• Title/Summary/Keyword: hierarchical learning

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Implementation of an Agent-centric Planning of Complex Events as Objects of Pedagogical Experiences in Virtual World

  • Park, Jong Hee
    • International Journal of Contents
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    • v.12 no.1
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    • pp.25-43
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    • 2016
  • An agent-centric event planning method is proposed for providing pedagogical experiences in an immersed environment. Two-level planning is required at in a macro-level (i.e., inter-event level) and an intra-event level to provide realistic experiences with the objective of learning declarative knowledge. The inter-event (horizontal) planning is based on search, while intra-event (vertical) planning is based on hierarchical decomposition. The horizontal search is dictated by several realistic types of association between events besides the conventional causality. The resulting schematic plan is further augmented by conditions associated with those agents cast into the roles of the events identified in the plan. Rather than following a main story plot, all the events potentially relevant to accomplishing an initial goal are derived in the final result of our planning. These derived events may progress concurrently or digress toward a new main goal replacing the current goal or event, and the plan could be merged or fragmented according to their respective lead agents' intentions and other conditions. The macro-level coherence across interconnected events is established via their common background world existing a priori. As the pivotal source of event concurrency and intricacy, agents are modeled to not only be autonomous but also independent, i.e., entities with their own beliefs and goals (and subsequent plans) in their respective parts of the world. Additional problems our method addresses for augmenting pedagogical experiences include casting of agents into roles based on their availability, subcontracting of subsidiary events, and failure of multi-agent event entailing fragmentation of a plan. The described planning method was demonstrated by monitoring implementation.

Discovery Methods of Similar Web Service Operations by Learning Ontologies (온톨로지 학습에 의한 유사 웹 서비스 오퍼레이션 발견 방법)

  • Lee, Yong-Ju
    • The KIPS Transactions:PartD
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    • v.18D no.2
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    • pp.133-142
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    • 2011
  • To ensure the successful employment of semantic web services, it is essential that they rely on the use of high quality ontologies. However, building such ontologies is difficult and costly, thus hampering web service deployment. This study automatically builds ontologies from WSDL documents and their underlying semantics, and presents discovery methods of similar web service operations using these ontologies. The key ingredient is techniques that cluster parameters in the collection of web services into semantically meaningful concepts, and capture the hierarchical relationships between the words contained in the tag. We implement an operation retrieval system for web services. This system finds out a ranked set of similar operations using a novel similarity measurement method, and selects the most optimal operation which satisfies user's requirements. It can be directly used for the web services composition.

Anomalous Trajectory Detection in Surveillance Systems Using Pedestrian and Surrounding Information

  • Doan, Trung Nghia;Kim, Sunwoong;Vo, Le Cuong;Lee, Hyuk-Jae
    • IEIE Transactions on Smart Processing and Computing
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    • v.5 no.4
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    • pp.256-266
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    • 2016
  • Concurrently detected and annotated abnormal events can have a significant impact on surveillance systems. By considering the specific domain of pedestrian trajectories, this paper presents two main contributions. First, as introduced in much of the work on trajectory-based anomaly detection in the literature, only information about pedestrian paths, such as direction and speed, is considered. Differing from previous work, this paper proposes a framework that deals with additional types of trajectory-based anomalies. These abnormal events take places when a person enters prohibited areas. Those restricted regions are constructed by an online learning algorithm that uses surrounding information, including detected pedestrians and background scenes. Second, a simple data-boosting technique is introduced to overcome a lack of training data; such a problem particularly challenges all previous work, owing to the significantly low frequency of abnormal events. This technique only requires normal trajectories and fundamental information about scenes to increase the amount of training data for both normal and abnormal trajectories. With the increased amount of training data, the conventional abnormal trajectory classifier is able to achieve better prediction accuracy without falling into the over-fitting problem caused by complex learning models. Finally, the proposed framework (which annotates tracks that enter prohibited areas) and a conventional abnormal trajectory detector (using the data-boosting technique) are integrated to form a united detector. Such a detector deals with different types of anomalous trajectories in a hierarchical order. The experimental results show that all proposed detectors can effectively detect anomalous trajectories in the test phase.

Analysis on Knowledge State of Inquiry Abilities of Elementary School Students on Electric Circuits (초등학생의 전기회로 탐구능력에 대한 지식상태 분석)

  • Lee, Hyong-Jae;Park, Sang-Tae
    • Journal of The Korean Association For Science Education
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    • v.35 no.5
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    • pp.857-870
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    • 2015
  • Concerning elementary school science subject electric circuit units, which are regarded as difficult by teachers and students, this study aims to use the knowledge state analysis method along with interviews to analyze the knowledge state and hierarchy of inquiry abilities. Before and after applying the electric circuit inquiry abilities module, the question items aimed at assessing the basic inquiry abilities and integrative inquiry abilities for electric circuits were presented to students, and their knowledge state was analyzed along with interviews. Through analysis of the knowledge structure and hierarchy of inquiry abilities about electric circuits, the way of thinking of teachers who taught inquiry abilities, and the way of thinking of students were found to be visually different from each other, and this is an important factor that should not be neglected in the process of teaching and learning about inquiry abilities and should be considered. In addition, the presentation of the knowledge state of and hierarchical relations between inquiry abilities factors can offer implications for guidance on students' learning about inquiry abilities.

The Effect of College Life Experiences on Academic Achievement in Cambodia (캄보디아 대학생의 대학생활 경험이 학업성취에 미치는 영향 분석)

  • Svay, Souma;Chung, Jae Young;Jeong, Yehwa;Jang, Seon Hee
    • Korean Journal of Comparative Education
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    • v.28 no.3
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    • pp.309-331
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    • 2018
  • The purpose of this study was to examine the academic achievement and college life experience of students in Cambodia and to analyze the effects of college life experiences on academic achievement of college students in Cambodia. The questionnaire survey was conducted using the 'College Student Experiences Questionnaire (CSEQ)' questionnaire of 524 students from five universities in the city of Phnom Penh, Cambodia. The data were analyzed using hierarchical regression analysis. The results of this study showed that the experiences of college students 'Computer and Information Technology', 'Course Learning', 'Club and Organization' had positive effects on academic achievement. The implications of this study are as follows: First, colleges have to install more infrastructure for students to easily use computers and the Internet inside the school, and to provide programs to develop ICT skills to all students. Second, college-based efforts are needed to improve the quality of lectures for providing the students' knowledge and skills. Third, students' club and organization participation should be set up in college to find ways to improve students' academic achievement.

Mediating Effect of Grit between Academic achievement satisfaction of Middle School Students and Academic Engagement (중학생의 학업성취만족도와 학업열의 사이에서 그릿의 매개효과)

  • Kwon, Eun-Kyeong
    • Journal of Digital Convergence
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    • v.19 no.12
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    • pp.225-230
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    • 2021
  • The purpose of this study is to understand the mediating effect of grit in the relationship between academic achievement satisfaction and Academic Engagement of middle school students. To this end, a survey was conducted on 575 middle school students in Changwon, Gyeongsangnam-do, on academic achievement satisfaction, Academic Engagement, and grit. This research was carried out by hierarchical regression analysis was conducted to understand the correlation analysis and mediating effect between major variables, and The significance of the mediating effect was verified by the Sobel test. As a result of the study, First, correlation analysis revealed a positive correlation between academic achievement satisfaction, grit, and Academic Engagement. Second, regression analysis showed that both consistency of interest and perseverance of effort were partially mediated between academic achievement satisfaction and Academic Engagement. This means that academic achievement satisfaction not only directly affects middle school students' Academic Engagement, but also has an indirect effect through grit. Finally, In order to increase the academic enthusiasm of middle school students, learning counseling plans such as education and counseling plans to improve academic interest and develop various learning motivation improvement programs were discussed.

Association Rules Analysis of Safe Accidents Caused by Falling Objects (낙하물에 기인한 안전사고의 연관규칙 분석)

  • Son, Ki-Young;Ryu, Han-Guk
    • Journal of the Korea Institute of Building Construction
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    • v.19 no.4
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    • pp.341-350
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    • 2019
  • Construction industry is one of the most dangerous industry. As the construction accidents occur due to the repeated factors found in each accidents, there is a limitation in analyzing all types of occupational accidents by the existing descriptive analysis and statistical test. In this study, we classified safety accidents caused by falling objects among the accident types occurring at construction sites into fatal and nonfatal accidents and deduced the factors. In addition, we deduced the association rules among the safety accidents factors caused by falling objects through the association rule analysis method among the machine learning techniques. Therefore, considering the association rules for fatal and nonfatal accidents proposed in this study, it would be possible to prevent accidents by searching for countermeasures against safety accidents caused by falling objects.

Stock prediction analysis through artificial intelligence using big data (빅데이터를 활용한 인공지능 주식 예측 분석)

  • Choi, Hun
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.25 no.10
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    • pp.1435-1440
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    • 2021
  • With the advent of the low interest rate era, many investors are flocking to the stock market. In the past stock market, people invested in stocks labor-intensively through company analysis and their own investment techniques. However, in recent years, stock investment using artificial intelligence and data has been widely used. The success rate of stock prediction through artificial intelligence is currently not high, so various artificial intelligence models are trying to increase the stock prediction rate. In this study, we will look at various artificial intelligence models and examine the pros and cons and prediction rates between each model. This study investigated as stock prediction programs using artificial intelligence artificial neural network (ANN), deep learning or hierarchical learning (DNN), k-nearest neighbor algorithm(k-NN), convolutional neural network (CNN), recurrent neural network (RNN), and LSTMs.

Analysis of Differences in Satisfaction with College Life of Freshmen According to on Smartphone Overdependence (스마트폰 과의존에 따른 신입생의 대학생활 만족도 차이 분석)

  • Park, Hye-Young;Lee, KyungHee
    • Journal of Convergence for Information Technology
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    • v.11 no.2
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    • pp.130-137
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    • 2021
  • The purpose of this study is to explore methods to prevent and improve the problem of overdependence on smartphones by analyzing the differences in satisfaction with college life satisfaction of freshmen. For this, data on freshmen of KCYPS were extracted and used. The data were analyzed using non-hierarchical cluster(K-means) analysis, T-test, one-way ANOVA, and Scheffé tests. The results of this study are as follows. First, it has been shown that freshmen who are overdependent on smartphones experience inconvenience in their daily life, withdrawal and anxiety, and resistance. Second, there is no significant difference in the level of satisfaction with college life according to gender(t=-.015, p<.05). Third, it is shown that the level of satisfaction with college life of overdependent freshmen on smartphone is significantly lower compared to that of average and moderate dependent freshmen. Based on the results, it was suggested that university-level efforts such as emotional support and learning strategy support are needed for freshmen who are overdependent on smartphones.

A Study on the Improvement of Accuracy of Cardiomegaly Classification Based on InceptionV3 (InceptionV3 기반의 심장비대증 분류 정확도 향상 연구)

  • Jeong, Woo Yeon;Kim, Jung Hun
    • Journal of Biomedical Engineering Research
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    • v.43 no.1
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    • pp.45-51
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    • 2022
  • The purpose of this study is to improve the classification accuracy compared to the existing InceptionV3 model by proposing a new model modified with the fully connected hierarchical structure of InceptionV3, which showed excellent performance in medical image classification. The data used for model training were trained after data augmentation on a total of 1026 chest X-ray images of patients diagnosed with normal heart and Cardiomegaly at Kyungpook National University Hospital. As a result of the experiment, the learning classification accuracy and loss of the InceptionV3 model were 99.57% and 1.42, and the accuracy and loss of the proposed model were 99.81% and 0.92. As a result of the classification performance evaluation for precision, recall, and F1 score of Inception V3, the precision of the normal heart was 78%, the recall rate was 100%, and the F1 score was 88. The classification accuracy for Cardiomegaly was 100%, the recall rate was 78%, and the F1 score was 88. On the other hand, in the case of the proposed model, the accuracy for a normal heart was 100%, the recall rate was 92%, and the F1 score was 96. The classification accuracy for Cardiomegaly was 95%, the recall rate was 100%, and the F1 score was 97. If the chest X-ray image for normal heart and Cardiomegaly can be classified using the model proposed based on the study results, better classification will be possible and the reliability of classification performance will gradually increase.