• Journal of Intelligence and Information Systems
• /
• v.25 no.1
• /
• pp.163-177
• /
• 2019

As smartphones are getting widely used, human activity recognition (HAR) tasks for recognizing personal activities of smartphone users with multimodal data have been actively studied recently. The research area is expanding from the recognition of the simple body movement of an individual user to the recognition of low-level behavior and high-level behavior. However, HAR tasks for recognizing interaction behavior with other people, such as whether the user is accompanying or communicating with someone else, have gotten less attention so far. And previous research for recognizing interaction behavior has usually depended on audio, Bluetooth, and Wi-Fi sensors, which are vulnerable to privacy issues and require much time to collect enough data. Whereas physical sensors including accelerometer, magnetic field and gyroscope sensors are less vulnerable to privacy issues and can collect a large amount of data within a short time. In this paper, a method for detecting accompanying status based on deep learning model by only using multimodal physical sensor data, such as an accelerometer, magnetic field and gyroscope, was proposed. The accompanying status was defined as a redefinition of a part of the user interaction behavior, including whether the user is accompanying with an acquaintance at a close distance and the user is actively communicating with the acquaintance. A framework based on convolutional neural networks (CNN) and long short-term memory (LSTM) recurrent networks for classifying accompanying and conversation was proposed. First, a data preprocessing method which consists of time synchronization of multimodal data from different physical sensors, data normalization and sequence data generation was introduced. We applied the nearest interpolation to synchronize the time of collected data from different sensors. Normalization was performed for each x, y, z axis value of the sensor data, and the sequence data was generated according to the sliding window method. Then, the sequence data became the input for CNN, where feature maps representing local dependencies of the original sequence are extracted. The CNN consisted of 3 convolutional layers and did not have a pooling layer to maintain the temporal information of the sequence data. Next, LSTM recurrent networks received the feature maps, learned long-term dependencies from them and extracted features. The LSTM recurrent networks consisted of two layers, each with 128 cells. Finally, the extracted features were used for classification by softmax classifier. The loss function of the model was cross entropy function and the weights of the model were randomly initialized on a normal distribution with an average of 0 and a standard deviation of 0.1. The model was trained using adaptive moment estimation (ADAM) optimization algorithm and the mini batch size was set to 128. We applied dropout to input values of the LSTM recurrent networks to prevent overfitting. The initial learning rate was set to 0.001, and it decreased exponentially by 0.99 at the end of each epoch training. An Android smartphone application was developed and released to collect data. We collected smartphone data for a total of 18 subjects. Using the data, the model classified accompanying and conversation by 98.74% and 98.83% accuracy each. Both the F1 score and accuracy of the model were higher than the F1 score and accuracy of the majority vote classifier, support vector machine, and deep recurrent neural network. In the future research, we will focus on more rigorous multimodal sensor data synchronization methods that minimize the time stamp differences. In addition, we will further study transfer learning method that enables transfer of trained models tailored to the training data to the evaluation data that follows a different distribution. It is expected that a model capable of exhibiting robust recognition performance against changes in data that is not considered in the model learning stage will be obtained.

• 대한공업교육학회지
• /
• v.34 no.2
• /
• pp.1-19
• /
• 2009

The goal of this study is to examine the status quo of industrial-educational cooperation in Technical high schools. Based upon the findings of the current conditions, this study ultimately aims to propose methods through which more active industrial-educational cooperation can be stimulated. The methods chosen for this study are reference research and surveys. The survey was conducted by imposing complete enumeration on the targeted high schools that specialize in industry related fields. The survey targets were the directions of academic affairs, the directions of practical affairs, and the directors of the educational curriculum of each school.The research results are as follows: First, the teachers recognize the necessities of having opportunities to gain specific skills in different industrial fields, having chances to get stable employment, and securing the industrial institution's competitiveness through the customized nurturing and supply of human resources as the primary goals of industrial-educational cooperation. Second, the teachers express the similar opinion that industrial-educational cooperation in their current system is inappropriate to achieve their goals. Third, the teachers claim that an educational curriculum that emphasizes industrial educational cooperation must be developed and managed. Fourth, it was found that when schools plan their educational curriculum, they often do not implement the requests from industrial institutions. Fifth, major educational program implement methods that meet the requests of the industrial institutions include field trips or the introduction of other field-based experience learning programs, the application of customized curriculums based on industrial-educational cooperation, and the invitation of industrial-educational personnel as teachers to school environments. Sixth, it was concluded that educational institutions need to proactively seek companies for cooperation; they need to support, develop, and manage school programs that are based on industrial-educational cooperation; and finally, institutions need to enthusiastically participate in the government's vocational education policies that are founded upon industrial-educational cooperation. Seventh, the enforcement of selective curriculum for the benefit of diversifying the educational program; the pursuit of balancing the specialized curriculum through shedding the national educational level provided within the regular curriculum; and the establishment of related amendments on the national level to provide effective industrial-educational cooperation have been identified as the vital factors that can develop the educational programs within high schools specializing in industry and that are closely related to industrial educational cooperation.

• Korean Journal of Environment and Ecology
• /
• v.24 no.3
• /
• pp.235-248
• /
• 2010

This study was carried out to the actual conditions and improvement of the eco-forests master plan in South Korea, and suggested its problems and improvement direction. Results from survey and analysis of limiting factors or constraints in the construction plans of eco-forests in Korea revealed that there were highly frequent problems involving site feasibility, topographic aspect, and existing vegetation. The results of survey on the status of land use indicated that the average ratio of the use of private estate was 29.7%, so then it was estimated that a great amount of investment in purchase of eco-forest site would be required. Results from survey on major introduced facilities showed that there was high frequency of introduction of infrastructure, building facility, recreational facility, convenience facility, and information facility, and that there was low frequency of introduction of plant culture system, ecological facility, structural symbol and sculpture, and the likes. There was just one eco-forest park where more than 500 species of plants grew, and the result of investigation indicated that the diversity of plant species in 11 eco-forest parks was lower than the standards for construction of eco-forest. Results from analysis of the projects costs revealed that investment cost in facilities was higher than planting costs, and that a large amount of investment was made in the initial stage of the project. There was no planned budget for the purpose of cultivating and maintaining the plants and vegetation after construction of eco-forest. The basic concepts in construction of eco-forests were established according to the guidelines presented by the Korea Forest Service; however, the detailed work of the project was planned with its user-oriented approach. Then the construction of eco-forest was being planned following the directions, which would lead to development of a plant garden similar to arboretum or botanical garden. Therefore, it is required that the architect who designs eco-forest as well as the public officer concerned firmly establish the concepts of eco-forest, and that, through close analysis of development conditions, a candidate site to fit the purpose of constructing eco-forest be selected, and also a substantive management plan be established upon completion of construction of eco-forest.

• Journal of the Korean Society of Fisheries and Ocean Technology
• /
• v.37 no.4
• /
• pp.302-307
• /
• 2001

The underwater background noise measured in Geoje and Tongyoung diving fishing ground from May to December, 2000 and analyzed to get optimum carrier frequency and transmitter power level for underwater wireless telephone design. The results obtained are summarized as follows: 1. At the Geoje and Tongyoung diving fishing ground, the lowest ambient noise band was 25~30kHz with 57dB and 52dB re 1$\mu$Pa, respectively. 2. At the Geoje and Tongyoung diving fishing ground, the lowest noise band during fishing activity was 67dB and 62dB re 1$\mu$Pa, respectively. 3. At the Geoje diving fishing ground, the noise of water jetter which is a digging machine for subbottom shells was 102dB re 1$\mu$Pa. 4. Considering the design parameters of underwater wireless telephone, it is found that the optimum carrier frequency band is around 30kHz and the transmitter source level should be at least 131dB re 1$\mu$Pa for 500m range telephone.

• Journal of the Korean Institute of Traditional Landscape Architecture
• /
• v.34 no.3
• /
• pp.50-66
• /
• 2016

This study attempts to understand and explain how "Directed Attention Restorative Environment (DARE)" is managed and fostered in "Gang-Hak (講學)" and "Yu-Sik (遊息)" spaces both inside and outside of Oksan Seowon Confucian Academy, Gyeongju. Directed Attention is a pivotal element in human information processing so that its restoration is crucial for effective thinking and learning. According to Kaplan & Kaplan's Attention Restoration Theory, an environment, in order to be restorative, should have four elements: 'Being Away,' 'Extent,' 'Fascination,' and 'Compatibility.' We could confirm OkSan Seowon Confucian Academy has an inner logic that integrates two basically different spacial concepts of "Jangsu" and "Yusik" and thus fosters the Attention Restorative Environment. Particularly, the Four Mountains and Five Platforms (四山五臺) surrounding the premises provides an excellent learning environment, and is in itself educational in terms of the Neo-Confucian epistemology with "Attaining Knowledge by way of Positioning Things (格物致知)" as its principle precept, and of its aesthetics with "Connectedness with Nature" as its central tenet. This study attempts to recapture the value of Korea's cultural heritage concerning the Human/Nature relationship; and it may provide useful insights and practical guidelines/grounds in designing today's schools and campuses, where the young people's needs for the Directed Attention- and Attention Restorative- Servicescapes seem to be greater than ever.

• Korean Journal of Agricultural and Forest Meteorology
• /
• v.24 no.4
• /
• pp.295-304
• /
• 2022

The purpose of this study is to detect the sorghum panicle using YOLOv5 based on RGB images acquired by a unmanned aerial vehicle (UAV) system. The high-resolution images acquired using the RGB camera mounted in the UAV on September 2, 2022 were split into 512×512 size for YOLOv5 analysis. Sorghum panicles were labeled as bounding boxes in the split image. 2,000images of 512×512 size were divided at a ratio of 6:2:2 and used to train, validate, and test the YOLOv5 model, respectively. When learning with YOLOv5s, which has the fewest parameters among YOLOv5 models, sorghum panicles were detected with mAP@50=0.845. In YOLOv5m with more parameters, sorghum panicles could be detected with mAP@50=0.844. Although the performance of the two models is similar, YOLOv5s ( 4 hours 35 minutes) has a faster training time than YOLOv5m (5 hours 15 minutes). Therefore, in terms of time cost, developing the YOLOv5s model was considered more efficient for detecting sorghum panicles. As an important step in predicting sorghum yield, a technique for detecting sorghum panicles using high-resolution RGB images and the YOLOv5 model was presented.

• Korean Journal of Remote Sensing
• /
• v.39 no.5_3
• /
• pp.949-965
• /
• 2023

In this study, we propose a method to monitor the surface area of agricultural reservoirs in South Korea using Sentinel-1 synthetic aperture radar images and the deep learning model, Swin Transformer. Utilizing the Google Earth Engine platform, datasets from 2017 to 2021 were constructed for seven agricultural reservoirs, categorized into 700 K-ton, 900 K-ton, and 1.5 M-ton capacities. For four of the reservoirs, a total of 1,283 images were used for model training through shuffling and 5-fold cross-validation techniques. Upon evaluation, the Swin Transformer Large model, configured with a window size of 12, demonstrated superior semantic segmentation performance, showing an average accuracy of 99.54% and a mean intersection over union (mIoU) of 95.15% for all folds. When the best-performing model was applied to the datasets of the remaining three reservoirsfor validation, it achieved an accuracy of over 99% and mIoU of over 94% for all reservoirs. These results indicate that the Swin Transformer model can effectively monitor the surface area of agricultural reservoirs in South Korea.

• Journal of the Korean Society of Food Science and Nutrition
• /
• v.45 no.5
• /
• pp.746-756
• /
• 2016

The purpose of this study was to investigate food safety knowledge, food safety attitudes, and handling behavior in the elderly. The survey was conducted on 358 individuals over 65 years old in urban and rural areas. Data were analyzed with descriptive analysis and ${\chi}^2$ test analysis of variance using SPSS. From the results on elderly's food safety knowledge, the item 'tangerines should be washed before eating' was correctly answered by urban subjects (75.4%) than rural subjects (49.7%). 'Is it okay to cook meat left on the sink since afternoon in the evening' showed the lowest correct answer rate in both urban (23.1%) and rural (31.9%) subjects. For the item related to food keeping, 'Bacterial cells do not multiply in Samgyetang when it is kept in a refrigerator right after boiling thoroughly', 58.5% of urban and 54.6% of rural elderly answered correctly. Most elderly people showed a tendency to think that boiled foods might be safe to eat. Secondly, for food safety attitudes, urban elderly had more proper attitude regarding the item, 'Namul is very tasty only when mixed with bare hands' (disagree rate 34.9%) than rural elderly (P<0.05)'. On the other hand, rural elderly had more positive attitudes regarding the store principle "first in, first out" compared to urban elderly (P<0.001). Thirdly, regarding food safety behaviors, only 67.9% of urban and 58.7% of rural elderly responded that they washed their hands right after answering the telephone while cooking. Exactly 33.8% of urban and 39.6% of rural older people replied 'defrost meat on top of sink or table' as the defrost method for frozen foods, showing that elderly did not recognize the risk of foodborne illness during improper defrosting at room temperature.

• Journal of Intelligence and Information Systems
• /
• v.26 no.3
• /
• pp.127-147
• /
• 2020

The world is suffering from numerous human and economic losses due to the novel coronavirus infection (COVID-19). The Korean government established a strategy to overcome the national infectious disease crisis through research and development. It is difficult to find distinctive features and changes in a specific R&D field when using the existing technical classification or science and technology standard classification. Recently, a few studies have been conducted to establish a classification system to provide information about the investment research areas of infectious diseases in Korea through a comparative analysis of Korea government-funded research projects. However, these studies did not provide the necessary information for establishing cooperative research strategies among countries in the infectious diseases, which is required as an execution plan to achieve the goals of national health security and fostering new growth industries. Therefore, it is inevitable to study information services based on the classification system and classification model for establishing a national collaborative R&D strategy. Seven classification - Diagnosis_biomarker, Drug_discovery, Epidemiology, Evaluation_validation, Mechanism_signaling pathway, Prediction, and Vaccine_therapeutic antibody - systems were derived through reviewing infectious diseases-related national-funded research projects of South Korea. A classification system model was trained by combining Scopus data with a bidirectional RNN model. The classification performance of the final model secured robustness with an accuracy of over 90%. In order to conduct the empirical study, an infectious disease classification system was applied to the coronavirus-related research and development projects of major countries such as the STAR Metrics (National Institutes of Health) and NSF (National Science Foundation) of the United States(US), the CORDIS (Community Research & Development Information Service)of the European Union(EU), and the KAKEN (Database of Grants-in-Aid for Scientific Research) of Japan. It can be seen that the research and development trends of infectious diseases (coronavirus) in major countries are mostly concentrated in the prediction that deals with predicting success for clinical trials at the new drug development stage or predicting toxicity that causes side effects. The intriguing result is that for all of these nations, the portion of national investment in the vaccine_therapeutic antibody, which is recognized as an area of research and development aimed at the development of vaccines and treatments, was also very small (5.1%). It indirectly explained the reason of the poor development of vaccines and treatments. Based on the result of examining the investment status of coronavirus-related research projects through comparative analysis by country, it was found that the US and Japan are relatively evenly investing in all infectious diseases-related research areas, while Europe has relatively large investments in specific research areas such as diagnosis_biomarker. Moreover, the information on major coronavirus-related research organizations in major countries was provided by the classification system, thereby allowing establishing an international collaborative R&D projects.