• Journal of Korean Society on Water Environment
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• v.39 no.3
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• pp.231-239
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• 2023

Public sewage treatment facilities are a necessary infrastructure for public health that treat sewage generated in cities and basin living areas and discharge it into rivers or seas. Recently, the role of public sewage treatment is receiving attention as a place of use of wastewater-based epidemiology (WBE), which analyzes human specific metabolic emissions or biomarkers present in sewage to investigate the environment to which the population is exposed in the water drain. WBE is mainly applied to investigate legal and water-law drug use or to predict and analyze the lifestyle of local residents. WBE has also been applied to predict and analyze the degree of infectious diseases that are prevalent worldwide, such as COVID-19. Since sewage flowing into public sewage treatment facilities includes living information of the population living in the drainage area, it is easy to collect basic data to predict the confirmation and spread of infectious diseases. Therefore, it is necessary to establish a new role of public sewage treatment facilities as an infrastructure necessary for WBE that can obtain information on the confirmation and spread of infectious diseases other than the traditional role of public sewage treatment. In South Korea, the sewerage supply rate is about 95.5% and the number of public sewage treatment facility is 4,209. This means that the infrastructure of sewerage is fully established. However, to successfully drive for WBE , research on monitoring and big-data analysis is needed.

• Science of Emotion and Sensibility
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• v.25 no.4
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• pp.45-52
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• 2022

Recently, interest in and demand for sensors that recognize physical activity and their products are increasing. In particular, the development of wearable materials that are flexible, stretchable, and able to detect the user's biological signals is drawing attention. In this study, an experiment was conducted to improve the dip-coating efficiency of a single-walled carbon nanotube dispersion solution after fine holes were made in a hydrophobic material with a micro needle. In this study, dip-coating was performed with a material that was not penetrated, and comparative analysis was performed. The electrical conductivity of the sensor was measured when the sensor was stretched using a strain universal testing machine (Dacell Co. Ltd., Seoul, Korea) and a multimeter (Keysight Technologies, Santa Rosa, CA, USA) was used to measure resistance. It was found that the electrical conductivity of a sensor that was subjected to needling was at least 16 times better than that of a sensor that was not. In addition, the gauge factor was excellent, relative to the initial resistance of the sensor, so good performance as a sensor could be confirmed. Here, the dip-coating efficiency of hydrophobic materials, which have superior physical properties to hydrophilic materials but are not suitable due to their high surface tension, can be adopted to more effectively detect body movements and manufacture sensors with excellent durability and usability.

• Journal of Intelligence and Information Systems
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• v.29 no.2
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• pp.23-34
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• 2023

Wearable technology for military applications has received considerable attention as a means of personal status check and monitoring. Among many, an implementation to recognize specific motion states of a human is promising in that allows active management of troops by immediately collecting the operational status and movement status of individual soldiers. In this study, as an extension of military wearable application research, a new ankle wearable device is proposed that can glean the information of a soldier on the battlefield on which action he/she takes in which environment. Presuming a virtual situation, the soldier's upper limbs are easily exposed to uncertainties about circumstances. Therefore, a sensing module is attached to the ankle of the soldier that may always interact with the ground. The obtained data comprises 3-axis accelerations and 3-axis rotational velocities, which cannot be interpreted by hand-made algorithms. In this study, to discern the behavioral characteristics of a human using these dynamic data, a data-driven model is introduced; four features extracted from sliced data (minimum, maximum, mean, and standard deviation) are utilized as an input of the model to learn and classify eight primary military movements (Sitting, Standing, Walking, Running, Ascending, Descending, Low Crawl, and High Crawl). As a result, the proposed device could recognize a movement status of a solider with 95.16% accuracy in an arbitrary test situation. This research is meaningful since an effective way of motion recognition has been introduced that can be furtherly extended to various military applications by incorporating wearable technology and artificial intelligence.

• Journal of Korean Society of Forest Science
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• v.112 no.4
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• pp.451-458
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• 2023

As forest fires continue to increase in scale worldwide, the importance of forest roads in relation to forest fire prevention and suppression has become increasingly evident. To ensure effective functioning during a forest fire disaster, it is crucial to apply appropriate road planning and ensure roads' structural integrity. However, previous studies have predominantly focused on the impact of forest fires on firebreak efficacy and road placement, meaning that insufficient attention has been paid to ensuring the safety of these facilities. Therefore, this study sought to compare the strength of concrete facilities within areas damaged by forest fires over the past three years by using the rebound hammer test to identify signs of thermal degradation. The results revealed that concrete facilities damaged by forest fires exhibited significantly lower strength (15.6 MPa) when compared with undamaged facilities (18.0 MPa) (p<0.001), and this trend was consistent across all the target facilities. Consequently, it is recommended that safety assessment criteria for concrete forest road facilities be established to prevent secondary disasters following forest fire damage. Moreover, continuous monitoring and research involving indoor experiments are imperative in terms of enhancing the stability of forest road structures. It is expected that such research will lead to the development of more effective strategies for forest fire prevention and suppression.

• The Sea:JOURNAL OF THE KOREAN SOCIETY OF OCEANOGRAPHY
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• v.15 no.4
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• pp.192-202
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• 2010

Submarine groundwater discharge (SGD) has been recognized as a provider for freshwater, nutrients, and dissolved constituents from continents to the oceans and paid more attention with regard to the mass balance of water or dissolved constituents on local and global scales. The submarine discharge of fresh groundwater (fresh SGD) through seepage or springs in coastal ocean may be especially important in aspects of water resource and marine environment managements in the future. Based on the worldwide compilations of observed fresh SGD, our review reveals that fresh SGD occurs in various marine environments along most shoreline of the world and the global estimates of fresh SGD were approximately 0.01-17% of surface runoff. In addition, the input of fresh SGD calculated and investigated in this study were about 50%, 57%, 89%, and 420% of total river discharge in Jeju Island, Yeongil Bay, Masan Bay, and Yeoja Bay, respectively. These inputs from fresh SGD along the shoreline of Korea Peninsula are much higher than those of the whole world, greatly vary with the region. However, since these estimates are based on the water balance method mainly used in coastal ocean, we have to perform continuous monitoring of various parameters, such as precipitation, tide, evapotanspiration and water residence time, which have an impact on the water balance in a lot of areas for evaluating the precise input of fresh SGD. In addition, since the method estimating the input of fresh SGD has brought up many problems, it is required to make an intercomparison between various methods such as hydrogeological assumption, numerical modeling, and seepage meter.

• Journal of Internet of Things and Convergence
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• v.10 no.2
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• pp.1-15
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• 2024

The construction of smart communities is a new method and important measure to ensure the security of residential areas. In order to solve the problem of low accuracy in face recognition caused by distorting facial features due to monitoring camera angles and other external factors, this paper proposes the following optimization strategies in designing a face recognition network: firstly, a global graph convolution module is designed to encode facial features as graph nodes, and a multi-scale feature enhancement residual module is designed to extract facial keypoint features in conjunction with the global graph convolution module. Secondly, after obtaining facial keypoints, they are constructed as a directed graph structure, and graph attention mechanisms are used to enhance the representation power of graph features. Finally, tensor computations are performed on the graph features of two faces, and the aggregated features are extracted and discriminated by a fully connected layer to determine whether the individuals' identities are the same. Through various experimental tests, the network designed in this paper achieves an AUC index of 85.65% for facial keypoint localization on the 300W public dataset and 88.92% on a self-built dataset. In terms of face recognition accuracy, the proposed network achieves an accuracy of 83.41% on the IBUG public dataset and 96.74% on a self-built dataset. Experimental results demonstrate that the network designed in this paper exhibits high detection and recognition accuracy for faces in surveillance videos.

• Korean Journal of Construction Engineering and Management
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• v.25 no.3
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• pp.37-46
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• 2024

Recently, 3D laser scanning technology, which can collect accurate and quick information on phenomena, has been attracting attention among smart construction technologies. 3D laser scanning technology can obtain information most similar to reality at construction sites. In this study, we would like to apply a new member identification method to an actual building and present the possibility of applying point cloud data, which can be collected using 3D laser scanning technology, to measuring progress at construction sites. In order to carry out the research, we collected location information for component identification from BIM, set a recognition margin for the collected location information, and proceeded to identify the components that make up the building from point cloud data. Research results We confirmed that the columns, beams, walls, and slabs that make up a building can be identified from point cloud data. The identification results can be used to confirm all the parts that have been completed in the actual building, and can be used in conjunction with the unit price of each part in the project BOQ for prefabricated calculations. In addition, the point cloud data obtained through research can be used as accurate data for quality control monitoring of construction sites and building maintenance management. The research results can contribute to improving the timeliness and accuracy of construction information used in future project applications.

• Journal of Global Scholars of Marketing Science
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• v.19 no.2
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• pp.40-52
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• 2009

Franchising is one of the fastest growing types of business. It is already popular and well-known in the U.S., and has been growing in many other countries including Korea. Furthermore, many Korean franchising companies have expanded their business overseas actively. According to the data by the Ministry of Industry and Resource, 82 companies out of a sample of 500 franchising companies are already operating in many foreign countries and 48% of them have started their foreign business since 2006. This clearly indicates the fast growing current trend of foreign operation by Korean franchising companies. In spite of the fast growing trend of foreign expansion in the industry, academic research on internationalization of franchising companies is extremely difficult to find. Accordingly, academic research on the issue is necessary and urgent in Korea. Among the various research questions on internationalization of franchising business, this study intends to investigate the difference in organizational factors between the franchising companies doing foreign operation and those doing business only domestically. More specifically, this research has the following purposes. First, considering the lack of theoretical basis of previous studies, resource-based theory and agency theory are employed as the theoretical bases. Second, this study explains the difference in internationalization based on organizational factors such as company size, history and growth rate. Third, the five hypotheses regarding the difference in organizational factors are presented and tested empirically, which is the first attempt in the area of this topic. Finally, the study attempts to clarify the conflicting implications among theories regarding some organizational factos such as growth rate. As the theoretical background, resource-based theory and agency theory are discussed. According to resource-based theory, a firm can grow continuously when it has competence and resource, and also the ability to develop them. The competence and resource can include capital, human resource, management skill, market information, ability to manage risk, etc. Meanwhile, agency theory views the relationship between franchisor and franchisee as an agency relationship. In agency theory, bonding capability and monitoring capability are the two key factors which promote internationalization of franchising companies. Based on the two theories, a conceptual model is designed. The model consists of two groups of variables. One is organizational factors including size, history, growth rate, price bonding and geographic dispersion. The other is whether a franchising company is operating overseas or not. We developed the following five research hypotheses basically describing the relationship between organizational factors and internationalization of franchising companies. H1: The size of franchising companies operating overseas is larger than that of franchising companies operating domestically. H2: The history of franchising companies operating overseas is longer than that of franchising companies operating domestically. H3: The growth rate of franchising companies operating overseas is higher than that of franchising companies operating domestically. H4: The price bonding of franchising companies operating overseas is higher than that of franchising companies operating domestically. H5: The geographic dispersion of franchising companies operating overseas is wider than that of franchising companies operating domestically. Data for the analyses are obtained from 2005 Korea Franchise Survey data co-generated by Ministry of Industry and Resource, GS1 Korea, and Korea Franchise Association. Out of 2,804 population companies, 2,489 companies are excluded for various reasons and 315 companies are selected as the final sample. Prior to hypotheses tests, validity and reliability of the measures of size, history, growth rate and price bonding are examined for further analyses. Geographic dispersion is not validated since it is measured using nominal data. A series of independent sample T-tests is used to find out whether there exists any significant difference between the companies internationalized and those operating only domestically for each organizational factor. Among the five factors, size and geographic dispersion show significant difference, growth rate and price bonding do not reveal any difference and, finally, history factor shows conflicting results in the difference depending on how to measure it.