• International journal of advanced smart convergence
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• v.12 no.1
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• pp.92-100
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• 2023

Wireless communication technology is becoming increasingly prevalent in smart factories, but the rise in the number of wireless devices can lead to interference in the ISM band and obstacles like metal blocks within the factory can weaken communication signals, creating radio shadow areas that impede information exchange. Consequently, accurately determining the radio communication coverage range is crucial. To address this issue, a Radio Environment Map (REM) can be used to provide information about the radio environment in a specific area. In this paper, a technique for estimating an indoor REM usinga mobile robot and machine learning methods is introduced. The mobile robot first collects and processes data, including the Received Signal Strength Indicator (RSSI) and location estimation. This data is then used to implement the REM through machine learning regression algorithms such as Extra Tree Regressor, Random Forest Regressor, and Decision Tree Regressor. Furthermore, the numerical and visual performance of REM for each model can be assessed in terms of R2 and Root Mean Square Error (RMSE).

• Journal of Educational Research in Mathematics
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• v.8 no.2
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• pp.621-634
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• 1998

Emthusiasm about the introduction of computers into mathematics education is widespred. But, the perspectives about the relationship between mathematics education and computer are diverse. The purpose of this study is to examine theoretical background for using computers in mathematics education. In spite of the pedagogical possibilities of computers. only a small minority of mathematics teachers are using computers in mathematics classroom. It is natural to seek this obstacles within theoretical background of the teachers who manage computers, In this study, We discuss the problems in the two sides. First, due to increased computer activity, relationship of mathematics in school with mathematics in society is changing. It is tension between academic mathematics and practical mathematics. School mathematics have to be changed toward stressing practical mathematics. Second problem is the dialectical relationship between the individual and the collective. While maintaining a respect for the individuality of student contributions. We take into account the social dimension of mathematical meaning-making. We discussed theoretical clarification of work collaborative learning. We propose the case study for the roles of computer in collaborative mathematics learning.

• Journal of Educational Research in Mathematics
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• v.11 no.2
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• pp.341-349
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• 2001

Infinity is one of the important concept in mathematics, science, philosophy etc. In history of mathematics, potential infinity concept conflicts with actual infinity concept. Reason that mathematicians refuse actual infinity concept during long period is because that actual infinity concept causes difficulty in our perceptions. This phenomenon is called epistemological obstacle by Brousseau. Potential infinity concept causes difficulty like history of development of infinity concept in mathematics learning. Even though students team about actual infinity concept, they use potential infinity concept in problem solving process. Therefore, we must make clear epistemological obstacles of infinity concept and must overcome them in learning of infinity concept. For this, it is useful to experience visualization about infinity concept. Also, it is to develop meta-cognition ability that students analyze and control their problem solving process. Conclusively, students must adjust potential infinity concept, and understand actual infinity concept that is defined in formal mathematics system.

• Journal of the Korean Institute of Rural Architecture
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• v.14 no.1
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• pp.21-28
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• 2012

Campus facilities were recently remodeled to provide the substantial learning rights of handicapped students in many campus to embody the dignity and value as man. So this study aims to identify the exterior connection facilities for handicapped students of S and D campuses. The summaries of this research are as follows. Installations of even crossing area(1.5mx1.5m) per 50m and even rest area(1.5mx1.5m) per 30m in walking or access ramp. Improving in accordance with exterior connection facility repairing master plan in S campus. Bringing down an angle degrees of the inclined walking or access ramp in D campus. Installation of exterior braille guide sign for blind students. All handicapped students must be guaranteed the same learning rights as normal men to remove obstacles as the upper mentioned imperfections in using exterior campus facilities.

• Journal of Korean Institute of Industrial Engineers
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• v.22 no.3
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• pp.499-515
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• 1996

The basic function of on industrial robot system is to move objects in the workspace fast and accurately. One difficulty in performing this function is that the path of robot should be programmed to avoid the collision with obstacles, that is, tools, or facilities. This path planning requires much off-line programming time. In this study, a SOM technique to find the collision-free path of robot in real time is developed. That is, the collision-free map is obtained through SOM learning and a collision-free path is found using the map in real time during the robot operation. A learning procedure to obtain the map and an algorithm to find a short path using the map is developed and simulated. Finally, a path smoothing method to stabilize the motion of robot is suggested.

• Journal of Digestive Cancer Research
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• v.5 no.1
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• pp.28-31
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• 2017

The number of laparosocpic liver resection performed every years has been increasing. There is a trend than more major hepatectomy and complex liver resection is being reported. However there has been a major obstacles in many centers because open liver resection is still considered as a gold standard and many surgeons are still getting used to the old method of liver resection. To start a new procedure, education and training is essential in order to achieve a good outcome without compromising the safety of the patients. A gradual progression is crucial in order to avoid dreadful complication. The development of the consensus meeting and difficulty score has facility the understanding of safe practice in the development of laparoscopic liver resection. In a long run, development of registry system will improve transparency and safety of this operation.

• Journal of the Institute of Convergence Signal Processing
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• v.23 no.3
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• pp.166-172
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• 2022

In this study, we photograph driving obstacle objects such as crosswalks, side spheres, manholes, braille blocks, partial ramps, temporary safety barriers, stairs, and inclined curb that hinder or cause inconvenience to the movement of the vulnerable using electric mobility aids. We develop an optimal AI model that classifies photographed objects and automatically recognizes them, and implement an algorithm that can efficiently determine obstacles in front of electric mobility aids. In order to enable object detection to be AI learning with high probability, the labeling form is labeled as a polygon form when building a dataset. It was developed using a Mask R-CNN model in Detectron2 framework that can detect objects labeled in the form of polygons. Image acquisition was conducted by dividing it into two groups: the general public and the transportation weak, and image information obtained in two areas of the test bed was secured. As for the parameter setting of the Mask R-CNN learning result, it was confirmed that the model learned with IMAGES_PER_BATCH: 2, BASE_LEARNING_RATE 0.001, MAX_ITERATION: 10,000 showed the highest performance at 68.532, so that the user can quickly and accurately recognize driving risks and obstacles.

• Journal of the Institute of Convergence Signal Processing
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• v.24 no.2
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• pp.119-125
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• 2023

In this study, we photograph driving obstacle objects such as crosswalks, side spheres, manholes, braille blocks, partial ramps, temporary safety barriers, stairs, and inclined curb that hinder or cause inconvenience to the movement of the vulnerable using electric mobility aids. We develop an optimal AI model that classifies photographed objects and automatically recognizes them, and implement an algorithm that can efficiently determine obstacles in front of electric mobility aids. In order to enable object detection to be AI learning with high probability, the labeling form is labeled as a polygon form when building a dataset. It was developed using a Mask R-CNN model in Detectron2 framework that can detect objects labeled in the form of polygons. Image acquisition was conducted by dividing it into two groups: the general public and the transportation weak, and image information obtained in two areas of the test bed was secured. As for the parameter setting of the Mask R-CNN learning result, it was confirmed that the model learned with IMAGES_PER_BATCH: 2, BASE_LEARNING_RATE 0.001, MAX_ITERATION: 10,000 showed the highest performance at 68.532, so that the user can quickly and accurately recognize driving risks and obstacles.

• The Journal of the Korea institute of electronic communication sciences
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• v.18 no.2
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• pp.231-240
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• 2023

It remains a challenge for robots to learn avoiding obstacles automatically in path planning using deep reinforcement learning (DRL). More and more researchers use DRL to train a robot in a simulated environment and verify the possibility of DRL to achieve automatic obstacle avoidance. Due to the influence factors of different environments robots and sensors, it is rare to realize automatic obstacle avoidance of robots in real scenarios. In order to learn automatic path planning by avoiding obstacles in the actual scene we designed a simple Testbed with the wall and the obstacle and had a camera on the robot. The robot's goal is to get from the start point to the end point without hitting the wall as soon as possible. For the robot to learn to avoid the wall and obstacle we propose to use the double deep Q networks (DDQN) to verify the possibility of DRL in automatic obstacle avoidance. In the experiment the robot used is Jetbot, and it can be applied to some robot task scenarios that require obstacle avoidance in automated path planning.

• Journal of the Korean Geographical Society
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• v.49 no.6
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• pp.970-984
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• 2014

This study aims to inquire into experience of geography teachers participating in a teacher learning community based on the grounded theory methodology. Participation observation was conducted on one of geography teacher learning communities. The total of 11 research participants were selected to conduct in-depth interviews. The data collected were analyzed by the coding method proposed by Strauss and Corbin(1990, 1998). In open coding, 125 concepts, 43 sub-categories and 17 categories were drawn and in axial coding by paradigm model, phenomenon, conditions, action/interaction and consequences turned out. In selective coding, the participants were classified into four types and the condition/consequence matrix was developed. As a result of the analysis, first, participation, obstacles and continuous participation factors of geography teachers in the teacher learning community could be understood from multi-dimensional aspects. Second, principles of the collaborative teacher learning and the factors promoting collaborative teacher learning were established. Third, the professional development of geography teachers through teacher learning community could be understood.