• Advanced Industrial SCIence
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• v.3 no.2
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• pp.17-22
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• 2024

Recently, as the ICT field has been used in various environments, it has become possible to analyze pests by crops, use robots when harvesting crops, and predict by big data by utilizing ICT technologies in a sustainable agricultural environment. However, in a sustainable agricultural environment, efforts to solve resource depletion, agricultural population decline, poverty increase, and environmental destruction are constantly being demanded. This paper proposes an artificial intelligence-based big data processing analysis method to reduce the production cost and increase the efficiency of crops based on a sustainable agricultural environment. The proposed technique strengthens the security and reliability of data by processing big data of crops combined with AI, and enables better decision-making and business value extraction. It can lead to innovative changes in various industries and fields and promote the development of data-oriented business models. During the experiment, the proposed technique gave an accurate answer to only a small amount of data, and at a farm site where it is difficult to tag the correct answer one by one, the performance similar to that of learning with a large amount of correct answer data (with an error rate within 0.05) was found.

• Journal of Internet of Things and Convergence
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• v.10 no.2
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• pp.125-130
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• 2024

With the rapid growth of mobility technology, the industrial sector is demanding storage devices that can reliably process data from various equipment and sensors in vehicles. NAND flash memory is being utilized as a storage device in mobility environments because it has the advantages of low power and fast data processing speed as well as strong external shock resistance. However, flash memory is characterized by data corruption due to long-term exposure to high temperatures. Therefore, a dedicated system for temperature management is required in mobility environments where high temperature exposure due to weather or external heat sources such as solar radiation is frequent. This paper designs a dedicated temperature management system for managing storage device temperature in a mobility environment. The designed temperature management system is a hybrid of traditional air cooling and water cooling technologies. The cooling method is designed to operate adaptively according to the temperature of the storage device, and it is designed not to operate when the temperature step is low to improve energy efficiency. Finally, experiments were conducted to analyze the temperature difference between each cooling method and different heat dissipation materials, proving that the temperature management policy is effective in maintaining performance.

• Journal of the Korea Society of Computer and Information
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• v.29 no.1
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• pp.41-49
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• 2024

Speech recognition technology is continuously advancing and widely used in various fields. In this study, we aimed to investigate the impact of speech data quality on speech recognition models by dividing the dataset into the entire dataset and the top 70% based on Signal-to-Noise Ratio (SNR). Utilizing Seamless M4T and Google Cloud Speech-to-Text, we examined the text transformation results for each model and evaluated them using the Levenshtein Distance. Experimental results revealed that Seamless M4T scored 13.6 in models using data with high SNR, which is lower than the score of 16.6 for the entire dataset. However, Google Cloud Speech-to-Text scored 8.3 on the entire dataset, indicating lower performance than data with high SNR. This suggests that using data with high SNR during the training of a new speech recognition model can have an impact, and Levenshtein Distance can serve as a metric for evaluating speech recognition models.

• Journal of Industrial Convergence
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• v.22 no.1
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• pp.185-195
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• 2024

The purpose of this study is to comprehensively interpret the practical adaptation experience of male nurses working shifts and to understand the meaning and essence. The data collection period was from September 2022 to November 2022 and in-depth interviews were conducted with 9 male nurses working at tertiary general hospitals, general hospitals, special hospitals and long-term care hospitals until content saturation. Data analysis was applied according to Colaizzi's phenomenological research method, and as a result of the study, 4 categories, and 11 theme were derived. The 4 categories consisted of 'Changes due to shift work', 'Difficulties arising from gender differences', 'Adaptation for job performance', and 'Growth and direction for the future'. Through this study, it was possible to explore the meaning of the practical adaptation experience of male nurses working in shifts, and it was found that it was necessary to develop and apply work environment improvement plans and male nurses' capacity building programs for nursing work.

• Journal of Ginseng Research
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• v.48 no.3
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• pp.245-252
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• 2024

Ginseng is a traditional herbal medicine used for prevention and treatment of various diseases as a tonic. Recent scientific cohort studies on life prolongation with ginseng consumption support this record, as those who consumed ginseng for more than 5 years had reduced mortality and cognitive decline compared to those who did not. Clinical studies have also shown that acute or long-term intake of ginseng total extract improves acute working memory performance or cognitive function in healthy individuals and those with subjective memory impairment (SMI), mild cognitive impairment (MCI), or early Alzheimer's disease (AD) dementia who are taking AD medication(s). Ginseng contains various components ranging from classical ginsenosides and polysaccharides to more recently described gintonin. However, it is unclear which ginseng component(s) might be the main candidate that contribute to memory or cognitive improvements or prevent cognitive decline in older individuals. This review describes recent clinical contributors to ginseng components in clinical tests and introduces emerging evidence that ginseng components could be novel candidates for cognitive improvement in older individuals, as ginseng components improve SMI cognition and exhibits add-on effects when coadministered with early AD dementia drugs. The mechanism behind the beneficial effects of ginseng components and how it improves cognition are presented. Additionally, this review shows how ginseng components can contribute to SMI, MCI, or early AD dementia when used as a supplementary food and/or medicine, and proposes a novel combination therapy of current AD medicines with ginseng component(s).

• Journal of the Korean Society of Radiology
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• v.81 no.6
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• pp.1290-1304
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• 2020

Medical image analyses have been widely used to differentiate normal and abnormal cases, detect lesions, segment organs, etc. Recently, owing to many breakthroughs in artificial intelligence techniques, medical image analyses based on deep learning have been actively studied. However, sufficient medical data are difficult to obtain, and data imbalance between classes hinder the improvement of deep learning performance. To resolve these issues, various studies have been performed, and data augmentation has been found to be a solution. In this review, we introduce data augmentation techniques, including image processing, such as rotation, shift, and intensity variation methods, generative adversarial network-based method, and image property mixing methods. Subsequently, we examine various deep learning studies based on data augmentation techniques. Finally, we discuss the necessity and future directions of data augmentation.

• Journal of Korean Society for Quality Management
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• v.52 no.1
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• pp.43-56
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• 2024

Purpose: The injection molding process, crucial for plastic shaping, encounters difficulties in sustaining product quality when replacing injection machines. Variations in machine types and outputs between different production lines or factories increase the risk of quality deterioration. In response, the study aims to develop a system that optimally adjusts conditions during the replacement of injection machines linked to molds. Methods: Utilizing a dataset of 12 injection process variables and 52 corresponding sensor variables, a predictive model is crafted using Decision Tree, Random Forest, and XGBoost. Model evaluation is conducted using an 80% training data and a 20% test data split. The dependent variable, classified into five characteristics based on temperature and pressure, guides the prediction model. Bayesian optimization, integrated into the selected model, determines optimal values for process variables during the replacement of injection machines. The iterative convergence of sensor prediction values to the optimum range is visually confirmed, aligning them with the target range. Experimental results validate the proposed approach. Results: Post-experiment analysis indicates the superiority of the XGBoost model across all five characteristics, achieving a combined high performance of 0.81 and a Mean Absolute Error (MAE) of 0.77. The study introduces a method for optimizing initial conditions in the injection process during machine replacement, utilizing Bayesian optimization. This streamlined approach reduces both time and costs, thereby enhancing process efficiency. Conclusion: This research contributes practical insights to the optimization literature, offering valuable guidance for industries seeking streamlined and cost-effective methods for machine replacement in injection molding.

• Quality Improvement in Health Care
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• v.29 no.2
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• pp.47-63
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• 2023

Purpose:This study aims to suggest the future direction for applying service design to improve the quality of healthcare as part of hospital service innovation and present implementation plans in Korea, based on a review of quality improvement activities and the current status of service design applications. Methods: Through a literature review, we examined the status of service design introduction and application in the healthcare field, focusing on cases in the US and Europe. The possibility and limitations of service design in the healthcare field were examined through a comparison of oversea and domestic cases. Results: Recently, service design has begun to be applied to the healthcare field worldwide. Service design shows the possibility of an alternative that alleviates and complements the limitations of existing quality improvement activities. It also offers the possibility of creating new organizational improvement and innovation approaches through integration and convergence with existing quality improvement activities and management innovation. Conclusion: To effectively apply service design to hospitals, it is necessary to integrate internal organizations related to service improvement, combine methods, and objectively measure and evaluate performance. To this end, we propose the operation of a nationwide education and training center for quality improvement and service design led by academic society. Service design will provide an opportunity to change the management innovation and organizational culture of hospitals beyond the scope of the current quality improvement, which deals only with micro-subjects of individual hospitals.

• The Journal of the Convergence on Culture Technology
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• v.10 no.2
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• pp.257-266
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• 2024

This study analyzed the characteristics of each type of subjective perception of cabin crew by applying Q-methodology to understand the competencies required of airline cabin crew. As a result of analyzing 33 Q-samples and 33 P-samples using the Ken-Q Analysis program, four types were identified: "Physical strength and appearance quality-oriented", "job performance-oriented", "communication ability-oriented", and "job consciousness-oriented". Most types showed high agreement on physical factors, ability to cope with emergency situations and work responsibility. The results can be used as basic data to develop effective curriculum for airline training course and airline service majors, and it can be a reference material to help job seekers understand the job and cultivate necessary competencies.

• The Journal of the Convergence on Culture Technology
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• v.10 no.2
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• pp.525-530
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• 2024

The need for an environmental monitoring system that obtains and provides environmental information in real time is increasing. In particular, in the case of water quality management in public waters, regular management must be conducted through manual and automatic measurement by law, and air pollution also requires regular measurement and management to reduce fine dust and exhaust gas in connection with the realization of carbon neutrality. In this study, we implemented a system that can measure and monitor water pollution and air pollution information in real time. A hovercraft capable of moving on land and water simultaneously was used as a measurement tool. Water quality measurement and air pollution measurement sensors were installed on the hovercraft body, and a communication module was installed to transmit the information to the monitoring system in real time. The structure of a hovercraft for environmental measurement was designed, and a LoRa module capable of low-power, long-distance communication was applied as a real-time information transmission communication module. The operational performance of the proposed system was confirmed through actual hardware implementation.