• Journal of the Korean Institute of Electrical and Electronic Material Engineers
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• v.35 no.1
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• pp.93-97
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• 2022

We report highly efficient quantum dot light-emitting diodes (QLEDs) with TiO₂ nanoparticles (NPs) as an alternative electron transport layer (ETL) and poly (methyl methacrylate) (PMMA) as an insulating layer. TiO₂ NPs were applied as ETLs of inverted structured QLEDs and the effect of the addition of PMMA between ETL and emission layer (EML) on device characteristics was studied in detail. A thin PMMA layer supported to make the charge balance in the EML of QLEDs due to its insulating property, which limits electron injection effectively. Green QLEDs with a PMMA layer produced the maximum luminance of 112,488 cd/m² and a current efficiency of 25.92 cd/A. We expect the extended application of TiO₂ NPs as the electron transport layer in inverted structured QLEDs device in the near future.

• Genomics & Informatics
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• v.20 no.3
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• pp.34.1-34.11
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• 2022

Multilevel analysis is an appropriate and powerful tool for analyzing hierarchical structure data widely applied from public health to genomic data. In practice, however, we may lose the information on multiple nesting levels in the multilevel analysis since data may fail to capture all levels of hierarchy, or the top or intermediate levels of hierarchy are ignored in the analysis. In this study, we consider a multilevel linear mixed effect model (LMM) with single imputation that can involve all data hierarchy levels in the presence of missing top or intermediate-level clusters. We evaluate and compare the performance of a multilevel LMM with single imputation with other models ignoring the data hierarchy or missing intermediate-level clusters. To this end, we applied a multilevel LMM with single imputation and other models to hierarchically structured cohort data with some intermediate levels missing and to simulated data with various cluster sizes and missing rates of intermediate-level clusters. A thorough simulation study demonstrated that an LMM with single imputation estimates fixed coefficients and variance components of a multilevel model more accurately than other models ignoring data hierarchy or missing clusters in terms of mean squared error and coverage probability. In particular, when models ignoring data hierarchy or missing clusters were applied, the variance components of random effects were overestimated. We observed similar results from the analysis of hierarchically structured cohort data.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.16 no.11
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• pp.3507-3522
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• 2022

Model pruning methods have attracted huge attention owing to the increasing demand of deploying models on low-resource devices recently. Most existing methods use the weight norm of filters to represent their importance, and discard the ones with small value directly to achieve the pruning target, which ignores the contribution of the small norm filters. This is not only results in filter contribution waste, but also gives comparable performance to training with the random initialized weights [1]. In this paper, we point out that the small norm filters can harm the performance of the pruned model greatly, if they are discarded directly. Therefore, we propose a novel filter contribution recycle (FCR) method for structured model pruning to resolve the fore-mentioned problem. FCR collects and reassembles contribution from the small norm filters to obtain a mixed contribution collector, and then assigns the reassembled contribution to other filters with higher probability to be preserved. To achieve the target FLOPs, FCR also adopts a weight decay strategy for the small norm filters. To explore the effectiveness of our approach, extensive experiments are conducted on ImageNet2012 and CIFAR-10 datasets, and superior results are reported when comparing with other methods under the same or even more FLOPs reduction. In addition, our method is flexible to be combined with other different pruning criterions.

• Journal of Information Technology Services
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• v.22 no.4
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• pp.123-140
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• 2023

In recent times, the global economy has been subject to increasing volatility, which has made it considerably more difficult to accurately predict economic indicators compared to previous periods. In response to this challenge, the present study conducts an exploratory investigation that aims to predict the Business Survey Index (BSI) by leveraging data mining techniques on both structured and unstructured data sources. For the structured data, we have collected information regarding foreign, domestic, and industrial conditions, while the unstructured data consists of content extracted from newspaper articles. By employing an extensive set of 44 distinct data mining techniques, our research strives to enhance the BSI prediction accuracy and provide valuable insights. The results of our analysis demonstrate that the highest predictive power was attained when using data exclusively from the t-1 period. Interestingly, this suggests that previous timeframes play a vital role in forecasting the BSI effectively. The findings of this study hold significant implications for economic decision-makers, as they will not only facilitate better-informed decisions but also serve as a robust foundation for predicting a wide range of other economic indicators. By improving the prediction of crucial economic metrics, this study ultimately aims to contribute to the overall efficacy of economic policy-making and decision processes.

• Journal of Information Science Theory and Practice
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• v.11 no.3
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• pp.1-15
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• 2023

The present study examines the impact of value co-creation on satisfaction and intention to adopt of e-resources among users. Four components of the DART model have been adopted to describe value co-creation. These components are dialogue, access, risk-assessment, and transparency. Ph.D. scholars and faculty members from National Capital Region, India, were requested to respond on a five-point Likert scale. A total of 220 responses were collected with the help of a structured questionnaire from respondents of the top 50 business schools according to National Institute Ranking Framework. These responses have been analysed by means of structured equation modelling on Adanco 2.2 software. Findings of the study reported the insignificant impact of access and risk-assessment, and positive impact of dialogue and transparency on satisfaction. Further, satisfaction has been identified, creating significant impact on adoption of e-resources. Such findings reflect the real picture of customer experience with respect to their role in co-creation of e-resources. Respondents have conveyed their dissatisfaction with the co-creation process of e-resources, as companies do not provide all the information and access to their customers beforehand. Consequently, customers fail to make informed decisions and also find themselves unable to show trust in the service providers of e-resources.

• Journal of Korea Multimedia Society
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• v.6 no.4
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• pp.685-697
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• 2003

The Web based multimedia programmes/courses are becoming widely available in recent years. Most of these courses focus on Behaviorist way of learning, which does not promote deep learning in any way. For Adults this approach further incapacitated, as it does not satisfy Andragogical needs. The search for Constructivist way of learning through the web applied to Indian conditions led to need for developing a curriculum development approach that would promote construction of knowledge through web based collaboration. This paper attempts to reengineer existing curriculum development processes and lays out a framework of‘Problem Based Online Learning (PBOL)’curriculum design. In this context, entire curriculum development life cycle is evolved and explained. This is a part of doctoral work (Ph.D), which is in progress and being undertaken by K.James Mathai, and guided of Dr.D.S.Karaulia.

• Journal of the Korean Society for Precision Engineering
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• v.14 no.12
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• pp.17-23
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• 1997

A 3-D vision system is developed to evaluate blanks' line up and monitor gap and thickness difference between blanks in tailored blank welding system. A structured lighting method is used for 3-D vision recognition. Images of sheared portion in blanks are irregular according to roughness of blank surface, shape of sheared geometry and blurring. It is difficult to get accurate and reliable informations in the case of using binary image processing or contour detection techniques in real time for such images. We propoe a new energy integration method robust to blurring and changes of illumination. The method is computationally simple, and uses feature restoration concept, different to another digital image restoration methods which aim image itself restoration and may be used in conventional applications using structured line lighting technique. Experimental results show this system measuring repeatability is .+-. pixel for gap and thickness difference in static and dynamic tests. The data are expected to be useful for preview gap control.

• International conference on construction engineering and project management
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• 2022.06a
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• pp.649-657
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• 2022

The COVID-19 pandemic has unprecedented impacts on different sectors around the globe. The effects observed in developing countries are even more severe. Some projects stopped while many have cost and time overrun issues. This paper conducted a case study on the COVID-19's effects on a hotel construction project in Nepal. The study reviewed the literature on COVID-19 and its impact on construction sectors and conducted a semi-structured interview with the project's personnel. The interview response was analysed and the contributing factors that impacted the project and its performance were identified. The paper found financial, operational, contractual, safety, and risk management issues in the hotel project. Overall, the project cost increased by 32% where the material cost increased by 35% and labor cost increased by 28%. This research discusses causes, measures, and provides a broad perspective of the problems, significant challenges, and opportunities associated with the effects of COVID-19 on the construction industry. The Owner as well as the Contractors incurred added costs because of COVID-19. The paper identified contributing factors and presented the challenges which could be used as opportunities to minimize unforeseen impacts of the pandemics in near future. The lesson learned from this case study was that the labor cost and materials cost could have been minimized if the Owner and the Contractor had established alternative resources such as using locally available labor, materials, and alternative suppliers.

• The Korean Journal of Emergency Medical Services
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• v.27 no.3
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• pp.101-111
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• 2023

Purpose: This study attempted to identify how academic self-efficacy, grit, and learned helplessness influence Academic delay behavior in college students and provide a foundation for reducing Academic delay behavior in college students. Methods: Data was collected from October 12, 2023 to October 30, 2023 using a structured questionnaire from 170 college students at a university in City D. The data was collected using a structured questionnaire. Results: Academic delay behaviors were significantly negatively correlated with academic self-efficacy (r=-.371, p<.001) and grit (r=-.562, p=.012), and significantly positively correlated with learned helplessness (r=.341, p<.001). Conclusion: Finally, In order to reduce academic delay behaviors among college students, it is necessary to actively utilize educational environments that promote academic achievement and grit, academic-related counseling programs, and learning environments that do not suffer from academic helplessness.

• Journal of Distribution Science
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• v.22 no.1
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• pp.25-36
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• 2024

Purpose: The study attempts to explore the operational performance of the existing Malaysian logistics companies and the extent of their adoption of digitalization. The role of digitalization in enhancing the performance of companies in the logistics industry in Malaysia, for value creation, is the topic of study. Research design, data and methodology: A qualitative research method with a semi-structured interview approach was applied and judgmental sampling was used as the sampling technique to collect data. The research has chosen nine companies in the logistics industry in Peninsular Malaysia, with the interviews aimed at eleven members of top and middle-level management. Data analysis was performed using logical system techniques to examine and evaluate data, reorganizing feedback, comparing it with literature, and transforming it into structured, valuable information after interviews. Results: The study revealed mixed opinions on digitalization in logistics, despite its potential benefits such as improved operational efficiency, real-time information, and customer service. However, high costs may hinder financial performance and require revisions due to stakeholder involvement. Conclusions: The Malaysian logistics industry's adoption of digitalization is gaining traction, with most companies satisfied with their status. However, challenges like cost and inefficiency persist, prompting calls for government support to improve efficiency and reduce costs while ensuring sustainable transportation.