• 디지털산업정보학회논문지
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• 제19권2호
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• pp.11-25
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• 2023

With the increasing advancement of VLSI technology, health care system is also developing to serve the humanity with better care. Therefore, biomedical implantable devices are one of the amazing important invention of scientist to collect data from the body cell for the diagnosis of diseases without any pain. This Biomedical implantable transceiver circuit has several important issues. Oscillator is one of them. For the design flexibility and complete transistor-based architecture ring oscillator is favorite to the oscillator circuit designer. This paper represents the design and analysis of the a 9-stage CMOS ring oscillator using cadence virtuoso tool in 180nm technology. It is also designed to generate the carrier signal of 403.5MHz frequency. Ring oscillator comprises of odd number of stages with a feedback circuit forming a closed loop. This circuit was designed with 9-stages of delay inverter and simulated for various parameters such as delay, phase noise or jitter and power consumption. The average power consumption for this oscillator is 9.32㎼ and average phase noise is only -86 dBc/Hz with the source voltage of 0.8827V.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제17권9호
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• pp.2334-2347
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• 2023

Metaverse services generate text data, data of ubiquitous computing, in real-time to analyze user emotions. Analysis of user emotions is an important task in metaverse services. This study aims to classify user sentiments using deep learning and pre-trained language models based on the transformer structure. Previous studies collected data from a single platform, whereas the current study incorporated the review data as "Metaverse" keyword from the YouTube and Google Play Store platforms for general utilization. As a result, the Bidirectional Encoder Representations from Transformers (BERT) and Robustly optimized BERT approach (RoBERTa) models using the soft voting mechanism achieved a highest accuracy of 88.57%. In addition, the area under the curve (AUC) score of the ensemble model comprising RoBERTa, BERT, and A Lite BERT (ALBERT) was 0.9458. The results demonstrate that the ensemble combined with the RoBERTa model exhibits good performance. Therefore, the RoBERTa model can be applied on platforms that provide metaverse services. The findings contribute to the advancement of natural language processing techniques in metaverse services, which are increasingly important in digital platforms and virtual environments. Overall, this study provides empirical evidence that sentiment analysis using deep learning and pre-trained language models is a promising approach to improving user experiences in metaverse services.

• 소성∙가공
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• 제32권6호
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• pp.329-334
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• 2023

The process of heat treatment in cold forging is an essential role in enhancing mechanical properties. However, it relies heavily on the experience and skill of individuals. The aim of this study is to predict hardness using machine learning to optimize production efficiency in cold forging manufacturing. Random Forest (RF), Gradient Boosting Regressor (GBR), Extra Trees (ET), and ADAboosting (ADA) models were utilized. In the result, the RF, GBR, and ET models show the excellent performance. However, it was observed that GBR and ET models leaned significantly towards the influence of temperature, unlike the RF model. We suggest that RF model demonstrates greater reliability in predicting hardness due to its ability to consider various variables that occur during the cold forging process.

• 로봇학회논문지
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• 제18권4호
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• pp.436-443
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• 2023

With the advancement of robot intelligence, the concept of man and unmanned teaming (MUM-T) has garnered considerable attention in military research. In this paper, we present a transformer-based architecture for predicting the health status of agents, with the help of multi-head attention mechanism to effectively capture the dynamic interaction between friendly and enemy forces. To this end, we first introduce a framework for generating a dataset of battlefield situations. These situations are simulated on a virtual simulator, allowing for a wide range of scenarios without any restrictions on the number of agents, their missions, or their actions. Then, we define the crucial elements for identifying the battlefield, with a specific emphasis on agents' status. The battlefield data is fed into the transformer architecture, with classification headers on top of the transformer encoding layers to categorize health status of agent. We conduct ablation tests to assess the significance of various factors in determining agents' health status in battlefield scenarios. We conduct 3-Fold corss validation and the experimental results demonstrate that our model achieves a prediction accuracy of over 98%. In addition, the performance of our model are compared with that of other models such as convolutional neural network (CNN) and multi layer perceptron (MLP), and the results establish the superiority of our model.

• 시스템엔지니어링학술지
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• 제19권2호
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• pp.1-17
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• 2023

This study aimed to examine the characteristics of ESG activities among major domestic companies in the carbon-emitting industry compared to industries with lower emissions, as ESG has emerged as a significant agenda across various industries. Departing from the traditional focus on the "why" of ESG, which primarily centers around financial performance, this research sought to uncover the "how" of effective ESG management in domestic companies. The analysis involved studying the sustainability reports of 124 companies using the Global Reporting Initiative (GRI) indicators and comparing high-emitting and non-high-emitting industries. The findings revealed industry-specific patterns in companies' ESG activities, providing valuable insights for future ESG evaluations and assessments. Furthermore, the advancement of rating analysis methods holds implications for ESG rating agencies and financial authorities in terms of policy-making.

• 중환자간호학회지
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• 제17권1호
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• pp.17-29
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• 2024

Purpose : This study sought to investigate novice nurses' communication education needs in the intensive care unit (ICU) using Importance-Performance Analysis (IPA) and Borich's need assessment model. This study identified communication challenges in clinical settings to develop a simulation program that enhances communication competencies based on educational requirements. Methods : A descriptive research design and a self-report questionnaire were used. The latter was developed and administered to 121 novice nurses with less than one year of experience in the ICU at various university hospitals in Korea. Data were collected via the online open chatroom from June 24th to July 28th, 2023. The communication education needs were identified using descriptive statistics, t-tests, IPA, and Borich's needs assessment model. Text analysis was used to categorize the participants' communication experience. Results : The results revealed that "communication with physicians," "communication with patients," and "communication with nurse on another shift" domains contained the most substantial educational needs for novice nurses working in the intensive care units. Conclusion : The results provide fundamental data for developing and enhancing customized communication education programs for novice ICU nurses. This valuable information could help ICU nurses and educators improve new nurses' communication skills, which would ultimately contribute to the advancement of nursing education and clinical practice.

• Asia pacific journal of information systems
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• 제34권1호
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• pp.321-350
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• 2024

When a competent employee leaves an organization, the technical skills and know-how possessed by that employee also disappear, which may lead to various problems, such as a decrease in organizational morale and technology leakage. To address such problems, it is important to increase employees' job satisfaction. Due to the advancement of both information and communication technology and social media, many former and current employees share information regarding companies in which they have worked or for which they currently work via job portal websites. In this study, a web crawl was used to collect reviews and job satisfaction ratings written by all and incumbent employees working in nine industries from Job Planet, a Korean job portal site. According to this analysis, regardless of the industry in question, organizational culture, welfare support, work system, growth capability and relationships had significant positive effects on job satisfaction, while time and attendance management, performance management, and organizational flexibility had significant negative effects on job satisfaction. With respect to the path difference between former and current employees, time and attendance management and organizational flexibility have greater negative effects on job satisfaction for current employees than for former employees. On the other hand, organizational culture, work system, and relationships had greater positive effects for current employees than for former employees.

• 한국정보전자통신기술학회논문지
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• 제17권1호
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• pp.47-52
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• 2024

코로나 펜데믹을 거치면서 중앙정부, 지방정부, 민간사업자를 중심으로 블록체인 기반 탈중앙화 신원인증(Decentralized ID) 기술 활용 및 고도화 연구가 다양한 분야에서 활발하게 진행되고 있다. 본 논문에서는 기존 중앙 서버 기반 신원인증을 탈중앙화 기반으로 변경하기 위해 하이퍼레저 패브릭 기반으로 개발한 결과를 소개한다. 이러한 개발 결과는 상용화 목적의 신원인증 시스템에 보안성, 투명성을 강화하여 사용자 ID 발급, 조회, 폐기에 대해 안정적인 서비스를 제공할 수 있다. 또한, 탈중앙화된 신원인증 시스템은 DID 생성 262,000 rps, DID 조회 1,850 rps 성능과 DID VP 생성 200 rps, DID VP 조회 220 rps 이하의 성능 결과를 공인 인증을 통해 검증하였다.

• Advances in concrete construction
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• 제16권5호
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• pp.255-267
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• 2023

The production of ultra-early-strength concrete (UESC) traditionally involves complexity or necessitates high-temperature curing conditions. However, this study aimed to achieve ultra-early-strength performance solely through room-temperature curing. Experimental results demonstrate that under room-temperature (28℃) curing conditions, the concrete attained compressive strengths of 20 MPa at 4 hours and 69.6 MPa at 24 hours. Additionally, it exhibited a flexural strength of 7.5 MPa after 24 hours. In contrast, conventional concrete typically reaches around 20.6 MPa (3,000 psi) after approximately 28 days, highlighting the rapid strength development of the UESC. This swift attainment of compressive strength represents a significant advancement for engineering purposes. Small amounts of steel fibers (0.5% and 1% by volume, respectively) were added to address potential concrete cracking due to early hydration heat and enhance mechanical properties. This allowed observation of the effects of different volume contents on ultra-early-strength fiber-reinforced concrete (UESFRC). Furthermore, the compressive strength of 0.5% and 1% UESFRC increased by 16.3% and 31.3%, respectively, while the flexural strength increased by 37.1% and 47.9%. Moreover, toughness increased by 58.2 and 69.7 times, respectively. These findings offer an effective solution for future emergency applications in public works.

• Geomechanics and Engineering
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• 제37권1호
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• pp.21-29
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• 2024

The effective management of damage in tunnels is crucial for ensuring their safety, longevity, and operational efficiency. In this paper, we propose an educational management model tailored specifically for addressing damage in tunnels, utilizing numerical solution techniques. By leveraging advanced computational methods, we aim to develop a comprehensive understanding of the factors contributing to tunnel damage and to establish proactive measures for mitigation and repair. The proposed model integrates principles of tunnel engineering, structural mechanics, and numerical analysis to facilitate a systematic approach to damage assessment, diagnosis, and management. Through the application of numerical solution techniques, such as finite element analysis, we demonstrate the efficacy of the proposed model in simulating various damage scenarios and predicting their impact on tunnel performance. Additionally, the educational component of the model provides valuable insights and training opportunities for tunnel management personnel, empowering them to make informed decisions and implement effective strategies for ensuring the structural integrity and safety of tunnel infrastructure. Overall, the proposed educational management model represents a significant advancement in tunnel management practices, offering a proactive and knowledge-driven approach to addressing damage and enhancing the resilience of tunnel systems.