• Journal of the Korean Institute of Intelligent Systems
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• v.12 no.6
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• pp.517-523
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• 2002

In this paper, we propose system that apply VIBL method to add speech recognition to LIBL method based on human s studying method to use natural language to steering system of ship, MERCS and winch appliances and use VIBL method to alternate process that linguistic instruction such as officer s steering instruction is achieved via ableman and control steering gear, MERCS and winch appliances. By specific method of study, ableman s suitable steering manufacturing model embodies intelligent steering gear controlling system that embody and language direction base studying method to present proper meaning element and evaluation rule to steering system of ship apply and respond more efficiently on voice instruction of commander using fuzzy inference rule. Also we embody system that recognize voice direction of commander and control MERCS and winch appliances. We embodied steering manufacturing model based on ableman s experience and presented rudder angle for intelligent steering system, compass bearing arrival time, evaluation rule to propose meaning element of stationary state and correct steerman manufacturing model rule using technique to recognize voice instruction of commander and change to text and fuzzy inference. Also we apply VIBL method to speech recognition ship control simulator and confirmed the effectiveness.

• The Journal of the Korea Contents Association
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• v.17 no.1
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• pp.25-38
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• 2017

This study investigates non-native speakers(NNS) of English use of backchannels with beginner-intermediate learners' use of 'uh', 'um(uhm)', 'and' and 'hm' suggesting a view as a possible pedagogical implication. The initial aim of this study was to learn this phenomenon and observe their conversation patterns to compare with previous studies. Based on the previous findings, the analyzed data using conventional Conversation Analysis (CA) methods indicate the possible presence of L1 topic markers, '-un' and '-nun' in the form of L2 backchannel tokens when uttered by beginning and intermediate level speakers of English and the presences of L2 backchannel tokens appear only in front of noun phrases. Additionally, these same words with these tokens and when translated back to Korean also require topic markers of '-un' and '-nun.' Finally, This study discusses possible pedagogical implications with the initial analysis of backchannel tokens for Korean EFL learners. In addition, the ultimate goal of this study is to refine this analysis with follow up experiments to validate this investigation into a working hypothesis generating discussions of this backchannel phenomenon from being viewed as a hindrance to as an positive influence that needs to be understood.

• School Mathematics
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• v.5 no.2
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• pp.259-273
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• 2003

A fraction is one of the most important concepts that students have to learn in elementary school. But it is a challenge for students to understand fraction concept because of its conceptual complexity. The focus of fraction learning is understanding the concept. Then the problem is how we can facilitate the conceptual understanding and estimate it. In this study, Moore's concept understanding scheme(concept definition, concept image, concept usage) was adopted as an theoretical framework to investigate students' fraction understanding. The questions of this study were a) what concept image do students have\ulcorner b) How well do students solve fraction problems\ulcorner c) How do students use fraction concept to generate fraction word problem\ulcorner By analyzing the data gathered from three elementary school, several conclusion was drawn. 1) The students' concept image of fraction is restricted to part-whole sub-construct. So is students' fraction understanding. 2) Students can solve part-whole fraction problems well but others less. This also imply that students' fraction understanding is partial. 3) Half of the subject(N=98) cannot pose problems that involve fraction and fraction operation. And some succeeded applied the concept mistakenly. To understand fraction, various fraction subconstructs have to be integrated as whole one. To facilitate this integration, fraction program should focus on unit, partitioning and quantity. This may be achieved by following activities: * Building on informal knowledge of fraction * Focusing on meaning other than symbol * Various partitioning activities * Facing various representation * Emphasizing quantitative aspects of fraction * Understanding the meanings of fraction operation Through these activities, teacher must help students construct various faction concept image and apply it to meaningful situation. Especially, to help students to construct various concept image and to use fraction meaningfully to pose problems, much time should be spent to problem posing using fraction.

• Journal of the Korean Geographical Society
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• v.31 no.2
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• pp.329-345
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• 1996

The purposes of this study are to review research trends of applied geography field, to retrospect geographical works done by Korean geographers in applied geography, and to prospect the future of applied geography. We are in the period where societal problems such as energy, transportation, pollution, environment, health care, and many others, require careful consideration and need throughout strategies for solution. Most societal problems have some geographical dimensions. Because these problems are geographic in nature, there is an obvious implication that geography as a discipline has something to offer in their solutions. In fact, most geographic problems are best presented and analyzed through the applications of geographic theories, concepts and tools. Applied geography is a branch of general geography. It relies on the scientific methods and uses the principles and methods of pure geography. However applied geography is different in that it analyzes and evaluates real world action and planning and seeks to implement and manipulate environmental and spatial realities. Thus, geographic theories and other social theories that have geographic dimensions are fundamental to applied geography. Applied geography has a short history as theme in Korean geography. During the last two decades. Korea achieved remarkable economic growth. We have also encountered widening regional disparity, housing shortage of larger cities, transportation congestion, environmental pollution and many other problems. Applied geographers have tried to analyze and solve such spatial problems during the last 30 years. The research trend of Korean applied geography can be subdivided into 5 categories: (1) land use analysis and efficient utilization, (2) national physical development and planning. (3) regional development and regional planning, (4) tourism and location-allocation, transportation planning. Still the overconcentration of Seoul metropolitan region and unbalanced regional development are perceived to be the serious spatial problems which may induce more works to solve these problems. In Korea new emphasis has to be given to some professional training and experimental learning, including methodology, field techniques data management, statistical analysis, cartography, GIS, and other tools, as applicable and beneficial to problem solving in real world. The growth of applied geography depends on new insights and purposed solutions of future applied geographers in Korea. Applied geographers will contribute to the creation of future Korean geographies.

• Journal of the Korean earth science society
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• v.40 no.2
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• pp.188-199
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• 2019

The purpose of this study was to investigate the tendency of inquiry of earth science content presented in North Korean textbooks of the 2013 National curriculum using Romey's method, and to help use as basic data for better understanding earth science education in North Korea. The content of earth science in the text, figure, question, and activity index of textbooks of Natural Science 1 and 2, Chosun Geography 2 of elementary junior high school, and of Geography 1 of advanced junior high school were all analyzed using Romey's method. The results of this study were as follows: First, the atmospheric science question and the astronomy text showed the tendency of inquiry type. Second, the proportion of oceanography was relatively small. Third, there were many non-inquiry questions or excessive inquiry questions, and both types of questions needed to be balanced. Fourth, there were a tendency that did not emphasize inquiry learning. Finally, the quantitative and qualitative level of inquiry tendency should be improved. In this paper, we propose to use a qualitative method when analyzing earth science content in North Korean textbooks, and suggested that we should further study the comparative analysis of inquiry tendency of earth science content using South and North Korean textbooks.

• 재활복지
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• v.18 no.4
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• pp.165-186
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• 2014

The purpose of the study is intended to analysis on students adjustment of students with disabilities in a special class of the elementary school focused on KCI journals through a systematic review. This study was searched from papers published from Jan, 2004 to May, 2014 using KISS, DBPIA, RISS, Google databases. The key words were "inclusive education, special class, inclusive class, student with disabilities, school adjustment, school life, school adjustment scale, elementary school". Results of data analysis were follows; 1. A total of 35 papers were analyzed. Except for 6 papers published in 2004~2007, 29 papers were published after 2008.; 2. The participant of study subject was total 141. Students with intellectual disability were 61.7%. Students with learning disabilities were 17.0%.; 3. The assessment domain of study was analyzed total 51 data.; academic achievement and task performance (25.4%), class attitude and participatory behavior(23.5%), problem behavior(21.5%). The Study in student with intellectual disability was 10 assessment domains.; 4. The method of assessment was total 41.; the use of operational definition(56.1%), the development of test (17.1%), and the use of assessment tool(14.6%).

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.22 no.2
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• pp.63-70
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• 2022

Although 2D Object detection has been largely improved in the past years with the advance of deep learning methods and the use of large labeled image datasets, 3D object detection from 2D imagery is a challenging problem in a variety of applications such as robotics, due to the lack of data and diversity of appearances and shapes of objects within a category. Google has just announced the launch of Objectron that has a novel data pipeline using mobile augmented reality session data. However, it also is corresponding to 2D-driven 3D object detection technique. This study explores more mature 2D object detection method, and applies its 2D projection to Objectron 3D lifting system. Most object detection methods use bounding boxes to encode and represent the object shape and location. In this work, we explore a stochastic representation of object regions using Gaussian distributions. We also present a similarity measure for the Gaussian distributions based on the Hellinger Distance, which can be viewed as a stochastic Intersection-over-Union. Our experimental results show that the proposed Gaussian representations are closer to annotated segmentation masks in available datasets. Thus, less accuracy problem that is one of several limitations of Objectron can be relaxed.

• Science of Emotion and Sensibility
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• v.26 no.4
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• pp.3-14
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• 2023

Recently, the effect of using social media on psychological well-being has been highlighted. However, studies exploring factors that may predict the quality of social media relationships are relatively rare. The present study investigated whether social media activity and psychological states, such as loneliness and depression, can predict the quality of social media relationships during the COVID-19 quarantine period using a machine learning technique. Ninety-five participants completed a self-report survey on loneliness, Instagram activity, quality of social media relationships, and depression at different time points (during the self-isolation and after the release of self-isolation). Similarity analyses, including multidimensional scaling (MDS), representational similarity analysis (RSA), and classification analyses, were conducted separately at each point in time. The results of MDS revealed that time spent on social media and depression were distinguished from others in the first dimension, and loneliness and passive use were distinguished from others in the second dimension. We divided the data into two groups based on the quality of social media relationships (high and low), and we conducted RSA on each group. Findings indicated an interaction between the quality of the social media relationships and the situation. Specifically, the effect of self-isolation on the high-quality social media relationship group is more pronounced than that on the low-quality group. The classification results also revealed that the predictors of social media relationships depend on whether or not they are isolated. Overall, the results of this study imply that social media relationship could be well predicted when people are not in isolated situations.

• The Mathematical Education
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• v.63 no.1
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• pp.1-18
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• 2024

This study aims to analyze low-performing high school students' difficulties in constructed response (CR) mathematics assessments and explore ways to use writing activities to support student learning. The participants took CR assessments, engaged in guided writing activities across 15 lessons, and provided responses to our interviews. The study identified 20 types of student difficulties, which were sorted into two main categories: "mathematical difficulties" and "CR difficulties." The difficult nature of mathematics as a school subject included a lack of understanding of mathematical concepts, students' difficulty with mathematical symbols and notations, and struggles with word problems. Challenges specific to CR assessments included students' difficulties arising from the testing conditions unlike those of multiple-choice items, and included issues related to constructing appropriate responses and psychological barriers. To address these challenges in CR assessments, the study conducted guided writing activities as an intervention, through which six themes were identified: (1) internalization of mathematical concepts, (2) mathematical thinking through relational understanding, (3) diverse problem-solving methods, (4) use of mathematical symbols, (5) reflective thinking, and (6) strategies to overcome psychological barriers.

• Journal of Intelligence and Information Systems
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• v.19 no.2
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• pp.39-54
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• 2013

Recent explosive increase of electronic commerce provides many advantageous purchase opportunities to customers. In this situation, customers who do not have enough knowledge about their purchases, may accept product recommendations. Product recommender systems automatically reflect user's preference and provide recommendation list to the users. Thus, product recommender system in online shopping store has been known as one of the most popular tools for one-to-one marketing. However, recommender systems which do not properly reflect user's preference cause user's disappointment and waste of time. In this study, we propose a novel recommender system which uses data mining and multi-model ensemble techniques to enhance the recommendation performance through reflecting the precise user's preference. The research data is collected from the real-world online shopping store, which deals products from famous art galleries and museums in Korea. The data initially contain 5759 transaction data, but finally remain 3167 transaction data after deletion of null data. In this study, we transform the categorical variables into dummy variables and exclude outlier data. The proposed model consists of two steps. The first step predicts customers who have high likelihood to purchase products in the online shopping store. In this step, we first use logistic regression, decision trees, and artificial neural networks to predict customers who have high likelihood to purchase products in each product group. We perform above data mining techniques using SAS E-Miner software. In this study, we partition datasets into two sets as modeling and validation sets for the logistic regression and decision trees. We also partition datasets into three sets as training, test, and validation sets for the artificial neural network model. The validation dataset is equal for the all experiments. Then we composite the results of each predictor using the multi-model ensemble techniques such as bagging and bumping. Bagging is the abbreviation of "Bootstrap Aggregation" and it composite outputs from several machine learning techniques for raising the performance and stability of prediction or classification. This technique is special form of the averaging method. Bumping is the abbreviation of "Bootstrap Umbrella of Model Parameter," and it only considers the model which has the lowest error value. The results show that bumping outperforms bagging and the other predictors except for "Poster" product group. For the "Poster" product group, artificial neural network model performs better than the other models. In the second step, we use the market basket analysis to extract association rules for co-purchased products. We can extract thirty one association rules according to values of Lift, Support, and Confidence measure. We set the minimum transaction frequency to support associations as 5%, maximum number of items in an association as 4, and minimum confidence for rule generation as 10%. This study also excludes the extracted association rules below 1 of lift value. We finally get fifteen association rules by excluding duplicate rules. Among the fifteen association rules, eleven rules contain association between products in "Office Supplies" product group, one rules include the association between "Office Supplies" and "Fashion" product groups, and other three rules contain association between "Office Supplies" and "Home Decoration" product groups. Finally, the proposed product recommender systems provides list of recommendations to the proper customers. We test the usability of the proposed system by using prototype and real-world transaction and profile data. For this end, we construct the prototype system by using the ASP, Java Script and Microsoft Access. In addition, we survey about user satisfaction for the recommended product list from the proposed system and the randomly selected product lists. The participants for the survey are 173 persons who use MSN Messenger, Daum Caf$\acute{e}$, and P2P services. We evaluate the user satisfaction using five-scale Likert measure. This study also performs "Paired Sample T-test" for the results of the survey. The results show that the proposed model outperforms the random selection model with 1% statistical significance level. It means that the users satisfied the recommended product list significantly. The results also show that the proposed system may be useful in real-world online shopping store.