• 의료ㆍ복지 건축 : 한국의료복지건축학회 논문집
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• 제15권2호
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• pp.51-58
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• 2009

These days the trend of special education is changing from special school-based education to special class room based education, and from separated education to integrated education. In accordance with this change, special classes should be planned for multi purposes so that the class room can be used for the place of teaching and learning, guidance, job education. This research surveyed the special teachers working for 937 schools which have special classes(elementary 631, middle 217 high school 89). The result of this survey shows the different responses according to the level of the schools. For education activities, elementary and middle schools put emphasis on curriculum rather than guidance. High education, elementary school should have the places for teaching and learning, student management, play ground. Middle schools give priority to the places for individual learning, computer and practical training. High schools value the places for job education and practical training above for learning.

• The Journal of Korean Physical Therapy
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• 제26권6호
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• pp.411-417
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• 2014

Purpose: This study attempts to find the effects of water-based exercise performed on stroke patients in their physiological cost index and static and dynamic balance. Methods: The subjects were 30 stroke patients, who were randomly divided a water-based exercise group and a land-based exercise group, each with 15 patients. Both exercises ware performed 3 day per week, for 40 minutes a day, for a period of eight weeks. Results: The Water-based exercise group showed a decreased physiological cost index compared to the land-based exercise group, with the physiological cost index of the water-based exercise group decreasing, while the land-based exercise group, showing a significant decrease. Water-based exercise increased static and dynamic balance capacity better than land-based group, showing a significant difference and better efficiency of water-based exercise when compared to land-based exercise. Conclusion: From the result of the study, we found that water-based exercise is more effective in improving PCI and static and dynamic balance capacity. Through this study, training in water-based stroke patients could use cardiovascular endurance and buoyancy and the vortex, as an effective treatment that can enhance the growth and voluntary participation in the range of the patient's own movement the thought is, in consideration of the changes in the physiological cost index due to the difference in the ground and water, and should establish a training program that matches the purpose.

• 한국멀티미디어학회논문지
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• 제20권5호
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• pp.769-781
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• 2017

Deep learning networks like Convolutional Neural Networks (CNNs) show successful performances in many computer vision applications such as image classification, object detection, and so on. For implementation of deep learning networks in embedded system with limited processing power and memory, deep learning network may need to be simplified. However, simplified deep learning network cannot learn every possible scene. One realistic strategy for embedded deep learning network is to construct a simplified deep learning network model optimized for the scene images of the installation place. Then, automatic training will be necessitated for commercialization. In this paper, as an intermediate step toward automatic training under fisheye camera environments, we study more precise human localization in fisheye images, and propose an accurate human localization method, Automatic Ground-Truth Labelling Method (AGTLM). AGTLM first localizes candidate human object bounding boxes by utilizing GoogLeNet-LSTM approach, and after reassurance process by GoogLeNet-based CNN network, finally refines them more correctly and precisely(tightly) by applying saliency object detection technique. The performance improvement of the proposed human localization method, AGTLM with respect to accuracy and tightness is shown through several experiments.

• Structural Engineering and Mechanics
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• 제70권6호
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• pp.671-681
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• 2019

This paper examines the applicability of artificial neural network (ANN) and multivariate adaptive regression splines (MARS) to predict the compressive strength of bacteria incorporated geopolymer concrete (GPC). The mix is composed of new bacterial strain, manufactured sand, ground granulated blast furnace slag, silica fume, metakaolin and fly ash. The concentration of sodium hydroxide (NaOH) is maintained at 8 Molar, sodium silicate ($Na_2SiO_3$) to NaOH weight ratio is 2.33 and the alkaline liquid to binder ratio of 0.35 and ambient curing temperature ($28^{\circ}C$) is maintained for all the mixtures. In ANN, back-propagation training technique was employed for updating the weights of each layer based on the error in the network output. Levenberg-Marquardt algorithm was used for feed-forward back-propagation. MARS model was developed by establishing a relationship between a set of predictors and dependent variables. MARS is based on a divide and conquers strategy partitioning the training data sets into separate regions; each gets its own regression line. Six models based on ANN and MARS were developed to predict the compressive strength of bacteria incorporated GPC for 1, 3, 7, 28, 56 and 90 days. About 70% of the total 84 data sets obtained from experiments were used for development of the models and remaining 30% data was utilized for testing. From the study, it is observed that the predicted values from the models are found to be in good agreement with the corresponding experimental values and the developed models are robust and reliable.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제13권1호
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• pp.206-221
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• 2019

Source localization in three-dimensional (3-D) wireless sensor networks (WSNs) is becoming a major research focus. Due to the complicated air-ground environments in 3-D positioning, many of the traditional localization methods, such as received signal strength (RSS) may have relatively poor accuracy performance. Benefit from prior learning mechanisms, fingerprinting-based localization methods are less sensitive to complex conditions and can provide relatively accurate localization performance. However, fingerprinting-based methods require training data at each grid point for constructing the fingerprint database, the overhead of which is very high, particularly for 3-D localization. Also, some of measured data may be unavailable due to the interference of a complicated environment. In this paper, we propose an efficient kernel based 3-D localization algorithm via tensor completion. We first exploit the spatial correlation of the RSS data and demonstrate the low rank property of the RSS data matrix. Based on this, a new training scheme is proposed that uses tensor completion to recover the missing data of the fingerprint database. Finally, we propose a kernel based learning technique in the matching phase to improve the sensitivity and accuracy in the final source position estimation. Simulation results show that our new method can effectively eliminate the impairment caused by incomplete sensing data to improve the localization performance.

• Structural Engineering and Mechanics
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• 제81권5호
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• pp.575-589
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• 2022

In order to enhance the greenness in the strain-hardening composites and to reduce the high cost of typical polyvinyl alcohol fiber reinforced engineered cementitious composite (PVA-ECC), an affordable strain-hardening composite with green binder content has been proposed. For optimizing the strain-hardening behavior of cementitious composites, this paper investigates the effects of polypropylene fibers on the first cracking strength, fracture properties, and micromechanical parameters of cementitious composites. For this purpose, digital image correlation (DIC) technique was utilized to monitor crack propagation. In addition, to have an in-depth understanding of fiber/matrix interaction, scanning electron microscope (SEM) analysis was used. To understand the effect of fibers on the strain hardening behavior of cementitious composites, ten mixes were designed with the variables of fiber length and volume. To investigate the micromechanical parameters from fracture tests on notched beam specimens, a novel technique has been suggested. In this regard, mechanical and fracture tests were carried out, and the results have been discussed utilizing both fracture and micromechanical concepts. This study shows that the fiber length and volume have optimal values; therefore, using fibers without considering the optimal values has negative effects on the strain-hardening behavior of cementitious composites.

• 한국정보처리학회:학술대회논문집
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• 한국정보처리학회 2009년도 춘계학술발표대회
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• pp.35-38
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• 2009

The paper presents an effective method to detect fire in video surveillance and monitoring system. The main contribution of this work is that we successfully use the Hidden Markov Models in the process of detecting the fire with a few preprocessing steps. First, the moving pixels detected from image difference, the color values obtained from the fire flames, and their pixels clustering are applied to obtain the image regions labeled as fire candidates; secondly, utilizing massive training data, including fire videos and non-fire videos, creates the Hidden Markov Models of fire and non-fire, which are used to make the final decision that whether the frame of the real-time video has fire or not in both temporal and spatial analysis. Experimental results demonstrate that it is not only robust but also has a very low false alarm rate, furthermore, on the ground that the HMM training which takes up the most time of our whole procedure is off-line calculated, the real-time detection and alarm can be well implemented when compared with the other existing methods.

• Nuclear Engineering and Technology
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• 제55권1호
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• pp.190-200
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• 2023

As the field of application of in-situ gamma spectroscopy is diversified, proficiency is required for consistent and accurate analysis. In this study, a program was developed to virtually create gamma energy spectra of artificial nuclides, which are difficult to obtain through actual measurements, for training. The virtual spectrum was created by synthesizing the spectra of the background radiation obtained through actual measurement and the theoretical spectra of the artificial radionuclides obtained by a Monte Carlo simulation. Since the theoretical spectrum can only be obtained for a given geometrical structure, representative major geometries for in-situ measurement (ground surface, concrete wall, radioactive waste drum) and the detectors (HPGe, NaI(Tl), LaBr₃(Ce)) were predetermined. Generated virtual spectra were verified in terms of validity and harmonization by gamma spectrometry and energy calibration. As a result, it was confirmed that the energy calibration results including the peaks of the measured spectrum and the peaks of the theoretical spectrum showed differences of less than 1 keV from the actual energies, and that the calculated radioactivity showed a difference within 20% from the actual inputted radioactivity. The verified data were assembled into a database and a program that can generate a virtual spectrum of desired condition was developed.

• 한국항공운항학회지
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• 제31권2호
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• pp.66-71
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• 2023

In the case of the Navy, if some of the co-pilots are included in the long-term promotion process due to the limited number of co-pilots, operational flight and administrative tasks will be added to the co-pilots not included in the rest of the Pilot in commander process. Therefore, to solve this problem, the co-pilot who has passed the PQS step-by-step process minimizes the personnel gap in the flight operation unit through a system that evaluates whether it is possible to perform its duties as a co-pilot through actual flight after entering the school. The advantage of the PQS course is that you can control flight plans on your own and minimize gaps in flight and ground work while carrying out the curriculum, but you can't focus on education or improve your skills due to irregular training flight cycles. Therefore, in this study, after collecting opinions on effective flight cycles through a survey of pilots of P-3C, the Navy's fixed-wing aircraft representative, we will analyze the association of aircraft volume performance by flight cycle to derive the optimal flight cycle of the P-3C pilot course.

• Geomechanics and Engineering
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• 제37권3호
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• pp.197-211
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• 2024

This research studies the effect of geotechnical factors on EPB-TBM performance parameters. The modeling was performed using simple and multivariate linear regression methods, artificial neural networks (ANNs), and Sugeno fuzzy logic (SFL) algorithm. In ANN, 80% of the data were randomly allocated to training and 20% to network testing. Meanwhile, in the SFL algorithm, 75% of the data were used for training and 25% for testing. The coefficient of determination (R²) obtained between the observed and estimated values in this model for the thrust force and cutterhead torque was 0.19 and 0.52, respectively. The results showed that the SFL outperformed the other models in predicting the target parameters. In this method, the R² obtained between observed and predicted values for thrust force and cutterhead torque is 0.73 and 0.63, respectively. The sensitivity analysis results show that the internal friction angle (φ) and standard penetration number (SPT) have the greatest impact on thrust force. Also, earth pressure and overburden thickness have the highest effect on cutterhead torque.