• Journal of Digital Convergence
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• v.19 no.4
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• pp.19-24
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• 2021

In this paper, an index of women's safety facilities was created and visualized using public data related to Seoul. CPTED, the women's safety facilities index was created by collecting and analyzing eight data related to the local women's safety index and five major crime victims of women. As a result of the correlation analysis between the factors of the female safety facility index and the number of female crime victims, three data were selected as the main factors, "CCTV," "street lamps," and "female security guardians", which were found to be meaningful at the 95% level of reliability. The distinction women's safety facility index was calculated by weighting the correlation coefficient between the main factors for calculating the women's safety facility index, and visualized using Python's Follium library.

• Journal of Distribution Science
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• v.20 no.7
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• pp.107-117
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• 2022

Purpose: The scope of forensic investigations serves to identify malicious activities, including leakage of crucial corporate information. The investigations also identify security lapses in available networks. The purpose of the present study is to explore how to block distribution channels to protect illegal leakage in supply chain through digital forensic method. Research design, data and methodology: The present study conducted the qualitative textual analysis and its data collection process entails five steps: identifying and collecting data, determining coding categories, coding the content, checking validity and reliability, and analyzing and presenting the results. This methodology is a significant research method due to its high quality of previous resources. Results: Applying previous literature analysis to the results of this study, the author figured out that there are four solutions as an evidences to block distribution channels, preventing illegal leakage regarding company information. The following subtitles show clear solutions: (1) Communicate with Stakeholders, (2) Preventing and addressing illegal leakage, (3) Victims of Data Breach, (4) Focusing Solely on Technical Teams. Conclusion: There are difficult scenarios that continue to introduce difficult questions surrounding engagement with digital evidence. Consequently, it is important to enhance data handling to provide answers for organizations that suffer due to illegal leakages of sensitive information.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.15 no.3
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• pp.814-836
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• 2021

Wildlife ecologists and biologists recapture deer to collect tracking data from deer collars or wait for a drop-off of a deer collar construction that is automatically detached and disconnected. The research teams need to manage a base camp with medical trailers, helicopters, and airplanes to capture deer or wait for several months until the deer collar drops off of the deer's neck. We propose an intelligent robust base-station research with a low-cost and time saving method to obtain recording sensor data from their collars to a listener node, and readings are obtained without opening the weatherproof deer collar. We successfully designed the and implemented a robust base station system for automatically collecting data of the collars and listener motes in harsh wilderness environments. Intelligent solutions were also analyzed for improved data collections and pattern predictions with drone-based detection and tracking algorithms.

• Journal of the Korea Institute of Military Science and Technology
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• v.25 no.5
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• pp.513-521
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• 2022

This study deals with an AI architecture model for collecting battlefield data using the tactical C4I system. Based on this model, the artificial staff can be utilized in tactical echelon. In the current structure of the Army's tactical C4I system, Servers are operated by brigade level and above and divided into an active and a standby server. In this C4I system structure, the AI server must also be installed in each unit and must be switched when the C4I server is switched. The tactical C4I system operates a server(DB) for each unit, so data matching is partially delayed or some data is not matched in the inter-working process between servers. To solve these issues, this study presents an operation concept so that all of alternate server can be integrated based on virtualization technology, which is used as an source data for AI Meta DB. In doing so, this study can provide criteria for the AI architectural model of the ground tactical echelon.

• International Journal of Computer Science & Network Security
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• v.23 no.8
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• pp.137-145
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• 2023

E-Commerce is a buzzword well known for electronic commerce activities including but not limited to the online shopping, digital payment transactions, and B2B online trading. In today's digital age, e-commerce has been playing a very important and vital role in areas such as retail shopping, sales automation, supply chain management, marketing and advertisement, and payment services. With a huge amount of data been collected from various e-commerce services available, there are multiple opportunities to use that data to analyze graphs and trends. Strategize profitable activities, and forecast future trade. This paper explains a contemporary approach for collecting key data metrics and implementing cost-effective automation that will support in improving conversion rates and sales performance of the e-commerce websites resulting in increased profitability.

• International conference on construction engineering and project management
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• 2022.06a
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• pp.50-56
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• 2022

Change Orders generally impact cost and schedule performance of highway projects. However, highway projects that do not have any change orders also face cost growth and schedule delays. This study seeks to determine the cost and schedule performance of Texas DOT projects by collecting project data for 120 highway projects completed between 2016 to 2020. For the study, we selected project data that has zero or negative change orders which were then grouped and analyzed based on their Project Types i.e., maintenance works; structural works; restoration and rehabilitation works; and safety works. The study found that performance of Maintenance and Safety type projects had less cost and schedule growth among the data analyzed. Statistical tests also found that even though the projects have no change orders, Rehabilitation and Restoration type projects experienced significant schedule growth compared to others. However, the data did not show any significant cost and schedule growth for the projects when statistical tests were performed on overall data. The study concluded that highway projects are experiencing schedule growth even though the projects had no change orders. Results from the study can help planners, engineers, and administrators to gain better insight on how different types of highway projects are performing in terms of cost and schedule and eventually derive appropriate solutions to minimize cost and schedule growth in such projects.

• Journal of Korea Society of Digital Industry and Information Management
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• v.18 no.1
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• pp.37-45
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• 2022

With the development of the 4th industry, big data using AI is being used in many areas of our lives, and the importance of data is increasing accordingly. In particular, as various services using personal information appear and hacking attacks that exploit them appear in various ways, the importance of personal information management is increasing. Personal information must be managed safely even when collecting, retaining, using, providing, and destroying personal information, and the rights of information subjects must be protected. In this paper, an analysis was performed on the notification of usage history during the protection of the rights of information subjects using the MyData model. According to the Personal Information Protection Act, users must be periodically notified of the use of personal information, so we notify each individual of the use of personal information through e-mail or SNS once a year. It is difficult to understand and manage which company use my personal information. Therefore, in this paper, a personal information usage history notification system model was proposed, and as a result of performance analysis, it is possible to provide the controllability, availability, integrity, source authentication, and personal information self-determination rights.

• The Journal of Korea Robotics Society
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• v.18 no.2
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• pp.182-188
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• 2023

Due to the acceleration of an aging society, the need for lower limb exoskeletons to assist gait is increasing. And for use in daily life, it is essential to have technology that can accurately estimate gait phase even in the walking environment and walking speed of the wearer that changes frequently. In this paper, we implement an LSTM-based gait phase estimation learning model by collecting gait data according to changes in gait speed in outdoor level ground and stair environments. In addition, the results of the gait phase estimation error for each walking environment were compared after learning for both max hip extension (MHE) and max hip flexion (MHF), which are ground truth criteria in gait phase divided in previous studies. As a result, the average error rate of all walking environments using MHF reference data and MHE reference data was 2.97% and 4.36%, respectively, and the result of using MHF reference data was 1.39% lower than the result of using MHE reference data.

• Proceedings of the Korean Society of Computer Information Conference
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• 2021.07a
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• pp.667-669
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• 2021

본 논문에서는 벡터 기반 데이터 증강 기법(Data augmentation)을 제안하여 학습 데이터를 구축한 뒤, 이를 합성곱 신경망(Convolutional Neural Networks, CNN)으로 실제 균열과 가까운 패턴을 표현할 수 있는 프레임워크를 제안한다. 건축물의 균열은 인명 피해를 가져오는 건물 붕괴와 낙하 사고를 비롯한 큰 사고의 원인이다. 이를 인공지능으로 해결하기 위해서는 대량의 데이터 확보가 필수적이다. 하지만, 실제 균열 이미지는 복잡한 패턴을 가지고 있을 뿐만 아니라, 위험한 상황에 노출되기 때문에 대량의 데이터를 확보하기 어렵다. 이러한 데이터베이스 구축의 문제점은 인위적으로 특정 부분에 변형을 주어 데이터양을 늘리는 탄성왜곡(Elastic distortion) 기법으로 해결할 수 있지만, 본 논문에서는 이보다 향상된 균열 패턴 결과를 CNN을 활용하여 보여준다. 탄성왜곡 기법보다 CNN을 이용했을 때, 실제 균열 패턴과 유사하게 추출된 결과를 얻을 수 있었고, 일반적으로 사용되는 픽셀 기반 데이터가 아닌 벡터 기반으로 데이터 증강을 설계함으로써 균열의 변화량 측면에서 우수함을 보였다. 본 논문에서는 적은 개수의 균열 데이터를 입력으로 사용했음에도 불구하고 균열의 방향 및 패턴을 다양하게 생성하여 쉽게 균열 데이터베이스를 구축할 수 있었다. 이는 장기적으로 구조물의 안정성 평가에 이바지하여 안전사고에 대한 불안감에서 벗어나 더욱 안전하고 쾌적한 주거 환경을 조성할 것으로 기대된다.

• The Journal of Industrial Distribution & Business
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• v.14 no.7
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• pp.19-26
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• 2023

Purpose: This study explores the intrinsic and extrinsic stress factors that affect employees' job satisfaction. The study reviews the literature on three intrinsic and three extrinsic stress factors that influence the job satisfaction level of employees, establishing the various research findings on the factors and finding the relevant links that such findings have to current research. Research design, data and methodology: The present researcher collected the relevant prior studies via literature content approach that was used by numerous previous works. The researcher transcribed the data gathered from the participants. The next analyst would code the different features of data systematically across the entire set of data, thereby collecting the relevant data for each of the codes. Results: The investigation suggests six stress factors to be connected to job satisfaction, such as Hours of Work Employee Job Satisfaction, Communication and Employee job Satisfaction, Leadership Style Employee Job Satisfaction, Competition Employee Job Satisfaction, Career Development Opportunities Employee Job Satisfaction, Strikes and employee Job Satisfaction Conclusions: This research concludes that organizations with proper communication channels will certainly influence their employees positively and hence give them job satisfaction. Overall, this qualitative research has found that intrinsic and extrinsic factors influence the job satisfaction level of employees in a workplace.