• Journal of Korean Traditional Oncology
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• v.27 no.1
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• pp.25-36
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• 2022

The Randomized Control Trial (RCT) is the most well-established and widely used statistical methodology in clinical research; however, applying thorough RCT to cancer patients presents challenges such as ethical concerns, high costs, short clinical periods, and limitations in collecting various side effects. To address this issue, the propensity score matching method, which takes advantage of the benefits of observational research while compensating for the drawbacks of randomized control trials, is used in a variety of fields. In recent years, 28 studies on the effectiveness of Korean medicine on tumors have been conducted abroad using the Propensity Score Matching Method, but none have been conducted in Korea. The majority of studies have focused on liver cancer, colon cancer, lung cancer, and stomach cancer, with endpoints such as survival time, incidence rate, quality of life, and treatment outcomes revealing statistical differences in how Korean medicine intervention affects treatment outcomes. As a result, well-established studies using the propensity matching score methodology should be useful in evaluating the impact of Korean medicine in oncology treatments.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.26 no.9
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• pp.1382-1391
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• 2022

White-box cryptography can respond to white-box attacks that can access and modify memory by safely hiding keys in the lookup table. However, because the size of lookup tables is large and the speed of encryption is slow, it is difficult to apply them to devices that require real-time while having limited resources, such as IoT(Internet of Things) devices. In this work, we propose a scheme for collecting short-length plaintexts and processing them at once, utilizing the characteristics that white-box ciphers process encryption on a lookup table size basis. As a result of comparing the proposed method, assuming that the table sizes of the Chow and XiaoLai schemes were 720KB(Kilobytes) and 18,000KB, respectively, memory usage reduced by about 29.9% and 1.24% on average in the Chow and XiaoLai schemes. The latency was decreased by about 3.36% and about 2.6% on average in the Chow and XiaoLai schemes, respectively, at a Traffic Load Rate of 15 Mbps(Mega bit per second) or higher.

• Journal of the Korean Society of Physical Medicine
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• v.18 no.1
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• pp.99-110
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• 2023

PURPOSE: This study was conducted to suggest a way to easily understand and utilize the International Classification of Functioning, Disability and Health (ICF) or Korean Standard Classification of Functioning, Disability and Health (KCF), a common and standard language related to health information. METHODS: The tools used by physical therapists to evaluate the functioning of neurological patients were collected from 10 domestic hospitals. By applying the ICF linking rule, two experts compared, analyzed, and linked the concepts in the items of the collected tools and the ICF/KCF codes. The frequency of use of the selected tool, the matching rate of the liking results of two experts, and the number of the codes linked were treated as descriptive statistics and the code set was presented as a list. RESULTS: The berg balance scale, trunk impairment scale, timed up and go test, functional ambulation category, 6 Minute walk test, manual muscle test, and range of motion measurements were the most commonly used tools for evaluating the functioning. The total number of items of the seven tools was 33, and the codes linked to the ICF/KCF were 69. Twenty-two codes were mapped, excluding duplicate codes. Ten codes in the body function, 11 codes in the activity, and one code in the environmental factor were included. CONCLUSION: The information on the development process of the code set will increase the understanding of ICF/KCF and the developed code set can conveniently be used for collecting patients' functioning information.

• Land and Housing Review
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• v.14 no.3
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• pp.137-144
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• 2023

The amount of soil cutting, transported, and filing up the soil in the project area is considered to change the volume depending on the condition of the soil; the volume change rate of the soil is calculated by collecting undisturbed samples below 1 m to 2.0 m above the surface through test pits. In this study, large-scale field tests are carried out. There are areas with an excavation depth of 10m or more, but some errors have occurred in calculating the soil volume by uniformly applying the soil conversion factor for a depth of 1 to 2 m. According to the field tests, the earthwork volumes applied with the soil conversion factor for each depth increase by 3.9 to 9.4% compared to the soil volume applied uniformly with that of 2 m depth.

• Journal of Practical Agriculture & Fisheries Research
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• v.6 no.1
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• pp.3-16
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• 2004

The objective of this study was to investigate the necessity of rural tourism education in the Korea National Agricultural College and suggest the educational plan. Recently, the Korean government proposes the rural tourism as an alternative plan for solving the problems of agriculture and rural community that experience difficulty by the opening of agricultural market and the falling price, etc. As result of investigation of cases of OECD nations and the growth rate of tourism market in Korea, it has been determined that the demand of rural tourism was sufficient. The Ministry of Agriculture & Forestry makes a goal of attracting the yearly 150million tourists by 2013 to the rural communities. Rural tourism can be new income source in the rural communities in Korea. It is important to develop the resources in the rural amenity and promote the tourism leader group with it that will be applicable in the field in order that this rural tourism may take its place as main source of income. As a result of research, on the characteristics of the Korea National Agricultural College that the demand of manpower about the rural tourism and the most of students settled down on the rural community after their graduation, it has been determined that the education for rural tourism leaders in the Korea National Agricultural College would authenticate the validity. Also, it suggested the educational plan by the curriculum for the education for the rural tourism leaders, and suggested the necessity of the establishment of the department of rural tourism. The establishment of the department of rural tourism in the Korea National Agricultural College should be investigated and determined carefully through the relations with the other departments and the process of collecting the public opinions within and outside schools, etc.

• International Journal of Advanced Culture Technology
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• v.10 no.1
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• pp.274-283
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• 2022

Korea is facing a number difficulties arising from rising housing prices. As 'housing' takes the lion's share in personal assets, many difficulties are expected to arise from fluctuating housing prices. The purpose of this study is creating housing price prediction model to prevent such risks and induce reasonable real estate purchases. This study made many attempts for understanding real estate instability and creating appropriate housing price prediction model. This study predicted and validated housing prices by using the LSTM technique - a type of Artificial Intelligence deep learning technology. LSTM is a network in which cell state and hidden state are recursively calculated in a structure which added cell state, which is conveyor belt role, to the existing RNN's hidden state. The real sale prices of apartments in autonomous districts ranging from January 2006 to December 2019 were collected through the Ministry of Land, Infrastructure, and Transport's real sale price open system and basic apartment and commercial district information were collected through the Public Data Portal and the Seoul Metropolitan City Data. The collected real sale price data were scaled based on monthly average sale price and a total of 168 data were organized by preprocessing respective data based on address. In order to predict prices, the LSTM implementation process was conducted by setting training period as 29 months (April 2015 to August 2017), validation period as 13 months (September 2017 to September 2018), and test period as 13 months (December 2018 to December 2019) according to time series data set. As a result of this study for predicting 'prices', there have been the following results. Firstly, this study obtained 76 percent of prediction similarity. We tried to design a prediction model of real estate transaction price with the LSTM Model based on AI and Bigdata. The final prediction model was created by collecting time series data, which identified the fact that 76 percent model can be made. This validated that predicting rate of return through the LSTM method can gain reliability.

• Journal of Software Assessment and Valuation
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• v.7 no.1
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• pp.29-39
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• 2011

To evaluate the quality of clone detection tools, we should know how many clones the tool misses. Hence we need to have the standard code-clone reference corpus for a carefully chosen set of sample source codes. The reference corpus available so far has been built by manually collecting clones from the results of various existing tools. This paper presents a tree-pattern-based clone detection tool that can be used for automatic generation of reference corpus. Our tool is compared with CloneDR for precision and Bellon's reference corpus for recall. Our tool finds no false positives and 2 to 3 times more clones than CloneDR. Compared to Bellon's reference corpus, our tools shows the 93%-to-100% recall rate and detects far more clones.

• Journal of the Korea institute for structural maintenance and inspection
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• v.27 no.6
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• pp.144-151
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• 2023

In this study, a database was established by collecting experimental results on various concrete mixtures subjected to freeze-thaw cycles, based on which an artificial neural network-based prediction model was developed to estimate durability resistance of concrete. A regression analysis was also conducted to derive an equation for estimating relative dynamic modulus of elasticity subjected to freeze-thaw loads. The error rate and coefficient of determination of the proposed artificial neural network model were approximately 11% and 0.72, respectively, and the regression equation also provided very similar accuracy. Thus, it is considered that the proposed artificial neural network model and regression equation can be used for estimating relative dynamic modulus of elasticity for various concrete mixtures subjected to freeze-thaw loads.

• Journal of the Korea Safety Management & Science
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• v.25 no.4
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• pp.141-151
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• 2023

Recently, due to the expansion of the logistics industry, demand for logistics automation equipment is increasing. The modern logistics industry is a high-tech industry that combines various technologies. In general, as various technologies are grafted, the complexity of the system increases, and the occurrence rate of defects and failures also increases. As such, it is time for a predictive maintenance model specialized for logistics automation equipment. In this paper, in order to secure the operational safety and reliability of the parcel loading system, a predictive maintenance platform was implemented based on the Naive Bayes-LSTM(Long Short Term Memory) model. The predictive maintenance platform presented in this paper works by collecting data and receiving data based on a RabbitMQ, loading data in an InMemory method using a Redis, and managing snapshot DB in real time. Also, in this paper, as a verification of the Naive Bayes-LSTM predictive maintenance platform, the function of measuring the time for data collection/storage/processing and determining outliers/normal values was confirmed. The predictive maintenance platform can contribute to securing reliability and safety by identifying potential failures and defects that may occur in the operation of the parcel loading system in the future.

• Convergence Security Journal
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• v.23 no.5
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• pp.45-55
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• 2023

With the widespread use of digital devices, anonymous communication technologies such as the dark web and deep web are becoming increasingly popular for criminal activity. Because these technologies leave little local data on the device, they are difficult to track using conventional crime investigation techniques. The United States and the United Kingdom have enacted laws and developed systems to address this issue, but South Korea has not yet taken any significant steps. This paper proposes a new blockchain-based crime investigation method that uses physical memory data analysis to track the behavior of anonymous network users. The proposed method minimizes infringement of basic rights by only collecting physical memory data from the device of the suspected user and storing the tracking information on a blockchain, which is tamper-proof and transparent. The paper evaluates the effectiveness of the proposed method using a simulation environment and finds that it can track the behavior of dark website users with a residual rate of 77.2%.