• International journal of advanced smart convergence
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• v.12 no.3
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• pp.127-140
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• 2023

While tools exist for blind people to understand shapes, these are not commercially available nor affordable and often require the assistance of sighted people. Thus, we designed two low-cost grid-based tactile tools using toggle buttons (TogGrid) and cotton balls (CottonGrid). To assess the potential of these as an educational tool, we conducted a user study with 12 people with visual impairments where they were asked to understand and reproduce shapes under different conditions. Although CottonGrid is relatively cheap and easy to make, findings show that TogGrid was perceived to be better in terms of perceived easiness, task completion time, accuracy, and preference in general. Particularly, participants valued TogGrid for enabling them to identify and correct errors. Based on the findings, we provide implications for utilizing toggle buttons for designing educational instruments for learning and expressing shapes for blind people.

• Journal of Engineering Education Research
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• v.11 no.3
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• pp.12-23
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• 2008

The purpose of this study is to explore teaching and learning strategies through analyzing cases of foreign engineering education. With the analysis criteria composed of engineering education model, teaching and learning method, evaluation strategy, and technology supporting strategy, 10 foreign colleges of engineering in 5 countries were examined and analyzed. Teaching and learning strategies deduced from analysis state as follows. First of all, it need to develop engineering education models that reform should be made in systematic approach to teaching and learning, workplaces and laboratories, evaluation, technology support, etc. Secondly, the strategy for teaching and learning recommends supporting student directed learning, active learning participation, and collaboration learning by inductive learning strategies such as problem based learning, inquiry learning, project based learning, studio based learning, and blended learning. Thirdly, the evaluation strategy suggests that evaluation should be made to reflect students' learning and facilitate continuous learning based current learning results while it is necessary to build up a whole evaluation system. Finally, it is the educational technology approach for systematic engineering education that is required considering that many foreign colleges of engineering have reformed engineering education through technology supporting systems and are maximizing research and education in connection with other universities. This study is expected to contribute as preliminary data in developing further teaching and learning models and strategies for nurturing engineering students.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.14 no.2
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• pp.113-121
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• 2014

A subsea oil production system must be safely operated for 20-30 years after being installed. Because of the severe conditions of the subsea environment, such as extreme high pressure, low visibility, the possibility of unexpected impact by any object, and corrosion by seawater, subsea oil production systems should be monitored by subsea data logger systems and remotely operated vehicles to check for abnormal vibration and leakage to prevent a catastrophic accident. Because of the severity of subsea environmental conditions and the dominance of a few companies in the market, many people have thought that it would be difficult to develop a subsea data logger system. The primary objectives of the study described in this paper were to analyze existing subsea data logger systems to establish the requirements for a subsea data logger system, implement a prototype subsea data logger system, and conduct a test of the prototype subsea data logger system.

• Journal of the Korea Safety Management & Science
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• v.16 no.3
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• pp.239-248
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• 2014

Most systems used in industrial sites, actually have non-linearity and uncertainty. Therefore there are a lot of difficulties in evaluating conditions of these systems. Generally, the quantitative analysis and expression are found hard because the general public cannot easily make an accurate interpretation on the systems. Thus development of a system that utilizes an expertise from skilled analysts is required. In this research, a real-time sensor signal conditioning system and Fuzzy-expert system have been separately set up into an inference algorithm. So that it ensures a fast, accurate, objective and quantitative operational condition value provided to the manager. Therefore, FE_AFCDM is suggested in this literature, as an effective system for diagnosing the problems related to the air compressor. It can quantify the uncertain and absurd condition to operate the air compressor facilities safely and financially.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.22 no.12
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• pp.1596-1603
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• 2018

Rapidly detecting and warning of fires is necessary for minimizing human injury and property damage. Generally, when fires occur, both the smoke and the flames are generated, so fire detection systems need to detect both the smoke and the flames. However, most fire detection systems only detect flames or smoke and have the disadvantage of slower processing speed due to additional preprocessing task. In this paper, we implemented a fire detection system which predicts the flames and the smoke at the same time by constructing a CNN model that supports multi-labeled classification. Also, the system can monitor the fire status in real time by using Grad-CAM which visualizes the position of classes based on the characteristics of CNN. Also, we tested our proposed system with 13 fire videos and got an average accuracy of 98.73% and 95.77% respectively for the flames and the smoke.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.18 no.5
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• pp.1162-1170
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• 2014

In this paper, an accurate remote gaze tracking method with two cameras is presented using a modified Starburst algorithm and honography normalization. Starburst algorithm, which was originally developed for head-mounted systems, often fails in detecting accurate pupil centers in remote tracking systems with a larger field of view due to lots of noises. A region of interest area for pupil is found using template matching, and then only within this area Starburst algorithm is applied to yield pupil boundary candidate points. These are used in improved RANSAC ellipse fitting to produce the pupil center. For gaze estimation robust to head movement, an improved homography normalization using four LEDs and calibration based on high order polynomials is proposed. Finally, it is shown that accuracy and robustness of the system is improved using two cameras rather than one camera.

• Journal of The Korean Society of Agricultural Engineers
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• v.61 no.1
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• pp.9-20
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• 2019

The primary objective of this study was to analyze the delivery ratio using Hydrological Simulation Program - Fortran (HSPF) in Okdong-cheon watershed. Model parameters related to hydrology and water quality were calibrated and validated by comparing model predictions with the 8-day interval filed data collected for ten years from the Korea Ministry of Environment. The results indicated that hydrology and water quality parameters appeared to be reasonably comparable to the field data. The pollutant delivery loads of the watershed in 2015 were simulated using the HSPF model. The delivery ratios of each subwatershed were also estimated by the simple ratio calculation of pollutant discharge load and pollutant delivery load. Coefficients of the regression equation between the delivery ratio and specific discharge were also computed using the delivery ratio. Based on the results, multiple regression analysis was performed using the discharge and the physical characteristics of the subwatershed such as the area. The equation of delivery ratio derived in this study is only for the Okdong-cheon watershed, so the larger studies are needed to apply the findings to other watersheds.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.21 no.7
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• pp.1349-1354
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• 2017

In this paper, we propose a fast hand-gesture recognition algorithm for embedded system. Existing hand-gesture recognition algorithm has a difficulty to use in a low performance system such as embedded systems and mobile devices because of high computational complexity of contour tracing method that extracts all points of hand contour. Instead of using algorithms based on contour tracing, the proposed algorithm uses concentric-circle tracing method to estimate the abstracted contour of fingers, then classify hand-gestures by extracting features. The proposed algorithm has an average recognition rate of 95% and an average execution time of 1.29ms, which shows a maximum performance improvement of 44% compared with algorithm using the existing contour tracing method. It is confirmed that the algorithm can be used in a low performance system such as embedded systems and mobile devices.

• Journal of Engineering Education Research
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• v.25 no.3
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• pp.35-44
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• 2022

Artificial intelligence is a core technology in the era of digital transformation, and as the technology level is advanced and used in various industries, its influence is growing in various fields, including social, ethical and legal issues. Therefore, it is time to raise social awareness on ethics of artificial intelligence as a prevention measure as well as improvement of laws and institutional systems related to artificial intelligence development. In this study, we analyzed unstructured data, typically text, such as online news articles and comments to confirm the degree of social awareness on ethics of artificial intelligence development. The analysis showed that the public intended to concentrate on specific issues such as "Human," "Robot," and "President" in 2018 to 2019, while the public has been interested in the use of personal information and gender conflics in 2020 to 2021.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.20 no.9
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• pp.1649-1656
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• 2016

Performance of the existing sensor-based fire detection system is limited according to factors in the environment surrounding the sensor. A number of image-based fire detection systems were introduced in order to solve these problem. But such a system can generate a false alarm for objects similar in appearance to fire due to algorithm that directly defines the characteristics of a flame. Also fir detection systems using movement between video flames cannot operate correctly as intended in an environment in which the network is unstable. In this paper, we propose an image-based fire detection method using CNN (Convolutional Neural Network). In this method, firstly we extract fire candidate region using color information from video frame input and then detect fire using trained CNN. Also, we show that the performance is significantly improved compared to the detection rate and missing rate found in previous studies.