Validation of ECOSTRESS Based Land Surface Temperature and Evapotranspiration (PT-JPL) Data Across Korea (국내에서 ECOSTRESS 지표면 온도 및 증발산(PT-JPL) 자료의 검증)
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- KSCE Journal of Civil and Environmental Engineering Research
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- 제44권5호
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- pp.637-648
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- 2024
The frequency of extreme weather events such as heavy and extreme rainfall has been increasing due to global climate change. Accordingly, it is essential to quantify hydrometeorological variables for efficient water resource management. Among the various hydro-meteorological variables, Land Surface Temperature (LST) and Evapotranspiration (ET) play key roles in understanding the interaction between the surface and the atmosphere. In Korea, LST and ET are mainly observed through ground-based stations, which also have limitation in obtaining data from ungauged watersheds, and thus, it hinders to estimate spatial behavior of LST and ET. Alternatively, remote sensing-based methods have been used to overcome the limitation of ground-based stations. In this study, we evaluated the applicability of the National Aeronautics and Space Administration's (NASA) ECOsystem Spaceborne Thermal Radiometer Experiment on Space Station (ECOSTRESS) LST and ET data estimated across Korea (from July 1, 2018 to December 31, 2022). For validation, we utilized NASA's MODerate Resolution Imaging Spectroradiometer (MODIS) data and eddy covariance flux tower observations managed by agencies under the Ministry of Environment of South Korea. Overall, results indicated that ECOSTRESS-based LSTs showed similar temporal trends (R: 0.47~0.73) to MODIS and ground-based observations. The index of agreement also showed a good agreement of ECOSTRESS-based LST with reference datasets (ranging from 0.82 to 0.91), although it also revealed distinctive uncertainties depending on the season. The ECOSTRESS-based ET demonstrated the capability to capture the temporal trends observed in MODIS and ground-based ET data, but higher Mean Absolute Error and Root Mean Square Error were also exhibited. This is likely due to the low acquisition rate of the ECOSTRESS data and environmental factors such as cooling effect of evapotranspiration, overestimation during the morning. This study suggests conducting additional validation of ECOSTRESS-based LST and ET, particularly in topographical and hydrological aspects. Such validation efforts could enhance the practical application of ECOSTRESS for estimating basin-scale LST and ET in Korea.
The overall study of Samsaebulhoedo (painting of the Assembly of Buddhas of Three Ages) at Yongjusa Temple has focused on dating it, analyzing the painting style, identifying its painter, and scrutinizing the related documents. However, its greater coherence could be achieved through additional support from empirical evidence and logical consistency. Recent studies on Samsaebulhoedo at Yongjusa Temple that postulate that the painting could have been produced by a monk-painter in the late nineteenth century and that an original version produced in 1790 could have been retouched by a painter in the 1920s using a Western painting style lack such empirical proof and logic. Although King Jeongjo's son was not yet installed as crown prince, the Samsaebulhoedo at Yongjusa Temple contained a conventional written prayer wishing for a long life for the king, queen, and crown prince: "May his majesty the King live long / May her majesty the Queen live long / May his highness the Crown Prince live long" (主上殿下壽萬歲, 王妃殿下壽萬歲, 世子邸下壽萬歲). Later, this phrase was erased using cinnabar and revised to include unusual content in an exceptional order: "May his majesty the King live long / May his highness the King's Affectionate Mother (Jagung) live long / May her majesty the Queen live long / May his highness the Crown Prince live long" (主上殿下壽萬歲, 慈宮邸下壽萬歲, 王妃殿下壽萬歲, 世子邸下壽萬歲). A comprehensive comparison of the formats and contents in written prayers found on late Joseon Buddhist paintings and a careful analysis of royal liturgy during the reign of King Jeongjo reveal Samsaebulhoedo at Yongjusa Temple to be an original version produced at the time of the founding of Yongjusa Temple in 1790. According to a comparative analysis of formats, iconography, styles, aesthetic sensibilities, and techniques found in Buddhist paintings and paintings by Joseon court painters from the eighteenth and nineteenth centuries, Samsaebulhoedo at Yongjusa Temple bears features characteristic of paintings produced around 1790, which corresponds to the result of analysis on the written prayer. Buddhist paintings created up to the early eighteenth century show deities with their sizes determined by their religious status and a two-dimensional conceptual composition based on the traditional perspective of depicting close objects in the lower section and distant objects above. This Samsaebulhoedo, however, systematically places the Buddhist deities within a threedimensional space constructed by applying a linear perspective. Through the extensive employment of chiaroscuro as found in Western painting, it expresses white highlights and shadows, evoking a feeling that the magnificent world of the Buddhas of the Three Ages actually unfolds in front of viewers. Since the inner order of a linear perspective and the outer illusion of chiaroscuro shading are intimately related to each other, it is difficult to believe that the white highlights were a later addition. Moreover, the creative convergence of highly-developed Western painting style and techniques that is on display in this Samsaebulhoedo could only have been achieved by late-Joseon court painters working during the reign of King Jeongjo, including Kim Hongdo, Yi Myeong-gi, and Kim Deuksin. Deungun, the head monk of Yongjusa Temple, wrote Yongjusa sajeok (History of Yongjusa Temple) by compiling the historical records on the temple that had been transmitted since its founding. In Yongjusa sajeok, Deungun recorded that Kim Hongdo painted Samsaebulhoedo as if it were a historical fact. The Joseon royal court's official records, Ilseongnok (Daily Records of the Royal Court and Important Officials) and Suwonbu jiryeong deungnok (Suwon Construction Records), indicate that Kim Hongdo, Yi Myeong-gi, and Kim Deuksin all served as a supervisor (gamdong) for the production of Buddhist paintings. Since within Joseon's hierarchical administrative system it was considered improper to allow court painters of government position to create Buddhist paintings which had previously been produced by monk-painters, they were appointed as gamdong in name only to avoid a political liability. In reality, court painters were ordered to create Buddhist paintings. During their reigns, King Yeongjo and King Jeongjo summoned the literati painters Jo Yeongseok and Kang Sehwang to serve as gamdong for the production of royal portraits and requested that they paint these portraits as well. Thus, the boundary between the concept of supervision and that of painting occasionally blurred. Supervision did not completely preclude painting, and a gamdong could also serve as a painter. In this light, the historical records in Yongjusa sajeok are not inconsistent with those in Ilseongnok, Suwonbu jiryeong deungnok, and a prayer written by Hwang Deok-sun, which was found inside the canopy in Daeungjeon Hall at Yongjusa Temple. These records provided the same content in different forms as required for their purposes and according to the context. This approach to the Samsaebulhoedo at Yongjusa Temple will lead to a more coherent explanation of dating the painting, analyzing its style, identifying its painter, and interpreting the relevant documents based on empirical grounds and logical consistency.
Recently, AlphaGo which is Bakuk (Go) artificial intelligence program by Google DeepMind, had a huge victory against Lee Sedol. Many people thought that machines would not be able to win a man in Go games because the number of paths to make a one move is more than the number of atoms in the universe unlike chess, but the result was the opposite to what people predicted. After the match, artificial intelligence technology was focused as a core technology of the fourth industrial revolution and attracted attentions from various application domains. Especially, deep learning technique have been attracted as a core artificial intelligence technology used in the AlphaGo algorithm. The deep learning technique is already being applied to many problems. Especially, it shows good performance in image recognition field. In addition, it shows good performance in high dimensional data area such as voice, image and natural language, which was difficult to get good performance using existing machine learning techniques. However, in contrast, it is difficult to find deep leaning researches on traditional business data and structured data analysis. In this study, we tried to find out whether the deep learning techniques have been studied so far can be used not only for the recognition of high dimensional data but also for the binary classification problem of traditional business data analysis such as customer churn analysis, marketing response prediction, and default prediction. And we compare the performance of the deep learning techniques with that of traditional artificial neural network models. The experimental data in the paper is the telemarketing response data of a bank in Portugal. It has input variables such as age, occupation, loan status, and the number of previous telemarketing and has a binary target variable that records whether the customer intends to open an account or not. In this study, to evaluate the possibility of utilization of deep learning algorithms and techniques in binary classification problem, we compared the performance of various models using CNN, LSTM algorithm and dropout, which are widely used algorithms and techniques in deep learning, with that of MLP models which is a traditional artificial neural network model. However, since all the network design alternatives can not be tested due to the nature of the artificial neural network, the experiment was conducted based on restricted settings on the number of hidden layers, the number of neurons in the hidden layer, the number of output data (filters), and the application conditions of the dropout technique. The F1 Score was used to evaluate the performance of models to show how well the models work to classify the interesting class instead of the overall accuracy. The detail methods for applying each deep learning technique in the experiment is as follows. The CNN algorithm is a method that reads adjacent values from a specific value and recognizes the features, but it does not matter how close the distance of each business data field is because each field is usually independent. In this experiment, we set the filter size of the CNN algorithm as the number of fields to learn the whole characteristics of the data at once, and added a hidden layer to make decision based on the additional features. For the model having two LSTM layers, the input direction of the second layer is put in reversed position with first layer in order to reduce the influence from the position of each field. In the case of the dropout technique, we set the neurons to disappear with a probability of 0.5 for each hidden layer. The experimental results show that the predicted model with the highest F1 score was the CNN model using the dropout technique, and the next best model was the MLP model with two hidden layers using the dropout technique. In this study, we were able to get some findings as the experiment had proceeded. First, models using dropout techniques have a slightly more conservative prediction than those without dropout techniques, and it generally shows better performance in classification. Second, CNN models show better classification performance than MLP models. This is interesting because it has shown good performance in binary classification problems which it rarely have been applied to, as well as in the fields where it's effectiveness has been proven. Third, the LSTM algorithm seems to be unsuitable for binary classification problems because the training time is too long compared to the performance improvement. From these results, we can confirm that some of the deep learning algorithms can be applied to solve business binary classification problems.
This study was designed to testify the reliability and validation on the Korean version of the Social Adaptation Self-rating Scale(SASS) which was developed from Bose et al. for the evaluation of social motivation and behavior of depressed patients in 1997. Interests for the social world, those of social functioning, of patients were involved in the addition of new measure of disturbance. And those were distinct from abnormalities of thought, mood and symptoms of patients with major depression. As the previous reports there were several evidences that treatments may be less likely to be effective if the system they act on is dysfunctional. Thus, a better social situation favoured better outcome. As a matter of fact, however, those reports were developed in the course of the evaluation of interpersonal therapy(IPT) and cognitive therapy. Accordingly the conversed question -whether pharmacological therapy with antidepressants can impact on social functioning in addition to addressing the core features of illness- has been addressed. To date, anyhow, it is accepted that enhancement of social functioning may be a therapeutic principle in its own right and illness rarely divorced from social context. In terms of those concepts the introduction of an assessment of social functioning into pharmacotherapeutic studies of depression has been welcomed and might be a potent instrument for evaluating the relative pharmacoeconomic benefits of different treatments. Despite of many scales which were applied for the evaluation of symptoms in the patients with depression, however, the scale for the evaluation of social functiong has not been introduced in Korea yet. Thus, this study was designed to introduce the concepts of social functioning in the patients with depression and to testify the reliability and validation on Korean version of SASS. This Korean version of SASS was submitted to a reliability and validation procedure based on the data from healthy general population survey in 291 individuals and 40 patients with major depression. Cronbach a was 0.790 in total subjects group and the correlation of test-retest was statistically significant(y=0.653, p<0.0l). Thus, the Korean version of SASS might be shown to be valid and reliable. The results of multivariate analyses allowed the identification of 3 principle factors(factor 1 = intersts in social activities, factor 2 = active interpersonal relationship, factor 3 = selfesteem) in normal group, however, it could be counted as only one factor in the depression group because nearly total items of SASS were involved in factor 1. In the view of these results, the Korean version of SASS may be useful additional tool for the evaluation of social functioning in depression.
With the rapid development of artificial intelligence technology, various techniques have been developed to extract meaningful information from unstructured text data which constitutes a large portion of big data. Over the past decades, text mining technologies have been utilized in various industries for practical applications. In the field of business intelligence, it has been employed to discover new market and/or technology opportunities and support rational decision making of business participants. The market information such as market size, market growth rate, and market share is essential for setting companies' business strategies. There has been a continuous demand in various fields for specific product level-market information. However, the information has been generally provided at industry level or broad categories based on classification standards, making it difficult to obtain specific and proper information. In this regard, we propose a new methodology that can estimate the market sizes of product groups at more detailed levels than that of previously offered. We applied Word2Vec algorithm, a neural network based semantic word embedding model, to enable automatic market size estimation from individual companies' product information in a bottom-up manner. The overall process is as follows: First, the data related to product information is collected, refined, and restructured into suitable form for applying Word2Vec model. Next, the preprocessed data is embedded into vector space by Word2Vec and then the product groups are derived by extracting similar products names based on cosine similarity calculation. Finally, the sales data on the extracted products is summated to estimate the market size of the product groups. As an experimental data, text data of product names from Statistics Korea's microdata (345,103 cases) were mapped in multidimensional vector space by Word2Vec training. We performed parameters optimization for training and then applied vector dimension of 300 and window size of 15 as optimized parameters for further experiments. We employed index words of Korean Standard Industry Classification (KSIC) as a product name dataset to more efficiently cluster product groups. The product names which are similar to KSIC indexes were extracted based on cosine similarity. The market size of extracted products as one product category was calculated from individual companies' sales data. The market sizes of 11,654 specific product lines were automatically estimated by the proposed model. For the performance verification, the results were compared with actual market size of some items. The Pearson's correlation coefficient was 0.513. Our approach has several advantages differing from the previous studies. First, text mining and machine learning techniques were applied for the first time on market size estimation, overcoming the limitations of traditional sampling based- or multiple assumption required-methods. In addition, the level of market category can be easily and efficiently adjusted according to the purpose of information use by changing cosine similarity threshold. Furthermore, it has a high potential of practical applications since it can resolve unmet needs for detailed market size information in public and private sectors. Specifically, it can be utilized in technology evaluation and technology commercialization support program conducted by governmental institutions, as well as business strategies consulting and market analysis report publishing by private firms. The limitation of our study is that the presented model needs to be improved in terms of accuracy and reliability. The semantic-based word embedding module can be advanced by giving a proper order in the preprocessed dataset or by combining another algorithm such as Jaccard similarity with Word2Vec. Also, the methods of product group clustering can be changed to other types of unsupervised machine learning algorithm. Our group is currently working on subsequent studies and we expect that it can further improve the performance of the conceptually proposed basic model in this study.
Purpose: To improve the management of a medical linear accelerator, the records of operational failures of a Varian CL2l00C over a ten year period were retrospectively analyzed. Materials and Methods: The failures were classified according to the involved functional subunits, with each class rated Into one of three levels depending on the operational conditions. The relationships between the failure rate and working ratio and between the failure rate and outside temperature were investigated. In addition, the average life time of the main part and the operating efficiency over the last 4 years were analyzed. Results: Among the recorded failures (total 587 failures), the most frequent failure was observed in the parts related with the collimation system, including the monitor chamber, which accounted for
1. Introduction: Contrast to the offline purchasing environment, online store cannot offer the sense of touch or direct visual information of its product to the consumers. So the builder of the online shopping mall should provide more concrete and detailed product information(Kim 2008), and Alba (1997) also predicted that the quality of the offered information is determined by the post-purchase consumer satisfaction. In practice, many fashion and apparel online shopping malls offer the picture information with the product on the real person model to enhance the usefulness of product information. On the other virtual product experience has been suggested to the ways of overcoming the online consumers' limited perceptual capability (Jiang & Benbasat 2005). However, the adoption and the facilitation of the virtual reality tools requires high investment and technical specialty compared to the text/picture product information offerings (Shaffer 2006). This could make the entry barrier to the online shopping to the small retailers and sometimes it could be demanding high level of consumers' perceptual efforts. So the expensive technological solution could affects negatively to the consumer decision making processes. Nevertheless, most of the previous research on the online product information provision suggests the VR be the more effective tools. 2. Research Model and Hypothesis: Presented in
The organization for managing records and archives did not emerge together with the founding of the Chinese Communist Party. Such management became active with the establishment of the Department of Documents (文書科) and its affiliated offices overseeing reading and safekeeping of official papers, after the formation of the Central Secretariat(中央秘書處) in 1926. Improving the work of the Secretariat's organization became the focus of critical discussions in the early 1930s. The main criticism was that the Secretariat had failed to be cognizant of its political role and degenerated into a mere "functional organization." The solution to this was the "politicization of the Secretariat's work." Moreover, influenced by the "Rectification Movement" in the 1940s, the party emphasized the responsibility of the Resources Department (材料科) that extended beyond managing documents to collecting, organizing and providing various kinds of important information data. In the mean time, maintaining security with regard to composing documents continued to be emphasized through such methods as using different names for figures and organizations or employing special inks for document production. In addition, communications between the central political organs and regional offices were emphasized through regular reports on work activities and situations of the local areas. The General Secretary not only composed the drafts of the major official documents but also handled the reading and examination of all documents, and thus played a central role in record processing. The records, called archives after undergoing document processing, were placed in safekeeping. This function was handled by the "Document Safekeeping Office(文件保管處)" of the Central Secretariat's Department of Documents. Although the Document Safekeeping Office, also called the "Central Repository(中央文庫)", could no longer accept, beginning in the early 1930s, additional archive transfers, the Resources Department continued to strengthen throughout the 1940s its role of safekeeping and providing documents and publication materials. In particular, collections of materials for research and study were carried out, and with the recovery of regions which had been under the Japanese rule, massive amounts of archive and document materials were collected. After being stipulated by rules in 1931, the archive classification and cataloguing methods became actively systematized, especially in the 1940s. Basically, "subject" classification methods and fundamental cataloguing techniques were adopted. The principle of assuming "importance" and "confidentiality" as the criteria of management emerged from a relatively early period, but the concept or process of evaluation that differentiated preservation and discarding of documents was not clear. While implementing a system of secure management and restricted access for confidential information, the critical view on providing use of archive materials was very strong, as can be seen in the slogan, "the unification of preservation and use." Even during the revolutionary movement and wars, the Chinese Communist Party continued their efforts to strengthen management and preservation of records & archives. The results were not always desirable nor were there any reasons for such experiences to lead to stable development. The historical conditions in which the Chinese Communist Party found itself probably made it inevitable. The most pronounced characteristics of this process can be found in the fact that they not only pursued efficiency of records & archives management at the functional level but, while strengthening their self-awareness of the political significance impacting the Chinese Communist Party's revolution movement, they also paid attention to the value possessed by archive materials as actual evidence for revolutionary policy research and as historical evidence of the Chinese Communist Party.
The data center is a physical environment facility for accommodating computer systems and related components, and is an essential foundation technology for next-generation core industries such as big data, smart factories, wearables, and smart homes. In particular, with the growth of cloud computing, the proportional expansion of the data center infrastructure is inevitable. Monitoring the health of these data center facilities is a way to maintain and manage the system and prevent failure. If a failure occurs in some elements of the facility, it may affect not only the relevant equipment but also other connected equipment, and may cause enormous damage. In particular, IT facilities are irregular due to interdependence and it is difficult to know the cause. In the previous study predicting failure in data center, failure was predicted by looking at a single server as a single state without assuming that the devices were mixed. Therefore, in this study, data center failures were classified into failures occurring inside the server (Outage A) and failures occurring outside the server (Outage B), and focused on analyzing complex failures occurring within the server. Server external failures include power, cooling, user errors, etc. Since such failures can be prevented in the early stages of data center facility construction, various solutions are being developed. On the other hand, the cause of the failure occurring in the server is difficult to determine, and adequate prevention has not yet been achieved. In particular, this is the reason why server failures do not occur singularly, cause other server failures, or receive something that causes failures from other servers. In other words, while the existing studies assumed that it was a single server that did not affect the servers and analyzed the failure, in this study, the failure occurred on the assumption that it had an effect between servers. In order to define the complex failure situation in the data center, failure history data for each equipment existing in the data center was used. There are four major failures considered in this study: Network Node Down, Server Down, Windows Activation Services Down, and Database Management System Service Down. The failures that occur for each device are sorted in chronological order, and when a failure occurs in a specific equipment, if a failure occurs in a specific equipment within 5 minutes from the time of occurrence, it is defined that the failure occurs simultaneously. After configuring the sequence for the devices that have failed at the same time, 5 devices that frequently occur simultaneously within the configured sequence were selected, and the case where the selected devices failed at the same time was confirmed through visualization. Since the server resource information collected for failure analysis is in units of time series and has flow, we used Long Short-term Memory (LSTM), a deep learning algorithm that can predict the next state through the previous state. In addition, unlike a single server, the Hierarchical Attention Network deep learning model structure was used in consideration of the fact that the level of multiple failures for each server is different. This algorithm is a method of increasing the prediction accuracy by giving weight to the server as the impact on the failure increases. The study began with defining the type of failure and selecting the analysis target. In the first experiment, the same collected data was assumed as a single server state and a multiple server state, and compared and analyzed. The second experiment improved the prediction accuracy in the case of a complex server by optimizing each server threshold. In the first experiment, which assumed each of a single server and multiple servers, in the case of a single server, it was predicted that three of the five servers did not have a failure even though the actual failure occurred. However, assuming multiple servers, all five servers were predicted to have failed. As a result of the experiment, the hypothesis that there is an effect between servers is proven. As a result of this study, it was confirmed that the prediction performance was superior when the multiple servers were assumed than when the single server was assumed. In particular, applying the Hierarchical Attention Network algorithm, assuming that the effects of each server will be different, played a role in improving the analysis effect. In addition, by applying a different threshold for each server, the prediction accuracy could be improved. This study showed that failures that are difficult to determine the cause can be predicted through historical data, and a model that can predict failures occurring in servers in data centers is presented. It is expected that the occurrence of disability can be prevented in advance using the results of this study.
This paper will analyze the filial piety based ethics of Daesoonjinrihoe (大巡眞理會) and the traditional filial piety of Confucianism (儒敎), Buddhism (佛敎) and Taoism (道敎) through comparing and contrasting their unique systems. The traditional Korean ethics regarding filial piety are in great need of reformation as the relationship between the parents and children should not be vertical or unilateral but parallel and reciprocal. However, there have not been sufficient in-depth studies on this specific ideology and alternative approaches. Regarding this prospect, one representative Korean indigenous new religion, Daesoonjinrihoe has emerged and directly engages in the collision between traditionalism and modernity. The modernity of Daesoonjinrihoe, enables the observation of how the filial piety based ethics have developed within a system of doctrine and thereby provides an exemplary model of traditional filial piety reimagined in accordance with modern sensibilities. A brief summary of comparative findings is as follows: First, Daesoonjinrihoe and Confucianism have taken serving parents with respect as an ethic within filial piety, but Confucianism engenders this ideal through the unilateral and unconditional sacrifice of younger people based on patriarchal feudalism whereas Daesoonjinrihoe has rejected such unilateral sacrifice and instead promotes mutual beneficience between parents and children. This difference occurs, in part, due to the filial piety of Confucianism rising in the midst of the feudal order whereas the ideology of Daesoonjinrihoe contains ideals such as "the reciprocation of favor for mutual beneficence (報恩相生)" and "respect for humanity (人尊)," both of which serve as key principles of the new religious world as envisioned by Daesoonjinrihoe. Second, filial piety in Buddhism and Taoism tends to be passive and inactive and is often expressed by praying for happiness and longevity for one's parents while they are alive and later praying for the heavenly rebirth of one's parents after they die. The filial piety of Daesoonjinrihoe also partially contains such ideas, however; they are extended much further and arrive upon novel and profound expressions. The spectrum of the filial piety in Daesoonjinrihoe expands to the extent children perform actions to resolve their parent's sins and pave a new road for their parents. This filial piety requires a cultivation practice from both parents and children. This system of dual cultivation was established because the world-view of Daesoonjinrihoe enables both parents and children to enjoy happiness and wealth both of which are achieved through the completion of religious objectives following cultivation practice. Third, Confucianism and Daesoonjinrihoe hold memorial services for ancestors with sincerity as an expression of filial piety. Filial piety in the Confucian context excludes ideas from Shamanism and thereby memorial services are held for impersonal entities, however; in the Daesoonjinrihoe context, memorial services are held for personal-entities. Accordingly, holding a memorial service for ancestors with sincerity has a greater sense of realism in Daesoonjinrihoe than it does in Confucianism. Fourth, while Confucianism and Daesoonjinrihoe both aim to requite the grace received from ancestors, the contents of grace and reciprocation of favors (報恩) are viewed differently. In Confucianism, since the ancestors existed previously and bestowed the gift of life to their children and indirectly, all of their descendents. Therefore, memorial services for ancestors are held to convey gratitude and filial piety. However, in Daesoonjinrihoe, ancestors not only bestowed the gift of earthly life to their descendents, in the spirit realm, ancestral spirits also spend sixty years accumulating the merit necessary to imbue each of their descendents with spiritual insight. Consequently, filial piety is expressed through memorial services as well as spiritual cultivation. Fifth, in Confucianism, achieving the fame and prestige indicative of success in the mundane world can be an act of filial piety as it would bring pride to one's ancestors, but in Daesoonjinrihoe, succeeding in religious objectives through spiritual cultivation is considered to be a higher form of filial piety. Sixth, Confucianism, Buddhism and Taoism all observe filial piety as system of familial ethics based in morality. This is likewise true of Daesoonjinrihoe, however; Daesoonjinrihoe confers greater importance on filial piety as an essential form of ethics for religious redemption. This is due to the Daesoon interpretation that the absence of filial piety was the direct cause which led to the sickened state of the world and its collapse. Forgetting the grace of parents who have given the gift of life or the grace of ancestral spirits who have accumulated merit on behalf of their descendents are acts of ingratitude which are unacceptable during the period of Reordering of the Universe. Judging from these findings, Daesoonjinrihoe embraces parts of traditional filial piety as it exists in Confucianism, Buddhism and Taoism, but it does so on the ground of its own unique culture. Through re-interpretation and re-creation, ideas regarding filial piety are being further developed. Namely, filial piety in Daesoonjinrihoe is regulations founded upon the reciprocation of favors for mutual beneficence and respect for humanity. Therefore, it is understood as a concept wherein one's own cultivation practice is performed in order to reach religious objectives, the perfection of personal character, and spiritual insight. This requires that even recipents of filial piety (i.e., parents) perform certain cultivation practices to enjoy happiness and wealth. Additionally, filial piety in Daesoonjinrihoe manifests a reinforced religious character and also serves as a system ethics which is soteriologically essential for salvation during the period known as the Reordering of the Universe.
, research model suggests VR effect could be moderated by the product types by the usage situations. Product types could be defined as the portable product and installed product, and the information offering type as still picture of the product, picture of the product with the real-person model and VR. 3. Methods and Results: 3.1. Experimental design and measured variables We designed the 2(product types) X 3(product information types) experimental setting and measured dependent variables such as information usefulness, attitude toward the shopping mall, overall product quality, purchase intention and the revisiting intention. In the case of information usefulness and attitude toward the shopping mall were measured by multi-item scale. As a result of reliability test, Cronbach's Alpha value of each variable shows more than 0.6. Thus, we ensured that the internal consistency of items. 3.2. Manipulation check The main concern of this study is to verify the moderate effect by the product type of usage situation. indicates that our experimental manipulation of the moderate effect of the product type was successful. 3.3. Results As
indicates, there was a significant main effect on the only one dependent variable(attitude toward the shopping mall) by the information types. As predicted, VR has highest mean value compared to other information types. Thus, H1 was partially supported. However, main effect by the product types was not found. To evaluate H2 and H3, a two-way ANOVA was conducted. As
indicates, there exist the interaction effects on the three dependent variables(information usefulness, overall product quality and purchase intention) by the information types and the product types. As predicted, picture of the product with the real-person model has highest mean among the information types in the case of portable product. On the other hand, VR has highest mean among the information types in the case of installed product. Thus, H2 and H3 was supported. 4. Implications: The present study found the moderate effect by the product type of usage situation. Based on the findings the following managerial implications are asserted. First, it was found that information types are affect only the attitude toward the shopping mall. The meaning of this finding is that VR effects are not enough to understand the product itself. Therefore, we must consider when and how to use this VR tools. Second, it was found that there exist the interaction effects on the information usefulness, overall product quality and purchase intention. This finding suggests that consideration of usage situation helps consumer's understanding of product and promotes their purchase intention. In conclusion, not only product attributes but also product usage situations must be fully considered by the online retailers when they want to meet the needs of consumers.
Chinese Communist Party's Management of Records & Archives during the Chinese Revolution Period
(혁명시기 중국공산당의 문서당안관리)
Development of a complex failure prediction system using Hierarchical Attention Network
(Hierarchical Attention Network를 이용한 복합 장애 발생 예측 시스템 개발)
A Study on the Religiosity of Filial Piety Ethics in Daesoonjinrihoe
(대순진리회의 효 윤리에 나타난 종교성 연구)
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