• 한국인터넷방송통신학회논문지
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• 제21권6호
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• pp.111-116
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• 2021

초분광 영상은 적외선 영역의 전자기파 대역을 수백 개의 파장으로 나누어 영상화한 데이터로 다양한 분야에서 물체를 찾거나 분류하는 것에 활용된다. 최근에는 딥러닝을 사용하여 분류하는 방법이 주목받고 있지만 초분광 영상 데이터의 특성으로 인해 초분광 영상을 학습 데이터로 사용하기 위해서는 기존의 가시광 영상과는 다른 처리 기법이 필요하다. 이를 위해 초분광 큐브에서 특정 파장의 영상을 선택하여 Ground Truth 작업을 수행하고 환경정보를 포함하여 데이터를 관리하는 소프트웨어를 개발하였다. 본 논문에서는 해당 소프트웨어의 구성과 기능에 대하여 설명한다.

• Safety and Health at Work
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• 제12권2호
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• pp.184-191
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• 2021

Background: Hearing protection devices (HPDs) are often used in the workplace to prevent hearing damage caused by noise. However, a factor that can lead to hearing loss in the workplace is improper HPD fitting, and the previous literature has shown that instructing workers on how to properly insert their HPDs can make a significant difference in the degree of attenuation. Methods: Two studies were completed on a total of 33 Hydro One workers. A FitCheck Solo field attenuation estimation system was used to measure the personal attenuation rating (PAR) before and after providing one-on-one fitting instructions. In addition, external ear canal diameters were measured, and a questionnaire with items related to frequency of use, confidence, and discomfort was administered. Results: Training led to an improvement in HPD attenuation, particularly for participants with poorer PARs before training. The questionnaire results indicated that much HPD discomfort is caused by heat, humidity, and communication difficulties. External ear canal asymmetry did not appear to significantly influence the measured PAR. Conclusion: In accordance with the previous literature, our studies suggest that one-on-one instruction is an effective training method for HPD use. Addressing discomfort issues from heat, humidity, and communication issues could help to improve the use of HPDs in the workplace. Further research into the effects of canal asymmetry on the PAR is needed.

• International Journal of Internet, Broadcasting and Communication
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• 제13권1호
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• pp.37-46
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• 2021

Recently, social technologies have been created to solve problems from businesses for the establishment of generational solidarity ecosystem in terms of employment, residential space, network and social capital, age, cognitive and environmental aspects. This is senior-friendly healthcare business system aimed at meeting the senior needs for health life to enjoy active consumption culture life even after retirement, becoming a catalyst for minimizing generational conflicts, preventing the cognitive and physical deterioration of seniority in the areas of life healthcare, fitness and well-aging, and expanding into systems necessary for seniority self-reliance. We would like to draw up the development and requirements of the concept of the service platform for the study of collective characteristics for generation solidarity with senior class and the establishment of a customized senior health life system for generation solidarity. This system is characterized by a platform that can prevent the decline of seniors' cognitive and physical functions and enhance emotional stability. It is significant in providing feedback on the risk perception index, fall index, and prevention training index information to the child through the analysis and extraction of the senior health index for risk perception, fall probability, and fall prevention.

• International Journal of Internet, Broadcasting and Communication
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• 제15권4호
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• pp.270-278
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• 2023

We propose a container orchestration system for process workloads that combines the potential of big data and machine learning technologies to integrate enterprise process-centric workloads. This proposed system analyzes big data generated from industrial automation to identify hidden patterns and build a machine learning prediction model. For each machine learning case, training data is loaded into a data store and preprocessed for model training. In the next step, you can use the training data to select and apply an appropriate model. Then evaluate the model using the following test data: This step is called model construction and can be performed in a deployment framework. Additionally, a visual hierarchy is constructed to display prediction results and facilitate big data analysis. In order to implement parallel computing of PCA in the proposed system, several virtual systems were implemented to build the cluster required for the big data cluster. The implementation for evaluation and analysis built the necessary clusters by creating multiple virtual machines in a big data cluster to implement parallel computation of PCA. The proposed system is modeled as layers of individual components that can be connected together. The advantage of a system is that components can be added, replaced, or reused without affecting the rest of the system.

• Journal of Animal Science and Technology
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• 제66권1호
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• pp.167-177
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• 2024

Iris segmentation is an initial step for identifying the biometrics of animals when establishing a traceability system for livestock. In this study, we propose a deep learning framework for pixel-wise segmentation of bovine iris with a minimized use of annotation labels utilizing the BovineAAEyes80 public dataset. The proposed image segmentation framework encompasses data collection, data preparation, data augmentation selection, training of 15 deep neural network (DNN) models with varying encoder backbones and segmentation decoder DNNs, and evaluation of the models using multiple metrics and graphical segmentation results. This framework aims to provide comprehensive and in-depth information on each model's training and testing outcomes to optimize bovine iris segmentation performance. In the experiment, U-Net with a VGG16 backbone was identified as the optimal combination of encoder and decoder models for the dataset, achieving an accuracy and dice coefficient score of 99.50% and 98.35%, respectively. Notably, the selected model accurately segmented even corrupted images without proper annotation data. This study contributes to the advancement of iris segmentation and the establishment of a reliable DNN training framework.

• 한국인터넷방송통신학회논문지
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• 제16권3호
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• pp.57-64
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• 2016

CCTV 활용과 관련 산업발달에 따라 CCTV 관련 분야에 활동하는 전문 인력의 효과적인 양성 필요성이 대두되고 있다. 따라서 본 연구의 목적은 CCTV 분야의 효과적인 인력양성 방안에 대한 연구로서 14인의 전문가 패널을 이용한 델파이 방식을 통해 연구했다. 본 연구에서 제시하는 CCTV 분야의 효과적인 인력양성을 위한 방안은 다음과 같다. 교육 수강생 측면에서, 교육과정과 교육내용에 대한 적절한 설명이 제시되고, 동기부여를 위해 교육 후 자격증 확보 방안 마련 취업 알선 등으로 교육 후 신분에 대한 보장 환경 제공해야 한다. 교육 참여기업(기관) 측면에서는, 수강 후 이직 방지방안 마련, 교육비용에 대한 정부의 지원, 교육 수강으로 인한 업무 공백 해결 등이 있다. 교육운영 기관 측면에서 보면, 교육 참여에 따른 다양한 혜택을 제공, 관련기관과의 협력을 통한 적절한 홍보와 교육 프로그램 소개, 수요자의 요구사항에 맞는 적절한 교육을 제공, 교육과목 선택 및 교육과정 운영에 따른 수강 선택권을 확대해야 한다. 또한 교육을 운영하기 위해 소요되는 비용에 대한 부담감을 줄이기 위한 방안마련, 운영인력의 부족을 해결하기 위해 전문 시니어 인력을 활용, 수강생 선발의 기준은 현업 근무경험자 또는 교육이 요구되는 수요자 중심으로 선발이 필요하다.

• 실천공학교육논문지
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• 제6권1호
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• pp.65-70
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• 2014

최근 산업구조가 고도화됨에 따라 기술의 변화가 크게 일어나고 있으며 특성화고 및 마이스터고의 교육에 있어서도 이와 같은 기술변화에 맞는 교육이 필요로 되고 있다. 이와 같은 요구에 따라 특성화고 및 마이스터고 전문교과 교원에 대한 현장역량강화 및 기업과의 인적 교류 확대를 위하여 현장직무연수 프로그램이 개발되어 운영되었다. 본 연구에서는 한국기술교육대학교 능력개발교육원에서 2013년도 운영된 단기 및 중 장기의 현장직무연수 프로그램을 분석하고 그 문제점과 개선방안을 도출하였다. 분석결과 현장직무연수에 대한 만족도가 상당히 높게 나왔으며 앞으로 산업과 기술의 변화에 대응할 수 있는 연수 프로그램으로 정착될 수 있도록 개선방향을 도출하였다.

• 대한인간공학회지
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• 제31권4호
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• pp.577-583
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• 2012

Objective: This paper describes the process and results related to the development of gesture recognition-based natural user interface(NUI) for vehicle maintenance e-Training system. Background: E-Training refers to education training that acquires and improves the necessary capabilities to perform tasks by using information and communication technology(simulation, 3D virtual reality, and augmented reality), device(PC, tablet, smartphone, and HMD), and environment(wired/wireless internet and cloud computing). Method: Palm movement from depth camera is used as a pointing device, where finger movement is extracted by using OpenCV library as a selection protocol. Results: The proposed NUI allows trainees to control objects, such as cars and engines, on a large screen through gesture recognition. In addition, it includes the learning environment to understand the procedure of either assemble or disassemble certain parts. Conclusion: Future works are related to the implementation of gesture recognition technology for a multiple number of trainees. Application: The results of this interface can be applied not only in e-Training system, but also in other systems, such as digital signage, tangible game, controlling 3D contents, etc.

• 대한의용생체공학회:학술대회논문집
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• 대한의용생체공학회 1996년도 추계학술대회
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• pp.114-117
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• 1996

In this study, remote articulation training system which connects the hearing disabled trainee and the speech therapist via B-ISDN is introduced. The hearing disabled does not have the hearing feedback of his own pronunciation, and the chance of watching his speech organs' movement trajectory will offer him the self-training of articulation. So the system has two purposes of self articulation training and trainer's on-line checking in remote place. We estimate the vocal tract articulatory movements from the speech signal using inverse modelling and display the movement trajectory on the sideview of human face graphically. The trajectories of trainees' articulation is displayed along with the reference trajectories, so the trainee can control his articulating to make the two trajectories overlapped. For on-line communication and ckecking training record, the system has the function of video conferencing and transferring articulatory data.

• Safety and Health at Work
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• 제6권4호
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• pp.345-352
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• 2015

Background: Goal-oriented communication of risk of hazards is necessary in order to reduce risk of workers' exposure to chemicals. Adequate training of workers and enterprise priority setting are essential elements. Cleaning enterprises have many challenges and the existing paradigms influence the risk levels of these enterprises. Methods: Information on organization and enterprises' prioritization in training programs was gathered from cleaning enterprises. A measure of enterprises' conceptual level of importance of chemical health hazards and a model for working out the risk index (RI) indicating enterprises' conceptual risk level was established and used to categorize the enterprises. Results: In 72.3% of cases, training takes place concurrently with task performances and in 67.4% experienced workers conduct the trainings. There is disparity between employers' opinion on competence level of the workers and reality. Lower conceptual level of importance was observed for cleaning enterprises of different sizes compared with regional safety delegates and occupational hygienists. Risk index values show no difference in risk level between small and large enterprises. Conclusion: Training of cleaning workers lacks the prerequisite for suitability and effectiveness to counter risks of chemical health hazards. There is dereliction of duty by management in the sector resulting in a lack of competence among the cleaning workers. Instituting acceptable easily attainable safety competence level for cleaners will conduce to risk reduction, and enforcement of attainment of the competence level would be a positive step.