• Journal of Korea Society of Digital Industry and Information Management
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• v.19 no.4
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• pp.117-126
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• 2023

Traditional markets, formed naturally, often feature aged buildings and facilities that are susceptible to fire. However, the lack of adequate fire detection systems in these markets can easily lead to large-scale fires upon ignition. Therefore, this study was conducted with the aim of detecting fires in traditional markets, utilizing thermal imaging cameras for data collection and the YOLOv8 model for object detection experiments. Data were collected in the night markets within traditional markets of xx city and by simulating fire scenarios. A comparative analysis of the Nano and XL models of YOLOv8 revealed that the XL model is more effective in detecting fires. The XL model not only demonstrated higher accuracy in correctly identifying flames but also tended to miss fewer fires compared to the Nano model. In the case of objects other than flames, the XL model showed superior performance over the Nano model. Taking all these factors into account, it is anticipated that with further data collection and improvement in model performance, a suitable fire detection system for traditional markets can be developed.

• Archives of design research
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• v.11 no.2
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• pp.203-213
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• 1998

The forthcoming twenty-first century is at the mercy of information and culture. A quality of humanlife is under the control of a cultural level. A nation's creative culture and a cultural level represent all things about the nation; and a national image, as a whole result of culture, is enormously influential. This new era of culturalism gives us a significant responsibility for getting ready for the late industrial society by practically harmonizing rationality of modem culture with conception of traditional culture. Industrializing culture and culturalizing industry will be the most important strategy for existence in these days of borderless international competitiveness. Cultural products which is containing a nation's own culture can not only enhance the national image, but also become high value-added industry. While general products are developed for the purpose of convenient and practical use, cultural products are created with the intention of informing international society about a nation or a region. In order to confront with a global market system and a change of cultural environment, it is necessary to create a proper design with cultural inheritance for modem likes and senses, to produce the design on a commercial scale, and to strengthen its competitiveness on international markets. In order that a commodity is born, distributed throughout markets, and delivered to a final consumer, it is essential to understand complicated process such as development, distribution and marketing of products and to systematize each part. Although we should not neglect any part, a political and systemical plan or a distributional and marketing idea will be beside the point in this article. This article presents importance of traditional patterns as a Korean cultural image, and it shows the process of designing and developing products in order for traditional patterns to be utilized for products effectively. I expect that concrete activation and systematization for those works can be carried out successively.

• Journal of Digital Convergence
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• v.19 no.11
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• pp.75-83
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• 2021

This study presented the analysis results and implications by identifying the structural relationship between the image of food tourism products, the long-term orientation of attachment, and the behavioral intention. The convenience sampling method of the non-probability sampling method was used, and the survey was conducted non-face-to-face due to COVID-19. This study was conducted for customers who live in Jeollabuk-do and Jeollanam-do and have experienced local traditional food. As for the survey method, the main researcher's acquaintances and related experts were consulted and utilized to select the survey subjects, and the survey was conducted by sending/returning them by mail or e-mail. Statistical processing was analyzed using SPSS 25.0 and AMOS 25.0 statistical packages. As a result of the verification, the relationship between the image and attachment of food tourism, the relationship between the long-term orientation in the attachment of traditional food, and the behavioral intention in the attachment of traditional food are significant. A significant positive (+) relationship was formed in the relationship of hypothesis setting according to the research purpose of the relationship.

• Journal of Korean Library and Information Science Society
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• v.47 no.4
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• pp.191-217
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• 2016

Traditional records information system has greatly improved accessibility to users by providing internet access to the digitized form of traditional records, access to which have previously been restricted for the purpose of preservation. This study investigated the accessibility and serviceability of Korean traditional records by examining current traditional record information systems in Korea. After compiling a list of traditional records information systems, which were grouped by operating agency, we analyzed them by coverage period, document type, and content format as well as examining search options and browse categories. We also categorized and examined the information systems by user type. The result showed that out of 105 traditional records information systems serving various content types and services, only a fraction(16.1%) provide a comprehensive information that includes bibliographic information, annotated description, content image, content text, and translated text, and less than a half(49.5%) provide a detailed search, all of which point to a less than optimal conditions for access to traditional records and suggest a strong need for improved traditional records information systems in Korea.

• The Journal of Information Systems
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• v.29 no.2
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• pp.111-130
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• 2020

Purpose SNS (Social Network Service) is one of new promising marketing tools which allow marketer to do two-way communication and social interaction. Three characteristics of SNS marketing including informativeness, interactivity, and playfulness are distinguished from traditional marketing. The purpose of this study is to examine the relationships between three characteristics of SNS marketing, brand image, and purchase intention. Design/methodology/approach The present study proposed a research model integrating SNS marketing characteristics, brand image, and purchase intention represented by structural equation modelling and four hypotheses. A total of 20 questionnaire items for five variables were developed and measured by using five point Likert scale. 199 valid data were collected and used to test four hypotheses using SmartPLS. Findings Three hypotheses that the characteristics of SNS marketing such as informativeness, interactivity, and playfulness have a positive influence on brand image were supported at the significance level of 0.05 and 0.001 respectively. The hypothesis regarding the relationship between brand image and purchase intention was also supported at the significance level of 0.001. Brand image plays a significant mediating role in the relationship between SNS marketing and purchase intention. In particular, the result of research that playfulness of SNS marketing affects brand image significantly suggests a new future research theme regarding spiritual marketing. Implications for academics and practitioners were suggested.

• Journal of Electrical Engineering and Technology
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• v.7 no.2
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• pp.264-272
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• 2012

In the field of medical diagnostics, interested parties have resorted increasingly to medical imaging. It is well established that the accuracy and completeness of diagnosis are initially connected with the image quality, but the quality of the image is itself dependent on a number of factors including primarily the processing that an image must undergo to enhance its quality. This paper introduces an algorithm for medical image compression based on the quincunx wavelets coupled with SPIHT coding algorithm, of which we applied the lattice structure to improve the wavelet transform shortcomings. In order to enhance the compression by our algorithm, we have compared the results obtained with those of other methods containing wavelet transforms. For this reason, we evaluated two parameters known for their calculation speed. The first parameter is the PSNR; the second is MSSIM (structural similarity) to measure the quality of compressed image. The results are very satisfactory regarding compression ratio, and the computation time and quality of the compressed image compared to those of traditional methods.

• Investigative Magnetic Resonance Imaging
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• v.23 no.2
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• pp.81-99
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• 2019

Recently, deep learning methods have shown great potential in various tasks that involve handling large amounts of digital data. In the field of MR imaging research, deep learning methods are also rapidly being applied in a wide range of areas to complement or replace traditional model-based methods. Deep learning methods have shown remarkable improvements in several MR image processing areas such as image reconstruction, image quality improvement, parameter mapping, image contrast conversion, and image segmentation. With the current rapid development of deep learning technologies, the importance of the role of deep learning in MR imaging research appears to be growing. In this article, we introduce the basic concepts of deep learning and review recent studies on various MR image processing applications.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.16 no.3
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• pp.894-907
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• 2022

The features extracted by convolutional neural networks are more descriptive of images than traditional features, and their convolutional layers are more suitable for retrieving images than are fully connected layers. The convolutional layer features will consume considerable time and memory if used directly to match an image. Therefore, this paper proposes a feature weighting and region integration method for convolutional layer features to form global feature vectors and subsequently use them for image matching. First, the 3D feature of the last convolutional layer is extracted, and the convolutional feature is subsequently weighted again to highlight the edge information and position information of the image. Next, we integrate several regional eigenvectors that are processed by sliding windows into a global eigenvector. Finally, the initial ranking of the retrieval is obtained by measuring the similarity of the query image and the test image using the cosine distance, and the final mean Average Precision (mAP) is obtained by using the extended query method for rearrangement. We conduct experiments using the Oxford5k and Paris6k datasets and their extended datasets, Paris106k and Oxford105k. These experimental results indicate that the global feature extracted by the new method can better describe an image.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.17 no.2
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• pp.471-485
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• 2023

As data sharing increases explosively, such information encoded in QR code is completely public as private messages are not securely protected. This paper proposes a new 'PROMISE' framework for hiding information based on the QR code projection matrix by using image segmentation without modifying the essential QR code characteristics. Projection matrix mapping, matrix scrambling, fusion image segmentation and steganography with SEL(secret embedding logic) are part of the PROMISE framework. The QR code could be mapped to determine the segmentation site of the fusion image as a binary information matrix. To further protect the site information, matrix scrambling could be adopted after the mapping phase. Image segmentation is then performed on the fusion image and the SEL module is applied to embed the secret message into the fusion image. Matrix transformation and SEL parameters should be uploaded to the server as the secret key for authorized users to decode the private message. And it was possible to further obtain the private message hidden by the framework we proposed. Experimental findings show that when compared to some traditional information hiding methods, better anti-detection performance, greater secret key space and lower complexity could be obtained in our work.

• The Journal of Information Systems
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• v.32 no.4
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• pp.149-162
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• 2023

Purpose In the textile industry, fabric defects significantly impact product quality and consumer satisfaction. This research seeks to enhance defect detection by developing a transformer-based deep learning image segmentation model for learning high-dimensional image features, overcoming the limitations of traditional image classification methods. Design/methodology/approach This study utilizes the ZJU-Leaper dataset to develop a model for detecting defects in fabrics. The ZJU-Leaper dataset includes defects such as presses, stains, warps, and scratches across various fabric patterns. The dataset was built using the defect labeling and image files from ZJU-Leaper, and experiments were conducted with deep learning image segmentation models including Deeplabv3, SegformerB0, SegformerB1, and Dinov2. Findings The experimental results of this study indicate that the SegformerB1 model achieved the highest performance with an mIOU of 83.61% and a Pixel F1 Score of 81.84%. The SegformerB1 model excelled in sensitivity for detecting fabric defect areas compared to other models. Detailed analysis of its inferences showed accurate predictions of diverse defects, such as stains and fine scratches, within intricated fabric designs.