• KSII Transactions on Internet and Information Systems (TIIS)
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• v.17 no.3
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• pp.861-880
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• 2023

Semantic segmentation of road scene is the key technology of autonomous driving, and the improvement of convolutional neural network architecture promotes the improvement of model segmentation performance. The existing convolutional neural network has the simplification of learning knowledge and the complexity of the model. To address this issue, we proposed a road scene semantic segmentation algorithm based on multi-task collaborative learning. Firstly, a depthwise separable convolution atrous spatial pyramid pooling is proposed to reduce model complexity. Secondly, a collaborative learning framework is proposed involved with saliency detection, and the joint loss function is defined using homoscedastic uncertainty to meet the new learning model. Experiments are conducted on the road and nature scenes datasets. The proposed method achieves 70.94% and 64.90% mIoU on Cityscapes and PASCAL VOC 2012 datasets, respectively. Qualitatively, Compared to methods with excellent performance, the method proposed in this paper has significant advantages in the segmentation of fine targets and boundaries.

• Journal of Gastric Cancer
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• v.10 no.4
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• pp.247-253
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• 2010

Purpose: Most stomach surgeons have been educated sufficiently in conventional open distal gastrectomy (ODG) but insufficiently in laparoscopy-assisted distal gastrectomy (LADG). We compared learning curves and clinical outcomes between ODG and LADG by a single surgeon who had sufficient education of ODG and insufficient education of LADG. Materials and Methods: ODG (90 patients, January through September, 2004) and LADG groups (90 patients, June 2006 to June 2007) were compared. The learning curve was assessed with the mean number of retrieved lymph nodes, operation time, and postoperative morbidity/mortality. Results: Mean operation time was 168.3 minutes for ODG and 183.6 minutes for LADG. The mean number of retrieved lymph nodes was 37.9. Up to about the 20th to 25th cases, the slope decrease in the learning curve for LADG was more apparent than for ODG, although they both reached plateaus after the 50th cases. The mean number of retrieved lymph nodes reached the overall mean after the 30th and 40th cases for ODG and LADG, respectively. For ODG, complications were evenly distributed throughout the subgroups, whereas for LADG, complications occurred in 10 (33.3%) of the first 30 cases. Conclusions: Compared with conventional ODG, LADG is feasible, in particular for a surgeon who has had much experience with conventional ODG, although LADG required more operative time, slightly more time to get adequately retrieved lymph nodes and more complications. However, there were more minor problems in the first 30 LADG than ODG cases. The unfavorable results for LADG can be overcome easily through an adequate training program for LADG.

• Journal of Korean Academy of Nursing
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• v.30 no.4
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• pp.1055-1065
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• 2000

The purpose of this study was to develop, through the integration of instructional theory, a Courseware and to investigate the effectiveness of a web-based computer assisted instruction(WBI) program for preventing drug abuse, a serious problem for youth problem. During the first stage of this study done "Drug Abuse Prevention" Courseware was developed based on, Gagn & Brigg's instructional design theory, Keller's ARCS theory and the CAI model of Hannafin & Peck. For the second stage, the courseware was used to provide education for students adolescents in drug abuse prevention. This study used an quasi-experimental, one-group pretest-posttest design with a convenience sample of 36 male high school students who were at one high school located in Seoul. Data were collected using self-reported questionnaires which included a learning achievement tool, the Keller's IMMS (Instructional Material Motivation Survey), on attitudes to drug use, and on responses to the WBI instruction. Prior to the experiment, the "drug abuse prevention" learning method and the procedures of the study were explained to the students, and then the learning achievement of the subjects was measured as a pretest. The students were then given 2 weeks WBI utilizing the courseware. A post-test which included the pre-test learning achievement questionnaire and a survey of learning motivation and attitudes toward drug were given two weeks after the education was completed. The data analysis was done using SPSS/PC. Paired t-test was used to analyze the differences between the pre-test and post-test scores for learning achievement. The results of the analysis are as follows: There were significant differences in learning achievement between the pre-test and post-test(t=-18.62, p=0.000). The hypothesis, that learning achievement will be higher, after the class has used the courseware, than before was supported. The scores for learning motivation and attitudes toward drugs were also higher than the results of existing studies. In conclusion, this study suggests that WBI is an effective learning method in the prevention of drug abuse for adolescents as it can be used for self-learning and repeated learning as assisted instruction. Recommendation would be given that further research needs to be develped in the courseware by cognitive learning style and by multimedia courseware and virtual reality system.

• English Language & Literature Teaching
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• v.12 no.3
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• pp.187-210
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• 2006

This study aims to investigate the effects of the implementation of self-directed learning through the homepage between the teacher and the students for English reading classes. The study focuses on the questions of whether the self-directed learning through the homepage, compared to the teacher-centered learning, would enable a significantly positive change in the students' achievements and of what their responses to this new learning method are. 72 students were grouped into an experimental and a control group, and then each group was subdivided into three levels (high, medium, low) of proficiency. Findings demonstrate that the experimental group showed statistically more significant increases in their scores of reading proficiency test than the control group. For the question of students' responses to the learning experience, the three groups within the experimental group responded to a questionnaire survey with regard to the positive attitude of learning, the effectiveness of self-directed learning and its learning materials, and usability of the homepage. In general, the experimental group considered the experience satisfactory, although the degree of positive responses varied according to the proficiency level of the group. This suggests the importance and effectiveness of self-directed learning using the computer and internet as a supplementary learning tool.

• Journal of the Korean School Mathematics Society
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• v.9 no.4
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• pp.521-538
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• 2006

The purpose of this study is to examine the effect of teaching mathematical proofs that made use of the 'proof assisted cards' at the second year of middle school and to investigate students' ability to geometric proofs as well as changes of mathematical attitudes toward geometric proofs. The subjects are seven students at the 2nd year of D Middle School in Daegu who made use of the 'proof assisted cards' during five class periods. The researcher interviewed the students to investigate learning questions made by students as well as the 'proof assisted cards' before and after use. The findings are as follows: first, the students made change of geometric proof ability by proof activity with the 'proof assisted cards' and second, the students made significant change of mathematical attitudes toward geometric proofs by proof activity using the cards.

• Speech Sciences
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• v.7 no.3
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• pp.69-85
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• 2000

Recently, Computer Assisted Language Learning (CALL) received widely held attention from diverse audiences. However, to the author's knowledge, relatively little attention was paid to the educational implications of voice recognition (VR) softwares in language teaching in general, and teaching and learning pronunciation in particular. This study explores, and extends the applicability of VR softwares toward second language research areas addressing how VR softwares might facilitate interview data entering processes. To aid the readers' understanding in this field, the background of classroom interaction research, and the rationale of why interview data, therefore the role of VR softwares, becomes critical in this realm of inquiry will be discussed. VR softwares' development and a brief report on the features of up-to-date VR softwares will be sketched. Finally, suggestions for future studies investigating the impact of VR softwares on second language learning, teaching, and research will be offered.

• Journal of Digital Contents Society
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• v.7 no.3
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• pp.175-182
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• 2006

The Internet is now of the fastest growing areas of telecommunications and of Computer Assisted Language Learning. It is rapidly becoming more integrated into society and accessible to people form around the world. A number of educators believe there is potential for language teaching and learning opportunities through the Internet, and have already developed uses and resources for this purpose. The range of what is available is growing continually. The purpose of this study is to research CMC via the Internet and other long-distance networks, to investigate the analyse best and worst things about studying English on the internet and to suggest some findings from the comparison between internet and classroom learning by means of questionnaire.

• Korean Journal of Radiology
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• v.21 no.4
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• pp.387-401
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• 2020

Radiomics and deep learning have recently gained attention in the imaging assessment of various liver diseases. Recent research has demonstrated the potential utility of radiomics and deep learning in staging liver fibroses, detecting portal hypertension, characterizing focal hepatic lesions, prognosticating malignant hepatic tumors, and segmenting the liver and liver tumors. In this review, we outline the basic technical aspects of radiomics and deep learning and summarize recent investigations of the application of these techniques in liver disease.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.20 no.8
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• pp.403-416
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• 2019

The focus of this study is on the new instructional and pedagogical application of teaching English as a foreign language (TEFL) with technology and by gender. Participants comprised 204 TEFL students in Korea. The study was conducted in the 2017 academic year. For this study, all participants attended English class using technology for three hours a week. Course syllabus, lecture notes, and other study materials were uploaded to the school website. Homework assignments, quizzes, and exams were also distributed through the website. To ascertain whether there are any differential effects from gender on learning English as a foreign language using technology, the quantitative materials included pre- and post-tests. This study also adopted qualitative methods, with structured interviews to obtain participants' comprehensive view of technology-assisted English lessons. Paired sample t-tests and independent t-tests were administered to analyze the quantitative data. The qualitative data were analyzed with the content analysis method. Findings show that both male and female students improved their English-speaking skills using technology. However, no gender difference was found in technology-assisted TEFL. Technology use for learning English also resulted in both genders' positive perceptions of language lessons. Based on these findings, this study yields practical implications for TEFL teachers in Korea.

• Smart Structures and Systems
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• v.24 no.6
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• pp.733-744
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• 2019

Wind speed forecasting is critical for a variety of engineering tasks, such as wind energy harvesting, scheduling of a wind power system, and dynamic control of structures (e.g., wind turbine, bridge, and building). Wind speed, which has characteristics of random, nonlinear and uncertainty, is difficult to forecast. Nowadays, machine learning approaches (generalized regression neural network (GRNN), back propagation neural network (BPNN), and extreme learning machine (ELM)) are widely used for wind speed forecasting. In this study, two schemes are proposed to improve the forecasting performance of machine learning approaches. One is that optimization algorithms, i.e., cross validation (CV), genetic algorithm (GA), and particle swarm optimization (PSO), are used to automatically find the optimal model parameters. The other is that the combination of different machine learning methods is proposed by finite mixture (FM) method. Specifically, CV-GRNN, GA-BPNN, PSO-ELM belong to optimization algorithm-assisted machine learning approaches, and FM is a hybrid machine learning approach consisting of GRNN, BPNN, and ELM. The effectiveness of these machine learning methods in wind speed forecasting are fully investigated by one-year field monitoring data, and their performance is comprehensively compared.