• Journal of Korean Medicine Rehabilitation
• /
• v.32 no.3
• /
• pp.13-27
• /
• 2022

Objectives This study investigated the trends in domestic and international clinical research in craniosacral therapy, classified as a type of Chuna manual therapy, and suggested further directions in Korean medicine. Methods This scoping review was performed using the Arksey and O'Malley methodological framework and preferred reporting items as per the preferred reporting items for systematic reviews and meta-analyses extension for scoping reviews checklist. Eight electronic databases (PubMed, EMBASE, Cochrane Library, Koreanstudies Information Service System [KISS], KMBASE, Oriental Medicine Advanced Searching Integrated System [OASIS], Research Information Sharing Service [RISS], ScienceON) were searched to identify articles with the search terms "craniosacral therapy" and "cranial osteopathy" until December 2021. Results Forty-five studies were eligible as per our inclusion criteria. Most research studies (n=44) were conducted in the field of medicine and pharmacy, especially in rehabilitation medicine (n=16). As a result of the study design, randomized controlled trials (n=20) were the most common, and chronic pain (n=9) was the most frequently targeted disease, followed by headache (n=7). Thirty-two studies suggested interventions and 20 studies used Upledger's 10-step protocol. The average duration of craniosacral therapy was 41 min per session, administered 1.4 times per week. Outcome measurements were analyzed and categorized with the examination procedure for the patient. Conclusions This is the first scoping review of craniosacral therapy in Korea, and we believe that our findings could support its utility as Chuna. In the future, more studies should be conducted to establish the evidence of clinical efficacy of craniosacral therapy and develop standard techniques in Korean medicine.

• Journal of Korea Entertainment Industry Association
• /
• v.14 no.6
• /
• pp.77-89
• /
• 2020

The film "Parasite" portrays Korea's history and its present in a space that clearly represents the real world's hierarchy as a vertical structure. It demonstrates the problems of an insurmountable reality and the elements of various conflicts occurring below the surface of Korean society through a complex mix of human emotions and relationships. The most realistic yet unrealistic characters cross boundaries between being victims and perpetrators, defamiliarizing ordinary scenes from everyday life through their small mistakes, strange obsessions, bizarre behavior, anxious psychology, and desperate struggles. This study analyzes the expression of the film "Parasite" through its characters with the belief that the film expresses director Bong Joon-ho's consistent cinematic philosophy of taking reality beyond the traditional rules of film genres. By doing so, Bong creates a feature of the expression that shifts genres as the characters' personalities amplify related behaviors, conflicts and questions, and that this is the core of the unique nuance and distinct humor of this film. In addition, the personalities of the characters interact with all the film's elements (cinematic techniques, space, props, etc.), evoking effects of various meanings, which are transmitted through the actors'images and acting. In this respect, the study analyzes how the actors were cast in order to realistically reproduce the characters of the actors, how their acting was harmonized with the film's elements, and its features as well as how they were expressed.

• KIPS Transactions on Computer and Communication Systems
• /
• v.11 no.11
• /
• pp.381-394
• /
• 2022

Recently, due to the personalization and customization of data, Internet-based services have increased requirements for real-time processing, such as real-time AI inference and data analysis, which must be handled immediately according to the user's situation or requirement. Real-time tasks have a set deadline from the start of each task to the return of the results, and the guarantee of the deadline is directly linked to the quality of the services. However, traditional container systems are limited in operating real-time tasks because they do not provide the ability to allocate and manage deadlines for tasks executed in containers. In addition, tasks such as AI inference and data analysis basically utilize graphical processing units (GPU), which typically have performance impacts on each other because performance isolation is not provided between containers. And the resource usage of the node alone cannot determine the deadline guarantee rate of each container or whether to deploy a new real-time container. In this paper, we propose a monitoring technique for tracking and managing the execution status of deadlines and real-time GPU tasks in containers to support real-time processing of GPU tasks running on containers, and a node list management technique for container placement on appropriate nodes to ensure deadlines. Furthermore, we demonstrate from experiments that the proposed technique has a very small impact on the system.

• Journal of Bio-Environment Control
• /
• v.31 no.3
• /
• pp.152-162
• /
• 2022

This study developed simulation model for predicting the greenhouse interior environment using artificial intelligence machine learning techniques. Various methods have been studied to predict the internal environment of the greenhouse system. But the traditional simulation analysis method has a problem of low precision due to extraneous variables. In order to solve this problem, we developed a model for predicting the temperature inside the greenhouse using machine learning. Machine learning models are developed through data collection, characteristic analysis, and learning, and the accuracy of the model varies greatly depending on parameters and learning methods. Therefore, an optimal model derivation method according to data characteristics is required. As a result of the model development, the model accuracy increased as the parameters of the hidden unit increased. Optimal model was derived from the GRU algorithm and hidden unit 6 (r² = 0.9848 and RMSE = 0.5857℃). Through this study, it was confirmed that it is possible to develop a predictive model for the temperature inside the greenhouse using data outside the greenhouse. In addition, it was confirmed that application and comparative analysis were necessary for various greenhouse data. It is necessary that research for development environmental control system by improving the developed model to the forecasting stage.

• Journal of Intelligence and Information Systems
• /
• v.28 no.4
• /
• pp.347-364
• /
• 2022

Fraudulent companies or sellers strategically manipulate reviews to influence customers' purchase decisions; therefore, the reliability of reviews has become crucial for customer decision-making. Since customers increasingly rely on online reviews to search for more detailed information about products or services before purchasing, many researchers focus on detecting manipulated reviews. However, the main problem in detecting manipulated reviews is the difficulties with obtaining data with manipulated reviews to utilize machine learning techniques with sufficient data. Also, the number of manipulated reviews is insufficient compared with the number of non-manipulated reviews, so the class imbalance problem occurs. The class with fewer examples is under-represented and can hamper a model's accuracy, so machine learning methods suffer from the class imbalance problem and solving the class imbalance problem is important to build an accurate model for detecting manipulated reviews. Thus, we propose an OpenAI-based reviews generation model to solve the manipulated reviews imbalance problem, thereby enhancing the accuracy of manipulated reviews detection. In this research, we applied the novel autoregressive language model - GPT-3 to generate reviews based on manipulated reviews. Moreover, we found that applying GPT-3 model for oversampling manipulated reviews can recover a satisfactory portion of performance losses and shows better performance in classification (logit, decision tree, neural networks) than traditional oversampling models such as random oversampling and SMOTE.

• Journal of Conservation Science
• /
• v.38 no.3
• /
• pp.234-242
• /
• 2022

The study aimed to investigate the split casting method based on the recreation of the iron-seated Buddha (ISB) statue (number 1971) in the Chuncheon Museum. The statue was designed using three-dimensional scan data and reduced to half-size. Using the existing research results, the ISB statue was created by mold production and split casting. The mold was prepared by mixing sand and clay at a ratio of 3:4 and 1:3 on the outside and inside, respectively, and then casting was done. Various casting defects were observed in the ISB casting and similar shapes were seen. The casting defects included veining or finning, misrun, open or external shrinkage, surface or subsurface blowholes, surface pinholes, and shift. The microstructures were identified as branch-shaped dendrite and pearlite organizations, and black graphite was observed between the cementite organizations. The study findings may be relevant in exploring traditional casting and manufacturing techniques of ISB and may aid in the production of the original form of ISB.

• Knowledge Management Research
• /
• v.23 no.2
• /
• pp.277-299
• /
• 2022

The massive card transaction data generated in the tourism industry has become an important resource that implies tourist consumption behaviors and patterns. Based on the transaction data, developing a smart service system becomes one of major goals in both tourism businesses and knowledge management system developer communities. However, the lack of rating scores, which is the basis of traditional recommendation techniques, makes it hard for system designers to evaluate a learning process. In addition, other auxiliary factors such as temporal, spatial, and demographic information are needed to increase the performance of a recommendation system; but, gathering those are not easy in the card transaction context. In this paper, we introduce CTDDTR, a novel approach using card transaction data to recommend tourism services. It consists of two main components: i) Temporal preference Embedding (TE) represents tourist groups and services into vectors through Doc2Vec. And ii) Deep tourism Recommendation (DR) integrates the vectors and the auxiliary factors from a tourism RDF (resource description framework) through MLP (multi-layer perceptron) to provide services to tourist groups. In addition, we adopt RFM analysis from the field of knowledge management to generate explicit feedback (i.e., rating scores) used in the DR part. To evaluate CTDDTR, the card transactions data that happened over eight years on Jeju island is used. Experimental results demonstrate that the proposed method is more positive in effectiveness and efficacies.

• Journal of Intelligence and Information Systems
• /
• v.29 no.3
• /
• pp.249-265
• /
• 2023

Recently, the satellite industry has been paying attention to the private-led 'New Space' paradigm, which is a departure from the traditional government-led industry. The space industry, which is considered to be the next food industry, is still receiving relatively little attention in Korea compared to the global market. Therefore, the purpose of this study is to explore future signals that can help determine the market entry strategies of private companies in the domestic satellite industry. To this end, this study utilizes the theoretical background of future signal theory and the Keyword Portfolio Map method to analyze keyword potential in patent document data based on keyword growth rate and keyword occurrence frequency. In addition, news data was collected to categorize future signals into first symptom and early information, respectively. This is utilized as an interpretive indicator of how the keywords reveal their actual potential outside of patent documents. This study describes the process of data collection and analysis to explore future signals and traces the evolution of each keyword in the collected documents from a weak signal to a strong signal by specifically visualizing how it can be used through the visualization of keyword maps. The process of this research can contribute to the methodological contribution and expansion of the scope of existing research on future signals, and the results can contribute to the establishment of new industry planning and research directions in the satellite industry.

• Journal of Service Research and Studies
• /
• v.13 no.1
• /
• pp.26-47
• /
• 2023

In the age of digital media transformation, the rapid rise of social media has changed the paradigm of traditional marketing techniques by leveraging the influence of influencers. However, the influence of influencers cannot be freed from ethical issues that arise as individuals, so virtual influencers are emerging as a countermeasure. This study is a study on how to increase the influencer effect of virtual models with a focus on the MZ generation in medical service. This study investigated whether respondents in their 40s or younger were aware of 'Rosy', a virtual influencer, and then conducted a survey on those who recognized 'Rosy'. As a result of this study, first, both cognitive and emotional motivation had a positive influence on fanship and attractiveness for virtual influencer. In addition, it was found that there was a difference in follow motive according to gender. Second, in order to lead to the intention of visiting hospitals, which is the medical service industry, only the cognitive motives with useful and reliable information and useful information for the virtual influencer were found to be significant in intention to visit.

• Asia-pacific Journal of Multimedia Services Convergent with Art, Humanities, and Sociology
• /
• v.6 no.7
• /
• pp.427-437
• /
• 2016

This study has the goal of analyzing the techniques and characteristics of urban development, after additionally constructing the high-speed railway in Japan's Kyushu district and building a new railway station to enable the existing traditional stations accommodate with the high-speed railway. Such analysis is made in order to draw the conclusion of its intended (designed) meaning and attributes and to further research on finding an applicable urban development method in the domestic railway station development. The object of this study includes examples of stations renewed within the five years when Shinkansen in the Kyushu district was extended or stations which are in process of development such as Hakata station, Kumamoto station, and Kagoshima-chuo station. From the analysis of this study, the strategies are as follows.; active connecting both geographical location and function of Station, re-establishment of relation with city center and Station, establishment of close linking system for both tourist spot development, methods of Shinkansen line construction and extension a development opposite site of railway, securing the living population from high density & Mixed use development of Station Building.