• Journal of Information Processing Systems
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• v.20 no.1
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• pp.105-115
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• 2024

The hybrid teaching approach of "MOOC + SPOC + Flipped Classroom" overcomes the constraints of time and space that are typically associated with traditional teaching methods, thus compensating for the shortcomings of traditional approaches. These changes in education are driven by the "Internet+" wave and the growing popularity of online teaching. The "MOOC + SPOC + Flipped Classroom" hybrid teaching mode can successfully compensate for the drawbacks of traditional teaching methods, thereby overcoming their restrictions. By defining relevant concepts, one can distill the key characteristics of the "MOOC + SPOC + Flipped Classroom" hybrid teaching mode. Formative assessment was employed to thoroughly evaluate the effectiveness of this teaching approach. By leveraging the advantages of massive open online course (MOOC), small private online course (SPOC), and flipped classroom, the "MOOC +SPOC + Flipped Classroom" teaching mode incorporates real-time student assessment through peer evaluation, computer-aided evaluation, and teacher evaluation. This mode promotes the simultaneous development of theoretical knowledge and practical skills, helping students to establish strong foundations while fostering their practical abilities. While the traditional teaching method remains fruitful, the convenience of today's network allows the teaching profession to continually evolve. The traditional teaching mode heavily relies on teachers, making it impossible to conduct lessons without them. However, the development of MOOC enables students to seek knowledge online from their preferred teachers, rather than solely relying on their assigned instructors.

• Journal of Advanced Navigation Technology
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• v.17 no.6
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• pp.804-809
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• 2013

The current state monitoring system at a semiconductor manufacturing process is based on the manually collected sensor data, which involves limitations when it comes to complex malfunction detection and real time monitoring. This study aims to design a situation recognition algorithm to form a network over time by creating a domain ontology and to suggest a system to provide users with services by generating events upon finding risk factors in the semiconductor process. To this end, a multiple sensor node for situational inference was designed and tested. As a result of the experiment, events to which the rule of time inference was applied occurred for the contents formed over time with regard to a quantity of collected data while the events that occurred with regard to malfunction and external time factors provided log data only.

• Journal of Intelligence and Information Systems
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• v.22 no.4
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• pp.177-192
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• 2016

Machine learning is a field of artificial intelligence. It refers to an area of computer science related to providing machines the ability to perform their own data analysis, decision making and forecasting. For example, one of the representative machine learning models is artificial neural network, which is a statistical learning algorithm inspired by the neural network structure of biology. In addition, there are other machine learning models such as decision tree model, naive bayes model and SVM(support vector machine) model. Among the machine learning models, we use SVM model in this study because it is mainly used for classification and regression analysis that fits well to our study. The core principle of SVM is to find a reasonable hyperplane that distinguishes different group in the data space. Given information about the data in any two groups, the SVM model judges to which group the new data belongs based on the hyperplane obtained from the given data set. Thus, the more the amount of meaningful data, the better the machine learning ability. In recent years, many financial experts have focused on machine learning, seeing the possibility of combining with machine learning and the financial field where vast amounts of financial data exist. Machine learning techniques have been proved to be powerful in describing the non-stationary and chaotic stock price dynamics. A lot of researches have been successfully conducted on forecasting of stock prices using machine learning algorithms. Recently, financial companies have begun to provide Robo-Advisor service, a compound word of Robot and Advisor, which can perform various financial tasks through advanced algorithms using rapidly changing huge amount of data. Robo-Adviser's main task is to advise the investors about the investor's personal investment propensity and to provide the service to manage the portfolio automatically. In this study, we propose a method of forecasting the Korean volatility index, VKOSPI, using the SVM model, which is one of the machine learning methods, and applying it to real option trading to increase the trading performance. VKOSPI is a measure of the future volatility of the KOSPI 200 index based on KOSPI 200 index option prices. VKOSPI is similar to the VIX index, which is based on S&P 500 option price in the United States. The Korea Exchange(KRX) calculates and announce the real-time VKOSPI index. VKOSPI is the same as the usual volatility and affects the option prices. The direction of VKOSPI and option prices show positive relation regardless of the option type (call and put options with various striking prices). If the volatility increases, all of the call and put option premium increases because the probability of the option's exercise possibility increases. The investor can know the rising value of the option price with respect to the volatility rising value in real time through Vega, a Black-Scholes's measurement index of an option's sensitivity to changes in the volatility. Therefore, accurate forecasting of VKOSPI movements is one of the important factors that can generate profit in option trading. In this study, we verified through real option data that the accurate forecast of VKOSPI is able to make a big profit in real option trading. To the best of our knowledge, there have been no studies on the idea of predicting the direction of VKOSPI based on machine learning and introducing the idea of applying it to actual option trading. In this study predicted daily VKOSPI changes through SVM model and then made intraday option strangle position, which gives profit as option prices reduce, only when VKOSPI is expected to decline during daytime. We analyzed the results and tested whether it is applicable to real option trading based on SVM's prediction. The results showed the prediction accuracy of VKOSPI was 57.83% on average, and the number of position entry times was 43.2 times, which is less than half of the benchmark (100 times). A small number of trading is an indicator of trading efficiency. In addition, the experiment proved that the trading performance was significantly higher than the benchmark.

• Journal of the Institute of Electronics Engineers of Korea TC
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• v.44 no.1
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• pp.54-61
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• 2007

In this paper, on-demand service streaming protocol for user-created contents in digital cable broadcasting environment is considered. In order to provide variety media contents service like UCC in digital cable broadcasting environment, the same service model as RVOD(Real Video on Demand) is required and the different interface for each broadcasting platform is needed in a current OCAP environment. Using return path based RTP, we separate existing VOD stream band into broadcasting and VOD stream band. In order to broaden On-demand service, consistent expansion of the infrastructure same as live broadcasting system is inefficient in the digital cable broadcasting environment. Using existing network protocol, the service which is insensitive to the infrastructure for VOD service becomes possible. Therefore we considered the analysis of the class of download available structure in the Set-Top-Box for RTP(Real-time Transport Protocol) and designing the decoding available streaming server for UCC transcoding and transmission in the receiver. Designing a efficient VOD service and system under the broadcasting environment gives a expansion of On-Demand service and more chance to upload and utilization of contents.

• Journal of the Institute of Electronics Engineers of Korea TC
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• v.46 no.8
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• pp.59-66
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• 2009

Recently, as the expectation about the IPTV (Internet Protocol TV) service quality is rapidly increased by the development of the national high-speed internet and TPS (the Triple Play Service : data + image + audio) service Therefore, the enactment of the national quality standards about the IPTV service quality guaranteeing the real time video quality of a subscriber and the international standards are hastily needed. This paper built a test bed with the network domain and the subscriber set-top box domain including the headend area and commercial network characteristic in order to test in the environment which is similar to the characteristic of the service business network. And by using the constructed environment, the characteristics required for SLA(service Level Agreement) of the IPTV service are presented as the quality test according to the service environment change.

• Structural Engineering and Mechanics
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• v.58 no.3
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• pp.459-473
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• 2016

Various vague and unstructured problems encountered the civil engineering/designers that persuaded by their experiences. One of these problems is the structural failure of the reinforced concrete (RC) building determination. Typically, using the traditional Limit state method is time consuming and complex in designing structures that are optimized in terms of one/many parameters. Recent research has revealed the Artificial Neural Networks potentiality in solving various real life problems. Thus, the current work employed the Multilayer Perceptron Feed-Forward Network (MLP-FFN) classifier to tackle the problem of predicting structural failure of multistoried reinforced concrete buildings via detecting the failure possibility of the multistoried RC building structure in the future. In order to evaluate the proposed method performance, a database of 257 multistoried buildings RC structures has been constructed by professional engineers, from which 150 RC structures were used. From the structural design, fifteen features have been extracted, where nine features of them have been selected to perform the classification process. Various performance measures have been calculated to evaluate the proposed model. The experimental results established satisfactory performance of the proposed model.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.35 no.7B
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• pp.1018-1033
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• 2010

Recently, as the use of mobile terminal is generalized, the needs of high-speed Internet mobile service is increased. Also users want to receive the multimedia contents what they want through the various terminals in anywhere, anytime via wired and wireless integrated environment. Therefore, various mechanisms that support the mobility are proposed. However, these mechanisms are difficult to support seamless mobility and QoS awareness on the mobile multicast environment. In this paper, we propose a QoS aware handover mechanism that is able to provide the high-quality and real-time services such as mobile IPTV in an integrated environment for these requests of users. Proposed mechanism manages the multicast admission control and multicast handover using the 2-layer multicast information management at the wired and wireless integrated network that extended the service guaranteed methods through the probing based admission control of the wired network to the wireless network based on PMIPv6. We present a performance evaluation results and features analyzed by the simulations using the ㎱-2.

• Journal of Digital Convergence
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• v.18 no.6
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• pp.109-120
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• 2020

The supply chain without digitization is just a series of discrete, siloed steps taken through marketing, product development, manufacturing, and logistics, and finally into the hands of the customer. Digitization brings down those walls, and the chain becomes a completely integrated network fully transparent to all the parties involved. The ulitimate goals of digitizatized supply chain management are velocity and visibility. This network will depend on a number of key technologies including integrated planning and execution systems, supply chain analytics, autonomous logistics, smart warehousing and factory, etc, enabling companies to react to disruptions in the supply chain, and even anticipate them, by fully modeling the network, creating "what-if" scenarios, and adjusting the supply chain in real time as conditions change. This paper presents a number of studies on digitalization of supply chains and provides a discussion on issues raised in the process of technology adoption. Implications of the study findings are also provided.

• Journal of the Institute of Electronics Engineers of Korea TC
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• v.43 no.11 s.353
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• pp.16-24
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• 2006

In this paper, we implement a U-healthcare system that can be applied to a service integration system. This system consists of a wireless network system a sensor module, and a integration server. The wireless network system collects data and the sensor module measures body fat, blood pressure, quantity of exercise, and SPO2. The server integrates user certification, security service and VOD service and collects user health information in real-time, and sends the data in case of emergency to a doctor or guardian.

• Journal of the Institute of Electronics and Information Engineers
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• v.49 no.9
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• pp.379-385
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• 2012

This paper suggests U-healthcare system for individual health management realizing the gateway, client, and Java-based network server by using the vital signal measuring system and android-based mobile platform. This study realized the vital signal measuring system based on the technology to measure the ECG, oxygen saturation, blood pressure, and respiration, etc. And all the information of measurement was transmitted to the mobile gateway using the 3-bite transmission protocol consisting of headers and data. The data transmitted to the mobile gateway was used to examine the mobile client's personal health indexes through the network server. This paper realized and tested the android-based gateway, client, and the broadcasting network server and verified their validity with simulations and actual humans. As a result, the U-healthcare system suggested was proved to be effective in managing each individual's health from short distance and long distance. And it could examine each individual's health conditions in real-time and was found to be advantageous in that it could secure the guardian's mobility.