• Korea Journal of Hospital Management
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• v.28 no.1
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• pp.24-36
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• 2023

Purposes: The purpose of this study was to analyze the factors associated with current smoking status in Wonju-si and Chuncheon-si, and to study the cause of difference in smoking rates between these two regions. Methodology: Data was from the National Health Insurance Service database from 2019 to 2020. Current smoking status was based on the response to the health examination questionnaire. Logistic regression analysis was conducted to identify factors associated with current smoking status. The study included 207,307 individuals from Wonju-si and 173,698 individuals from Chuncheon-si. Findings: The smoking rate of Wonju-si was 19.83%, and Chuncheon-si was 18.20%, showing a difference in the smoking rates between the two regions. Logistic regression analysis found that men, those aged 40-49, being a self-employed insured, a medical-aid beneficiary, having a lower income, working in construction, transport, storage, communication, or manufacturing industries, having a high-risk drinking level and being underweight were significantly associated with a higher likelihood of smoking(p<0.05). Additionally, having a chronic disease was associated with a lower likelihood of smoking in the case of Chuncheon-si(p<0.05). Practical Implication: This study found the differences of factors associated with smoking rates between the two regions and could provide implications for establishing intervention programs or policies that could contribute to lowering the smoking rate in areas with high smoking rates.

• Journal of the Korea Society of Computer and Information
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• v.14 no.8
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• pp.127-136
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• 2009

Voice of the customer(VOC) is a term used in business and information technology(IT) to describe the process of capturing a customer's requirements in enterprises or various organizations. Recently, in order to satisfy customer's needs, enterprises try to utilize VOC at recurrence prevention of problems and their improvement activities, planning and development of product/service by processing, storing, and analyzing VOC. Until now, VOC management systems are introduced around service industries such as hotel business and insurance/financial business, etc. This paper proposes an integrated management scheme of VOC which are captured by various communication channels and describes a case of implementing an integrated VOC management system on the basis of the proposed scheme for the large-scale manufacturing company. By the implemented system, VOC are stored and utilized as the important knowledge assets of enterprises.

• Korean Journal of Agricultural Science
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• v.48 no.4
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• pp.703-718
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• 2021

An irrigation monitoring system is an efficient approach to save water and to provide effective irrigation scheduling for rice cultivation in desert soils. This research aimed to design, fabricate, and evaluate the basic performance of an irrigation monitoring system based on information and communication technology (ICT) for rice cultivation under drip and micro-sprinkler irrigation in desert soils using a Raspberry Pi. A data acquisition system was installed and tested inside a rice cultivating net house at the United Arab Emirates University, Al-Foah, Al-Ain. The Raspberry Pi operating system was used to control the irrigation and to monitor the soil water content, ambient temperature, humidity, and light intensity inside the net house. Soil water content sensors were placed in the desert soil at depths of 10, 20, 30, 40, and 50 cm. A sensor-based automatic irrigation logic circuit was used to control the actuators and to manage the crop irrigation operations depending on the soil water content requirements. A developed webserver was used to store the sensor data and update the actuator status by communicating via the Pi-embedded Wi-Fi network. The maximum and minimum average soil water contents, ambient temperatures, humidity levels, and light intensity values were monitored as 33.91 ± 2 to 26.95 ± 1%, 45 ± 3 to 24 ± 3℃, 58 ± 2 to 50 ± 4%, and 7160-90 lx, respectively, during the experimental period. The ICT-based monitoring system ensured precise irrigation scheduling and better performance to provide an adequate water supply and information about the ambient environment.

• Proceedings of the Korea Water Resources Association Conference
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• 2021.06a
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• pp.455-455
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• 2021

The Life Cycle Assessment (LCA) as an environmental impact assessment tool has received increasing attention over the years. Unlike the water footprint (WF) and carbon footprint (CF) assessments whose focus is only on a single environmental aspect, the LCA systematically analyzes the different impacts along the entire life cycle, making possible the identification of potential environmental tradeoffs. In Korea, LCA has drawn much attention from both industry and academia since the mid-90s. However, the level of Korea-related LCA studies with respect to different sectors in the past 20 years has not been analyzed. This study, therefore, sought to assess the status of environmental Life Cycle Assessment (LCA) studies in Korea, with a view to understanding the current level of sustainability reporting and identify potential research gaps. Online searches of English written articles published between 2000 and 2019 were conducted on Google, Google scholar, Scopus, and Web of Science databases using the Keywords "life cycle assessment", "lca", and "Korea." At the end of the search, about 88 LCA related studies were identified for Korea within the study period. Majority of these studies focused on the construction (49%) and energy (31%) sectors with fewer environmental studies on the transportation (9%), manufacturing (8%), agriculture (2%), and information and communication (1%) industries. Based on publication trend, results show that LCA studies in Korea have been on the rise in the past 20 years, even though the number of publications has not followed a constant pace. In comparison with the economic sectors of the country, reports show an inadequacy in the coverage of major industries of growing economic relevance like the tourism, health, and agriculture, suggesting a need to further increase and improve LCA related studies in these sectors.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2021.10a
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• pp.208-210
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• 2021

As the number of objects connected to the Internet increases rapidly, intelligent device development projects are gradually expanding that provide direct value to humans, away from simple monitoring functions, including sensors and communication functions, or delivery to servers.It is expected that the device will develop a technology that analyzes surrounding sensing information and changes the surrounding environment in consideration of users' preferences or safety. By establishing a biosignal measurement system in a developed product that can bring various effects using air, it will be possible to grasp the user's condition through a pattern of change in pressure distribution when seated. This paper proposes a construction system that enhances the comfort of using an air car seat through contact between a temperature measurement sensor and a user, and enables effective management of measured biosignals by linking them with an air pump control system.

• KIPS Transactions on Computer and Communication Systems
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• v.12 no.12
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• pp.357-362
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• 2023

Bridges are important transportation infrastructure, but they are subject to damage and cracking due to various environmental factors and constant traffic loads, which accelerate their aging. With many bridges now older than their original construction, there is a need for systems to ensure safety and diagnose deterioration. Bridges are already utilizing structural health monitoring (SHM) technology to monitor the condition of bridges in real time or periodically. Along with this technology, the development of intelligent bridge monitoring technology utilizing artificial intelligence and Internet of Things technology is underway. In this paper, we study an edge system technique for predicting bridge safety using fast Fourier transform and dimensionality reduction algorithm for maintenance of aging bridges. In particular, unlike previous studies, we investigate whether it is possible to form a dataset using sensor data collected from actual bridges and check the safety of bridges.

• International journal of advanced smart convergence
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• v.12 no.4
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• pp.208-216
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• 2023

The purpose of our study is to design datasets for Artificial Intelligence learning for cold sea fish farming. Salmon is considered one of the most popular fish species among men and women of all ages, but most supplies depend on imports. Recently, salmon farming, which is rapidly emerging as a specialized industry in Gangwon-do, has attracted attention. Therefore, in order to successfully develop salmon farming, the need to systematically build data related to salmon and salmon farming and use it to develop aquaculture techniques is raised. Meanwhile, the catch of pollack continues to decrease. Efforts should be made to improve the major factors affecting pollack survival based on data, as well as increasing the discharge volume for resource recovery. To this end, it is necessary to systematically collect and analyze data related to pollack catch and ecology to prepare a sustainable resource management strategy. Image data was obtained using CCTV and underwater cameras to establish an intelligent aquaculture strategy for salmon and pollock, which are considered representative fish species in Gangwon-do. Using these data, we built learning data suitable for AI analysis and prediction. Such data construction can be used to develop models for predicting the growth of salmon and pollack, and to develop algorithms for AI services that can predict water temperature, one of the key variables that determine the survival rate of pollack. This in turn will enable intelligent aquaculture and resource management taking into account the ecological characteristics of fish species. These studies look forward to achievements on an important level for sustainable fisheries and fisheries resource management.

• Earthquakes and Structures
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• v.26 no.5
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• pp.349-361
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• 2024

Excessive torsional behaviour is one of the major reasons for failure of buildings, as inferred from past earthquakes. Numerous seismic codes across the world specify a displacement-based or drift-based criterion for classifying buildings as torsionally irregular. In recent years, quite a few researchers have pointed out some of the inherent deficiencies associated with the current codal guidelines on torsional irregularity. This short communication paper aims to envisage the need for a revision of the displacement-based guidelines on torsional irregularity, and further highlight the appropriateness of a rotation-based criterion. A set of 6 reinforced concrete building models with asymmetric shear walls are analysed using ETABS v18.0.2, by varying the number of stories from 1 to 9, and the torsional irregularity coefficient of various stories is calculated using the displacement-based formula. Since rotation about the vertical axis is a direct indication of the twist experienced by a building, the calculated torsional irregularity coefficients of all stories are compared with the corresponding floor rotations. The conflicting results obtained for the torsional irregularity coefficients are projected through five categories, namely mismatch with floor rotations, inconsistency in trend, lack of clarity in incorporation of negative values, sensitivity to low values of displacement and error conceived in the mathematical formulation. The findings indicate that the irregularity coefficient does not accurately represent the torsional behaviour of buildings in a realistic sense. The Indian seismic code-based values of 1.2 and 1.4, which are used to characterize buildings as torsionally irregular are observed to be highly sensitive to the numerical values of displacements, rather than the actual degree of rotation. The study thus emphasizes the revision of current guidelines based on a more relevant rotation-based or eccentricity-based approach.

• Geomechanics and Engineering
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• v.37 no.1
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• pp.65-72
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• 2024

Water ingress poses a common and intricate geological hazard with profound implications for tunnel construction's speed and safety. The project's success hinges significantly on the precision of estimating water inflow during excavation, a critical factor in early-stage decision-making during conception and design. This article introduces an optimized model employing the gene expression programming (GEP) approach to forecast tunnel water inflow. The GEP model was refined by developing an equation that best aligns with predictive outcomes. The equation's outputs were compared with measured data and assessed against practical scenarios to validate its potential applicability in calculating tunnel water input. The optimized GEP model excelled in forecasting tunnel water inflow, outperforming alternative machine learning algorithms like SVR, GPR, DT, and KNN. This positions the GEP model as a leading choice for accurate and superior predictions. A state-of-the-art machine learning-based graphical user interface (GUI) was innovatively crafted for predicting and visualizing tunnel water inflow. This cutting-edge tool leverages ML algorithms, marking a substantial advancement in tunneling prediction technologies, providing accuracy and accessibility in water inflow projections.

• International Journal of Computer Science & Network Security
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• v.23 no.12
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• pp.137-144
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• 2023

The relevance of the research topic lies in the necessity to use social networks as innovative tools of marketing communications. A wide audience and the ability to segment the market for a specific consumer determine the construction of a corporate strategy, which will be based on using the social networking approach. The spread of the global coronavirus pandemic has led to the rapid development of remote communication channels between the company and the customer. The issue of using marketing tools in social networks acquires the most urgent importance in the modern world of the introduction and implementation of the company's marketing strategies. The purpose of the academic paper is to study the use of social networks as features of implementing the marketing campaign. Social networks are the result of the development of digital technologies and the processes of creating an information society involved in the digital space. The objectives of the research are to analyse the opportunity of using social networks as a tool for marketing communications and their implementation at the level of its widespread use by enterprises and establishments. It is significant to create an advertising campaign by defining the target audience and outlining the key aspects, on which the company is focused. The research methodology consists in determining the theoretical and methodological approaches to the essence of introducing social networks and their practical importance in the implementation of marketing activities of companies. The obtained results can significantly improve the quality of functioning of modern enterprises and organizations that plan to master a new market segment or gain competitive advantages in the existing one. The academic paper examines the essence of social networks as a tool of marketing communications. The key principles of the development of digital social platforms were revealed. The quality of implementing the advertising campaign in the social network was studied, and further prospects for the development of using social networks as a component of the marketing strategy were outlined. Therefore, the academic paper analyses the problems of using social networks as a marketing tool.