• Communications of Mathematical Education
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• v.37 no.4
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• pp.717-736
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• 2023

The purpose of this study is to develop a statistical program using data and artificial intelligence prediction models and apply it to one class in the sixth grade of elementary school to see if it is effective in improving students' statistical literacy. Based on the analysis of problems in today's elementary school statistical education, a total of 15 sessions of the program was developed to encourage elementary students to experience the entire process of statistical problem solving and to make correct predictions by incorporating data, the core in the era of the Fourth Industrial Revolution into AI education. The biggest features of this program are the recognition of the importance of data, which are the key elements of artificial intelligence education, and the collection and analysis activities that take into account context using real-life data provided by public data platforms. In addition, since it consists of activities to predict the future based on data by using engineering tools such as entry and easy statistics, and creating an artificial intelligence prediction model, it is composed of a program focused on the ability to develop communication skills, information processing capabilities, and critical thinking skills. As a result of applying this program, not only did the program positively affect the statistical literacy of elementary school students, but we also observed students' interest, critical inquiry, and mathematical communication in the entire process of statistical problem solving.

• Journal of the Korean Society of Radiology
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• v.17 no.6
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• pp.947-955
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• 2023

This study was conducted to investigate the awareness of spent nuclear fuel among residents in nuclear power plant areas and use it as basic data for establishing a disposal facility for high-level radioactive waste. 204 questionnaires collected online were analyzed using SPSS Window Ver 28.0. To verify differences between groups, t-test and one-way ANOVA were performed. And correlation analysis was conducted to confirm the relationship between variables. As a result, first, risk perception regarding nuclear-related accidents showed statistically significant differences depending on gender and educational level. The position on the construction of a permanent disposal facility for spent nuclear fuel showed a statistically significant difference depending on gender, education, and age, and the perception of the importance of each evaluation standard for establishing a spent nuclear fuel management plan showed a statistically significant difference depending on education and age. In terms of trust in information-providing institutions, trust in the National Assembly was found to be the lowest. Second, the results of the correlation analysis between variables showed that local residents are aware that an alternative to the current disposal of spent nuclear fuel is needed, and that financial support for the construction of a permanent disposal facility is needed. Therefore, in order to build a high-level radioactive waste disposal site, it is believed that it is necessary to increase trust in the government, collect opinions from local residents, and provide economic support.

• Journal of Internet Computing and Services
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• v.24 no.6
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• pp.73-80
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• 2023

The recent steep increase in the minimum hourly wage has increased the burden of labor costs, and the share of unmanned stores is increasing in the aftermath of COVID-19. As a result, theft crimes targeting unmanned stores are also increasing, and the "Just Walk Out" system is introduced to prevent such thefts, and LiDAR sensors, weight sensors, etc. are used or manually checked through continuous CCTV monitoring. However, the more expensive sensors are used, the higher the initial cost of operating the store and the higher the cost in many ways, and CCTV verification is difficult for managers to monitor around the clock and is limited in use. In this paper, we would like to propose an AI image processing fusion algorithm that can solve these sensors or human-dependent parts and detect customers who perform abnormal behaviors such as theft at low costs that can be used in unmanned stores and provide cloud-based notifications. In addition, this paper verifies the accuracy of each algorithm based on behavior pattern data collected from unmanned stores through motion capture using mediapipe, object detection using YOLO, and fusion algorithm and proves the performance of the convergence algorithm through various scenario designs.

• Korean Journal of Construction Engineering and Management
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• v.25 no.1
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• pp.32-41
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• 2024

In the construction industry, not only safety accidents, but also various complex risks such as construction delays, cost increases, and environmental pollution occur, and management technologies are needed to solve them. Among them, process risk management, which directly affects the project, lacks related information compared to its importance. This study tried to develop a MATM tunnel process risk classification system to solve the difficulty of risk information retrieval due to the use of different classification systems for each project. Risk collection used existing literature review and experience mining techniques, and DB construction utilized the concept of natural language processing. For the structure of the classification system, the existing WBS structure was adopted in consideration of compatibility of data, and an RBS linked to the work species of the WBS was established. As a result of the research, a risk classification system was completed that easily identifies risks by work type and intuitively reveals risk characteristics and risk factors linked to risks. As a result of verifying the usability of the established classification system, it was found that the classification system was effective as risks and risk factors for each work type were easily identified by user input of keywords. Through this study, it is expected to contribute to preventing an increase in cost and construction period by identifying risks according to work types in advance when planning and designing NATM tunnels and establishing countermeasures suitable for those factors.

• Journal of Korean Tunnelling and Underground Space Association
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• v.25 no.6
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• pp.479-493
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• 2023

The need for safety management has arisen due to the increasing number of years of operated underground structures, such as tunnels and utility tunnels, and accidents caused by those aging infrastructures. However, in the case of privately managed underground utility ducts, there is a lack of detailed guidelines for facility safety and maintenance, resulting in inadequate safety management. Furthermore, the absence of basic design information and the limited space for safety assessments make applying currently used non-destructive testing methods challenging. Therefore, this study suggests non-destructive inspection methods using ultrasonic and impact-echo techniques to assess the quality of underground structures. Thickness, presence of rebars, depth of rebars, and the presence and depth of internal defects are assessed to provide fundamental data for the safety assessment of box-type general underground structures. To validate the proposed methodology, different conditions of concrete specimens are designed and cured to simulate actual field conditions. Applying ultrasonic and impact signals and collecting data through multi-channel accelerometers determine the thickness of the simulated specimens, the depth of embedded rebar, and the extent of defects. The predicted results are well agreed upon compared with actual measurements. The proposed methodology is expected to contribute to developing safety diagnostic methods applicable to general underground structures in practical field conditions.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.34 no.4
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• pp.781-799
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• 2024

Recently, the US and EU have been institutionally introducing and promoting Coordinated Vulnerability Disclosure(CVD) to strengthen the response to security vulnerabilities in ICT products and services, based on collaboration with white-hat hackers. In response to these changes in cybersecurity, we propose a three-step approach to introduce CVD through the Information and Communications Network Act(ICNA). In the first step, to comprehend the necessity and requirements for legislating CVD, we survey the current situation in Korea and the trends of CVD in the US, EU, and OECD. In the second step, we analyze the necessity for legislating CVD and derive the requirements for its legislation. In this paper, we analyze the necessity for legislating CVD from three perspectives: the need for introducing CVD, the need for institutionalization based on law, and the suitability of the ICNA as the legislation. The derived requirements for CVD legislation include the establishment and publication of Vulnerability Disclosure Policy(VDP), legal protection for white-hat hackers, and designation and role assignments of coordinator. In the third step, we introduce approaches to apply the requirements for CVD legislation to the ICNA, which is the law governing prevention and response to cybersecurity incidents in private sector.

• Journal of IKEEE
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• v.23 no.4
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• pp.1461-1464
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• 2019

In this paper, we propose the development of embedded board for integrated radiation exposure protection fireman's life-saving alarm capable of location tracking and radiation measurement. The proposed techniques consist of signal processing unit, communication unit, power unit, main control unit. Signal processing units apply shielding design, noise reduction technology and electromagnetic wave subtraction technology. The communication unit is designed to communicate using the wifi method. In the main control unit, power consumption is reduced to a minimum, and a high performance system is formed through small, high density and low heat generation. The proposed techniques are equipment operated by exposure to poor conditions, such as disaster and fire sites, so they are designed and manufactured for external appearance considering waterproof and thermal endurance. The proposed techniques were tested by an authorized testing agency to determine the effectiveness of embedded board. The waterproof grade has achieved the IP67 rating, which can maintain stable performance even when flooded with water at the disaster site due to the nature of the fireman's equipment. The operating temperature was measured in the range of -10℃ to 50℃ to cope with a wide range of environmental changes at the disaster site. The battery life was measured to be available 144 hours after a single charge to cope with emergency disasters such as a collapse accident. The maximum communication distance, including the PCB, was measured to operate at 54.2 meters, a range wider than the existing 50 meters, at a straight line with the command-and-control vehicle in the event of a disaster. Therefore, the effectiveness of embedded board for embedded board for integrated radiation exposure protection fireman's life-saving alarm has been demonstrated.

• Horticultural Science & Technology
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• v.30 no.4
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• pp.442-448
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• 2012

Many outbreaks of food-borne illnesses have been associated with the consumption of fresh vegetables and fruits contaminated with food-borne pathogens. Contaminated medium, manure and irrigation water are probable vehicles for the pathogen in many outbreaks. The aim of this study was to determine the potential transfer of Escherichia coli and Bacillus cereus from medium and soil fertilized with contaminated compost or irrigation with contaminated water to the edible parts of lettuce. Moreover, survivals of the two pathogens on lettuce contaminated medium, soil and irrigation water were estimated. Lettuce seeds were planted in medium contaminated with 7.5 log colony forming unit (CFU)/g of E. coli and B. cereus. Seedlings grown in the contaminated medium were transplanted in soil fertilized with contaminated pig manure compost or uncontaminated soil. Contaminated irrigation water with E. coli and B. cereus at 8.0 log CFU/mL was applied only once on the plant by sprinkle irrigation and surface irrigation. Although E. coli and B. cereus in medium and sprouted lettuce after planting seeds were reduced as time passed, these pathogens survived in seedling raising stage for extended periods. The numbers of E. coli and B. cereus in lettuce grown on contaminated soil were detected over 4.0 log CFU/g for 21 days. The numbers of E. coli and B. cereus in lettuce applied by sprinkle irrigation were higher than those of surface irrigation by 5.0 log CFU/g. Our results indicated that contaminated medium, soil and irrigation water can play an important role in the presence of food-borne pathogens on vegetables.

• The KIPS Transactions:PartB
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• v.10B no.3
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• pp.281-286
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• 2003

A large number of features are collected for problem solving in real life, but to utilize ail the features collected would be difficult. It is not so easy to collect of correct data about all features. In case it takes advantage of all collected data to learn, complicated learning model is created and good performance result can't get. Also exist interrelationships or hierarchical relations among the features. We can reduce feature's number analyzing relation among the features using heuristic knowledge or statistical method. Heuristic technique refers to learning through repetitive trial and errors and experience. Experts can approach to relevant problem domain through opinion collection process by experience. These properties can be utilized to reduce the number of feature used in learning. Experts generate a new feature (highly abstract) using raw data. This paper describes machine learning model that reduce the number of features used in learning using heuristic function and use abstracted feature by neural network's input value. We have applied this model to the win/lose prediction in pro-baseball games. The result shows the model mixing two techniques not only reduces the complexity of the neural network model but also significantly improves the classification accuracy than when neural network and heuristic model are used separately.

• Journal of Life Science
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• v.17 no.12
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• pp.1660-1668
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• 2007

The non-ionic surfactant (NIS) Tween 80 was evaluated for its ability to influence invitro cumulative gas production, dry matter digestibility, cellulolytic enzyme activities, anaerobic microbial growth rates, and adhesion to substrates by mixed rumen microorganisms on rice straw, alfalfa hay, cellulose filter paper and tall fescue hay. The addition of NIS Tween 80 at a level of 0.05% increased significantly (P<0.05) in vitro DM digestibility, cumulative gas production, microbial growth rate and cellulolytic enzyme activity from all of substrates used in this study. In vitro cumulative gas production from the NIS-treated substrates; rice straw, alfalfa hay, filter paper and tall fescue hay was significantly (P<0.05) improved by 274.8, 235.2, 231.1 and 719.5% compared with the control, when substrates were incubated for 48 hr in vitro. The addition of 0.05% NIS Tween 80 to cultures growing on alfalfa hay resulted in a significant increase in CMCase (38.1%), xylanase (121.4%), Avicelase (not changed) and amylase (38.2%) activities after 36 h incubation. These results indicated that the addition of 0.05% Tween 80 could greatly stimulate the release of some kinds of cellulolytic enzymes without decreasing cell growth rate in contrast to trends reported with aerobic microorganism. Our SEM observation showed that NIS Tween. 80 did not influence the microbial adhesion to substrates used in the study. Present data clearly show that improved gas production, DM digestibility and cellulolytic enzyme activity by Tween 80 is not due to increased bacterial adhesion on the substrates.