• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2014.10a
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• pp.370-372
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• 2014

This study questions, and an automatic scoring system written in HTML, and XML-based system that is at issue, the issue questions in a convenient offline automatically how to register, Easy to manage questions of issues, questions and problems of merging the PC and the mobile device in a place that can be obtained without taking the test system study. Server systems, and real-time registration questions merging problem, such as difficulty adjusting to the test required to build the system. Clients communicate with the server using the mobile device and the PC is required to take the exam in the View application, and responses are sent for treatment research.

• KIPS Transactions on Computer and Communication Systems
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• v.9 no.11
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• pp.256-264
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• 2020

Industrial Wireless Sensor Networks (IWSNs) is exploited to achieve various objectives such as improving productivity and reducing cost in the diversity of industrial application, and it has requirements such as low-delay and high reliability packet transmission. To accomplish the requirement, the network manager performs graph construction and resource allocation about network topology, and determines the transmission cycle and path of each node in advance. However, this network management scheme cannot treat mobile devices that cause continuous topology changes because graph reconstruction and resource reallocation should be performed as network topology changes. That is, despite the growing need of mobile devices in many industries, existing scheme cannot adequately respond to path failure caused by movement of mobile device and packet loss in the process of path recovery. To solve this problem, a network management scheme is required to prevent packet loss caused by mobile devices. Thus, we analyse the location and movement cycle of mobile devices over time using machine learning for predicting the mobility pattern. In the proposed scheme, the network manager could prevent the problems caused by mobile devices through performing graph construction and resource allocation for the predicted network topology based on the movement pattern. Performance evaluation results show a prediction rate of about 86% compared with actual movement pattern, and a higher packet delivery ratio and a lower resource share compared to existing scheme.

• 제어로봇시스템학회:학술대회논문집
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• 2001.10a
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• pp.43.6-43
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• 2001

In this paper, we describe an actor-critic method as a kind of temporal difference (TD) algorithms. The value function is regarded as a current estimator, in which two value functions have different inputs: one is an actual experience; the other is a simulated experience obtained through a predictive model. Thus, the parameter´s updating for the actor and critic parts is based on actual and simulated experiences, where the critic is constructed by a radial-basis function neural network (RBFNN) and the actor is composed of a kinematic-based controller. As an example application of the present method, a tracking control problem for the position coordinates and azimuth of a nonholonomic mobile robot is considered. The effectiveness is illustrated by a simulation.

• 제어로봇시스템학회:학술대회논문집
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• 2001.10a
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• pp.44.1-44
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• 2001

This paper discusses the interacting mobile robots for tele-operation system using the world wide web. In multi-agent and web-based teleoperation environment the problem of communication delay must be solved for the efficient and robust control of the system. The standard graphic user interface(GUI)is implemented using Java Programing language. The web browser is used to integrate the virtual environment and the standard GUI(Java applet) in a single user interface. Users can access a dedicated WWWserver and download the user interface. Reinforcement learning is applied to indirect control in order to autonomously operate without the need of human intervention. Java application has been developed to communicate and control multi robots using WWW. The effectiveness of our multi robots system is verified by simulation and experiments ...

• Journal of the Semiconductor & Display Technology
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• v.20 no.3
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• pp.117-119
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• 2021

With the development of the industry, the use of drones in specific mission flight is being actively studied. These drones fly a specified path and perform repetitive tasks. if the drone system will detect objects in real time, the performance of these mission flight will increase. In this paper, we implement object detection system and mount GPU acceleration to maximize the efficiency of limited device resources with drone video using Tensorflow Lite which enables in-device inference from a mobile device and Mobile SDK of DJI, a drone manufacture. For performance comparison, the average processing time per frame was measured when object detection was performed using only the CPU and when object detection was performed using the CPU and GPU at the same time.

• Journal of Korea Game Society
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• v.11 no.4
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• pp.163-174
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• 2011

The purpose of this study was to apply a variety of criteria to analyzing mobile applications for early childhood education, which are now available in application market, and was also to explore how the developmental characteristics and multimedia content characteristics of early childhood could be applied to mobile applications for early childhood education. To meet these purposes, this study targeted total 61 applications for infancy education in terms of mobile applications loaded on online education categories such as iPhone App Store and Android Market. Based on analytic criteria on the foundation of content type by learning type, cognitive load theory and multimedia design principle, this study analyzed those applications for early childhood. As a result, it was found that there were needs to develop a little more various categories of applications, and there were also needs to develop such applications that they can make the best use of smart phone's performance, comply with multimedia design principles but avoid any imprudent use of multimedia.

• Journal of Software Assessment and Valuation
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• v.15 no.1
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• pp.63-70
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• 2019

These days, as Interest in Image recognition with deep learning is increasing, there has been a lot of research in image recognition using deep learning. In this study, we propose a system for classifying rocks through rock images of 18 types of rock(6 types of igneous, 6 types of metamorphic, 6 types of sedimentary rock) which are addressed in the high school curriculum, using CNN model based on Tensorflow, deep learning open source framework. As a result, we developed a classifier to distinguish rocks by learning the images of rocks and confirmed the classification performance of rock classifier. Finally, through the mobile application implemented, students can use the application as a learning tool in classroom or on-site experience.

• Journal of Information Processing Systems
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• v.18 no.3
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• pp.443-456
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• 2022

An efficient and reasonable resource allocation strategy can greatly improve the service quality of Internet of Vehicles (IoV). However, most of the current allocation methods have overestimation problem, and it is difficult to provide high-performance IoV network services. To solve this problem, this paper proposes a network resource allocation strategy based on deep learning network model DDQN. Firstly, the method implements the refined modeling of IoV model, including communication model, user layer computing model, edge layer offloading model, mobile model, etc., similar to the actual complex IoV application scenario. Then, the DDQN network model is used to calculate and solve the mathematical model of resource allocation. By decoupling the selection of target Q value action and the calculation of target Q value, the phenomenon of overestimation is avoided. It can provide higher-quality network services and ensure superior computing and processing performance in actual complex scenarios. Finally, simulation results show that the proposed method can maintain the network delay within 65 ms and show excellent network performance in high concurrency and complex scenes with task data volume of 500 kbits.

• Journal of Korea Multimedia Society
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• v.21 no.5
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• pp.626-637
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• 2018

Human exchanges information not only through words, but also through body gesture or hand gesture. And they can be used to build effective interfaces in mobile, virtual reality, and augmented reality. The past 2D gesture recognition research had information loss caused by projecting 3D information in 2D. Since the recognition of the gesture in 3D is higher than 2D space in terms of recognition range, the complexity of gesture recognition increases. In this paper, we proposed a real-time gesture recognition deep learning model and application in 3D space using deep learning technique. First, in order to recognize the gesture in the 3D space, the data collection is performed using the unity game engine to construct and acquire data. Second, input vector normalization for learning 3D gesture recognition model is processed based on deep learning. Thirdly, the SELU(Scaled Exponential Linear Unit) function is applied to the neural network's active function for faster learning and better recognition performance. The proposed system is expected to be applicable to various fields such as rehabilitation cares, game applications, and virtual reality.

• Journal of The Korean Association For Science Education
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• v.34 no.3
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• pp.285-294
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• 2014

This study investigates the effects of formative assessment utilizing mobile applications on interest and self-directedness in science instruction. The study subjects are two 6th grade classes from H elementary school located in Incheon, and the experimental group and the comparative group are composed of 21 students, respectively. The students from the experimental group have been taught with mobile devices while the comparative group has been taught in methods consistent with the current teaching standards. For the sake of research, the results of the method applied to the mobile device focus group have been edited using Google Drive Forms, entered as QR codes and stored in order for them to later be utilized for teaching and learning process. In the process, the teacher has provided the students with feedback based on their answers. The students of comparative group are to solve the same formative assessment in paper. As a result, the teacher of the mobile device focus group has been able to go through twenty-nine questions on formative assessment in the teaching and learning process, confirm the correct answers five times and provide feedback twenty-five times for additional explanation. In the inquiry about interest, the mobile device group scored 4.64 points and the standard one scored just 1.99 points (p<0.01). Fifteen students answered in the interview that and the major reason why they scored high has been because it was fun to study with mobile devices. When it comes to self-directedness over the process of teaching and learning, the mobile device focus group has answered positively but the standard group has scored relatively low (p<0.01).