• The Journal of the Korea institute of electronic communication sciences
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• v.17 no.3
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• pp.515-520
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• 2022

In context awareness using multiple sensors, when using sensor data detected and sent by each sensor, it is necessary to give different weights for each sensor. Even if the same type of sensor is configured for the same situation, sometimes it is necessary to assign different weights due to other secondary factors. It is inevitable to assign weights to events in the real world, and it can be said that a weighting method that can be used in a context awareness system using multiple sensors is necessary. In this study, we propose a weighting method for each sensor that reports to the host while the sensors continue to detect over time. In most IoT environments, the sensor continues the detection activity, and when the detected value shows a change pattern beyond a predetermined range, it is basically reported to the host. This can be called a kind of data stream environment. A weighting method was proposed for sensing data from multiple sensors in a data stream environment, and the new weighting method was to select and assign weights to data that indicates a context change in the stream.

• Journal of Food Hygiene and Safety
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• v.36 no.6
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• pp.474-480
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• 2021

Sodium alginate is the sodium salt of alginic acid, commonly used as a food additive for stabilizing, thickening, and emulsifying properties. A relatively simple and universal analysis method is used to study sodium alginate due to the complex pretreatment process and extended analysis time required during the quantitative method. As for the equipment, HPLC-UVD and Unison US-Phenyl column were used for analysis. For the pretreatment condition, a shaking apparatus was used for extraction at 150 rpm for 180 minutes at room temperature. The calibration curve made from the standard sodium alginate solution in 5 concentration ranges showed that the linearity (R²) is 0.9999 on average. LOD and LOQ showed 3.96 mg/kg and 12.0 mg/kg, respectively. Furthermore, the average intraday and inter-day accuracy (%) and precision (RSD%) were 98.47-103.74% and 1.69-3.08% for seaweed jelly noodle samples and 99.95-105.76% and 0.59-3.63% for sherbet samples, respectively. The relative uncertainty value was appropriate for the CODEX standard with 1.5-7.9%. To evaluate the applicability of the method developed in this study, the sodium alginate concentrations of 103 products were quantified. The result showed that the detection rate is highest from starch vermicelli and instant fried noodles to sugar processed products.

• Korean Journal of Agricultural and Forest Meteorology
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• v.24 no.2
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• pp.95-114
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• 2022

This study presented the possibility of automatic frost observation and the related image data acquisition through the design and installation of a Multiple-sensor based Frost Observation System (MFOS). The MFOS is composed of an RGB camera, a thermal camera and a leaf wetness sensor, and each device performs complementary roles. Through the test operation of the equipment before the occurrence of frost, the voltage value of the leaf wetness sensor increased when maintaining high relative humidity in the case of no precipitation. In the case of Gapyeong- gun, the high relative humidity was maintained due to the surrounding agricultural waterways, so the voltage value increased significantly. In the RGB camera image, leaf wetness sensor and the surface were not observed before sunrise and after sunset, but were observed for the rest of the time. In the case of precipitation, the voltage value of the leaf wetness sensor rapidly increased during the precipitation period and decreased after the precipitation was terminated. In the RGB camera image, the leaf wetness sensor and surface were observed regardless of the precipitation phenomenon, but the thermal camera image was taken due to the precipitation phenomenon, but the leaf wetness sensor and surface were not observed. Through, where actual frost occurred, it was confirmed that the voltage value of leaf wetness sensor was higher than the range corresponding to frost, but frost was observed on the surface and equipment surface by the RGB camera.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.40 no.3
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• pp.239-247
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• 2022

Cities are becoming more complex due to rapid industrialization and population growth in modern times. In particular, urban areas are rapidly changing due to housing site development, reconstruction, and demolition. Thus accurate road information is necessary for various purposes, such as High Definition Map for autonomous car driving. In the case of the Republic of Korea, accurate spatial information can be generated by making a map through the existing map production process. However, targeting a large area is limited due to time and money. Road, one of the map elements, is a hub and essential means of transportation that provides many different resources for human civilization. Therefore, it is essential to update road information accurately and quickly. This study uses Semantic Segmentation algorithms Such as LinkNet, D-LinkNet, and NL-LinkNet to extract roads from drone images and then apply hyperparameter optimization to models with the highest performance. As a result, the LinkNet model using pre-trained ResNet-34 as the encoder achieved 85.125 mIoU. Subsequent studies should focus on comparing the results of this study with those of studies using state-of-the-art object detection algorithms or semi-supervised learning-based Semantic Segmentation techniques. The results of this study can be applied to improve the speed of the existing map update process.

• Korean Journal of Remote Sensing
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• v.38 no.6_1
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• pp.1069-1080
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• 2022

The tropospheric ozone is a pollutant that causes a great deal of damage to humans and ecosystems worldwide. In the event that ozone moves downwind from its source, a localized problem becomes a regional and global problem. To enhance ozone monitoring efficiency, geostationary satellites with continuous diurnal observations have been developed. The objective of this study is to derive the Tropospheric Ozone Movement Vector (TOMV) by employing continuous observations of tropospheric ozone from geostationary satellites for the first time in the world. In the absence of Geostationary Environmental Monitoring Satellite (GEMS) tropospheric ozone observation data, the GEOS-Chem model calculated values were used as synthetic data. Comparing TOMV with GEOS-Chem, the TOMV algorithm overestimated wind speed, but it correctly calculated wind direction represented by pollution movement. The ozone influx can also be calculated using the calculated ozone movement speed and direction multiplied by the observed ozone concentration. As an alternative to a backward trajectory method, this approach will provide better forecasting and analysis by monitoring tropospheric ozone inflow characteristics on a continuous basis. However, if the boundary of the ozone distribution is unclear, motion detection may not be accurate. In spite of this, the TOMV method may prove useful for monitoring and forecasting pollution based on geostationary environmental satellites in the future.

• Journal of Korean Neurosurgical Society
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• v.65 no.6
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• pp.790-800
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• 2022

Objective : EID3 (EP300-interacting inhibitor of differentiation) was identified as a novel member of EID family and plays a pivotal role in colorectal cancer development. However, its role in glioma remained elusive. In current study, we identified EID3 as a novel oncogenic molecule in human glioma and is critical for glioma cell survival, proliferation and invasion. Methods : A total of five patients with glioma were recruited in present study and fresh glioma samples were removed from patients. Four weeks old male non-obese diabetic severe combined immune deficiency (NOD/SCID) mice were used as transplant recipient models. The subcutaneous tumor size was calculated and recorded every week with vernier caliper. EID3 and AMP-activated protein kinase α1 (AMPKα1) expression levels were confirmed by real-time polymerase chain reaction and Western blot assays. Colony formation assays were performed to evaluate cell proliferation. Methyl thiazolyl tetrazolium (MTT) assays were performed for cell viability assessment. Trypan blue staining approach was applied for cell death assessment. Cell Apoptosis DNA ELISA Detection Kit was used for apoptosis assessment. Results : EID3 was preferentially expressed in glioma tissues/cells, while undetectable in astrocytes, neuronal cells, or normal brain tissues. EID3 knocking down significantly hindered glioma cell proliferation and invasion, as well as induced reduction of cell viability, apoptosis and cell death. EID3 knocking down also greatly inhibited tumor growth in SCID mice. Knocking down of AMPKα1 could effectively rescue glioma cells from apoptosis and cell death caused by EID3 absence, indicating that AMPKα1 acted as a key downstream regulator of EID3 and mediated suppression effects caused by EID3 knocking down inhibition. These findings were confirmed in glioma cells generated patient-derived xenograft models. AMPKα1 protein levels were affected by MG132 treatment in glioma, which suggested EID3 might down regulate AMPKα1 through protein degradation. Conclusion : Collectively, our study demonstrated that EID3 promoted glioma cell proliferation and survival by inhibiting AMPKα1 expression. Targeting EID3 might represent a promising strategy for treating glioma.

• The Journal of the Korea Contents Association
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• v.22 no.3
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• pp.71-80
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• 2022

In the past, fish diseases were bacterial in aqua farms, but in recent years, the frequency of fish diseases has increased as they have become viral and mixed. Viral diseases in an enclosed space called a aqua farm have a high spread rate, so it is very likely to lead to mass death. Fast identification of fish diseases is important to prevent group death. However, diagnosis of fish diseases requires a high level of expertise and it is difficult to visually check the condition of fish every time. In order to prevent the spread of the disease, an automatic identification system of diseases or fish is needed. In this paper, in order to improve the performance of the disease identification system of Paralichthys olivaceus based on deep learning, the existing pre-processing method is compared and tested. Target diseases were selected from three most frequent diseases such as Scutica, Vibrio, and Lymphocystis in Paralichthys olivaceus. The RGB, HLS, HSV, LAB, LUV, XYZ, and YCRCV were used as image pre-processing methods. As a result of the experiment, HLS was able to get the best results than using general RGB. It is expected that the fish disease identification system can be advanced by improving the recognition rate of diseases in a simple way.

• Journal of Internet Computing and Services
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• v.23 no.5
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• pp.69-78
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• 2022

As the use of Internet of Things (IoT) devices has expanded, digital forensics coverage of the National Police Agency has expanded to smart home areas. Accordingly, most of the existing studies conducted to acquire smart home platform data were mainly conducted to analyze local data of mobile devices and analyze network perspectives. However, meaningful data for evidence analysis is mainly stored on cloud storage on smart home platforms. Therefore, in this paper, we study how to acquire stored in the cloud in a Hey Home Air environment by extracting accessToken of user accounts through a cookie database of browsers such as Microsoft Edge, Google Chrome, Mozilia Firefox, and Opera, which are recorded on a PC when users use the Hey Home app-based "Hey Home Square" service. In this paper, the it was configured with smart temperature and humidity sensors, smart door sensors, and smart motion sensors, and artifacts such as temperature and humidity data by date and place, device list used, and motion detection records were collected. Information such as temperature and humidity at the time of the incident can be seen from the results of the artifact analysis and can be used in the forensic investigation process. In addition, the cloud data acquisition method using OpenAPI proposed in this paper excludes the possibility of modulation during the data collection process and uses the API method, so it follows the principle of integrity and reproducibility, which are the principles of digital forensics.

• Therapeutic Science for Rehabilitation
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• v.11 no.2
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• pp.39-51
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• 2022

Objective : This study aimed to investigate the awareness and experience of community-based dysphagia therapy and related education in community-dwelling older adults. Methods : A total of 89 older adults were recruited from a public health center in Gyeonggi-do. Awareness, experience, and related education regarding community-based dysphagia therapy were analyzed using descriptive statistics. Results : We analyzed 89 questionnaires. Awareness, treatment experience, and education regarding dysphagia were low; however, the importance and intention to participate were high. Respondents wanted education about proper chewing and safe swallowing, oral health, oral motor exercise, and participation in community-based dysphagia programs in public health centers. The reason for the lack of experience in dysphagia education and therapy is insufficient information and opportunities. The respondents had a good understanding of dysphagia symptoms. Conclusion : Dysphagia therapy maintains swallowing and eating functions as a life-long Activity of Daily Living, and is a very important area in community rehabilitation. Based on the results of this survey, the necessity and importance of community-based dysphagia were identified. It is time to provide correct information and develop a systematic education program for community-based dysphagia therapy. Occupational therapists need to play an active role in improving quality of life by early detection and providing proper intervention.

• Journal of the Society of Cosmetic Scientists of Korea
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• v.48 no.4
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• pp.321-330
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• 2022

This study attempted to establish an optimal multi-compound simultaneous analysis method that can secure reliable results for 15 - preservatives, 2 - sun screens and 1 - antioxidants of cosmetics using HPLC-PDA. Since the potential of hydrogen (pH) in the mobile phase affects the acid dissociation constant (pKa) of the preservatives, and the peak retention time shift and area change were observed. The peak separation condition was established by adjusting the pH to 0.1% H₃PO₄ addition (mL) when preparing the mobile phase. As a results of method validation, the linearity correlation coefficient (R²) of above 0.999 were obtained, and accuracy 87.9 ~ 101.1%, 0.1 ~ 7.6% precision for two types of cosmetics (cream and shampoo). It was found that the limit of detection (LOD) was 0.1 ~ 0.2 mg/kg and the limit of quantitation (LOQ) was 2.0 ~ 4.0 mg/kg. In addition, it was possible to simultaneously separate p-anisic acid, a natural compound that was difficult to separate in HPLC due to the small difference from methylparaben, a synthetic preservatives. Through this study, it will be effectively used to secure quality control and safety for compound that need restrictions on use cosmetics.