• Proceedings of the Korean Vacuum Society Conference
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• 한국진공학회 2013년도 제45회 하계 정기학술대회 초록집
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• pp.277.1-277.1
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• 2013

Molecular diagnostics consists of three processes, which are a sample pretreatment, a nucleic acid amplification, and an amplicon detection. Among three components, sample pretreatment is an important process in that it can increase the limit of detection by purifying nucleic acid in biological sample from contaminants that may interfere with the downstream genetic analysis such as nucleic acid amplification and detection. To achieve point-of-care virus detection system, the sample pretreatment process needs to be simple, rapid, and automatic. However, the commercial RNA extraction kits such as Rneasy (Qiagen) or MagnaPure (Roche) kit are highly labor-intensive and time-consuming due to numerous manual steps, and so it is not adequate for the on-site sample preparation. Herein, we have developed a rotary microfluidic system to extract and purify the RNA without necessity of external mechanical syringe pumps to allow flow control using microfluidic technology. We designed three reservoirs for sample, washing buffer, and elution buffer which were connected with different dimensional microfluidic channels. By controlling RPM, we could dispense a RNA sample solution, a washing buffer, and an elution buffer successively, so that the RNA was captured in the sol-gel solid phase, purified, and eluted in the downstream. Such a novel rotary sample preparation system eliminates some complicated hardwares and human intervention providing the opportunity to construct a fully integrated genetic analysis microsystem.

• Horticultural Science & Technology
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• 제19권2호
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• pp.179-185
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• 2001

Throughout the world, physical and chemical analyses of horticultural substrates are carried out in many different ways at the different laboratories. In Europe, standardization in properties and analytical methods of horticultural substrates has been a topic over the last decades. As a result, the CEN methods as European standard methods for the physical and chemical analyses were introduced and the final draft was reported in 1999 by CEN(Committee for European Standardization). Dry matter and moisture content are analyzed after drying samples at $103^{\circ}C$. Laboratory compacted bulk density is analyzed by determining the weight of sample compacted in the test cylinder with constant volume. Dry bulk density, particle density, total pore space, water volume, air volume and volume shrinkage are determined by saturating, draining and drying the sample using double rings and a sand suction table. pH and EC are analyzed by 1:5(sample:distilled water) extraction method on the basis of volume. Organic matter and ash content are determined after drying and combusting the samples. Now, CEN methods are being regarded almost as European standard methods. Further study needs to be carried out for universal applicability of the CEN methods to all the substrates.

• Journal of Korea Multimedia Society
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• 제6권2호
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• pp.267-275
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• 2003

The development of the mobile communication has been enlarged gradually and has been changed voice centered services into data centered ones supporting Internet to provide various kinds of mobile internet services. Researches for data transmission have been achieved actively lot the effective approachment of web in the mobile terminal. The users using mobile communication are increasing for its easy handcarried and movement and the information in internet based upon wire communication has been changed into mobile communication fast. The development of mobile internet requires various mobile contents using mobile internet at any time and at any place due to rapid enhance of network capacity and mobile internet according to network expansion. To accept these needs, there are many difficult problems that contents must be remade according to various terminal features and the develoument costs much. To solve these problems, this paper has the pun)me that contents of Web documents are changed and processed through XML palter and design new mobile contents system, providing mobile services rapidly and obtaining the charge reduction result with the enhance of contents development to the shortening of a development Period.

• Journal of Korea Multimedia Society
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• 제19권8호
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• pp.1424-1432
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• 2016

A person often needs to visit a facility that have not been visited before. In this case, it is necessary to easily identify the building in which the facility is located. Indoor navigation is also important, as the person may get lost due to the complex structure of buildings. To solve these problems, this paper presents a mobile application which provides a user with indoor place information and indoor navigation. A user is requested to take a photograph of a building of interest or of the current location. Then, the proposed application identifies the building of interest or the current location of the user by utilizing an image matching technique. For fast matching, database filtering by using GPS/magnetometer data and pre-extraction of features for images in the database are utilized. In case of indoor navigation, the application provides the actual images of check points as well as the moving direction. Simulation results show that the proposed system successfully identifies the location of users and provides place information and indoor navigation.

• Journal of Korean Society of Industrial and Systems Engineering
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• 제44권3호
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• pp.98-105
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• 2021

The sensory stimulation of a cosmetic product has been deemed to be an ancillary aspect until a decade ago. That point of view has drastically changed on different levels in just a decade. Nowadays cosmetic formulators should unavoidably meet the needs of consumers who want sensory satisfaction, although they do not have much time for new product development. The selection of new products from candidate products largely depend on the panel of human sensory experts. As new product development cycle time decreases, the formulators wanted to find systematic tools that are required to filter candidate products into a short list. Traditional statistical analysis on most physical property tests for the products including tribology tests and rheology tests, do not give any sound foundation for filtering candidate products. In this paper, we suggest a deep learning-based analysis method to identify hand cream products by raw electric signals from tribological sliding test. We compare the result of the deep learning-based method using raw data as input with the results of several machine learning-based analysis methods using manually extracted features as input. Among them, ResNet that is a deep learning model proved to be the best method to identify hand cream used in the test. According to our search in the scientific reported papers, this is the first attempt for predicting test cosmetic product with only raw time-series friction data without any manual feature extraction. Automatic product identification capability without manually extracted features can be used to narrow down the list of the newly developed candidate products.

• Journal of the Korea Society of Computer and Information
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• 제26권11호
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• pp.201-208
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• 2021

The purpose of this study is to investigate factors affecting unmet medical care in elderly hypertensive patients. The purpose of this study was to understand the reasons for unmet medical care in elderly hypertensive patients over 65 years of age and to identify the characteristics of each type to improve the medical use system and to contribute to policy making so that unmet medical care does not occur. Using data from the 7th period of the National Health and Nutrition Examination Survey (2016, 2017), 23 sample households were selected using the phylogenetic extraction method among appropriate households and analyzed using the SPSS 18.0 Program. As a result of the study, the unmet medical care of those who had suicidal thoughts compared to those who had not had suicidal thoughts in the past year, when females were higher than males, had worse subjective health status, those who did not subscribe than those who had private insurance, and those who had smoked in the past year. The experience rate was high. This is considered to be able to contribute to improving the medical service system and making policy decisions so that unmet medical care does not occur in the future.

• The Journal of the Korea institute of electronic communication sciences
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• 제14권5호
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• pp.969-976
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• 2019

A lightweight artificial intelligence hardware has made great strides in many application areas. In general, a lightweight artificial intelligence system consist of lightweight artificial intelligence engine and preprocessor including feature selection, generation, extraction, and normalization. In order to achieve optimal performance in broad range of applications, lightweight artificial intelligence system needs to choose a good preprocessing function and set their respective hyper-parameters. This paper proposes a unified framework for a lightweight artificial intelligence system and utilization method for finding models with optimal performance to use on a given dataset. The proposed unified framework can easily generate a model combined with preprocessing functions and lightweight artificial intelligence engine. In performance evaluation using handwritten image dataset and fall detection dataset measured with inertial sensor, the proposed unified framework showed building optimal artificial intelligence models with over 90% test accuracy.

• Journal of Information Technology Services
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• 제21권2호
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• pp.109-126
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• 2022

The number and variety of products and services offered by companies have increased dramatically, providing customers with more choices to meet their needs. As a solution to this information overload problem, the provision of tailored services to individuals has become increasingly important, and the personalized recommender systems have been widely studied and used in both academia and industry. Existing recommender systems face important problems in practical applications. The most important problem is that it cannot clearly explain why it recommends these products. In recent years, some researchers have found that the explanation of recommender systems may be very useful. As a result, users are generally increasing conversion rates, satisfaction, and trust in the recommender system if it is explained why those particular items are recommended. Therefore, this study presents a methodology of providing an explanatory function of a recommender system using a review text left by a user. The basic idea is not to use all of the user's reviews, but to provide them in a summarized form using only reviews left by similar users or neighbors involved in recommending the item as an explanation when providing the recommended item to the user. To achieve this research goal, this study aims to provide a product recommendation list using user-based collaborative filtering techniques, combine reviews left by neighboring users with each product to build a model that combines text summary methods among deep learning-based natural language processing methods. Using the IMDb movie database, text reviews of all target user neighbors' movies are collected and summarized to present descriptions of recommended movies. There are several text summary methods, but this study aims to evaluate whether the review summary is well performed by training the Sequence-to-sequence+attention model, which is a representative generation summary method, and the BertSum model, which is an extraction summary model.

• Smart Structures and Systems
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• 제30권1호
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• pp.75-88
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• 2022

Engineering structures in operation essentially belong to time-varying or nonlinear structures and the resultant response signals are usually non-stationary. For such time-varying structures, it is of great importance to extract time-dependent dynamic parameters from non-stationary response signals, which benefits structural health monitoring, safety assessment and vibration control. However, various traditional signal processing methods are unable to extract the embedded meaningful information. As a newly developed technique, variational mode decomposition (VMD) shows its superiority on signal decomposition, however, it still suffers two main problems. The foremost problem is that the number of modal components is required to be defined in advance. Another problem needs to be addressed is that VMD cannot effectively separate non-stationary signals composed of closely spaced or overlapped modes. As such, a new method named generalized adaptive variational modal decomposition (GAVMD) is proposed. In this new method, the number of component signals is adaptively estimated by an index of mean frequency, while the generalized demodulation algorithm is introduced to yield a generalized VMD that can decompose mode overlapped signals successfully. After that, synchrosqueezing wavelet transform (SWT) is applied to extract instantaneous frequencies (IFs) of the decomposed mono-component signals. To verify the validity and accuracy of the proposed method, three numerical examples and a steel cable with time-varying tension force are investigated. The results demonstrate that the proposed GAVMD method can decompose the multi-component signal with overlapped modes well and its combination with SWT enables a successful IF extraction of each individual component.

• The Journal of Korean Medicine
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• 제43권2호
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• pp.75-91
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• 2022

Objectives: The purpose of this overview was to summarize the evidence regarding the effectiveness of Cognitive Behavioral Therapy (CBT) for sleep disorders through systematic reviews (SRs) and meta-analyses (MAs). Methods: An overview of systematic review was conducted according to the study protocol (reviewregistry1320). A comprehensive literature search was performed using three databases (Pubmed, Cochrane Central Register of Controlled Trials, and Web of Science) and three Korean databases (KoreaMed, KMbase, and ScienceON). Final studies were selected by three authors according to inclusion and exclusion criteria, and data needed for analysis were extracted by a pre-planned extraction framework. Methodological quality of systematic review was assessed using the 'Assessment of multiple systematic reviews 2 (AMSTAR2)'. Results: Fourteen SRs and MAs were included, of which eleven SRs were performed MAs. Twelve studies studied insomnia among sleep disorders, and the rest are nightmares and sleep disturbances with PTSD. Ten studies reported the effect of CBT on sleep disorders measured by insomnia severity index (ISI) and sleep onset latency (SOL), and all reported a significant improvement effect. Eight studies reported the effect of CBT on sleep disorders measured by wake time after sleep onset (WASO), and seven studies reported a significant improvement effect. The methodological quality of the studies evaluated with AMSTAR 2 was mainly low or very low because of omission of protocol registration and excluded study list. Conclusions: Practical guidelines and studies show that CBT is effective for sleep disorders, but access to CBT needs to be improved.