• Korean Institute of Interior Design Journal
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• v.22 no.4
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• pp.149-157
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• 2013

As a period of pluralism, today's museum architecture has been expanding social and cultural meaning. So, Various expressions are appearing in museum architecture. Accordingly, the museum must be very reproducible and comply with aesthetic requirements. At the same time, museum construction in urban design and features must satisfy professional requirements. SANAA is one of contemporary architects has been decisively deleted existing fixed and functional layout type of program through 'The new hierarchy'. Thus, the experience of the space will vary. Now, museum space is urgently needed than ever before crustal movements. Thus, this study aims to contribute an alternative to the museum space configuration according to the trend of the times through 'The new hierarchy' of SANAA. This paper is limited to the cases of the SANAA's museum architecture. We analyze the characteristics of representation on 'The new hierarchy' appear in the museum space configuration and then, examine the value of the spatial. SANAA's 'New Hierarchy' is going to set the cognitive boundary by expression targeting plane and the surface. It is completely different than the previous boundaries. Characteristics of the expression represents non-centrality, decentrally, non-oriented, uncertainty, non-territorialization, uniformity. It is steady that identity of Space, Human, Environment in Museum. They have a relationship each concept of Independence, autonomy, equality.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.11 no.2
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• pp.83-91
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• 2012

An RF energy detector for spectrum sensing in TV white space transceiver is presented. It is based on an RF active filtering technique that comprises a low-noise amplifier with a frequency-translation high-pass filtering feedfoward loop, which attenuates the unwanted sideband energy and only passes the wanted band energy. Unlike the conventional architecture, a new architecture that can attenuate both sidebands at the same time is proposed. A simplified system modeling method is presented to assess the non-ideality effects on the RF energy detector performances. System behavioral simulations demonstrate that the proposed architecture can be instrumental for realizaing a RF energy detector circuit in CMOS.

• KIEAE Journal
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• v.14 no.5
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• pp.75-80
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• 2014

An attempt has been made to prove the so-called 'feature accumulation theory'. It is the theory describing that people tend to feel the same space with more identifiable objects much larger than that with fewer objects. Applying this theory to our cognition of spatial size, this paper made an experiment. Students were asked that if the lecture room they are sitting becomes a module (module 1), then how large are the questioned spaces in the campus. The result was striking. Through the mental image processing, they answered that the library and the architecture building looks much smaller than they actually are, and more surprisingly the basketball field much more smaller than it really is. This experiment shows that there is a strong tendency by which people regard the space much larger when there are more occupiable or behavior-causing elements in the space. In the case of basketball field, since there is nothing that can be occupied, this open space is seen as a small space for the subjects. This line of cognitive perception can be applied to the practice of urban planning and architectural planning. With the same size of given space, we can make it feel more rich and larger.

• Journal of Korean Society of Rural Planning
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• v.28 no.2
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• pp.51-59
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• 2022

The purpose of this study is to provide a plan to promote the use of life SOC facilities by analyzing the factors affecting utilization of life SOC facilities established as part of the rural center revitalization project. To this end, we selected Seongjeon-myeon, Gangjin-gun where the rural center revitalization project was implemented, conducted a survey on residents while analyzing the project details, and analyzed the results. This study revealed that the residents with a cognitive level for the rural center revitalization project and life SOC tended to more actively use the life SOC facilities. Therefore, to boost residents' use of the life SOC facilities, it is necessary to promote their understanding of and interest in the rural center revitalization project in the project implementation phase and have them be sufficiently aware of the facilities by operating pilot programs for residents in each facility and holding local events and festivals. This study will lay a steppingstone for active resident use of life SOC facilities established in rural centers and provide basic data for further research.

• Architectural research
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• v.24 no.1
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• pp.1-11
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• 2022

As the occurrence of a crime is dependent on different factors, their correlations are beyond the ordinary cognitive range. Owing to this limitation, systems face difficulty in correlating various factors, thereby requiring the assistance of artificial intelligence (AI) to overcome such limitations. Therefore, AI has become indispensable for crime prediction. Crimes can cause severe and irrevocable damage to a society. Recently, big data has been introduced for developing highly accurate models for crime prediction. Prediction of night crimes should be given significant consideration, because crimes primarily occur during nights, when the spatiotemporal characteristics become vulnerable to crimes. Many environmental factors that influence crime rate are applied for crime prediction, and their influence on crime rate may differ based on temporal characteristics and the nature of crime. This study aims to identify the environmental factors that influence sex and theft crimes occurring at night and proposes an artificial neural network (ANN) model to predict sex and theft crimes at night in random areas. The crime data of A district in Seoul for 12 years (2004-2015) was used, and environmental factors that influence sex and theft crimes were derived through multiple regression analysis. Two types of crime prediction models were developed: Type A using all environmental factors as input data; Type B with only the significant factors (obtained from regression analysis) as input data. The Type B model exhibited a greater accuracy than Type A, by 3.26 and 9.47 % higher for theft and sex crimes, respectively.

• Korean Journal of Cognitive Science
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• v.28 no.4
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• pp.299-314
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• 2017

Predicting compound-protein interactions in-silico is significant for the drug discovery. In this paper, we propose an scalable machine learning model to predict compound-protein interaction. The key idea of this scalable machine learning model is the architecture of pairwise neural network model and feature embedding method from the raw data, especially for protein. This method automatically extracts the features without additional knowledge of compound and protein. Also, the pairwise architecture elevate the expressiveness and compact dimension of feature by preventing biased learning from occurring due to the dimension and type of features. Through the 5-fold cross validation results on large scale database show that pairwise neural network improves the performance of predicting compound-protein interaction compared to previous prediction models.

• International Journal of Human Ecology
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• v.8 no.2
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• pp.29-46
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• 2007

The purpose of this study was to analyze characteristics of the bedroom environment of nursing homes for the elderly in Korea. Field case research was performed using a structured checklist and measurements, from Oct. 28th to Dec. 2nd, 2006. Collected data were analyzed for cognitive efficiency, privacy, safety, supportiveness and amenity. Based on nursing homes for the elderly nationwide (Ministry of Health and Welfare, 2006), we choose 43 facilities in which Seoul and six megalopolis areas that had answered our questionnaire in 2006. We then narrowed the list to 14 facilities, balanced them in terms of regional population. The contents of investigation consisted of eight categories: that general characteristics of the bedrooms (including number of residents per room, using a bed or floor mat, the size and shape of the chamber, space for wheelchair turning, signage), door of bedroom (including door, doorknob, door sill/level difference), windows in the bedroom(including type of window, window sill height, window treatment, window safety device/shape, view/daylight), furniture (including personal furniture and lock), finishes (material, character and color of wall, floor, ceiling), lighting (including types of lighting, night lighting, switch), bathroom in the bedroom (including signage, door size/type, doorknob shape, height of the washbowl, size of toilet bowl, handrail, finishes), and other facilities (including outlet and handrails).

• Journal of the Ergonomics Society of Korea
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• v.31 no.6
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• pp.705-713
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• 2012

Objective: The aim of this study is to predict human visual target search using ACT-R cognitive architecture in real scene images. Background: Human uses both the method of bottom-up and top-down process at the same time using characteristics of image itself and knowledge about images. Modeling of human visual search also needs to include both processes. Method: In this study, visual target object search performance in real scene images was analyzed comparing experimental data and result of ACT-R model. 10 students participated in this experiment and the model was simulated ten times. This experiment was conducted in two conditions, indoor images and outdoor images. The ACT-R model considering the first saccade region through calculating the saliency map and spatial layout was established. Proposed model in this study used the guide of visual search and adopted visual search strategies according to the guide. Results: In the analysis results, no significant difference on performance time between model prediction and empirical data was found. Conclusion: The proposed ACT-R model is able to predict the human visual search process in real scene images using salience map and spatial layout. Application: This study is useful in conducting model-based evaluation in visual search, particularly in real images. Also, this study is able to adopt in diverse image processing program such as helper of the visually impaired.

• Journal of the Korean Institute of Landscape Architecture
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• v.13 no.1
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• pp.109-121
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• 1985

A study on the image identification of urban streetscape is valuable for illuminating identity that is not yet fully approached in the field of environmental design. This analysis of urban streetscape for image identification allows us to make a more detailed exploration of an important approaching methods in dealing with the structural characteristics of identity. As a matter of fact, the earlier indirect studies on this image identification were made by environmental designers, such as architectural and urban designer in the field of environmental perception and came to its environmental cognition & environmental pattern research with assistances by such researchers as K. Lynch A. Rapoport & Christopher Alexander. Through its environmental perception research, we can see its structural characteristics that is aesthetic & visual structural contents of physical environmental elements. And we can see its cognitive characteristics through the environmental cognitive research, that is continuity, territoriality, identity of place, uniqueness or individuality, meaning & symbolism. Through its environmental pattern research, we can see its physical, socio - economic, cultural and symbolic pattern identification contents, that is physical form of the city, style of the street, pattern of streetscape, socio- economic & geographical locality, arid life cycle, life style, common style of the behavior, cultural pattern of the activity, socio - cultural expression of the symbol. In these process, we can set up a set of the environmental design criterias from those three integral studies for identity. And for an environmental research, Tongsung-Ro around the CBD (central business district) in Taegu City was selected for a case study, because this streetscape is suitable for that approaching methods in this study.

• Journal of Internet of Things and Convergence
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• v.10 no.1
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• pp.69-75
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• 2024

This paper proposes an innovative cognitive IoT framework specifically designed for fog computing (FC) in the context of industrial Internet of Things (IIoT). The discourse in this paper is centered on the intricate design and functional architecture of the Cognitive IoT platform. A crucial feature of this platform is the integration of machine learning (ML) and artificial intelligence (AI), which enhances its operational flexibility and compatibility with a wide range of industrial applications. An exemplary application of this platform is highlighted through the Predictive Maintenance-as-a-Service (PdM-as-a-Service) model, which focuses on real-time monitoring of machine conditions. This model transcends traditional maintenance approaches by leveraging real-time data analytics for maintenance and management operations. Empirical results substantiate the platform's effectiveness within a fog computing milieu, thereby illustrating its transformative potential in the domain of industrial IoT applications. Furthermore, the paper delineates the inherent challenges and prospective research trajectories in the spheres of Cognitive IoT and Fog Computing within the ambit of Industrial Internet of Things (IIoT).