, it is shown that the proposed technique is more suitable for spinning process data. In addition, by comparing the original data and the data processed with the proposed method to various models, it is shown that the performance of the tensile tenacity and elongation prediction model is improved in the models using the proposed methods compared to the models not using the proposed methods.

Super High-Resolution Image Style Transfer (초-고해상도 영상 스타일 전이)

  • Kim, Yong-Goo
    • Journal of Broadcast Engineering
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    • v.27 no.1
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    • pp.104-123
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    • 2022
  • Style transfer based on neural network provides very high quality results by reflecting the high level structural characteristics of images, and thereby has recently attracted great attention. This paper deals with the problem of resolution limitation due to GPU memory in performing such neural style transfer. We can expect that the gradient operation for style transfer based on partial image, with the aid of the fixed size of receptive field, can produce the same result as the gradient operation using the entire image. Based on this idea, each component of the style transfer loss function is analyzed in this paper to obtain the necessary conditions for partitioning and padding, and to identify, among the information required for gradient calculation, the one that depends on the entire input. By structuring such information for using it as auxiliary constant input for partition-based gradient calculation, this paper develops a recursive algorithm for super high-resolution image style transfer. Since the proposed method performs style transfer by partitioning input image into the size that a GPU can handle, it can perform style transfer without the limit of the input image resolution accompanied by the GPU memory size. With the aid of such super high-resolution support, the proposed method can provide a unique style characteristics of detailed area which can only be appreciated in super high-resolution style transfer.

A Case Study of SW Project English Teaching through PBL method in an Untact Environment (Untact 상황에서 PBL 교수법을 통한 SW 프로젝트 영어 지도 사례 연구)

  • Lee, Sungock;Kim, Minkyu;Lee, Hyuesoo;Jung, Hoekyung
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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    • 2021.10a
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    • pp.514-517
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    • 2021
  • The purpose of this study is to discover the occupational identity by examining the narrative of the life of a vocational training teacher with self-esteem in programming fields. The following six types of occupational identity were found: 'a positive image of a vocational training teacher(fits oneself)', 'I feel proud of myself while doing vocational training activities.', 'a teacher who continues to develop him/herself as an expert in the subject class', 'a teacher who immerses him/herself as an expert on student change and growth', 'a teacher engaged in leading activities to create opportunities for vocational training', and 'a teacher of continuous pursuit'. This study has significance in exploring the structure of occupational identity recognition and experience of its formation of a self-esteemed vocational training teacher in programming fields, which have not been studied.

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A Study on Teaching the Method of Lagrange Multipliers in the Era of Digital Transformation (라그랑주 승수법의 교수·학습에 대한 소고: 라그랑주 승수법을 활용한 주성분 분석 사례)

  • Lee, Sang-Gu;Nam, Yun;Lee, Jae Hwa
    • Communications of Mathematical Education
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    • v.37 no.1
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    • pp.65-84
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    • 2023
  • The method of Lagrange multipliers, one of the most fundamental algorithms for solving equality constrained optimization problems, has been widely used in basic mathematics for artificial intelligence (AI), linear algebra, optimization theory, and control theory. This method is an important tool that connects calculus and linear algebra. It is actively used in artificial intelligence algorithms including principal component analysis (PCA). Therefore, it is desired that instructors motivate students who first encounter this method in college calculus. In this paper, we provide an integrated perspective for instructors to teach the method of Lagrange multipliers effectively. First, we provide visualization materials and Python-based code, helping to understand the principle of this method. Second, we give a full explanation on the relation between Lagrange multiplier and eigenvalues of a matrix. Third, we give the proof of the first-order optimality condition, which is a fundamental of the method of Lagrange multipliers, and briefly introduce the generalized version of it in optimization. Finally, we give an example of PCA analysis on a real data. These materials can be utilized in class for teaching of the method of Lagrange multipliers.

The Effect of Fluid Intake Enhancing Program for Institutionalized Elderly (시설노인의 수분 섭취 강화 프로그램의 효과분석)

  • Oh, Heeyoung;Lee, Eun-Hyun;Hur, Myung-Haeng;Kim, Eun-Kyung
    • 한국노년학
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    • v.27 no.2
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    • pp.357-370
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    • 2007
  • The purposes of this study were to 1) develop fluid intake enhancing program for the institutionalized elderly and 2) examine the effect of fluid intake enhancing program on amount of daily fluid consumed, urine specific gravity, and urine color. Data were collected from 39 nursing home residents in a nursing home located in urban Chung-chung providence. With a convenient sample of 39 nursing home residents, consecutive three days of 24 hour fluid intake, were measured and recorded. Urine samples were obtained and urine specific gravity, urine color were analyzed at pre-intervention, 4 weeks, and 6 weeks following the intervention. When compared to pre-intervention, the average amount of daily fluid intake was significantly increased at 4 weeks and 6 weeks following the intervention. The proportion of subjects who consumed less than Adequate Intake(AI) was 35.9% at pre-intervention and was decreased to 10.3%, 7.7%. In conclusion, inadequate fluid intake among institutionalized elderly is prevalent. From careful employment of the fluid intake enhancing program, increase in fluid consumption among institutionalized elderly can be expected.

A Study on the Utilization of Digital Learning Support Tools in the Field of French Studies Education (프랑스학 교육 분야의 디지털 학습지원 매체 활용에 관한 연구)

  • Kim yeonjoo
    • The Journal of the Convergence on Culture Technology
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    • v.9 no.5
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    • pp.685-695
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    • 2023
  • This study aimed to investigate the current utilization and implications of digital learning support media in the field of French studies, and to explore future research directions. To achieve this, we conducted a comprehensive review of the use of digital media in various learning processes within French studies. Additionally, we examined the direct application of ChatGPT, an emerging technology, to learning by extending its use to foreign language and education fields. Our findings indicate that the application of digital learning support media in French studies is somewhat limited, with selective use in processes such as online class support media, pre-class learning, efficient learning and interaction, and self-directed learning. In the case of ChatGPT, our research found that no studies have been conducted within French studies, and very few studies have been conducted on its practical application in other educational fields. While ChatGPT has a wide range of applications and has shown positive effects on learners, ethical concerns have been raised regarding the quality, source, and reliability of information. Therefore, future research in French studies should focus on educational application and effectiveness verification in university teaching and learning situations, as well as interdisciplinary convergence with digital learning support media.

Image-Data-Acquisition and Data-Structuring Methods for Tunnel Structure Safety Inspection (터널 구조물 안전점검을 위한 이미지 데이터 취득 및 데이터 구조화 방법)

  • Sung, Hyun-Suk;Koh, Joon-Sub
    • Journal of the Korean Geotechnical Society
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    • v.40 no.1
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    • pp.15-28
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    • 2024
  • This paper proposes a method to acquire image data inside tunnel structures and a method to structure the acquired image data. By improving the conditions by which image data are acquired inside the tunnel structure, high-quality image data can be obtained from area type tunnel scanning. To improve the data acquisition conditions, a longitudinal rail of the tunnel can be installed on the tunnel ceiling, and image data of the entire tunnel structure can be acquired by moving the installed rail. This study identified 0.5 mm cracked simulation lines under a distance condition of 20 m at resolutions of 3,840 × 2,160 and 720 × 480 pixels. In addition, the proposed image-data-structuring method could acquire image data in image tile units. Here, the image data of the tunnel can be structured by substituting the application factors (resolution of the acquired image and the tunnel size) into a relationship equation. In an experiment, the image data of a tunnel with a length of 1,000 m and a width of 20 m were obtained with a minimum overlap rate of 0.02% to 8.36% depending on resolution and precision, and the size of the local coordinate system was found to be (14 × 15) to (36 × 34) pixels.

Identifying Analog Gauge Needle Objects Based on Image Processing for a Remote Survey of Maritime Autonomous Surface Ships (자율운항선박의 원격검사를 위한 영상처리 기반의 아날로그 게이지 지시바늘 객체의 식별)

  • Hyun-Woo Lee;Jeong-Bin Yim
    • Journal of Navigation and Port Research
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    • v.47 no.6
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    • pp.410-418
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    • 2023
  • Recently, advancements and commercialization in the field of maritime autonomous surface ships (MASS) has rapidly progressed. Concurrently, studies are also underway to develop methods for automatically surveying the condition of various on-board equipment remotely to ensure the navigational safety of MASS. One key issue that has gained prominence is the method to obtain values from analog gauges installed in various equipment through image processing. This approach has the advantage of enabling the non-contact detection of gauge values without modifying or changing already installed or planned equipment, eliminating the need for type approval changes from shipping classifications. The objective of this study was to identify a dynamically changing indicator needle within noisy images of analog gauges. The needle object must be identified because its position significantly affects the accurate reading of gauge values. An analog pressure gauge attached to an emergency fire pump model was used for image capture to identify the needle object. The acquired images were pre-processed through Gaussian filtering, thresholding, and morphological operations. The needle object was then identified through Hough Transform. The experimental results confirmed that the center and object of the indicator needle could be identified in images of noisy analog gauges. The findings suggest that the image processing method applied in this study can be utilized for shape identification in analog gauges installed on ships. This study is expected to be applicable as an image processing method for the automatic remote survey of MASS.

User Experience Analysis and Management Based on Text Mining: A Smart Speaker Case (텍스트 마이닝 기반 사용자 경험 분석 및 관리: 스마트 스피커 사례)

  • Dine Yeon;Gayeon Park;Hee-Woong Kim
    • Information Systems Review
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    • v.22 no.2
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    • pp.77-99
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    • 2020
  • Smart speaker is a device that provides an interactive voice-based service that can search and use various information and contents such as music, calendar, weather, and merchandise using artificial intelligence. Since AI technology provides more sophisticated and optimized services to users by accumulating data, early smart speaker manufacturers tried to build a platform through aggressive marketing. However, the frequency of using smart speakers is less than once a month, accounting for more than one third of the total, and user satisfaction is only 49%. Accordingly, the necessity of strengthening the user experience of smart speakers has emerged in order to acquire a large number of users and to enable continuous use. Therefore, this study analyzes the user experience of the smart speaker and proposes a method for enhancing the user experience of the smart speaker. Based on the analysis results in two stages, we propose ways to enhance the user experience of smart speakers by model. The existing research on the user experience of the smart speaker was mainly conducted by survey and interview-based research, whereas this study collected the actual review data written by the user. Also, this study interpreted the analysis result based on the smart speaker user experience dimension. There is an academic significance in interpreting the text mining results by developing the smart speaker user experience dimension. Based on the results of this study, we can suggest strategies for enhancing the user experience to smart speaker manufacturers.