Geophysical exploration methods are very useful for generating high-resolution images of underground structures, and such methods can be applied to investigation of buried cultural properties and for determining their exact locations. In this study, image feature extraction and image segmentation methods were applied to automatically distinguish the structures of buried relics from the high-resolution ground-penetrating radar (GPR) images obtained at the center of Silla Kingdom, Gyeongju, South Korea. The major purpose for image feature extraction analyses is identifying the circular features from building remains and the linear features from ancient roads and fences. Feature extraction is implemented by applying the Canny edge detection and Hough transform algorithms. We applied the Hough transforms to the edge image resulted from the Canny algorithm in order to determine the locations the target features. However, the Hough transform requires different parameter settings for each survey sector. As for image segmentation, we applied the connected element labeling algorithm and object-based image analysis using Orfeo Toolbox (OTB) in QGIS. The connected components labeled image shows the signals associated with the target buried relics are effectively connected and labeled. However, we often find multiple labels are assigned to a single structure on the given GPR data. Object-based image analysis was conducted by using a Large-Scale Mean-Shift (LSMS) image segmentation. In this analysis, a vector layer containing pixel values for each segmented polygon was estimated first and then used to build a train-validation dataset by assigning the polygons to one class associated with the buried relics and another class for the background field. With the Random Forest Classifier, we find that the polygons on the LSMS image segmentation layer can be successfully classified into the polygons of the buried relics and those of the background. Thus, we propose that these automatic classification methods applied to the GPR images of buried cultural heritage in this study can be useful to obtain consistent analyses results for planning excavation processes.
This paper aims to investigate 4D printing materials for soft robots. 4D printing is a targeted evolution of the 3D printed structure in shape, property, and functionality. It is capable of self-assembly, multi-functionality, and self-repair. In addition, it is time-dependent, printer-independent, and predictable. The shape-shifting behaviors considered in 4D printing include folding, bending, twisting, linear or nonlinear expansion/contraction, surface curling, and generating surface topographical features. The shapes can shift from 1D to 1D, 1D to 2D, 2D to 2D, 1D to 3D, 2D to 3D, and 3D to 3D. In the 4D printing auxetic structure, the kinetiX is a cellular-based material design composed of rigid plates and elastic hinges. In pneumatic auxetics based on the kirigami structure, an inverse optimization method for designing and fabricating morphs three-dimensional shapes out of patterns laid out flat. When 4D printing material is molded into a deformable 3D structure, it can be applied to the exoskeleton material of soft robots such as upper and lower limbs, fingers, hands, toes, and feet. Research on 4D printing materials for soft robots is essential in developing smart clothing for healthcare in the textile and fashion industry.
This study is to structurally examine the regional income disparity in Korea. It measures the regional income inducement by household consumption expenditure per unit income, and the regional interdependency of income using 2005 and 2015 Regional Input-Output Tables of 16 provincial regions of Korea. The results are as follows. Firstly, the income inducement by consumption expenditure per unit income decreased overall, mainly due to the decrease in the income inducement of other regions than due to that of their region. Secondly, in many regions, the inter-relational income dependency per unit income decreased also, this too, mainly due to the decrease in the income transfer to other region. And, the income inducement effects of consumption expenditure per unit income of Seoul and Gyeonggi, which occupy a large portion of the Korean economy, were lower than that of other regions, but took the largest portion of income inducements generated by other regions as well as by themselves and absorbed the income transfers from other regions the most. The higher income inducement and income absorption in Seoul and Gyeonggi by consumption expenditure of other regions were mainly because of the high share in service of their consumption structure, the progress in tertiarization of their industrial structure, and the high wage portion. These results also mean that viewed from the regional interdependency of income, the income of Seoul and that of Gyeonggi are highly dependent on the income of other regions. Especially, Gyeonggi which leads the overseas exports of high-tech based manufactured products, has other external factors that contribute to their high income inducement, whereas, Seoul which shows high income absorption using its inter-relations with other domestic regions based on the services, has an income-generating structure that is sensitive to other regions' economic situation. Amid overall declines in regional income inducements and in income transfers, and continuing concentrations into Seoul and Gyeonggi regions, to alleviate the regional disparity, the regional industry policies should, rather than benchmarking the policies of the two concentrated regions, enhance their own inter-regional relationships by strengthening the comparative advantage of their regionally specialized industry.
In this study, conductive polymers and the enzyme tyrosinase (Tyr) were deposited on the surface of a screen printed carbon electrode (SPCE), which can be fabricated as a disposable sensor chip, and applied to the detection of bisphenol F (BPF), an endocrine disruptor with proven links to male diseases and thyroid disorders, using electrochemical methods. On the surface of the SPCE working electrode, which was negatively charged by oxygen plasma treatment, a positively charged conductive polymer, poly(diallyldimethyl ammonium chloride) (PDDA), a negatively charged polymer compound, poly(sodium 4-styrenesulfonate) (PSS), and another layer of PDDA were layered by electrostatic attraction in the order of PDDA, PSS, and finally PDDA. Then, a layer of Tyr, which was negatively charged due to pH adjustment to 7.0, was added to create a PDDA-PSS-PDDA-Tyr sensor for BPF. When the electrode sensor is exposed to a BPF solution, which is the substrate and target analyte, 4,4'-methylenebis(cyclohexa-3,5-diene-1,2-dione) is generated by an oxidation reaction with the Tyr enzyme on the electrode surface. The reduction process of the product at 0.1 V (vs. Ag/AgCl) generating 4,4'-methylenebis(benzene-1,2-diol) was measured using cyclic and differential pulse voltammetries, resulting in a change in the peak current with respect to the concentration of BPF. In addition, we compared the detection performance of BPF using an ionic liquid electrolyte as an alternative to phosphate-buffered saline, which has been used in many previous sensing studies. Furthermore, the selectivity of bisphenol S, which acts as an interfering substance with a similar structure to BPF, was investigated. Finally, we demonstrated the practical applicability of the sensor by applying it to analyze the concentration of BPF in real samples prepared in the laboratory.
Due to the rapid development of ICT, corporate business models quickly changed and because of the radical growth of IT technology, sequential or gradual survival has become difficult. Internet-based new businesses such as IT service companies are seeking for new convergence business models that have not existed before to create business models that are more competitive, but the economic efficiency of business models that were successful in the past is wearing off. Yet, as reaching the critical point where the platform value becomes extremely high for platforms via the Internet is happening at a much higher speed than before, platform-ization has become a very important condition for rapid business expansion for all kinds of businesses. This study analyzes the necessity of establishing platform business models in IT service planning and identifies their characteristics through case analyses of platform business models. The results derived features First, there is a need to ensure sufficient buyers and sellers, and second, platform business model should provide customers with distinctive value of the only platforms are generating. third, the common interests between platform-driven company and a partner, participants Should be existing. Fourthly, by expanding base of participants and upgrades, expansion of adjacent areas we must have a continuous scalability and evolution must be sustainable. While it is expected that the identified characteristics will cause tremendous impacts to the establishment of platform business models and to the graphing of service planning, we also look forward to this study serving as the starting point for the establishment of theories of profit models for platform businesses, which were not mentioned in the study, so that planners responsible for platform-based IT service planning will spend less time and draw bigger schemes in building planning drafts.
The amount of dust generated during the dissolution of scrap in an electric arc furnace is approximately 1.5% of the scrap metal input, and it is primarily collected in a bag filter. Electric arc furnace dust primarily consists of zinc and ion. The processing of zinc starts with its conversion into pellet form by the addition of a carbon-based reducing agent(coke, anthracite) and limestone (C/S control). These pellets then undergo reduction, volatilization, and re-oxidation in rotary kiln or RHF reactor to recover crude zinc oxide (60%w/w). Next, iron is discharged from the electric arc furnace dust as a solid called Fe clinker (secondary by-product of the Fe-base). Several methods are then used to treat the Fe clinker, which vary depending on the country, including landfilling and recycling (e.g., subbase course material, aggregate for concrete, Fe-source for cement manufacturing). However, landfilling has several drawbacks, including environmental pollution due to leaching, high landfill costs, and wastage of iron resources. To improve Fe recovery in the clinker, we pulverized it into optimal -sized particles and employed specific gravity and magnetic force selection methods to isolate this metal. A carbon-based reducing agent and a binding material were added to the separated coarse powder (>10㎛) to prepare briquette clinker. A small amount (1-3%w/w) of the briquette clinker was charged with the scrap in an electric arc furnace to evaluate its feasibility as an additives (carbonaceous material, heat-generating material, and Fe source).
Suho Bak;Seon Woong Jang;Heung-Min Kim;Tak-Young Kim;Geon Hui Ye
Korean Journal of Remote Sensing
/
v.39
no.2
/
pp.193-205
/
2023
A large amount of floating debris from land-based sources during heavy rainfall has negative social, economic, and environmental impacts, but there is a lack of monitoring systems for floating debris accumulation areas and amounts. With the recent development of artificial intelligence technology, there is a need to quickly and efficiently study large areas of water systems using drone imagery and deep learning-based object detection models. In this study, we acquired various images as well as drone images and trained with You Only Look Once (YOLO)v5s and the recently developed YOLO7 and YOLOv8s to compare the performance of each model to propose an efficient detection technique for land-based floating debris. The qualitative performance evaluation of each model showed that all three models are good at detecting floating debris under normal circumstances, but the YOLOv8s model missed or duplicated objects when the image was overexposed or the water surface was highly reflective of sunlight. The quantitative performance evaluation showed that YOLOv7 had the best performance with a mean Average Precision (intersection over union, IoU 0.5) of 0.940, which was better than YOLOv5s (0.922) and YOLOv8s (0.922). As a result of generating distortion in the color and high-frequency components to compare the performance of models according to data quality, the performance degradation of the YOLOv8s model was the most obvious, and the YOLOv7 model showed the lowest performance degradation. This study confirms that the YOLOv7 model is more robust than the YOLOv5s and YOLOv8s models in detecting land-based floating debris. The deep learning-based floating debris detection technique proposed in this study can identify the spatial distribution of floating debris by category, which can contribute to the planning of future cleanup work.
Won-Woo Seo;Hongki Kang;Wansang Yoon;Pyung-Chae Lim;Sooahm Rhee;Taejung Kim
Korean Journal of Remote Sensing
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v.39
no.6_1
/
pp.1211-1224
/
2023
Clouds cause many difficult problems in observing land surface phenomena using optical satellites, such as national land observation, disaster response, and change detection. In addition, the presence of clouds affects not only the image processing stage but also the final data quality, so it is necessary to identify and remove them. Therefore, in this study, we developed a new cloud detection technique that automatically performs a series of processes to search and extract the pixels closest to the spectral pattern of clouds in satellite images, select the optimal threshold, and produce a cloud mask based on the threshold. The cloud detection technique largely consists of three steps. In the first step, the process of converting the Digital Number (DN) unit image into top-of-atmosphere reflectance units was performed. In the second step, preprocessing such as Hue-Value-Saturation (HSV) transformation, triangle thresholding, and maximum likelihood classification was applied using the top of the atmosphere reflectance image, and the threshold for generating the initial cloud mask was determined for each image. In the third post-processing step, the noise included in the initial cloud mask created was removed and the cloud boundaries and interior were improved. As experimental data for cloud detection, CAS500-1 L2G images acquired in the Korean Peninsula from April to November, which show the diversity of spatial and seasonal distribution of clouds, were used. To verify the performance of the proposed method, the results generated by a simple thresholding method were compared. As a result of the experiment, compared to the existing method, the proposed method was able to detect clouds more accurately by considering the radiometric characteristics of each image through the preprocessing process. In addition, the results showed that the influence of bright objects (panel roofs, concrete roads, sand, etc.) other than cloud objects was minimized. The proposed method showed more than 30% improved results(F1-score) compared to the existing method but showed limitations in certain images containing snow.
The source of value-added creation in modern times has been transformed from material to man's value-added generating power, and ownership of the means of production has been converted from a particular landlord, capitalist to a person with value-added capacity, and a system of capital participation is needed beyond the profit-sharing system or performance incentive system in which workers of an enterprise participate in simple profits if they significantly increase the added value of the company. It is also necessary to introduce our private stock system as a means of addressing the problem of capital bias and for the stable development of capitalism. The purpose of Employee Stock Ownership Plans is to improve the economic and social status of workers and promote labor-management cooperation by allowing workers to acquire and hold shares of the stock company in which the employee ownership association is established through the employee ownership association, but the reality is that our stock ownership system has failed to achieve its purpose due to insufficient protection against the employee. In terms of welfare, the acquisition of our company shares should include active government support for the welfare of workers' ownership on a social welfare level rather than on the logic of the capital market, and in terms of investment, it would not be appropriate to apply the regulation for investor protection to see workers' acquisition of our company shares as 'investment' in the view of workers' willingness to own shares on the stock market. Therefore, as a way to support and deregulate employee's stock acquisition, 1. Expanding direct support, such as tax support, 2. As employee's stock ownership association is being discussed as a division's nature, it is less effective in terms of various management, not investment, and 3. Those who own stocks with 1% of the company's shares and 300 million won in face value will be classified as major shareholders. As a way to reduce the risk of management of our company owners and cooperative funds, As a measure to reduce the risk of management of our company owners and cooperative funds, only our employee shareholders' association shall manage the fund in a long-term deposit, and even though our employee's stock is managed by the association or company after the end of the deposit period, the management of each employee shall be allowed and In terms of improving the utilization of our company's stock and fund, 1. Employee's stockholders are prohibited from lending during the deposit period, but it is necessary to improve profitability by allowing them to borrow under strict restrictions, 2. It is necessary to make the use of the employee's welfare funds available for the preservation of losses, and to stipulate the redemption obligations of unlisted companies in order to improve the redemption system of our company.
Due to long-term social distancing due to the spread of COVID-19, business trends of restaurant companies are being implemented in accordance with the changed environment such as packaging and subscription. However, even in this environment, upscale restaurants are generating high profits by trying to differentiate themselves from existing restaurants by providing high-quality services with the best facilities. Therefore, this study describes how customers' experience of upscale restaurant service influences behavioral loyalty. That is, the purpose of this study is to determine the effect of service experience on cognitive satisfaction and emotional attachment, and to examine the causal role of cognitive satisfaction and emotional attachment by confirming the relationship between these constructs and relationship commitment and behavioral loyalty. To verify this, data were collected through face-to-face interviews with 300 consumers who recently used a upscale restaurant. Of the collected data, 275 copies(91.6%) were used for the final analysis, and inaccurate or erroneous data among 25 response sheets were excluded. In this study, the validity and reliability of the data were checked and the research hypothesis was verified by using SPSS 21.0 and AMOS 20 statistical package. Frequency analysis was performed to confirm the demographic characteristics of the respondent. Structural equation model analysis(SEM) was used to confirm the fit of the research model and to verify the research hypothesis. As a result of the research hypothesis analysis, it was found that service experience had a positive effect on cognitive satisfaction, and cognitive satisfaction had a positive effect on emotional attachment, relationship commitment, and behavioral loyalty. Also, it was found that emotional attachment had a positive effect on relationship commitment and behavioral loyalty, and relationship commitment had a positive effect on behavioral loyalty. However, service experience did not affect emotional attachment. With this study, marketers and managers of upscale restaurants such as hotel restaurants need to accurately select their target audience, understand their service needs, and then present the appropriate service to them. In addition, they should not only induce cognitive satisfaction by providing excellent service to their customers, but also identify moments of truth and present appropriate services so that satisfied customers can strengthen their emotional attachment. In addition, it is necessary to strengthen the relationship with their firms by forming friendly relationships with customers who have high emotional attachment, and also to induce relationship commitment so that such customers have a strong sense of belonging and attachment to their firms.
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