• Journal of the Korea Society of Computer and Information
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• v.27 no.8
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• pp.233-240
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• 2022

In this paper, we propose a marketing strategy for traditional markets that lays the foundation for regional economic development by developing traditional markets as regionally specialized tourism resources. This study conducted a survey of local residents and tourists, who are market users, and conducted a factor analysis to establish a market brand strategy using SPSS 25 and a reliability analysis to verify internal consistency. In addition, correlation analysis was performed to verify the significance to confirm the relevance. The analysis results of Anyang Central Market brand tourism products for traditional market marketing strategies are as follows. First, it is necessary to establish a brand identity that activates brand elements and brand criteria and brand positioning. Second, it is required to improve brand awareness, which can elicit brand awareness and brand information and brand memory. Third, it is necessary to improve the brand image that can increase brand association and brand loyalty. Fourth, it is necessary to make efforts to improve brand equity, which can improve brand value, brand concern, and brand life. By developing and proposing marketing policies for traditional markets by utilizing market brand strategies, it can be expected to revitalize traditional markets and local economies as specialized local tourism resources.

• Korean Journal of Mineralogy and Petrology
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• v.34 no.4
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• pp.209-218
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• 2021

Studies of pore structure in shale gas reservoirs are essential to increase recovery rates, which is in the spotlight concerning unconventional resources. In this study, the distribution of pores in shale gas reservoir sample were observed using Scanning Electron Microscope Particle Analysis (SELPA), which is appropriate to analyze the distribution of particle or shape for sample in large area. A sample from the A-068 borehole drilled in the Liard Basin was analyzed; calcite is the main mineral. The pore size ranges from tens of nanometers to hundreds of micrometers and the contribution of each pore size to overall sample porosity was determined using SELPA. The distribution of pores was determined by observing the surface in the same area at magnifications of ×1000, ×3000 and ×5000. Pores less than 100 nm were observed at high magnifications and confirm that small-scale pore distribution can be analyzed and identified rapidly using SELPA. The method introduced in this study will be useful to understand pore structures in unconventional reservoirs.

• The Journal of the Convergence on Culture Technology
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• v.8 no.6
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• pp.979-986
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• 2022

In this study, the virtual exhibition using 3D architectural space was analyzed in terms of the viewer's experience. For this purpose, the analysis items of the virtual architectural space include whether the actual architectural space is reproduced, the introduction of surreal elements, the degree of freedom of movement and circulation, the level of photorealism of spatial expression, the level of reproduction of the exhibits and information provision method, and the interaction with other participants. Six virtual exhibition projects designed by a well-known architect were selected and analyzed. Three directions were found through the analysis. First, even when designing a virtual exhibition space with a high degree of freedom, there is a tendency to present a familiar architectural environment. Second, the current method of creating a virtual architectural space is that the method using a 360-degree rendering image and the method using a game engine coexist with pros and cons. Third, the interaction between participants in the virtual exhibition is implemented only by using a game engine. It is expected that the virtual space production environment using the game engine to be developed will become more advantageous in the future.

• KIPS Transactions on Software and Data Engineering
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• v.12 no.2
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• pp.77-82
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• 2023

The Ministry of Agriculture, Food and Rural Affairs established the FarmMap, an digital map of agricultural land. In this study, using deep learning, we suggest the application of farm map reading to farmland such as paddy fields, fields, ginseng, fruit trees, facilities, and uncultivated land. The farm map is used as spatial information for planting status and drone operation by digitizing agricultural land in the real world using aerial and satellite images. A reading manual has been prepared and updated every year by demarcating the boundaries of agricultural land and reading the attributes. Human reading of agricultural land differs depending on reading ability and experience, and reading errors are difficult to verify in reality because of budget limitations. The farmmap has location information and class information of the corresponding object in the image of 5 types of farmland properties, so the suitable AI technique was tested with ResNet50, an instance segmentation model. The results of attribute reading of agricultural land using deep learning and attribute reading by humans were compared. If technology is developed by focusing on attribute reading that shows different results in the future, it is expected that it will play a big role in reducing attribute errors and improving the accuracy of digital map of agricultural land.

• Journal of IKEEE
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• v.27 no.3
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• pp.345-349
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• 2023

In this paper, we propose a study on the development of deep learning structure for defective pixel detection of next-generation smart LED display board using imaging device. In this research, a technique utilizing imaging devices and deep learning is introduced to automatically detect defects in outdoor LED billboards. Through this approach, the effective management of LED billboards and the resolution of various errors and issues are aimed. The research process consists of three stages. Firstly, the planarized image data of the billboard is processed through calibration to completely remove the background and undergo necessary preprocessing to generate a training dataset. Secondly, the generated dataset is employed to train an object recognition network. This network is composed of a Backbone and a Head. The Backbone employs CSP-Darknet to extract feature maps, while the Head utilizes extracted feature maps as the basis for object detection. Throughout this process, the network is adjusted to align the Confidence score and Intersection over Union (IoU) error, sustaining continuous learning. In the third stage, the created model is employed to automatically detect defective pixels on actual outdoor LED billboards. The proposed method, applied in this paper, yielded results from accredited measurement experiments that achieved 100% detection of defective pixels on real LED billboards. This confirms the improved efficiency in managing and maintaining LED billboards. Such research findings are anticipated to bring about a revolutionary advancement in the management of LED billboards.

• Journal of the Korean Institute of Landscape Architecture
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• v.50 no.6
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• pp.15-29
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• 2022

The Byungsan Neo-Confucian Academy, a 17th-century World Heritage Site in Korea, is being praised as a manifestation of naturalness or non-artificiality of the traditional Korean borrowed scenery technique (借景, chagyeong). This study, however, aims to reinterpret the chagyeong of the Byungsan Academy (hereafter the Academy) as a device of illusion evoking an idealized vision of nature. In the process of interpretation, 'picture and frame'-a widely accepted expression that represents the chagyeong of the Academy-will be foregrounded as the pivotal concept mediating the change of perspectives from naturalistic to ideological. This study consists of the following three parts. First, it shows that 'picture and frame' represent a modern way of seeing the Academy as an architectural heritage in harmony with nature; it denotes pristine nature and the empty architectural frame that safely circumscribes the innate beauty of the natural landscape. Second, departing from the naturalistic perspective, this study argues that the architectural framework of the Academy composes scenography enticing the viewer to imagine the idealized, Confucian image of nature that compares to the landscape imagery found in the landscape poetry and paintings that were produced and appreciated by the 17th-century Confucian literati. Lastly, based on the above interpretation, this study stresses that the 'picture' one encountered at the Academy in the 17th century was not the framed scene of a natural landscape but the illusion it caused; the architectural 'frame' worked not as a symbol of naturalness but as an institutional apparatus of vision manipulating the way one sees-and therefore imagines-the landscape.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.40 no.1
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• pp.41-49
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• 2022

Recently interests on the application of thermal cameras have increased with the advance of image analysis technology. Aside from a simple image acquisition, applications such as digital twin and thermal image management systems have gained popularity. To this end, we studied the effect of emissivity on the DN (Digital Number) value in the process of derivation of a relational expression for converting DN to an actual surface temperature. The DN value is a number representing the spectral band value of the thermal image, and is an important element constituting the thermal image data. However, the DN value is not a temperature value indicating the actual surface temperature, but a brightness value indicating high and low heat as brightness, and has a non-linear relationship with the actual surface temperature. The reliable relationship between DN and the actual surface temperature is critical for a thermal image processing. We tested the relationship between the actual surface temperature and the DN value of the thermal image, and then the radiation adjustment was performed to better estimate actual surface temperatures. As a result, the relation graph between the actual surface temperature and the DN value similarly show linear pattern with the relation graph between the radiation-controlled non-contact thermometer and the DN value. And the non-contact temperature after adjusting the emissivity was closer to the actual surface temperature than before adjusting the emissivity.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.42 no.2
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• pp.249-256
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• 2022

Various studies are being actively conducted to show that the real-time visualization technology that combines BIM (Building Information Modeling) and AR (Augmented Reality) helps to increase construction management decision-making and processing efficiency. However, when large-capacity BIM data is projected into AR, there are various limitations such as data transmission and connection problems and the image cut-off issue. To improve the high efficiency of visualizing, a mesh optimization algorithm based on the k-nearest neighbors (KNN) classification framework to reconstruct BIM data is proposed in place of existing mesh optimization methods that are complicated and cannot adequately handle meshes with numerous boundaries of the 3D models. In the proposed algorithm, our target BIM model is optimized with the Unity C# code based on triangle centroid concepts and classified using the KNN. As a result, the algorithm can check the number of mesh vertices and triangles before and after optimization of the entire model and each structure. In addition, it is able to optimize the mesh vertices of the original model by approximately 56 % and the triangles by about 42 %. Moreover, compared to the original model, the optimized model shows no visual differences in the model elements and information, meaning that high-performance visualization can be expected when using AR devices.

• Korea Science and Art Forum
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• v.24
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• pp.321-332
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• 2016

As functions of public library has become diversified, proper environment color plan enhancing a supporting environment of user based on a function of public library should be achieved by utilizing space chromatics which is a psychological environmental factor. Therefore, public library's color environment of each space functions should be understood and the foundation of color plan enhancing supporting environment of user should also be established under the premise that public library color environment which supports integrated functions to every local residents by meeting functional roles of library. As functions of public library expands, this study has its purpose to analyze color environment characteristics by mainly focusing on library of Busan region to study color environment supporting function of each space. Through a literature research, function and role of color, environment color have considered, and through a preceding research analysis on public library's present condition analysis and tendency of library color preference, theoretical background on library color environment has deducted. By researching present condition of environment color application at 9 public libraries located at Busan, the environment color characteristics of library has deducted through an image adjective analysis using color system, coloration analysis, IRI(Image Research Institute) color image scale. This study can be provided as a reference data for environment color plan based on spatial function to enhance supporting environment of public library user, and it is expected to utilize in the library facility plan which has been diversified.

• Korean Chemical Engineering Research
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• v.61 no.3
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• pp.388-393
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• 2023

The analysis of engineering data using neural network based on supervised learning has been utilized in various engineering fields such as optimization of chemical engineering process, concentration prediction of particulate matter pollution, prediction of thermodynamic phase equilibria, and prediction of physical properties for transport phenomena system. The supervised learning requires training data, and the performance of the supervised learning is affected by the composition and the configurations of the given training data. Among the frequently observed engineering data, the data is given in log-scale such as length of DNA, concentration of analytes, etc. In this study, for widely distributed log-scaled training data of virtual 100×100 images, available loss functions were quantitatively evaluated in terms of (i) confusion matrix, (ii) maximum relative error and (iii) mean relative error. As a result, the loss functions of mean-absolute-percentage-error and mean-squared-logarithmic-error were the optimal functions for the log-scaled training data. Furthermore, we figured out that uniformly selected training data lead to the best prediction performance. The optimal loss functions and method for how to compose training data studied in this work would be applied to engineering problems such as evaluating DNA length, analyzing biomolecules, predicting concentration of colloidal suspension.