• Journal of the Society of Disaster Information
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• v.19 no.1
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• pp.216-230
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• 2023

Purpose: The purpose is to prevent accidents by predicting disasters through the analysis of near-miss. Method: In this study, a near-miss literature review and data were collected at construction sites, and a questionnaire survey was conducted to use logistic regression analysis and decision tree analysis to classify the possibility of near-miss connection. Result: As a result of analyzing the effects of near-miss types on mental, physical, and safety habits and behaviors, the factor with a high influence on the body is the need for near-miss management, the type of job is electricity·information communication, and health status in order, and the mental factor is the construction scale The influence was high, and the factors with the highest influence on the habit behavior factors were analyzed in the order of experience, number of serious injuries, and occupation in order of illusion, inappropriate work instructions, and body parts. Through decision tree analysis, factors and patterns that affect the possibility of a near-miss being a surprise accident were identified. Conclusion: Construction site officials consider the observation of near-miss and mentally and physically. Specific management of the relevance of physical aspects to near-miss should be implemented, and a work environment in which serious accidents are reduced is expected through personnel allocation, work plans, work procedures and methods, and feedback so that inappropriate work instructions do not lead to near-miss.

• Journal of Animal Science and Technology
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• v.65 no.1
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• pp.244-257
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• 2023

The study aimed to investigate the effect of low-frequency oscillations on the cow udder, milk parameters, and animal welfare during the automated milking process. The study's objective was to investigate the impact of low-frequency oscillations on the udder and teats' blood circulation by creating a mathematical model of mammary glands, using milkers and vibrators to analyze the theoretical dynamics of oscillations. The mechanical vibration device developed and tested in the study was mounted on a DeLaval automatic milking machine, which excited the udder with low-frequency oscillations, allowing the analysis of input parameters (temperature, oscillation amplitude) and using feedback data, changing the device parameters such as vibration frequency and duration. The experimental study was performed using an artificial cow's udder model with and without milk and a DeLaval milking machine, exciting the model with low-frequency harmonic oscillations (frequency range 15-60 Hz, vibration amplitude 2-5 mm). The investigation in vitro applying low-frequency of the vibration system's first-order frequencies in lateral (X) direction showed the low-frequency values of 23.5-26.5 Hz (effective frequency of the simulation analysis was 25.0 Hz). The tested values of the first-order frequency of the vibration system in the vertical (Y) direction were 37.5-41.5 Hz (effective frequency of the simulation analysis was 41.0 Hz), with higher amplitude and lower vibration damping. During in vivo experiments, while milking, the vibrator was inducing mechanical milking-similar vibrations in the udder. The vibrations were spreading to the entire udder and caused physiotherapeutic effects such as activated physiological processes and increased udder base temperature by 0.57℃ (p < 0.001), thus increasing blood flow in the udder. Used low-frequency vibrations did not significantly affect milk yield, milk composition, milk quality indicators, and animal welfare. The investigation results showed that applying low-frequency vibration on a cow udder during automatic milking is a non-invasive, efficient method to stimulate blood circulation in the udder and improve teat and udder health without changing milk quality and production. Further studies will be carried out in the following research phase on clinical and subclinical mastitis cows.

• Journal of the Korea Society of Computer and Information
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• v.14 no.11
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• pp.81-90
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• 2009

It is inevitable for college students to be confused when they first face university education, which requires them to be self-reliant and responsible, after finishing their course of education, which is passive under control of period and environment, in primary, middle, and high schools. Introduction to college courses, which require students to be subjective and responsible, to be taken after chronically and environmentally controlled primary and secondary education, are but confusing. In this stage, college education should provide ground for educational system so that students can escape from repetitively enforced way of studying of fixed curriculums and study creatively and subjectively while befitting each individual's aptitude. For instance, in programming classes in engineering school, students scholastic achievements are closely interrelated with the professor's educational principles. A change in method of education, from one previously focused on theoretical contents to one centered on practices and experiments, can reap good results. Also, as the need arose for introduction of practice-focused evaluation system, from recognition-centered professor evaluating system to enablement of actively developing creative and self-reliant way of learning, we applied the Rublic System. It is a feedback system that all or most students become the evaluators, of which the indicators of evaluation such as category, standard, and score are public. We have looked into whether or not there has been an improvement in GPAs of students, and if there exists an improvement then what efforts should be made to solidify the system.

• The Journal of Bigdata
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• v.8 no.1
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• pp.83-97
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• 2023

Project evaluation is the process of evaluating the progress and results of a project. Smart city projects can be divided into system components (infrastructure, services, platforms), or projects can run simultaneously for multiple services. In addition, services are developed and expanded through additional projects. In order to ensure that the smart city, which is composed of various projects, proceeds in accordance with the goals and strategies, periodic project evaluation is required during the project implementation process. The smart city project evaluation system proposed in this paper is designed to provide comprehensive and objective indicators by reflecting various factors that must be considered for projects occurring in all stages of planning, design, construction, and operation of smart cities. The indicators derived from the evaluation system can be used by decision makers to determine the direction of smart city project development. In addition, it is designed so that the performance of the project can be evaluated interim before the end of the project and the feedback obtained from it can be reflected. To introduce the application method of the smart city project evaluation system proposed in this study, the evaluation system developed in this study was applied to the smart city project case of Incheon Free Economic Zone (IFEZ). Based on the evaluation results, items that can maximize the improvement effect of each smart city project item were presented, and the direction of smart city project implementation was suggested. By utilizing a smart city project evaluation system that reflects the characteristics of smart city projects that are composed of multiple projects, comprehensive planning and management of smart city projects will be possible, and this study will serve as a reference for identifying priority improvement factors for projects.

• The Journal of the Convergence on Culture Technology
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• v.9 no.6
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• pp.539-544
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• 2023

In this study, several important aspects were studied in producing video advertisements based on the lifestyle and SNS status of Generation Z. Generation Z highly values participation and interaction due to the nature of SNS, so SNS advertisements should be produced in a way that induces active interaction with viewers and accepts feedback. Here's a summary of the main parts. It prefers various content formats of Generation Z that consume information. Advertisements should be produced in various formats such as text, images, and videos, and should have flexibility suitable for various platforms. Because each SNS platform has its own characteristics due to platform specialization, this study suggests that advertisements analyze the characteristics of the platform and use the appropriate content strategy for the optimized platform. As an emphasis on value proposition, we propose an advertising format setting to focus on what value the product or brand provides. It is important to clearly emphasize the advantages and intrinsic value of a product or service in video advertising, and in conclusion, we propose to focus on the case of increasing interest by adopting modern and trendy design of storytelling as an attractive and unique design method of aesthetic design and visual effects. Considering these factors comprehensively, the research value of this paper will be able to establish an effective SNS marketing strategy by producing video advertisements that match the lifestyle and SNS usage characteristics of Generation Z.

• Journal of the Korea Society of Computer and Information
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• v.29 no.1
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• pp.273-285
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• 2024

With the active utilization of Online Judge (OJ) systems in the field of education, various studies utilizing learner data have emerged. This research proposes a problem recommendation based on a user-based collaborative filtering approach with learner data to support learners in their problem selection. Assistance in learners' problem selection within the OJ system is crucial for enhancing the effectiveness of education as it impacts the learning path. To achieve this, this system identifies learners with similar problem-solving tendencies and utilizes their problem-solving history. The proposed technique has been implemented on an OJ site in the fields of algorithms and programming, operated by the Chungbuk Education Research and Information Institute. The technique's service utility and usability were assessed through expert reviews using the Delphi technique. Additionally, it was piloted with site users, and an analysis of the ratio of correctness revealed approximately a 16% higher submission rate for recommended problems compared to the overall submissions. A survey targeting users who used the recommended problems yielded a 78% response rate, with the majority indicating that the feature was helpful. However, low selection rates of recommended problems and low response rates within the subset of users who used recommended problems highlight the need for future research focusing on improving accessibility, enhancing user feedback collection, and diversifying learner data analysis.

• Journal of the Korea Society of Computer and Information
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• v.29 no.7
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• pp.11-20
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• 2024

In this paper, we propose the BAG (Bit-width Aware Generator) and the Intermediate Layer Knowledge Distillation using Channel-wise Attention to reduce the knowledge gap between a quantized network, a full-precision network, and a generator in GDFQ (Generative Data-Free Quantization). Since the generator in GDFQ is only trained by the feedback from the full-precision network, the gap resulting in decreased capability due to low bit-width of the quantized network has no effect on training the generator. To alleviate this problem, BAG is quantized with same bit-width of the quantized network, and it can generate synthetic images, which are effectively used for training the quantized network. Typically, the knowledge gap between the quantized network and the full-precision network is also important. To resolve this, we compute channel-wise attention of outputs of convolutional layers, and minimize the loss function as the distance of them. As the result, the quantized network can learn which channels to focus on more from mimicking the full-precision network. To prove the efficiency of proposed methods, we quantize the network trained on CIFAR-100 with 3 bit-width weights and activations, and train it and the generator with our method. As the result, we achieve 56.14% Top-1 Accuracy and increase 3.4% higher accuracy compared to our baseline AdaDFQ.

• Journal of Christian Education in Korea
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• v.77
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• pp.251-276
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• 2024

This study aimed to enhance the educational competencies of instructors and improve the quality of higher education by identifying instructing types, developing an assessment diagnostic tool, and designing a customized faculty training curriculum for each type. To achieve this, a literature review and Delphi research were conducted. The results are summarized as follows: First, instructing types such as 'Star Lecturer', 'Learning Mentor', and 'Designer' were identified through the analysis of previous studies. Second, a diagnostic tool for determining an instructor's type was developed by modifying and enhancing Grasha's Teaching Style Inventory, which is widely used both domestically and internationally. This tool comprises 24 questions, with 8 questions for each type. Third, a curriculum was designed for each instructing type, consisting of common courses necessary for all types and specialized courses tailored to the characteristics of each type. The common courses cover essentials for lesson design, implementation, and evaluation, while the specialized courses cater to the unique needs of each instructing type. Fourth, the developed model, tools, and curriculum underwent validation. A Delphi method was employed with a group of 10 experts, leading to revisions and finalizations based on their feedback. This study has laid the groundwork for instructors to identify their own teaching styles and receive customized training, thereby enhancing their teaching effectiveness and overall educational quality. However, further research is necessary to develop systems and mechanisms for the operationalization of these findings, including incentives for instructors and strategies for disseminating information among participants.

• Journal of Intelligence and Information Systems
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• v.25 no.1
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• pp.139-161
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• 2019

The utilization of the e-commerce market has become a common life style in today. It has become important part to know where and how to make reasonable purchases of good quality products for customers. This change in purchase psychology tends to make it difficult for customers to make purchasing decisions in vast amounts of information. In this case, the recommendation system has the effect of reducing the cost of information retrieval and improving the satisfaction by analyzing the purchasing behavior of the customer. Amazon and Netflix are considered to be the well-known examples of sales marketing using the recommendation system. In the case of Amazon, 60% of the recommendation is made by purchasing goods, and 35% of the sales increase was achieved. Netflix, on the other hand, found that 75% of movie recommendations were made using services. This personalization technique is considered to be one of the key strategies for one-to-one marketing that can be useful in online markets where salespeople do not exist. Recommendation techniques that are mainly used in recommendation systems today include collaborative filtering and content-based filtering. Furthermore, hybrid techniques and association rules that use these techniques in combination are also being used in various fields. Of these, collaborative filtering recommendation techniques are the most popular today. Collaborative filtering is a method of recommending products preferred by neighbors who have similar preferences or purchasing behavior, based on the assumption that users who have exhibited similar tendencies in purchasing or evaluating products in the past will have a similar tendency to other products. However, most of the existed systems are recommended only within the same category of products such as books and movies. This is because the recommendation system estimates the purchase satisfaction about new item which have never been bought yet using customer's purchase rating points of a similar commodity based on the transaction data. In addition, there is a problem about the reliability of purchase ratings used in the recommendation system. Reliability of customer purchase ratings is causing serious problems. In particular, 'Compensatory Review' refers to the intentional manipulation of a customer purchase rating by a company intervention. In fact, Amazon has been hard-pressed for these "compassionate reviews" since 2016 and has worked hard to reduce false information and increase credibility. The survey showed that the average rating for products with 'Compensated Review' was higher than those without 'Compensation Review'. And it turns out that 'Compensatory Review' is about 12 times less likely to give the lowest rating, and about 4 times less likely to leave a critical opinion. As such, customer purchase ratings are full of various noises. This problem is directly related to the performance of recommendation systems aimed at maximizing profits by attracting highly satisfied customers in most e-commerce transactions. In this study, we propose the possibility of using new indicators that can objectively substitute existing customer 's purchase ratings by using RFM multi-dimensional analysis technique to solve a series of problems. RFM multi-dimensional analysis technique is the most widely used analytical method in customer relationship management marketing(CRM), and is a data analysis method for selecting customers who are likely to purchase goods. As a result of verifying the actual purchase history data using the relevant index, the accuracy was as high as about 55%. This is a result of recommending a total of 4,386 different types of products that have never been bought before, thus the verification result means relatively high accuracy and utilization value. And this study suggests the possibility of general recommendation system that can be applied to various offline product data. If additional data is acquired in the future, the accuracy of the proposed recommendation system can be improved.

• Journal of Korean Home Economics Education Association
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• v.27 no.1
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• pp.51-65
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• 2015

The purpose of the study was to describe the operating status of "Logic and Writing in Home Economics Education(HEE)" course and the students' perception about the course. For this study, the syllabuses of "Logic and Writing" course in HE education department were reviewed. The survey method was used in this descriptive study. Respondents in this study were 116 students taking the "Logic and Writing in Home Economics Education" course. Questionnaires from the students were collected through on-line and off-line mail. The results of the study were as the follows: First, goals of the "Logic and Writing in HE Education" course were as the follows in order: to enhance writing skill about various subjects related to Home Economics; to foster HE teachers' professionalism through persuasive power logically; to foster writing skill logically; to prepare HE teacher recruitment exam; and to foster teaching skills to enhance students' writing. The student evaluation methods in the course were mainly attendance, examination, tasks, discussion and presentation, and class participation. Second, degree of satisfaction of students taking the course was higher than average. The student respondents perceived that the course was helpful to improve their logical thinking and critical analytical skill, writing skill related to HE education and education, ability to express one's opinion clearly and exactly, understanding of the fundamental concept of logic and the structure and method of the essay, comprehensive understanding of HE education, and ability to solve the problems specifically. However, they responded that it was difficult to practice writing, to discuss and debate frequently, to follow uncertain assessment criteria, and to present frequently. They wanted the instructor to give the feedback more frequently.