• KIPS Transactions on Software and Data Engineering
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• v.9 no.1
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• pp.33-38
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• 2020

This paper proposes a technique for counting construction materials by analyzing an image acquired by a Drone. The proposed technique use drone log which includes drone and camera information, RCNN for predicting construction material type, dummy area and Photogrammetry for counting the number of construction material. The existing research has large error ranges for predicting construction material detection and material dummy area, because of a lack of training data. To reduce the error ranges and improve prediction stability, this paper increases the training data with a method of data augmentation, but only uses rotated training data for data augmentation to prevent overfitting of the training model. For the quantity calculation, we use a drone log containing drones and camera information such as Yaw and FOV, RCNN model to find the pile of building materials in the image and to predict the type. And we synthesize all the information and apply it to the formula suggested in the paper to calculate the actual quantity of material pile. The superiority of the proposed method is demonstrated through experiments.

• Journal of the Korean School Mathematics Society
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• v.11 no.1
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• pp.97-115
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• 2008

In high school mathematics class, to subtract a number b from a, we add the additive inverse of b to a and to divide a number a by a non-zero number b, we multiply a by the multiplicative inverse of b, which is the formal approach for operations of real numbers. This article aims to give a connection between the intuitive models in middle school mathematics class and the formal approach in high school for teaching operations of negative integers. First, we highlight the teaching methods(Hwang et al, 2008), by which subtraction of integers is denoted by addition of integers. From this methods and activities applying the counting model, we give new teaching methods for the rule that the product of negative integers is positive. The teaching methods with horizontal mathematization(Treffers, 1986; Freudenthal, 1991) of operations of integers, which is based on consistently applying the intuitive model(number line model, counting model), will remove the gap, which is exist in both teachers and students of middle and high school mathematics class. The above discussion is based on students' cognition that the number system in middle and high school and abstracted number system in abstract algebra course is formed by a conceptual structure.

• Journal of IKEEE
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• v.28 no.2
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• pp.150-157
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• 2024

In this paper, we propose a novel algorithm for predicting the number of apples on an apple tree using a deep learning-based object detection model and a polynomial regression model. Measuring the number of apples on an apple tree can be used to predict apple yield and to assess losses for determining agricultural disaster insurance payouts. To measure apple fruit load, we photographed the front and back sides of apple trees. We manually labeled the apples in the captured images to construct a dataset, which was then used to train a one-stage object detection CNN model. However, when apples on an apple tree are obscured by leaves, branches, or other parts of the tree, they may not be captured in images. Consequently, it becomes difficult for image recognition-based deep learning models to detect or infer the presence of these apples. To address this issue, we propose a two-stage inference process. In the first stage, we utilize an image-based deep learning model to count the number of apples in photos taken from both sides of the apple tree. In the second stage, we conduct a polynomial regression analysis, using the total apple count from the deep learning model as the independent variable, and the actual number of apples manually counted during an on-site visit to the orchard as the dependent variable. The performance evaluation of the two-stage inference system proposed in this paper showed an average accuracy of 90.98% in counting the number of apples on each apple tree. Therefore, the proposed method can significantly reduce the time and cost associated with manually counting apples. Furthermore, this approach has the potential to be widely adopted as a new foundational technology for fruit load estimation in related fields using deep learning.

• The Korean Journal of Applied Statistics
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• v.25 no.5
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• pp.859-864
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• 2012

Poisson regression and negative binomial regression are usually used to analyze counting data; however, these models are unsuitable for fit zero-inflated data that contain unexpected zero-valued observations. In this paper, we review the zero-inflated regression in which Bernoulli process and the counting process are hierarchically mixed. It is known that zero-inflated regression can efficiently model the over-dispersion problem. Vuong statistic is employed to compare performances of the zero-inflated models with other standard models.

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.18 no.3
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• pp.323-334
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• 2008

According to the delivery condition, the breakage of a product occurs when it is delivered to the customers. Therefore product's makers evaluate the durability under the delivery process by accelerated life testing. In order to conduct this accelerated life testing accurately, it is very important to identify the acceleration-factor exactly between on-road and accelerated life test condition. In this paper, the acceleration-factor is identified by applying linear damage summation law, rain-flow cycle counting and Dirlik theory under the conditions of the random vibration. And approximated FEM model of the connecting-pipe to the compressor is developed for fatigue analysis. This model is finally verified by comparing the experiment results to the numerical analysis results.

• Journal of Educational Research in Mathematics
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• v.8 no.2
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• pp.527-540
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• 1998

In the teacher's guide of mathematics textbook for the 1st grade of the middle school, the clear and logical reason why the multiplication of negative number to negative number makes positive number, and $a^{-m}$ with a>0 and m>0, is defined by ${\frac{1}{a^m}}$ is not given. When we define the multiplication or the power by successive addition or successive multiplication of the same number, respectively, we encounter this ambiguity, in the case that the number of successive operations is negative, In this paper, we name this number, negative counting number, and we make the following more logical and intuitive definition, which is "negatively many successive operations is defined by positively many successive inverse operations." According to this new definition, we define the multiplication by the successive addition or the successive subtraction of the same number, when the multiplier is positive or negative respectively, and the power by the successive multiplication or the power is positive or negative, respectively. In addition, using this new definition and following the E.R.S Instruction strategy which revised and complemented the Bruner's E.I.S Instruction strategy, we develope new teaching model available in the 1st grade class of middle school where the concept of integers, three operations of integers are introduced.ntroduced.

• Korean Journal of Optics and Photonics
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• v.2 no.4
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• pp.203-208
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• 1991

We investigated the nonradiative energy transfer process from Rhodamine 6G to Malachite Green in ethylen glycol solvent using time correlated single photon counting system equipped with a modelocked Ar ' laser. The reduced concentration and critical transfer distance for various acceptor concentration were obtained by using a full-fitting analysis of the fluorescence decay curves. We found that Huber model is more suitable than Forster model and the influence of energy migration through the dipole-dipole interaction becomes more significant for the low acceptor concentrations relative to the donor concentration($5\times 10^4$mol/l).

• Journal of Internet of Things and Convergence
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• v.5 no.2
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• pp.67-72
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• 2019

As Internet voting can take place regardless of a voter's location, the participation rate of the voters would be increased and economic costs will be reduced. But the drawback of it is that all participants have to trust the election management server. If the server colludes with the specific candidate, the other candidates cannot prove rigged election. In addition, majority of researches on Internet voting are mainly focused on the voting restricted by the region and the country. Thus, it's not appropriate for the election in Internet community such as YouTube channels. As the Internet community is composed of members from all around the world, the new type of voting model is needed. In this study, we propose the smart contract based Internet voting model applicable on the blockchain network. The proposed smart contract model consists of candidate registration, voter registration, voting and counting stages. In the proposed model, anonymity of the voter is assured in the voter registration and voting stages, and all candidates can confirm the fairness of the election in the counting stage.

• Korean Journal of Remote Sensing
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• v.23 no.6
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• pp.567-573
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• 2007

Tidal channel development is influenced by sediment type, grain size, composition and tidal current. Tidal channels are usually characterized by channel formation, density and shape. Quantitative analysis of tidal channels using remotely sensed data have rarely been studied. The objective of this study is to quantify tidal channels in terms of fractal dimension and compare different inter-tidal channel patterns and compare with DEM (Digital Elevation Model). For the fractal analysis, we used box counting method which had been successfully applied to streams, coastlines and others linear features. For a study, the southern part of Ganghwado tidal flats was selected which know for high dynamics of tidal currents and vast tidal flats. This area has different widths and lengths of tidal channels. IKONOS was used for extracting tidal channels, and the box counting method was applied to obtain fractal dimensions (D) for each tidal channel. Yeochari area where channels showed less dense development and low DEM had low fractal dimenwion near $1.00{\sim}1.20$. Area (near Donggumdo and Yeongjongdo) of dendritic channel pattern and high DEM resulted in high fractal dimension near $1.20{\sim}1.35$. The difference of fractal dimensions according to channel development in tidal flats is relatively large enough to use as an index for tidal channel classification. Therefore we could conclude that fractal dimension, channel development and DEM in tidal channel has high correlation. Using fractal dimension, channel development and DEM, it would be possible to quantify the tidal channel development in association with surface characteristics.

• Journal of the Korean Data and Information Science Society
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• v.16 no.4
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• pp.1147-1157
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• 2005

Bonus-Malus system is generally constructed based on claim frequency and Bayesian credibility model is used to represent claim frequency distribution. However, there is a problem with traditionally used credibility model for the purpose of constructing bonus-malus system. In traditional Bonus-Malus system adopted credibility model, individual estimates of premium rates for insureds are determined based solely on the total number of claim frequency without considering when those claims occurred. In this paper, a new model which is a modification of structural time series model applicable to counting time series data are suggested. Based on the suggested model relatively higher premium rates are charged to insured with more claim records.