• Journal of Korea Water Resources Association
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• v.55 no.spc1
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• pp.1283-1293
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• 2022

The purpose of this study is to predict residual chlorine in order to maintain stable residual chlorine concentration in sedimentation basin by using artificial intelligence algorithms in water treatment process employing pre-chlorination. Available water quantity and quality data are collected and analyzed statistically to apply into mathematical multiple regression and artificial intelligence models including multi-layer perceptron neural network, random forest, long short term memory (LSTM) algorithms. Water temperature, turbidity, pH, conductivity, flow rate, alkalinity and pre-chlorination dosage data are used as the input parameters to develop prediction models. As results, it is presented that the random forest algorithm shows the most moderate prediction result among four cases, which are long short term memory, multi-layer perceptron, multiple regression including random forest. Especially, it is result that the multiple regression model can not represent the residual chlorine with the input parameters which varies independently with seasonal change, numerical scale and dimension difference between quantity and quality. For this reason, random forest model is more appropriate for predict water qualities than other algorithms, which is classified into decision tree type algorithm. Also, it is expected that real time prediction by artificial intelligence models can play role of the stable operation of residual chlorine in water treatment plant including pre-chlorination process.

• KIPS Transactions on Software and Data Engineering
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• v.12 no.4
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• pp.189-198
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• 2023

As crimes frequently occur on the street, the spread of CCTV is increasing. However, due to the shortcomings of passively operated CCTV, the need for intelligent CCTV is attracting attention. Due to the heavy system of such intelligent CCTV, high-performance devices are required, which has a problem in that it is expensive to replace the general CCTV. To solve this problem, an intelligent CCTV system that recognizes low-quality images and operates even on devices with low performance is required. Therefore, this paper proposes a Saying CCTV system that can detect threats in real time by using the AWS cloud platform to lighten the system and convert images into text. Based on the data extracted using YOLO v4 and OpenPose, it is implemented to determine the risk object, threat behavior, and threat situation, and calculate the risk using machine learning. Through this, the system can be operated anytime and anywhere as long as the network is connected, and the system can be used even with devices with minimal performance for video shooting and image upload. Furthermore, it is possible to quickly prevent crime by automating meaningful statistics on crime by analyzing the video and using the data stored as text.

• Nutrition Research and Practice
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• v.17 no.4
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• pp.682-697
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• 2023

BACKGROUND/OBJECTIVES: Tibetan tea is a kind of dark tea, due to the inherent complexity of natural products, the chemical composition and beneficial effects of Tibetan tea are not fully understood. The objective of this study was to unravel the composition of Tibetan tea using knowledge-guided multilayer network (KGMN) techniques and explore its potential antioxidant and hypolipidemic mechanisms in mice. MATERIALS/METHODS: The C57BL/6J mice were continuously gavaged with Tibetan tea extract (T group), green tea extract (G group) and ddH2O (H group) for 15 days. The activity of total antioxidant capacity (T-AOC) and superoxide dismutase (SOD) in mice was detected. Transcriptome sequencing technology was used to investigate the molecular mechanisms underlying the antioxidant and lipid-lowering effects of Tibetan tea in mice. Furthermore, the expression levels of liver antioxidant and lipid metabolism related genes in various groups were detected by the real-time quantitative polymerase chain reaction (qPCR) method. RESULTS: The results showed that a total of 42 flavonoids are provisionally annotated in Tibetan tea using KGMN strategies. Tibetan tea significantly reduced body weight gain and increased T-AOC and SOD activities in mice compared with the H group. Based on the results of transcriptome and qPCR, it was confirmed that Tibetan tea could play a key role in antioxidant and lipid lowering by regulating oxidative stress and lipid metabolism related pathways such as insulin resistance, P53 signaling pathway, insulin signaling pathway, fatty acid elongation and fatty acid metabolism. CONCLUSIONS: This study was the first to use computational tools to deeply explore the composition of Tibetan tea and revealed its potential antioxidant and hypolipidemic mechanisms, and it provides new insights into the composition and bioactivity of Tibetan tea.

• Journal of Service Research and Studies
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• v.11 no.1
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• pp.59-79
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• 2021

Service-related research in accordance with the transition to the service economy era has been conducted in a wide variety of ways, but the development of a service-related scale suitable for the present time is still insignificant. The purpose of this study is to define the nature of services and to develop measurement items for them. First, four categories of service nature were adopted in the previous study. The four categories are 'relationship', 'interactivity', 'horizontality', and 'harmony'. In this study, sub-factors and specific items of each of these four service essences were extracted and developed as measurable items. As a qualitative study, the four categories of sub-factors were extracted, and a mixed study was adopted to prove the reliability and validity of the extracted factors through quantitative studies. The scale items were identified through literature study, free response method, and Delphi technique, and the measurement items were refined through a second questionnaire of 30 Delphi panels composed of experts. As a result of the study, 15 out of 52 questions for relationship, 11 out of 45 questions for bilateral direction, 9 out of 33 questions for horizontality, and 17 out of 61 questions for harmonization were derived after secondary refining. Through this study, it was possible to uncover new essential items suitable for the service economy era. SNS, network, synergy, platform, system, real name, and breakthrough are concepts that have not been obtained in previous studies, and can be seen as contributions of this study. However, due to various limitations, this study did not cover all aspects of the service, but mainly dealt with people-centered services, which are part of the service. In the future, it is necessary to study the development of service essence measurement items for the overall aspect of services developed according to the evolution of the service economy era.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.37 no.2
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• pp.77-84
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• 2024

In the fourth industrial-revolution era, the construction industry is transitioning from traditional methods to digital processes. This shift has been challenging owing to the industry's employment of diverse processes and extensive human resources, leading to a gradual adoption of digital technologies through trial and error. One critical area of focus is the safety management at construction sites, which is undergoing significant research and efforts towards digitization and automation. Despite these initiatives, recent statistics indicate a persistent occurrence of accidents and fatalities in construction sites. To address this issue, this study utilizes large-scale language-model artificial intelligence to analyze big data from a construction safety-management information network. The findings are integrated into on-site models, which incorporate real-time updates from detailed design models and are enriched with location information and spatial characteristics, for enhanced safety management. This research aims to develop a big-data-driven safety-management platform to bolster facility and worker safety by digitizing construction-site safety data. This platform can help prevent construction accidents and provide effective education for safety practices.

• IMMUNE NETWORK
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• v.21 no.6
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• pp.43.1-43.14
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• 2021

Group 3 innate lymphoid cells (ILC3), which express IL-22 and IL-17A, has been introduced as one of pathologic cells in axial spondyloarthritis (axSpA). Dyslipidaemia should be managed in axSpA patients to reduce cardiovascular disease, and dyslipidaemia promotes inflammation. This study aimed to reveal the role of circulating ILC3 in axSpA and the impact of dyslipidaemia on axSpA pathogenesis. AxSpA patients with or without dyslipidaemia and healthy control were recruited. Peripheral blood samples were collected, and flow cytometry analysis of circulating ILC3 and CD4⁺ T cells was performed. The correlation between Ankylosing Spondylitis Disease Activity Score (ASDAS)-C-reactive protein (CRP) and circulating immune cells was evaluated. The effect of oxidized low-density lipoprotein cholesterol (oxLDL-C) on immune cell differentiation was confirmed. AxSpA human monocytes were cultured with with oxLDL-C, IL-22, or oxLDL-C plus IL-22 to evaluate osteoclastogenesis using tartrate-resistant acid phosphatase (TRAP) staining and real-time quantitative PCR of osteoclast-related gene expression. Total of 34 axSpA patients (13 with dyslipidaemia and 21 without) were included in the analysis. Circulating IL-22⁺ ILC3 and Th17 were significantly elevated in axSpA patients with dyslipidaemia (p=0.001 and p=0.034, respectively), and circulating IL-22⁺ ILC3 significantly correlated with ASDAS-CRP (Rho=0.4198 and p=0.0367). Stimulation with oxLDL-C significantly increased IL-22⁺ ILC3, NKp44^- ILC3, and Th17 cells, and these were reversed by CD36 blocking agent. IL-22 and oxLDL-C increased TRAP⁺ cells and osteoclast-related gene expression. This study suggested potential role of circulating IL-22⁺ ILC3 as biomarker in axSpA. Furthermore, dyslipidaemia augmented IL-22⁺ ILC3 differentiation, and oxLDL-C and IL-22 markedly increased osteoclastogenesis of axSpA.

• IMMUNE NETWORK
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• v.22 no.2
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• pp.17.1-17.14
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• 2022

We aimed to investigate associations of dietary diversity (DD) with gut microbial diversity and the development of hen's egg allergy (HEA) in infants. We enrolled 68 infants in a high-risk group and 32 infants in a control group based on a family history of allergic diseases. All infants were followed from birth until 12 months of age. We collected infant feeding data, and DD was defined using 3 measures: the World Health Organization definition of minimum DD, food group diversity, and food allergen diversity. Gut microbiome profiles and expression of cytokines were evaluated by bacterial 16S rRNA sequencing and real-time reverse transcriptase-polymerase chain reaction. High DD scores at 3 and 4 months were associated with a lower risk of developing HEA in the high-risk group, but not in the control group. In the high-risk group, high DD scores at 3, 4, and 5 months of age were associated with an increase in Chao1 index at 6 months. We found that the gene expression of IL-4, IL-5, IL-6, and IL-8 were higher among infants who had lower DD scores compared to those who had higher DD scores in high-risk infants. Additionally, high-risk infants with a higher FAD score at 5 months of age showed a reduced gene expression of IL-13. Increasing DD within 6 months of life may increase gut microbial diversity, and thus reduce the development of HEA in infants with a family history of allergic diseases.

• Animal Bioscience
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• v.37 no.8
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• pp.1345-1354
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• 2024

Objective: The objective of this study was to identify candidate genes that play important roles in skeletal muscle development in ducks. Methods: In this study, we investigated the transcriptional sequencing of embryonic pectoral muscles from two specialized lines: Liancheng white ducks (female) and Cherry valley ducks (male) hybrid Line A (LCA) and Line C (LCC) ducks. In addition, prediction of target genes for the differentially expressed mRNAs was conducted and the enriched gene ontology (GO) terms and Kyoto encyclopedia of genes and genomes signaling pathways were further analyzed. Finally, a protein-to-protein interaction network was analyzed by using the target genes to gain insights into their potential functional association. Results: A total of 1,428 differentially expressed genes (DEGs) with 762 being up-regulated genes and 666 being down-regulated genes in pectoral muscle of LCA and LCC ducks identified by RNA-seq (p<0.05). Meanwhile, 23 GO terms in the down-regulated genes and 75 GO terms in up-regulated genes were significantly enriched (p<0.05). Furthermore, the top 5 most enriched pathways were ECM-receptor interaction, fatty acid degradation, pyruvate degradation, PPAR signaling pathway, and glycolysis/gluconeogenesis. Finally, the candidate genes including integrin b3 (Itgb3), pyruvate kinase M1/2 (Pkm), insulin-like growth factor 1 (Igf1), glucose-6-phosphate isomerase (Gpi), GABA type A receptor-associated protein-like 1 (Gabarapl1), and thyroid hormone receptor beta (Thrb) showed the most expression difference, and then were selected to verification by quantitative real-time polymerase chain reaction (qRT-PCR). The result of qRT-PCR was consistent with that of transcriptome sequencing. Conclusion: This study provided information of molecular mechanisms underlying the developmental differences in skeletal muscles between specialized duck lines.

• Journal of Intelligence and Information Systems
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• v.22 no.4
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• pp.109-122
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• 2016

Recently, big data analysis has developed into a field of interest to individuals and non-experts as well as companies and professionals. Accordingly, it is utilized for marketing and social problem solving by analyzing the data currently opened or collected directly. In Korea, various companies and individuals are challenging big data analysis, but it is difficult from the initial stage of analysis due to limitation of big data disclosure and collection difficulties. Nowadays, the system improvement for big data activation and big data disclosure services are variously carried out in Korea and abroad, and services for opening public data such as domestic government 3.0 (data.go.kr) are mainly implemented. In addition to the efforts made by the government, services that share data held by corporations or individuals are running, but it is difficult to find useful data because of the lack of shared data. In addition, big data traffic problems can occur because it is necessary to download and examine the entire data in order to grasp the attributes and simple information about the shared data. Therefore, We need for a new system for big data processing and utilization. First, big data pre-analysis technology is needed as a way to solve big data sharing problem. Pre-analysis is a concept proposed in this paper in order to solve the problem of sharing big data, and it means to provide users with the results generated by pre-analyzing the data in advance. Through preliminary analysis, it is possible to improve the usability of big data by providing information that can grasp the properties and characteristics of big data when the data user searches for big data. In addition, by sharing the summary data or sample data generated through the pre-analysis, it is possible to solve the security problem that may occur when the original data is disclosed, thereby enabling the big data sharing between the data provider and the data user. Second, it is necessary to quickly generate appropriate preprocessing results according to the level of disclosure or network status of raw data and to provide the results to users through big data distribution processing using spark. Third, in order to solve the problem of big traffic, the system monitors the traffic of the network in real time. When preprocessing the data requested by the user, preprocessing to a size available in the current network and transmitting it to the user is required so that no big traffic occurs. In this paper, we present various data sizes according to the level of disclosure through pre - analysis. This method is expected to show a low traffic volume when compared with the conventional method of sharing only raw data in a large number of systems. In this paper, we describe how to solve problems that occur when big data is released and used, and to help facilitate sharing and analysis. The client-server model uses SPARK for fast analysis and processing of user requests. Server Agent and a Client Agent, each of which is deployed on the Server and Client side. The Server Agent is a necessary agent for the data provider and performs preliminary analysis of big data to generate Data Descriptor with information of Sample Data, Summary Data, and Raw Data. In addition, it performs fast and efficient big data preprocessing through big data distribution processing and continuously monitors network traffic. The Client Agent is an agent placed on the data user side. It can search the big data through the Data Descriptor which is the result of the pre-analysis and can quickly search the data. The desired data can be requested from the server to download the big data according to the level of disclosure. It separates the Server Agent and the client agent when the data provider publishes the data for data to be used by the user. In particular, we focus on the Big Data Sharing, Distributed Big Data Processing, Big Traffic problem, and construct the detailed module of the client - server model and present the design method of each module. The system designed on the basis of the proposed model, the user who acquires the data analyzes the data in the desired direction or preprocesses the new data. By analyzing the newly processed data through the server agent, the data user changes its role as the data provider. The data provider can also obtain useful statistical information from the Data Descriptor of the data it discloses and become a data user to perform new analysis using the sample data. In this way, raw data is processed and processed big data is utilized by the user, thereby forming a natural shared environment. The role of data provider and data user is not distinguished, and provides an ideal shared service that enables everyone to be a provider and a user. The client-server model solves the problem of sharing big data and provides a free sharing environment to securely big data disclosure and provides an ideal shared service to easily find big data.

• Journal of Intelligence and Information Systems
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• v.17 no.4
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• pp.143-155
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• 2011

Lately electronic tagging policy for the sexual offenders was introduced in order to reduce and prevent sexual offences. However, most sexual offences against children happening these days are committed by the tagged offenders whose identities have been released. So, for the crime prevention, we need measures with which we could minimize the suffers more promptly and actively. This paper suggests a new system to relieve the sexual abuse related anxiety of the children and solve the problems that electronic bracelet has. Existing bracelets are only worn by serious criminals, and it's only for risk management and positioning, there is no way to protect the children who are the potential victims of sexual abuse and there actually happened some cases. So we suggest also letting the students(children) wear the LBS(Location Based Service) and USN(Ubiquitous Sensor Network) technology based electronic bracelets to monitor and figure out dangerous situations intelligently, so that we could prevent sexual offences against children beforehand, and while a crime is happening, we could judge the situation of the crime intelligently and take swift action to minimize the suffer. And by checking students' attendance and position, guardians could know where their children are in real time and could protect the children from not only sexual offences but also violent crimes against children like kidnapping. The overall system is like follows : RFID Tag for children monitors the approach of offenders. While an offender's RFID tag is approaching, it will transmit the situation and position as the first warning message to the control center and the guardians. When the offender is going far away, it turns to monitoring mode, and if the tag of the child or the offender is taken off or the child and offender stay at one position for 3~5 minutes or longer, then it will consider this as a dangerous situation, then transmit the emergency situations and position as the second warning message to the control center and the guardians, and ask for the dispatch of police to prevent the crime at the initial stage. The RFID module of criminals' electronic bracelets is RFID TAG, and the RFID module for the children is RFID receiver(reader), so wherever the offenders are, if an offender is at a place within 20m from a child, RFID module for children will transmit the situation every certain periods to the control center by the automatic response of the receiver. As for the positioning module, outdoors GPS or mobile communications module(CELL module)is used and UWB, WI-FI based module is used indoors. The sensor is set under the purpose of making it possible to measure the position coordinates even indoors, so that one could send his real time situation and position to the server of central control center. By using the RFID electronic roll book system of educational institutions and safety system installed at home, children's position and situation can be checked. When the child leaves for school, attendance can be checked through the electronic roll book, and when school is over the information is sent to the guardians. And using RFID access control turnstiles installed at the apartment or entrance of the house, the arrival of the children could be checked and the information is transmitted to the guardians. If the student is absent or didn't arrive at home, the information of the child is sent to the central control center from the electronic roll book or access control turnstiles, and look for the position of the child's electronic bracelet using GPS or mobile communications module, then send the information to the guardians and teacher so that they could report to the police immediately if necessary. Central management and control system is built under the purpose of monitoring dangerous situations and guardians' checking. It saves the warning and pattern data to figure out the areas with dangerous situation, and could help introduce crime prevention systems like CCTV with the highest priority. And by DB establishment personal data could be saved, the frequency of first and second warnings made, the terminal ID of the specific child and offender, warning made position, situation (like approaching, taken off of the electronic bracelet, same position for a certain time) and so on could be recorded, and the data is going to be used for preventing crimes. Even though we've already introduced electronic tagging to prevent recurrence of child sexual offences, but the crimes continuously occur. So I suggest this system to prevent crimes beforehand concerning the children's safety. If we make electronic bracelets easy to use and carry, and set the price reasonably so that many children can use, then lots of criminals could be prevented and we can protect the children easily. By preventing criminals before happening, it is going to be a helpful system for our safe life.