• Journal of Microbiology and Biotechnology
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• v.32 no.5
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• pp.657-662
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• 2022

Glycosyltransferase (GT)-specific degenerate PCR screening followed by in silico sequence analyses of the target clone was used to isolate a member of family1 GT-encoding genes from the established fosmid libraries of soil actinomycetes Micromonospora echinospora ATCC 27932. A recombinant MeUGT1 was heterologously expressed as a His-tagged protein in E. coli, and its enzymatic reaction with semi-synthetic phenoxodiol isoflavene (as a glycosyl acceptor) and uridine diphosphate-glucose (as a glycosyl donor) created two different glycol-attached products, thus revealing that MeUGT1 functions as an isoflavonoid glycosyltransferase with regional flexibility. Chromatographic separation of product glycosides followed by the instrumental analyses, clearly confirmed these previously unprecedented glycosides as phenoxodiol-4'-α-O-glucoside and phenoxodiol-7-α-O-glucoside, respectively. The antioxidant activities of the above glycosides are almost the same as that of parental phenoxodiol, whereas their anti-proliferative activities are all superior to that of cisplatin (the most common platinum chemotherapy drug) against two human carcinoma cells, ovarian SKOV-3 and prostate DU-145. In addition, they are more water-soluble than their parental aglycone, as well as remaining intractable to the simulated in vitro digestion test, hence demonstrating the pharmacological potential for the enhanced bio-accessibility of phenoxodiol glycosides. This is the first report on the microbial enzymatic biosynthesis of phenoxodiol glucosides.

• The Journal of Information Systems
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• v.32 no.2
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• pp.87-108
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• 2023

Purpose The main purpose of this study is to improve fake news detection performance by using video information to overcome the limitations of extant text- and image-oriented studies that do not reflect the latest news consumption trend. Design/methodology/approach This study collected video clips and related information including news scripts, speakers' facial expression, and video metadata from YouTube to develop fake news detection model. Based on the collected data, seven combinations of related information (i.e. scripts, video metadata, facial expression, scripts and video metadata, scripts and facial expression, and scripts, video metadata, and facial expression) were used as an input for taining and evaluation. The input data was analyzed using six models such as support vector machine and deep neural network. The area under the curve(AUC) was used to evaluate the performance of classification model. Findings The results showed that the ACU and accuracy values of three features combination (scripts, video metadata, and facial expression) were the highest in logistic regression, naïve bayes, and deep neural network models. This result implied that the fake news detection could be improved by using video information(video metadata and facial expression). Sample size of this study was relatively small. The generalizablity of the results would be enhanced with a larger sample size.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.46 no.4
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• pp.173-180
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• 2023

Smart factory companies are installing various sensors in production facilities and collecting field data. However, there are relatively few companies that actively utilize collected data, academic research using field data is actively underway. This study seeks to develop a model that detects anomalies in the process by analyzing spindle power data from a company that processes shafts used in automobile throttle valves. Since the data collected during machining processing is time series data, the model was developed through unsupervised learning by applying the Holt Winters technique and various deep learning algorithms such as RNN, LSTM, GRU, BiRNN, BiLSTM, and BiGRU. To evaluate each model, the difference between predicted and actual values was compared using MSE and RMSE. The BiLSTM model showed the optimal results based on RMSE. In order to diagnose abnormalities in the developed model, the critical point was set using statistical techniques in consultation with experts in the field and verified. By collecting and preprocessing real-world data and developing a model, this study serves as a case study of utilizing time-series data in small and medium-sized enterprises.

• Proceedings of the Korea Contents Association Conference
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• 2003.05a
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• pp.67-73
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• 2003

The cyber-education is fully recognized and proliferated such as to Internet language centers or virtual universities, and so on. However, the acquisition of e-learning tools as well as the construction of educational contents are quite difficult tasks. Therefore, in this study, important information for the acquisition of hardwares such as multimedia editing tools, servers, educational facilities is suggested, and the critical success factors for the acquisition of cyber educational solution softwares such as authoring tools and loaming management systems are proposed.

• Journal of Intelligence and Information Systems
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• v.3 no.1
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• pp.69-81
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• 1997

In this paper, first we propose an architecture of fuzzy neural networks with triangular fuzzy weights. The proposed fuzzy neural network can handle fuzzy input vectors. In both cases, outputs from the fuzzy network are fuzzy vectors. The input-output relation of each unit of the fuzzy neural network is defined by the extention principle of Zadeh. Also we define a cost function for the level sets(i. e., $\alpha$-cuts)of fuzzy outputs and fuzzy targets. Then we derive a learning algorithm from the cost function for adjusting three parameters of each triangular fuzzy weight. Finally, we illustrate our a, pp.oach by computer simulation examples.

• 한국HCI학회:학술대회논문집
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• 2007.02a
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• pp.612-615
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• 2007

This research studies the Virtual Reality simulation of Newton's physics law on rigid body type of objects for physics learning. With network support, collaborative interaction is enabled so that people from different places can interact with the same set of objects in Collaborative Virtual Environment. The taxonomy of the interaction in different levels of collaboration is described as: distinct objects and same object, in which there are same object - sequentially, same object - concurrently - same attribute, and same object - concurrently - distinct attributes. The case studies are the interaction of users in two cases: destroying and creating a set of arranged rigid bodies. We identify a specific type of application for contents authoring with modeling systems integrated with real-time physics and implemented in VR system. In our application called Virtual Dollhouse, users can observe physics law while constructing a dollhouse using existing building blocks, under gravity effects.

• 제어로봇시스템학회:학술대회논문집
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• 1992.10b
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• pp.61-64
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• 1992

In this paper, a visual pattern recognition system is proposed, which can recognize both a pattern and its location. This system, referred to as the expanded neocognitron, has the following capabilities: (1) A higher performance in extraction of features, and (2) A new capability for recognizing the locations of patterns. This system adopts the learning and recognizing mechanism of the neocognitron. First, the ability to classify pattern is enhanced by improving the mechanisms of feature extraction and learning algorithm. Second, the function of detecting the location of each pattern is realized by developing an architecture which does not reduce structure, i.e., the unit density is constant all the way from the input stage to the output stage.

• Journal of Engineering Education Research
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• v.17 no.3
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• pp.34-41
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• 2014

In distance education, use of proper software tools can greatly enhance student's attention and learning efficiency. In such software tools, offering diverse multimedia information is one of the most critical factors. However, integration and synchronization of the various media types has been relatively difficult parts of implementation. This paper proposes a prototype system that uses a metafile and event handling mechanism for the uniform treatment of various media types. This event-level integration and synchronization of multimedia makes the implementation relatively simple. With this approach, instructor's behaviors are automatically recorded, and the instructors can freely choose and show any type of multimedia contents while lecturing. Current commercial or non-commercial lecture management systems could incorporate this approach, so that the distance education market could be expanded with richer multimedia contents.

• The Journal of the Acoustical Society of Korea
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• v.17 no.1E
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• pp.36-43
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• 1998

A fuzzy logic filter is constructed from a set of fuzzy IF-THEN rules which change adaptively to minimize some criterion function as new information becomes available. This paper generalizes the fuzzy logic filter and it's adaptive filtering algorithm to include complex parameters and complex signals. Using the complex Stone-Weierstrass theorem, we prove that linear combinations of the fuzzy basis functions are capable of uniformly approximating and complex continuous function on a compact set to arbitrary accuracy. Based on the fuzzy basis function representations, a complex orthogonal least-squares (COLS) learning algorithm is developed for designing fuzzy systems based on given input-output pairs. Also, we propose an adaptive algorithm based on LMS which adjust simultaneously filter parameters and the parameter of the membership function which characterize the fuzzy concepts in the IF-THEN rules. The modeling of a nonlinear communications channel based on a complex fuzzy is used to demonstrate the effectiveness of these algorithm.

• 제어로봇시스템학회:학술대회논문집
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• 2001.10a
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• pp.43.2-43
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• 2001

In this paper, we consider the problems of the evolutionary designed neural networks structures by genetic algorithm. Neural networks has been applied to various application fields since back-propagation algorithm was proposed, e.g. function approximation, pattern or character recognition and so on. However, one of difficulties to use the neural networks. It is how to design the structure of the neural network. Researchers and users design networks structures and training parameters such as learning rate and momentum rate and so on, by trial and error based on their experiences. In the case of designing large scales neural networks, it is very hard work for manually design by try and error. For this difficulty, various structural learning algorithms have been proposed. Especially, the technique of using genetic algorithm for networks structures design has been ...