• Wind and Structures
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• v.28 no.2
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• pp.129-140
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• 2019

Accurately simulating the wind field of large-scale region, for instant urban areas, the locations of large span bridges, wind farms and so on, is very difficult, due to the complicated terrains or land surfaces. Currently, the regional wind field can be simulated through the combination of observation data and numerical model using observation-nudging in the Weather Research and Forecasting model (WRF). However, the main drawback of original observation-nudging method in WRF is the effects of observation on the surrounding field is fully mathematical express in terms of temporal and spatial, and it ignores the effects of terrain, wind direction and atmospheric circulation, while these are physically unreasonable for the turbulence. For these reasons, a spatial correlation-based observation-nudging method, which can take account the influence of complicated terrain, is proposed in the paper. The validation and comparation results show that proposed method can obtain more reasonable and accurate result than original observation-nudging method. Finally, the discussion of wind field along bridge span obtained from the simulation with spatial correlation-based observation-nudging method was carried out.

• Advances in Computational Design
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• v.4 no.2
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• pp.155-177
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• 2019

Operation and Maintenance (O&M) phase is the main contributor to the total lifecycle cost of a building. Previous studies have described that Building Information Models (BIM), if available with detailed asset information and their properties, can enable rapid troubleshooting and execution of O&M tasks by providing the required information of the facility. Despite the potential benefits, there is still rarely BIM with Mechanical, Electrical and Plumbing (MEP) assets and properties that are available for O&M. BIM is usually not in possession for existing buildings and generating BIM manually is a time-consuming process. Hence, there is a need for an automated approach that can reconstruct the MEP systems in BIM. Previous studies investigated automatic reconstruction of BIM using architectural drawings, structural drawings, or the combination with photos. But most of the previous studies are limited to reconstruct the architectural and structural components. Note that mechanical components in the building typically require more frequent maintenance than architectural or structural components. However, the building mechanical drawings are relatively more complex due to various type of symbols that are used to represent the mechanical systems. In order to address this challenge, this paper proposed a symbol recognition framework that can automatically recognize the different type of symbols in the building mechanical drawings. This study applied vector-based computer vision techniques to recognize the symbols and their properties (e.g., location, type, etc.) in two vector-based input documents: 2D drawings and the symbol description document. The framework not only enables recognizing and locating the mechanical component of interest for BIM reconstruction purpose but opens the possibility of merging the updated information into the current BIM in the future reducing the time of repeated manual creation of BIM after every renovation project.

• 한국사회정책
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• v.25 no.4
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• pp.39-67
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• 2018

The Korean welfare state has achieved remarkable development during the last two decades, but simultaneously we have witnessed growing prevalent social conflicts and exclusion in the society. This research argues that the source of current problems lies in the nature of the Korean welfare regime, so called, 'paternalistic liberalism'. The paternalistic liberalism has been formulated by the combination of legacies of the developmental state and neo-liberalism. Paternalism with the growth-oriented and employment-centered approach has been a significant factor to restrict individuals' freedom and happiness in the Korean welfare state. It has also been embedded in the Korean welfare state such as social insurance, workfare programs, and centralized social services. In this context, this research proposes social liberalism, pursuing real freedom for all, as a new paradigm for the Korean welfare state. Breaking from the old path, Freecurity, combining freedom and security, which is argued to be the upgraded version of flexicurity, is also newly proposed as the operating model of social liberalism.

• IEMEK Journal of Embedded Systems and Applications
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• v.14 no.5
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• pp.277-286
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• 2019

In this paper, we propose an efficient hyperplane generation technique to classify human activity from combination of events and sequence information obtained from multiple-event sensors. By generating hyperplane efficiently, our machine learning algorithm classify with less memory and run time than the LSVM (Linear Support Vector Machine) for embedded system. Because the fact that light weight and high speed algorithm is one of the most critical issue in the IoT, the study can be applied to smart home to predict human activity and provide related services. Our approach is based on reducing numbers of hyperplanes and utilizing robust string comparing algorithm. The proposed method results in reduction of memory consumption compared to the conventional ML (Machine Learning) algorithms; 252 times to LSVM and 34,033 times to LSTM (Long Short-Term Memory), although accuracy is decreased slightly. Thus our method showed outstanding performance on accuracy per hyperplane; 240 times to LSVM and 30,520 times to LSTM. The binarized image is then divided into groups, where each groups are converted to binary number, in order to reduce the number of comparison done in runtime process. The binary numbers are then converted to string. The test data is evaluated by converting to string and measuring similarity between hyperplanes using Levenshtein algorithm, which is a robust dynamic string comparing algorithm. This technique reduces runtime and enables the proposed algorithm to become 27% faster than LSVM, and 90% faster than LSTM.

• Tuberculosis and Respiratory Diseases
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• v.82 no.4
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• pp.277-284
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• 2019

Idiopathic nonspecific interstitial pneumonia (NSIP) is one of the varieties of idiopathic interstitial pneumonias. Diagnosis of idiopathic NSIP can be done via multidisciplinary approach in which the clinical, radiologic, and pathologic findings were discussed together and exclude other causes. Clinical manifestations include subacute or chronic dyspnea and cough that last an average of 6 months, most of which occur in non-smoking, middle-aged women. The common findings in thoracic high-resolution computed tomography in NSIP are bilateral reticular opacities, traction bronchiectasis, reduced volume of the lobes, and ground-glass opacity in the lower lungs. These lesions can involve diffuse bilateral lungs or subpleural area. Unlike usual interstitial pneumonia, honeycombing is sparse or absent. Pathology shows diffuse interstitial inflammation and fibrosis which are temporally homogeneous, namely NSIP pattern. Idiopathic NSIP is usually treated with steroid only or combination with immunosuppressive agents such as azathioprine, cyclophosphamide, cyclosporine, and mycophenolate mofetil. Prognosis of idiopathic NSIP is better than idiopathic pulmonary fibrosis. Many studies have reported a 5-year survival rate of more than 70%.

• Herbal Formula Science
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• v.27 no.1
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• pp.45-52
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• 2019

Objectives : Hyperthermia is a widely used therapeutic tool for cancer therapy and a well-known inducer of apoptosis. Although the Cinnamomi cortex (CC) is a potent anticancer agent for several human carcinomas, it is less potent in the human U937 cell line. To explore any enhancing effects of CC with hyperthermia induced apoptosis, this study investigated the combined effects and apoptotic mechanisms of hyperthermia and CC in U937 cells. Methods : U937 cells were heat treated at $43^{\circ}C$ for 30 min with or without pre-treatment for 1h with CC and then incubated at $37^{\circ}C$ with 5% $CO_2$. Cell viability was analyzed by MTT assay and Trypan blue assay. Morphological changes reflecting apoptosis were visualized under microscope. Synergy effect of CC combined with hyperthermia were calculated by Compusyn software. The expression of proteins related to apoptosis and signaling pathways was determined by western blotting. Results : Hyperthermia with CC reduced cell viability and induced apoptosis. Combined hyperthermia and CC treatment markedly augmented apoptosis by upregulating proapoptotic proteins and suppressing antiapoptotic proteins, culminating in caspase-3 activation. Furthermore, the combined treatment, decreased the expression of in Bcl-2 family, cyclin D1, VEGF, MMP2 and MMP9 expression. Conclusion : This study provides compelling evidence that hyperthermia, in combination with CC, is a promising therapeutic strategy for enhancement of apoptosis and suggests a promising therapeutic approach for cancer.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.19 no.2
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• pp.243-253
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• 2019

First steps of Planetary exploration are usually conducted with the use of autonomous rovers. These rovers are capable of finding its own path and perform experiments about the planet's surface. This paper makes a proposal for a multi-agent system which effectively take the advantage of a blackboard system for share knowledge and effort of each agent. Agents use Reactive Model with the combination of Belief Desire Intension (BDI) Model and also use a Path Finding Algorithm for calculate shortest distance and a path for travel on the planet's surface. This approach can perform a surface exploration on a given terrain within a short period of time. Information which are gathered on the blackboard are used to make an output with detailed surface soil variance results. The developed Multi-Agent system performed well with different terrain sizes.

• The Journal of Information Systems
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• v.30 no.1
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• pp.65-84
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• 2021

Purpose Based on the development of artificial intelligence and big data technologies, the RegTech has been emerged to reduce regulatory costs and to enable efficient supervision by regulatory bodies. The word RegTech is a combination of regulation and technology, which means using the technological methods to facilitate the implementation of regulations and to make efficient surveillance and supervision of regulations. The purpose of this study is to describe the recent adoption of RegTech and to provide basic examples of applying RegTech to capital market regulations. Design/methodology/approach English-based ontology and deep learning technologies are quite developed in practice, and it will not be difficult to expand it to European or Latin American languages that are grammatically similar to English. However, it is not easy to use it in most Asian languages such as Korean, which have different grammatical rules. In addition, in the early stages of adoption, companies, financial institutions and regulators will not be familiar with this machine-based reporting system. There is a need to establish an ecosystem which facilitates the adoption of RegTech by consulting and supporting the stakeholders. In this paper, we provide a simple example that shows a procedure of applying RegTech to recognize and interpret Korean language-based capital market regulations. Specifically, we present the process of converting sentences in regulations into a meta-language through the morpheme analyses. We next conduct deep learning analyses to determine whether a regulatory sentence exists in each regulatory paragraph. Findings This study illustrates the applicability of RegTech-based ontology and deep learning technologies in Korean-based capital market regulations.

• International Journal of Computer Science & Network Security
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• v.21 no.7
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• pp.63-69
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• 2021

Flipped learning is necessary for modern education but quite difficult to implement. In pedagogical science, the question remains to what extent the practical work of the teacher in combination with the technologies of flipped learning will improve the quality of higher education. The aim of this article is to study the effectiveness and feasibility of using flipped learning technologies, assessing their perception by students (advantages and problems), identified an algorithm for introducing flipped learning technology in higher education institutions. Research methods. The main method is an experiment. An evaluation of the effectiveness of the study was conducted using a questionnaire and observation method. Statistical methods were used to evaluate the results of the experiment. The research hypothesis is that flipped learning allows the teacher to spend more time on an individual approach, to understand the real needs of students, and provide effective feedback, thereby improving the quality of learning and motivation of students, especially while studying complex material. The results of the study are to prove the effectiveness of the technology of flipped education in the study of complex disciplines, courses, topics. The use of flipped learning strategies improves the self-regulation of the educational process, group work skills, improves students' ability to learn, overcome difficulties. The technology of flipped learning in the presence of modern technical means and constant work on improving the level of digital literacy is an effective means for students to master complex topics and problematic issues that require additional consideration and discussion. The perspective of further research is the consideration of integrated approaches to the application of flipped learning technologies to the principles of STEAM-education, multilingual and multicultural programs, etc. It is also worth continuing to develop a set of methods aimed at enhancing the student's learning activities, the formation of group work skills, direct participation in creating the foundations of higher education.

• Smart Media Journal
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• v.10 no.3
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• pp.23-30
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• 2021

Although the manufacturing time series data clustering technique is an important grouping solution in the field of detecting and improving manufacturing large data-based equipment and process defects, it has a disadvantage of low accuracy when applying the existing static data target clustering technique to time series data. In this paper, an evolutionary computation-based time series cluster analysis approach is presented to improve the coherence of existing clustering techniques. To this end, first, the image shape resulting from the manufacturing process is converted into one-dimensional time series data using linear scanning, and the optimal sub-clusters for hierarchical cluster analysis and split cluster analysis are derived based on the Pearson distance metric as the target of the transformation data. Finally, by using a genetic algorithm, an optimal cluster combination with minimal similarity is derived for the two cluster analysis results. And the performance superiority of the proposed clustering is verified by comparing the performance with the existing clustering technique for the actual manufacturing process image.