• Journal of the Korean Recycled Construction Resources Institute
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• v.11 no.4
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• pp.355-363
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• 2023

In safety assessment of a aged bridge, dynamic characteristics and displacement are directly related to the rigidity of the structural system, especially displacement is the most important factor as the physical quantity that the bridge user can directly detect. However, in order to measure the displacement of the bridge, it is difficult to install displacement sensors at the bottom of the bridge and conduct traffic blocking and loading tests, resulting in increased costs or impossible measurements depending on the bridge's environment. In this study, a method of measuring the displacement of a bridge using only accelerometers without installing displacement sensors and ambient vibration without a loading test was proposed. For the analysis of bridge dynamic characteristics and displacement using ambient vibration, the mode shape and natural frequency of the bridge were extracted using a TDD technique known to enable quick analysis with simple calculations, and the unit load displacement of the bridge was analyzed through flexibility analysis to calculate static displacement. To verify this proposed technology, an on-site test was conducted on C Bridge, and the results were compared with the measured values of the loading test and the structural analysis data. As a result, it was confirmed that the mode shape and natural frequency were 0.42 to 1.13 % error ratio, and the maximum displacement at the main span was 3.58 % error ratio. Therefore, the proposed technology can be used as a basis data for indirectly determine the safety of the bridge by comparing the amount of displacement compared to the design and analysis values by estimating the displacement of the bridge that could not be measured due to the difficulty of installing displacement sensors.

• The Journal of the Acoustical Society of Korea
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• v.42 no.6
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• pp.544-551
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• 2023

Speech enhancement used to improve the perceptual quality and intelligibility of noise speech has been studied as a method using a complex-valued spectrum that can improve both magnitude and phase in a method using a magnitude spectrum. In this paper, a study was conducted on how to apply attention mechanism to complex-valued spectrum-based speech enhancement systems to further improve the intelligibility and quality of noise speech. The attention is performed based on additive attention and allows the attention weight to be calculated in consideration of the complex-valued spectrum. In addition, the global average pooling was used to consider the importance of the feature map. Complex-valued spectrum-based speech enhancement was performed based on the Deep Complex U-Net (DCUNET) model, and additive attention was conducted based on the proposed method in the Attention U-Net model. The results of the experiments on noise speech in a living room environment showed that the proposed method is improved performance over the baseline model according to evaluation metrics such as Source to Distortion Ratio (SDR), Perceptual Evaluation of Speech Quality (PESQ), and Short Time Object Intelligence (STOI), and consistently improved performance across various background noise environments and low Signal-to-Noise Ratio (SNR) conditions. Through this, the proposed speech enhancement system demonstrated its effectiveness in improving the intelligibility and quality of noisy speech.

• Journal of Internet of Things and Convergence
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• v.9 no.6
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• pp.57-62
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• 2023

This research is a comparative analysis of the U.S. S&P 500 index using the volatility breakout strategy against the Buy and Hold approach. The volatility breakout strategy is a trading method that exploits price movements after periods of relative market stability or concentration. Specifically, it is observed that large price movements tend to occur more frequently after periods of low volatility. When a stock moves within a narrow price range for a while and then suddenly rises or falls, it is expected to continue moving in that direction. To capitalize on these movements, traders adopt the volatility breakout strategy. The 'k' value is used as a multiplier applied to a measure of recent market volatility. One method of measuring volatility is the Average True Range (ATR), which represents the difference between the highest and lowest prices of recent trading days. The 'k' value plays a crucial role for traders in setting their trade threshold. This study calculated the 'k' value at a general level and compared its returns with the Buy and Hold strategy, finding that algorithmic trading using the volatility breakout strategy achieved slightly higher returns. In the future, we plan to present simulation results for maximizing returns by determining the optimal 'k' value for automated trading of the S&P 500 index using artificial intelligence deep learning techniques.

• Journal of the Korean Society of Radiology
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• v.17 no.7
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• pp.1067-1073
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• 2023

Breast cancer is one of the top three most common cancers in modern women, and the incidence rate is increasing rapidly. Breast cancer has a high family history and a mortality rate of about 15%, making it a high-risk group. Therefore, breast cancer needs constant management after an early examination. Among the various equipment that can diagnose cancer, ultrasound has the advantage of low risk and being able to diagnose in real time. In addition, breast ultrasound will be more useful because Asian women's breasts are denser and less sensitive. However, the results of ultrasound examinations vary greatly depending on the technology of the examiner. To compensate for this, we intend to incorporate motion tracking technology. Motion tracking is a technology that specifies and analyzes a location according to the movement of an object in a three-dimensional space. Therefore, real-time control is possible, and complex and fast movements can be recorded in real time. We would like to present the production of an ultrasound examination guide using these advantages.

• KIPS Transactions on Computer and Communication Systems
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• v.11 no.6
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• pp.167-174
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• 2022

PIPO lightweight block ciphers were announced in ICISC'20. In this paper, a single-block optimization implementation and parallel optimization implementation of PIPO lightweight block cipher ECB, CBC, and CTR operation modes are performed on a 32-bit RISC-V processor. A single block implementation proposes an efficient 8-bit unit of Rlayer function implementation on a 32-bit register. In a parallel implementation, internal alignment of registers for parallel implementation is performed, and a method for four different blocks to perform Rlayer function operations on one register is described. In addition, since it is difficult to apply the parallel implementation technique to the encryption process in the parallel implementation of the CBC operation mode, it is proposed to apply the parallel implementation technique in the decryption process. In parallel implementation of the CTR operation mode, an extended initialization vector is used to propose a register internal alignment omission technique. This paper shows that the parallel implementation technique is applicable to several block cipher operation modes. As a result, it is confirmed that the performance improvement is 1.7 times in a single-block implementation and 1.89 times in a parallel implementation compared to the performance of the existing research implementation that includes the key schedule process in the ECB operation mode.

• KIPS Transactions on Software and Data Engineering
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• v.12 no.12
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• pp.505-518
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• 2023

3D point cloud semantic segmentation is a computer vision task that involves dividing the point cloud into different objects and regions by predicting the class label of each point. Existing 3D semantic segmentation models have some limitations in performing sufficient fusion of multi-modal features while ensuring both characteristics of 2D visual features extracted from RGB images and 3D geometric features extracted from point cloud. Therefore, in this paper, we propose MMCA-Net, a novel 3D semantic segmentation model using 2D-3D multi-modal features. The proposed model effectively fuses two heterogeneous 2D visual features and 3D geometric features by using an intermediate fusion strategy and a multi-modal cross attention-based fusion operation. Also, the proposed model extracts context-rich 3D geometric features from input point cloud consisting of irregularly distributed points by adopting PTv2 as 3D geometric encoder. In this paper, we conducted both quantitative and qualitative experiments with the benchmark dataset, ScanNetv2 in order to analyze the performance of the proposed model. In terms of the metric mIoU, the proposed model showed a 9.2% performance improvement over the PTv2 model using only 3D geometric features, and a 12.12% performance improvement over the MVPNet model using 2D-3D multi-modal features. As a result, we proved the effectiveness and usefulness of the proposed model.

• The Mathematical Education
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• v.62 no.4
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• pp.531-549
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• 2023

Despite the significance of mathematics teacher guidebooks as a support for teacher learning, there are few studies that address how elementary mathematics teacher guidebooks support teacher learning. The purpose of this study was to analyze the educative features of elementary mathematics teacher guidebooks for grades 3 and 4. For this, six units from each of ten kinds of teacher guidebooks were analyzed in terms of seven dimensions of Teacher Learning Opportunities in Korean Mathematics Curriculum Materials (TLO-KMath). The results of this study showed that mathematics content knowledge for teaching was richly provided and well organized. Teacher guidebooks provided teacher knowledge to anticipate and understand student errors and misconceptions, but were not enough. Sample dialogues between a teacher and students were offered in the teacher guidebooks, making it easier for teachers to identify the overall lesson flow and key points of classroom discourse. Formative assessment was emphasized in the teacher guidebooks, including lesson-specific student responses and their concomitant feedback examples per main activity. Supplementary activities and worksheets were provided, but it lacked rationales for differentiated instruction in mathematics. Teacher knowledge of manipulative materials and technology use in mathematics was provided only in specific units and was generally insufficient. Teacher knowledge in building a mathematical community was mainly provided in terms of mathematical competency, mathematical classroom culture, and motivation. This paper finally presented implications for improving teacher guidebooks to actively support teacher learning.

• The Sea:JOURNAL OF THE KOREAN SOCIETY OF OCEANOGRAPHY
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• v.13 no.4
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• pp.342-347
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• 2008

Mortality and growth rate of the soft coral, Dendronephthya gigantea, from Jejudo Island on the southern coast of Korea were investigated from February 2003 to October 2004 using SCUBA diving. 48 individuals with variable sizes of D. gigantea of the depth of 15m were tagged with flagging tapes and plastic films, and then monitored with two month intervals. The average mortality of two-month term for the study period was 50.4%, with the peak of 84.6% during the summer storms in August - October 2003. About the size class mortality, individuals of size class I(${\leq}$10 cm) showed the highest mortality, followed by size class III(>20 cm) and size class II(10 cm-20 cm). Growth rate did not show a seasonal pattern. For growth in length, individuals of D. gigantea grew about 3cm in average for two-month period, with a maximum growth of 6.4 cm which occurred in August - October 2003. For growth in diameter, individuals grew about 0.3 cm for 2 month term, with a maximum of 1.4cm in April - June 2004. Individuals of size class I usually grew faster than those of larger size classes. D. gigantea population in Jejudo Island was strongly affected by summer storms, which was due to annual event of summer typhoon. Never the less, it appears that the local population can be maintained by fast growth of the juvenile stage and active recruitment to compensate the high mortality caused by the summer disturbance.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.17 no.1
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• pp.31-37
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• 2024

In this study, we propose a machine vision-based pedestrian signal detection algorithm that operates efficiently even in computing resource-constrained environments. This algorithm demonstrates high efficiency within limited resources and is designed to minimize the impact of ambient lighting by sequentially applying HSV color space-based image processing, binarization, morphological operations, labeling, and other steps to address issues such as light glare. Particularly, this algorithm is structured in a relatively simple form to ensure smooth operation within embedded system environments, considering the limitations of computing resources. Consequently, it possesses a structure that operates reliably even in environments with low computing resources. Moreover, the proposed pedestrian signal system not only includes pedestrian signal detection capabilities but also incorporates IoT functionality, allowing wireless integration with a web server. This integration enables users to conveniently monitor and control the status of the signal system through the web server. Additionally, successful implementation has been achieved for effectively controlling 50W LED pedestrian signals. This proposed system aims to provide a rapid and efficient pedestrian signal detection and control system within resource-constrained environments, contemplating its potential applicability in real-world road scenarios. Anticipated contributions include fostering the establishment of safer and more intelligent traffic systems.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.37 no.1
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• pp.9-16
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• 2024

Using the proper orthogonal decomposition (POD) based intrusive reduced order model (ROM), the total degrees of freedom of the structural system can be significantly reduced and the critical time step satisfying the conditional stability increases in the explicit time integrations. In this study, therefore, the changes in the critical time step in the explicit time integrations are investigated using both the POD-ROM and Voronoi-cell lattice model (VCLM). The snapshot matrix is composed of the data from the structural response under the arbitrary dynamic loads such as seismic excitation, from which the POD-ROM is constructed and the predictive capability is validated. The simulated results show that the significant reduction in the computational time can be achieved using the POD-ROM with sufficiently ensuring the numerical accuracy in the seismic analyses. In addition, the validations show that the POD based intrusive ROM is compatible with the Voronoi-cell lattice based explicit dynamic analyses. In the future study, the research results will be utilized as an elemental technology for the developments of the real-time predictive models or monitoring system involving the high-fidelity simulations of structural dynamics.