• Journal of Korea Water Resources Association
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• v.41 no.1
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• pp.1-15
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• 2008

The purpose of this study is to propose a procedure that will be able to find the most efficient sets of weight coefficients for the Geum-River basin in Korea. The result obtained from multi-objective optimization model is inherently sensitive to the weight coefficient on each objective. In multi-objective reservoir operation problems, the coefficient setting may be more complicated because of the natural variation of inflow. Therefore, for multi-objective reservoir operation problems, it may be important for modelers to provide reservoir operators with appropriate sets of weight coefficients considering the inflow variation. This study presents a procedure to find an appropriate set of weight coefficients under the situation that has inflow variation. The proposed procedure uses GA-CoMOM to provide a set of weight coefficient sets. A DEA-window analysis and a cross efficiency analysis are then performed in order to evaluate and rank the sets of weight coefficients for various inflow scenarios. This proposed procedure might be able to find the most efficient sets of weight coefficients for the Geum-River basin in Korea.

• Journal of the Institute of Electronics Engineers of Korea TC
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• v.43 no.5 s.347
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• pp.7-16
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• 2006

IPTV is referred to the service which provide integrated IPTV services for providing video, 10/100-Mbit/sec Internet, voice, video-on-demand (VOD), and other broadband applications including home security, video conferencing, and telemedicine. All services are integrated into an IP (Internet Protocol) architecture designed specifically for Gigabit Ethernet FTTH systems, HFC or xDLC. It is absolutely necessary that telecon operators provide IP video delivery platforms that enable service providers to transform their business. With their own products, they can better manage their existing services and generate new revenues from broadcast TV, movies on demand and multimedia. Triple-play is a combination of broadcast, telephony and broadband services offered through IPTV networks. With cable operators allowed to offer a triple-play bundle, the nation's telecom operators are beginning to get a little anxious. Cable operators assert that triple-play is a must-have and natural extension of the cable service bundle. The Korean Cable TV Association asserts that the triple-play model is of paramount importance to the cable industry's future growth. But the telecom sector considers itself unfairly disadvantaged, saying they cannot compete until regulatory issues are resolved. The start of web-based television in Korea may still be some time off with a confrontation between the nation's IT regulator and broadcasting sector over the service's legal boundaries shows no signs of being resolved my time soon. korea should be is the fastest-growing provider of IPTV solutions in the industry, with over worldwide customers.

• Journal of Intelligence and Information Systems
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• v.26 no.2
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• pp.131-145
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• 2020

In line with the trend of industrial innovation, IoT technology utilized in a variety of fields is emerging as a key element in creation of new business models and the provision of user-friendly services through the combination of big data. The accumulated data from devices with the Internet-of-Things (IoT) is being used in many ways to build a convenience-based smart system as it can provide customized intelligent systems through user environment and pattern analysis. Recently, it has been applied to innovation in the public domain and has been using it for smart city and smart transportation, such as solving traffic and crime problems using CCTV. In particular, it is necessary to comprehensively consider the easiness of securing real-time service data and the stability of security when planning underground services or establishing movement amount control information system to enhance citizens' or commuters' convenience in circumstances with the congestion of public transportation such as subways, urban railways, etc. However, previous studies that utilize image data have limitations in reducing the performance of object detection under private issue and abnormal conditions. The IoT device-based sensor data used in this study is free from private issue because it does not require identification for individuals, and can be effectively utilized to build intelligent public services for unspecified people. Especially, sensor data stored by the IoT device need not be identified to an individual, and can be effectively utilized for constructing intelligent public services for many and unspecified people as data free form private issue. We utilize the IoT-based infrared sensor devices for an intelligent pedestrian tracking system in metro service which many people use on a daily basis and temperature data measured by sensors are therein transmitted in real time. The experimental environment for collecting data detected in real time from sensors was established for the equally-spaced midpoints of 4×4 upper parts in the ceiling of subway entrances where the actual movement amount of passengers is high, and it measured the temperature change for objects entering and leaving the detection spots. The measured data have gone through a preprocessing in which the reference values for 16 different areas are set and the difference values between the temperatures in 16 distinct areas and their reference values per unit of time are calculated. This corresponds to the methodology that maximizes movement within the detection area. In addition, the size of the data was increased by 10 times in order to more sensitively reflect the difference in temperature by area. For example, if the temperature data collected from the sensor at a given time were 28.5℃, the data analysis was conducted by changing the value to 285. As above, the data collected from sensors have the characteristics of time series data and image data with 4×4 resolution. Reflecting the characteristics of the measured, preprocessed data, we finally propose a hybrid algorithm that combines CNN in superior performance for image classification and LSTM, especially suitable for analyzing time series data, as referred to CNN-LSTM (Convolutional Neural Network-Long Short Term Memory). In the study, the CNN-LSTM algorithm is used to predict the number of passing persons in one of 4×4 detection areas. We verified the validation of the proposed model by taking performance comparison with other artificial intelligence algorithms such as Multi-Layer Perceptron (MLP), Long Short Term Memory (LSTM) and RNN-LSTM (Recurrent Neural Network-Long Short Term Memory). As a result of the experiment, proposed CNN-LSTM hybrid model compared to MLP, LSTM and RNN-LSTM has the best predictive performance. By utilizing the proposed devices and models, it is expected various metro services will be provided with no illegal issue about the personal information such as real-time monitoring of public transport facilities and emergency situation response services on the basis of congestion. However, the data have been collected by selecting one side of the entrances as the subject of analysis, and the data collected for a short period of time have been applied to the prediction. There exists the limitation that the verification of application in other environments needs to be carried out. In the future, it is expected that more reliability will be provided for the proposed model if experimental data is sufficiently collected in various environments or if learning data is further configured by measuring data in other sensors.