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
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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.
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.
As the 4th industrial revolution progresses, foreign countries are promoting smart manufacturing innovation through digital transformation as a priority task early on to secure a competitive edge in the manufacturing industry. In response, the Korean government is also promoting a policy to enhance the competitiveness of small and medium-sized manufacturing companies by promoting digital transformation in the corporate sector to meet the global trend of the 4th industrial revolution era. Manufacturing powerhouses such as Germany and Japan see manufacturing as a key sector in digital transformation and are leading related policies, while emerging countries such as China are also promoting manufacturing innovation strategies such as building digital infrastructure and creating a digital innovation ecosystem. Korea is promoting the 'Korean-style smart factory dissemination and expansion strategy' by transforming Germany's manufacturing innovation strategy for smart factory supply to suit the domestic situation. However, the policy to supply smart factories so far has been conducted with support from individual companies under the leadership of the government, and most of the smart factories are at the basic level, and it is evaluated that there are limitations such as the lack of manpower to operate smart factories. In addition, while the current policy focuses on expanding the supply of smart factories in SMEs, it is necessary to establish a smart manufacturing system through linkages between large and small businesses in order to achieve the original goal of establishing a smart manufacturing system. Therefore, it can be said that from the standpoint of small and medium-sized enterprises (SMEs), who are consumers of smart factories, it can be said that the digital transformation policy can achieve the expected results only when appropriate incentives are provided for the introduction of smart factories in a situation where management resources such as funds, technology, and human resources are lacking. In addition, it is judged that the uncertainty of the performance of digital investment always exists, and as long as large and small companies are maintained as an ecosystem of delivery and subcontracting, there is very little incentive for small and medium-sized manufacturing companies to voluntarily invest in or advance digital transformation. Therefore, the digital transformation policy of small and medium-sized manufacturing companies in the future has practical significance in that it suggests that there is a need to seek ways to attract SMEs' digital-related voluntary investment.
In accordance with the government's stance of actively promoting intelligent administrative service policies through data utilization, in the disaster and safety management field, it also is proceeding with disaster and safety management policies utilizing data and constructing systems for responding efficiently to new and complex disasters and establishing scientific and systematic safety policies. However, it is difficult to quickly and accurately grasp the on-site situation in the event of a disaster, and there are still limitations in providing information necessary for situation judgment and response only by displaying vast data. This paper focuses on deriving specific needs to make disaster situation management work more intelligent and efficient by utilizing intelligent information technology. Through individual interviews with workers at the Central Disaster and Safety Status Control Center, we investigated the scope of disaster situation management work and the main functions and usability of the geographic information system (GIS)-based integrated situation management system by practitioners in this process. In addition, the data built in the system was reclassified according to purpose and characteristics to check the status of data in the GIS-based integrated situation management system. To derive needed to make disaster situation management more intelligent and efficient by utilizing intelligent information technology, 3 strategies were established to quickly and accurately identify on-site situations, make data-based situation judgments, and support efficient situation management tasks, and implementation tasks were defined and task priorities were determined based on the importance of implementation tasks through analytic hierarchy process (AHP) analysis. As a result, 24 implementation tasks were derived, and to make situation management efficient, it is analyzed that the use of intelligent information technology is necessary for collecting, analyzing, and managing video and sensor data and tasks that can take a lot of time of be prone to errors when performed by humans, that is, collecting situation-related data and reporting tasks. We have a conclusion that among situation management intelligence strategies, we can perform to develop technologies for strategies being high important score, that is, quickly and accurately identifying on-site situations and efficient situation management work support.
As wildfires are difficult to predict, real-time monitoring is crucial for a timely response. Geostationary satellite images are very useful for active fire detection because they can monitor a vast area with high temporal resolution (e.g., 2 min). Existing satellite-based active fire detection algorithms detect thermal outliers using threshold values based on the statistical analysis of brightness temperature. However, the difficulty in establishing suitable thresholds for such threshold-based methods hinders their ability to detect fires with low intensity and achieve generalized performance. In light of these challenges, machine learning has emerged as a potential-solution. Until now, relatively simple techniques such as random forest, Vanilla convolutional neural network (CNN), and U-net have been applied for active fire detection. Therefore, this study proposed an active fire detection algorithm using state-of-the-art (SOTA) deep learning techniques using data from the Advanced Himawari Imager and evaluated it over East Asia and Australia. The SOTA model was developed by applying EfficientNet and lion optimizer, and the results were compared with the model using the Vanilla CNN structure. EfficientNet outperformed CNN with F1-scores of 0.88 and 0.83 in East Asia and Australia, respectively. The performance was better after using weighted loss, equal sampling, and image augmentation techniques to fix data imbalance issues compared to before the techniques were used, resulting in F1-scores of 0.92 in East Asia and 0.84 in Australia. It is anticipated that timely responses facilitated by the SOTA deep learning-based approach for active fire detection will effectively mitigate the damage caused by wildfires.
The purpose of this study was to improve weed management systems under varying carbon dioxide concentrations and temperatures by evaluating the growth of Acalypha australis and observing the efficacy of four foliar and four soil herbicides, as well as measuring phytotoxicity in soybean crops treated with these herbicides. In both growth chamber and greenhouse conditions, plant height and shoot fresh weight of Acalypha australis increased as temperature increased. The variable to maximum fluorescence ratio (Fv/Fm), relative electron transport rate (ETR), plant height, leaf area, and shoot fresh weight of Acalypha australis were higher at carbon dioxide concentrations of 800 ppm than at 400 ppm. The efficacy of a foliar herbicide, glufosinate, on Acalypha australis was lower at 30℃ than at 20℃ and 25℃ in the growth chamber condition and was also lower at 29℃ than at 21℃ and 25℃ in greenhouse conditions. In contrast, mecoprop efficacy on Acalypha australis was lower at 20℃ and 25℃ than at 30℃ in growth chamber conditions and lower at 21℃ and 25℃ than at 29℃ in greenhouse conditions. Glyphosate efficacy was lower at 21℃ than at 25℃ and 29℃ under greenhouse conditions. With soil herbicides, metolachlor and ethalfluraline, efficacies were higher at relatively high temperatures under both growth chamber and greenhouse conditions. However, in the case of linuron, the difference in efficacy was not observed under varying temperatures in both growth chamber and greenhouse conditions. When ¼ of the recommended glyphosate rates were applied to Acalypha australis, efficacy was lower under 800 ppm carbon dioxide concentrations than under 400 ppm. In contrast, when ¼ of the recommended rate of bentazone was applied to Acalypha australis, efficacy was higher under 800 ppm carbon dioxide concentrations than under 400 ppm. Despite application rates, glufosinate efficacy differed insignificantly under different carbon dioxide concentrations. When applied at ¼ of the recommended rate, the efficacy of ethalfuralin was higher under 800 ppm carbon dioxide concentrations than under 400 ppm. However, efficacies of other herbicides were not different despite varying carbon dioxide concentrations. Soybean phytotoxicity in crops treated with the recommended rate and twice the recommended rate of soil herbicides was not significantly different regardless of temperature and carbon dioxide concentrations. Overall, weed efficacy of some herbicides decreased in response to different temperatures and carbon dioxide concentrations. Therefore, new weed management methods are required to ensure high rates of weed control in conditions affected by climate change.
Korea has developed as an influential country over Asia and all over the world based on remarkable economic development. And the background of this development was possible due to the existence of those who sacrificed precious lives and contributed to the nation's existence in the past crisis. Every year, Korea holds an annual commemorative event with people of national merit, Korean War veterans, and their families, expressing gratitude for sacrifices and contributions at home and abroad, and providing economic support. The tragedy of the Korean War and the pro-democracy movement in Korea over the past half century will one day become a history of the distant past over time. As generations change and the purpose and method of exchange by region change, the tragic situation that occurred earlier and the way people sacrificed for the country are expected to be different from before. In particular, it is true that the number of Korean War veterans and their families is gradually decreasing as they are now old. In addition, due to the outbreak of global infectious diseases such as COVID-19, it is difficult to plan and conduct face to face events as well as before. Currently, Korea's digital technology is introducing various methods. 5G communication networks, smart-phones, tablet PCs, and smart devices that can experience virtual reality are already used in our real lives. Business meetings are held in a metaverse environment, and concerts by famous singers are held in an online environment. Artificial intelligence technology has also been introduced in the field of human resource recruitment and customer response services, improving the work efficiency of companies. And it seems that this technology can be used in the field of veterans. In particular, there is a metaverse technology that can vividly show the situation during the Korean War, and a way to digitalize the voices and facial expressions of currently surviving veterans to convey their memories and lessons to future generations in the long run. If this digital technology method is realized on an online platform to hold a veterans' celebration event, veterans and their families on the other side of the world will be able to participate in the event more conveniently.
Woo-Do Lee;Hyunsoo Kim;Jiseon Son;Eui-Chul Hong;Hee-Jin Kim;Yeon-Seo Yun;Hye Kyung Shin;Hwan-Ku Kang
Korean Journal of Poultry Science
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v.50
no.4
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pp.325-336
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2023
This study used leaves and stems of 'Tongchaeru', one of the sweet potato varieties, to investigate broiler productivity, meat quality, blood properties, growth hormones, and immune factor levels according to drying method and amount added to feed. For this experiment, a total of 720 1-day-old male Ross 308 broilers were used. Treatments were assigned with 3 replicates per treatment and 20 birds were assigned to each replicate. The treatment group was designed into 12 treatments according to the type of natural product (leaves (L), stems (S)), drying type (natural (N), hot air (H), freeze (F)) and amount added (0.1%, 0.3%). The test was conducted for a total of 5 weeks. In this study, there was no significant difference in productivity depending on the type and amount of additives added (P>0.05). The FS 0.3% group showed high pH and WHC levels, and the shear force was lowest at HL 0.1% group (P<0.05). Blood cell and serum biochemical components were similar in all treatments, and growth hormone IGF-1 was highest in FS 0.1% group (P<0.05). There was no significant difference in IFN-γ, but the highest level of IL-6 was seen in the HS 0.1% group (P<0.05). In conclusion, the meat quality and the level of growth hormone and immune factors in the body were different depending on the type and amount of dried leaves and stems of sweet potato 'Tongchaeru', further study is needed to compare the selected additives and amounts added with those without additions.
Recently, import and export companies have been using T/T remittance and Surrender B/L more frequently than L/C when selecting the process and method of trade payment settlement. The new trade and logistics environment is thriving in the era of the Fourth Industrial Revolution (4IR). Document-based trade transactions are undergoing a digitalization as bills of lading or smart contracts are being developed. The purpose of this study is to verify whether exporters choose export payment types based on negotiating factors. In addition, we would like to discuss the application of the characteristics of the new trade and logistics environment. Data for analysis was collected through surveys. The collection method consisted of direct visits to the company, e-mail, fax, and online surveys. The survey distribution period is from February 1, 2023, to April 30, 2023. The questionnaire was distributed in 2,000 copies, and 447 copies were collected. The final 336 copies were used for analysis, excluding 111 copies that were deemed inappropriate for the purpose of this study. The results of the study are shown below. First, among the negotiating factors, the product differentiation of exporters did not significantly affect the selection of export payment types. Second, among the negotiating factors, the greater the purchasing advantage recognized by exporters, the higher the possibility of using the post-transfer method. In addition to analyzing the results, this study suggests that exporters should consider adopting new payment methods, such as blockchain technology-based bills of lading and trade finance platforms, to adapt to the characteristics of the evolving trade and logistics environment. Therefore, exporters should continue to show interest in initiatives aimed at digitizing trade documents as a response to the challenges posed by bills of lading. In future studies, it is necessary to address the lack of social awareness in Korea by conducting advanced research abroad.
This study compared the nature of disgust caused by the crime scene with that by the stereotype of the sexual-minority defendant, and compared the effect of each type of disgust on evidence evaluation and legal judgment. A total of 600 participants (300 men, average age of 44.40) were randomly assigned to sources of disgust (crime scene, sexual minorities defendant, control condition), the existence of additional evidence of innocence (o/x), and the existence of judicial directives (o/x). As a result of the study, disgust under the condition of a cruel crime scene with strong physical disgust was significantly higher than that of the sexual minority defendant, interpreted the evidence in a more guilty direction, and was more prone to_evaluate that the defendant was guilty. It is noteworthy that evidence evaluation was a significant moderating variable between disgust and probability of guilt under conditions where the source of disgust was a sexual minority, but not under control conditions and crime scene condition. It means that the effect of disgust on legal judgment may not be direct when the defendant is a sexual minority. In addition, the existence of the judicial instruction had a significant inverse effect on the sentence. And simple effect analysis found that presenting judicial instruction lowered probability of guilt only under the control condition. This makes it reasonable to infer that disgust derived from the characteristics of the crime scene and the defendant can be recognized as integral emotions that are difficult to correct with instructions. Finally, pity for the defendant was significantly higher under the conditions of sexual minority which shows that an emotional response of sympathy may occur in addition to disgust for sexual minorities. After examining the nature of disgust (physical & moral), legal judgment according to the source and degree of disgust was reviewed. In addition, the meaning of disgust and sympathy for the sexual minority defendant was discussed.
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