• Journal of Information Processing Systems
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• v.20 no.4
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• pp.558-573
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• 2024

Considering factors such as illumination, camera quality variations, and background-specific variations, identifying a face using a smartphone-based facial image capture application is challenging. Face Image Quality Assessment refers to the process of taking a face image as input and producing some form of "quality" estimate as an output. Typically, quality assessment techniques use deep learning methods to categorize images. The models used in deep learning are shown as black boxes. This raises the question of the trustworthiness of the models. Several explainability techniques have gained importance in building this trust. Explainability techniques provide visual evidence of the active regions within an image on which the deep learning model makes a prediction. Here, we developed a technique for reliable prediction of facial images before medical analysis and security operations. A combination of gradient-weighted class activation mapping and local interpretable model-agnostic explanations were used to explain the model. This approach has been implemented in the preselection of facial images for skin feature extraction, which is important in critical medical science applications. We demonstrate that the use of combined explanations provides better visual explanations for the model, where both the saliency map and perturbation-based explainability techniques verify predictions.

• International Journal of Internet, Broadcasting and Communication
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• v.16 no.3
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• pp.262-273
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• 2024

We provide a detailed analysis of the data processing and model training process for vulnerability classification using Transformer-based language models, especially sentence text-to-text transformers (ST5)-XXL and XLNet. The main purpose of this study is to compare the performance of the two models, identify the strengths and weaknesses of each, and determine the optimal learning rate to increase the efficiency and stability of model training. We performed data preprocessing, constructed and trained models, and evaluated performance based on data sets with various characteristics. We confirmed that the XLNet model showed excellent performance at learning rates of 1e-05 and 1e-04 and had a significantly lower loss value than the ST5-XXL model. This indicates that XLNet is more efficient for learning. Additionally, we confirmed in our study that learning rate has a significant impact on model performance. The results of the study highlight the usefulness of ST5-XXL and XLNet models in the task of classifying security vulnerabilities and highlight the importance of setting an appropriate learning rate. Future research should include more comprehensive analyzes using diverse data sets and additional models.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.18 no.9
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• pp.2589-2604
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• 2024

Brain tumors, characterized by uncontrollable cellular growths, are a significant global health challenge. Navigating the complexities of tumor identification due to their varied dimensions and positions, our research introduces enhanced methods for precise detection. Utilizing advanced learning techniques, we've improved early identification by preprocessing clinical dataset-derived images, augmenting them via a Generative Adversarial Network, and applying an Improved Privacy-Preserving Collaborative Convolutional Neural Network (IPC-CNN) for segmentation. Recognizing the critical importance of data security in today's digital era, our framework emphasizes the preservation of patient privacy. We evaluated the performance of our proposed model on the Figshare and BRATS 2018 datasets. By facilitating a collaborative model training environment across multiple healthcare institutions, we harness the power of distributed computing to securely aggregate model updates, ensuring individual data protection while leveraging collective expertise. Our IPC-CNN model achieved an accuracy of 99.40%, marking a notable advancement in brain tumor classification and offering invaluable insights for both the medical imaging and machine learning communities.

• International Journal of Advanced Culture Technology
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• v.12 no.3
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• pp.140-147
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• 2024

Oil and gas industry is a unique sector with complex activities, long supply chains and strict rules for the business. It is important to use enterprise resource planning (ERP) systems to address these challenges as it helps in simplifying operations, improving efficiency and facilitating evidence-based decision making. Nonetheless, successful integration of ERP systems in this industry involves careful planning, customization and alignment with specific business processes including regulatory requirements. Several critical factors, such as strong change management, support of top managers and training that works have been identified in the study. Amongst the hurdles are employee resistance towards the changes, data migration complications and integration with existing systems. Nonetheless, NOCL's ERP implementation resulted in significant improvements in operating efficiency, better data visibility and compliance management. It also led to a decrease in financial reporting timeframes, more accurate inventory tracking and improved decision-making capabilities. The study provides useful insights on how to optimize oil and gas sector ERP implementations; key among them is practical advice including strengthening change management strategies, prioritizing data security and collaborating with ERP vendors. The research highlights the importance of tailoring ERP solutions to specific industry needs as well as emphasizes the strategic role of ongoing monitoring/feedback for future benefits sustainability.

• Journal of Korean Society for Quality Management
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• v.52 no.3
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• pp.509-527
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• 2024

Purpose: This study aims to investigate the factors influencing the adoption of Generative AI in the workplace, focusing on both enablers and inhibitors. By employing the dual factor theory, this research examines how knowledge support, customization, entertainment, perceived risk, realistic threat, and identity threat impact the intention to adopt Generative AI technologies such as ChatGPT. Methods: Data were collected from 192 participants via MTurk, all of whom had experience using Generative AI. The survey was conducted in June 2024, and the data were analyzed using Partial Least Squares Structural Equation Modeling (PLS-SEM) to ensure the validity and reliability of the measurement model. Attention-check questions were used to ensure data quality, and participants provided demographic information at the end of the survey. Results: : The findings reveal that knowledge support and entertainment significantly enhance the intention to adopt Generative AI, whereas realistic threat poses a substantial barrier. Customization, perceived risk, and identity threat did not significantly affect adoption intentions. Conclusion: This study contributes to the literature by addressing the gap in understanding the adoption mechanisms of Generative AI in professional settings. It highlights the importance of promoting AI's knowledge support and entertainment capabilities while addressing employees' concerns about job security. Organizations should emphasize these benefits and proactively mitigate perceived threats to foster a positive reception of Generative AI technologies. The findings offer practical implications for enhancing user acceptance and provide a foundation for future research in this area.

• Journal of Legislation Research
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• no.41
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• pp.87-123
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• 2011

Korea is expected to become an 'aged society' with more than 14 percent of the public aged 65 years or more by 2018. The rapid aging is giving rise to various problems within the society along with falling birthrate in a short period of time. In this context, the role and function of laws on welfare for the aged must be particularly emphasized. Also the Senior Citizens Welfare Act is of great importance as it provides social welfare service on the basis of functional connection with social insurance and public assistance. First, this paper looks into the history of laws related to welfare for the elderly such as the Senior Welfare Act, the Act on Long-term Care Insurance for Senior Citizens and the Basic Old Age Pension Act as well as the findings of earlier studies. In the second place, it will break down such laws by main components aiming to examine details of the laws and questions raised regarding them and to seek ways to achieve improvement with an emphasis on health care, old age income security, housing welfare(assisted living facilities), job security for the aged. The Senior Welfare Act offers substance of social welfare service for the elderly. Income security, health and medical care, welfare measures through long-term care and assisted living facilities, social participation by working are the key elements and all of them should be closely associated to ensure citizens get sufficient public support in their old age. For this purpose, the Senior Welfare Act is under a normative network with laws such as Act on Long-term Care Insurance for Senior Citizens and Basic Old Age Pension Act. Current laws on welfare for the aged including Senior Welfare Act are not sufficiently responsive to the aged society of the 21st century. Income security combined with decent social participation, health and medical care closely connected with long-term care system, efficient expense sharing between government and local government, enhancement of effectiveness of welfare measures can be considered as means to improve current welfare system so that the elderly can enjoy their old age with dignity and respect.

• Informatization Policy
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• v.29 no.1
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• pp.24-37
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• 2022

Amid rapid changes in the ICT environment attributed to the 4th Industrial Revolution, the development of information & communication technology, and COVID-19, the existing internet developed without considering security, mobility, manageability, QoS, etc. As a result, the structure of the internet has become complicated, and problems such as security, stability, and reliability vulnerabilities continue to occur. In addition, there is a demand for a new concept of the internet that can provide stability and reliability resulting from digital transformation-geared advanced technologies such as artificial intelligence and IoT. Therefore, in order to suggest a way of implementing the Korean future internet that can strengthen cybersecurity, this study suggests the direction and strategy for promoting the future internet that is suitable for the Korean cyber environment through analyzing important key factors in the implementation of the future internet and evaluating the trend and suitability of domestic & foreign research related to future internet. The importance of key factors in the implementation of the future internet proceeds in the order of security, integrity, availability, stability, and confidentiality. Currently, future internet projects are being studied in various ways around the world. Among numerous projects, Bright Internet most adequately satisfies the key elements of future internet implementation and was evaluated as the most suitable technology for Korea's cyber environment. Technical issues as well as strategic and legal issues must be considered in order to promote the Bright Internet as the frontrunner Korean future internet. As for technical issues, it is necessary to adopt SAVA IPv6-NID in selecting the Bright Internet as the standard of Korean future internet and integrated data management at the data center level, and then establish a cooperative system between different countries. As for strategic issues, a secure management system and establishment of institution are needed. Lastly, in the case of legal issues, the requirement of GDPR, which includes compliance with domestic laws such as Korea's revised Data 3 Act, must be fulfilled.

• Strategy21
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• s.32
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• pp.36-70
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• 2013

Waegu(倭寇)'s invasion in the Late Goryeo(高麗) Dynasty was huge damage for Goryeo's local society. And It was shock that Goryeo government's basic foundation of rules. Invasion background of waegu for Kyeong-in-yeon(庚寅年, 1350) was Kyushyu(九州)'s political divide because of Nihon(日本) government's confusion. Waegu was huge damage for Goryeo's Jo-wun(漕運, the shipping system of grain paid as a tax) system. So, government started military response, but it was turn out a failure and had great damage. When execution of military operations failed, Goryeo government sent diplomatic delegation to request the prevent of waegu, but the invasion continued. Since waegu invasion, Goryeo was got nowhere with defence of waegu. So, some people demanded for a new understanding of the ocean defence in the government. Lee-Saek(李穡), Woo-Hyeonbo(禹玄寶), Lee-Hee(李禧) and Jung-Ji(鄭地) were representatives of a new understanding of the ocean defence. Their demands were received attention when all operations had been failed. Therefore, Goryeo government began to reorganization of the naval forces and set up a special committee of gunpowder manufacturing named Hwa-tong-do-gam(火筒都監). This administrative reform was achieved substantial results since then. In 1380, the naval battle at Jin-po(鎭浦) was a big event that first gunpowder attack the waegu. Since Jin-po, Goryeo's naval forces gain confidence. In 1389, Dae-ma-do(對馬島) was attacked by Park-Wi(朴葳). It was meant that Goryeo's naval forces had huge offense power. Goryeo's defence system was focused on a northern race before 14th century waegu's invasion. So they were neglected their ocean defence. But after military operation of waegu's invasion was failure, they focused on the ocean defence. A new understanding of the ocean defence was foundation of that. It means to us to a new understanding of the ocean defence. Now, East Asia has maritime disputes. And we have high exposure to potential threats. So, we have a new understanding of importance of the ocean defence. And we fight for 21th century's ocean threats as foundation of sense of national security.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.17 no.4
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• pp.49-59
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• 2017

Smart sensing plays a key role in a variety of IoT applications, and its importance is growing more and more together with the development of artificial intelligence. Therefore the importance of smart sensors cannot be overemphasized. However, most studies related to smart sensors have been focusing on specific application purposes, for example, security, energy saving, monitoring, and there are not much effort on researches on how to efficiently configure various types of smart sensors to be needed in the future. In this paper, a component-based framework with hierarchical structure for efficient construction of smart sensor is proposed and its application to smart home is designed and implemented. The proposed method shows that various types of smart sensors to be appeared in the near future can be configured through the design and development of necessary components within the proposed software framework. In addition, since it has a layered architecture, the configuration of the smart sensor can be expanded by inserting the internal or external layers. In particular, it is possible to independently design the internal and external modules when designing an IoT application service through connection with the external device layer. A small-scale smart home system is designed and implemented using the proposed method, and a home cloud operating as an external layer, is further designed to accommodate and manage multiple smart homes. By developing and thus adding the components of each layer, it will be possible to efficiently extend the range of applications such as smart cars, smart buildings, smart factories an so on.

• Journal of the Korean housing association
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• v.20 no.4
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• pp.113-120
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• 2009

The demands of residents can be predicted by analyzing the housing viewpoint of residents. And also, the housing viewpoint can change according to various environmental changes, so it's important for us to understand the trend of change. Therefore, the housing viewpoints of university students who will be subjective residents of houses in future were analyzed by observing change due to trend of time. Target for this study is female university students in 20s. A portion of previously presented material (Korean Home Economics Association 37,1, 67-78) was used as data for 1998 and a questionnaire with 171 female university students was conducted on December 2008 for data for 2008. The following result was drawn from examination of change in the housing viewpoint due to trend of time by comparing the housing viewpoint of university students between 1998 and 2008. First, importance of was decreased and importance of was increased in functions of residence. Second, regardless of the time passage, the most students thought and as their opinions on housing. And also, the most students considered a living room as the most important space inside of a house regardless of the time passage and the level of considering a living room as the most important space was more increased. Third, the level of consideration got higher with time in the selection of houses. , , , , , and had higher level of consideration regardless of time passage. Items of which level of consideration increased with time are , , , , , and , and items of which level of consideration decreased are and . Fourth, it can be understood that the level of satisfaction in housing got higher with time. And it can be said that , , , and were not increased in the level of satisfaction in housing compared with 10 years ago. Fifth, regardless of time passage, the level of satisfaction in housing was lower than the level of consideration in the event of selection of houses. As , , and had lower levels of satisfaction in the event of selection of houses compared with the levels of consideration, they have higher possibility of dissatisfaction in housing.