• Journal of Internet Computing and Services
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• v.22 no.1
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• pp.23-30
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• 2021

This paper proposes a noise-tolerant image classification system using multiple autoencoders. The development of deep learning technology has dramatically improved the performance of image classifiers. However, if the images are contaminated by noise, the performance degrades rapidly. Noise added to the image is inevitably generated in the process of obtaining and transmitting the image. Therefore, in order to use the classifier in a real environment, we have to deal with the noise. On the other hand, the autoencoder is an artificial neural network model that is trained to have similar input and output values. If the input data is similar to the training data, the error between the input data and output data of the autoencoder will be small. However, if the input data is not similar to the training data, the error will be large. The proposed system uses the relationship between the input data and the output data of the autoencoder, and it has two phases to classify the images. In the first phase, the classes with the highest likelihood of classification are selected and subject to the procedure again in the second phase. For the performance analysis of the proposed system, classification accuracy was tested on a Gaussian noise-contaminated MNIST dataset. As a result of the experiment, it was confirmed that the proposed system in the noisy environment has higher accuracy than the CNN-based classification technique.

• Journal of Convergence for Information Technology
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• v.10 no.12
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• pp.15-21
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• 2020

Although IoT systems are used in a variety of heterogeneous environments as cloud environments develop, all IoT devices are not provided with reliable protocols and services. This paper proposes an IoT data management technique that can extend the IoT cloud environment to an n-layer multi-level structure so that information collected from different heterogeneous IoT devices can be efficiently sorted and processed. The proposed technique aims to classify and process IoT information by transmitting routing information and weight information through wireless data link data collected from heterogeneous IoT devices. The proposed technique not only delivers information classified from IoT devices to the corresponding routing path but also improves the efficiency of IoT data processing by assigning priority according to weight information. The IoT devices used in the proposed technique use each other's reliable protocols, and queries for other IoT devices locally through a local cloud composed of hierarchical structures have features that ensure scalability because they maintain a certain cost.y channels of IoT information in order to make the most of the multiple antenna technology.

• Journal of the Korean Association of Geographic Information Studies
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• v.23 no.4
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• pp.173-183
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• 2020

In the midst of the aging of underground facilities in urban areas and anxiety about road excavation safety accidents, the Ministry of Land, Infrastructure and Transport began to build Underground Geospatial Infomation Map from 2015 as part of the 「ground subsidence prevention measures」 and efficient use of underground spaces. So, the scope is spreading every year. The current Underground Geospatial Infomation Map information is web-based and is operated in a desktop environment, so it is true that there are some limitations in its use in a field environment such as an excavation construction site. The Underground Geospatial Infomation Map, built and operated in a web-based environment, is a large-scale 3D data. Therefore, in order to service by transmitting data to the field without delay, it is necessary to lighten the Underground Geospatial Infomation Map data. In addition, the current Underground Geospatial Infomation Map is not unified in data formats such as 3DS and COLLADA, and the coordinate system method is also different in relative coordinates and absolute coordinates. In this study, by analyzing domestic and overseas prior research and technical use cases, a mobile Underground Geospatial Infomation Map data format and a lightweight method were presented, and a technology development was conducted to create a mobile underground space integration map in the presented format. In addition, the weight reduction rate was tested by applying 3D data compression technology so that data can be transmitted quickly in the field, and technology was developed that can be used by decompressing 3D data compressed in the field. finally, it aims to supplement the technology experimentally developed in this study and conduct additional research to produce it as software that can be used in the excavation site and use it.

• Journal of Broadcast Engineering
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• v.25 no.6
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• pp.861-869
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• 2020

We introduce the application that automatically makes several images stored in user's device into one video by using the different climax patterns appearing for each film genre. For the classification of the genre characteristics of movies, a climax pattern model style was created by analyzing the genre of domestic movie drama, action, horror and foreign movie drama, action, and horror. The climax pattern was characterized by the change in shot size, the length of the shot, and the frequency of insert use in a specific scene part of the movie, and the result was visualized. The model visualized by genre developed as a template using Firebase DB. Images stored in the user's device were selected and matched with the climax pattern model developed as a template for each genre. Although it is a short video, it is a feature of the proposed application that it can create an emotional story video that reflects the characteristics of the genre. Recently, platform operators such as YouTube and Naver are upgrading applications that automatically generate video using a picture or video taken by the user directly with a smartphone. However, applications that have genre characteristics like movies or include video-generation technology to show stories are still insufficient. It is predicted that the proposed automatic video editing has the potential to develop into a video editing application capable of transmitting emotions.

• The Journal of Korean Philosophical History
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• no.56
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• pp.209-238
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• 2018

The purpose of this research is to analyze characteristics of the method of education or learning reflected in the teacher-student relationship in On Haeng Lok By Toe-gye and explore their relevance to modern education. By writing various works and conversing with his students, Toe-gye devoted himself in the education of the traditional Confucian principles. Specially, he taught his students based on two Confucian educative principles, namely Shim Deuk(心得) and Goong Haeng(躬行). Judging from this, Toe-gye can be seen as someone who tries to fulfill the role of teacher as dictated in the educative principles of the Confucianism. In Confucianism, teacher is responsible for forming a well-rounded view on life in student, rather than simply transmitting knowledge. As such, the teacher was supposed to find a harmonious way to create something new based on what was inherited from the past generation and try to do his best in learning new things himself and teaching his students. These Toe-gye managed to do successfully, earning his students' trust and respect. Being moved and inspired by their teacher, the students continued their intellectual pursuit. This relationship between Toe-gye and his students can be analyzed from the perspective of education method and discussed in terms of cognitive learning and adult learning. In terms of cognitive learning, the education method reflected in the relationship is similar to potential learning, insight learning, and imitation learning. In terms of adult learning, it is similar to self-directed learning and communicative learning.!

• The Journal of Korean Philosophical History
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• no.39
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• pp.143-168
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• 2013

The purpose of this paper is to study the succession and method of five-masters of southern school in transmitting the internal alchemy in Taoism which is established by Zhang Bo-duan. In history, the internal alchemy is divided into a few schools but all of them are under the umbrella of Zhang Bo-duan's alchemy. The five master's method has been consistent from Zhang Bo-duan to Seok Tae to Seol Do Gwang based on three reasons. First, they lived long while practicing the method. Second, they learned the method from their direct master secretly. Third, they kept practicing the individual method while staying in the secular world rather than in a religious body. I limit three of them Zhang Bo-Dan, Seok Tae, Seol Do Gwang as figures who practiced the pure internal alchemy. Thus I argue that the method stayed only for 200 years, arising from the late Dang Dynasty and disappearing in 1911, when Seol Do-Gwang was dead. This method can be instructed only to the appropriate figure, and the specific steps of method are taught through the oral instruction so that this method cannot be wide spread. Based on the fact that the time of practicing method is quite long and it needs intensive and constant efforts, it is difficult for a mundane person to practice and cope with the training. Jin Nam and Baek Ok Seom are believed that they belonged to the school of Shin So. Baek Ok Seom is regarded as a figure that made efforts to unite the school of Wei and the internal alchemy. However, he made lots of fabrication and discrepancy. Thus I state that Jin Nam and Baek Ok Seom need to be out in the succession and method of five masters of southern school in Taoism. Their changed method in quality needs to be organized in a new genealogy.

• Journal of Korea Society of Industrial Information Systems
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• v.25 no.6
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• pp.33-45
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• 2020

This paper aims to look at the perspective that the latest cutting-edge technologies are predicting individual diseases in the actual medical environment in a situation where various types of wearable devices are rapidly increasing and used in the healthcare domain. Through the process of collecting, processing, and transmitting data by merging clinical data, genetic data, and life log data through a user-participating wearable device, it presents the process of connecting the learning model and the feedback model in the environment of the Deep Neural Network. In the case of the actual field that has undergone clinical trial procedures of medical IT occurring in such a high-tech medical field, the effect of a specific gene caused by metabolic syndrome on the disease is measured, and clinical information and life log data are merged to process different heterogeneous data. That is, it proves the objective suitability and certainty of the deep neural network of heterogeneous data, and through this, the performance evaluation according to the noise in the actual deep learning environment is performed. In the case of the automatic encoder, we proved that the accuracy and predicted value varying per 1,000 EPOCH are linearly changed several times with the increasing value of the variable.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.25 no.5
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• pp.719-730
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• 2021

We have demonstrated a sandwich-type ZnO-based piezoelectric energy harvesting nanogenerator, namely ZCZ-NG device, composed of symmetrically stacked layers of ZnO/carbon tape/ZnO structure. Especially, we have adopted a conductive double-sided adhesive carbon tape in an effort to fabricate a high-quality ZCZ-NG device, leading to its superior output performance in terms of the peak-to-peak output voltage. Effects of the device size, ZnO layer thickness, and bending strain rate on the device performance have been investigated by measuring the output voltage. Moreover, to evaluate the effectiveness of the fabricated ZCZ-NG devices, we have experimentally implemented a sensor network testbed which can utilize the output voltages of ZCZ-NG devices. This sensor network testbed consists of several components such as Arduino-based transmitter and receiver nodes, wirelessly transmitting the sensed information of each node. We hope that this research combining the ZnO-based energy harvesting devices and IoT sensor networks will contribute to the development of more advanced energy harvester-driven IoT sensor networks in the future.

• Journal of Biomedical Engineering Research
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• v.42 no.6
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• pp.259-267
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• 2021

Recently, the market for personal health care and medical devices based on Bluetooth Low Energy(BLE) has grown rapidly. BLE is being used in various medical data communication devices based on low power consumption and universal compatibility. However, since data errors occurring in the transmission of medical data can lead to medical accidents, it is necessary to analyze the causes of errors and study methods to reduce data error. In this paper, the minimum communication speed to be used in medical devices was set to at least 800 byte/sec based on the wireless electrocardiography regulations of the Ministry of Food and Drug Safety. And the data loss rate was tested when data was transmitted at a speed higher than 800 byte/sec. The factors that cause communication data error were classified, and the relationship between each factor and the data error rate was analyzed through experiments. When there were two or more activated peripherals connected to the central, data error occurred due to channel hopping and bottleneck, and the data error rate increased in proportion to the communication distance and the number of activated peripherals. Through this experiment, when the BLE is used in a medical device that intermittently transmits biosignal data, the risk of a medical accident is predicted to be low if the number of peripherals is 3 or less. But, it was determined that BLE would not be suitable for the development of a biosignal measuring device that must be continuously transmitted in real time, such as an electrocardiogram.

• Journal of the Korea Institute of Building Construction
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• v.21 no.6
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• pp.677-687
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• 2021

If a fire breaks out in a building, occupants can evacuate more rapidly if they are able to identify the location of the fire, the exits, and themselves. This study derives the requirements of system development, such as distance non-limitation, a non-additional device, a non-centralized server system, and low power for an emergency, to identify information about the fire and the location of evacuees. The objective is to receive and transmit information and reduce the time and effort of the database for location tracking. Accordingly, this study develops a server-independent system that collects information related to a building fire and an evacuee's location and provides information to the evacuee on their mobile device. The system is composed of a transmitting unit to disseminate fire location information and a mobile device application to determine the locations of the fire and the evacuee. The developed system can contribute to reducing the damage to humans because evacuees can identify the location of the fire, exits, and themselves regardless of the impaired server system by fire, the interruption of power source, and the evacuee's location. Furthermore, this study proposes a theoretical basis for reducing the effort required for database construction of the k-nearest neighbor fingerprint.