• The Korean Journal of Community Living Science
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• v.22 no.1
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• pp.115-129
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• 2011

The purpose of this study was to examine the effect of parenting behavior and parent-child communication on elementary school children's multiple intelligence. 321 children selected from two elementary schools and their mothers participated in the study. Data were collected using the multiple intelligence index, parenting behavior inventory and parent-child communication index. The data were statistically analyzed using the t-test, one-way ANOVA(Duncan test), and multiple regression analysis. The study showed that there were some significant differences in children's multiple intelligence according to the children's gender, income, mother and father's educational background. There were some significant differences in children's multiple intelligence according to the parenting behavior, warmth acceptance and permissiveness nonintervention behaviors, and to the parent-child open communication and problematic communication. It was also found that children's gender, family income, warmth acceptance behavior, permissiveness nonintervention behavior, open communication and problematic communication were all significant predictors of the children's multiple intelligence. Implications based on this study are as follows; in order to increase the children' multiple intelligence, parents should be warmer and more accepting and have open communication with their children.

• Journal of Intelligence and Information Systems
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• v.17 no.1
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• pp.17-35
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• 2011

The collective intelligence is a common-based production by the collaboration and competition of many peer individuals. In other words, it is the aggregation of individual intelligence to lead the wisdom of crowd. Recently, the utilization of the collective intelligence has become one of the emerging research areas, since it has been adopted as an important principle of web 2.0 to aim openness, sharing and participation. This paper introduces an approach to seek the collective intelligence by cognition of the relation and interaction among individual participants. It describes a methodology well-suited to evaluate individual intelligence in information retrieval and classification as an application field. The research investigates how to derive and represent such cognitive intelligence from individuals through the application of fuzzy relational theory to personal construct theory and knowledge grid technique. Crucial to this research is to implement formally and process interpretatively the cognitive knowledge of participants who makes the mutual relation and social interaction. What is needed is a technique to analyze cognitive intelligence structure in the form of Hasse diagram, which is an instantiation of this perceptive intelligence of human beings. The search for the collective intelligence requires a theory of similarity to deal with underlying problems; clustering of social subgroups of individuals through identification of individual intelligence and commonality among intelligence and then elicitation of collective intelligence to aggregate the congruence or sharing of all the participants of the entire group. Unlike standard approaches to similarity based on statistical techniques, the method presented employs a theory of fuzzy relational products with the related computational procedures to cover issues of similarity and dissimilarity.

• Journal of Korean Society of Archives and Records Management
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• v.13 no.3
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• pp.99-125
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• 2013

This study proposes an education program using presidential archives to develop the multiple intelligence of children and the youth based on the multiple intelligence theory and the resource-based learning theory. To accomplish this, we performed a literature review and interviews with an archivist working in the Presidential Archive in Korea. This study compared and analyzed the Presidential Archives' education programs between the U.S. and Korea. This study can be useful and valuable in developing education programs in two areas, with the first area being the fact that the proposed program could help learners improve academic abilities by developing multiple intelligence and the second area being the fact that the program could increase the awareness of the importance of presidential archives. With the proposed program, the utilization of presidential archives can be facilitated.

• Journal of the Korea Society of Computer and Information
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• v.27 no.6
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• pp.33-42
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• 2022

In the existing intelligent command control system study, the analysis results of the commander's battlefield situation questions are provided from knowledge-based situation data. Analysis reporters write these results in various expressions of natural language. However, it is important to analyze situations about information and intelligence according to context. Analyzing the battlefield situation using artificial intelligence is necessary. We propose a virtual dataset generation method based on battlefield simulation scenarios in order to provide a dataset necessary for the battlefield situation analysis based on artificial intelligence. Dataset is generated after identifying battlefield knowledge elements in scenarios. When a candidate hypothesis is created, a unit hypothesis is automatically created. By combining unit hypotheses, similar identification hypothesis combinations are generated. An aggregation hypothesis is generated by grouping candidate hypotheses. Dataset generator SW implementation demonstrates that the proposed method can be generated the virtual battlefield situation dataset.

• Journal of Digital Convergence
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• v.15 no.6
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• pp.51-59
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• 2017

The role of government is to defend its lands and people from enemies. The range of that defense has now extended into the cyber domain, regarded as the fourth domain of the conventional defense domains (i.e., land, sea, sky, and universe). Traditionally, a government's intelligence power overrides that of its civilians, and government is exclusively responsible for defense. However, it is difficult for government to take the initiative to defend in the cyber domain because civilians already have a greater means for collecting information, which is known as being "intelligence inverse" in the cyber domain. To this end, we first define the intelligence inverse phenomenon and then analyze its main features. Then we investigate foreign countries' efforts to overcome the phenomenon and look at the current domestic situation. Based on these results, we describe the appropriate role of the National Intelligence Agency to handle cyber threats and offer a cyber threat intelligence model to share with civilians to help protect against these threats. Using the proposed model, we propose that the National Intelligence Agency should establish a base system that will respond to cyber threats more effectively.

• Communications of Mathematical Education
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• v.34 no.4
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• pp.545-561
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• 2020

The purpose of this study is to investigate the applications and possibilities of major programs that provide services using artificial intelligence in mathematics education. For this study, related papers, reports, and materials were collected and analyzed, focusing on materials mostly published within the last five years. The researcher searched the keywords of "artificial intelligence", "artificial intelligence", "AI" and "mathematics education" independently or in combination. As a result of the study, artificial intelligence for mathematics education was mostly supporting learners' personalized mathematics learning, defining it as an auxiliary role to support human mathematics teachers, and upgrading the technology of not only cognitive aspects but also affective aspects. As suggestions, the researcher argued that followings are necessary: Research for the establishment of an elaborate artificial intelligence mathematical system, discovery of artificial intelligence technology for appropriate use to support mathematics education, development of high quality of mathematics contents for artificial intelligence, and the establishment and operation of a cloud-based comprehensive system for mathematics education. The researcher proposed that continuous research to effectively help students study mathematics using artificial intelligence including students' emotional or empathetic abilities, and collaborative learning, which is only possible in offline environments. Also, the researcher suggested that more sophisticated materials should be developed for designing mathematics teaching and learning by using artificial intelligence.

• Informatization Policy
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• v.29 no.2
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• pp.3-36
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• 2022

Most research in artificial intelligence (AI) has focused on the development of new algorithms. But as artificial intelligence has been spreading over many applications and gaining more attention from managers in the organization, academia has begun to understand the necessity of developing new artificial intelligence theories related to AI management. We reviewed recent studies in the field from 2015, and further analysis has been done for 785 studies chosen based on citation numbers of over 20. The results show that most studies have still been in the prototyping application phase of artificial intelligence across different industries. We conclude our study by calling for more research in the application of artificial intelligence in terms of organizational structures and project and risk management.

• Journal of Information Processing Systems
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• v.15 no.6
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• pp.1365-1377
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• 2019

Summarizing the differences in Chinese-Vietnamese bilingual news plays an important supporting role in the comparative analysis of news views between China and Vietnam. Aiming at cross-language problems in the analysis of the differences between Chinese and Vietnamese bilingual news, we propose a new method of summarizing the differences based on an undirected graph model. The method extracts elements to represent the sentences, and builds a bridge between different languages based on Wikipedia's multilingual concept description page. Firstly, we calculate the similarity between Chinese and Vietnamese news sentences, and filter the bilingual sentences accordingly. Then we use the filtered sentences as nodes and the similarity grade as the weight of the edge to construct an undirected graph model. Finally, combining the random walk algorithm, the weight of the node is calculated according to the weight of the edge, and sentences with highest weight can be extracted as the difference summary. The experiment results show that our proposed approach achieved the highest score of 0.1837 on the annotated test set, which outperforms the state-of-the-art summarization models.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.4
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• pp.1989-2011
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• 2019

Vehicle detection based on aerial images is an interesting and challenging research topic. Most of the traditional vehicle detection methods are based on the sliding window search algorithm, but these methods are not sufficient for the extraction of object features, and accompanied with heavy computational costs. Recent studies have shown that convolutional neural network algorithm has made a significant progress in computer vision, especially Faster R-CNN. However, this algorithm mainly detects objects in natural scenes, it is not suitable for detecting small object in aerial view. In this paper, an accurate and effective vehicle detection algorithm based on Faster R-CNN is proposed. Our method fuse a hyperactive feature map network with Eltwise model and Concat model, which is more conducive to the extraction of small object features. Moreover, setting suitable anchor boxes based on the size of the object is used in our model, which also effectively improves the performance of the detection. We evaluate the detection performance of our method on the Munich dataset and our collected dataset, with improvements in accuracy and effectivity compared with other methods. Our model achieves 82.2% in recall rate and 90.2% accuracy rate on Munich dataset, which has increased by 2.5 and 1.3 percentage points respectively over the state-of-the-art methods.

• Journal of Information Technology Applications and Management
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• v.17 no.1
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• pp.127-139
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• 2010

Customer behavior pattern discovery is the fundament for conducting customer oriented services and the services management. But, the composition, need, interest and experience of customers may be continuously changing, thereof lead to the difficulty in refining a stable description of their consistent behavior pattern. This paper presented a new method for the behavior pattern discovery from a changing collection of customers. It was originally inspired from the swarm intelligence of ant colony. By the adaptive clustering, some typical behavior patterns which reflect the characteristics of related customer clusters can extracted dynamically and adaptively.