• Title/Summary/Keyword: Industrial classification

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Detection of Apnea Signal using UWB Radar based on Short-Time-Fourier-Transform (국소 퓨리에 변환 기반 레이더 신호를 활용한 무호흡 검출)

  • Hwang, Chaehwan;Kim, Suyeol;Lee, Deokwoo
    • Journal of the Korea Academia-Industrial cooperation Society
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    • v.20 no.7
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    • pp.151-157
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    • 2019
  • Recently, monitoring respiration of people has been of interest using non-invasive method. Among the vital signals usually used for indicating health status, non-invasive and portable device based monitoring respiratory status is practically useful and enable one to promptly deal with abnormal physical status. This paper proposes the approach to real-time detection of apnea signal based on Short-Time-Fourier-Transform(STFT). Contrary to the analysis of a signal in frequency domain using Fast-Fourier Transform, this paper employs Short-time-Fourier-Transform so that frequency response can be analyzed in short time interval. The respiratory signal is acquired using UWB radar sensor that enables one to obtain respiration signal in contactless way. Detection of respiratory status is carried out by analyzing frequency response, and classification of respiratory status can be provided. In particular, STFT is employed to analyze respiratory signal in real-time, leading to effective analysis of the respiratory status in practice. In the case of existence of noise in the signal, appropriate filtering process is employed as well. The proposed method is straightforward and is workable in practice to analyze the respiratory status of people. To evaluate the proposed method, experimental results are provided.

Risk Management-Based Application of Anti-Tampering Methods in Weapon Systems Development (무기 시스템 개발에서 기술보호를 위한 위험관리 기반의 Anti-Tampering 적용 기법)

  • Lee, Min-Woo;Lee, Jae-Chon
    • Journal of the Korea Academia-Industrial cooperation Society
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    • v.19 no.12
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    • pp.99-109
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    • 2018
  • Tampering involves illegally removing technologies from a protected system through reverse engineering or developing a system without proper authorization. As tampering of a weapon system is a threat to national security, anti-tampering measures are required. Precedent studies on anti-tampering have discussed the necessity, related trends, application cases, and recent cybersecurity-based or other protection methods. In a domestic situation, the Defense Technology Protection Act focuses on how to prevent technology leakage occurring in related organizations through personnel, facilities and information systems. Anti-tampering design needs to determine which technologies are protected while considering the effects of development cost and schedule. The objective of our study is to develop methods of how to select target technologies and determine counter-measures to protect these technologies. Specifically, an evaluation matrix was derived based on the risk analysis concept to select the protection of target technologies. Also, based on the concept of risk mitigation, the classification of anti-tampering techniques was performed according to its applicability and determination of application levels. Results of the case study revealed that the methods proposed can be systematically applied for anti-tampering in weapon system development.

An Analysis of Factors Affecting Satisfaction with Seoul Public Bike (서울시 공공자전거 이용환경 만족도 영향요인 분석)

  • Kim, So-Yun;Lee, Kyung-Hwan;Ko, Eun-Jeong
    • Journal of the Korea Academia-Industrial cooperation Society
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    • v.22 no.2
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    • pp.475-486
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    • 2021
  • The purpose of this study was to propose a policy direction to improve the service of public bicycles in Seoul by identifying the physical characteristics that affect the satisfaction level in the Seoul Metropolitan Government's public bicycle use environment. To this end, a survey was conducted on users regarding their experiences using public bicycles in Seoul, and the responses of 567 people were analyzed. IPA analysis and ordinal logistic analysis were used. An analysis of the Seoul Metropolitan Government's public bicycle IPA showed that the satisfaction level was lower than that of importance in all categories. Among them, the most urgent need for improvement was the installation of bicycle roads, improved connectivity of bicycle roads, improved road management, classification of roads and bicycle roads, improved safety during night driving, and low satisfaction levels. Second, an analysis of the factors affecting the satisfaction in the public bicycle use environment showed that the model's explanatory power increased significantly from 0.062 to 0.437 after incorporating perceived variables, confirming that the perceived neighborhood environment characteristics are an important variable for determining the satisfaction level in the public bicycle use environment, among the perceived neighborhood environmental characteristics, accessibility, convenience, manageability.

Binary classification of bolts with anti-loosening coating using transfer learning-based CNN (전이학습 기반 CNN을 통한 풀림 방지 코팅 볼트 이진 분류에 관한 연구)

  • Noh, Eunsol;Yi, Sarang;Hong, Seokmoo
    • Journal of the Korea Academia-Industrial cooperation Society
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    • v.22 no.2
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    • pp.651-658
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    • 2021
  • Because bolts with anti-loosening coatings are used mainly for joining safety-related components in automobiles, accurate automatic screening of these coatings is essential to detect defects efficiently. The performance of the convolutional neural network (CNN) used in a previous study [Identification of bolt coating defects using CNN and Grad-CAM] increased with increasing number of data for the analysis of image patterns and characteristics. On the other hand, obtaining the necessary amount of data for coated bolts is difficult, making training time-consuming. In this paper, resorting to the same VGG16 model as in a previous study, transfer learning was applied to decrease the training time and achieve the same or better accuracy with fewer data. The classifier was trained, considering the number of training data for this study and its similarity with ImageNet data. In conjunction with the fully connected layer, the highest accuracy was achieved (95%). To enhance the performance further, the last convolution layer and the classifier were fine-tuned, which resulted in a 2% increase in accuracy (97%). This shows that the learning time can be reduced by transfer learning and fine-tuning while maintaining a high screening accuracy.

An Analysis of Teacher's Job Stress: Differences in Teacher-Student Relationship and Parental Involvement (잠재프로파일 분석을 통한 초등학교 교사의 직무스트레스 유형 분류 및 영향 요인 검증: 교사-아동 관계, 학부모 교육 참여 차이)

  • Choi, Hyo-Sik;Yeon, Eun Mo
    • Journal of the Korea Academia-Industrial cooperation Society
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    • v.22 no.6
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    • pp.431-440
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    • 2021
  • The purpose of this study was to classify the latent profiles of elementary school teachers' job stress and to explore the effects of the relative variables to determine these classifications. In addition, the differences in the teacher-student relationship and parental involvement in school based on the classification were discussed. Data from 709 elementary school teachers who participated in the 11th wave of the Panel Study on Korean Children in 2018 were analyzed by Latent Profile Analysis (LPA). The findings can be summarized as follows. First, four subgroups could be defined according to the elementary school teachers' job stress: low-level job stress group, mid-level job stress group, mid-level administrative work stress group, and mid-level relationship and guidance stress group. Second, the final education and average time to work were significant determinants of the latent groups. Third, teacher-student conflict and parental involvement in school showed differences between the subgroups. Specifically, the mid-level relationship and guidance stress group reported the highest conflict level with children and the lowest parental involvement in school. These findings suggest promoting relief and preventative training programs for elementary school teachers to overcome various job stress.

A Study on the Analysis of R&D Trends and the Development Plan of Electronic Attack System (전자공격체계 연구개발 동향 분석과 발전방안에 대한 연구)

  • Sim, Jaeseong;Park, Byoung-Ho
    • Journal of the Korea Academia-Industrial cooperation Society
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    • v.22 no.6
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    • pp.469-476
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    • 2021
  • An electronic attack (EA) system is an essential weapon system for performing electronic warfare missions that contain signal tracking and jamming against multiple threats using electromagnetic waves, such as air defense radars, wireless command and communication networks, and guided missiles. The combat effectiveness can be maximized, and the survivability of militarily protecting combat power can be enhanced through EA mission operations, such as disabling the functions of multiple threats. The EA system can be used as a radio frequency jamming system to respond to drone attacks on the core infrastructure, such as airports, power plants, and communication broadcasting systems, in the civilian field. This study examined the criteria for classification according to the electronic attack missions of foreign EA systems based on an aviation platform. The foreign R&D trends by those criteria were investigated. Moreover, by analyzing the R&D trends of domestic EA systems and future battlefields in the domestic security environments, this paper proposes technological development plans of EA systems suitable for the future battlefield environments compared to the foreign R&D trends.

Human Skeleton Keypoints based Fall Detection using GRU (PoseNet과 GRU를 이용한 Skeleton Keypoints 기반 낙상 감지)

  • Kang, Yoon Kyu;Kang, Hee Yong;Weon, Dal Soo
    • Journal of the Korea Academia-Industrial cooperation Society
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    • v.22 no.2
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    • pp.127-133
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    • 2021
  • A recent study of people physically falling focused on analyzing the motions of the falls using a recurrent neural network (RNN) and a deep learning approach to get good results from detecting 2D human poses from a single color image. In this paper, we investigate a detection method for estimating the position of the head and shoulder keypoints and the acceleration of positional change using the skeletal keypoints information extracted using PoseNet from an image obtained with a low-cost 2D RGB camera, increasing the accuracy of judgments about the falls. In particular, we propose a fall detection method based on the characteristics of post-fall posture in the fall motion-analysis method. A public data set was used to extract human skeletal features, and as a result of an experiment to find a feature extraction method that can achieve high classification accuracy, the proposed method showed a 99.8% success rate in detecting falls more effectively than a conventional, primitive skeletal data-use method.

Development of Permit Vehicle Classification System for Bridge Evaluation in Korea (허가차량 통행에 대한 교량의 안전성 평가를 위한 허가차량 분류 체계 개발)

  • Yu, Sang Seon;Kim, Kyunghyun;Paik, Inyeol;Kim, Ji Hyeon
    • Journal of the Korea Academia-Industrial cooperation Society
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    • v.21 no.12
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    • pp.845-856
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    • 2020
  • This study proposes a bridge evaluation system for indivisible permit vehicles such as hydraulic cranes. The permit loads for the bridge evaluation are divided into three categories: routine permit loads, special permit 1 loads, and special permit 2 loads. Routine permit and special permit 1 vehicles are allowed to cross a bridge with normal traffic. For these two permits, the standard lane model in the Korean Highway Bridge Design Code was adopted to consider normal traffic in the same lane. Special permit 2 vehicles are assumed to cross a bridge without other traffic. Structural analyses of two prestressed-beam bridges and two steel box girder bridges were conducted for the proposed permit loads. The rating factors of the four bridges for all permit loads were calculated as sufficiently large values for the moment and shear force so that crossing the bridges can be permitted. A reliability assessment of the bridges was performed to identify the reliability levels for the permit vehicles. It was confirmed that the reliability level of the minimum required strength obtained by the load-resistance factors yields the target reliability index of the design code for the permit vehicles.

A Method of Obtaining Correction Factor for Settlement Prediction of Soft Ground Using Correlation of Theoretical and Measured Settlement of Gimhae-Jinyoung through SPSS Analysis (이론 및 계측 침하량의 SPSS 상관분석을 통한 김해진영 연약 지반의 침하량 예측 보정계수 산출법)

  • Jang, Won-Cheol;Kim, Byoung-Il;Kim, Young-Uk
    • Journal of the Korea Academia-Industrial cooperation Society
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    • v.22 no.5
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    • pp.502-508
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    • 2021
  • Predicting the settlement of soft ground is an important aspect of soft ground design. In this study, a method is proposed that increases the reliability of settlement predictions based on-site investigation data, including piezocone penetration test results, at the Gimhae-Jinyoung district, adjacent area to the Nakdong River. Soils in the area waweres classified using the Robertson Chart (1986, 1990), and theoretical settlement was calculated using the equations proposed by Terzaghi (1925) and Sanglerat (1972). SPSS was used to obtain the correlation between theoretical and measured settlements. Results produced settlement prediction errors for the Terzaghi and Sanglerat methods of 17.28% and 26.96%, respectively. A correction factor calculated by SPSS correlation analysis for the relation between and theoretical and measured settlements is proposed that improves the reliability of settlement prediction in soils of the classification examined.

Investigating Key Security Factors in Smart Factory: Focusing on Priority Analysis Using AHP Method (스마트팩토리의 주요 보안요인 연구: AHP를 활용한 우선순위 분석을 중심으로)

  • Jin Hoh;Ae Ri Lee
    • Information Systems Review
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    • v.22 no.4
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    • pp.185-203
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    • 2020
  • With the advent of 4th industrial revolution, the manufacturing industry is converging with ICT and changing into the era of smart manufacturing. In the smart factory, all machines and facilities are connected based on ICT, and thus security should be further strengthened as it is exposed to complex security threats that were not previously recognized. To reduce the risk of security incidents and successfully implement smart factories, it is necessary to identify key security factors to be applied, taking into account the characteristics of the industrial environment of smart factories utilizing ICT. In this study, we propose a 'hierarchical classification model of security factors in smart factory' that includes terminal, network, platform/service categories and analyze the importance of security factors to be applied when developing smart factories. We conducted an assessment of importance of security factors to the groups of smart factories and security experts. In this study, the relative importance of security factors of smart factory was derived by using AHP technique, and the priority among the security factors is presented. Based on the results of this research, it contributes to building the smart factory more securely and establishing information security required in the era of smart manufacturing.