• Current Photovoltaic Research
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• v.10 no.2
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• pp.49-55
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• 2022

With rapid growth in light-harvesting efficiency from 3.8 to 25.8%, organic-inorganic hybrid perovskite solar cells (PSCs) have attracted great attention as promising photovoltaic devices. However, despite of their outstanding performance, the commercialization of PSCs has been suffered from severe stability issues, especially for UV and humidity: (i) UV irradiation towards PSCs is able to lead UV-induced decomposition of perovskite films or catalytic reactions of charge-transporting layers, and (ii) exposure to surrounding humidity causes irreversible hydration of perovskite layers by the penetration of water molecules, resulting considerable decrease in their power-conversion efficiency (PCE). This review investigates current status of strategies to enhance UV and humidity stability of PSCs in terms of UV-management and moisture protection, respectively. Furthermore, the multifunctional approach to increase long-term stability as well as performance is discussed as advanced research directions for the commercialization of PSCs.

• Tribology and Lubricants
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• v.37 no.6
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• pp.208-212
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• 2021

Chemical mechanical polishing (CMP) is a key technology used for the global planarization of thin films in semiconductor production and smoothing the surface of substrate materials. CMP is a type of hybrid process using a material removal mechanism that forms a chemically reacted layer on the surface of a material owing to chemical elements included in a slurry and mechanically removes the chemically reacted layer using abrasive particles. Sapphire is known as a material that requires considerable time to remove materials through CMP owing to its high hardness and chemical stability. This study introduces a technology using electrolytic ionization and ultraviolet (UV) light in sapphire CMP and compares it with the existing CMP method from the perspective of the material removal rate (MRR). The technology proposed in the study experimentally confirms that the MRR of sapphire CMP can be increased by approximately 29.9, which is judged as a result of the generation of hydroxyl radicals (·OH) in the slurry. In the future, studies from various perspectives, such as the material removal mechanism and surface chemical reaction analysis of CMP technology using electrolytic ionization and UV, are required, and a tribological approach is also required to understand the mechanical removal of chemically reacted layers.

• Korean Journal of Clinical Pharmacy
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• v.32 no.4
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• pp.281-287
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• 2022

Pharmacists should maintain professional competencies to provide optimal pharmaceutical care services to patients, which can be achieved through continued commitment to lifelong learning. Traditionally continuing education (CE) has been widely used as a way of lifelong learning for many healthcare professionals. It, however, has several limitations. CE is delivered in the form of instructor-led education focused on multiple learners. Learning is passive and reactive for participants, so it sometimes does not lead to bringing behavioral changes in workplace performance. Therefore, recently the concept of lifelong learning tends to move from CE toward continuing professional development (CPD). CPD is an ongoing process that improves knowledge, skills, and competencies throughout a professional's career. It is a more comprehensive structured approach toward the enhancement of personal competencies. It emphasizes an individual's learning needs and goals and enables learning to become proactive, conscious, and self-directed. CPD consists of four stages: reflect, plan, learn, and evaluate. CE is one component of CPD. Each stage is recorded in a CPD portfolio. There are many practical difficulties in implementing the complete CPD system for lifelong learning of pharmacists in many countries including Korea. Applying a hybrid form that utilizes CPD and CE together, as in the case of some countries, could be an alternative. Furthermore, in undergraduate pharmacy education, it is necessary to teach students about CPD and train them on how to perform CPD as a pharmacist.

• Transactions of Materials Processing
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• v.32 no.3
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• pp.122-128
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• 2023

As electric vehicles (EV) have increasingly replaced the conventional vehicles with internal combustion engines (ICE), most of automotive makers are actively devoting to the technology development of EV parts. Accordingly, the manufacturing process for power source has been also shifting from engine/transmission to EV motor/reducer system. However, lack of experience in developing the EV motor still remains as a technical challenge. In this paper, we employed the forming simulation based on finite element modeling to solve this problem. In particular, in order to increase the accuracy of the forming simulation, we introduced the elastic-plastic constitutive model parameters for polymer-copper hybrid wire by investigating the individual strain-stress curves, and elastic modulus of polymer and copper. Then, the reliability of modeling procedure was confirmed by comparing the simulated results with experiments. Finally, the identified mechanical properties and finite element modeling were applied to a hairpin forming process, which involves multiple deformation paths such as bending, pressing, widening, and twisting. The proposed numerical approach can replace common experience or experiment based trials by reducing production time and cost in the future.

• The Research Journal of the Costume Culture
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• v.31 no.4
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• pp.467-488
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• 2023

The purpose of this study is to determine the concepts of heterotopic image and fashion space, and the characteristics of fashion space and images from the perspective of fashion brands and users. This study examines the evolution of fashion space and consumers with it, based on Foucault's theory of heterotopia, which refers to spaces that blend contradictory features not typically found within a single physical structure. This is accomplished by employing a single case study of Ader Error's Ader Space, a Seoul-based brand known for its unique approach to presenting and communicating fashion. Based on an analysis of Instagram posts of Ader Error along with the hashtag searches "aderspace" and "adererror", this study categorizes heterotopia from the perspective of fashion brands into three properties: fashion space as a medium for selling fashion products; fashion space as getaway to hybrid fashion practices; and fashion space as an illusionary place to experience fashion. From the user perspective, the heterotopic image of Ader Space portrayed on Instagram is characterized by the image of fashion products in an extraordinary fashion space, the image of a fashion space beyond space and time, and the image of exposing the hidden and the illusion-compensation of fashion space. This study contributes to a heightened understanding of the evolutionary concept of the fashion space.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.17 no.8
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• pp.1996-2015
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• 2023

High-definition (HD) maps can provide precise road information that enables an autonomous driving system to effectively navigate a vehicle. Recent research has focused on leveraging semantic segmentation to achieve automatic annotation of HD maps. However, the existing methods suffer from low recognition accuracy in automatic driving scenarios, leading to inefficient annotation processes. In this paper, we propose a novel semantic segmentation method for automatic HD map annotation. Our approach introduces a new encoder, known as the convolutional transformer hybrid encoder, to enhance the model's feature extraction capabilities. Additionally, we propose a multi-level fusion module that enables the model to aggregate different levels of detail and semantic information. Furthermore, we present a novel decoupled boundary joint decoder to improve the model's ability to handle the boundary between categories. To evaluate our method, we conducted experiments using the Bird's Eye View point cloud images dataset and Cityscapes dataset. Comparative analysis against stateof-the-art methods demonstrates that our model achieves the highest performance. Specifically, our model achieves an mIoU of 56.26%, surpassing the results of SegFormer with an mIoU of 1.47%. This innovative promises to significantly enhance the efficiency of HD map automatic annotation.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.17 no.4
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• pp.1276-1295
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• 2023

Sensor networks are now an essential aspect of wireless communication, especially with the introduction of new gadgets and protocols. Their ability to be deployed anywhere, especially where human presence is undesirable, makes them perfect choices for remote observation and control. Despite their vast range of applications from home to hostile territory monitoring, limited battery power remains a limiting factor in their efficacy. To analyze and transmit data, it requires intelligent use of available battery power. Several studies have established effective routing algorithms based on clustering. However, choosing optimal cluster heads and similarity measures for clustering significantly increases computing time and cost. This work proposes and implements a simple two-phase technique of route creation and maintenance to ensure route reliability by employing nature-inspired ant colony optimization followed by the fuzzy decision engine (FDE). Benchmark methods such as PSO, ACO and GWO are compared with the proposed HRCM's performance. The objective has been focused towards establishing the superiority of proposed work amongst existing optimization methods in a standalone configuration. An average of 15% improvement in energy consumption followed by 12% improvement in latency reduction is observed in proposed hybrid model over standalone optimization methods.

• International Journal of Computer Science & Network Security
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• v.23 no.5
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• pp.53-64
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• 2023

Early detection of endometrial carcinoma in uterus is essential for effective treatment. Endometrial carcinoma is the worst kind of endometrium cancer among the others since it is considerably more likely to affect the additional parts of the body if not detected and treated early. Non-invasive medical computer vision, also known as medical image processing, is becoming increasingly essential in the clinical diagnosis of various diseases. Such techniques provide a tool for automatic image processing, allowing for an accurate and timely assessment of the lesion. One of the most difficult aspects of developing an effective automatic categorization system is the absence of huge datasets. Using image processing and deep learning, this article presented an artificial endometrium cancer diagnosis system. The processes in this study include gathering a dermoscopy images from the database, preprocessing, segmentation using hybrid Fuzzy C-Means (FCM) and optimizing the weights using the Whale Optimization Algorithm (WOA). The characteristics of the damaged endometrium cells are retrieved using the feature extraction approach after the Magnetic Resonance pictures have been segmented. The collected characteristics are classified using a deep learning-based methodology called Long Short-Term Memory (LSTM) and Bi-directional LSTM classifiers. After using the publicly accessible data set, suggested classifiers obtain an accuracy of 97% and segmentation accuracy of 93%.

• The Journal of Economics, Marketing and Management
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• v.12 no.1
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• pp.17-28
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• 2024

Purpose: This paper is designed to deliver a deeper understanding of the implications of digitalization strategies in the tourism industry, exploring the opportunities and challenges in South Korea. Research design, data and methodology: To identify effective strategies, an integrated approach is employed in the research that encompasses the Glocal RPM analysis and SANEL HERMES model, as well as the examination of digital tourism factors within the DIANA economy. The data used for this study were derived from multiple sources, including literature review, participation interview, tourist survey and expert questionnaire. By conducting a tourist survey using questionnaires in this research, Glocal RPM and SANEL HERMES hybrid method is used identifying and classifying influencing factors limiting digitalization in tourism. As a final step, experts use a Quantitative Strategic Planning Matrix to propose, assess, and rank a number of digitalization strategies. Results: According to the analysis, the study revealed that combining both tools contributes to a more holistic understanding of the environment, uncovering the positives and negatives from diverse perspectives. The average satisfaction percentage of experts was determined to be 38%, indicating anatal level of digitalization for tourism industry in South Korea. Conclusions: These results can serve as a valuable guide for policymakers and stakeholders in formulating targeted strategies to enhance glocalization, rationality, professionalism, and morality within the digitalization context.

• Smart Structures and Systems
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• v.32 no.3
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• pp.179-193
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• 2023

This study explores an alternative to the existing centralized process for data anomaly detection in modern Internet of Things (IoT)-based structural health monitoring (SHM) systems. An edge intelligence framework is proposed for the early detection and classification of various data anomalies facilitating quality enhancement of acquired data before transmitting to a central system. State-of-the-art deep neural network pruning techniques are investigated and compared aiming to significantly reduce the network size so that it can run efficiently on resource-constrained edge devices such as wireless smart sensors. Further, depthwise separable convolution (DSC) is invoked, the integration of which with advanced structural pruning methods exhibited superior compression capability. Last but not least, quantization-aware training (QAT) is adopted for faster processing and lower memory and power consumption. The proposed edge intelligence framework will eventually lead to reduced network overload and latency. This will enable intelligent self-adaptation strategies to be employed to timely deal with a faulty sensor, minimizing the wasteful use of power, memory, and other resources in wireless smart sensors, increasing efficiency, and reducing maintenance costs for modern smart SHM systems. This study presents a theoretical foundation for the proposed framework, the validation of which through actual field trials is a scope for future work.