• Korean Journal of Remote Sensing
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• v.39 no.6_1
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• pp.1211-1224
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• 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.

• Korean Journal of Remote Sensing
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• v.39 no.6_1
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• pp.1413-1425
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• 2023

The increasing frequency of wildfires due to climate change is causing extreme loss of life and property. They cause loss of vegetation and affect ecosystem changes depending on their intensity and occurrence. Ecosystem changes, in turn, affect wildfire occurrence, causing secondary damage. Thus, accurate estimation of the areas affected by wildfires is fundamental. Satellite remote sensing is used for forest fire detection because it can rapidly acquire topographic and meteorological information about the affected area after forest fires. In addition, deep learning algorithms such as convolutional neural networks (CNN) and transformer models show high performance for more accurate monitoring of fire-burnt regions. To date, the application of deep learning models has been limited, and there is a scarcity of reports providing quantitative performance evaluations for practical field utilization. Hence, this study emphasizes a comparative analysis, exploring performance enhancements achieved through both model selection and data design. This study examined deep learning models for detecting wildfire-damaged areas using Landsat 8 satellite images in California. Also, we conducted a comprehensive comparison and analysis of the detection performance of multiple models, such as U-Net and High-Resolution Network-Object Contextual Representation (HRNet-OCR). Wildfire-related spectral indices such as normalized difference vegetation index (NDVI) and normalized burn ratio (NBR) were used as input channels for the deep learning models to reflect the degree of vegetation cover and surface moisture content. As a result, the mean intersection over union (mIoU) was 0.831 for U-Net and 0.848 for HRNet-OCR, showing high segmentation performance. The inclusion of spectral indices alongside the base wavelength bands resulted in increased metric values for all combinations, affirming that the augmentation of input data with spectral indices contributes to the refinement of pixels. This study can be applied to other satellite images to build a recovery strategy for fire-burnt areas.

• Journal of Venture Innovation
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• v.3 no.2
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• pp.41-76
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• 2020

This study confirmed factors affecting smart factory technology acceptance through empirical analysis. It is a study on what factors have an important influence on the introduction of the smart factory, which is the core field of the 4th industry. I believe that there is academic and practical significance in the context of insufficient research on technology acceptance in the field of smart factories. This research was conducted based on the Unified Theory of Acceptance and Use of Technology (UTAUT), whose explanatory power has been proven in the study of the acceptance factors of information technology. In addition to the four independent variables of the UTAUT : Performance Expectancy, Effort Expectancy, Social Influence, and Facilitating Conditions, Government Assistance Expectancy, which is expected to be an important factor due to the characteristics of the smart factory, was added to the independent variable. And, in order to confirm the technical factors of smart factory technology acceptance, the Task Technology Fit(TTF) was added to empirically analyze the effect on Behavioral Intention. Trust is added as a parameter because the degree of trust in new technologies is expected to have a very important effect on the acceptance of technologies. Finally, empirical verification was conducted by adding Innovation Resistance to a research variable that plays a role as a moderator, based on previous studies that innovation by new information technology can inevitably cause refusal to users. For empirical analysis, an online questionnaire of random sampling method was conducted for incumbents of domestic small and medium-sized enterprises, and 309 copies of effective responses were used for empirical analysis. Amos 23.0 and Process macro 3.4 were used for statistical analysis. For accurate statistical analysis, the validity of Research Model and Measurement Variable were secured through confirmatory factor analysis. Accurate empirical analysis was conducted through appropriate statistical procedures and correct interpretation for causality verification, mediating effect verification, and moderating effect verification. Performance Expectancy, Social Influence, Government Assistance Expectancy, and Task Technology Fit had a positive (+) effect on smart factory technology acceptance. The magnitude of influence was found in the order of Government Assistance Expectancy(β=.487) > Task Technology Fit(β=.218) > Performance Expectancy(β=.205) > Social Influence(β=.204). Both the Task Characteristics and the Technology Characteristics were confirmed to have a positive (+) effect on Task Technology Fit. It was found that Task Characteristics(β=.559) had a greater effect on Task Technology Fit than Technology Characteristics(β=.328). In the mediating effect verification on Trust, a statistically significant mediating role of Trust was not identified between each of the six independent variables and the intention to introduce a smart factory. Through the verification of the moderating effect of Innovation Resistance, it was found that Innovation Resistance plays a positive (+) moderating role between Government Assistance Expectancy, and technology acceptance intention. In other words, the greater the Innovation Resistance, the greater the influence of the Government Assistance Expectancy on the intention to adopt the smart factory than the case where there is less Innovation Resistance. Based on this, academic and practical implications were presented.

• Journal of Venture Innovation
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• v.5 no.1
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• pp.19-37
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• 2022

The purpose of this study was to find out what could be the cause of increasing the re-use intention for the continuous management of customers in terms of finding a strategic plan for the survival of Medium Sized Hospital To this end, a hypothesis for the direct effect verifying the structural relationship, a hypothesis for the mediating effect of attachment, and a hypothesis for the moderating effect on the hospital image were presented. The survey analysis results for customers who experienced the services of 5 Medium Sized Hospital in Gyeonggi-do were as follows. First, The results of analysis of the effect of Medium Sized Hospital customers' perceived value on reuse intention are as follows. all sub-factors of perceived value did not have a significant effect on reuse intention. This is significant in that it shows that the change occurred due to the involvement of attachment. Second, the results of examining the mediating effect of attachment in the relationship between the perceived value of small and medium hospital customers and their intention to reuse are as follows. Attachment to doctor's competency significantly mediated the relationship between quality value and reuse intention, emotional value and reuse intention, and social value and reuse intention. Significantly mediated the relationship between the provinces and the relationship between the price value and the intention to reuse. Third, hospital image significantly adjusted the relationship between quality value and medical technology competency. Based on the above results, it is necessary to establish a strategy of value perceived by customers as a strategy to increase the reuse intention of small and medium hospital customers. Therefore, the strategic goal setting of this value should be 'promoting attachment', and since the hospital image adjusts the perceived value and attachment of small and medium hospital customers, it is an image strategy that allows customers to appreciate their attachment to doctors and medical technology more highly. will have to establish.

• Journal of the Korean Society of Marine Environment & Safety
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• v.29 no.6
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• pp.639-652
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• 2023

The fundamental background behind the introduction of the fishing vessel system is to allow petty small fishers to engage in pure fishery business activities with fishing vessels during normal times and engage in fishing vessel business only during specific periods (closed fishing season, etc.) thereby granting a qualification as an auxiliary tool for the economic activities of petty small fishers. In addition, fishing boats are allowed to engage in excursion ship activities using fishing vessels registered under the Fishing Vessels Act, the form of fishing vessels should also have a general and universal structure that is practically easy to engage in fishing activities in the field in accordance with the relevant regulations. However, most fishing vessel proprietors are currently focusing only on increasing income, and rather than building fishing vessels in a reasonable form suitable for the original purpose of general fishing vessels, they prefer an abnormal hull form equivalent to expediency, that is biased hull structure biased toward the fishing vessel business. As a result, it is causing serious problems in safety management as well as conflict [damaging relative equity in government support measures (tax-free oil supply, etc.), and depletion of livelihood-type fish stocks] with fishing vessel forces who consider the fishing vessel business only to be a part of the side job among all fishery business activities. Meanwhile, the most fundamental cause of this problem is that the current Fishing Management and Promotion Act, limits the concept of fishing vessels to fishing vessels registered under the Fishing Vessels Act, and applies survey standards accordingly. Accordingly, in this study, through analysis of the distribution status of fishing vessels, structural characteristics, operation status of fishing vessels, and the government's fishing promotion policies, etc., the relevant laws (regulations) have been reorganized to suit the current reality of the concept of fishing vessels to separate the current fishing vessel from fishing vessels and operate it as a fishing-only vessel.

• Journal of the Korean GEO-environmental Society
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• v.24 no.12
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• pp.61-67
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• 2023

Heat pipes located underground in urban areas and operated under high temperature and pressure conditions can cause large-scale human and economic damage if damaged. In order to predict damage in advance, damage and construction information of heat pipe are analyzed to derive independent variables that have a correlation with frequency of damage, and a simple regression analysis modified model using each variable is applied to the field. However, as the correlation between independent variables applied to the model increases, the independence between variables is harmed and the reliability of the model decreases. In this study, the independence of the pipe diameter, burial depth, insulation level of monitoring system, and disconnection or short circuit of the detection line, which are judged to be interrelated, was tested to derive a method for combining variables and setting categories necessary to apply to the frequency of damage estimation model. For the test of independence, the continuous variables pipe diameter and burial depth were each converted into three categories, insulation level of monitoring system was converted into two categories, and the categorical variable disconnection or short circuit of the detection line status was kept as two categories. As a result of the test of independence, p-value between pipe diameter and burial depth, level of monitoring system and disconnection or short circuit of the detection line was lower than the significance level (α = 0.05), indicating a large correlation between them. Therefore, the pipe diameter and burial depth were combined into one variable, and the categories of the combined variable were set to 9 considering the previously set categories. The insulation level of monitoring system and the disconnection or short circuit of the detection line were also combined into one variable. Since the insulation level is unreliable when the detection line status is disconnection or short circuit, the categories of the combined variable were set to 3.

• Journal of Intelligence and Information Systems
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• v.29 no.4
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• pp.229-256
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• 2023

The increase in telecommuting and household electricity demand due to the pandemic has led to significant changes in electricity demand patterns. This has led to difficulties in identifying KEPCO's PPA (power purchase agreements) and residential solar power generation and has added to the challenges of electricity demand forecasting and grid operation for power exchanges. Unlike other energy resources, electricity is difficult to store, so it is essential to maintain a balance between energy production and consumption. A shortage or overproduction of electricity can cause significant instability in the energy system, so it is necessary to manage the supply and demand of electricity effectively. Especially in the Fourth Industrial Revolution, the importance of data has increased, and problems such as large-scale fires and power outages can have a severe impact. Therefore, in the field of electricity, it is crucial to accurately predict the amount of power generation, such as renewable energy, along with the exact demand for electricity, for proper power generation management, which helps to reduce unnecessary power production and efficiently utilize energy resources. In this study, we reviewed the renewable energy generation forecasting system, its objectives, and practical applications to construct optimal aggregated power resources using data from 169 power plants provided by the Ministry of Trade, Industry, and Energy, developed an aggregation algorithm considering the settlement of the forecasting system, and applied it to the analytical logic to synthesize and interpret the results. This study developed an optimal aggregation algorithm and derived an aggregation configuration (Result_Number 546) that reached 80.66% of the maximum settlement amount and identified plants that increase the settlement amount (B1783, B1729, N6002, S5044, B1782, N6006) and plants that decrease the settlement amount (S5034, S5023, S5031) when aggregating plants. This study is significant as the first study to develop an optimal aggregation algorithm using aggregated power resources as a research unit, and we expect that the results of this study can be used to improve the stability of the power system and efficiently utilize energy resources.

• Journal of the Korean Academy of Esthetic Dentistry
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• v.32 no.1
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• pp.16-22
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• 2023

Esthetic factors are very important in the success of maxillary anterior implant restoration. However, achieving esthetic results is difficult, especially in cases where periodontitis has resulted in severe alveolar bone loss. In the case of maxillary anterior teeth, the alveolar ridge resorption that begins immediately after tooth extraction interferes with the esthetic implant restoration. Therefore immediate implant placement can be performed to minimize the alveolar ridge resorption. However, in severe bone loss cases, immediate implant placement could result in esthetic failure, and this result might cause irreparable problems. We can also perform alveolar ridge preservation and then place implants later. On JCP published in 2019, there is the consensus of European academy of periodontology on the extraction socket management and the timing of implant placement. This consensus states that alveolar ridge preservation should be considered when there is severe labial bone loss in an esthetically important area such as maxillary anterior region. On performing the alveolar ridge preservation, we cannot obtain the primary wound closure, so secondary wound healing is induced with open membrane technique or soft tissue grafting should be performed for primary wound closure. However, the secondary wound healing can have a negative impact on bone regeneration, and soft tissue grafting such as FGG or CT graft can be burdensome for both patients and dentists. On the other hand, by using the granulation tissue in the extraction socket, primary closure can be achieved without soft tissue grafting. Also some studies have shown that granulation tissue in periodontal defects contains stem cells that may help in tissue regeneration. Based on this, implant restorations were performed on maxillary anterior teeth with severe alveolar bone loss by alveolar ridge preservation using granulation tissue. In spite of the severe bone defect of the extraction socket, relatively esthetic results could be obtained in implant restorations.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.17 no.1
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• pp.121-137
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• 2022

The purpose of this study is to present the necessary success factors and strategies for high-tech social ventures and stakeholders in the related ecosystem by empirically identifying factors that affect their sustainable performance. Based on prior research, the dimensions of three performance factors were presented: core technology competency, core business competency, and social mission orientation. Then, such sub-dimensions such as technology innovation orientation, R&D capability, business model, customer orientation, social network, and social mission pursuit were derived. For empirical analysis, a survey was conducted on domestic high-tech social ventures, and the significance of the hypothesis was tested through PLS-structural equation analysis of the collected 243 valid data. As a result, it was found that the technology innovation orientation was embedded as an abstract organizational and cultural characteristic in the high-tech social venture, which is a research sample, and thus did not significantly affect the dependent variable. In other words, aiming for the latest cutting-edge technology alone cannot affect performance, and it is a result of proving the need for substantial influencing factors that can strengthen it. On the other hand, the business model had a significant effect only on social performance, which is presumed to be the limitation of measurement tools developed for social enterprises, and the results of additional multi-group analysis to determine the cause also supported the basis for this estimation. Excluding the previous two performance factors, R&D competency, customer orientation, social network, and social mission pursuit were all found to have a significant positive (+) effect on social and economic performance. This study laid a foundation for related research by identifying high-tech social ventures emerging in the ecosystem of a social economy and expanded empirical research models related to the performance of existing social enterprises and social ventures. However, in the research method or process, there were limitations such as factor derivation or verification for balance of dual performance, subjective measurement method, and sample representativeness. It is expected that more in-depth follow-up studies will continue by supplementing future limitations and designing improved research models.

• Journal of Food Hygiene and Safety
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• v.39 no.2
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• pp.118-127
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• 2024

This study investigated the levels of 345 pesticide residues in 50 herbal medicines sold in Incheon metropolitan city to determine their safety. Pesticide residues are harmful substances that can cause serious health problems owing to their toxicity and carcinogenicity. The analysis of pesticide residues in the samples was conducted using the quick, easy, cheap, effective, rugged, and safe (QuEChERS) method, known for its high analysis efficiency, to analyze a wide range of pesticides for which no standards have been set. The analysis was cross-validated with the pretreatment method outlined in the Korea Pharmacopoeia. Among the 50 samples encompassing 24 different herbs, 22 pesticide residues were detected in 24 samples, covering 7 distinct herbs, resulting in a detection rate of 48%. It is noteworthy that, except for two cases, all detected pesticides were those for which no standards were set. However, after conducting a risk evaluation considering the daily dosage of herb, it was determined that the levels of pesticide residues were within safe limits. Pesticides with high frequency within the same category of herbs were detected, indicating the necessity for continuous monitoring and regulation. In addition, comparative analysis using the pretreatment method outlined in the Korean Pharmacopoeia, yielded similar results, suggesting the possibility of analyzing pesticide residues in herbs using the QuEChERS method. The study emphasizes the importance of continuous monitoring of pesticide residues in herbs and the development of high-efficiency reliability analysis methods should continue to ensure consumer safety.