• Journal of Broadcast Engineering
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• v.25 no.5
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• pp.698-708
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• 2020

VVC (Versatile Video Coding), which has been developing as a next generation video coding standard. Compared to HEVC (High Efficiency Video Coding), VVC is improved by about 34% in RA (Random Access) configuration and about 30% in LDB (Low-Delay B) configuration by adopting various techniques such as recursive block partitioning structure and GPM (Geometric Partitioning Mode). But the encoding complexity is increased by about 10x and 7x, respectively. In this paper, we propose a fast decision method of GPM mode and block partitioning using directionality of block to reduce encoding complexity of VVC. The proposed method is to apply the Hough transform to the current block to identify the directionality of the block, thereby determining the GPM mode and the specific block partitioning method to be skipped in the rate-distortion cost search process. As a result, compared to VTM8.0, the proposed method reduces about 31.01% and 29.84% encoding complexity for RA and LDB configuration with 2.48% and 2.69% BD-rate loss, respectively.

• The Sea:JOURNAL OF THE KOREAN SOCIETY OF OCEANOGRAPHY
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• v.26 no.4
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• pp.307-326
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• 2021

Real-time sea level observations from tide gauges include missing and erroneous values. Classification as abnormal values can be done for the latter by the quality control procedure. Although the 3𝜎 (three standard deviations) rule has been applied in general to eliminate them, it is difficult to apply it to the sea-level data where extreme values can exist due to weather events, etc., or where erroneous values can exist even within the 3𝜎 range. An artificial intelligence model set designed in this study consists of non-annotated recurrent neural networks and ensemble techniques that do not require pre-labeling of the abnormal values. The developed model can identify an erroneous value less than 20 minutes of tide gauge recording an abnormal sea level. The validated model well separates normal and abnormal values during normal times and weather events. It was also confirmed that abnormal values can be detected even in the period of years when the sea level data have not been used for training. The artificial neural network algorithm utilized in this study is not limited to the coastal sea level, and hence it can be extended to the detection model of erroneous values in various oceanic and atmospheric data.

• Science of Emotion and Sensibility
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• v.26 no.2
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• pp.129-140
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• 2023

Following ISO 20471, in this study, first, two sets of safety clothes and safety vests were made by designing and attaching animal and bird patterns preferred by children to retroreflective films and black fabrics on those fluorescent fabrics and retroreflective materials prescribed by international standards. Second, by mounting a smart photonic device on the safety clothing so that the body can be recognized from a distance even without an ambient light source at night, children can emit three types of light depending on the situation with just one-touch of the button. From a result of comparison with visibility a day and night by dressing a mannequin in the made smart safety clothing, the difference in visibility was evident at night, it was confirmed that we can see the figure of a person even at a distance of approximately 70 m. Therefore, it is expected to contribute to the prevention of traffic and other accidents on the road, as the drivers driving at night or in bad weather can recognize a person from a distance. Third, in case of the energy is exhausted and cannot maintain the stability of the light-emitting function of the optical faber, we can use energy harvesting device, and the light-emitting time will be extended. As a result it comes up to emit light stably for a long time. And this prove that smart photonic safety clothing can also be used for night workers. Therefore, optical fiber safety clothing is expected to be highly wearable not only in real life but also in dark industrial sites due to stable charging by applying the energy harvesting provided by solar cells.

• The Mathematical Education
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• v.61 no.1
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• pp.1-28
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• 2022

The purpose of this study is to explore how students' fractional knowledge is related to their solving of proportion problems. To this end, 28 clinical interviews with four middle-grade students, each lasting about 30~50 minutes, were carried out from May 2021 to August 2021. The present study focuses on two 7th grade students who exhibited their ability to coordinate three levels of units prior to solving whole number problems. Although the students showed interiorization of three levels of units in solving whole number problems, how they coordinated three levels of units were different in solving proportion problems depending on whether the problems required reasoning with whole numbers or fractions. The students could coordinate three levels of units prior to solving the problems involving whole numbers, they coordinated three levels of units in activity for the problems involving fractions. In particular, the ways the two students employed partitioning operations and how they coordinated quantitative unit structures were different in solving proportion problems involving improper fractions. The study contributes to the field by adding empirical data corroborating the hypotheses that students' ability to transform one three levels of units structure into another one may not only be related to their interiorization of recursive partitioning operations, but it is an important foundation for their construction of splitting operations for composite units.

• Journal of the Institute of Electronics and Information Engineers
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• v.52 no.12
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• pp.109-117
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• 2015

In this paper, we proposed error-reducing method to source or measure a current or voltage for LED in the I-V characteristic analysis system using a digital signal processor (DSP). this method has the advantage of reducing a non-linear circuit error and random error. random error can be reduced using recursive averaging technique and non-linear circuit error can be reduced using 2rd polynomial regression calibration parameters fitting with measured sample data. it corrects measured error of IR, VR, VF1, VF2, VF3 of LED using calibration parameters. experimental results show that can be performed with about 0.017~0.043% accuracy.

• The Journal of the Korea institute of electronic communication sciences
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• v.16 no.2
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• pp.329-338
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• 2021

This study predicts the amount of wind power generation for rational operation plan of wind power generation and capacity calculation of ESS. For forecasting, we present a method of predicting wind power generation by combining a physical approach and a statistical approach. The factors of wind power generation are analyzed and variables are selected. By collecting historical data of the selected variables, the amount of wind power generation is predicted using deep learning. The model used is a hybrid model that combines a bidirectional long short term memory (LSTM) and a convolution neural network (CNN) algorithm. To compare the prediction performance, this model is compared with the model and the error which consist of the MLP(:Multi Layer Perceptron) algorithm, The results is presented to evaluate the prediction performance.

• School Mathematics
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• v.19 no.3
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• pp.553-570
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• 2017

The purpose of this study was to gain insights into investigating the feasibility on integrating computational thinking(CT) into school mathematics. Definitions and the components of CT were varied among studies. In this study, CT in mathematics was focused on thinking related with mathematical problem solving under ICT supportive environment where computing tools are available to students to solve problems and verify their answers. The focus is not given on the computing environment itself but on CT in mathematics education. For integrating CT into mathematical problem solving, providing computing environment, understanding of tools and supportive curriculum revisions for integration are essential. Coding with language specially developed for mathematics education such as LOGO, and solving realistic mathematical problems using S/W such as Excel in mathematics classrooms, or integrating CT into math under STEAM contexts are suggested for integration CT into math education. Several conditions for the integration were discussed in this paper.

• Journal of the Korean Association of Oral and Maxillofacial Surgeons
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• v.25 no.4
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• pp.371-374
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• 1999

The treatment of adults with dentofacial deformities is frequently complicated by existence of discrepancies in transverse dimension. Control of the transverse dimension through surgical technique is now a valuable treatment consideration in non-growing patients. Proper diagnosis of relative and absolute maxillary transverse deficiency is imperative prior to surgical intervention. Therapeutic purpose should be implemented accordingly to facilitate correction of transverse discrepancies concomitant with treatment objectives in sagittal dimension in order to provide the patient with the most stable and functional result possible. Concomitant surgical correction of narrow palate require less treatment time, treatment cost and post-treatment relapse is less than to do only orthodontic therapy. This report is concerned with rapid palatal expansion by a combination of corticotomy and orthodontic treatment.

• Journal of Korea Multimedia Society
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• v.9 no.11
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• pp.1395-1409
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• 2006

A spatial data warehouse has spatial data cube composed of multi-dimensional data for efficient OLAP(On-Line Analytical Processing) operations. A spatial data cube supporting concept hierarchies holds huge amount of data so that many researches have studied a incremental update method for minimum modification of a spatial data cube. The Cube, however, compressed by eliminating prefix and suffix redundancy has coalescing paths that cause update inconsistencies for some updates can affect the aggregate value of coalesced cell that has no relationship with the update. In this paper, we propose incremental batch update method of a spatial data cube. The proposed method uses duplicated nodes and extended node structure to avoid update inconsistencies. If any collision is detected during update procedure, the shared node is duplicated and the duplicate is updated. As a result, compressed spatial data cube that includes concept hierarchies can be updated incrementally with no inconsistency. In performance evaluation, we show the proposed method is more efficient than other naive update methods.

• Journal of the Korea Society of Computer and Information
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• v.17 no.12
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• pp.149-158
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• 2012

Proposed is a hybrid randomizing function using two asymptotically optimal randomizing functions: Elias function and Peres function. Randomizing function is an mathematical abstraction of producing a uniform random bits from a source of randomness with bias. It is known that the output rate of Elias function and Peres function approaches to the information-theoretic upper bound. Especially, for each fixed input length, Elias function is optimal. However, its computation is relatively complicated and depends on input lengths. On the contrary, Peres function is defined by a simple recursion. So its computation is much simpler, uniform over the input lengths, and runs on a small footprint. In view of this tradeoff between computational complexity and output efficiency, we propose a hybrid randomizing function that has strengths of the two randomizing functions and analyze it.