• Journal of the Korean Institute of Intelligent Systems
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• v.21 no.3
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• pp.323-328
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• 2011

In real system application, the 3-D obstacle avoidance system for the autonomous control of the underwater flight vehicle (UFV) operates with the following problems: the sonar offers the range/bearing information of obstacles in a local detection area, it requires the system that has reduced acoustic noise and power consumption in terms of the autonomous underwater vehicle (AUV), it has the UFV operation constraints such as maximum pitch and depth, and it requires an easy design procedure in terms of its structures and parameters. To solve these problems, an intelligent 3-D obstacle avoidance algorithm using the evolution strategy (ES) and the fuzzy logic controller (FLC), is proposed. To verify the performance of the proposed algorithm, the 3-D obstacle avoidance of UFV is performed. Simulation results show that the proposed algorithm effectively solves the problems in the real system application.

• Journal of the Korea Society for Simulation
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• v.30 no.4
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• pp.1-8
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• 2021

Deep learning is one of the most widely accepted methods for the forecasting of time series data which have the complexity and non-linear behavior. In this paper, we investigate the modification of a state-of-art WaveNet deep learning architecture and walk forward validation (WFV) in order to forecast electric power consumption data 24-hour-ahead. WaveNet originally designed for raw audio uses 1D dilated causal convolution for long-term information. First of all, we propose a modified version of WaveNet which activates real numbers instead of coded integers. Second, this paper provides with the training process with tuning of major hyper-parameters (i.e., input length, batch size, number of WaveNet blocks, dilation rates, and learning rate scheduler). Finally, performance evaluation results show that the prediction methodology based on WFV performs better than on the traditional holdout validation.

• The Journal of the Korea Contents Association
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• v.18 no.11
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• pp.13-29
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• 2018

An increasing number of people in their lifes have used personal web-casting services as a new type of broadcasting, whose power has grown in the broadcasting market and industry. Nevertheless, limited research concerning personal web-casting has been conducted so far. This research explored consumption structures of personal web-casting users in terms of their genre usage based on the theoretical concept of genre repertoire. And it also examined what determinants have influences on these structures by focusing on as an representative case in South Korea. The findings showed that sensation seeking, motivation for getting information and social presence affect genre repertoire of personal web-casting users. They also indicated that there is a moderating effect of social presence in the relationship between motivation for joy and genre repertoire.

• Electronics and Telecommunications Trends
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• v.34 no.5
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• pp.14-25
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• 2019

As the Internet of Things, artificial intelligence and big data have received a lot of attention as key growth engines in the era of the fourth industrial revolution, data acquisition and utilization in mobile, automotive, robotics, manufacturing, agriculture, health care and national defense are becoming more important. Due to numerous data-based industrial changes, demand for sensor technologies is exploding, especially for intelligent sensor technologies that combine control, judgement, storage and communication functions with the sensors's own functions. Intelligent sensor technology can be defined as a convergence component technology that combines intelligent sensor units, intelligent algorithms, modules with signal processing circuits, and integrated plaform technologies. Intelligent sensor technology, which can be applied to variety of smart IT convergence services such as smart devices, smart homes, smart cars, smart factory, smart cities, and others, is evolving towards intelligent and convergence technologies that produce new high-value information through recognition, reasoning, and judgement based on artificial intelligence. As a result, development of intelligent sensor units is accelerating with strategies for miniaturization, low-power consumption and convergence, new form factor such as flexible and stretchable form, and integration of high-resolution sensor arrays. In the future, these intelligent sensor technologies will lead explosive sensor industries in the era of data-based artificial intelligence and will greatly contribute to enhancing nation's competitiveness in the global sensor market. In this report, we analyze and summarize the recent trends in intelligent sensor technologies, especially those for four core technologies.

• Korean Journal of Materials Research
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• v.31 no.3
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• pp.132-138
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• 2021

Electrochromic devices (ECDs) have been drawing great attention due to their high color contrast, low power consumption, and memory effect, and can be used in smart windows, automatic dimming mirrors, and information display devices. As with other electronic devices such as LEDs (light emitting diodes), solar cells, and transistors, the mechanical flexibility of ECDs is one of the most important issue for their potential applications. In this paper, we report on flexible ECDs (f-ECDs) fabricated using an all-in-one EC gel, which is a mixture of electrolyte and EC material. The f-ECDs are compared with rigid ECDs (r-ECDs) on ITO glass substrate in terms of color contrast, coloration efficiency, and switching speed. It is confirmed that the f-ECDs embedding all-in-one gel show strong blue absorption and have competitive EC performance. Repetitive bending tests show a degradation of electrochromic performance, which must be improved using an optimized device fabrication process.

• Journal of Convergence for Information Technology
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• v.12 no.1
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• pp.172-179
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• 2022

Unlike other processes such as washing, the ironing process in the laundry process is difficult to standardize and thus relies on manual labor. Unlike upper garments, pants have pleats at the waist as well as a crease line below the waist, Therefore, two separate ironing devices have been developed and used. However, in this method, problems such as additional worker input, space loss, and wrinkling of pants occur due to manual movement between processes, Consequently, a pants ironing device that combines the two equipments is required. The all-in-one pants ironing system described in this paper automatically sequentially irons the upper part and side of the pants regardless of the length, shape, and upper pleats of the pants. It also performs a self-diagnosis function while displaying the ironing progress on the user's monitor. As a result of this study, it became possible to double the amount of ironing and reduce power consumption by more than 20% compared to the case of using two independent equipment.

• Journal of Appropriate Technology
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• v.7 no.1
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• pp.26-32
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• 2021

In the process of vaccine delivery and vaccination, temperature is mostly controlled by an insulated containers containing ice. Moreover, amount of wasted vaccine is significant because the temperature of the vaccine is not properly controlled. A core challenge of vaccination is temperature data monitoring, since it is critical for managing and operating strategical vaccination by health organizations. In this research, a real-time monitoring vaccine carrier system was developed. Temperature, location, and power consumption data of the vaccine carrier were monitored and working performances of the vaccine carrier were tested in both Korea and Tanzania (Arusha and Kilimanjaro regions). For both places, Short Message Service (SMS) communication method was used to send information of the carrier's status. As a result, the monitoring system was able to transmit and receive real-time data of the vaccine carrier status while the vaccine carrier was tested. The vaccine status data can be accessed from any location through the cloud server and web-based user interface.

• Journal of the Korea Society for Simulation
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• v.19 no.2
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• pp.119-125
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• 2010

In ad-hoc networks, dynamically reconfigurable and temporary wireless networks, all mobile devices cooperatively maintain network connectivity with no assistance of base stations while they have limited amounts of energy that is used in different rates depending on the power level. Since every node has to perform the functions of a router, if some nodes die early due to lack of energy, it will not be possible for other nodes to communicate with each other and network lifetime will be shortened. Consequently, it is very important to develop a technique to efficiently consume the limited amounts of energy resources so that the network lifetime is maximized. In this paper, geographical localized routing is proposed to help making smarter routing decision using only local information and reduce the routing overhead. The proposed localized routing algorithm selects energy-aware neighbors considering the transmission energy and error rate over the wireless link, and the residual energy of the node, which enables nodes to achieve balanced energy-consumption and the network lifetime to prolong.

• Journal of Software Assessment and Valuation
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• v.15 no.1
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• pp.55-62
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• 2019

The needs for small size and low power consumption of information devices is being implemented with SOC technology that implements the program on a single chip in Internet of Thing. Copyright disputes due to piracy are increasing in semiconductor chips as well, arising from disputes in the chip implementation of the design house and chip implementation by the illegal use of the source code. However, since the final chip implementation is made in the design house, it is difficult to protect the copyright. In this paper, we deal with the analysis method for extracting similarity and the criteria for setting similarity judgment in the dispute of source code written in HDL language. Especially, the chip which is manufactured based on the same specification will be divided into the same configuration and the code type.

• International conference on construction engineering and project management
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• 2022.06a
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• pp.1256-1263
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• 2022

With the advent of the Fourth Industrial Revolution, the amount of energy used in buildings has been increasing due to changes in the energy use structure caused by the massive spread of information-oriented equipment, climate change and greenhouse gas emissions. For the efficient use of energy, it is necessary to have a plan that can predict and reduce the amount of energy use according to the type of energy source and the use of buildings. To address such issues, this study presents a model embedded in a digital twin that predicts energy use in buildings. The digital twin is a system that can support a solution of urban problems through the process of simulations and analyses based on the data collected via sensors in real-time. To develop the energy use prediction model, energy-related data such as actual room use, power use and gas use were collected. Factors that significantly affect energy use were identified through a correlation analysis and multiple regression analysis based on the collected data. The proof-of-concept prototype was developed with an exhibition facility for performance evaluation and validation. The test results confirm that the error rate of the energy consumption prediction model decreases, and the prediction performance improves as the data is accumulated by comparing the error rates of the model. The energy use prediction model thus predicts future energy use and supports formulating a systematic energy management plan in consideration of characteristics of building spaces such as the purpose and the occupancy time of each room. It is suggested to collect and analyze data from other facilities in the future to develop a general-purpose energy use prediction model.