• International Journal of Computer Science & Network Security
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• v.22 no.4
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• pp.183-192
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• 2022

The role that English currently plays is undeniable. It has become the most common means of communication among native speakers of several languages around the world. English penetrates into all areas of people's daily lives. In the field of Information Technology (IT), English has taken a dominant position, as many of the terms used on a daily basis are written in English. The purpose of the article is to analyze the linguistic features of anglicisms in the field of Information Technology. Methods. The research is based on systematic and comparative analysis, dialectical method, as well as methods of classification and generalization. Results. This study presents the results of compiling a multilingual glossary with anglicisms used in the GitHub and 3D Slicer fields. Despite the limited number of terms included in the glossary, the article provides a lot of evidence for the influence of the English language in the areas of Information Technology, GitHub and 3D Slicer under consideration. The types of anglicisms used in the 3D Slicer area seem to be more diverse than in the GitHub area. This study found that five European languages use language strategies to solve any communication problem. The multilingual glossary showed that in some cases there is a coexistence between Anglicism and the native term. In other cases, the English term is the only one used in different languages. There are cases when only the native language is used. Conclusions. This study is a useful tool that helps to improve the efficiency of communication between engineers and technicians who speak different native languages. The ultimate goal of this research will be to create a multilingual glossary that is still under development and is likely to cover other IT areas such as Python and VTK.

• Smart Structures and Systems
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• v.29 no.1
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• pp.181-193
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• 2022

Data-driven structural health monitoring (SHM) of civil infrastructure can be used to continuously assess the state of a structure, allowing preemptive safety measures to be carried out. Long-term monitoring of large-scale civil infrastructure often involves data-collection using a network of numerous sensors of various types. Malfunctioning sensors in the network are common, which can disrupt the condition assessment and even lead to false-negative indications of damage. The overwhelming size of the data collected renders manual approaches to ensure data quality intractable. The task of detecting and classifying an anomaly in the raw data is non-trivial. We propose an approach to automate this task, improving upon the previously developed technique of image-based pre-processing on one-dimensional (1D) data by enriching the features of the neural network input data with multiple channels. In particular, feature engineering is employed to convert the measured time histories into a 3-channel image comprised of (i) the time history, (ii) the spectrogram, and (iii) the probability density function representation of the signal. To demonstrate this approach, a CNN model is designed and trained on a dataset consisting of acceleration records of sensors installed on a long-span bridge, with the goal of fault detection and classification. The effect of imbalance in anomaly patterns observed is studied to better account for unseen test cases. The proposed framework achieves high overall accuracy and recall even when tested on an unseen dataset that is much larger than the samples used for training, offering a viable solution for implementation on full-scale structures where limited labeled-training data is available.

• Korean journal of aerospace and environmental medicine
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• v.30 no.3
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• pp.83-85
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• 2020

In commemoration of Vol. 30, Issue 3, our journal prepared five review articles and one original paper. The global outbreak of COVID-19 in 2020 has impacted our society, and especially the aviation and travel industries have been severely damaged. Kwon presented the aviation medical examination regulations related to COVID-19 announced by the Ministry of Land, Infrastructure, and Transport of the Republic of Korea. Lim summarized various efforts of airlines to overcome the crisis in the aviation industry. He also discussed the management of these aircraft as the number of airplanes landing for long periods increased. Finally, he suggested various quarantine guidelines at airports and onboard aircraft. COVID-19 has had a profound impact on mental health as well as physical effects. Kim investigated the impact of COVID-19 on mental health and suggested ways to manage the stress caused by it. The Internet of Things (IoT) refers to a technology in which devices communicate with each other through wired or wireless communication. Hyun explained the current state of the technology of the IoT and how it could be used, especially in the aviation field. In the area of airline service, various situations arise between passengers and crew. Therefore, role-playing is useful in performing education to prepare and respond to passengers' different needs appropriately. Ra introduced the conceptual background and general concepts of role-playing and presented the actual role-play's preparation process, implementation, evaluation, and feedback process. For a fighter to fly for a long time and perform a rapid air attack, air refueling is essential, which serves refueling from the air rather than from the aircraft base. Koo developed a questionnaire based on the HFACS (Human Factors Analysis and Classification System) model and used it to conduct a fighter pilot survey and analyze the results.

• International Journal of Computer Science & Network Security
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• v.22 no.9
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• pp.334-342
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• 2022

Nowadays, as we can notice on social media, most users choose to use more than one language in their online postings. Thus, social media analytics needs reviewing as code-switching analytics instead of traditional analytics. This paper aims to present evidence comparable to the accuracy of code-switching analytics techniques in analysing the mood state of social media users. We conducted a systematic literature review (SLR) to study the social media analytics that examined the effectiveness of code-switching analytics techniques. One primary question and three sub-questions have been raised for this purpose. The study investigates the computational models used to detect and measures emotional well-being. The study primarily focuses on online postings text, including the extended text analysis, analysing and predicting using past experiences, and classifying the mood upon analysis. We used thirty-two (32) papers for our evidence synthesis and identified four main task classifications that can be used potentially in code-switching analytics. The tasks include determining analytics algorithms, classification techniques, mood classes, and analytics flow. Results showed that CNN-BiLSTM was the machine learning algorithm that affected code-switching analytics accuracy the most with 83.21%. In addition, the analytics accuracy when using the code-mixing emotion corpus could enhance by about 20% compared to when performing with one language. Our meta-analyses showed that code-mixing emotion corpus was effective in improving the mood analytics accuracy level. This SLR result has pointed to two apparent gaps in the research field: i) lack of studies that focus on Malay-English code-mixing analytics and ii) lack of studies investigating various mood classes via the code-mixing approach.

• International Journal of Computer Science & Network Security
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• v.22 no.10
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• pp.165-170
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• 2022

Nowadays more and more attention is paid to digital technologies, digitization, and the digitization of public services in particular. Progressive countries aim to build "digital" governance and a digital economy. In this aspect, the international experience of using digitization in the field of public administration, including in local self-government bodies, plays an important role. Therefore, it is important to analyze the international legal experience of the functioning of local self-government in the conditions of digitization. The purpose of the work is to study the international legal experience of the functioning of local self-government in the conditions of digitization. The object of the study is local self-government in the conditions of digitization through the prism of international legal experience. The subject of the study is social relations that arise, change, and cease during the implementation of digitization in local self-government in Ukraine and foreign countries. The research methodology consists of such methods as the method of philosophical hermeneutics; dialectical method; classification method; comparative method; target method; method of documentary analysis; generalization method. Research results. As a result of the conducted research, the international experience of the functioning of local self-government in conditions of digitization was analyzed. In particular, the impact of digitization processes on the course of the decentralization reform in Ukraine is summarized. Also, from the analysis of international experience, a conclusion was made about the potential possibility of reducing the existing gap in the process of communication between the central government and united territorial communities thanks to the introduction of the latest technologies in the field of administrative services, to stimulate innovative and economic development of regions, attracting the attention of businesses and potential investors, as well as the functioning of more open local authorities with electronic communication tools.

• Journal of Korean Society of Rural Planning
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• v.28 no.3
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• pp.95-109
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• 2022

This study attempted to suggest the factors that facilities that aim to exchange urban-rural coexistence base spaces with urban-rural areas should have. In order to derive factors, 15 literatures preceded by similar studies were investigated, and systematic classification was attempted. Finally, the factors for activating urban and rural base facilities were organized into 3 categories, 9 sectors, and 30 activation factors. The three major categories consisted of resources and facilities, content and programs, operational status. As a result of the AHP survey, in the survey area, which is a categories, resources and facilities composed of hardware factors originally possessed by the facility showed the highest score of 48.9. In the sectors, the convenience of facility use was 25.7 points, and the rich state of tangible and intangible resources was 13.3 points in order. In the sectors, income from paid experience programs at facilities was 8.3 points, physical accessibility to facilities was 8.2 points, and the type of areas where the facilities were located was 7.7 points in order. It showed high importance in the order of resources and facilities composed of hardware factors, content and programs composed of software factors, and manpower and operation composed of humanware factors. In general, it was shown that the physical factors of the place when using urban and rural base facilities were judged as the main factors.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.17 no.2
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• pp.520-541
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• 2023

In CRNs, SS is of utmost significance. Every CR user generates a sensing report during the training phase beneath various circumstances, and depending on a collective process, either communicates or remains silent. In the training stage, the fusion centre combines the local judgments made by CR users by a majority vote, and then returns a final conclusion to every CR user. Enough data regarding the environment, including the activity of PU and every CR's response to that activity, is acquired and sensing classes are created during the training stage. Every CR user compares their most recent sensing report to the previous sensing classes during the classification stage, and distance vectors are generated. The posterior probability of every sensing class is derived on the basis of quantitative data, and the sensing report is then classified as either signifying the presence or absence of PU. The ISVM technique is utilized to compute the quantitative variables necessary to compute the posterior probability. Here, the iterations of SVM are tuned by novel GO-PSA by combining GOA and PSO. Novel GO-PSA is developed since it overcomes the problem of computational complexity, returns minimum error, and also saves time when compared with various state-of-the-art algorithms. The dependability of every CR user is taken into consideration as these local choices are then integrated at the fusion centre utilizing an innovative decision combination technique. Depending on the collective choice, the CR users will then communicate or remain silent.

• Nuclear Engineering and Technology
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• v.54 no.12
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• pp.4809-4818
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• 2022

The decommissioning project of a nuclear facility is a large-scale process that is expected to take about 15 years or longer. The range of risks to be considered is large and complex, then, it is expected that various risks will arise in decision-making by area during the project. Therefore, in this study, the risk family derived from the Decommissioning Risk Management (DRiMa) project was reconstructed into a decommissioning project risk profile suitable for the Kori Unit 1. Two criteria of uncertainty and importance are considered in order to prioritize the selected 26 risks of decommissioning project. The uncertainty is scored according to the relevant laws and decommissioning plan preparation guidelines, and the project importance is scored according to the degree to which it primarily affects the triple constraints of the project. The results of risks are divided into high, medium, and low. Among them, 10 risks are identified as medium level and 16 risks are identified as low level. 10 risks, which are medium levels, are classified in five categories: End state of decommissioning project, Management of waste and materials, Decommissioning strategy and technology, Legal and regulatory framework, and Safety. This study is a preliminary assessment of the risk of the decommissioning project that could be considered in the preparation stage. Therefore, we expect that the project risks considered in this study can be used as an initial data for reevaluation by reflecting the detail project progress in future studies.

• Animal Bioscience
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• v.36 no.10
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• pp.1465-1487
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• 2023

The purpose of this study was to investigate the recent development of meat analog, industrialization, and the related legal changes worldwide. Summarizing the current status of the industrialization of meat analog, studies on plant-based meat, mycoprotein, and edible insects were mainly conducted to investigate their sensory properties (texture, taste, flavor, and color resembling meat), nutritional and safety evaluations, acquisition method of meat alternatives, and commercialization. Cultured meat is mainly studied for developing muscle satellite cell acquisition and support techniques or materials for the formation of structures. However, these technologies have not reached the level for active industrialization. Even though there are differences in the food categories and labeling between countries, it is common to cause confusion or to relay false information to consumers; therefore, it is important to provide accurate information. In this study, there were some differences in the food classification and food definition (labeling) contents for each country and state depending on the product shape or form, raw materials, and ingredients. Therefore, this study can provide information about the current research available on meat alternatives, improve regulation, and clarify laws related to the meat analog industry, which can potentially grow alongside the livestock industry.

• International conference on construction engineering and project management
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• 2022.06a
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• pp.792-799
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• 2022

Building Information Modeling (BIM) technology is a key component of modern construction engineering and project management workflows. As-is BIM models that represent the spatial reality of a project site can offer crucial information to stakeholders for construction progress monitoring, error checking, and building maintenance purposes. Geometric methods for automatically converting raw scan data into BIM models (Scan-to-BIM) often fail to make use of higher-level semantic information in the data. Whereas, semantic segmentation methods only output labels at the point level without creating object level models that is necessary for BIM. To address these issues, this research proposes a hybrid semantic-geometric approach for clutter-resistant floorplan generation from laser-scanned building point clouds. The input point clouds are first pre-processed by normalizing the coordinate system and removing outliers. Then, a semantic segmentation network based on PointNet++ is used to label each point as ceiling, floor, wall, door, stair, and clutter. The clutter points are removed whereas the wall, door, and stair points are used for 2D floorplan generation. A region-growing segmentation algorithm paired with geometric reasoning rules is applied to group the points together into individual building elements. Finally, a 2-fold Random Sample Consensus (RANSAC) algorithm is applied to parameterize the building elements into 2D lines which are used to create the output floorplan. The proposed method is evaluated using the metrics of precision, recall, Intersection-over-Union (IOU), Betti error, and warping error.