• KIPS Transactions on Computer and Communication Systems
• /
• v.11 no.9
• /
• pp.281-288
• /
• 2022

AGVs are often used in industrial applications to transport heavy materials around a large industrial building, such as factories or warehouses. In particular, in fulfillment centers their usefulness is maximized for automation. To increase productivity in warehouses such as fulfillment centers, sophisticated path planning of AGVs is required. We propose a scheme that can be applied to QMIX, a popular cooperative MARL algorithm. The performance was measured with three metrics in several fulfillment center layouts, and the results are presented through comparison with the performance of the existing QMIX. Additionally, we visualize the transport paths of trained AGVs for a visible analysis of the behavior patterns of the AGVs as heat maps.

• Journal of Digital Policy
• /
• v.1 no.1
• /
• pp.15-20
• /
• 2022

Recently, the healthcare field is trying to develop a model that can improve service quality by reflecting the requirements of various industrial fields. In this paper, we propose an Internet of Behavior (IoB) environment model that can process users' healthcare information in real time in a 5G environment to improve healthcare services. The purpose of the proposed model is to analyze the user's healthcare information through deep learning and then check the health status in real time. In this case, the biometric information of the user is transmitted through communication equipment attached to the portable medical equipment, and user authentication is performed through information previously input to the attached IoB device. The difference from the existing IoT healthcare service is that it analyzes the user's habits and behavior patterns and converts them into digital data, and it can induce user-specific behaviors to improve the user's healthcare service based on the collected data.

• The Mathematical Education
• /
• v.61 no.3
• /
• pp.499-519
• /
• 2022

Ratio and rate are key topics in the area of 'Patterns', but there are various perspectives on them. This study compared and analyzed the perspectives of Korean and Singaporean mathematics textbooks on ratio and rate, and explored how teaching and learning methods develop according to each perspective in terms of quantitative reasoning. To this end, we reorganized the analysis criteria based on some studies, and analyzed the textbooks of the two countries in relation to context, relationship, and representation. The results of the study are as follows. Regarding the context, there were differences in the situations, types of units and use of units of the problems presented in textbooks. In terms of relationship, there were differences in the types of two quantities and relationship of quantities. Lastly, there were differences in the representation of ratio and rate. Through these results, we found that elementary mathematics textbooks in Korea and Singapore take different perspectives on ratio and rate. In particular, the perspective taken by Korean textbooks on ratio and rate had unique points different from that of other previous studies. Considering this Korean perspective, we suggested some implications that could help improve textbooks related to ratio and rate and teach them meaningfully.

• Journal of Korean Society on Water Environment
• /
• v.39 no.1
• /
• pp.46-60
• /
• 2023

Climate change causes fluctuations in water quality in the aquatic environment, which can cause changes in water circulation patterns and severe adverse effects on aquatic ecosystems in the future. Therefore, research is needed to predict and respond to water quality changes caused by climate change in advance. In this study, we tried to predict the dissolved oxygen (DO), chlorophyll-a, and turbidity of the Paldang reservoir for about two weeks using long short-term memory (LSTM) and gated recurrent units (GRU), which are deep learning algorithms based on recurrent neural networks. The model was built based on real-time water quality data and meteorological data. The observation period was set from July to September in the summer of 2021 (Period 1) and from March to May in the spring of 2022 (Period 2). We tried to select an algorithm with optimal predictive power for each water quality parameter. In addition, to improve the predictive power of the model, an important variable extraction technique using random forest was used to select only the important variables as input variables. In both Periods 1 and 2, the predictive power after extracting important variables was further improved. Except for DO in Period 2, GRU was selected as the best model in all water quality parameters. This methodology can be useful for preventive water quality management by identifying the variability of water quality in advance and predicting water quality in a short period.

• Korean Educational Research Journal
• /
• v.43 no.1
• /
• pp.183-213
• /
• 2022

The purpose of this study is to examine the implications of Deleuze and Guattari's Machinism and Pedagogy of Assemblages. A slow, empirical process offered by Deleuze and Guattari is possible only if they experience a repetition of the duration in time. The identity of this world, a combination of potential and reality, is expressed as a machine. The identity of the 'machine' is the generation. The identity of the information society that exists everywhere in the cloud and unconsciously collects big data is also the information society. The information society is at risk of leaning toward a society in which individual desires are managed prior to the manifestation of a self-reliance a machine consisting of unmarked and mechanical arrangements. Social science based on the theory of layout shares the characteristics of repetition patterns, coexistence of linguistic and materiality, attention to boundary and negation to total whole. The pedagogy of layout, in which the collective pattern is structurally deformed in time, conforms to the original problem consciousness of Deleuze and Guattari, slow and empirical education. In addition, the work of examining the materiality and expression of the education-machine will contribute to the establishment of a new learning theory, an educational theory in the era of trans-human.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
• /
• 2021.05a
• /
• pp.151-154
• /
• 2021

Big data analysis is the process of discovering meaningful new correlations, patterns, and trends in large volumes of data stored in data stores and creating new value. Thus, most big data analysis technology methods include data mining, machine learning, natural language processing, and pattern recognition used in existing statistical computer science. Also, using the R language, a big data tool, we can express analysis results through various visualization functions using pre-processing text data. The data used in this study was analyzed for 21 papers in the March 2021 among the journals of the Korea Institute of Information and Communication Engineering. In the final analysis results, the most frequently mentioned keyword was "Data", which ranked first 305 times. Therefore, based on the results of the analysis, the limitations of the study and theoretical implications are suggested.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
• /
• 2021.05a
• /
• pp.326-327
• /
• 2021

Newly, big data utilization has been widely interested in a wide variety of industrial fields. Big data analysis is the process of discovering meaningful new correlations, patterns, and trends in large volumes of data stored in data stores and creating new value. Thus, most big data analysis technology methods include data mining, machine learning, natural language processing, and pattern recognition used in existing statistical computer science. Also, using the R language, a big data tool, we can express analysis results through various visualization functions using pre-processing text data. The data used in this study were analyzed for 29 papers in a specific journal. In the final analysis results, the most frequently mentioned keyword was "Research", which ranked first 743 times. Therefore, based on the results of the analysis, the limitations of the study and theoretical implications are suggested.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
• /
• 2021.10a
• /
• pp.281-283
• /
• 2021

The representative companies mentioned in the recommendation service in the domestic OTT(Over-the-top media service) market are YouTube and Netflix. YouTube, through various methods, started personalized recommendations in earnest by introducing an algorithm to machine learning that records and uses users' viewing time from 2016. Netflix categorizes users by collecting information such as the user's selected video, viewing time zone, and video viewing device, and groups people with similar viewing patterns into the same group. It records and uses the information collected from the user and the tag information attached to the video. In this paper, we propose a method to improve video media recommendation by automatically generating metadata of video media that was written by hand.

• Smart Structures and Systems
• /
• v.32 no.3
• /
• pp.135-151
• /
• 2023

Using 3D asphalt pavement surface data, a deep and multiscale network named CrackNet-M is proposed in this paper for pixel-level crack detection for improvements in both accuracy and robustness. The CrackNet-M consists of four function-specific architectural modules: a central branch net (CBN), a crack map enhancement (CME) module, three pooling feature pyramids (PFP), and an output layer. The CBN maintains crack boundaries using no pooling reductions throughout all convolutional layers. The CME applies a pooling layer to enhance potential thin cracks for better continuity, consuming no data loss and attenuation when working jointly with CBN. The PFP modules implement direct down-sampling and pyramidal up-sampling with multiscale contexts specifically for the detection of thick cracks and exclusion of non-crack patterns. Finally, the output layer is optimized with a skip layer supervision technique proposed to further improve the network performance. Compared with traditional supervisions, the skip layer supervision brings about not only significant performance gains with respect to both accuracy and robustness but a faster convergence rate. CrackNet-M was trained on a total of 2,500 pixel-wise annotated 3D pavement images and finely scaled with another 200 images with full considerations on accuracy and efficiency. CrackNet-M can potentially achieve crack detection in real-time with a processing speed of 40 ms/image. The experimental results on 500 testing images demonstrate that CrackNet-M can effectively detect both thick and thin cracks from various pavement surfaces with a high level of Precision (94.28%), Recall (93.89%), and F-measure (94.04%). In addition, the proposed CrackNet-M compares favorably to other well-developed networks with respect to the detection of thin cracks as well as the removal of shoulder drop-offs.

• Korean Journal of Veterinary Service
• /
• v.46 no.4
• /
• pp.293-302
• /
• 2023

This study provides a comprehensive analysis of the epidemiological trends and challenges in managing tuberculosis (TB) in livestock in Korea from 2013 to 2022. Tuberculosis, caused by the Mycobacterium tuberculosis complex, is a significant zoonotic disease affecting cattle, deer, and other domesticated animals. Despite the initiation of a test-and-slaughter eradication policy in 1964, TB has continued to persist in Korean livestock, particularly in cattle and deer. This study used data from the Korea Animal Health Integrated System and provincial animal health laboratories to analyze TB incidence in various livestock including different cattle breeds and deer species. The results from 2013 to 2022 showed a peak in TB cases in 2019 with a subsequent decline by 2022. The study highlighted a significant incidence of TB in Korean native cattle and the need for amore inclusive approach towards TB testing and control in different cattle breeds. Additionally, the study underscored the importance of addressing TB in other animals such as goats, wildlife, and companion animals for a holistic approach to TB eradication in Korea. The findings suggest that while the test-and-slaughter strategy has been historically effective, there is a need for adaptation to the current challenges, and learning from successful eradiation stories on other countries like Australia. A collaborative effort involving an expanded surveillance system, active private sector participation, and robust government support essential for the efficient eradication of TB in livestock in Korea.