• The Journal of the Korea Contents Association
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• v.22 no.2
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• pp.125-134
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• 2022

Due to the development of smartphone technology, as of 2020, 91.9% of people use the Internet[1] to frequently acquire information through websites and mobile apps. As the number of homepages in charge of providing information is increasing every year, the number of applications for web vulnerability diagnosis, which diagnoses the safety of homepages, is also increasing. In the existing web vulnerability check, the number of diagnostic personnel should increase in proportion to the number of homepages that need diagnosis because the diagnosticians manually test the homepages for vulnerabilities. In reality, however, there is a limit to securing a web vulnerability diagnosis manpower, and if the number of diagnosis manpower is increased, a lot of costs are incurred. To solve these problems, an automatic diagnosis tool is used to replace a part of the manual diagnosis. This paper explores a new method to expand the current automatic diagnosis range. In other words, automatic diagnosis possible items were derived by analyzing the impact of web vulnerability diagnosis items. Furthermore, automatic diagnosis identified possible items through comparative analysis of diagnosis results by performing manual and automatic diagnosis on the website in operation. In addition, it is possible to replace manual diagnosis for possible items, but not all vulnerability items, through the improvement of automatic diagnosis tools. This paper will explore some suggestions that can help improve plans to support and implement automatic diagnosis. Through this, it will be possible to contribute to the creation of a safe website operating environment by focusing on the parts that require precise diagnosis.

• Ecology and Resilient Infrastructure
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• v.9 no.1
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• pp.24-35
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• 2022

For water quality management, it is necessary to continuously improve the forecasting by analyzing the past water quality, and a Data-driven model is emerging as an alternative. Because the Data-driven model is built based on a wide range of data, it is essential to apply the correlation analysis method for the combination of input variables to obtain more reliable results. In this study, the Gamma Test was applied as a preceding step to build a faster and more accurate data-driven water quality prediction model. First, a physical-based model (HSPF, EFDC) was operated to produce daily water quality reflecting the complexity of the watershed according to various hydrological conditions for Paldang Dam. The Gamma Test was performed on the water quality at the water quality prediction site (Paldangdam2) and major rivers flowing into the Paldang Dam, and the method of selecting the optimal input data combination was presented through the analysis results (Gamma, Gradient, Standar Error, V-Ratio). As a result of the study, the selection criteria for a more efficient combination of input data that can save time by omitting trial and error when building a data-driven model are presented.

• Journal of Korean Society of Disaster and Security
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• v.15 no.3
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• pp.79-88
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• 2022

Cable-supported bridges, as important large infrastructures, require a long-term and systematic maintenance strategy. In particular, various methods have been proposed to secure safety for the bridges, such as installing various types of sensor on members in the bridges, and setting management thresholds. It is evidently necessary to propose a strategic plan to efficiently manage increasing number of cable-supported bridges and data collected from a number of sensors. This study aims to develop an analysis tool that can automatically remove abnormal signals and calculate statistical results for the purpose of efficiently analyzing a wide range of data collected from a long span bridge measurement system. To develop the tool, basic information such as the types and quantity of sensors installed in long span bridges and signal characteristics of the collected data were analyzed. Thereafter, the Humpel filtering method was used to determine the presence or absence of an abnormality in the signal and then filtered. The statistical results with filtered data were shown. Finally, one cable-stayed bridge and one suspension bridge currently in use were chosen as the target bridges to verify the performance of the developed tool. Signal processing and statistical analysis with the tool were performed. The results are similar to the results reported in the existing work.

• Proceedings of the Korean Society of Near Infrared Spectroscopy Conference
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• 2001.06a
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• pp.1246-1246
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• 2001

The quality of meat is highly variable in many properties. This variability originates from both animal production and meat processing. At the pre-slaughter stage, animal factors such as breed, sex, age contribute to this variability. Environmental factors include feeding, rearing, transport and conditions just before slaughter (Hildrum et al., 1995). Meat can be presented in a variety of forms, each offering different opportunities for adulteration and contamination. This has imposed great pressure on the food manufacturing industry to guarantee the safety of meat. Tissue and muscle speciation of flesh foods, as well as speciation of animal derived by-products fed to all classes of domestic animals, are now perhaps the most important uncertainty which the food industry must resolve to allay consumer concern. Recently, there is a demand for rapid and low cost methods of direct quality measurements in both food and food ingredients (including high performance liquid chromatography (HPLC), thin layer chromatography (TLC), enzymatic and inmunological tests (e.g. ELISA test) and physical tests) to establish their authenticity and hence guarantee the quality of products manufactured for consumers (Holland et al., 1998). The use of Near Infrared Reflectance Spectroscopy (NIRS) for the rapid, precise and non-destructive analysis of a wide range of organic materials has been comprehensively documented (Osborne et at., 1993). Most of the established methods have involved the development of NIRS calibrations for the quantitative prediction of composition in meat (Ben-Gera and Norris, 1968; Lanza, 1983; Clark and Short, 1994). This was a rational strategy to pursue during the initial stages of its application, given the type of equipment available, the state of development of the emerging discipline of chemometrics and the overwhelming commercial interest in solving such problems (Downey, 1994). One of the advantages of NIRS technology is not only to assess chemical structures through the analysis of the molecular bonds in the near infrared spectrum, but also to build an optical model characteristic of the sample which behaves like the “finger print” of the sample. This opens the possibility of using spectra to determine complex attributes of organic structures, which are related to molecular chromophores, organoleptic scores and sensory characteristics (Hildrum et al., 1994, 1995; Park et al., 1998). In addition, the application of statistical packages like principal component or discriminant analysis provides the possibility to understand the optical properties of the sample and make a classification without the chemical information. The objectives of this present work were: (1) to examine two methods of sample presentation to the instrument (intact and minced) and (2) to explore the use of principal component analysis (PCA) and Soft Independent Modelling of class Analogy (SIMCA) to classify muscles by quality attributes. Seventy-eight (n: 78) beef muscles (m. longissimus dorsi) from Hereford breed of cattle were used. The samples were scanned in a NIRS monochromator instrument (NIR Systems 6500, Silver Spring, MD, USA) in reflectance mode (log 1/R). Both intact and minced presentation to the instrument were explored. Qualitative analysis of optical information through PCA and SIMCA analysis showed differences in muscles resulting from two different feeding systems.

• Korean Journal of Fisheries and Aquatic Sciences
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• v.56 no.1
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• pp.33-43
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• 2023

This study compared the nutritional composition of rainbow trout Oncorhynchus mykiss from different inland-based trout farms. The proximate composition ranges of the fish were 67.10-72.77 g/100 g moisture, 19.13-21.35 g/100 g crude protein, 5.12-11.72 g/100 g crude lipid, and 1.24-1.97 g/100 g ash. In addition, rainbow trout contained significantly different mono- and poly-unsaturated fatty acid concentrations, ranging from 1.31 to 4.33 g/100 g and 1.21 to 3.2 g/100 g, respectively. The content of n-3 and n-6 fatty acids ranged from 0.68 to 1.68 and from 0.49 to 1.61 g/100 g, respectively. The n-6/n-3 ratio was in the range of 0.79-1.59. The vitamin content of the rainbow trout from the different farms was 14.83-49.30 ㎍/100 g vitamin A, 922.05-3,179.38 ㎍/100 g alpha-tocopherol, ND-73.59 ㎍/100 g, gamma-tocopherol, 2.97-14.55 ㎍/100 g vitamin D, and 76.63-126.03 ㎍/100 g vitamin B₂. Slight differences were observed in the crude lipid, fatty acid, and vitamins A and E contents among the of rainbow trouts from the different farms. The results suggest that the fish nutrient composition, especially that of lipids, was significantly different among rainbow trouts from different farms, but may not be related to the production area.

• KOREAN JOURNAL OF PACKAGING SCIENCE & TECHNOLOGY
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• v.29 no.2
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• pp.111-118
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• 2023

In this study, the feasibility of laser patterning on the surface of food packaging polymer film was confirmed, and the surface patterning process conditions of femtosecond laser were established. In addition, it was proved that the surface properties of the film can be changed and controlled through the fabrication of various patterned films on the surface of food packaging films such as HDPE, PP, and PET. Various patterned surfaces, including large-scale circular patterns induced by a single femtosecond laser pulse, roughness patterns achieved by overlapping single pulses by 30%, straight line patterns, roughness patterns obtained by overlapping straight line patterns, and grid patterns formed by intersecting straight line patterns were fabricated. The characteristics of the patterned HDPE, PP, and PET films, based on the surface pattern structure and size, were analyzed using SEM, AFM, and contact angle measurements. Compared to the surface of each control film without femtosecond laser patterning, the contact angles of the surfaces of large-area circular patterning HDPE and PP films, large-area roughness patterning HDPE and PP films by overlapping 30% of single pulses, and large-area roughness patterning PET film by overlapping rectilinear patterning were in the range of 27.1-37.5 degree. This indicated that the HDPE, PP, and PET films became more hydrophilic after patterning. On the other hand, the HDPE film patterned with a large-scale grid pattern exhibited a contact angle of 120.4 degree, indicating that the HDPE film became more hydrophobic after patterning. Therefore, films that have been changed to hydrophilic surfaces through patterning can be used in anti-fouling applications where proteins, cells, viruses, and other food materials do not adhere or are easily detached. In addition, if a superhydrophobic surface of 150 degrees or more is fabricated through more precise lattice patterning in the future, it will be possible to use it for superhydrophobic surface applications such as self-cleaning.

• Journal of the Korean Regional Science Association
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• v.39 no.3
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• pp.65-83
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• 2023

The purpose of this study is to conceptually define "spatial inclusivity" and empirically examine the impact of disability severity and spatial inclusivity on social participation among individuals experiencing physical discomfort. The social and spatial environment of the residential area is crucial for individuals with disabilities who face limited activity range and complex barriers due to physical constraints. In this study, spatial inclusivity from the perspective of people with disabilities is defined as establishment of equal relationships with non-disabled individuals within the local community, as well as the availability of basic facilities and services in a safe urban space that allows for access and utilization. This concept consists of three dimensions: individual networks, social environment, and physical environment. The physical environment encompasses safety levels, natural environment, living environment, public transportation conditions, medical services in residential areas. We used the 2019 Community Health Survey to examine the relationship between disability severity, spatial inclusivity, and social participation using a two level regression model. The findings are as follows: Firstly, personal relationships at the individual level and the physical environment at the local level have a positive impact on social participation. Secondly, when identifying dividing the physical environment into five sub-factors, no significant influence of individual factors is found. Thirdly, trustworthy and friendly social environment at the local level has a negative impact on social participation. These results provide empirical evidence that spatial inclusivity has an effect on the social participation of individuals with disabilities and suggest implications for urban planning to create and enhance conditions for the social participation of individuals with disabilities.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2022.05a
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• pp.317-321
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• 2022

In response to Incheon tap water accident in 2019, the Ministry of Environment has created the "Comprehensive Measures for Water Safety Management" to improve water operation management, provide systematic technical support, and respond to accidents. Accordingly, K-water is making a smart water supply management system for the entire process of tap water. In order to advance the response to water accidents, it is essential to secure the reliability of real-time water operation data such as flow rate, pressure, and water level, and to develop and apply a warning algorithm in advance using big data analysis techniques. In this paper, various statistical techniques are applied using water supply operation data (flow, pressure, water level, etc) to prepare the foundation for the selection of the optimal operating range and advancement of the monitoring and alarm system. In addition, the arrival time is analyzed through cross-correlation analysis of changes in raw water turbidity between the water intake and water treatment plants. The purpose of this paper is to study the model that predicts the raw water turbidity of a water treatment plant by applying raw water turbidity data considering the time delay according to the flow rate change.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2022.05a
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• pp.288-290
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• 2022

As part of the SOC digitization for smart water management and flood prevention, the government reported that automatic and remote control system for drainage facilities (180 billion won) to 57% of national rivers and established a real-time monitoring system (30 billion won). In addition, they were also planning to establish a smart dam safety management system (15 billion won) based on big data at 11 regions. Therefore, research is needed for smart water management and flood prevention system that can accurately calculate the flow rate through real-time flow rate measurement of rivers. In particular, the most important thing to improve the system implementation and accuracy is to ensure the accuracy of real-time flow rate measurements. To this end, radar sensors for measuring the flow rate of electromagnetic waves in the United States and Europe have been introduced and applied to the system in Korea, but demand for improvement of the system continues due to high price range and performance. Consequently, we would like to propose an improved flow rate measurement and flood forecast system by developing a radar sensor for measuring the electromagnetic surface current meter for real-time flow rate measurement.

• Nutrition Research and Practice
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• v.17 no.2
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• pp.241-256
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• 2023

BACKGROUND/OBJECTIVES: Diabetes-specific oral nutritional supplements (ONS) have anti-hyperglycemic effects, while D-allulose exerts anti-diabetic and anti-obesity effects. In this study, we investigated the efficacy and safety of diabetes-specific ONS, including allulose, on glycemic and weight changes in overweight or obese patients with type 2 diabetes mellitus (T2DM). SUBJECTS/METHODS: A single-arm, historical-control pilot clinical trial was conducted on 26 overweight or obese patients with T2DM (age range: 30-70 yrs). The participants were administered 2 packs of diabetes-specific ONS, including allulose (200 kcal/200 mL), every morning for 8 weeks. The glycemic profiles, obesity-related parameters, and lipid profiles were assessed to evaluate the efficacy of ONS. RESULTS: After 8 weeks, fasting blood glucose (FBG) level significantly decreased from 139.00 ± 29.66 mg/dL to 126.08 ± 32.00 mg/dL (P = 0.007) and glycosylated hemoglobin (HbA1c) improved (7.23 ± 0.82% vs. 7.03 ± 0.69%, P = 0.041). Moreover, the fasting insulin (δ: -1.81 ± 3.61 μU/mL, P = 0.017) and homeostasis model assessment for insulin resistance (HOMA-IR) (δ: -0.87 ± 1.57, P = 0.009) levels decreased at 8 weeks, and body weight significantly decreased from 67.20 ± 8.29 kg to 66.43 ± 8.12 kg (P = 0.008). Body mass index (BMI) also decreased in accordance with this (from 25.59 ± 1.82 kg/m² to 25.30 ± 1.86 kg/m², P = 0.009), as did waist circumference (δ: -1.31 ± 2.04 cm, P = 0.003). CONCLUSIONS: The consumption of diabetes-specific ONS with allulose in overweight or obese patients with T2DM improved glycemic profiles, such as FBG, HbA1c, and HOMA-IR, and reduced body weight and BMI.