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Pine wilt disease spreading prevention system using semantic segmentation Chulhyun Hwang; Jaean Jeong; Hoekyung Jung
International Journal of Electrical and Computer Engineering (IJECE) Vol 11, No 3: June 2021
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v11i3.pp2666-2673

Pine wilt disease is a disease that affects ecosystems by rapidly killing trees in a short period of time due to the close interaction between three factors such as trees, mediates, and pathogens. There is no 100% mortality infectious forest pests. According to the Korea Forest Service survey, as of April 2019, the damage of pine re-nematode disease was about 490,000 dead trees in 117 cities, counties and wards across the country. It's a fatal condition. In order to prevent this problem, this paper proposes a system that detects dead trees, early infection trees, and the like, using deep learning-based semantic segmentation. In addition, drones were used to photograph the area of the forest, and a separate pixel segmentation label could be used to identify three levels of transmission information: Suspicion, attention, and confirmation. This allows the user to grasp information such as area, location, and alarm to prevent the spread of re-nematode disease.

Fruit tree disease classification system using generative adversarial networks Changsu Kim; Hyesoo Lee; Hoekyung Jung
International Journal of Electrical and Computer Engineering (IJECE) Vol 11, No 3: June 2021
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v11i3.pp2508-2515

Smart farm refers to a farm that can remotely and automatically maintain proper growth and management of crops and livestock by integrating technology with agriculture. Currently, smart farms are concentrated in the field of smart horticulture, and although spreading research is being conducted in limited spaces. In addition, it is difficult to obtain a sufficient amount of data to be used for learning, and there is a problem that data imbalance occurs because it is difficult to obtain a similar amount for each class. In this paper, we propose a method to amplify a small amount of data and to solve the problems of imbalance data by using a feature that can learn to mimic the data of a generative adversarial network. The proposed method can create dataset of various crops and also show high hit rate. Dataset generated from crops would be used to solve problems of data imbalance by learning.

Body Information Analysis based Personal Exercise Management System Jongwon Lee; Hyunju Lee; Donggyun Yu; Hoekyung Jung
International Journal of Electrical and Computer Engineering (IJECE) Vol 8, No 2: April 2018
Publisher : Institute of Advanced Engineering and Science

Recently, people's interest in health is deepening. So health-related systems are being developed. Existing exercise management systems provided users with exercise related information using PC or smart phone. However, there is a problem that the accuracy of the algorithm for analyzing the user's body information and providing information is low.In this paper, we analyze users' body mass index (BMI) and basal metabolic rate (BMR) and we propose a system that provides the user with necessary information through recommendation algorithm. It informs the user of exercise intensity and momentum, and graphs the exercise history of the user. It also allows the user to refer to the fitness history of other users in the same BMI group. This allows the user to receive more personalized services than the existing exercise management system, thereby enabling efficient exercise.

Human activity recognition by using convolutional neural network Hankil Kim; Sungock Lee; Hoekyung Jung
International Journal of Electrical and Computer Engineering (IJECE) Vol 9, No 6: December 2019
Publisher : Institute of Advanced Engineering and Science

In recent years, many researchers have studied the HAR (Human Activity Recognition) system. HAR using smart home sensor is based on computing in smart environment, and intelligent surveillance system conducts intensive research on peripheral support life. The previous system studied in some of the activities is a fixed motion and the methodology is less accurate. In this paper, vision-based studies using thermal imaging cameras improve the accuracy of motion recognition in intelligent surveillance systems. We use one of the deep learning architectures widely used in image recognition systems called Convolutional Neural Networks (CNN). Therefore, we use CNN and thermal cameras to provide accuracy and many features through the proposed method.

Personal customized recommendation system reflecting purchase criteria and product reviews sentiment analysis Wu Guanchen; Minkyu Kim; Hoekyung Jung
International Journal of Electrical and Computer Engineering (IJECE) Vol 11, No 3: June 2021
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v11i3.pp2399-2406

As the size of the e-commerce market grows, the consequences of it are appearing throughout society. The business environment of a company changes from a product center to a user center and introduces a recommendation system. However, the existing research has shown a limitation in deriving customized recommendation information to reflect the detailed information that users consider when purchasing a product. Therefore, the proposed system reflects the user's subjective purchasing criteria in the recommendation algorithm. And conduct sentiment analysis of product review data. Finally, the final sentiment score is weighted according to the purchase criteria priority, recommends the results to the user.

User command acquisition based IoT automatic control system Inshik Kang; Hyunok Song; Hoekyung Jung
Indonesian Journal of Electrical Engineering and Computer Science Vol 13, No 1: January 2019
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v13.i1.pp307-312

Recently, researches are being conducted to build a smart environment using various sensors and devices and to provide customized services to users through IoT (Internet of Things). The existing IoT system operates the device only by using the threshold value. So, there are problems that device operates when a service that does not consider a user characteristic is provided or when user not necessary. In this paper, to solve these problems, the system collects the remote control commands and compares it with the value of device operation threshold and sets the changed threshold value. In addition, devices not registered in the server constitute the environment by linking with existing task. Therefore, it is possible to provide a customized service to the users.

Automatic control system based on iot data identification Hankil Kim; Jaehyun Park; Hoekyung Jung
Indonesian Journal of Electrical Engineering and Computer Science Vol 19, No 3: September 2020
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v19.i3.pp1525-1532

Recently, as the internet of things (IoT) technology has developed, researches are rigorously conducted to construct smart environments such as smart home, smart grid, and industrial IoT. However, currently existing systems consists of a series of events, and even if an existing task is running, unnecessary work still occurs as both works happen simultaneously. In this paper, we propose an automatic work control system to solve this problem. The proposed system transmits the data measured by the sensor to the server and identifies non-real-time tasks such as real-time work which is related to the dangerous situations, ventilation and temperature control. In addition, priority among the tasks is set in a way that existing tasks are stopped when high priority tasks occur. Accordingly, this can reduce the unnecessary waste of power, and the user is able to receive a proactive service.

Improving data quality using a deep learning network Chulhyun Hwang; Kyouhwan Lee; Hoekyung Jung
Indonesian Journal of Electrical Engineering and Computer Science Vol 20, No 1: October 2020
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v20.i1.pp306-312

IoT data is collected in real time and is treated as highly reliable data because of its high precision. However, it often exhibits incomplete values for reasons such as sensor aging and failure, poor operating environment, and communication problems. The characteristics of IoT data transmitted with high precision and time series are suitable to use LSTM, which is one kind of RNN. In this paper, when applying LSTM to data quality improvement in IoT environment where data are collected simultaneously from several sensors, it is suggested that it is effective to construct LSTM individually for each sensor accuracy.

Main keyword comparison based on document analysis system Jongwon Lee; Jaeseung Lee; Hoekyung Jung
Indonesian Journal of Electrical Engineering and Computer Science Vol 19, No 3: September 2020
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v19.i3.pp1533-1539

Existing document analysis systems list words in the document using a morpheme analyzer. Such a structural feature is difficult to help users to understand the document. To understand a document, you need to analyze the keyword in the document and extract the paragraphs including the keyword. The proposed system retrieves keywords from documents written in XML format, extracts them, and displays them to the user. In addition, it extracts the paragraphs including the keyword entered by the user and maintains paragraph sequence and delete for duplicate paragraphs. Then, the frequency and weight of the keyword are calculated, and the number of paragraphs is reduced by removing the paragraphs including the keyword having a weight less than other keywords weighed. This method may reduce the time and effort required for the user to understand the document as compared to the existing document analysis systems.

IoT task management system using control board Changsu Kim; Youngkuk Kim; Hoekyung Jung
Indonesian Journal of Electrical Engineering and Computer Science Vol 13, No 1: January 2019
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v13.i1.pp155-161

Recently, Internet of Things (IoT) has been providing services that increase convenience for users by connecting objects to a network. As a result, the number of users and smart devices utilizing IoT is also increasing. So, the existing system has a problem that when a variety of devices are added, a bottleneck or an overload of the server occurs, because of structure of the system. In this paper, we propose IoT task management system using control board to solve these problems. The server performs only simple communication and analysis, and the management of tasks such as remote control is carried out using the control board. Also, it analyzes the user's remote control command and recommends to users the most used equipment. Through this, it is possible to reduce the data throughput and traffic of the server and to provide the service with increased convenience and accuracy of operation.

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