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한국정보처리학회> JIPS(Journal of Information Processing Systems)> Implementation of Quality Management System for Wild-Simulated Ginseng Using Blockchain

KCI등재SCOUPUS

Implementation of Quality Management System for Wild-Simulated Ginseng Using Blockchain

Youngjun Sung , Yoojae Won
  • : 한국정보처리학회
  • : JIPS(Journal of Information Processing Systems) 18권2호
  • : 연속간행물
  • : 2022년 04월
  • : 173-187(15pages)
JIPS(Journal of Information Processing Systems)

DOI


목차

1. Introduction
2. Related Work
3. Proposed Quality Management System
4. Implementation and Experiments
5. Conclusion
Acknowledgement
References

키워드 보기


초록 보기

A special government agency has been charged with implementing quality management to guarantee the quality of wild-simulated ginseng. However, these processes are carried out by use of documents, and this has resulted in information omission and high document management costs. To solve this problem, this study analyzed the existing quality management process by using a smart contract for the existing offline form and proposed a new quality management system for storing and managing all log data in the blockchain. This system reduced documentation management costs about quality management and recorded information in the previous step through the quality management steps, thus forming a step-by-step record chain. Experiments were conducted by implementing this system, which improved data integrity and reliability. Additionally, sensitive information, such as personal information, was included in the system by use of the off-chain technology.

UCI(KEPA)

간행물정보

  • : 공학분야  > 전자공학
  • : KCI등재
  • : SCOPUS
  • : 격월
  • : 1976-913x
  • : 2092-805X
  • : 학술지
  • : 연속간행물
  • : 2005-2022
  • : 989


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KCI등재 SCOPUS

1Implementation of Quality Management System for Wild-Simulated Ginseng Using Blockchain

저자 : Youngjun Sung , Yoojae Won

발행기관 : 한국정보처리학회 간행물 : JIPS(Journal of Information Processing Systems) 18권 2호 발행 연도 : 2022 페이지 : pp. 173-187 (15 pages)

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초록보기

A special government agency has been charged with implementing quality management to guarantee the quality of wild-simulated ginseng. However, these processes are carried out by use of documents, and this has resulted in information omission and high document management costs. To solve this problem, this study analyzed the existing quality management process by using a smart contract for the existing offline form and proposed a new quality management system for storing and managing all log data in the blockchain. This system reduced documentation management costs about quality management and recorded information in the previous step through the quality management steps, thus forming a step-by-step record chain. Experiments were conducted by implementing this system, which improved data integrity and reliability. Additionally, sensitive information, such as personal information, was included in the system by use of the off-chain technology.

KCI등재 SCOPUS

2Path-Based Computation Encoder for Neural Architecture Search

저자 : Ying Yang , Xu Zhang , Hu Pan

발행기관 : 한국정보처리학회 간행물 : JIPS(Journal of Information Processing Systems) 18권 2호 발행 연도 : 2022 페이지 : pp. 188-196 (9 pages)

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Recently, neural architecture search (NAS) has received increasing attention as it can replace human experts in designing the architecture of neural networks for different tasks and has achieved remarkable results in many challenging tasks. In this study, a path-based computation neural architecture encoder (PCE) was proposed. Our PCE first encodes the computation of information on each path in a neural network, and then aggregates the encodings on all paths together through an attention mechanism, simulating the process of information computation along paths in a neural network and encoding the computation on the neural network instead of the structure of the graph, which is more consistent with the computational properties of neural networks. We performed an extensive comparison with eight encoding methods on two commonly used NAS search spaces (NAS-Bench-101 and NAS-Bench-201), which included a comparison of the predictive capabilities of performance predictors and search capabilities based on two search strategies (reinforcement learning-based and Bayesian optimization-based) when equipped with different encoders. Experimental evaluation shows that PCE is an efficient encoding method that effectively ranks and predicts neural architecture performance, thereby improving the search efficiency of neural architectures.

KCI등재 SCOPUS

3A Manually Captured and Modified Phone Screen Image Dataset for Widget Classification on CNNs

저자 : Sungchul Byun , Seong-soo Han , Chang-sung Jeong

발행기관 : 한국정보처리학회 간행물 : JIPS(Journal of Information Processing Systems) 18권 2호 발행 연도 : 2022 페이지 : pp. 197-207 (11 pages)

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The applications and user interfaces (UIs) of smart mobile devices are constantly diversifying. For example, deep learning can be an innovative solution to classify widgets in screen images for increasing convenience. To this end, the present research leverages captured images and the ReDraw dataset to write deep learning datasets for image classification purposes. First, as the validation for datasets using ResNet50 and EfficientNet, the experiments show that the dataset composed in this study is helpful for classification according to a widget's functionality. An implementation for widget detection and classification on RetinaNet and EfficientNet is then executed. Finally, the research suggests the Widg-C and Widg-D datasets―a deep learning dataset for identifying the widgets of smart devices―and implementing them for use with representative convolutional neural network models.

KCI등재 SCOPUS

4Models and Methods for the Evaluation of Automobile Manufacturing Supply Chain Coordination Degree Based on Collaborative Entropy

저자 : Qiang Xiao , Hongshuang Wang

발행기관 : 한국정보처리학회 간행물 : JIPS(Journal of Information Processing Systems) 18권 2호 발행 연도 : 2022 페이지 : pp. 208-222 (15 pages)

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초록보기

Through the analysis of the coordination mechanism of the supply chain system of China's automobile manufacturing industry, the factors affecting the supply subsystem, the manufacturing subsystem, the sales subsystem, and the consumption subsystem are sorted out, the supply chain coordination index system based on the influence factor of four subsystems is established. The evaluation models of the coordination degree in the subsystem of the supply chain, the coordination degree among the subsystems, and the comprehensive coordination degree are established by using the efficiency coefficient method and the collaborative entropy method. Experimental results verify the accuracy of the evaluation model using the empirical analysis of the collaborative evaluation index data of China's automobile manufacturing industry from 2000 to 2019. The supply chain synergy of automobile manufacturing industry was low from 2001 to 2005, and it increased to a certain extent from 2006 to 2008 with a small growth rate from 0.10 to 0.15. From 2009 to 2013, the supply chain synergy of automobile manufacturing industry increased rapidly from 0.24 to 0.49, and it also increased rapidly but fluctuated from 2014 to 2019, first rising from 0.68 to 0.84 then dropping to 0.71. These results provide reference for the development of China's automobile manufacturing supply chain system and scientific decision-making basis for the formulation of relevant policies of the automobile manufacturing industry.

KCI등재 SCOPUS

5Automated Print Quality Assessment Method for 3D Printing AI Data Construction

저자 : Hyun-ju Yoo , Nammee Moon

발행기관 : 한국정보처리학회 간행물 : JIPS(Journal of Information Processing Systems) 18권 2호 발행 연도 : 2022 페이지 : pp. 223-234 (12 pages)

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The evaluation of the print quality of 3D printing has traditionally relied on manual work using dimensional measurements. However, the dimensional measurement method has an error value that depends on the person who measures it. Therefore, we propose the design of a new print quality measurement method that can be automatically measured using the field-of-view (FOV) model and the intersection over union (IoU) technique. First, the height information of the modeling is acquired from a camera; the output is measured by a sensor; and the images of the top and isometric views are acquired from the FOV model. The height information calculates the height ratio by calculating the percentage of modeling and output, and compares the 2D contour of the object on the image using the FOV model. The contour of the object is obtained from the image for 2D contour comparison and the IoU is calculated by comparing the areas of the contour regions. The accuracy of the automated measurement technique for determining, which derives the print quality value was calculated by averaging the IoU value corrected by the measurement error and the height ratio value.

KCI등재 SCOPUS

6A Fast Inter-prediction Mode Decision Algorithm for HEVC Based on Spatial-Temporal Correlation

저자 : Weixin Yao , Dan Yang

발행기관 : 한국정보처리학회 간행물 : JIPS(Journal of Information Processing Systems) 18권 2호 발행 연도 : 2022 페이지 : pp. 235-244 (10 pages)

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초록보기

Many new techniques have been adopted in HEVC (High efficiency video coding) standard, such as quadtree-structured coding unit (CU), prediction unit (PU) partition, 35 intra-mode, and so on. To reduce computational complexity, the paper proposes two optimization algorithms which include fast CU depth range decision and fast PU partition mode decision. Firstly, depth range of CU is predicted according to spatial-temporal correlation. Secondly, we utilize the depth difference between the current CU and CU corresponding to the same position of adjacent frame for PU mode range selection. The number of traversal candidate modes is reduced. The experiment result shows the proposed algorithm obtains a lot of time reducing, and the loss of coding efficiency is inappreciable.

KCI등재 SCOPUS

7A Deep Learning Approach for Identifying User Interest from Targeted Advertising

저자 : Wonkyung Kim , Kukheon Lee , Sangjin Lee , Doowon Jeong

발행기관 : 한국정보처리학회 간행물 : JIPS(Journal of Information Processing Systems) 18권 2호 발행 연도 : 2022 페이지 : pp. 245-257 (13 pages)

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In the Internet of Things (IoT) era, the types of devices used by one user are becoming more diverse and the number of devices is also increasing. However, a forensic investigator is restricted to exploit or collect all the user's devices; there are legal issues (e.g., privacy, jurisdiction) and technical issues (e.g., computing resources, the increase in storage capacity). Therefore, in the digital forensics field, it has been a challenge to acquire information that remains on the devices that could not be collected, by analyzing the seized devices. In this study, we focus on the fact that multiple devices share data through account synchronization of the online platform. We propose a novel way of identifying the user's interest through analyzing the remnants of targeted advertising which is provided based on the visited websites or search terms of logged-in users. We introduce a detailed methodology to pick out the targeted advertising from cache data and infer the user's interest using deep learning. In this process, an improved learning model considering the unique characteristics of advertisement is implemented. The experimental result demonstrates that the proposed method can effectively identify the user interest even though only one device is examined.

KCI등재 SCOPUS

8Implementation of Image Transmission Based on Vehicle-to-Vehicle Communication

저자 : Changhao Piao , Xiaoyue Ding , Jia He , Soohyun Jang , Mingjie Liu

발행기관 : 한국정보처리학회 간행물 : JIPS(Journal of Information Processing Systems) 18권 2호 발행 연도 : 2022 페이지 : pp. 258-267 (10 pages)

다운로드

(기관인증 필요)

초록보기

Weak over-the-horizon perception and blind spot are the main problems in intelligent connected vehicles (ICVs). In this paper, a V2V image transmission-based road condition warning method is proposed to solve them. The encoded road emergency images which are collected by the ICV are transmitted to the on-board unit (OBU) through Ethernet. The OBU broadcasts the fragmented image information including location and clock of the vehicle to other OBUs. To satisfy the channel quality of the V2X communication in different times, the optimal fragment length is selected by the OBU to process the image information. Then, according to the position and clock information of the remote vehicles, OBU of the receiver selects valid messages to decode the image information which will help the receiver to extend the perceptual field. The experimental results show that our method has an average packet loss rate of 0.5%. The transmission delay is about 51.59 ms in low-speed driving scenarios, which can provide drivers with timely and reliable warnings of the road conditions.

KCI등재 SCOPUS

9An Approach to Applying Multiple Linear Regression Models by Interlacing Data in Classifying Similar Software

저자 : Hyun-il Lim

발행기관 : 한국정보처리학회 간행물 : JIPS(Journal of Information Processing Systems) 18권 2호 발행 연도 : 2022 페이지 : pp. 268-281 (14 pages)

다운로드

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초록보기

The development of information technology is bringing many changes to everyday life, and machine learning can be used as a technique to solve a wide range of real-world problems. Analysis and utilization of data are essential processes in applying machine learning to real-world problems. As a method of processing data in machine learning, we propose an approach based on applying multiple linear regression models by interlacing data to the task of classifying similar software. Linear regression is widely used in estimation problems to model the relationship between input and output data. In our approach, multiple linear regression models are generated by training on interlaced feature data. A combination of these multiple models is then used as the prediction model for classifying similar software. Experiments are performed to evaluate the proposed approach as compared to conventional linear regression, and the experimental results show that the proposed method classifies similar software more accurately than the conventional model. We anticipate the proposed approach to be applied to various kinds of classification problems to improve the accuracy of conventional linear regression.

KCI등재 SCOPUS

10A BERT-Based Automatic Scoring Model of Korean Language Learners' Essay

저자 : Jung Hee Lee , Ji Su Park , Jin Gon Shon

발행기관 : 한국정보처리학회 간행물 : JIPS(Journal of Information Processing Systems) 18권 2호 발행 연도 : 2022 페이지 : pp. 282-291 (10 pages)

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This research applies a pre-trained bidirectional encoder representations from transformers (BERT) handwriting recognition model to predict foreign Korean-language learners' writing scores. A corpus of 586 answers to midterm and final exams written by foreign learners at the Intermediate 1 level was acquired and used for pre-training, resulting in consistent performance, even with small datasets. The test data were pre-processed and fine-tuned, and the results were calculated in the form of a score prediction. The difference between the prediction and actual score was then calculated. An accuracy of 95.8% was demonstrated, indicating that the prediction results were strong overall; hence, the tool is suitable for the automatic scoring of Korean written test answers, including grammatical errors, written by foreigners. These results are particularly meaningful in that the data included written language text produced by foreign learners, not native speakers.

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KCI등재SCOUPUS

1Implementation of Quality Management System for Wild-Simulated Ginseng Using Blockchain

저자 : Youngjun Sung , Yoojae Won

발행기관 : 한국정보처리학회 간행물 : JIPS(Journal of Information Processing Systems) 18권 2호 발행 연도 : 2022 페이지 : pp. 173-187 (15 pages)

다운로드

(기관인증 필요)

초록보기

A special government agency has been charged with implementing quality management to guarantee the quality of wild-simulated ginseng. However, these processes are carried out by use of documents, and this has resulted in information omission and high document management costs. To solve this problem, this study analyzed the existing quality management process by using a smart contract for the existing offline form and proposed a new quality management system for storing and managing all log data in the blockchain. This system reduced documentation management costs about quality management and recorded information in the previous step through the quality management steps, thus forming a step-by-step record chain. Experiments were conducted by implementing this system, which improved data integrity and reliability. Additionally, sensitive information, such as personal information, was included in the system by use of the off-chain technology.

KCI등재SCOUPUS

2Path-Based Computation Encoder for Neural Architecture Search

저자 : Ying Yang , Xu Zhang , Hu Pan

발행기관 : 한국정보처리학회 간행물 : JIPS(Journal of Information Processing Systems) 18권 2호 발행 연도 : 2022 페이지 : pp. 188-196 (9 pages)

다운로드

(기관인증 필요)

초록보기

Recently, neural architecture search (NAS) has received increasing attention as it can replace human experts in designing the architecture of neural networks for different tasks and has achieved remarkable results in many challenging tasks. In this study, a path-based computation neural architecture encoder (PCE) was proposed. Our PCE first encodes the computation of information on each path in a neural network, and then aggregates the encodings on all paths together through an attention mechanism, simulating the process of information computation along paths in a neural network and encoding the computation on the neural network instead of the structure of the graph, which is more consistent with the computational properties of neural networks. We performed an extensive comparison with eight encoding methods on two commonly used NAS search spaces (NAS-Bench-101 and NAS-Bench-201), which included a comparison of the predictive capabilities of performance predictors and search capabilities based on two search strategies (reinforcement learning-based and Bayesian optimization-based) when equipped with different encoders. Experimental evaluation shows that PCE is an efficient encoding method that effectively ranks and predicts neural architecture performance, thereby improving the search efficiency of neural architectures.

KCI등재SCOUPUS

3A Manually Captured and Modified Phone Screen Image Dataset for Widget Classification on CNNs

저자 : Sungchul Byun , Seong-soo Han , Chang-sung Jeong

발행기관 : 한국정보처리학회 간행물 : JIPS(Journal of Information Processing Systems) 18권 2호 발행 연도 : 2022 페이지 : pp. 197-207 (11 pages)

다운로드

(기관인증 필요)

초록보기

The applications and user interfaces (UIs) of smart mobile devices are constantly diversifying. For example, deep learning can be an innovative solution to classify widgets in screen images for increasing convenience. To this end, the present research leverages captured images and the ReDraw dataset to write deep learning datasets for image classification purposes. First, as the validation for datasets using ResNet50 and EfficientNet, the experiments show that the dataset composed in this study is helpful for classification according to a widget's functionality. An implementation for widget detection and classification on RetinaNet and EfficientNet is then executed. Finally, the research suggests the Widg-C and Widg-D datasets―a deep learning dataset for identifying the widgets of smart devices―and implementing them for use with representative convolutional neural network models.

KCI등재SCOUPUS

4Models and Methods for the Evaluation of Automobile Manufacturing Supply Chain Coordination Degree Based on Collaborative Entropy

저자 : Qiang Xiao , Hongshuang Wang

발행기관 : 한국정보처리학회 간행물 : JIPS(Journal of Information Processing Systems) 18권 2호 발행 연도 : 2022 페이지 : pp. 208-222 (15 pages)

다운로드

(기관인증 필요)

초록보기

Through the analysis of the coordination mechanism of the supply chain system of China's automobile manufacturing industry, the factors affecting the supply subsystem, the manufacturing subsystem, the sales subsystem, and the consumption subsystem are sorted out, the supply chain coordination index system based on the influence factor of four subsystems is established. The evaluation models of the coordination degree in the subsystem of the supply chain, the coordination degree among the subsystems, and the comprehensive coordination degree are established by using the efficiency coefficient method and the collaborative entropy method. Experimental results verify the accuracy of the evaluation model using the empirical analysis of the collaborative evaluation index data of China's automobile manufacturing industry from 2000 to 2019. The supply chain synergy of automobile manufacturing industry was low from 2001 to 2005, and it increased to a certain extent from 2006 to 2008 with a small growth rate from 0.10 to 0.15. From 2009 to 2013, the supply chain synergy of automobile manufacturing industry increased rapidly from 0.24 to 0.49, and it also increased rapidly but fluctuated from 2014 to 2019, first rising from 0.68 to 0.84 then dropping to 0.71. These results provide reference for the development of China's automobile manufacturing supply chain system and scientific decision-making basis for the formulation of relevant policies of the automobile manufacturing industry.

KCI등재SCOUPUS

5Automated Print Quality Assessment Method for 3D Printing AI Data Construction

저자 : Hyun-ju Yoo , Nammee Moon

발행기관 : 한국정보처리학회 간행물 : JIPS(Journal of Information Processing Systems) 18권 2호 발행 연도 : 2022 페이지 : pp. 223-234 (12 pages)

다운로드

(기관인증 필요)

초록보기

The evaluation of the print quality of 3D printing has traditionally relied on manual work using dimensional measurements. However, the dimensional measurement method has an error value that depends on the person who measures it. Therefore, we propose the design of a new print quality measurement method that can be automatically measured using the field-of-view (FOV) model and the intersection over union (IoU) technique. First, the height information of the modeling is acquired from a camera; the output is measured by a sensor; and the images of the top and isometric views are acquired from the FOV model. The height information calculates the height ratio by calculating the percentage of modeling and output, and compares the 2D contour of the object on the image using the FOV model. The contour of the object is obtained from the image for 2D contour comparison and the IoU is calculated by comparing the areas of the contour regions. The accuracy of the automated measurement technique for determining, which derives the print quality value was calculated by averaging the IoU value corrected by the measurement error and the height ratio value.

KCI등재SCOUPUS

6A Fast Inter-prediction Mode Decision Algorithm for HEVC Based on Spatial-Temporal Correlation

저자 : Weixin Yao , Dan Yang

발행기관 : 한국정보처리학회 간행물 : JIPS(Journal of Information Processing Systems) 18권 2호 발행 연도 : 2022 페이지 : pp. 235-244 (10 pages)

다운로드

(기관인증 필요)

초록보기

Many new techniques have been adopted in HEVC (High efficiency video coding) standard, such as quadtree-structured coding unit (CU), prediction unit (PU) partition, 35 intra-mode, and so on. To reduce computational complexity, the paper proposes two optimization algorithms which include fast CU depth range decision and fast PU partition mode decision. Firstly, depth range of CU is predicted according to spatial-temporal correlation. Secondly, we utilize the depth difference between the current CU and CU corresponding to the same position of adjacent frame for PU mode range selection. The number of traversal candidate modes is reduced. The experiment result shows the proposed algorithm obtains a lot of time reducing, and the loss of coding efficiency is inappreciable.

KCI등재SCOUPUS

7A Deep Learning Approach for Identifying User Interest from Targeted Advertising

저자 : Wonkyung Kim , Kukheon Lee , Sangjin Lee , Doowon Jeong

발행기관 : 한국정보처리학회 간행물 : JIPS(Journal of Information Processing Systems) 18권 2호 발행 연도 : 2022 페이지 : pp. 245-257 (13 pages)

다운로드

(기관인증 필요)

초록보기

In the Internet of Things (IoT) era, the types of devices used by one user are becoming more diverse and the number of devices is also increasing. However, a forensic investigator is restricted to exploit or collect all the user's devices; there are legal issues (e.g., privacy, jurisdiction) and technical issues (e.g., computing resources, the increase in storage capacity). Therefore, in the digital forensics field, it has been a challenge to acquire information that remains on the devices that could not be collected, by analyzing the seized devices. In this study, we focus on the fact that multiple devices share data through account synchronization of the online platform. We propose a novel way of identifying the user's interest through analyzing the remnants of targeted advertising which is provided based on the visited websites or search terms of logged-in users. We introduce a detailed methodology to pick out the targeted advertising from cache data and infer the user's interest using deep learning. In this process, an improved learning model considering the unique characteristics of advertisement is implemented. The experimental result demonstrates that the proposed method can effectively identify the user interest even though only one device is examined.

KCI등재SCOUPUS

8Implementation of Image Transmission Based on Vehicle-to-Vehicle Communication

저자 : Changhao Piao , Xiaoyue Ding , Jia He , Soohyun Jang , Mingjie Liu

발행기관 : 한국정보처리학회 간행물 : JIPS(Journal of Information Processing Systems) 18권 2호 발행 연도 : 2022 페이지 : pp. 258-267 (10 pages)

다운로드

(기관인증 필요)

초록보기

Weak over-the-horizon perception and blind spot are the main problems in intelligent connected vehicles (ICVs). In this paper, a V2V image transmission-based road condition warning method is proposed to solve them. The encoded road emergency images which are collected by the ICV are transmitted to the on-board unit (OBU) through Ethernet. The OBU broadcasts the fragmented image information including location and clock of the vehicle to other OBUs. To satisfy the channel quality of the V2X communication in different times, the optimal fragment length is selected by the OBU to process the image information. Then, according to the position and clock information of the remote vehicles, OBU of the receiver selects valid messages to decode the image information which will help the receiver to extend the perceptual field. The experimental results show that our method has an average packet loss rate of 0.5%. The transmission delay is about 51.59 ms in low-speed driving scenarios, which can provide drivers with timely and reliable warnings of the road conditions.

KCI등재SCOUPUS

9An Approach to Applying Multiple Linear Regression Models by Interlacing Data in Classifying Similar Software

저자 : Hyun-il Lim

발행기관 : 한국정보처리학회 간행물 : JIPS(Journal of Information Processing Systems) 18권 2호 발행 연도 : 2022 페이지 : pp. 268-281 (14 pages)

다운로드

(기관인증 필요)

초록보기

The development of information technology is bringing many changes to everyday life, and machine learning can be used as a technique to solve a wide range of real-world problems. Analysis and utilization of data are essential processes in applying machine learning to real-world problems. As a method of processing data in machine learning, we propose an approach based on applying multiple linear regression models by interlacing data to the task of classifying similar software. Linear regression is widely used in estimation problems to model the relationship between input and output data. In our approach, multiple linear regression models are generated by training on interlaced feature data. A combination of these multiple models is then used as the prediction model for classifying similar software. Experiments are performed to evaluate the proposed approach as compared to conventional linear regression, and the experimental results show that the proposed method classifies similar software more accurately than the conventional model. We anticipate the proposed approach to be applied to various kinds of classification problems to improve the accuracy of conventional linear regression.

KCI등재SCOUPUS

10A BERT-Based Automatic Scoring Model of Korean Language Learners' Essay

저자 : Jung Hee Lee , Ji Su Park , Jin Gon Shon

발행기관 : 한국정보처리학회 간행물 : JIPS(Journal of Information Processing Systems) 18권 2호 발행 연도 : 2022 페이지 : pp. 282-291 (10 pages)

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This research applies a pre-trained bidirectional encoder representations from transformers (BERT) handwriting recognition model to predict foreign Korean-language learners' writing scores. A corpus of 586 answers to midterm and final exams written by foreign learners at the Intermediate 1 level was acquired and used for pre-training, resulting in consistent performance, even with small datasets. The test data were pre-processed and fine-tuned, and the results were calculated in the form of a score prediction. The difference between the prediction and actual score was then calculated. An accuracy of 95.8% was demonstrated, indicating that the prediction results were strong overall; hence, the tool is suitable for the automatic scoring of Korean written test answers, including grammatical errors, written by foreigners. These results are particularly meaningful in that the data included written language text produced by foreign learners, not native speakers.

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자료제공: 네이버학술정보
발행기관 최신논문
자료제공: 네이버학술정보

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