• Advances in nano research
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• v.7 no.3
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• pp.209-221
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• 2019

Graphene, with impressive electronic properties, have high potential in the microelectronic field. However, graphene itself is a zero bandgap material which is not suitable for digital logic gates and its application. Thus, much focus is on graphene nanoribbons (GNRs) that are narrow strips of graphene. During GNRs fabrication process, the occurrence of defects that ultimately change electronic properties of graphene is difficult to avoid. The modelling of GNRs with defects is crucial to study the non-idealities effects. In this work, nearest-neighbor tight-binding (TB) model for GNRs is presented with three main simplifying assumptions. They are utilization of basis function, Hamiltonian operator discretization and plane wave approximation. Two major edges of GNRs, armchair-edged GNRs (AGNRs) and zigzag-edged GNRs (ZGNRs) are explored. With single vacancy (SV) defects, the components within the Hamiltonian operator are transformed due to the disappearance of tight-binding energies around the missing carbon atoms in GNRs. The size of the lattices namely width and length are varied and studied. Non-equilibrium Green's function (NEGF) formalism is employed to obtain the electronics structure namely band structure and density of states (DOS) and all simulation is implemented in MATLAB. The band structure and DOS plot are then compared between pristine and defected GNRs under varying length and width of GNRs. It is revealed that there are clear distinctions between band structure, numerical DOS and Green's function DOS of pristine and defective GNRs.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.38 no.6
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• pp.645-653
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• 2020

Recently studies on how to use the UAV (Unmanned Aerial Vehicle) are actively being conducted, and the National Geographic Information Institute published the 『Work Guidelines for Public Surveying of Unmanned Aerial Vehicles』. However, the guidelines do not provide the optimum shooting conditions required for each application. In this study, we tried to find the suitable shooting conditions for the production of 3D (Three-dimensional) spatial information and orthophoto. To this end, 45 experiments were conducted by various altitudes, overlaps, and camera angles within an above ground level of 150m. For evaluating the 3D modeling by shooting conditions, point densities of 9 verification areas were analyzed, and to evaluate the orthophotos, 1/1,000 digital maps were compared. Considering the quality of the output and the processing time for precise 3D construction, an altitude of 50m, an overlap of 70~80%, and a camera angle of 80~90° are suitable as shooting conditions, and an altitude of 100m and camera angle of 80~90° are suitable for orthophoto generation.

• Journal of the Korea Society of Computer and Information
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• v.26 no.1
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• pp.171-178
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• 2021

In this paper, the author proposes a method for detecting modification of transmitted messages in C/C++ based Discrete Event System Specification (DEVS) simulation. When a message generated by a model instance is delivered to other model instances, it may be modified by some of the recipients. Such modifications may corrupt simulation results, which may lead to wrong decision making. In the proposed method, every model instance stores a copy of every transmitted message. Before the deletion of the transmitted message, the instance compares them. Once a modification has been detected, the method interrupt the current simulation run. The procedure is automatically performed by a simulator instance. Thus, the method does not require programmers to follow secure coding or to add specific codes in their models. The performance of the method is compared with a DEVS simulator.

• The Journal of Industrial Distribution & Business
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• v.12 no.4
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• pp.35-51
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• 2021

Purpose: As the digital environment has expanded opportunity for consumers to acquire information from social media and social network services(SNS), With this environment, influencer has not only promoted products, but also participated in distribution and influencing on their followers. Despite the increasing interest in influencers, there has not been enough research on the structure of fashion influencer, relationship of immersion and purchase intention. This study examined the effects of fashion influencers' characteristics to the immersion of relationship with followers and purchase intention. Research design, data and methodology: For data collection, a pilot survey and the final survey were conducted. The pilot survey data was conducted to 50 female SNS users following fashion influencers. Based on the pilot tests, questionnaire was revised and the final survey was conducted online from august 22 to September 1, 2019 to female SNS users who have followed fashion influencer. A total of 408 data were collected, and exploratory factor analysis, correlation analysis, and structural equational modeling techniques were employed for the data analyses using AMOS 26.0 and SPSS 26.0. Results: First, five factors were extracted for the fashion influencers' characteristics: interactivity, similarity, reliability, expertise and attractiveness. Second, fashion influences' reliability, expertise, similarity, interactivity have a positive (+) effects on relationship immersion; however, attractiveness has no effect on relationship immersion with followers and fashion influencer. It was also determined that relationship immersion had positive (+) influences on purchase intention. The relationship immersion has been found to have a partially mediated effect and similarity has complete mediated effects between interactivity, reliability, and expertise of fashion influencers and purchasing intentions. In terms of fashion opinion leadership, it was found to have a significant influence on purchase intention only for low fashion leadership groups. Conclusions: The present study found the structural relationships among the influencer characteristics, relationship immersion and purchase intentions to provide framework for succeeding research. This research revealed academic association of intention of purchasing through use of fashion social media and fashion influencer marketing. The results also showed the practical implications that fashion influencers' expertise and reliability perceived by their followers are key determinants to success in influencer marketing.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.25 no.3
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• pp.396-402
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• 2021

As the world is trying to establish smart city, unmanned vehicle control systems are being widely used. This paper writes about an unmanned parking control system that uses an adaptive background image modeling method, suggesting the method of updating the background image, modeled with an adaptive Gaussian mixture model, in both global and local way according to the moving object. Specifically, this paper focuses on suggesting two methods; a method of minimizing the influence of a moving object on a background image and a method of accurately updating the background image by quickly removing afterimages of moving objects within the area of interest to be monitored. In this paper, through the implementation of the unmanned vehicle control system, we proved that the proposed system can quickly and accurately distinguish both moving and static objects such as vehicles from the background image.

• Journal of Sensor Science and Technology
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• v.30 no.6
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• pp.388-394
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• 2021

The conventional microelectromechanical system (MEMS) process has been used to fabricate sensors with high costs and high-volume productions. Emerging 3D printing can utilize various materials and quickly fabricate a product using low-cost equipment rather than traditional manufacturing processes. 3D printing also can produce the sensor using various materials and design its sensing structure with freely optimized shapes. Hence, 3D printing is expected to be a new technology that can produce sensors on-site and respond to on-demand demand by combining it with open platform technology. Therefore, this paper reviews three standard 3D printing technologies, such as Fused Deposition Modeling (FDM), Direct Ink Writing (DIW), and Digital Light Processing (DLP), which can apply to the sensor fabrication process. The review focuses on strain/load sensors having both sensing material features and structural features as well. NCPC (Nano Carbon Piezoresistive Composite) is also introduced as a promising 3D material due to its favorable sensing characteristics.

• Smart Media Journal
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• v.11 no.8
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• pp.73-83
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• 2022

In order to support new construction engineering companies with weak information power to successfully advance into the overseas construction market, this study tried to analyze what are the keywords of interest in the overseas construction market and how they differ from Korea. For this purpose, we recently collected 2,473 news article titles and major articles targeting smart cities that are of high interest in Korea and Vietnam. Through network configuration and topic modeling, we examined the connection relationship between the word of interest and the word of interest. In addition, the influence of the word of interest in the network was measured using PageRank centrality. Through this analysis, it was found that there is a high interest in smart city-related construction, cities, and digital in both countries, and the difference in terms of interest between Korea and Vietnam was inferred. Finally, the limitations of this study and additional research directions to complement them are presented.

• Journal of Radiation Protection and Research
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• v.47 no.3
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• pp.111-133
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• 2022

The exciting advancement related to the "modeling of digital human" in terms of a computational phantom for radiation dose calculations has to do with the latest hype related to deep learning. The advent of deep learning or artificial intelligence (AI) technology involving convolutional neural networks has brought an unprecedented level of innovation to the field of organ segmentation. In addition, graphics processing units (GPUs) are utilized as boosters for both real-time Monte Carlo simulations and AI-based image segmentation applications. These advancements provide the feasibility of creating three-dimensional (3D) geometric details of the human anatomy from tomographic imaging and performing Monte Carlo radiation transport simulations using increasingly fast and inexpensive computers. This review first introduces the history of three types of computational human phantoms: stylized medical internal radiation dosimetry (MIRD) phantoms, voxelized tomographic phantoms, and boundary representation (BREP) deformable phantoms. Then, the development of a person-specific phantom is demonstrated by introducing AI-based organ autosegmentation technology. Next, a new development in GPU-based Monte Carlo radiation dose calculations is introduced. Examples of applying computational phantoms and a new Monte Carlo code named ARCHER (Accelerated Radiation-transport Computations in Heterogeneous EnviRonments) to problems in radiation protection, imaging, and radiotherapy are presented from research projects performed by students at the Rensselaer Polytechnic Institute (RPI) and University of Science and Technology of China (USTC). Finally, this review discusses challenges and future research opportunities. We found that, owing to the latest computer hardware and AI technology, computational human body models are moving closer to real human anatomy structures for accurate radiation dose calculations.

• Journal of KIBIM
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• v.12 no.4
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• pp.80-92
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• 2022

Recently, remote work has arisen due to the social atmosphere and advancement of digital technology. Although effective in premeditated communications such as conferences or meetings, the current technology such as messengers and video chats insufficiently supports impromptu communications like a chance encounter, daily conversation with colleagues, or brief instant meetings. This causes various problems such as a decrease in social belonging and an increase in social isolation. The virtual workplace, which emerged as an alternative to this technology, is merely replicating the workplace layouts in reality with an absence of the proper design guideline. Therefore, this paper aims to establish the foundation for the better design of the virtual workplace for remote-work employees. The research compared 12 current workplace cases with the analysis with 5 categories(Spatial Composition, Scale, Individual & Collaboration Workplace, Socializing Space), and discovered the following results: 1) some design principles of the real workplace can be applied on the virtual workplace design, 2) the architectural components of the virtual workplace can differ from them of the real. Based on the results, the research suggests both the appropriate design methodologies of the virtual workplace considering the design principles of the real office layouts, and the design direction for the future of the virtual workplace. This research will be the foundation for the future design of the virtual workplace.

• Journal of Sensor Science and Technology
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• v.31 no.5
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• pp.318-323
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• 2022

Barium titanate (BaTiO₃) is considered to be a beneficial ceramic material for multilayer ceramic capacitor (MLCC) applications because of its high dielectric constant and low dielectric loss. Numerous attempts have been made to improve the physical properties of BaTiO₃ in response to recent market trends by employing multicomponent alloying strategies. However, owing to its significant number of atomic combinations and unpredictable physical properties, finding a traditional experimental approach to develop multicomponent systems is difficult; the development of such systems is also time-consuming. In this study, 168 new structures were fabricated using special quasi-random structures (SQSs) of Ba_1-xCa_xTi_1-yZryO₃, and 1680 physical properties were extracted from first-principles calculations. In addition, we built an integrated database to manage the computational results, and will provide big data solutions by performing data analysis combined with AI modeling. We believe that our research will enable the global materials market to realize digital transformation through datalization and intelligence of the material development process.