• East Asian Journal of Business Economics (EAJBE)
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• v.2 no.2
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• pp.37-47
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• 2014

Purpose - In this study, it is attempted to examine the Islamic banking practice in Iran based on new scientific methods. Design/methodology/approach- It is used the financial ratios demonstrating healthy or non-healthy of banks to assess the financial health of listed banks in Tehran Stock Exchange. The assessment of these ratios with use of decision tree as a non-parametric method for modeling is recommended for presenting this model. Information about the financial health of banks could be effective on the decisions of different groups of banks' financial reports users, including shareholders, auditors, stock exchange, central bank and etc. Findings - the results of the study show that Decision Tree is strong approach in order to classifying Islamic banks in Iran. Originality/value- So far, several studies have been conducted in various countries on the topic of this study. Considering the importance Islamic banking, it is almost the first study in Iran and the outcomes of the study may helpful to Iranian economy.

• ETRI Journal
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• v.34 no.2
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• pp.292-295
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• 2012

Beyond the simple keyword matching methods in contextual advertising, we propose a rich contextual matching (CM) model adopting a classification method for topic targeting and a query expansion method for semantic ad matching. This letter reports on an investigation into the empirical effects of the CM model by comparing the click-through rates (CTRs) of two practical online news advertising systems. Based on the evaluation results from over 100 million impressions, we prove that the average CTR of our proposed model outperforms that of a traditional model.

• Journal of Families and Better Life
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• v.33 no.2
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• pp.1-19
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• 2015

The objective of this study is to analyze the scope and depth of financial education currently delivered through three subjects in middle and high schools in South Korea. In order to systematically achieve the research objective, this study analyzed the textbooks to see how much coverage each topic received based upon the Finance Education Standards developed by the Financial Supervisory Service and the Korea Institute for Curriculum and Evaluation in 2011. In particular, this study used textbooks of three subjects such as Technology Home Economics, Social Studies, and Economics. Finally, this study discussed several implications for financial educators for teenagers and policy makers.

• Journal of Power Electronics
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• v.10 no.6
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• pp.660-666
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• 2010

This paper presents the approach followed to develop a course that introduces reliability into the design of power electronics converters. The course is part of the curriculum of a master of science in electrical engineering program, and it is aimed at providing reliability tools that can be used in a straightforward manner, while avoiding the mathematical intricacies. The reliability calculations are performed according to the Military Handbook 217, using the evaluation version of a commercial software package which greatly reduces the computational burden usually associated with this task. The course assessment shows that, after attending the course, students were able to improve the mean time between failures in a power-electronics converter, from a minimum of 5%, up to 100%.

• Asian Journal for Public Opinion Research
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• v.9 no.3
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• pp.240-265
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• 2021

Public services need to be evaluated regularly to identify areas that need further improvement. Data collection via Twitter is affordable and timely, so it has the potential to be utilized to evaluate the quality of public service. This study utilizes tweets mentioning three service units of the provincial government of Jakarta and applies both sentiment analysis and topic classification to predict a rating/score of public service quality. The research goal is to examine if the evaluation of public services based on social media data is possible. The findings indicate that the use of Twitter has an advantage in terms of sample size and variety of opinions. Tweets can be translated into scores as well. Nonetheless, the representativeness issue and the predominance of complaint tweets can affect the reliability of the results.

• Journal of Sensor Science and Technology
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• v.31 no.2
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• pp.79-84
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• 2022

Self-powered sensors play an important role in everyday life, and they cover a wide range of topics. These sensors are meant to measure the amount of relevant motion and transform the biomechanical activities into electrical signals using triboelectric nanogenerators (TENGs) since they are sensitive to external stimuli such as pressure, temperature, wetness, and motion. The present advancement of TENGs-based self-powered wearable, implantable, and patchable sensors for healthcare monitoring, human body motion, and medication delivery systems was carefully emphasized in this study. The use of TENG technology to generate electrical energy in real-time using self-powered sensors has been the topic of considerable research among various leading scholars. TENGs have been used in a variety of applications, including biomedical and healthcare physical sensors, wearable devices, biomedical, human-machine interface, chemical and environmental monitoring, smart traffic, smart cities, robotics, and fiber and fabric sensors, among others, as efficient mechanical-to-electric energy conversion technologies. In this evaluation, the progress accomplished by TENG in several areas is extensively reviewed. There will be a discussion on the future of self-powered sensors.

• Journal of Information Processing Systems
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• v.18 no.6
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• pp.794-802
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• 2022

The recovery of reasonable depth information from different scenes is a popular topic in the field of computer vision. For generating depth maps with better details, we present an efficacious monocular depth prediction framework with coordinate attention and feature fusion. Specifically, the proposed framework contains attention, multi-scale and feature fusion modules. The attention module improves features based on coordinate attention to enhance the predicted effect, whereas the multi-scale module integrates useful low- and high-level contextual features with higher resolution. Moreover, we developed a feature fusion module to combine the heterogeneous features to generate high-quality depth outputs. We also designed a hybrid loss function that measures prediction errors from the perspective of depth and scale-invariant gradients, which contribute to preserving rich details. We conducted the experiments on public RGBD datasets, and the evaluation results show that the proposed scheme can considerably enhance the accuracy of depth prediction, achieving 0.051 for log10 and 0.992 for δ<1.25³ on the NYUv2 dataset.

• Trans-
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• v.14
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• pp.65-92
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• 2023

The knowledge of the narrative agent not only constitutes the content and meaning of the narrative itself, but is also closely related to the emotional response of the recipient. Also, the disparity of knowledge between narrative agents is an important factor in making a narrative richer and more interesting. But It tends to be treated as a sub-topic of narration theory or genre/style studies rather than an independent subject of narrative studies or criticism. In this paper, I propose a model that can systematically and quantitatively analyze the knowledge of narrative agents. The proposed model consists of the knowledge structure that represents a narrative, the knowledge state that expresses the knowledge of narrative agent as a degree of belief, and the knowledge flow that means changes in the knowledge state according to the development of events. In addition, the formal notation of the knowledge structure and a probabilistic inference model that could obtain the state of knowledge were proposed, and the knowledge structure and knowledge flow were analyzed by applying the model to the actual narrative. It is expected that the proposed model will be of practical help in the creation and evaluation of narratives.

• International Journal of Advanced Culture Technology
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• v.12 no.1
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• pp.26-33
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• 2024

With the start of COVID-19 in 2020, the MBTI test became popular among Korean young generation and then developed into a nationwide hot topic. This paper aims to investigate the characteristics of the MBTI popularity in Korea and the public opinions toward this phenomenon. With the analysis of the reports contents, 231 news reports related to MBTI were selected from KINDS (Korea Integrated News Database System) as research samples. The general attitude of the media towards MBTI tests and the reasons for the formation of positive and negative evaluations will be discussed from three perspectives: media attention, media attitudes and cognitive sources. The research finds that the increasing interest in MBTI among the younger generation in Korea is driven by a post-epidemic desire for self-exploration, emotional planning, and online group affiliation. MBTI has gained quasi-scientific status, similar to horoscopes, influenced by celebrities and a substantial fan base in online communication. While widely used for entertainment and social currency, there are concerns that extensive labeling may unconsciously impact individuals' self-perception and hinder the development of a holistic and objective cognitive framework.

• The Journal of the Korea Contents Association
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• v.21 no.4
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• pp.50-59
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• 2021

To understand the research trends of English education in Korea for the last 20 years from 2000 to 2019, 12 major academic journals in Korea in the field of English education were selected, and bibliographic information of 7,329 articles published in these journals were collected and analyzed. The total number of articles increased from the 2000s to the first half of the 2010s, but decreased somewhat in the late 2010s and the number of publications by journal has become similar. These results show that the overall influence of English education journals has decreased and then leveled in terms of quantity. Next, 34 topics were extracted by applying latent Dirichlet allocation (LDA) topic modeling using the English abstract of the articles. Teacher, word, culture/media, and grammar appeared as topics that were highly studied. Topics such as word, vocabulary, and testing and evaluation appeared through unique keywords, and various topics related to learner factors emerged, becoming topics of interest in English education research. Then, topics were analyzed to determine which ones were rising or falling in frequency. As a result of this analysis, qualitative research, vocabulary, learner factor, and testing were found to be rising topics, while falling topics included CALL, language, teaching, and grammar. This change in research topics shows that research interests in the field of English education are shifting from static research topics to data-driven and dynamic research topics.