• KIPS Transactions on Software and Data Engineering
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• v.7 no.12
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• pp.497-504
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• 2018

This paper studies about the Oriental Medical Expert System, based on Open Source Drools for rule engine processing, which contains scalability, availability, and modifiability. The system is developed with the Spring MVC framework and Ajax for stable services of the Web-based Medical Expert System. The diagnosis and treatment process of this Medical Expert system provides a service that provides the general users to accesses the web with a series of questionnaires. In order to compensate for the asynchronous communication between clients and services, and also for the complicated JDBC weaknesses, we applied the data handling in JSON to reduce the servers' loads, and also the Mybatis framework to improve the performance of the RDBMS, respectively. In addition, as the number of users increases to cope with the maximum available services of the web-based system, the load balancing structure using Nginx has been developed to solve the server traffic problems and the service availability has been increased. The experimental results show the stable services by approving the scalability test.

• Journal of the Korea Society for Simulation
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• v.28 no.2
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• pp.149-158
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• 2019

This paper introduces an integrated Modeling & Simulation framework for the efficient development of the rescue robot which rescues a wounded patients or soldiers and disposes a dangerous objects or explosive materials in the battlefields and disastrous environments. An integrated M&S(Modeling & Simulation) framework would have enabled us to perform the dynamic simulation program GAZEBO based Software-in-the-Loop Simulation(SILS) which is to replacing the robot platform hardware with a simulation software. An integrated M&S framework would help us to perform designing robot and performance validation of robot control results more efficiently. Furthermore, Tele-operation performance in the unstructured environments could be improved. We review a case study of applying an integrated M&S framework tool in validating performance of mobility stabilization control, one of the most important control strategy in the rescue robot.

• Journal of Digital Convergence
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• v.17 no.1
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• pp.85-90
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• 2019

This paper is a study on IoT based map inside the building and fire perception system using microprocessor and LABVIEW program. The smart control system implemented in this paper is designed to identify the location of fire by using microprocessor, flame detection sensor, carbon monoxide sensor and temperature sensor, and to guide the optimal travel route through Zigbee communication. And the proposed system uses QR code to interoperate with smartphone. The coordinator control verified that the sensor value of the smart control system installed through the LABVIEW software was confirmed. The IoT based control system studied in this paper was implemented with Arduino mega board and LABVIEW software, and the operation status was confirmed by display device and coordination.

• Journal of the Korea Convergence Society
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• v.10 no.9
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• pp.23-29
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• 2019

In this paper, the mood of images was classified into eight categories through a deep convolutional neural network and video was automatically generated using proper background music. Based on the collected image data, the classification model is learned using a multilayer perceptron (MLP). Using the MLP, a video is generated by using multi-class classification to predict image mood to be used for video generation, and by matching pre-classified music. As a result of 10-fold cross-validation and result of experiments on actual images, each 72.4% of accuracy and 64% of confusion matrix accuracy was achieved. In the case of misclassification, by classifying video into a similar mood, it was confirmed that the music from the video had no great mismatch with images.

• Journal of Broadcast Engineering
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• v.24 no.1
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• pp.67-76
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• 2019

In this paper, we propose an efficient object classification method based on semantic segmentation for multi-labeled image data. In addition to various pixel unit information and processing techniques such as color information, contour, contrast, and saturation included in image data, a detailed region in which each object is located is extracted as a meaningful unit and the experiment is conducted to reflect the result in the inference. We use a neural network that has been proven to perform well in image classification to understand which object is located where image data containing various class objects are located. Based on these researches, we aim to provide artificial intelligence services that can classify real-time detailed areas of complex images containing various objects in the future.

• Journal of the Korea Society of Computer and Information
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• v.26 no.5
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• pp.95-101
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• 2021

In this study, we present how to improve the current seismic disaster information service by utilizing Shake, which can express the effects of earthquakes in the form of isolines. Using ShakeMap software provided by the U.S. Geological Survey, an automated rapid ShakeMap generation system was implemented, and based on this, an earthquake disaster information service improvement model was presented to identify earthquake risk in the form of intensity or peak ground acceleration. In order to verify the feasibility and effectiveness of the improved model, the seismic disaster information service app. was developed and operated on a trial basis in Pohang, Gyeongsangbuk-do. As a result of the operation, it was found that more detailed seismic risk information could be provided by providing information using rapid ShakeMap to induce users' safety behavior more effectively.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.13 no.6
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• pp.605-610
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• 2020

Software Defined Networking (SDN) is setting the standard for the management of networks due to its scalability, flexibility and functionality to program the network. The Distributed Denial of Service (DDoS) attack is most widely used to attack the SDN controller to bring down the network. Different methodologies have been utilized to detect DDoS attack previously. In this paper, first the dataset is obtained by Kaggle with 84 features, and then according to the rank, the 20 highest rank features are selected using Permutation Importance Algorithm. Then, the datasets are trained and tested with Convolution Neural Network (CNN) classifier model by utilizing deep learning techniques. Our proposed solution has achieved the best results, which will allow the critical systems which need more security to adopt and take full advantage of the SDN paradigm without compromising their security.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.18 no.3
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• pp.9-21
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• 2008

In this paper, we revisit a generally accepted opinion: implementing Elliptic Curve Cryptosystem (ECC) over GF$(2^m)$ on sensor motes using small word size is not appropriate because partial XOR multiplication over GF$(2^m)$ is not efficiently supported by current low-powered microprocessors. Although there are some implementations over GF$(2^m)$ on sensor motes, their performances are not satisfactory enough due to the redundant memory accesses that result in inefficient field multiplication and reduction. Therefore, we propose some techniques for reducing unnecessary memory access instructions. With the proposed strategies, the running time of field multiplication and reduction over GF$(2^{163})$ can be decreased by 21.1% and 24.7%, respectively. These savings noticeably decrease execution times spent in Elliptic Curve Digital Signature Algorithm (ECDSA) operations (Signing and verification) by around $15{\sim}19%$.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.22 no.6
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• pp.1345-1354
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• 2012

The modern society with the wide spread USB memory, witnesses the acceleration in the development of USB products that applied secure technology. Secure USB is protecting the data using the method as device-based access control, encryption of stored files, and etc. In terms of forensic analyst, to access the data is a lot of troubles. In this paper, we studied software-based data en/decryption technology and proposed for analysis mechanism to validation vulnerability that secured on removable storage media. We performed a vulnerability analysis for USB storage device that applied security mechanism. As a result, we found vulnerabilities that extracts a source file without a password.

• Journal of Cadastre & Land InformatiX
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• v.51 no.1
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• pp.67-77
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• 2021

Spatial data is becoming very important as a medium that connects various data produced in smart cities, digital twins, autonomous driving, smart construction, and other applications. In addition, the rapid construction and update of spatial information is becoming a hot topic to satisfy the diverse needs of consumers in this field. This study developed a software prototype that can match the position of an image-based 3D building model produced without Ground Control Points using existing spatial data. As a result of applying this software to the test area, the 3D building model produced based on the image and the existing spatial data show a high positional matching rate, so that it can be widely used in applications requiring the latest 3D spatial data.