• The Journal of the Korea institute of electronic communication sciences
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• v.17 no.5
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• pp.977-984
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• 2022

Recently, with the economic development of Southeast Asia, the use of information devices is widely spreading, and the demand for application services using intelligent character recognition is increasing. This paper discusses deep learning-based feature extraction and recognition of Myanmar, one of the Southeast Asian countries. Myanmar alphabet (33 letters) and Myanmar numerals (10 numbers) are used for feature extraction. In this paper, the number of nine features are extracted and more than three new features are proposed. Extracted features of each characters and numbers are expressed with successful results. In the recognition part, convolutional neural networks are used to assess its execution on character distinction. Its algorithm is implemented on captured image data-sets and its implementation is evaluated. The precision of models on the input data set is 96 % and uses a real-time input image.

• Journal of the Society of Disaster Information
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• v.17 no.4
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• pp.802-816
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• 2021

Purpose: In this paper, we propose a direction of future research and development to be carried out in the passive tracking field by deriving a white space with enhanced search formula of patent analysis. Method: In this paper, we derive a white space by identifying the direction and the flow of technology change and by matrixing the object and solution through extensive patent search with enhanced search formula and analysis in the field of passive tracking technology. Result: By the proposed scheme, 'multi-target positioning and tracking' and '3D positioning technology' using artificial intelligence, adaptive/hybrid positioning technology, and radar/antenna were derived as white space technologies and confirmed with absence of any services or products. Conclusion: The derived white space technologies from this paper are the areas where patent applications are not active and there are not many prior patents, thus it is necessary to secure the rights through more active R&D and patent application activities.

• Journal of Information Technology Applications and Management
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• v.28 no.6
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• pp.145-161
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• 2021

Recently, as personal information utilization devices such as IoT, artificial intelligence, and wearable devices that focus on the individual have spread, privacy violations are also increasing. However, the privacy paradox of providing personal information to enjoy services while worrying is getting stronger. However, there are still preliminary studies on this. In this study, an intelligent home camera based on IoT technology was selected as a research object, and whether privacy paradox exists in the IoT environment, including smart home camera, was studied. To this end, the effect of perceived usefulness, a benefit factor of smart home camera use, and privacy concern, a risk factor, on intention to use was verified. In addition, it was investigated whether the relationship between privacy concerns and intention to use differs according to the presence or absence of use experience. In order to verify the research model, a survey was conducted with people with and without experience in using smart home cameras, and a total of 298 data samples were used for statistical analysis. As a result of the analysis, it was found that both perceived usefulness and privacy concerns had a positive effect on the intention to use, proving that privacy paradox exists in the IoT-based smart home camera environment. In addition, by analyzing the fact that privacy concerns have different effects on usage intentions depending on the user experience, it was verified that those with experience have a strong privacy paradox and those without experience have a weak privacy paradox. This study is meaningful because it seeks strategic implications to improve service and business performance by understanding the relationship between privacy attitudes and behaviors of IoT service providers, including smart home cameras.

• Journal of Internet Computing and Services
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• v.24 no.4
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• pp.85-92
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• 2023

Deep learning applications are increasingly being leveraged for disease detection tasks in medical imaging modalities such as X-ray, Computed Tomography (CT), and Magnetic Resonance Imaging (MRI). Most data-centric deep learning challenges necessitate the use of supervised learning methodologies to attain high accuracy and to facilitate performance evaluation through comparison with the ground truth. Supervised learning mandates a substantial amount of image and label sets, however, procuring an adequate volume of medical imaging data for training is a formidable task. Various data augmentation strategies can mitigate the underfitting issue inherent in supervised learning-based models that are trained on limited medical image and label sets. This research investigates the enhancement of a deep learning-based rib fracture segmentation model and the efficacy of data augmentation techniques such as left-right flipping, rotation, and scaling. Augmented dataset with L/R flipping and rotations(30°, 60°) increased model performance, however, dataset with rotation(90°) and ⨯0.5 rescaling decreased model performance. This indicates the usage of appropriate data augmentation methods depending on datasets and tasks.

• Journal of Internet Computing and Services
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• v.24 no.4
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• pp.1-13
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• 2023

As federated learning brings a large paradigm to modern artificial intelligence research, efforts are being made to incorporate federated learning into research in various fields. However, researchers who apply federated learning face the problem of choosing a federated learning framework and benchmark tool suitable for their situation and purpose. This study aims to present guidelines for selection of federated learning frameworks and benchmark tools considering the circumstances of researchers who apply federated learning in practice. In particular, there are three main contributions in this study. First, it generalizes the situation of the researcher applying federated learning by combining it with the goal of federated learning and proposes guidelines for selecting a federated learning framework suitable for each situation. Second, it shows the suitability of selection by comparing the characteristics and performance of each federated learning framework to the researcher. Finally, the limitations of the existing federated learning framework and a plan for real-world federated learning operation are proposed.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.23 no.4
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• pp.121-126
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• 2023

As service utilization for IT technologies such as artificial intelligence, big data, and IOT has recently increased, cloud computing has been introduced to efficiently manage vast amounts of data and IT infrastructure resources that process them to provide stable and reliable information services while streamlining infrastructure costs. Efforts for this are ongoing. This thesis compares and analyzes the operation results before and after cloud adoption in terms of system failures for 426 systems at 360 branches nationwide in cloud systems of companies operating a total of 1,750 cloud systems. As a result of the analysis, the number of failures and failure types , service downtime, etc., the introduction of the cloud yielded significant results in securing service continuity. Through this result, it is expected to provide meaningful implications to companies expecting to secure service continuity by adopting the cloud.

• Journal of the Korea Society of Computer and Information
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• v.28 no.9
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• pp.93-104
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• 2023

In modern society, the service method is tended to prefer the non-face-to-face method rather than the face-to-face method. However, services that recommend products such as shoes will inevitably be face-to-face method. In this paper, for the purpose of non-face-to-face service, a system that a foot size is automatically measured and some shoes are recommended based on the measurement result is proposed. To analyze the performance of the proposed method, size measurement error rate and recommendation performance were analyzed. In the recommendation performance experiments, a total of 10 methods for similarity calculation were used and the recommendation method with the best performance among them was applied to the system. From the experiments, the error rate the foot size was small and the recommendation performance was possible to derive significant results. The proposed method is at the laboratory level and needs to be expanded and applied to the real environment. Also, the recommendation method considering design could be needed in the future work.

• International Journal of Computer Science & Network Security
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• v.23 no.3
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• pp.110-122
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• 2023

Over the last few decades, various innovative technologies have emerged that have significantly contributed to making life easier for humans. Various information and communication technologies (ITCs) have emerged as a result of the global technological revolution, including big data, IoT, 4G and 5G networks, cloud computing, mobile computing, and artificial intelligence. These technologies have been adopted in urban planning and development, which gave rise to the concept of smart cities in the 1990s. A smart city is a type of city that uses ITCs to exchange and share information to enhance the quality of services for its citizens. With the global population increasing at unprecedented levels, cities are overwhelmed with a myriad of challenges, such as the energy crisis, environmental pollution, sanitation and sewage challenges, and water quality issues, and therefore, have become a convergence point of economic, social, and environmental risks. The concept of a smart city is a multidisciplinary, unified approach that has been adopted by governments and municipalities worldwide to overcome these challenges. Though challenging, this transformation is essential for cities with differing technological and social features, which all have the potential to determine the success or failure of the digital transformation of cities into smart cities. In recent years, researchers, businesses, and the government have all turned their attention to the emerging field of smart cities. Accordingly, this paper aims to represent a thorough understanding of the movement toward smart cities. The key themes identified are smart city definitions and concepts, smart city dimensions, and smart city architecture of different layers. Furthermore, this article discusses the challenges and some examples of smart cities.

• Journal of Korean Public Health Nursing
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• v.37 no.1
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• pp.5-24
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• 2023

Purpose: The objective of this review was to identify the research trends in Information and Communication Technology (ICT)-based health-related intervention studies for children and adolescents published in South Korea over the past 10 years. Methods: A scoping review was performed in accordance with the Preferred Reporting Items for Systematic Reviews and Meta Analyses (PRISMA) and the system classification framework for digital health intervention 1.0 of the World Health Organization (WHO) was applied to analyze how technology was being used to support the needs of the health system. Results: A total of 18 studies were included in the final analysis. The participants were mainly children with a variety of diseases. No studies had used innovative technology platforms such as artificial intelligence (AI), the Internet of Things (IoT), and robotics. In addition, the scope of application of the WHO classification criteria was quite limited. Finally, no intervention study considered technical operational indicators, such as the number of website visits and streaming as outcome measurements. Conclusions: Researchers should introduce advanced technology-based strategies to provide customized and professional healthcare services to children and adolescents in South Korea and continue efforts to integrate innovative ICT for various research purposes, subjects, and environments.

• Smart Media Journal
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• v.11 no.2
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• pp.63-69
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• 2022

As the use of various IoT devices increases, the importance of IoT platforms is also rising. Recently, artificial intelligence technology is being combined with IoT devices, and research applying a neuromorphic architecture to IoT devices with low power is also increasing. In this paper, an application scenario is proposed based on NA-IDE (Neuromorphic Architecture-based autonomous IoT application integrated development environment) with IoT devices and FPGA devices in a GUI format. The proposed scenario connects a camera module to an IoT device, collects MNIST dataset images online, recognizes the collected images through a neuromorphic board, and displays the recognition results through a device module connected to other IoT devices. If the neuromorphic architecture is applied to many IoT devices and used for various application services, the autonomous IoT application integrated development environment based on the neuromorphic architecture is expected to emerge as a core technology leading the 4th industrial revolution.