• Journal of Intelligence and Information Systems
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• v.18 no.4
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• pp.43-57
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• 2012

To enhance the competitive advantage in a constantly changing business environment, an enterprise management must make the right decision in many business activities based on both internal and external information. Thus, providing accurate information plays a prominent role in management's decision making. Intuitively, historical data can provide a feasible estimate through the forecasting models. Therefore, if the service department can estimate the service quantity for the next period, the service department can then effectively control the inventory of service related resources such as human, parts, and other facilities. In addition, the production department can make load map for improving its product quality. Therefore, obtaining an accurate service forecast most likely appears to be critical to manufacturing companies. Numerous investigations addressing this problem have generally employed statistical methods, such as regression or autoregressive and moving average simulation. However, these methods are only efficient for data with are seasonal or cyclical. If the data are influenced by the special characteristics of product, they are not feasible. In our research, we propose a forecasting framework that predicts service demand of manufacturing organization by combining Case-based reasoning (CBR) and leveraging an unsupervised artificial neural network based clustering analysis (i.e., Self-Organizing Maps; SOM). We believe that this is one of the first attempts at applying unsupervised artificial neural network-based machine-learning techniques in the service forecasting domain. Our proposed approach has several appealing features : (1) We applied CBR and SOM in a new forecasting domain such as service demand forecasting. (2) We proposed our combined approach between CBR and SOM in order to overcome limitations of traditional statistical forecasting methods and We have developed a service forecasting tool based on the proposed approach using an unsupervised artificial neural network and Case-based reasoning. In this research, we conducted an empirical study on a real digital TV manufacturer (i.e., Company A). In addition, we have empirically evaluated the proposed approach and tool using real sales and service related data from digital TV manufacturer. In our empirical experiments, we intend to explore the performance of our proposed service forecasting framework when compared to the performances predicted by other two service forecasting methods; one is traditional CBR based forecasting model and the other is the existing service forecasting model used by Company A. We ran each service forecasting 144 times; each time, input data were randomly sampled for each service forecasting framework. To evaluate accuracy of forecasting results, we used Mean Absolute Percentage Error (MAPE) as primary performance measure in our experiments. We conducted one-way ANOVA test with the 144 measurements of MAPE for three different service forecasting approaches. For example, the F-ratio of MAPE for three different service forecasting approaches is 67.25 and the p-value is 0.000. This means that the difference between the MAPE of the three different service forecasting approaches is significant at the level of 0.000. Since there is a significant difference among the different service forecasting approaches, we conducted Tukey's HSD post hoc test to determine exactly which means of MAPE are significantly different from which other ones. In terms of MAPE, Tukey's HSD post hoc test grouped the three different service forecasting approaches into three different subsets in the following order: our proposed approach > traditional CBR-based service forecasting approach > the existing forecasting approach used by Company A. Consequently, our empirical experiments show that our proposed approach outperformed the traditional CBR based forecasting model and the existing service forecasting model used by Company A. The rest of this paper is organized as follows. Section 2 provides some research background information such as summary of CBR and SOM. Section 3 presents a hybrid service forecasting framework based on Case-based Reasoning and Self-Organizing Maps, while the empirical evaluation results are summarized in Section 4. Conclusion and future research directions are finally discussed in Section 5.

• The Journal of Korean Academy of Prosthodontics
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• v.59 no.3
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• pp.261-270
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• 2021

Purpose. The aim of this study was (1) to compare the reverse engineering technique with other existing measurement methods and (2) to analyze the effect of implant angulations and impression coping types on implant impression accuracy with reverse engineering technique. Materials and methods. Three different master models were fabricated and the distance between the two implant center points in parallel master model was measured with different three methods; digital caliper measurement (Group DC), optical measuring (Group OM), and reverse engineering technique (Group RE). The 90 experimental models were fabricated with three types of impression copings for the three different implant angulation and the angular and distance error rate were calculated. One-way ANOVA was used for comparison among the evaluation methods (P < .05). The error rates of experimental groups were analyzed by two-way ANOVA (P < .05). Results. While there was significant difference between Group DC and RE (P < .05), Group OM had no significant difference compared with other groups (P > .05). The standard deviations in reverse engineering were much lower than those of digital caliper and optical measurement. Hybrid groups had no significant difference from the pick-up groups in distance error rates (P > .05). Conclusion. The reverse engineering technique demonstrated its potential as an evaluation technique of 3D accuracy of impression techniques.

• Journal of the Institute of Electronics and Information Engineers
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• v.53 no.7
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• pp.27-38
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• 2016

This work proposes a 12b 30MS/s 0.18um CMOS SAR ADC based on low-power composite switching with an active die area of $0.16mm^2$. The proposed composite switching employs the conventional $V_{CM}$-based switching and monotonic switching sequences while minimizing the switching power consumption of a DAC and the dynamic offset to constrain a linearity of the SAR ADC. Two equally-divided capacitors topology and the reference scaling are employed to implement the $V_{CM}$-based switching effectively and match an input signal range with a reference voltage range in the proposed C-R hybrid DAC. The techniques also simplify the overall circuits and reduce the total number of unit capacitors up to 64 in the fully differential version of the prototype 12b ADC. Meanwhile, the SAR logic block of the proposed SAR ADC employs a simple latch-type register rather than a D flip-flop-based register not only to improve the speed and stability of the SAR operation but also to reduce the area and power consumption by driving reference switches in the DAC directly without any decoder. The measured DNL and INL of the prototype ADC in a 0.18um CMOS are within 0.85LSB and 2.53LSB, respectively. The ADC shows a maximum SNDR of a 59.33dB and a maximum SFDR of 69.83dB at 30MS/s. The ADC consumes 2.25mW at a 1.8V supply voltage.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.48 no.6
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• pp.8-17
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• 2011

Recently, fusion camera systems that consist of depth sensors and color cameras have been widely developed with the advent of a new type of sensor, time-of-flight (TOF) depth sensor. The physical limitation of depth sensors usually generates low resolution images compared to corresponding color images. Therefore, the pre-processing module, such as camera calibration, three dimensional warping, and hole filling, is necessary to generate the high resolution depth map that is placed in the image plane of the color image. However, the result of the pre-processing step is usually inaccurate due to errors from the camera calibration and the depth measurement. Therefore, in this paper, we present a depth map upsampling method robust these errors. First, the confidence of the measured depth value is estimated by the interrelation between the color image and the pre-upsampled depth map. Then, the detailed depth map can be generated by the modified kernel regression method which exclude depth values having low confidence. Our proposed algorithm guarantees the high quality result in the presence of the camera calibration errors. Experimental comparison with other data fusion techniques shows the superiority of our proposed method.

• Horticultural Science & Technology
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• v.33 no.6
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• pp.941-946
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• 2015

A new Doritaenopsis cultivar 'Hwasu 5205' was bred by Kyungpook National University, Korea, which produces young plants through tissue culture techniques. The new cultivar 'Hwasu 5205', showing the phenotype of vivid red and large flower type characteristics, was derived from crossing between Phalaenopsis Happy Valentine and Doritaenopsis Happy Rose. An elite individual, number '02-05-205' later named as 'Hwasu 5205', was selected among about 300 individual progenies after more than 2 years of intensive selection covering vegetative and flowering distinctiveness. In year 2004-2005, 1st and 2nd characteristic analyses were carried out through performance and uniformity tests. 'Hwasu 5205' produces vivid red (RHS #PN78B) flowers of i ncurved type with large size, of 9.2 and 12.0 cm in flower height and width, respectively. Leaves of 'Hwasu 5205' grow horizontally and are about 24.3cm in length and 8.5cm in width, respectively. This cultivar possesses no genetic variation. It can be propagated rapidly in vitro and is easy to grow due to its vigorous growth habit. 'Hwasu 5205' was registered (Reg. #: 2915) to Korea Seed & Variety Service (KSVS) on 1st December, 2009 and the PBR(plant breeder's right)is currently controlled by Sangmiwon Orchid Company, Korea.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.38 no.4
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• pp.579-586
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• 2018

Short-term prediction of travel speed has been widely studied using data-driven non-parametric techniques. There is, however, a lack of research on the prediction aimed at urban areas due to their complex dynamics stemming from traffic signals and intersections. The purpose of this study is to develop a hybrid approach combining ensemble empirical mode decomposition (EEMD) and artificial neural network (ANN) for predicting urban travel speed. The EEMD decomposes the time-series data of travel speed into intrinsic mode functions (IMFs) and residue. The decomposed IMFs represent local characteristics of time-scale components and they are predicted using an ANN, respectively. The IMFs can be predicted more accurately than their original travel speed since they mitigate the complexity of the original data such as non-linearity, non-stationarity, and oscillation. The predicted IMFs are summed up to represent the predicted travel speed. To evaluate the proposed method, the travel speed data from the dedicated short range communication (DSRC) in Daegu City are used. Performance evaluations are conducted targeting on the links that are particularly hard to predict. The results show the developed model has the mean absolute error rate of 10.41% in the normal condition and 25.35% in the break down for the 15-min-ahead prediction, respectively, and it outperforms the simple ANN model. The developed model contributes to the provision of the reliable traffic information in urban transportation management systems.

• Korean Journal of Animal Reproduction
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• v.20 no.4
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• pp.371-378
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• 1997

Human lactoferrin (hLF) was expressed in the mammary gland of transgenic mice. Expresion of hLF was achieved by palcing its cDNA under the control of bovine $\beta$-casein gene. To improve the hLF expression level, two artificial introns were introduced into the expression vector. One intron is a hybrid-splice consisting of bovine $\beta$ casein intron 1 and rabbit $\beta$-casem intron II. The other intron is a DNA fragment spanning intron 8 of bovine $\beta$ casein gene. Trans sgenic mice were developed which expressed hLF in their milk. Twenty lines of transgenic mice were produced. hLF was present in the milk at concentrations of 1 ~ 200 ${\mu}\textrm{g}$ / ml. hLF RNA was only detected in the mammary gland of transgenic mice. The expressed RNA was cor r rectly spliced at the exon /intron junctions. To generate transgenic cows secreting active hLF in their milk, we transferred the DNA-injected bovine embryos to recipient heifers by surgical a and non-surgical methods out of 68 embryos transferred to 51 recipients by surgical or non-surgical method, 7 calves were normally born. Effect of embryo quality of DNA-injected blastocysts on pregnancy rate after transfer was investig a ated. Higher pregnancy rate of (38.9%) DNA-injected embryos was shown in excellent embryos. Pregnancy rates in the groups of good a and fair embryos were 15.4 and 14.3%, respectively. Effect of culture period of DNA-injected b bovine embryos on pregnancy rate after transfer was investigated. When Day-6 blastocysts of cuI ture were transferred, there was no pregnancy. Pregnancy rates of Day-7 and -8 blastocysts were 28.6 and 33.3%, respectively. There was no difference on pregnancy rate between Day-7 a and -8 bovine blastocysts after DNA injection. Thus, we established the techniques for transfer a and culture of DNA-injected bovine embryos. In a addition, factors affecting the pregnancy rate of DNA-injected embryos after transfer were investigated .

• Journal of Broadcast Engineering
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• v.9 no.1
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• pp.17-31
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• 2004

This paper proposes an algorithm for the robust transmission of video in error Prone environment using multiple description codingby optimal split of DCT coefficients and rate-distortionoptimization framework. In MDC, a source signal is split Into several coded streams, which is called descriptions, and each description is transmitted to the decoder through different channel. Between descriptions, structured correlations are introduced at the encoder, and the decoder exploits this correlation to reconstruct the original signal even if some descriptions are missing. It has been shown that the MDC is more resilient than the singe description coding(SDC) against severe packet loss ratecondition. But the excessive redundancy in MDC, i.e., the correlation between the descriptions, degrades the RD performance under low PLR condition. To overcome this Problem of MDC, we propose a hybrid MDC method that controls the SDC/MDC switching according to channel condition. For example, the SDC is used for coding efficiency at low PLR condition and the MDC is used for the error resilience at high PLR condition. To control the SDC/MDC switching in the optimal way, RD optimization framework are used. Lagrange optimization technique minimizes the RD-based cost function, D+M, where R is the actually coded bit rate and D is the estimated distortion. The recursive optimal pet-pixel estimatetechnique is adopted to estimate accurate the decoder distortion. Experimental results show that the proposed optimal split of DCT coefficients and SD/MD switching algorithm is more effective than the conventional MU algorithms in low PLR conditions as well as In high PLR condition.

• Journal of Wetlands Research
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• v.15 no.4
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• pp.535-541
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• 2013

The urbanization affects significantly on a natural water circulation system by increasing the imperviousness rate. It is also negatively affecting on urban temperature, environmental pollution, water quality, and aqua-ecosystems. The Korea MOE (Ministry of Environment) adapted a new environmental policy in order to reduce the impact of urbanization, which is the Green Stormwater Infrastructure (GSI) program. The GSI can be achieved by protecting conservable green spaces, enlarging more green spaces, and constructing more permeable pavements. The GSI is including many different techniques such as bioretention, rain garden, infiltration trench and so on. Also It is the infrastructures using natural mechanisms of soils, microorganisms, plants and animals on a water circulation system and pollutant reduction. In this research, a multi functional GSI technology with infiltration-filtration mechanisms has been developed and performed lab-scale tests to evaluate the performances about infiltration rate restoration and pollutant reduction. The most of pollutants including metals, organics and particulates were reduced about 50~90% due to water infiltration and storage functions. The clogging was found when the TSS loading rate was reached on $8.3{\sim}9.0kg/m^2$, which value is higher than the values in literatures. It means the new technology can show high performances with low maintenances.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.47 no.6
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• pp.28-39
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• 2010

The study aims at offering a solution to the problems of transmission delay and data throughput decrease as the number of contending On-Board Units (OBU) increases by applying CSMA medium access control protocol based upon IEEE 802.11p. In a competition-based medium, contention probability becomes high as OBU increases. In order to improve the performance of this medium access layer, the author proposes EDCA which a adaptive adjustment of the Contention Windows (CW) considering traffic density and data type. EDCA applies fixed values of Minimum Contention Window (CWmin) and Maximum Contention Window (CWmax) for each of four kinds of Access Categories (AC) for channel-specific service differentiation. EDCA does not guarantee the channel-specific features and network state whereas it guarantees inter-AC differentiation by classifying into traffic features. Thus it is not possible to actively respond to a contention caused by network congestion occurring in a short moment in channel. As a solution, CWminAS(CWmin Adaptation Scheme) and ACATICT(Adaptive Contention window Adjustment Technique based on Individual Class Traffic) are proposed as active CW control techniques. In previous researches, the contention probabilities for each value of AC were not examined or a single channel based AC value was considered. And the channel-specific demands of IEEE 802.11p and the corresponding contention probabilities were not reflected in the studies. The study considers the collision number of a previous service section and the current network congestion proposes a dynamic control technique ACCW(Adaptive Control of Contention windows in considering the WAVE situation) for CW of the next channel.