• Journal of Information Processing Systems
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• v.18 no.5
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• pp.628-636
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• 2022

Automatic program repair (APR) techniques focus on automatically repairing bugs in programs and providing correct patches for developers, which have been investigated for decades. However, most studies have limitations in repairing complex bugs. To overcome these limitations, we developed an approach that augments datasets by utilizing token tagging and applying machine learning techniques for APR. First, to alleviate the data insufficiency problem, we augmented datasets by extracting all the methods (buggy and non-buggy methods) in the program source code and conducting token tagging on non-buggy methods. Second, we fed the preprocessed code into the model as an input for training. Finally, we evaluated the performance of the proposed approach by comparing it with the baselines. The results show that the proposed approach is efficient for augmenting datasets using token tagging and is promising for APR.

• The Journal of the Korea institute of electronic communication sciences
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• v.12 no.1
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• pp.163-172
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• 2017

This study is a system that provides a suitable level of the problem, designing the learner certification simulation program based on the ITS(: Intelligent Tutoring System) based on the model and the learning expert model, the model through a buggy (Buggy Model). In the demand survey that reflects the needs of users, convenience, effectiveness, scalability, and reliability were required. In order to reflect this, various problems were developed, problem type analysis, difficulty control, student grades and level management. Users who are preparing for the certification test are expected to use the development system to solve the problems according to their own level and to solve various types of problems in a practical environment to greatly shorten the preparation period for certification.

• The Korean Journal of Emergency Medical Services
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• v.25 no.2
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• pp.99-112
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• 2021

Purpose: The study aimed to analyze the current status of traffic accident victims who were transported by 119 ambulances within the administrative district of Chungnam province and provide essential data for accident prevention. Methods: The pre-hospital care records of patients who called the 119 emergency service in 2019 were obtained from the Chungnam Fire Department. Data pertaining to 13,663 traffic accident victims who were transported to hospitals were analyzed. Results: Patients in those aged ≥60 years accounted for 49.8% of the total cases. In patients aged ≥80 years(n=2,154), motor cycle accidents were highest as 28.3%. In addition, cultivator (n=135) and buggy car (n=79) accident victims were the highest in aged ≥80 years as 66.7% and 67.1%, respectively. Traffic accident victims-population ratio in Chungnam was 0.65%, wherein 2.03% included population aged ≥80 years. Conclusion: It was clear that accidents varied across administrative districts depending on the age group of population distribution. Thus, safety measures for preventing motorcycle, cultivator, and buggy car accidents are necessary for areas with many older people aged ≥80 years.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.31B no.7
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• pp.159-169
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• 1994

In this paper, we develop a prototype of ITS(Intelligent Tutoring Systems) system: UNIX TUTOR. It is designed for the purpose of teaching the UNIX beginners the principal concepts of UNIX and the shell commands using the communication between the student and the system. UNIX TUTOR engages the student in a two-way conversation that is mixed-initiative dialogue and attempts to teach the student UNIX via the Socratic method of guided discovery and the Coaching method interchangeably. And the student model is based on both the overlay model and the buggy model together. Thus TUTOR aims at teaching the students effectively whose levels of learning are different using various explanations which are determined by the student model. Because the knowledge representation for UNIX-TUTOR is based on the frame structure and the production rules it is easy to represent the complicated constructs. UNIX TUTOR is implemented on the SPARC station using X/Motif and C for cp command among 10 ones which were selected.

• The KIPS Transactions:PartA
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• v.19A no.3
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• pp.147-154
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• 2012

The higher thinking skills, such as creativity and problem-solving about a given problem, are difficult to assess and diagnose. For an accurate diagnosis of these higher thinking abilities, we need to fully observe learner's problem-solving process or learner's individual reports. However, in an online learning or virtual class environments, evaluation of learner's problem-solving process becomes more difficult to diagnose. The best way to solve this problem is through reporting by tracking learner's actions when he tries to solve a problem. In this study, we developed a module which can evaluate and diagnose student's problem-solving ability by tracking actions in MS-Office suite, which is used by students to solve a given problem. This module performs based on the learner's job history through user tracking. To evaluate the effectiveness of this diagnostic module, we conducted satisfaction survey from students who were preparing the actual MOS exams. As a result, eighty-one (81) of the participants were positive on the effectiveness of the learning system with the use of this module.