• Title/Summary/Keyword: Industrial Security

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Unsupervised Learning-Based Threat Detection System Using Radio Frequency Signal Characteristic Data (무선 주파수 신호 특성 데이터를 사용한 비지도 학습 기반의 위협 탐지 시스템)

  • Dae-kyeong Park;Woo-jin Lee;Byeong-jin Kim;Jae-yeon Lee
    • Journal of Internet Computing and Services
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    • v.25 no.1
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    • pp.147-155
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    • 2024
  • Currently, the 4th Industrial Revolution, like other revolutions, is bringing great change and new life to humanity, and in particular, the demand for and use of drones, which can be applied by combining various technologies such as big data, artificial intelligence, and information and communications technology, is increasing. Recently, it has been widely used to carry out dangerous military operations and missions, such as the Russia-Ukraine war and North Korea's reconnaissance against South Korea, and as the demand for and use of drones increases, concerns about the safety and security of drones are growing. Currently, a variety of research is being conducted, such as detection of wireless communication abnormalities and sensor data abnormalities related to drones, but research on real-time detection of threats using radio frequency characteristic data is insufficient. Therefore, in this paper, we conduct a study to determine whether the characteristic data is normal or abnormal signal data by collecting radio frequency signal characteristic data generated while the drone communicates with the ground control system while performing a mission in a HITL(Hardware In The Loop) simulation environment similar to the real environment. proceeded. In addition, we propose an unsupervised learning-based threat detection system and optimal threshold that can detect threat signals in real time while a drone is performing a mission.

The impact of stress coping on life satisfaction in very old adults: Focusing on the mediating effects of social support (초고령 노인의 스트레스 대처방안이 삶의 만족도에 미치는 영향: 사회적 지지의 매개효과를 중심으로)

  • Hyun-Ah Jung;Hyun-Seung Park
    • Industry Promotion Research
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    • v.9 no.1
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    • pp.123-132
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    • 2024
  • The purpose of this study was to improve the understanding of stress coping in the very old and elderly and to improve life satisfaction through stress reduction as the population ages. To this end, this study aimed to test the mediating effect of social support on the relationship between stress coping and life satisfaction among very old people. In particular, we paid attention to the differences in stress coping from the existing elderly population and took the view that they should be studied as an independent group. To confirm this, we analysed 275 men and women aged 85 years and older who responded to the fifth supplementary survey of the National Elderly Security Panel (KReIS) conducted by the National Pension Service. IBM SPSS 26 was used to test the mediating effect of social support on the effect of stress coping measures on life satisfaction in the very old elderly. The results of the significance test of the independent variables on the mediating variable showed that stress coping was positively significant, i.e., the higher the level of stress coping, the higher the life satisfaction. In addition, the results of the significance test of the effects of the independent variables and mediators on the dependent variable showed that coping with stress had a significant effect, and the mediator, social support, also had a significant effect on life satisfaction. Therefore, this study suggests the need for social support to improve the level of life satisfaction through coping with stress in the very old elderly.

Intelligent Transportation System (ITS) research optimized for autonomous driving using edge computing (엣지 컴퓨팅을 이용하여 자율주행에 최적화된 지능형 교통 시스템 연구(ITS))

  • Sunghyuck Hong
    • Advanced Industrial SCIence
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    • v.3 no.1
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    • pp.23-29
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    • 2024
  • In this scholarly investigation, the focus is placed on the transformative potential of edge computing in enhancing Intelligent Transportation Systems (ITS) for the facilitation of autonomous driving. The intrinsic capability of edge computing to process voluminous datasets locally and in a real-time manner is identified as paramount in meeting the exigent requirements of autonomous vehicles, encompassing expedited decision-making processes and the bolstering of safety protocols. This inquiry delves into the synergy between edge computing and extant ITS infrastructures, elucidating the manner in which localized data processing can substantially diminish latency, thereby augmenting the responsiveness of autonomous vehicles. Further, the study scrutinizes the deployment of edge servers, an array of sensors, and Vehicle-to-Everything (V2X) communication technologies, positing these elements as constituents of a robust framework designed to support instantaneous traffic management, collision avoidance mechanisms, and the dynamic optimization of vehicular routes. Moreover, this research addresses the principal challenges encountered in the incorporation of edge computing within ITS, including issues related to security, the integration of data, and the scalability of systems. It proffers insights into viable solutions and delineates directions for future scholarly inquiry.

5G Network Resource Allocation and Traffic Prediction based on DDPG and Federated Learning (DDPG 및 연합학습 기반 5G 네트워크 자원 할당과 트래픽 예측)

  • Seok-Woo Park;Oh-Sung Lee;In-Ho Ra
    • Smart Media Journal
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    • v.13 no.4
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    • pp.33-48
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    • 2024
  • With the advent of 5G, characterized by Enhanced Mobile Broadband (eMBB), Ultra-Reliable Low Latency Communications (URLLC), and Massive Machine Type Communications (mMTC), efficient network management and service provision are becoming increasingly critical. This paper proposes a novel approach to address key challenges of 5G networks, namely ultra-high speed, ultra-low latency, and ultra-reliability, while dynamically optimizing network slicing and resource allocation using machine learning (ML) and deep learning (DL) techniques. The proposed methodology utilizes prediction models for network traffic and resource allocation, and employs Federated Learning (FL) techniques to simultaneously optimize network bandwidth, latency, and enhance privacy and security. Specifically, this paper extensively covers the implementation methods of various algorithms and models such as Random Forest and LSTM, thereby presenting methodologies for the automation and intelligence of 5G network operations. Finally, the performance enhancement effects achievable by applying ML and DL to 5G networks are validated through performance evaluation and analysis, and solutions for network slicing and resource management optimization are proposed for various industrial applications.

Study on Customer Satisfaction Performance Evaluation through e-SCM-based OMS Implementation (e-SCM 기반 OMS 구현을 통한 고객 만족 성과평가에 관한 연구)

  • Hyungdo Zun;ChiGon Kim;KyungBae Yoon
    • The Journal of the Convergence on Culture Technology
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    • v.10 no.3
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    • pp.891-899
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    • 2024
  • The Fourth Industrial Revolution is centered on a personalized demand fulfillment economy and is all about transformation and flexible processing that can deliver what customers want in real time across space and time. This paper implements the construction and operation of a packaging platform that can instantly procure the required packaging products based on real-time orders and evaluates its performance. The components of customer satisfaction are flexible and dependent on the situation which requires efficient management of enterprise operational processes based on an e-SCM platform. An OMS optimized for these conditions plays an important role in maximizing and differentiating the efficiency of a company's operations and improving its cost advantage. OMS is a system of mass customization that provides efficient MOT(Moment of Truth) logistics services to meet the eco-friendly issues of many individual customers and achieve optimized logistics operation goals to enhance repurchase intentions and sustainable business. OMS precisely analyzes the collected data to support information and decision-making related to efficiency, productivity, cost and provide accurate reports. It uses data visualization tools to express data visually and suggests directions for improvement of the operational process through statistics and prediction analysis.

A Study of Service Innovation in the Airport Industry using AHP (계층화 분석법을 활용한 공항 산업 서비스 혁신 연구)

  • Hong hwan Ahn;Han Sol Lim;Seung Kyun Ra;Bong Gyou Lee
    • Journal of Internet Computing and Services
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    • v.25 no.3
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    • pp.71-81
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    • 2024
  • In response to the COVID-19 pandemic, the global airport industry is actively introducing 4th Industrial Revolution technology-based systems for quarantine and passenger safety, and test bed construction and prior verification using airport infrastructure and resources are actively being conducted. Analysis of recent cases shows that despite the changing travel patterns of airport users and the diversification of airport service demands, most testbeds construction studies are still focused on suppliers, and task prioritization is also determined by decision makers. There is a tendency to rely on subjective judgment. In order to find practical ways to become a first mover that leads innovation in the aviation industry, this study selected tasks and derived priorities to build testbeds from a service perspective that reflects various customer service needs and changes. Research results using the AHP analysis method resulted in priorities in the order of access transportation and parking services (29.2%), security screening services (23.4%), and departure services (21.8%), and these analysis results were tested in the airport industry. It shows that innovation in testbeds construction is an important factor. In particular, the establishment of smart parking and UAM transportation testbeds not only helps strengthen airports as centers of technological innovation, but also promotes cooperation with companies, research institutes, and governments, and provides an environment for testing and developing new technologies and services. It can be a foundation for what can be done. The results and implications produced through this study can serve as useful guidelines for domestic and foreign airport practitioners to build testbeds and establish strategies.

Study on stability test of in process sample of recombinant Protein A (재조합 단백질 A 제조공정시료의 안정성실험에 관한 연구)

  • Kim, Yoo Gon;Lee, Woo Jong;Won, Chan Hee;Shin, Chul Soo
    • Analytical Science and Technology
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    • v.25 no.6
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    • pp.483-491
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    • 2012
  • This study is to investigate the issues on how to secure stability during the purification process for the production of recombinant protein A. The final recombinant protein A is produced by passing through the cation exchange column (SP) and the anion-exchange column (Q) during the production process, for which the samples produced by the step-by-step processes can be exposed to trouble in securing stable storage in case the next process cannot be taken within the proper time period. Accordingly, this study aims to evaluate the proper storage conditions and length of time when storing samples produced in the production process. That is, in this study, how to store fair samples, how long the storage period should be set up, and how to evaluate the security of its quality depending on time are dealt with. The items to be experimented with were enodotoxin, SDS-PAGE, HPLC purity and concentration. Experimental results showed that after passing the cation exchange column, when stored at $4^{\circ}C$ or room temperature, SDS-PAGE showed a major band, endotoxin is 5.0 Eu/mg or less, and concentration is on average of 8.21 to 8.24 mg/mL and RSD% 0.10~0.62%. In addition, HLPC purity showed somewhat stable results; at the HPLC purity 214 nm, the average is 99.24% to 99.37% and RSD% is 0.22~0.29%, while the average is 89.72% to 89.80% and RSD% 0.62~1.26% at 280 nm. On the contrary, after passing the anion exchange column, when stored at $4^{\circ}C$ or room temperature, SDS-PAGE revealed the major band, endotoxin is 0.5 Eu/mg or less, and concentration is on average of 5.59 mg/mL and RSD% 0.03~0.10%. when it comes to HLPC purity, the result showed that at the HPLC purity 214 nm, the average is 99.74% and RSD% is 0.10~0.11%, while the average is 96.16% to 96.85% and RSD% 0.72~1.13%. In conclusion, the stability of fair samples of recombinant protein A during the manufacturing process could be obtained without substance decomposition for 7~8 days at $4^{\circ}C$ or 20~21 days at room temperature.

The Effects of Performance of Public Health Services and Personal Characteristics on Community Image of Public Hospitals (공공보건의료사업 수행과 주민특성이 공공병원 이미지에 미치는 영향)

  • Sim, In Ok;Hwang, Eun Jeong
    • Journal of the Korea Academia-Industrial cooperation Society
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    • v.16 no.9
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    • pp.6089-6098
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    • 2015
  • This study purposes to identify the effects of performance of public health services (PHS) and personal characteristics on community image to public hospitals. The subjects of this study were 33 public hospitals and 1,789 community residents. The data of '2011 Public hospital evaluation programme' were utilized in this study. The personal characteristics consisted of nine items which were gender, age, education, occupation, monthly incomes, medical security, use experience, health state, and location type. The PHS performance consisted of five items which were number of doctors, number of nurses, total number of staff, budget per 1,000 community residents, and amount of activities per 1,000 community residents. The cronbach's alpha of community image instrument was 0.916. As the results of logistic regression, the significant variables of community image, were age (OR=0.34, 95% CI=0.19-0.60), education (OR=3.03, 95% CI=1.60-5.76), use experience (OR=0.57, 95% CI=0.40-0.81), health state (OR=0.69 95% CI=0.49-0.96), location type (OR=2.10, 95% CI=1.11-3.99), and amount of activities per 1,000 community residents (OR=0.58, 95% CI=0.35-0.96). Community image is very important to public hospitals. The workforce and budget related PHS were significantly demanded to improve community image. The Central and Local government should support to public hospitals to perform PHS effectively.

1970s Korean film and landscape of Others -with 'family community' and 'death' motif (1970년대 한국 영화와 타자들의 풍경 -'가족'과 '죽음' 모티프를 중심으로)

  • Han, Young-Hyeon
    • Journal of Popular Narrative
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    • v.25 no.4
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    • pp.429-465
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    • 2019
  • This paper analyzed the ways in which "others" were reproduced in Korean movies in the 1970s. In the midst of the social changes of the era, such as urbanization due to rapid industrial modernization, many people became laborers for industry in order to obtain the fruits of modernization.But the landscape of others, which was inevitably produced in the process of constructing such subjects, has been limited to analysis that is focused on gender and youth discourse. This article aims to extract the landscape of others in the 1970s by adopting a different perspective. The way in which the other is present can be divided into the following two categories. First, in 1970s film, the family community, in contrast with 1960s film, has disintegrated and cracked, due to the inability of others to enter or leave the community. The desperate perception that the family community can no longer function as a stable foundation or center of the constitution, and that it cannot have a sense of security and belonging,is revealed through the way the others are wandering in and out of the community. Second, 'Death' is an element of social life in the violence of the national ideology of the 1970s, and the everyday exceptional state. The way in which the 'other' is completely eliminated from the normal subjectivity requested by the state and is deported in film reflectshow everyday death or potential death is part of life of the 1970s. Normal life pursued through rapid urbanization and industrialization leads to the death of the other beings, but the way of existence of others is the desperate reality of the 1970s, when the boundaries of the state that provide stability and belonging are broken. As a result, the landscape of others in the 1970s reveals a violent reality that destroys the perfect middle class family discourse that industrial modernization was oriented around in the 1970s, and that produced masses of others who caused numerous deaths. In spite of regime censorship, Korean films were popularly revealing the violence of life brought in by the 1970s, following a detour of representation.

A Study on the Establishment of Comparison System between the Statement of Military Reports and Related Laws (군(軍) 보고서 등장 문장과 관련 법령 간 비교 시스템 구축 방안 연구)

  • Jung, Jiin;Kim, Mintae;Kim, Wooju
    • Journal of Intelligence and Information Systems
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    • v.26 no.3
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    • pp.109-125
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    • 2020
  • The Ministry of National Defense is pushing for the Defense Acquisition Program to build strong defense capabilities, and it spends more than 10 trillion won annually on defense improvement. As the Defense Acquisition Program is directly related to the security of the nation as well as the lives and property of the people, it must be carried out very transparently and efficiently by experts. However, the excessive diversification of laws and regulations related to the Defense Acquisition Program has made it challenging for many working-level officials to carry out the Defense Acquisition Program smoothly. It is even known that many people realize that there are related regulations that they were unaware of until they push ahead with their work. In addition, the statutory statements related to the Defense Acquisition Program have the tendency to cause serious issues even if only a single expression is wrong within the sentence. Despite this, efforts to establish a sentence comparison system to correct this issue in real time have been minimal. Therefore, this paper tries to propose a "Comparison System between the Statement of Military Reports and Related Laws" implementation plan that uses the Siamese Network-based artificial neural network, a model in the field of natural language processing (NLP), to observe the similarity between sentences that are likely to appear in the Defense Acquisition Program related documents and those from related statutory provisions to determine and classify the risk of illegality and to make users aware of the consequences. Various artificial neural network models (Bi-LSTM, Self-Attention, D_Bi-LSTM) were studied using 3,442 pairs of "Original Sentence"(described in actual statutes) and "Edited Sentence"(edited sentences derived from "Original Sentence"). Among many Defense Acquisition Program related statutes, DEFENSE ACQUISITION PROGRAM ACT, ENFORCEMENT RULE OF THE DEFENSE ACQUISITION PROGRAM ACT, and ENFORCEMENT DECREE OF THE DEFENSE ACQUISITION PROGRAM ACT were selected. Furthermore, "Original Sentence" has the 83 provisions that actually appear in the Act. "Original Sentence" has the main 83 clauses most accessible to working-level officials in their work. "Edited Sentence" is comprised of 30 to 50 similar sentences that are likely to appear modified in the county report for each clause("Original Sentence"). During the creation of the edited sentences, the original sentences were modified using 12 certain rules, and these sentences were produced in proportion to the number of such rules, as it was the case for the original sentences. After conducting 1 : 1 sentence similarity performance evaluation experiments, it was possible to classify each "Edited Sentence" as legal or illegal with considerable accuracy. In addition, the "Edited Sentence" dataset used to train the neural network models contains a variety of actual statutory statements("Original Sentence"), which are characterized by the 12 rules. On the other hand, the models are not able to effectively classify other sentences, which appear in actual military reports, when only the "Original Sentence" and "Edited Sentence" dataset have been fed to them. The dataset is not ample enough for the model to recognize other incoming new sentences. Hence, the performance of the model was reassessed by writing an additional 120 new sentences that have better resemblance to those in the actual military report and still have association with the original sentences. Thereafter, we were able to check that the models' performances surpassed a certain level even when they were trained merely with "Original Sentence" and "Edited Sentence" data. If sufficient model learning is achieved through the improvement and expansion of the full set of learning data with the addition of the actual report appearance sentences, the models will be able to better classify other sentences coming from military reports as legal or illegal. Based on the experimental results, this study confirms the possibility and value of building "Real-Time Automated Comparison System Between Military Documents and Related Laws". The research conducted in this experiment can verify which specific clause, of several that appear in related law clause is most similar to the sentence that appears in the Defense Acquisition Program-related military reports. This helps determine whether the contents in the military report sentences are at the risk of illegality when they are compared with those in the law clauses.