• The Journal of Korean Institute of Communications and Information Sciences
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• v.38C no.5
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• pp.420-427
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• 2013

Recently, for secure software development, static analysis tools have been used mostly to analyze the source code of the software and identify software weaknesses caused of vulnerabilities. In order to select the optimal static analysis tool, both weaknesses rules and analysis capabilities of the tool are important factors. Therefore, in this paper we propose the test codes developed for evaluating the rules and analysis capabilities of the tools. The test codes to involve 43 weaknesses such as SQL injection etc. can be used to evaluate the adequacy of the rules and analysis capabilities of the tools.

• Analytical Science and Technology
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• v.8 no.4
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• pp.623-630
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• 1995

Silicone rubber-based sodium-selective membranes are developed for solid-state ion sensors. It was shown that the potetiometric performance of SR-based membranes are greatly dependent on the type of neutral carriers employed; among the three ionophores, N,N,N',N'-tetracyclohexyl-1,2-phenylenedioxydiacetamide (ETH 2120), bis[(12-crown-4)methyl]dodecylmethylmalonate (D12C4DMM) and monensin methyl ester (MME), examined, only ETH 2120 was compatible with the SR-based matrix. Addition of about 20 wt% plasticizer to the SR-based matrix provided the resulting membranes with potentiometric properties essentially equivalent to those of the corresponding PVC-based membranes. Owing to the strong adhesive strength of SR-based membranes, the CWEs coated \vith those membranes exhibited long lifetime with conventional electrode-like performance. Blending of PU into the SR matrix increased the lifetime of CWEs from two weeks to one month.

• Journal of Platform Technology
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• v.9 no.2
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• pp.10-25
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• 2021

Although many studies have been conducted on risk analysis and evaluation in the on-premises environment in information security, studies on effective methodologies of risk analysis and evaluation for cloud computing systems are lacking. In 2015, the Cloud Computing Development Act was enacted, which served as an opportunity to promote the introduction of cloud computing. However, due to the increase in security incidents in the cloud computing system, activation is insufficient. In addition, the cloud computing system is not being actively introduced because of the difficulty in understanding the cloud computing system technology of the person in charge who intends to introduce the cloud computing system. In this regard, this study presented an effective risk analysis and evaluation method by examining the characteristics, concepts, and models of cloud computing systems and analyzing how these characteristics affect risk analysis and evaluation.

• Animal Bioscience
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• v.35 no.8
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• pp.1279-1288
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• 2022

Objective: The aim of this study was to investigate antioxidant activities of cinnamon (Cinnamomum cassia) extracts (extracted with different solvents) at various concentrations and to determine product quality of raw chicken patties added with different levels of cinnamon powder (CP) and oyster mushroon powder (OMP) during storage. Methods: After cinnamon was made into oven dried CP and extracted with water and different levels (50%, 80%, and 100%) of ethanol, antioxidant activities of these extracts were determined. CP and OMP were combined at different levels and added to raw chicken patties. Physicochemical properties and microbial counts were measured during refrigerated storage. Results: Cinnamon ethanol (80%) extract showed the highest (p<0.05) by 2,2-diphenyl-1picrylhydrazyl-radical scavenging activity and reducing power. Cinnamon water extract (CWE) had the highest iron chelating ability (p<0.05), while CP 100% ethanol extract had the highest content of total phenolic compound. Then, CP and OMP were applied to chicken patties at different levels (0.1% to 0.2%). After the addition of CPs, pH, L* (lightness), 2-thiobarbituric acid reactive substance, and volatile basic nitrogen values were decreased, whereas a* (redness) and b* (yellowness) values were increased. Microbial counts of total bacteria and Enterobacteriaceace were decreased with the addition of CP 0.2% regardless of the OMP level. Conclusion: The addition of CP in combination with OMP can increase the shelf-life of chicken patties during storage.

• Current Research on Agriculture and Life Sciences
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• v.15
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• pp.53-67
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• 1997

The objective of this study is to provide with the hydro-meteological and probabilistic characteristics of the storms of typhoons that have been passed through the Korean peninsula during the last twenty-three years since 1961. The paths and intensities of the typhoons were analyzed. Fifty weather stations were selected and the rainfall data during typhoon periods were collected. Rainfall data were analyzed for the patterns and probabilistic distributions. The results were presented to describe the areal distributions of probabilistic characteristics. The results obtained from this study can be summarized as follows: 1. The most frequent typhoon path that has passed through the Korean peninsula was type E, followed by types CWE, W, WE, and S. The most frequent typhoon intensity was type B, followed by A, super A, and e types, respectively. 2. The third quartile typhoon rainfall patterns appear most frequently followed by the second, first, and last quartiles, respectively, in Seoul, Pusan, Taegu, Kwangju and Taejon. The single typhoon rainfalls with long rainfall durations tended to show delayed type rainfall patterns predominantly compared to the single rainfalls with short rainfall durations. 3. The most frequent probabilistic distribution of typhoon rainfall event is Pearson type-III, followed by Two-parameter lognormal distribution, and Type-I extremal distribution. 4. The most frequent probability distribution model of seashore location was Pearson type-III distribution. The most frequent probability distribution model of inland location was two parameter lognormal distribution.

• Magazine of the Korean Society of Agricultural Engineers
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• v.36 no.3
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• pp.122-134
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• 1994

The objective of this study is to provide with the hydrometeological and probabilistic characteristics of the storms and winds of typhoons that have been passed through the Korea peninsula during the last twenty-three years since 1961. The paths and intensities of the typhoons were analyzed. Fifty weather stations were selected and the rainfall and wind data during typhoon periods were collected. Rainfall data were analyzed for the patterns and probabilistic distributions. The results were presented to describe the areal distributions of probabilistic characteristics. Wind data were also analysed for their probabilistic distributions. The results obtained from this study can be summarized as follows: 1. The most frequent typhoon path that have passed through the Korean peninsula was type E, which was followed by types CWE, W, WE, and S. The most frequent typhoon intensity was type B, that was followed by A, super A, and C types, respectively. 2. The third quartile typhoon rainfall patterns appear most frequently followed by the second, first, and quartiles, respectively, in Seoul, Pusan, Taegu, Kwangju and Taejon. The single typhoon rainfalls with long rainfall durations tended to show delayed type rainfall patterns predominantly compared to the single rainfalls with short rainfall durations. 3. The most frequent probabilistic distribution for typhoon rainfall event is Pearson type-III, followed by Two-parameter lognormal distribution, and Type-I extremal distribution. 4. The most frequent probability distribution model of seashore location was Pearson type-III distribution. The most frequent probability distribution model of inland location was two parameter lognormal distribution. 5. The most frequent probabilistic distribution for typhoon wind events was Type-I xtremal distribution, followed by Two-parameter lognormal distribution, and Normal distribution.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.28 no.6
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• pp.1449-1461
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• 2018

As the number of software vulnerabilities grows year by year, attacks on software are also taking place a lot. As a result, the security administrator must identify and patch vulnerabilities in the software. However, it is important to prioritize the patches because patches for all vulnerabilities are realistically hard. In this paper, we propose a scoring system that expands the scale of risk assessment metric by taking into consideration attack patterns or weaknesses cause vulnerabilities with the vulnerability information provided by the NIST(National Institute of Standards and Technology). The proposed scoring system is expanded based on the CWSS and uses only public vulnerability information to utilize easily for any company. In this paper, we applied the automated scoring system to software vulnerabilities, and showed the expanded metrics with consideration for influence of attack pattern and weakness are meaningful.

• Convergence Security Journal
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• v.18 no.3
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• pp.37-44
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• 2018

Today we live in a flood of web sites and access numerous websites through the Internet to obtain various information. However, unless the security of the Web site is secured, Web site security can not be secured from various malicious attacks. Hacking attacks, which exploit Web site security vulnerabilities for various reasons, such as financial and political purposes, are increasing. Various attack techniques such as SQL-injection, Cross-Site Scripting(XSS), and Drive-By-Download are being used, and the technology is also evolving. In order to defend against these various hacking attacks, it is necessary to remove the vulnerabilities from the development stage of the website, but it is not possible due to various problems such as time and cost. In order to compensate for this, it is important to identify vulnerabilities in Web sites through web vulnerability checking and take action. In this paper, we investigate web vulnerabilities and diagnostic techniques and try to understand the priorities of vulnerabilities in the development stage according to the actual status of each case through cases of actual web vulnerability diagnosis.

• Journal of Pharmacopuncture
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• v.25 no.2
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• pp.130-137
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• 2022

Objectives: Insulin resistance (IR) is major cause of type 2 diabetes (T2D), and adipokines (e.g., adiponectin, leptin, and resistin) play an important role in insulin sensitivity. Medicinal plants are frequently used for T2D treatment. This study investigates the effect of Artemisia annua L. (AA) extracts on adipokines in mice with high-fat-diet (HFD)/streptozotocin (STZ)-induced T2D. Methods: We divided 60 mice into 12 groups (n = 5 per group): control, untreated T2D, treated T2D, and 9 other groups. T2D was induced in all groups, except controls, by 8 weeks of HFD and STZ injection. The treated T2D group was administered 250 mg/kg of metformin (MTF), while the nine other groups were treated with 100, 200, and 400 mg/kg of hot-water extract (HWE), cold-water extract (CWE), and alcoholic extract (ALE) of AA (daily oral gavage) along with 250 mg/kg of MTF for 4 weeks. The intraperitoneal glucose tolerance test (IPGTT) was performed, and the homeostasis model assessment of adiponectin (HOMA-AD) index and blood glucose and serum insulin, leptin, adiponectin, and resistin levels were measured. Results: Similar to MTF, all three types of AA extracts (HWEs, CWEs, and ALEs) significantly (p < 0.0001) decreased the area under the curve (AUC) of glucose during the IPGTT, the HOMA-AD index, blood glucose levels, and serum insulin, leptin, and resistin levels and increased serum adiponectin levels in the MTF group compared to the T2D group (p < 0.0001). The HWEs affected adipokine release, while the CWEs and ALEs decreased leptin and resistin production. Conclusion: Water and alcoholic AA extracts have an antihyperglycemic and antihyperinsulinemic effect on HFD/STZ diabetic mice. In addition, they decrease IR by reducing leptin and resistin production and increasing adiponectin secretion from adipocytes.

• KIPS Transactions on Software and Data Engineering
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• v.12 no.10
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• pp.431-436
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• 2023

Recently the incorporation of artificial intelligence approaches in the field of software engineering has been one of the big topics. In the world, there are actively studying in two directions: 1) software engineering for artificial intelligence and 2) artificial intelligence for software engineering. We attempt to apply artificial intelligence to software engineering to identify and refactor bad code module areas. To learn the patterns of bad code elements well, we must have many datasets with bad code elements labeled correctly for artificial intelligence in this task. The current problems have insufficient datasets for learning and can not guarantee the accuracy of the datasets that we collected. To solve this problem, when collecting code data, bad code data is collected only for code module areas with high-complexity, not the entire code. We propose a method for exploring common weakness enumeration by learning the collected dataset based on transfer learning of the CodeBERT model. The CodeBERT model learns the corresponding dataset more about common weakness patterns in code. With this approach, we expect to identify common weakness patterns more accurately better than one in traditional software engineering.