• Journal of KIISE:Computing Practices and Letters
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• v.15 no.12
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• pp.983-987
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• 2009

One of the critical themes in the language acquisition is its exposure to linguistic environments. Linguistic environments, which interact with infants, include not only human beings such as its parents but also artificially crafted linguistic media as their functioning elements. An infant learns a language by exploring these extensive language environments around it. Based on such large linguistic data exposure, we propose a machine learning based method on the cognitive mechanism that simulate flexibly and appropriately infant's language learning. The infant's initial stage of language learning comes with sentence learning and creation, which can be simulated by exposing it to a language corpus. The core of the simulation is a memory-based learning model which has language hypernetwork structure. The language hypernetwork simulates developmental and progressive language learning using the structure of new data stream through making it representing of high level connection between language components possible. In this paper, we simulates an infant's gradual and developmental learning progress by training language hypernetwork gradually using 32,744 sentences extracted from video scripts of commercial animation movies for children.

• Journal of The Korean Association of Information Education
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• v.17 no.3
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• pp.233-242
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• 2013

"Problem-solving methods and procedures" sections in the 2009 revised informatics curriculum emphasized active use of algorithmic thinking to solve problems. And it is proposed to solve the various problems of real life using programming language for the implementation of the algorithm. Recently, various Educational Programming Language has been developed for elementary programming activity and many researches showed that students' cognitive burden was reduced in learning programming language with Educational Programming Languages. However implementation of the algorithm is difficult for novice programmer. For the reason, effective way is required for elementary students to connect design of the algorithm and implementation of the algorithm. Therefore, in this study propose the algorithm design worksheets that it is possible to create an algorithm to describe the content needed to implementation in programming education. And this study proved the effect of the algorithm design learning tools through experiment.

• The Journal of the Korea Contents Association
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• v.8 no.5
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• pp.94-103
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• 2008

In this paper, we adapt the $\kappa$-means clustering technique to segmenting a given 3D mesh. In order to avoid the locally minimal convergence and speed up the computing time, first we extract sharp vertices from the mesh by analysing its curvature and convexity that respectively reflect the local and global geometric characteristics from the viewpoint of cognitive science. Next the sharp vertices are partitioned into $\kappa$ clusters by iterated converging with the $\kappa$-means clustering method based on the geodesic distance instead of the Euclidean distance between each pair of the sharp vertices. For obtaining the effective result of $\kappa$-means clustering method, it is crucial to assign an initial value to $\kappa$ appropriately. Hence, we automatically compute a reasonable number of clusters as an initial value of $\kappa$. Finally the mesh segmentation is completed by merging other vertices except the sharp vertices into the nearest cluster by geodesic distance.

• Journal of Internet Computing and Services
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• v.19 no.4
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• pp.107-121
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• 2018

The purpose of this study is to explore the present US consumer behavioral trends and various cognitive schema types for sharing economy frame and shared service. For this, by applying Q methodology, this paper theoretically defines three differentiated typologies of US consumer in a interpretive perspective. This study is in-depth focused on discovering and categorizing characteristics of a respondent's thinking structure called 'schemata'. According to the entire procedures of Q methodology, this paper analyzed Q-sorted data from twenty-four people in the basis of forty Q-samples (statements). Consequently, we discovered four consumer groups named as Type 1 'Socialsumer', Type 2 'Smarsumer', Type 3 'Researsumer'.

• Proceedings of the Korea Society for Industrial Systems Conference
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• 1996.10a
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• pp.5-26
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• 1996

This study has two research objectives related to end-user computing (EUC) . One of the research objectives was to investigate the current status of EUC of Korean firms. Another research objective was to examine the relationship between individual difference of end-users and EUC success. Using survey data from 752 end-users of 23 firms, the surrent status of EUC and the relationship between individualdifferences of end-users and EUC success were investigated. The current status of EUC was examined from six perspectives : 1) what is the characteristics of EC strategy of Korean firms , 2) what are the individual characteristics of end-users in Korean firms, 3) what are the characteristics of tasks performed by end-users using computer 4) what are the application a areas of EUC 5) How end-users are satisfied with the support of firms, 6) what are system usage and satisfaction of end-users. It was also found that individual differences of endf-users are related to EUC success.More specifically , it was shown that the male gender, younger age, higher level of education , higher ran아 and organizational tenure, higher math ability , thinking type of cognitive style, positive and optimistic attitudes toward computer, more experience with computer, more computer education and knowledge are individual differences variables associated with EUC success. The results of stepwise regression analysis suggested that the individuaal difference variables accounted for 14%, 25% 39% and 30% of the variances of four EUC success variables, satisfaction for outcome , satisfaction for ability , frequency of computer use, and thenuber of tasks, respectively. These empirical findings suggest that EUC managers should consider individual differences of end-users in managing EUC , such as education, training, support, and human resource management , to maximize potential benefits of EUC.

• Journal of KIISE:Computing Practices and Letters
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• v.11 no.2
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• pp.112-123
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• 2005

The latest E-commerce sites provide personalized services to maximize user satisfaction for Internet user The collaborative filtering is an algorithm for personalized item real-time recommendation. Various supplementary methods are provided for improving the accuracy of prediction and performance. It is important to consider these two things simultaneously to implement a useful recommendation system. However, established studies on collaborative filtering technique deal only with the matter of accuracy improvement and overlook the matter of performance. This study considers representative attribute-neighborhood, recommendation textile set, and similarity grouping that are expected to improve performance to the recommendation agent system. Ultimately, this paper suggests empirical applications to verify the adequacy and the validity on this system with the development of Fashion Design Recommendation Agent System (FDRAS ).

• Korean Medical Education Review
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• v.18 no.2
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• pp.51-57
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• 2016

This literature review explores artificial intelligence (AI) technology trends and IBM Watson health and medical references. This study explains how healthcare will be changed by the evolution of AI technology, and also summarizes key technologies in AI, specifically the technology of IBM Watson. We look at this issue from the perspective of 'information overload,' in that medical literature doubles every three years, with approximately 700,000 new scientific articles being published every year, in addition to the explosion of patient data. Estimates are also forecasting a shortage of oncologists, with the demand expected to grow by 42%. Due to this projected shortage, physicians won't likely be able to explore the best treatment options for patients in clinical trials. This issue can be addressed by the AI Watson motivation to solve healthcare industry issues. In addition, the Watson Oncology solution is reviewed from the end user interface point of view. This study also investigates global company platform business to explain how AI and machine learning technology are expanding in the market with use cases. It emphasizes ecosystem partner business models that can support startup and venture businesses including healthcare models. Finally, we identify a need for healthcare company partnerships to be reviewed from the aspect of solution transformation. AI and Watson will change a lot in the healthcare business. This study addresses what we need to prepare for AI, Cognitive Era those are understanding of AI innovation, Cloud Platform business, the importance of data sets, and needs for further enhancement in our knowledge base.

• Journal of Internet Computing and Services
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• v.23 no.1
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• pp.95-103
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• 2022

The goal of education and training in military is to foster strong combatants who can fight and defeat enemies. The Korean military is deeply aware of the importance of education & training, and has been introducing various advanced training systems so far. Despite these efforts, however, the military environment to maintain and strengthen the level of training is becoming increasingly difficult. In this study, it was conducted on the effectiveness analysis and utilization of the game system for military education & training through literature review. As a result of literature analysis, the introduction of the game system could be expected to have various effects throughout the cognitive and behavioral areas. Based on this effect analysis, the concept and shape of game system operation for each purpose were derived, and an improved plan using the game system was proposed.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.25 no.12
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• pp.1729-1738
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• 2021

Machine learning has a close relationship with cognitive psychology and brain science and is developing together. This paper analyzes the OASIS-3 dataset using machine learning techniques and proposes a model for predicting dementia. Dimensional reduction through PCA (Principal Component Analysis) is performed on the data quantifying the volume of each area among OASIS-3 data, and only important elements (features) are extracted and then various machine learning including gradient boosting and stacking Apply the models and compare the performance of each. Unlike previous studies, the proposed technique has a great differentiation because it uses not only the brain biometric data, but also basic information data such as the participant's gender and medical information data of the participant. In addition, it was shown that the proposed technique through various performance evaluations is a model that can better predict dementia by finding features that are more related to dementia among various numerical data.

• Information Systems Review
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• v.18 no.4
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• pp.173-187
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• 2016

This study on the social effects of Internet of Things (IoTs) provides an overview of future job prospects through the scenario planning approach, highlighting the challenges and opportunities that IoTs will bring in the future. IoTs and the related field of technological innovations have become increasingly important in both academic and business communities in the past few years because of computing power breakthrough and its price drop. IoTs enables people to deal with routine works efficiently and challenges them even in non-routine and/or cognitive tasks, which are considered a unique area for individuals. The scenario planning analysis helps us to define the uncertain boundary and to estimate the potential opportunities and inherent threats to provide decision makers with a mind map on how the development of IoTs can influence employment. To assess the potential effects on jobs described in our scenarios, we briefly examine the local structure of employment and discuss which careers are expected to decline or grow in particular among the 52 standard occupational classifications in Korea.