• Korean Journal of Cognitive Science
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• v.21 no.4
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• pp.559-602
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• 2010

This study examines the concepts and functional characteristics of consciousness in comparison of memory and attention from the perspective of information processing. It also provides an understanding of the relationships between the three as hypothetical constructs. Consciousness is regarded as too ambiguous a concept to be understood and accepted as a mental construct without the inclusion of memory and attention in any conceptualization. We need one criterion to count satisfactorily as an explanation of consciousness in information processing. Consciousness would be a subjective awareness of momentary experience and also have the characteristic of an operating system performing control and consolidation in information processing. This could be called cognitive consciousness which refers to a subjective awareness and an executive control system, even though those are not equivalent concepts. Consciousness, memory and attention, three mental constructs could operate dependently or independently depending on the specific tasks conditioned in many information processing levels whose modules with three mental constructs could operate in hierarchy. In this premise, working memory could not be a unitary system, contrary to those of Baddeley and Hitch(1974) and Baddeley(1992, 2000), just being a mental workplace consisting of two components: the phonological loop, and the visual-spatial sketchpad without the episodic buffer and a central executive which are the characteristics of consciousness. In the continuum of information processing, the conscious processes and the unconscious processes seem not to be totally different and contrasting processes.

• Journal of the Korean Institute of Intelligent Systems
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• v.26 no.1
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• pp.56-63
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• 2016

In this study, we introduce a design of Fuzzy RBFNNs-based digit recognition system using the incremental-PCA in order to recognize the handwritten digits. The Principal Component Analysis (PCA) is a widely-adopted dimensional reduction algorithm, but it needs high computing overhead for feature extraction in case of using high dimensional images or a large amount of training data. To alleviate such problem, the incremental-PCA is proposed for the computationally efficient processing as well as the incremental learning of high dimensional data in the feature extraction stage. The architecture of Fuzzy Radial Basis Function Neural Networks (RBFNN) consists of three functional modules such as condition, conclusion, and inference part. In the condition part, the input space is partitioned with the use of fuzzy clustering realized by means of the Fuzzy C-Means (FCM) algorithm. Also, it is used instead of gaussian function to consider the characteristic of input data. In the conclusion part, connection weights are used as the extended diverse types in polynomial expression such as constant, linear, quadratic and modified quadratic. Experimental results conducted on the benchmarking MNIST handwritten digit database demonstrate the effectiveness and efficiency of the proposed digit recognition system when compared with other studies.

• Science of Emotion and Sensibility
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• v.5 no.4
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• pp.77-84
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• 2002

In this paper, we propose the NAVER, a general framework for multipurpose virtual environments, and introduce the case study of evaluating car prototypes using cave-like systems. As a framework to implement variant applications in virtual environment, NAVER is extensible, reconfigurable and scalable. NAVER consists of several external modules (Render Server, Control Server and Device Server), which communicate each other to share states and user-provided data and to perform their own functions. NAVER supports its own scripting language based on XML which allows a user to define variant interactions between objects in virtual environments as well as describe the scenario of an application. We used NAVER to implement the system for evaluating car prototyes in a CAVE-like virtual environment system. The CAVE-like virtual environment system at KIST consists three side screens and a floor screen (each of them is a square with side of 2.2m), four CRT projectors displays stereoscopic images to the screens, a haptic armmaster, and a 5.1 channel sound system. The system can provide a sense of reality by displaying auditory and tactile senses as well as visual images at the same time. We evaluate car prototypes in a CAVE-like system in which a user can observe, touch and manipulate the virtual installation of car interior.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.34 no.6
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• pp.619-627
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• 2016

Cells of a PV (photovoltaic) module can suffer defects due to various causes resulting in a loss of power output. As a malfunctioning cell has a higher temperature than adjacent normal cells, it can be easily detected with a thermal infrared sensor. A conventional method of PV cell inspection is to use a hand-held infrared sensor for visual inspection. The main disadvantages of this method, when applied to a large-scale PV power plant, are that it is time-consuming and costly. This paper presents an algorithm for automatically detecting defective PV panels using images captured with a thermal imaging camera from an UAV (unmanned aerial vehicle). The proposed algorithm uses statistical analysis of thermal intensity (surface temperature) characteristics of each PV module to verify the mean intensity and standard deviation of each panel as parameters for fault diagnosis. One of the characteristics of thermal infrared imaging is that the larger the distance between sensor and target, the lower the measured temperature of the object. Consequently, a global detection rule using the mean intensity of all panels in the fault detection algorithm is not applicable. Therefore, a local detection rule was applied to automatically detect defective panels using the mean intensity and standard deviation range of each panel by array. The performance of the proposed algorithm was tested on three sample images; this verified a detection accuracy of defective panels of 97% or higher. In addition, as the proposed algorithm can adjust the range of threshold values for judging malfunction at the array level, the local detection rule is considered better suited for highly sensitive fault detection compared to a global detection rule. In this study, we used a panel area extraction method that we previously developed; fault detection accuracy would be improved if panel area extraction from images was more precise. Furthermore, the proposed algorithm contributes to the development of a maintenance and repair system for large-scale PV power plants, in combination with a geo-referencing algorithm for accurate determination of panel locations using sensor-based orientation parameters and photogrammetry from ground control points.

• Korean Journal of Agricultural and Forest Meteorology
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• v.13 no.1
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• pp.28-34
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• 2011

This study was carried out to estimate monthly mean of daily maximum and minimum temperature across North Korea at a 30 m grid spacing for a climatological normal year (1971-2000) and the 4 decadal averages (1971-1980, 1981-1990, 1991-2000, and 2001-2010). A geospatial climate interpolation method, which has been successfully used to produce the so-called 'High-Definition Digital Climate Maps' (HD-DCM), was used in conjunction with the 27 North Korean and 17 South Korean synoptic data. Correction modules including local effects of cold air drainage, thermal belt, ocean, solar irradiance and urban heat island were applied to adjust the synoptic temperature data in addition to the lapse rate correction. According to the final temperature estimates for a normal year, North Korean winter is expected colder than South Korean winter by $7^{\circ}C$ in average, while the spatial mean summer temperature is lower by $3^{\circ}C$ than that for South Korea. Warming trend in North Korea for the recent 40 years (1971-2010) was most remarkable in spring and fall, showing a 7.4% increase in the land area with 15 or higher daily maximum temperature for April.

• Journal of Korea Water Resources Association
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• v.43 no.11
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• pp.995-1009
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• 2010

Accelerated soil erosion due to extreme climate change, such as increased rainfall intensity, and human-induced environmental changes, is a widely recognized problem. Existing soil erosion models are generally based on the gross erosion concept to compute annual upland soil loss in tons per acre per year. However, such models are not suitable for event-based simulations of erosion and deposition in time and space. Recent advances in computer geographic information system (GIS) technologies have allowed hydrologists to develop physically based models, and the trend in erosion prediction is towards process-based models, instead of conceptually lumped models. This study aims to propose an effective and robust distributed rainfall-sediment yield-runoff model consisting of basic element modules: a rainfall-runoff module based on the kinematic wave method for subsurface and surface flow, and a runoff-sediment yield-runoff model based on the unit stream power method. The model was tested on the Cheoncheon catchment, upstream of the Yongdam dam using hydrological data for three extreme flood events due to typhoons. The model provided acceptable simulation results with respect to both discharge and sediment discharge even though the simulated sedigraphs were underestimated, compared to observations. The spatial distribution of erosion and deposition demonstrated that eroded sediment loads were deposited in the cells along the channel network, which have a short overland flow length and a gentle local slope while the erosion rate increased as rainfall became larger. Additionally, spatially heterogeneous rainfall intensity, dependant on Thiessen polygons, led to spatially-distinct erosion and deposition patterns.

• Membrane Journal
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• v.22 no.6
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• pp.404-414
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• 2012

In order to investigate $SO_2$ removal, PEI hollow fiber membranes were produced by a dry-wet phase inversion method. The membrane support layer on surface was coated with PEBAX1657$^{(R)}$ and PEG blending materials. Modules were prepared for the single gas permeation characteristics of composite membrane according to temperature and pressure. As a result, $SO_2$ permeance and $SO_2/N_2$ selectivity were 220~1220 GPU and 100~506 through operating condition, respectively. Moreover, $SO_2/CO_2/N_2$ mixture gas was used to compare the performance of separation properties according to temperature, pressure and retentate flow rate difference. $SO_2$ removal efficiency was increased with pressure and temperature.

• Journal of Broadcast Engineering
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• v.18 no.6
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• pp.835-849
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• 2013

Joint Collaborative Team on Video Coding (JCT-VC), which have founded ISO/IEC MPEG and ITU-T VCEG, has standardized High Efficiency Video Coding (HEVC). Standardization of HEVC has started with purpose of twice or more coding performance compared to H.264/AVC. However, flexible and hierarchical coding block and recursive coding structure are problems to overcome of HEVC standard. Many fast encoding algorithms for reducing computational complexity of HEVC encoder have been proposed. However, it is hard to implement a real-time HEVC encoder only with those fast encoding algorithms. In this paper, for implementation of software-based real-time HEVC encoder, data-level parallelism using SIMD instructions and CPU/GPU multi-threading methods are proposed. And we also proposed appropriate operations and functional modules to apply the proposed methods on HM 10.0 software. Evaluation of the proposed methods implemented on HM 10.0 software showed 20-30fps for $832{\times}480$ sequences and 5-10fps for $1920{\times}1080$ sequences, respectively.

• KIPS Transactions on Software and Data Engineering
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• v.7 no.6
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• pp.205-220
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• 2018

Software defect prediction is helpful for allocating valuable project resources effectively for software quality assurance activities thanks to focusing on the identified fault-prone modules. If historical data collected within a company is sufficient, a Within-Project Defect Prediction (WPDP) can be utilized for accurate fault-prone module prediction. In case a company does not maintain historical data, it may be helpful to build a classifier towards predicting comprehensible fault prediction based on Cross-Project Defect Prediction (CPDP). Since CPDP employs different project data collected from other organization to build a classifier, the main obstacle to build an accurate classifier is that distributions between source and target projects are not similar. To address the problem, because it is crucial to identify effective similarity measure techniques to obtain high performance for CPDP, In this paper, we aim to identify them. We compare various similarity measure techniques. The effectiveness of similarity weights calculated by those similarity measure techniques are evaluated. The results are verified using the statistical significance test and the effect size test. The results show k-Nearest Neighbor (k-NN), LOcal Correlation Integral (LOCI), and Range methods are the top three performers. The experimental results show that predictive performances using the three methods are comparable to those of WPDP.

• Journal of Korean Home Economics Education Association
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• v.16 no.4 s.34
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• pp.43-56
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• 2004

The purpose of this study was to develop the web-based practical problem-solving teaching plans for middle school home economics class. Five practical problems which were obesity, food waste, processed food, genetically-modified food, and imported food were selected based on the food, nutrition and diet of adolescent in middle school home economics syllabus. Web-based practical problem-solving teaching plans were consisted of 5 processes: 1)recognition of the practical problem, 2)gathering and evaluation of various information, 3)figure out the best way to tackle the practical problem, 4)put into behavioral practice, and 5)analyze the results of the behavioral practice. For the effective lesson, several supplemental materials, such as individual and group reports format. obesity test methods, animations. pictures, and modules were developed. Teaching plans including supplemental materials provided might be useful to middle school home economics teachers.