• Journal of KIISE:Software and Applications
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• v.29 no.1_2
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• pp.42-52
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• 2002

Information extraction(IE) is a process of recognizing and fetching particular information fragments from a document. In previous work, most IE systems generate the extraction rules called the wrappers manually, and although this manual wrapper generation may achieve more correct extraction, it reveals some problems in flexibility, extensibility, and efficiency. Some other researches that employ automatic ways of generating wrappers are also experiencing difficulties in acquiring and representing useful domain knowledge and in coping with the structural heterogeneity among different information sources, and as a result, the real-world information sources with complex document structures could not be correctly analyzed. In order to resolve these problems, this paper presents an agent-based information extraction system named XTROS that exploits the domain knowledge to learn from documents in a semi-structured information source. This system generates a wrapper for each information source automatically and performs information extraction and information integration by applying this wrapper to the corresponding source. In XTROS, both the domain knowledge and the wrapper are represented as XML-type documents. The wrapper generation algorithm first recognizes the meaning of each logical line of a sample document by using the domain knowledge, and then finds the most frequent pattern from the sequence of semantic representations of the logical lines. Eventually, the location and the structure of this pattern represented by an XML document becomes the wrapper. By testing XTROS on several real-estate information sites, we claim that it creates the correct wrappers for most Web sources and consequently facilitates effective information extraction and integration for heterogeneous and complex information sources.

• The KIPS Transactions:PartD
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• v.18D no.5
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• pp.385-392
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• 2011

Recently, the concern of IT-in-Agriculture convergence technology that combines information technology and agriculture is increasing rapidly. Especially, the crop cultivation related prediction services by spatial data mining (SDM) can play an important role in reducing the damage of natural disaster and enhancing crop productivity. However, the data conversion and integration procedure to acquire the learning dataset of SDM for the prediction service need a lot of effort and time, because of their heterogeneity between distributed data. In addition, calculating spatial neighborhood relationships between spatial and non-spatial data necessitates requires the complicated calculation procedure for large dataset. In this paper, we suggest a SOA-based data integration framework that can effectively integrate distributed heterogeneous data by treating each data source as a service unit and support to find the optimal prediction service by improving productivity of learning dataset for SDM. In our experiment, we confirmed that our framework can be effectively applied to find the optimal prediction service for the frost damage area, by considering the case of peach crop cultivation in Icheon in Korea.

• Journal of the Korean Operations Research and Management Science Society
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• v.40 no.4
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• pp.145-156
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• 2015

Incorporation of individual learning and forgetting behaviors within worker-task assignment models produces a mixed integer nonlinear program (MINLP) problem, which is difficult to solve as a NP hard due to its nonlinearity in the objective function. Previous studies commonly assume homogeneity among workers in workforce scheduling that takes account of learning and forgetting characteristics. This paper expands previous researches by considering heterogeneous individual learning/forgetting, and investigates the impact of worker heterogeneity in initial expertise, steady-state productivity, learning and forgetting on system performance to assist manager's decision-making in worker-task assignments without tackling complex MINLP models. In order to understand the performance implications of workforce heterogeneity, this paper examines analytically how heterogeneity in each of the four parameters of the exponential learning and forgetting (L/F) model affects system performance in three cases : consecutive assignments with no break, n breaks of s-length each, and total b break-periods occurred over T periods. The study presents the direction of change in worker performance under different assignment schedules as the variance in initial expertise, steady-state productivity, learning or forgetting increases. Thus, it implies whether having more heterogenous workforce in terms of each of four parameters in the L/F model is desired or not in different schedules from the perspective of system productivity measurement.

• Journal of Biomedical Engineering Research
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• v.42 no.5
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• pp.232-240
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• 2021

Heterogeneity in cancer is the major obstacle for precision medicine and has become a critical issue in the field of a cancer diagnosis. Many attempts were made to disentangle the complexity by molecular classification. However, multi-dimensional information from dynamic responses of cancer poses fundamental limitations on biomolecular marker-based conventional approaches. Cell morphology, which reflects the physiological state of the cell, can be used to track the temporal behavior of cancer cells conveniently. Here, we first present a hybrid learning-based platform that extracts cell morphology in a time-dependent manner using a deep convolutional neural network to incorporate multivariate data. Feature selection from more than 200 morphological features is conducted, which filters out less significant variables to enhance interpretation. Our platform then performs unsupervised clustering to unveil dynamic behavior patterns hidden from a high-dimensional dataset. As a result, we visualize morphology state-space by two-dimensional embedding as well as representative morphology clusters and trajectories. This cell morphology profiling strategy by hybrid learning enables simplification of the heterogeneous population of cancer.

• Proceedings of the Korean Information Science Society Conference
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• 2002.04b
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• pp.697-699
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• 2002

본 논문에서는 웹기반 실시간 온라인 토론에서 집단구성을 내향성 집단, 외향성 집단 내향성/외향성 혼합집단으로 분류하고 집단구성방식이 토론 내용에 어떤 영향을 미치는지 연구하였다. 이를 위하여 학습자를 대상으로 MBTI(Myers Briggs Type Indicator) 성격유형 검사를 실시하고 온라인 토론을 수행한 후, 토론 내용을 Henri의 메시지 분석 모친에 기초한 지표를 기준으로 각 차원별 의미단위로 분석하였다. 그 차원들 중 사회적 차원과 상호작용적 차원을 토론 내용의 상호의존성으로, 인지적 차원과 메타 인지적 차원을 토론 내용의 과제관련성으로 범주화하였다. 실험 결과에 따르면 토론 내용의 총 의미단위 수, 상호의존성, 과세관련성 모두에서 이질적으로 구성된 내향성/외향성 혼합집단이 가장 긍정적인 영향을 미친 것을 확인하였다.

• Journal of Korean Society of Transportation
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• v.19 no.5
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• pp.119-134
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• 2001

This paper proposed a dynamic transit vehicle simulation model and a dynamic transit passengers simulation model, which can simultaneously simulate the transit vehicles and passengers traveling on a transit network, and also developed an algorithm of dynamic departure time choice model based on individual passenger. The proposed model assumes that each passenger's behavior is heterogeneous based on stochastic process by relaxing the assumption of homogeneity among passengers and travelers have imperfect information and bounded rationality to more actually represent and to simulate each passenger's behavior. The proposed model integrated a inference and preference reforming procedure into the learning and decision making process in order to describe and to analyze the departure time choices of transit passengers. To analyze and evaluate the model an example transit line heading for work place was used. Numerical results indicated that in the model based on heterogeneous passengers the travelers' preference influenced more seriously on the departure time choice behavior, while in the model based on homogeneous passengers it does not. The results based on homogeneous passengers seemed to be unrealistic in the view of rational behavior. These results imply that the aggregated travel demand models such as the traditional network assignment models based on user equilibrium, assuming perfect information on the network, homogeneity and rationality, might be different from the real dynamic travel demand patterns occurred on actual network.

• Journal of The Korean Association For Science Education
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• v.41 no.5
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• pp.429-440
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• 2021

In this article, we explored the value of interculturalism in developing the discourses of international cooperation in science education. By doing so, we interviewed four teachers who had an experience in teaching science in developing countries, and analyzed their experiences and perceptions in the lens of interculturalism and dialogue. Our analysis of teacher narratives shows the transition in the teachers' perspectives from volunteering and transmission to collaboration and learning. The transition from volunteering to collaboration occurred as the teachers learned how to meet 'the others' as themselves being strangers in the foreign context. Through intervening and colliding, teachers were able to reposition their identities as teachers. Furthermore, their science teaching practices show how the teachers tried to negotiate between the universal or idealistic value of science education and the heterogeneities formed by the country's cultural and specific situation of science education. Through these experiences, the teachers began to understand the importance of the culturally specific 'need' for science education. In conclusion, we proposed a discourse of science education collaboration based on interculturalism in terms of the diversity and complexity of science education practices in developing countries, teacher professionalism, culturally relevant pedagogy and sustainable policy.

• The Journal of Korean Association of Computer Education
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• v.14 no.1
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• pp.35-43
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• 2011

The purpose of this research is to confirm that how the support type of the assistant teacher changes the students' creativity and self-efficacy in the Robot Education, particularly Robot Edu-Camp. The study objects are 72 elementary students for 8 groups; each group has 9 students, and 4 groups of them have the assistant teachers and others are supported by giving some feedbacks for their questions or some information if they need. The assumption of this study sets up as in the following; there are no differences for the students' creativity and self-efficacy between the supporting of the assistant teachers with making robots and programing together and the giving feedbacks and information if students need. To verify this assumption, we use the nonequivalent control group in the pretest-posttest designs. The result is as in the following. There's no meaningful differences of the students' creativity by the support type of the assistant teachers. But in the self-efficacy, the groups which are giving feedbacks and information if they need have more higher level of achievement than others. The result shows that if the assistant teachers help the students directly, the students' levels of the self-direction, and control are low because they lean on the teachers. This will give you some implications to the follow-up studies about the support type of the assistant teachers in the Robot Education.

• The Journal of Korean Association of Computer Education
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• v.14 no.3
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• pp.25-36
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• 2011

The purpose of this study was to analyze the effects of educational programming language(EPL) using the meta-analysis method. In order to achieve the purpose of this study, t-test and F-test were performed for the effect size differences between the variables. The results of the study were as follows: First, EPL turned out to be highly effective in improving learning effects. The total mean of effect size was as big as 1.01 and the value of $U_3$ was 84.38%. EPL increased the learning effect by 34.38% compared with the control group. Second, the moderator variables such as subject, publication type, and learner's school age there was no statistically significant differences. By designing the experiment nonequivalent control group pretest-posttest design showed statistically significant effect size compared with single group pretest-posttest design. Third, the mean effect sizes of the dependent variables were as follows: Creativity 1.90, problem solving ability 1.25, logical thinking ability 1.18, learning motivation 0.81, and achievement 0.59. EPL showed positive effect than traditional teaching and learning method comprehensively.

• Journal of The Korean Association For Science Education
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• v.22 no.4
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• pp.717-724
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• 2002

In this study. the effects of grouping by students' agreeableness in cooperative learning strategy applied to middle school science classes on their achievement. confidence, satisfaction, attitude toward science class, and cohesion of group members were investigated. One hundred and fifty-eight students were assigned to control group, homogeneous group and heterogeneous group, and taught about separation of mixture for 7 class hours. The results revealed that there was no significant difference in the achievement test scores. However, significant interaction between the instruction and the level of agreeableness were found in the satisfaction and the cohesion of group members. Students of higher agreeableness level in the homogeneous group were more satisfied with science class and cohesive. Students' attitude toward science class in the homogeneous group was also significantly higher than those in the other groups.