• Journal of Oriental Neuropsychiatry
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• v.33 no.3
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• pp.301-316
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• 2022

Objectives: To compare Korean medicine (KM) and traditional Chinese medicine (TCM) psychotherapy for anxiety. Methods: Databases including MEDLINE (via PubMed), EMBASE (via Elsevier), Cochrane Central Register of Controlled Trials, China National Knowledge Infrastructure, and Oriental Medicine Advanced Searching Integrated System were comprehensively searched. Prospective clinical studies on KM or TCM psychotherapy for patients with anxiety disorder or individuals with elevated anxiety levels published up to August 3, 2022 were reviewed. Psychotherapy was divided into counselling, art therapy, and meditation according to its characteristics. Results: A total of 12 clinical studies were reviewed, including nine randomized controlled trials. The most common disorder investigated was post-traumatic stress disorder. Ten studies used TCM psychotherapy and two used KM psychotherapy. As for differences between TCM psychotherapy and KM psychotherapy, TCM psychotherapy utilized pattern identification in the procedure more actively than KM psychotherapy. In addition, some TCM studies have attempted to directly converge Western psychotherapy (i.e., hypnosis) and Eastern psychotherapy (i.e., Taoin qigong therapy). In the case of KM psychotherapy, there was an attempt to incorporate psychotherapy with Sasang constitutional medicine. Reported effects of TCM psychotherapy and KM psychotherapy on anxiety were positive. Conclusions: Research status of KM psychotherapy and TCM psychotherapy for anxiety was investigated, revealing some of their characteristics, commonalities, and differences. Findings of this review have the potential to provide a clue to the development of conventional KM psychotherapy and new medical technology for KM psychotherapy.

• The Journal of Pediatrics of Korean Medicine
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• v.37 no.1
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• pp.15-44
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• 2023

Objectives The purpose of this study is to analyze the types of childhood simple obesity and suggest clinical symptoms, treatment principles, and traditional Chinese medicine (TCM) treatments for each type. Methods All kinds of literature published by the China National Knowledge Infrastructure (CNKI) up to August 20, 2022 were analyzed. We extracted information about types of childhood simple obesity, relevant clinical symptoms, treatment principles and TCM treatments. Results 25 studies were included. Spleen deficiency with dampness obstruction, gastrointestinal dampness-heat, internal excess of phlegm-dampness were the most reported. Spleen deficiency with dampness obstruction has symptoms of powerless, heavy limbs, pale tongue, teeth-marked tongue, sunken and slippery pulse. As a treatment, herbal medicine (HM) like modified Banggihwanggitang and acupoint like Joksamri were mainly reported. Gastrointestinal dampness-heat has symptoms of thirst, constipation, edacity, rapid hungering, heavy limbs, red tongue, slippery and rapid pulse. HM like Modified Xiehuangsan to clear heat was mainly reported. Internal excess of phlegm-dampness has symptoms of heavy limbs, lack of strength, tongue with white slimy fur, slippery pulse. Modified Ijintang to dry dampness to resolve phlegm was mainly reported. Conclusions This study analyzed types of pattern, clinical symptoms, treatment principles, and TCM treatments of childhood simple obesity. Based on this study, it is necessary to derive a standardized dialectical information that reflects the domestic situation.

• Journal of Korean Society of Archives and Records Management
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• v.20 no.2
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• pp.107-113
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• 2020

This case focuses on the Seoul Credit Guarantee Foundation, which applied RFID technology as a record management system for efficient record management by identifying the characteristics of the agency's work that requires the management of large and similar nonelectronic records. When issuing RFID tags in conjunction with the business system, the records management system automatically obtains metadata from the system and secures it as a list, and records management personnel actively use it as the basis for overall records management tasks. To that end, the company reorganized its business processes, designed functions that reflect its unique business, and established infrastructure. These resulted in easier identification of the output and holding volume of accurate records, and work efficiency. Finally, people in charge of the work increased their awareness of records management.

• Journal of Intelligence and Information Systems
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• v.27 no.3
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• pp.57-73
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• 2021

Maintenance and prevention of failure through anomaly detection of ICT infrastructure is becoming important. System monitoring data is multidimensional time series data. When we deal with multidimensional time series data, we have difficulty in considering both characteristics of multidimensional data and characteristics of time series data. When dealing with multidimensional data, correlation between variables should be considered. Existing methods such as probability and linear base, distance base, etc. are degraded due to limitations called the curse of dimensions. In addition, time series data is preprocessed by applying sliding window technique and time series decomposition for self-correlation analysis. These techniques are the cause of increasing the dimension of data, so it is necessary to supplement them. The anomaly detection field is an old research field, and statistical methods and regression analysis were used in the early days. Currently, there are active studies to apply machine learning and artificial neural network technology to this field. Statistically based methods are difficult to apply when data is non-homogeneous, and do not detect local outliers well. The regression analysis method compares the predictive value and the actual value after learning the regression formula based on the parametric statistics and it detects abnormality. Anomaly detection using regression analysis has the disadvantage that the performance is lowered when the model is not solid and the noise or outliers of the data are included. There is a restriction that learning data with noise or outliers should be used. The autoencoder using artificial neural networks is learned to output as similar as possible to input data. It has many advantages compared to existing probability and linear model, cluster analysis, and map learning. It can be applied to data that does not satisfy probability distribution or linear assumption. In addition, it is possible to learn non-mapping without label data for teaching. However, there is a limitation of local outlier identification of multidimensional data in anomaly detection, and there is a problem that the dimension of data is greatly increased due to the characteristics of time series data. In this study, we propose a CMAE (Conditional Multimodal Autoencoder) that enhances the performance of anomaly detection by considering local outliers and time series characteristics. First, we applied Multimodal Autoencoder (MAE) to improve the limitations of local outlier identification of multidimensional data. Multimodals are commonly used to learn different types of inputs, such as voice and image. The different modal shares the bottleneck effect of Autoencoder and it learns correlation. In addition, CAE (Conditional Autoencoder) was used to learn the characteristics of time series data effectively without increasing the dimension of data. In general, conditional input mainly uses category variables, but in this study, time was used as a condition to learn periodicity. The CMAE model proposed in this paper was verified by comparing with the Unimodal Autoencoder (UAE) and Multi-modal Autoencoder (MAE). The restoration performance of Autoencoder for 41 variables was confirmed in the proposed model and the comparison model. The restoration performance is different by variables, and the restoration is normally well operated because the loss value is small for Memory, Disk, and Network modals in all three Autoencoder models. The process modal did not show a significant difference in all three models, and the CPU modal showed excellent performance in CMAE. ROC curve was prepared for the evaluation of anomaly detection performance in the proposed model and the comparison model, and AUC, accuracy, precision, recall, and F1-score were compared. In all indicators, the performance was shown in the order of CMAE, MAE, and AE. Especially, the reproduction rate was 0.9828 for CMAE, which can be confirmed to detect almost most of the abnormalities. The accuracy of the model was also improved and 87.12%, and the F1-score was 0.8883, which is considered to be suitable for anomaly detection. In practical aspect, the proposed model has an additional advantage in addition to performance improvement. The use of techniques such as time series decomposition and sliding windows has the disadvantage of managing unnecessary procedures; and their dimensional increase can cause a decrease in the computational speed in inference.The proposed model has characteristics that are easy to apply to practical tasks such as inference speed and model management.

• Earthquakes and Structures
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• v.2 no.3
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• pp.207-232
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• 2011

The development of reliable earthquake mitigation plans and seismic risk management procedures can only be based on the establishment of comprehensive earthquake hazard and loss scenarios. Two cities, Grevena (Greece) and D$\ddot{u}$zce (Turkey), were used as case studies in order to apply a comprehensive methodology for the vulnerability and loss assessment of lifelines. The methodology has the following distinctive phases: detailed inventory, identification of the typology of each component and system, evaluation of the probabilistic seismic hazard, geotechnical zonation, ground response analysis and estimation of the spatial distribution of seismic motion for different seismic scenarios, vulnerability analysis of the exposed elements at risk. Estimating adequate earthquake scenarios for different mean return periods, and selecting appropriate vulnerability functions, expected damages of the water and waste water systems in D$\ddot{u}$zce and of the roadway network and waste water system of Grevena are estimated and discussed; comparisons with observed earthquake damages are also made in the case of D$\ddot{u}$zce, proving the reliability and the efficiency of the proposed methodology. The results of the present study constitute a sound basis for the development of efficient loss scenarios for lifelines and infrastructure facilities in seismic prone areas. The first part of this paper, concerning the estimation of the seismic ground motions, has been utilized in the companion paper by Kappos et al. (2010) in the same journal.

• Journal of the Korean Society of Hazard Mitigation
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• v.10 no.4
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• pp.63-68
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• 2010

Utility-Pipe Conduit is, Housing and city effectively accommodate what they absolutely need power, communications, gas, pipeline, water supply, drainage, energy facilities etc, according to expansion of urban infrastructure are derived, several ways to solve problems in, collection facilities in place are maintained and managed facility. If Utility-Pipe Conduit is damaged, as well as national security, because their impact on society as a whole, by introducing large vulnerability in the fire prevention activities and suppression measures and disaster for our situation by introducing measures, comprehensive analysis of the fire risk, it shall establish fire prevention activities and suppression through analysis of Utility-Pipe Conduit design, institutional issues, the problem of fire protection facilities, fire spread phenomenon etc. Because of Utility-Pipe Conduit is an enclosed place, so incomplete combustion due to lack of oxygen supply that there are problem such dark smoke, carbon monoxide etc, toxic combustion products and heat generation and visual impairment is an issue difficult to enter. As well as fire prevention activities, the fire In light of the particularity of the under ground than above ground fire, so this phenomenon is weak fire fighting that fire to become effective fire fighting tactics, basically it is necessary difficulty softening, non-burn softening and prevent combustion expansion of the cable is installed on the Utility-Pipe Conduit, having to considering the specificity of the response command system and relevant organizations to establish an on-site, Structural identification and other information gathering required to record of Response agencies, keep air conditioning system 24 hours and strengthening Virtual Total Training of Response agen

• Journal of the Korea Academia-Industrial cooperation Society
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• v.17 no.11
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• pp.716-723
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• 2016

A computerized information management system of road bridges as a national key infrastructure is needed to effectively collect data of the current status, improve the reliability of data, and use the results from the analysis of the accumulated data as fundamental resources for supporting the establishment of policies. The Internet-based Bridge Information System (BIS), including a database and geographic information systems (GIS), was designed, and the data items were comprised of essential information, such as GIS-based location coordinates, bridge condition grade information and so on. The BIS was developed to be connected with a related information system, and it is possible to make the current information of traffic volume, address and so on by adopting the GIS. To enhance the reliability of the information of current bridge status, it is also possible to improve the accuracy of data through an information verifying function to prevent entry errors. In addition, the BIS can easily support the establishment of policies offering various types of knowledge information that were available in the past based on an analysis of the accumulated data. The intuitive identification and analysis of the current status is to be feasible through a GIS screen. Improvement of the business efficiency and data accuracy and time-series information analysis are available by managing the information of current status through BIS. In the future, it is expected that BIS can be used effectively for the establishment of reasonable maintenance policies of the nation.

• Journal of Korea Water Resources Association
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• v.47 no.8
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• pp.671-684
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• 2014

Change point analysis is a efficient tool to understand the fundamental information in hydro-meteorological data such as rainfall, discharge, temperature etc. Especially, this fundamental information to change points to future rainfall data identified by reasonable detection skills can affect the prediction of flood and drought occurrence because well detected change points provide a key to resolve the non-stationary or inhomogeneous problem by climate change. Therefore, in this study, the comparative study to assess the performance of the 3 change point detection skills, cumulative sum (CUSUM) method, Bayesian change point (BCP) method, and segmentation by dynamic programming (DP) was performed. After assessment of the performance of the proposed detection skills using the 3 types of the synthetic series, the 2 reasonable detection skills were applied to the observed and future rainfall data at the 5 rainfall gauges in South Korea. Finally, it was suggested that BCP (with 0.9 posterior probability) could be best detection skill and DP could be reasonably recommended through the comparative study. Also it was suggested that BCP (with 0.9 posterior probability) and DP detection skills to find some change points could be reasonable at the North-eastern part in South Korea. In future, the results in this study can be efficiently used to resolve the non-stationary problems in hydrological modeling considering inhomogeneity or nonstationarity.

• Korean Journal of Plant Resources
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• v.31 no.1
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• pp.1-9
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• 2018

As a part of an infrastructure project on medicinal herb-based remedies, we conducted a phytohemical investigation of the 100% MeOH extract from the aerial part of Boehmeria quelpaertense; our findings resulted in the isolation of flavonoids (1-2), isoquercitrin (1) and hyperoside (2). The identification and structural elucidation of these compounds were based on $^1H$-, $^{13}C-NMR$, and LC ESI IT-TOF MS data. All the compounds isolated from this plant were reported for the first time. In this study, we examined the antioxidant activity of the 1 and 2 on the hydrogen peroxide ($H_2O_2$)-induced oxidative stress in a Rat Cardiomyoblast cell line (H9c2). The pretreatment of the flavonoids showed that it protects against $H_2O_2$-mediated cell death in the H9c2 cell line. Also, it decreases the intracellular reactive oxygen species (ROS) levels by the flavonoids in the $H_2O_2$-treated H9c2 cell line. These results showed that the 1 and 2 are a source of antioxidants. As a result, they might be helpful in preventing the progress of various oxidative stress mediated diseases, including myocardial infarction.

• International Journal of Internet, Broadcasting and Communication
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• v.12 no.2
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• pp.8-14
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• 2020

Recently, there was an increasing demand for an integrated access control system which is capable of user recognition, door control, and facility operations control for smart buildings automation. The market available door lock access control solutions need to be improved from the current level security of door locks operations where security is compromised when a password or digital keys are exposed to the strangers. At present, the access control system solution providers focusing on developing an automatic access control system using (RF) based technologies like bluetooth, WiFi, etc. All the existing automatic door access control technologies required an additional hardware interface and always vulnerable security threads. This paper proposes the user identification and authentication solution for automatic door lock control operations using camera based visible light communication (VLC) technology. This proposed approach use the cameras installed in building facility, user smart devices and IoT open source controller based LED light sensors installed in buildings infrastructure. The building facility installed IoT LED light sensors transmit the authorized user and facility information color grid code and the smart device camera decode the user informations and verify with stored user information then indicate the authentication status to the user and send authentication acknowledgement to facility door lock integrated camera to control the door lock operations. The camera based VLC receiver uses the artificial intelligence (AI) methods to decode VLC data to improve the VLC performance. This paper implements the testbed model using IoT open-source based LED light sensor with CCTV camera and user smartphone devices. The experiment results are verified with custom made convolutional neural network (CNN) based AI techniques for VLC deciding method on smart devices and PC based CCTV monitoring solutions. The archived experiment results confirm that proposed door access control solution is effective and robust for automatic door access control.