• KIPS Transactions on Computer and Communication Systems
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• v.11 no.10
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• pp.323-332
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• 2022

As various services using AI technology are being developed, much attention is being paid to AI service production. Recently, AI technology is acknowledged as one of ICT services, a lot of research is being conducted for general-purpose AI service production. In this paper, I describe the research results in terms of systems for AI service production, focusing on the distribution and production of machine learning models, which are the final steps of general machine learning development procedures. Three different Ubuntu systems were built, and experiments were conducted on the system, using data from 2017 validation COCO dataset in combination of different AI models (RFCN, SSD-Mobilenet) and different communication methods (gRPC, REST) to request and perform AI services through Tensorflow serving. Through various experiments, it was found that the type of AI model has a greater influence on AI service inference time than AI machine communication method, and in the case of object detection AI service, the number and complexity of objects in the image are more affected than the file size of the image to be detected. In addition, it was confirmed that if the AI service is performed remotely rather than locally, even if it is a machine with good performance, it takes more time to infer the AI service than if it is performed locally. Through the results of this study, it is expected that system design suitable for service goals, AI model development, and efficient AI service production will be possible.

• 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.

• KIPS Transactions on Software and Data Engineering
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• v.12 no.9
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• pp.381-386
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• 2023

Many existing test case generation researchers extract test cases from models. However, research on generating test cases from natural language requirements is required in practice. For this purpose, the combination of natural language analysis and requirements engineering is very necessary. However, Requirements analysis written in Korean is difficult due to the diverse meaning of sentence expressions. We research test case generation through natural language requirement definition analysis, C3Tree model, cause-effect graph, and decision table steps as one of the test case generation methods from Korean natural requirements. As an intermediate step, this paper generates test cases from C3Tree model-based decision tables using meta-modeling. This method has the advantage of being able to easily maintain the model-to-model and model-to-text transformation processes by modifying only the transformation rules. If an existing model is modified or a new model is added, only the model transformation rules can be maintained without changing the program algorithm. As a result of the evaluation, all combinations for the decision table were automatically generated as test cases.

• KIPS Transactions on Software and Data Engineering
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• v.12 no.3
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• pp.141-148
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• 2023

Accurate overlay metrology is essential to achieve high yields of semiconductor products. Overlay metrology performance is greatly affected by overlay target design and measurement method. Therefore, in order to improve the performance of the overlay target, measurement methods applicable to various targets are required. In this study, we propose a new algorithm that can measure image-based overlay. The proposed measurement algorithm can estimate the sub-pixel position by using a motion vector. The motion vector may estimate the position of the sub-pixel unit by applying a quadratic equation model through polynomial expansion using pixels in the selected region. The measurement method using the motion vector can calculate the stacking error in all directions at once, unlike the existing correlation coefficient-based measurement method that calculates the stacking error on the X-axis and the Y-axis, respectively. Therefore, more accurate overlay measurement is possible by reflecting the relationship between the X-axis and the Y-axis. However, since the amount of computation is increased compared to the existing correlation coefficient-based algorithm, more computation time may be required. The purpose of this study is not to present an algorithm improved over the existing method, but to suggest a direction for a new measurement method. Through the experimental results, it was confirmed that measurement results similar to those of the existing method could be obtained.

• The Korean Journal of Franchise Management
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• v.2 no.2
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• pp.70-83
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• 2011

The number of agricultural products due to open in response to international competitiveness of the farming press and the need for structural adjustment in agriculture and in agricultural crops receive a fair market price, fair trade, such as improving efficiency sidaejeo appropriate response to the request of the government must have. For this purpose, compared to the communist bojaphan agricultural water efficiently changing the structure of the distribution, agricultural products originating from the acquisition phase choice of shipping a stable product supply and plans to expand production system to induce a smooth supply of agricultural products, expand processing capacity and sales control should be. Also, in the distribution process by eliminating various immoral conduct commerce retail establishment and enforcement of policies for efficient and accurate distribution statistics, information is needed. The ultimate goal of agricultural restructuring and ensure fair price for producers sangpuui and improvement of production facilities for maximizing and affordable for consumers, according to your preferences to receive the best offer will be Foo. Therefore, management increases the efficiency of just distribution costs, or margins, lowering the improvement is not practical to restructure the distribution structure of costs for the best product and must supply the next country of agricultural products, strengthen the consumer's purchase desire to meet will be.

• Asia Marketing Journal
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• v.13 no.1
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• pp.113-141
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• 2011

Companies are competing each other, and as the competitions became higher, consumer's information processing for purchase became more complicated. Consumer confusion problem is getting more serious, but there are still not much considerations on this problem. The purpose of this study is to find out that the consumer confusion can causes consumer's negative emotion(anger). This research studied the mediation effect of negative emotion on the relationship between consumer confusion, which was classified into three categories, and two consequences, word-of-mouth and trust. And also it concentrates on moderating effects of negative affectivity and intolerance of uncertainty in the relationship between consumer confusion and negative emotion. For the empirical study, we carried out a survey targeting consumers who live in the Dae-gu metropolitan area. The specific results of this study are as follows. First, all sub-dimensions of the consumer confusion had a positive effect on anger. Second, anger had a positive effect on word of mouth and on the other hand, anger had a negative effect on trust. Third, negative affectivity had a moderating effects on the links between overload and ambiguity confusion with anger, and intolerance of uncertainty only had a moderating effects on the links between overload confusion and anger.

• 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.

• KIPS Transactions on Software and Data Engineering
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• v.12 no.10
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• pp.455-460
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• 2023

Text augmentation is a methodology that creates new augmented texts by transforming or generating original texts for the purpose of improving the performance of NLP models. However existing text augmentation techniques have limitations such as lack of expressive diversity semantic distortion and limited number of augmented texts. Recently text augmentation using large language models and few-shot learning can overcome these limitations but there is also a risk of noise generation due to incorrect generation. In this paper, we propose a text augmentation method called TAGS that generates multiple candidate texts and selects the appropriate text as the augmented text. TAGS generates various expressions using few-shot learning while effectively selecting suitable data even with a small amount of original text by using contrastive learning and similarity comparison. We applied this method to task-oriented chatbot data and achieved more than sixty times quantitative improvement. We also analyzed the generated texts to confirm that they produced semantically and expressively diverse texts compared to the original texts. Moreover, we trained and evaluated a classification model using the augmented texts and showed that it improved the performance by more than 0.1915, confirming that it helps to improve the actual model performance.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.19 no.3
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• pp.69-79
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• 2024

Companies should resolve consumer dissatisfaction and increase brand loyalty by actively identifying the factors of consumer dissatisfaction and proactively responding to expected complaint behavior to induce repurchase. This is a management goal that should be pursued in common regardless of the size of the company. The specific purpose of this study is to find out whether the degree of dissatisfaction differs depending on whether or not consumers' expected performance before purchase and the actual perceived performance after purchase is compared, whether the degree of dissatisfaction affects the type of complaint behavior, which is a subsequent behavior, and whether the attributable behavior has a moderating effect in this process and whether the persistence of the result and the controllability of the cause act as a factor that determines the attribution position. In particular, compared to general companies, venture companies are more likely to overload the information processing ability of managers and are likely to make various irrational errors in decision making, so this study has important academic and practical implications. As a result of the analysis, the negative inconsistency group had the highest degree of dissatisfaction, and the higher the degree of inconsistency, the higher the dissatisfaction. The attributable behavior of unsatisfied consumers had a moderating effect on the degree of dissatisfaction, and the dissatisfaction was significantly higher in the external attributable group than the internal attributable group, which was statistically significant. On the other hand, the persistence of the result had a statistically significant effect on the attribution position, but the controllability of the cause was not. The degree of attributable behavior and dissatisfaction did not affect the type of complaining behavior, showing limited influence. Along with the interpretation of these results, this study presents various implications, especially for small and medium-sized/venture companies that provide new durable products.

• The korean journal of orthodontics
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• v.27 no.5 s.64
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• pp.815-824
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• 1997

The purpose of this study is to develop the basic algorithm for the finite element method modeling of individual malocclusions. Usually, a great deal of time is spent in preprocessing. To reduce the time required, we developed a standardized procedure for measuring the position of each tooth and a program to automatically preprocess. The following procedures were carried to complete this study. 1. Twenty-eight teeth morphologies were constructed three-dimensionally for the finite element analysis and saved as separate files. 2. Standard brackets were attached so that the FA points coincide with the center of the brackets. 3. The study model of a patient was made. 4. Using the study model, the crown inclination, angulation, and the vertical distance from the tip of a tooth was measured by using specially designed tools. 5. The arch form was determined from a picture of the model with an image processing technique. 6. The measured data were input as a rotational matrix. 7. The program provides an output file containing the necessary information about the three-dimensional position of teeth, which is applicable to several finite element programs commonly used. The program for a basic algorithm was made with Turbo-C and the subsequent outfile was applied to ANSYS. This standardized model measuring procedure and the program reduce the time required, especially for preprocessing and can be applied to other malocclusions easily.