Along with the aging of the population, the number of dementia patients is increasing, and the social and economic burden is also increasing. Currently, the effective way to manage dementia patients is to identify patients with dementia early. However, in rural and island areas where medical staff are scarce, there is a problem that it is difficult to visit a hospital and get an early examination. Therefore, we propose a remote early detection system for dementia to solve the problems. The remote dementia early diagnosis system is a system that allows a patient to receive examination and treatment from a remote dementia expert using remote medical technology based on real-time image communication. The remote early diagnosis system for dementia consists of a local client system used by medical staff at health centers in the island, an image server that transmits, stores and manages images, and an expert client used by remote dementia experts. The local client subsystem satisfies the current medical law's remote collaboration by allowing the patient to use it with the health center's medical staff. In addition, expert clients are used by dementia experts, and can store/manage patient information, analyze patient history information, and predict the degree of dementia progression in the future.
The Journal of the Institute of Internet, Broadcasting and Communication
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v.20
no.6
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pp.85-91
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2020
Recently, video-taping equipment such as CCTV have been seeing more use for crime prevention and general safety concerns. Since these video-taping equipment operates all throughout the day, the need for security personnel is lessened, and naturally costs incurred from managing such manpower should also decrease. However, technology currently used predominantly lacks self-sufficiency when given the task of searching for a specific object in the recorded video such as a person, and has to be done manually; current security-based video equipment is insufficient in an environment where real-time information retrieval is required. In this paper, we propose a technology that uses the latest deep-learning technology and OpenCV library to quickly search for a specific person in a video; the search is based on the clothing information that is inputted by the user and transmits the result in real time. We implemented our system to automatically recognize specific human objects in real time by using the YOLO library, whilst deep learning technology is used to classify human clothes into top/bottom clothes. Colors are also detected through the OpenCV library which are then all combined to identify the requested object. The system presented in this paper not only accurately and quickly recognizes a person object with a specific clothing, but also has a potential extensibility that can be used for other types of object recognition in a video surveillance system for various purposes.
Cha, Sangwon;Oh, Eunha;Oh, Selim;Han, Sang Beom;Im, Hosub
Journal of Environmental Health Sciences
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v.47
no.1
/
pp.64-77
/
2021
Objective: Biological monitoring of trace elements in human blood samples has become an important indicator of the health environment. The purpose of this study was to detect and evaluate multiple metal items in blood samples based on ICP-MS, to perform comparative evaluation with the existing analysis method, and to develop and verify a new method. Methods: 100 μL of whole blood from 80 healthy subjects was used to analyze ten metals (Sb, tAs, Cd, Pb, Mn, Hg, Mo, Ni, Se, Tl) using ICP-MS. Verification of the analysis method included calculation of linearity, accuracy, precision and detection limits. In addition, a comparative test with the conventional graphite furnace atomic absorption spectroscopy (GF-AAS) method was performed. In the case of Pb, Cd, and Hg in whole blood, cross-analysis between Pb, Cd, and Hg analysis methods was performed to confirm the difference between the existing method and the new method (ICP-MS). Results: The coefficient of determination (R2) was 0.999 or higher in seven items and 0.995 or higher in three items. The Pb result showed that Pearson's correlation coefficient was very high at 0.983, and the intraclass correlation coefficient was 0.966. The Cd result showed that Pearson's correlation coefficient was 0.917 between the existing method and the new analysis concentration value. Its intraclass correlation coefficient was 0.960, and there was no significant difference between the two groups. Hg had a low correlation at 0.687, and the intraclass correlation coefficient was 0.761, which was lower than that of Pb and Cd. The intra-day and inter-day accuracy of Pd and Cd were satisfactory, but Hg did not meet the criteria for both accuracy and precision when compared with the conventional analysis method. Conclusion: This study can be meaningful in that it proposes a more efficient and feasible analysis method by verifying a blood heavy metal concentration experiment using multiple simultaneous analyses. All samples were processed and analyzed using the new ICP-MS. It was confirmed that the agreement between the two methods was very high, with the agreement between the current and new methods being 0.769 to 0.998. This study proposes an efficient simultaneous methodology capable of analyzing multiple elements with small samples. In the future, studies of various applications and the reliability of ICP-MS analysis methods are required, and research on the verification of accurate, precise, and continuous analysis methods is required.
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.
Jung-Whan Chon;Kun-Ho Seo;Tae-Jin Kim;Hye-Young Youn;Seok-Hyeong Kang;Won-Uk Hwang;Hajeong Jeong;Dongkwan Jeong;Kwang-Young Song
Journal of Dairy Science and Biotechnology
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v.41
no.1
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pp.9-25
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2023
Yogurt fermentation is known to be beneficial because it provides a low pH and harsh environment for foodborne pathogens and improves organoleptic properties. Additionally, organic acids produced through fermentation have a good effect on the viscosity and gelling properties of yogurt. Several potential health benefits of probiotic and generally recognized as safe strains have been suggested. Yogurt is the preferred vehicle for delivering probiotics to health-conscious consumers. Therefore, manufacturers of probiotic beverages must comply with the relevant regulations. The development of probiotic yogurt begins with the selection of strains with safety and functional properties of probiotics. The selected probiotic strain should be technically suitable for viability and improve organoleptic quality while maintaining the number of bacteria above the standard value during processing and storage conditions. In addition, the efficacy of probiotic strains contained in yogurt should be investigated, confirmed, and approved according to well-designed clinical trials. Although various methods are used to detect probiotic strains, the recently widely used next generation sequencing method can be actively utilized. In the future, more research should be conducted with the latest methods to identify probiotic functions and accurately detect probiotic strains.
Journal of the Korean Society of Marine Environment & Safety
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v.28
no.7
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pp.1140-1147
/
2022
With the development of digital technology, the marine environment is expected to change rapidly. In the case of autonomous vessels, technology is being developed in many countries, and the international community has begun to discuss ways to operate it. Changes in ships cause changes in the marine traffic environment and urge changes to aids to navigation. This study aims to analyze the cyber security management awareness of VTS personnel to improve the cyber security system for aids to navigation. To this end, the current status of cyber security management was reviewed with a focus on VTS, and a survey was conducted on VTS personnel. The survey analysis used the IPA methodology, and as a result of the analysis, a clear difference was observed in the perception of cybersecurity between those with experience in security and those without experience. In addition, technical measures related to cyber-attack detection and blocking should be implemented with the highest priority. The results of this study can be used as basic data for improving the cyber security management system for aids to navigation.
KIPS Transactions on Software and Data Engineering
/
v.12
no.2
/
pp.99-110
/
2023
This study proposed a classification of malicious network traffic using the cyber threat framework(Mitre ATT&CK) and machine learning to solve the real-time traffic detection problems faced by current security monitoring systems. We applied a network traffic dataset called UNSW-NB15 to the Mitre ATT&CK framework to transform the label and generate the final dataset through rare class processing. After learning several boosting-based ensemble models using the generated final dataset, we demonstrated how these ensemble models classify network traffic using various performance metrics. Based on the F-1 score, we showed that XGBoost with no rare class processing is the best in the multi-class traffic environment. We recognized that machine learning ensemble models through Mitre ATT&CK label conversion and oversampling processing have differences over existing studies, but have limitations due to (1) the inability to match perfectly when converting between existing datasets and Mitre ATT&CK labels and (2) the presence of excessive sparse classes. Nevertheless, Catboost with B-SMOTE achieved the classification accuracy of 0.9526, which is expected to be able to automatically detect normal/abnormal network traffic.
Kim, Pangyi;Choi, Yoon-Hyeong;Park, YeongChul;Park, Tae-Hyun;Leem, JongHan
Journal of Environmental Health Sciences
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v.48
no.1
/
pp.1-8
/
2022
Objectives: The purpose of this study is to reveal the circumstances under which the cases of harm to health caused by humidifier disinfectant were neglected and show the points where the number of victims and the degree of damage could have been reduced. In addition, it attempts to describe how damage management proceeded immediately after the incident and actually exacerbated the damage. Finally, it explores the unfortunate aspects of the recent trial. By doing so, it attempts to take this as an opportunity to consider whether a tragic event such as the humidifier disinfectant incident could occur in the future. Methods: This study collected and analyzed data on chemical material characteristics related to humidifier disinfectants, data on health effect characteristics, data on related laws and regulations from the Ministry of Environment, data related to the damage investigation by the Korea Environmental Industry and Technology Institute, and current contents. Results: The lack of related systems and laws is the area where the greatest responsibility for the cause of the humidifier disinfectant disaster falls, so it is difficult for the government to escape this responsibility. Establishing a dedicated department to identify the prevalence of certain diseases within the functions of the Health Insurance Review and Assessment Service to monitor health can greatly contribute to the prevention and management of diseases through early detection and management of group outbreaks caused by harmful factors. Humidifier disinfectant damage relief should have been expanded earlier beyond HDLI (humidifier disinfectant lung injury) to include non-specific diseases such as asthma, pneumonia, and interstitial pneumonia. The scope of relief benefits should have also been expanded earlier to include the payment of disability benefits. Fortunately, with the 2020 revision of the Special Act, the conditions for estimating causal relations were eased and individual screening systems such as health impact assessment were reorganized along with the introduction of a rapid screening system. Conclusions: The management system for chemical substances in a country is clearly of paramount importance, and the ministry in charge must have a response system in case of damage to health effects. Administration that looks at the victims' situation from their point of view is needed, and technical countermeasures are required to quickly recognize the prevalence of certain diseases.
Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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2022.10a
/
pp.236-238
/
2022
According to the current Road Traffic Act, the 2020 amendment bill is currently in effect as a system that designates vehicle types for each lane for the purpose of securing road use efficiency and traffic safety. When comparing the number of traffic accident fatalities per 10,000 vehicles in Germany and Korea, the number of traffic accident deaths in Germany is significantly lower than in Korea. The representative case of the German autobahn, which did not impose a speed limit, suggests that Korea's speeding laws are not the only answer to reducing the accident rate. The designated lane system, which is observed in accordance with the keep right principle of the Autobahn Expressway, plays a major role in reducing traffic accidents. Based on this fact, we propose a traffic enforcement system to crack down on vehicles violating the designated lane system and improve the compliance rate. We develop a designated lane enforcement system that recognizes vehicle types using Yolo5, a deep learning object recognition model, recognizes license plates and lanes using OpenCV, and stores the extracted data in the server to determine whether or not laws are violated.Accordingly, it is expected that there will be an effect of reducing the traffic accident rate through the improvement of driver's awareness and compliance rate.
Journal of the Korea institute for structural maintenance and inspection
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v.27
no.6
/
pp.30-38
/
2023
As the number of old buildings subject to safety inspection increases, the burden on designated institutions and management entities that are responsible for safety management is increasing. Accordingly, when selecting buildings subject to safety inspection, appropriate safety inspection standards and appropriate technology are essential. The current safety inspection standards for old buildings give low scores when it is difficult to confirm damage such as cracks in structural members due to finishing materials. This causes the evaluation results to be underestimated regardless of the actual safety status of the structure, resulting in an increase in the number of aging buildings subject to safety inspection. Accordingly, this study proposed a thermal imaging technique, a non-destructive and non-contact inspection, to detect cracks inside finishing materials. A concrete specimen was produced to observe cracks inside the finishing material using a thermal imaging camera, and thermal image data was measured by exciting a heat source on the concrete surface and cracked area. As a result of the measurement, it was confirmed that it was possible to observe cracks inside the finishing material with a width of 0.3mm, 0.5mm, and 0.7mm, but it was difficult to determine the cracks due to uneven temperature distribution due to surface peeling and peeling of the wallpaper. Accordingly, as a result of performing data analysis by deriving the amplitude and phase difference of the thermal image data, clear crack measurement was possible for 0.5mm and 0.7mm cracks. Based on this study, we hope to increase the efficiency of field application and analysis through the development of technology using big data-based deep learning in the diagnosis of internal crack damage in finishing materials.
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