• The Journal of the Korea institute of electronic communication sciences
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• v.19 no.5
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• pp.1035-1040
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• 2024

The main objective of inspecting structures is to ensure the safety of all entities that utilize these structures as cracks in structures if not attended to could lead to serious calamities. With that objective in mind, artificial intelligence (AI) based technologies to assist human inspectors are needed especially for retaining walls in structures. In this paper, we predict the crack displacement of retaining walls using an Polynomial Regressive (PR) analysis model, as well as Long Short Term Memory (LSTM) and Gated Recurrent Unit (GRU) deep learning models, and compare their performance. For the performance comparison, we apply multi-variable feature inputs, by utilizing temperature and rainfall data that may affect the crack displacement of the retaining wall. The training and inference data were collected through measuring sensors such as inclinometers, thermometers, and rain gauges. The results show that the multi-variable feature model had a MAE of 0.00186, 0.00450 and 0.00842, which outperformed the single variable feature model at 0.00393, 0.00556 and 0.00929 for the polynomial regression model, LSTM model and the GRU model respectively from the evaluation performed.

• Journal of Internet of Things and Convergence
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• v.10 no.4
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• pp.35-41
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• 2024

Due to increasingly busy lifestyles, sleep time is gradually being reduced, leading to a growing interest in effective sleep methods. Traditional alarms that only ring at a set time can disrupt efficient sleep and increase fatigue. To solve this problem, a smart alarm system utilizing Raspberry Pi has been proposed. The proposed alarm not only rings at a preset time, like conventional alarms, but also helps by using an infrared sensor attached to the Raspberry Pi to detect the user's sleep onset time and calculate the optimal sleep duration, setting the alarm accordingly. Additionally, it allows for easy naps during the day by setting a fixed nap time. This Smart Alarm system was implemented using MIT App Inventor. The proposed Smart Alarm system is expected to contribute to more efficient sleep.

• Journal of the Korean Association of Geographic Information Studies
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• v.13 no.4
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• pp.111-124
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• 2010

To monitor the environment of land surface change is considered as an important research field since those parameters are related with land use, climate change, meteorological study, agriculture modulation, surface energy balance, and surface environment system. For the change detection, many different methods have been presented for distributing more detailed information with various tools from ground based measurement to satellite multi-spectral sensor. Recently, using high resolution satellite data is considered the most efficient way to monitor extensive land environmental system especially for higher spatial and temporal resolution. In this study, we use two different spatial resolution satellites; the one is SPOT/VEGETATION with 1 km spatial resolution to detect coarse resolution of the area change and determine objective threshold. The other is Landsat satellite having high resolution to figure out detailed land environmental change. According to their spatial resolution, they show different observation characteristics such as repeat cycle, and the global coverage. By correlating two kinds of satellites, we can detect land surface change from mid resolution to high resolution. The K-mean clustering algorithm is applied to detect changed area with two different temporal images. When using solar spectral band, there are complicate surface reflectance scattering characteristics which make surface change detection difficult. That effect would be leading serious problems when interpreting surface characteristics. For example, in spite of constant their own surface reflectance value, it could be changed according to solar, and sensor relative observation location. To reduce those affects, in this study, long-term Normalized Difference Vegetation Index (NDVI) with solar spectral channels performed for atmospheric and bi-directional correction from SPOT/VEGETATION data are utilized to offer objective threshold value for detecting land surface change, since that NDVI has less sensitivity for solar geometry than solar channel. The surface change detection based on long-term NDVI shows improved results than when only using Landsat.

• KOREAN JOURNAL OF PACKAGING SCIENCE & TECHNOLOGY
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• v.25 no.3
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• pp.79-87
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• 2019

The degree of cosmetic's oxidation depends on the storage conditions and external conditions when using the product. The microbial contamination and oxygen exposure often results in the quality deterioration of cosmetics. In addition, the problem is that consumers often use cream-type cosmetics, which have short expiration period (6-12 months), even after the product is expired. When using the deteriorated cosmetics, it can be fatal to consumers' safety including some symptoms such as folliculitis, rashes, edema, and dermatitis. Therefore, it is necessary to develop sealed smart packaging for cosmetics to prevent the deterioration of cosmetics and improve consumer safety. In this study, we have developed smart packaging design for cosmetics that can measure the surrounding environment and expiration date for the cosmetics in the real time. In addition, the smart packaging includes sensor, which are linked to the mobile application. Users can find out the measurement results through the application. Also, the packaging design and functions were set up based on the survey results by the user and feasible model can be produced based on user choice. The measurement in the three environment has been done after manufactured the sensor, PCB, and mobile application. As a result, it works normally within a certain range under all three environmental conditions. It is believed that the information on expiration dates and storage environment can be efficiently delivered to the consumers through developed cosmetics smart packaging and applications. The development of UI/UX design for consumer is further studied. The UX/UI design of the application plays an essential role in achieving this goal through the commercialization the cosmetic products in the wide range.

• Journal of Mushroom
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• v.17 no.4
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• pp.211-217
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• 2019

Currently, cultivation of mushrooms using the Information and Communication Technology (ICT)-based smart farming technique is increasing rapidly. The main environmental factors for growth of mushrooms are temperature, humidity, carbon dioxide (CO₂), and light. Among all the mentioned factors, currently, only temperature has been maintained under automatic control. However, humidity and ventilation are controlled using a timer, based on technical experience.Therefore, in this study, a Pleurotus eryngii first-generation smart farm model was set up that can automatically control temperature, humidity, and ventilation. After installing the environmental control system and the monitoring device, the environmental condition of the mushroom cultivation room and the growth of the fruiting bodies were studied. The data thus obtained was compared to that obtained using the conventional cultivation method.In farm A, the temperature during the primordia formation stage was about 17℃, and was maintained at approximately 16℃ during the fruiting stage. The humidity was initially maintained at 95%, and the farm was not humidified after the primordia formation stage. There was no sensor for CO₂ management, and the system was ventilated as required by observing the shape of the pileus and the stipe. It was observed that, the concentration of CO₂ was between 700 and 2,500 ppm during the growth period. The average weight of the mushrooms produced in farm A was 125 g, and the quality was between that of the premium and the first grade.In farm B. The CO₂ sensor was in use for measurement purposes only; the system was ventilated as required by observing the shape of the pileus and the stipe. During the growth period, the CO₂ concentration was observed to be between 640 and 4,500 ppm. The average weight of the mushrooms produced in farm B was 102 g.These results indicate that the quality of the king oyster mushroom is determined by the environmental conditions, especially by the concentration of CO₂. Thus, the data obtained in this study can be used as an optimal smart farm model, where, by improving the environmental control method of farm A, better quality mushrooms were obtained.

• Economic and Environmental Geology
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• v.54 no.3
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• pp.399-408
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• 2021

Natural soil was artificially contaminated with heavy metals (Cd, Pb, and Zn), and the movement of earthworm was characterized in real time using the ViSSET system composed of vibration sensor and the other components. The manifestation mechanism of ecological toxicity of heavy metals was interpreted based on the accumulative frequency of earthworm movement obtained from the real-time monitoring as well as the conventional indices of earthworm behavior, such as the change in body weight before and after tests and biocumulative concentrations of each contaminant. The results showed the difference in the earthworm movement according to the species of heavy metal contaminants. In the case of Cd, the earthworm movement was decreased with increasing its concentration and then tended to be increased. The activity of earthworm was severely increased with increasing Pb concentration, but the movement of earthworm was gradually decreased with increasing Zn concentration. The body weight of earthworm was proved to be greatly decreased in the Zn-contaminated soil, but it was similarly decreased in Cd- and Pb-contaminated soils. The bioaccumulation factor (BAF) was higher in the sequence of Cd > Zn > Pb, and particularly the biocumulative concentration of Pb did not show a clear tendency according to the Pb concentrations in soil. It was speculated that Cd is accumulated as a metallothionein-bound form in the interior of earthworm for a long time. In particular, Cd has a bad influence on the earthworm through the critical effect at its higher concentrations. Pb was likely to reveal its ecotoxicity via skin irritation or injury of sensory organs rather than ingestion pathway. The ecotoxicity of Zn seemed to be manifested by damaging the cell membranes of digestive organs or inordinately activating metabolism. Based on the results of real-time monitoring of earthworm movement, the half maximal effective concentration (EC50) of Pb was estimated to be 751.2 mg/kg, and it was similar to previously-reported ones. The study confirmed that if the conventional indices of earthworm behavior are combined with the results of newly-proposed method, the mechanism of toxicity manifestation of heavy metal contaminants in soils is more clearly interpreted.

• Journal of the Korean Association of Geographic Information Studies
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• v.25 no.1
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• pp.101-119
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• 2022

Existing algal bloom monitoring is based on field sampling, and there is a limit to understanding the spatial distribution of algal blooms, such as the occurrence and spread of algae, due to local investigations. In this study, algal bloom monitoring was performed using an unmanned aerial vehicle and multispectral sensor, and data on the distribution of algae were provided. For the algal bloom monitoring site, data were acquired from the Mulgeum·Mae-ri site located in the lower part of the Nakdong River, which is the areas with frequent algal bloom. The Chlorophyll-a(Chl-a) value of field-collected samples and the Chl-a estimation formula derived from the correlation between the spectral indices were comparatively analyzed. As a result, among the spectral indices, Maximum Chlorophyll Index (MCI) showed the highest statistical significance(R²=0.91, RMSE=8.1mg/m³). As a result of mapping the distribution of algae by applying MCI to the image of August 05, 2021 with the highest Chl-a concentration, the river area was 1.7km², the Warning area among the indicators of the algal bloom warning system was 1.03km²(60.56%) and the Algal Bloom area occupied 0.67km²(39.43%). In addition, as a result of calculating the number of occurrence days in the area corresponding to the "Warning" in the images during the study period (July 01, 2021~November 01, 2021), the Chl-a concentration above the "Warning" level was observed in the entire river section from 12 to 19 times. The algal bloom monitoring method proposed in this study can supplement the limitations of the existing algal bloom warning system and can be used to provide information on a point-by-point basis as well as information on a spatial range of the algal bloom warning area.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.17 no.4
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• pp.193-204
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• 2022

This study analyzed the degree of influence of measurement and improvement of customer satisfaction level targeting kiosk users. In modern times, due to the development of technology and the improvement of the online environment, the probability that simple labor tasks will disappear after 10 years is close to 90%. Even in domestic research, it is predicted that 'simple labor jobs' will disappear due to the influence of advanced technology with a probability of about 36%. there is. In particular, as the demand for non-face-to-face services increases due to the Corona 19 virus, which is recently spreading globally, the trend of introducing kiosks has accelerated, and the global market will grow to 83.5 billion won in 2021, showing an average annual growth rate of 8.9%. there is. However, due to the unmanned nature of these kiosks, some consumers still have difficulties in using them, and consumers who are not familiar with the use of these technologies have a negative attitude towards service co-producers due to rejection of non-face-to-face services and anxiety about service errors. Lack of understanding leads to role conflicts between sales clerks and consumers, or inequality is being created in terms of service provision and generations accustomed to using technology. In addition, since kiosk is a representative technology-based self-service industry, if the user feels uncomfortable or requires additional labor, the overall service value decreases and the growth of the kiosk industry itself can be suppressed. It is important. Therefore, interviews were conducted on the main points of direct use with actual users centered on display color scheme, text size, device design, device size, internal UI (interface), amount of information, recognition sensor (barcode, NFC, etc.), Display brightness, self-event, and reaction speed items were extracted. Afterwards, using the questionnaire, the Kano model quality attribute classification of each expected evaluation item was carried out, and Timko's customer satisfaction coefficient, which can be calculated with accurate numerical values The PCSI Index analysis was additionally performed to determine the improvement priorities by finally classifying the improvement impact of the kiosk expected evaluation items through research. As a result, the impact of improvement appears in the order of internal UI (interface), text size, recognition sensor (barcode, NFC, etc.), reaction speed, self-event, display brightness, amount of information, device size, device design, and display color scheme. Through this, we intend to contribute to a comprehensive comparison of kiosk-based research in each field and to set the direction for improvement in the venture industry.

• Journal of Internet Computing and Services
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• v.14 no.5
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• pp.69-76
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• 2013

The incidence of globally infectious and pathogenic diseases such as H1N1 (swine flu) and Avian Influenza (AI) has recently increased. An infectious disease is a pathogen-caused disease, which can be passed from the infected person to the susceptible host. Pathogens of infectious diseases, which are bacillus, spirochaeta, rickettsia, virus, fungus, and parasite, etc., cause various symptoms such as respiratory disease, gastrointestinal disease, liver disease, and acute febrile illness. They can be spread through various means such as food, water, insect, breathing and contact with other persons. Recently, most countries around the world use a mathematical model to predict and prepare for the spread of infectious diseases. In a modern society, however, infectious diseases are spread in a fast and complicated manner because of rapid development of transportation (both ground and underground). Therefore, we do not have enough time to predict the fast spreading and complicated infectious diseases. Therefore, new system, which can prevent the spread of infectious diseases by predicting its pathway, needs to be developed. In this study, to solve this kind of problem, an integrated monitoring system, which can track and predict the pathway of infectious diseases for its realtime monitoring and control, is developed. This system is implemented based on the conventional mathematical model called by 'Susceptible-Infectious-Recovered (SIR) Model.' The proposed model has characteristics that both inter- and intra-city modes of transportation to express interpersonal contact (i.e., migration flow) are considered. They include the means of transportation such as bus, train, car and airplane. Also, modified real data according to the geographical characteristics of Korea are employed to reflect realistic circumstances of possible disease spreading in Korea. We can predict where and when vaccination needs to be performed by parameters control in this model. The simulation includes several assumptions and scenarios. Using the data of Statistics Korea, five major cities, which are assumed to have the most population migration have been chosen; Seoul, Incheon (Incheon International Airport), Gangneung, Pyeongchang and Wonju. It was assumed that the cities were connected in one network, and infectious disease was spread through denoted transportation methods only. In terms of traffic volume, daily traffic volume was obtained from Korean Statistical Information Service (KOSIS). In addition, the population of each city was acquired from Statistics Korea. Moreover, data on H1N1 (swine flu) were provided by Korea Centers for Disease Control and Prevention, and air transport statistics were obtained from Aeronautical Information Portal System. As mentioned above, daily traffic volume, population statistics, H1N1 (swine flu) and air transport statistics data have been adjusted in consideration of the current conditions in Korea and several realistic assumptions and scenarios. Three scenarios (occurrence of H1N1 in Incheon International Airport, not-vaccinated in all cities and vaccinated in Seoul and Pyeongchang respectively) were simulated, and the number of days taken for the number of the infected to reach its peak and proportion of Infectious (I) were compared. According to the simulation, the number of days was the fastest in Seoul with 37 days and the slowest in Pyeongchang with 43 days when vaccination was not considered. In terms of the proportion of I, Seoul was the highest while Pyeongchang was the lowest. When they were vaccinated in Seoul, the number of days taken for the number of the infected to reach at its peak was the fastest in Seoul with 37 days and the slowest in Pyeongchang with 43 days. In terms of the proportion of I, Gangneung was the highest while Pyeongchang was the lowest. When they were vaccinated in Pyeongchang, the number of days was the fastest in Seoul with 37 days and the slowest in Pyeongchang with 43 days. In terms of the proportion of I, Gangneung was the highest while Pyeongchang was the lowest. Based on the results above, it has been confirmed that H1N1, upon the first occurrence, is proportionally spread by the traffic volume in each city. Because the infection pathway is different by the traffic volume in each city, therefore, it is possible to come up with a preventive measurement against infectious disease by tracking and predicting its pathway through the analysis of traffic volume.

• Korean Journal of Optics and Photonics
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• v.19 no.6
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• pp.416-421
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• 2008

A scheme for predicting the concentration of a glucose solution based on its relative optical absorbance at multiple probe wavelengths was proposed and verified. The relative absorbance at each of the probe wavelength was obtained with respect to the absorbance at a reference wavelength. The single reference wavelength (1310 nm) and a group of four different probe wavelengths (1064, 1550, 1685, 1798 nm) were selected to exhibit the glucose absorbance with opposite signs, thereby enhancing the accuracy of the prediction. The final glucose concentration was estimated by taking the average of the predicted values provided by the four probe wavelengths. The absorbance of the glucose solution for the path length of 5 mm was $-1.42{\times}10^{-6}\;AU$/(mg/dL) at the reference wavelength of 1310 nm and peaked at $+8.12{\times}10^{-6}\;AU$/(mg/dL) at 1685 nm. The concentration of the glucose solution was decently predicted by means of the proposed scheme with the standard error of prediction of ${\sim}28\;mg/dL$. In addition, the influence of the ambient temperature and the fat thickness upon the prediction of the glucose concentration was examined. The absorption change with the temperature was $-9.1{\times}10^{-5}\;AU/^{\circ}C$ in the temperature range of $26{\sim}40^{\circ}C$ at the reference wavelength, and $-2.08{\times}10^{-2}\;AU/^{\circ}C$ at 1550 nm. And the absorption change with respect to the fat thickness was +1.093 AU/mm at the probe wavelength of 1685 nm.