• Journal of the Architectural Institute of Korea Structure & Construction
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• v.35 no.7
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• pp.171-178
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• 2019

Auto Climbing Formwork System (ACS) for construction of high-rise building is a construction method for automatically lifting the formwork system supported by the anchor on the pre-constructed concrete wall. It has excellent construction speed and quality, but it has the possibility of structural failure depending on the quality of concrete and also has low economical efficiency due to the use of foreign technology. In order to overcome these problems, this study conducted an optimum design for the development of a new concept of Corner Supported Auto Climbing System (CS-ACS) in conjunction with the development of corner steel-reinforced concrete core wall system. For the design the formwork system, the basic module and structural member compositions were planned, and the structural analysis program was used to analyze the optimum member's cross section and spacing. As a result, the horizontal displacement and the stress of the horizontal members were influenced by the spacing more than the cross-section of the member. On the other hand, vertical members did not affect the displacement and stress of the formwork system. The form tie was very effective in controlling the displacement when adjusting the spacing of the horizontal members, but when the spacing of the form tie is more than 1,500mm, it is analyzed that form tie is yielding in basic module. When the span of the formwork system is more than 30m, it is analyzed that the basic module needs to be changed because of the increase of overall displacement.

• Journal of Energy Engineering
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• v.16 no.3
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• pp.113-119
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• 2007

The auto-ignition characteristics and combustion behaviors of one-dimensional array of water-in-fuel droplets suspended in a high temperature chamber have been investigated experimentally with various droplet spacing and number of droplets. The fuels used were pure n-decane and emulsified n-decane with water contents varied from 10% to 30%. All experiments have been performed at 920 K under the atmospheric pressure. The number of droplets in an array were fixed as 3 or 5 and its spacing was varied from 3 mm to 7 mm by 1mm interval. The imaging technique with a high-speed camera has been adopted to measure the ignition delay and flame life time. The micro-explosion behaviors were also observed. As the droplet array sparing increased, the ignition delay also increased regardless of water contents. However, the life time of droplet array decreased as the droplet spacing increased. The full combustion time in array of 3 droplets was found to be longer than that for 5 droplets case due to the longer ignition delay.

• Journal of Mechanical Science and Technology
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• v.16 no.5
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• pp.583-590
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• 2002

When a mechanical structure is driven by stationary wide band random point forces, the resulting vibration depends upon the number, location, and joint statistical properties of the exciting forces. In this study, under the assumption of light damping, an approximate procedure for analyzing plates is briefly outlined. The effects of number, location and correlation of the force field on the vibration level are then investigated for various cases in which random point forces with band limited white noise are applied, and the optimal spacing between input forces that produces a relative minimum in the vibration response is predicted.

• Smart Media Journal
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• v.7 no.4
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• pp.17-23
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• 2018

We proposed a LSTM-based RNN model that can effectively perform the automatic spacing characteristics. For those long or noisy sentences which are known to be difficult to handle within Neural Network Learning, we defined a proper input data format and decoding data format, and added dropout, bidirectional multi-layer LSTM, layer normalization, and attention mechanism to improve the performance. Despite of the fact that Sejong corpus contains some spacing errors, a noise-robust learning model developed in this study with no overfitting through a dropout method helped training and returned meaningful results of Korean word spacing and its patterns. The experimental results showed that the performance of LSTM sequence-to-sequence model is 0.94 in F1-measure, which is better than the rule-based deep-learning method of GRU-CRF.

• Journal of KIISE
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• v.45 no.2
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• pp.157-164
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• 2018

Due to the revolutionary advances in deep learning, performance of pattern recognition has increased significantly in many applications like speech recognition and image recognition, and some systems outperform human-level intelligence in specific domains. Unlike pattern recognition, in this paper, we focus on generating Korean sentences based on a few Korean sentences. We apply variational recurrent auto-encoder (VRAE) and modify the model considering some characteristics of Korean sentences. To reduce the number of words in the model, we apply a word spacing model. Also, there are many Korean sentences which have the same meaning but different word order, even without subjects or objects; therefore we change the unidirectional encoder of VRAE into a bidirectional encoder. In addition, we apply an interpolation method on the encoded vectors from the given sentences, so that we can generate new sentences which are similar to the given sentences. In experiments, we confirm that our proposed method generates better sentences which are semantically more similar to the given sentences.

• KIPS Transactions on Software and Data Engineering
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• v.8 no.11
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• pp.441-448
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• 2019

Previous researches on automatic spacing of Korean sentences has been researched to correct spacing errors by using n-gram based statistical techniques or morpheme analyzer to insert blanks in the word boundary. In this paper, we propose an end-to-end automatic word spacing by using deep neural network. Automatic word spacing problem could be defined as a tag classification problem in unit of syllable other than word. For contextual representation between syllables, Bi-LSTM encodes the dependency relationship between syllables into a fixed-length vector of continuous vector space using forward and backward LSTM cell. In order to conduct automatic word spacing of Korean sentences, after a fixed-length contextual vector by Bi-LSTM is classified into auto-spacing tag(B or I), the blank is inserted in the front of B tag. For tag classification method, we compose three types of classification neural networks. One is feedforward neural network, another is neural network language model and the other is linear-chain CRF. To compare our models, we measure the performance of automatic word spacing depending on the three of classification networks. linear-chain CRF of them used as classification neural network shows better performance than other models. We used KCC150 corpus as a training and testing data.

• Journal of Biosystems Engineering
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• v.38 no.1
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• pp.1-8
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• 2013

Purpose: Path planning and tracking algorithms applicable to various agricultural operations, such as tillage, planting, and spraying, are needed to generate steering angles for auto-guidance tractors to track a point ahead on the path. An optimal coverage path algorithm can enable a vehicle to effectively travel across a field by following a sequence of parallel paths with fixed spacing. This study proposes a path generation and tracking algorithm for an auto-guided Korean tractor with a tillage implement that generates a path with C-type turns and follows the generated path in a paddy field. A mathematical model was developed to generate a waypoint path for a tractor in a field. This waypoint path generation model was based on minimum tractor turning radius, waypoint intervals and LBOs (Limit of Boundary Offsets). At each location, the steering angle was calculated by comparing the waypoint angle and heading angle of the tractor. A path following program was developed with Labview-CVI to automatically read the waypoints and generate steering angles for the tractor to proceed to the next waypoint. A feasibility test of the developed program for real-time path tracking was performed with a mobile platform traveling on flat ground. The test results showed that the developed algorithm generated the desired path and steering angles with acceptable accuracy.

• Special Issue of the Society of Naval Architects of Korea
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• 2011.09a
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• pp.90-94
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• 2011

Longitudinal shell member that arranged block unit on 3D-curved surface is performed manual working by designer considering spacing of division characteristic, location and twisting at geometrical 3-dimensional form. Shell expansion drawing that drawn by initial design and shell landing work performed by hull production design have overlap of design work in terms of arrangement of shell longitudinal member. In this study, eliminate design overlap on shell member arrangement that is one of ship longitudinal member. Develop shell member optimization and auto arrangement system.

• The Korean Journal of Nuclear Medicine Technology
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• v.21 no.2
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• pp.55-64
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• 2017

Purpose Recently, with the spread of SPECT/CT, various image correction methods can be applied quickly and accurately, which enabled us to expect quantitative accuracy as well as image quality improvement. Among them, the Collimator Detector Response(CDR) recovery is a correction method aiming at resolution recovery by compensating the blurring effect generated from the distance between the detector and the object. The purpose of this study is to find out quantitative change depending on the change in detection distance in SPECT/CT images with CDR recovery applied. Materials and Methods In order to find out the error of acquisition count depending on the change of detection distance, we set the detection distance according to the obit type as X, Y axis radius 30cm for circular, X, Y axis radius 21cm, 10cm for non-circular and non-circular auto(=auto body contouring, ABC_spacing limit 1cm) and applied reconstruction methods by dividing them into Astonish(3D-OSEM with CDR recovery) and OSEM(w/o CDR recovery) to find out the difference in activity recovery depending on the use of CDR recovery. At this time, attenuation correction, scatter correction, and decay correction were applied to all images. For the quantitative evaluation, calibration scan(cylindrical phantom, $^{99m}TcO_4$ 123.3 MBq, water 9293 ml) was obtained for the purpose of calculating the calibration factor(CF). For the phantom scan, a 50 cc syringe was filled with 31 ml of water and a phantom image was obtained by setting $^{99m}TcO_4$ 123.3 MBq. We set the VOI(volume of interest) in the entire volume of the syringe in the phantom image to measure total counts for each condition and obtained the error of the measured value against true value set by setting CF to check the quantitative accuracy according to the correction. Results The calculated CF was 154.28 (Bq/ml/cps/ml) and the measured values against true values in each conditional image were analyzed to be circular 87.5%, non-circular 90.1%, ABC 91.3% and circular 93.6%, non-circular 93.6%, ABC 93.9% in OSEM and Astonish, respectively. The closer the detection distance, the higher the accuracy of OSEM, and Astonish showed almost similar values regardless of distance. The error was the largest in the OSEM circular(-13.5%) and the smallest in the Astonish ABC(-6.1%). Conclusion SPECT/CT images showed that when the distance compensation is made through the application of CDR recovery, the detection distance shows almost the same quantitative accuracy as the proximity detection even under the distant condition, and accurate correction is possible without being affected by the change in detection distance.

• Journal of Korean Society on Water Environment
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• v.30 no.2
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• pp.159-165
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• 2014

Vegetative Filter Strip (VFS) is one of effective Best Management Practices (BMPs) to prevent sediment-laden water problem, is installed at the edge of source area such agricultural area so that sediment occurred in source area is trapped by VFS before it flow into stream or river. Appropriate scale of it needs to be simulated before it is installed, considering various field conditions. In this study, a model using VFSMOD-w model and Genetic Algorithm to determine effective VFS length was developed, it is available to calibrate input parameter related to source area sediment yield through thousands of VFSMOD-w simulations. Useful DBs, moreover, are stored in the model so that very specific input parameters can be used with reasonable values. Compared simulated values to observed data values for calibration, R2 and Nash-Stucliffe model efficiency coefficient were 0.74 and 0.65 in flow comparison, and 0.89 and 0.79 in sediment comparison. The model determined 1.0 m of Filter Length, 0.18 of Filter Slope, and 0.2 cm of Filter Media Spacing to reduce 80% of sediment by VFS. The model has not only Auto-Calibration module also DBs for specific input parameters, thus, the model is expected to be used for effective VFS scale.