• Journal of Environmental Policy
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• v.13 no.3
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• pp.109-133
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• 2014

With a growing concern about climate change and green house gases mitigation, carbon labeling policy has been launched in several countries as an environmental policy which connects low carbon production to low carbon consumption. This research aims to propose a model that explains consumers' attitude and brand loyalty toward carbon labeling products. This model specifies the consumer's psychological processes by which consumer values, such as autonomy and environmental values, affect carbon labeling product and corporate images and finally form brand loyalty toward carbon labeling products. Panel data were collected in two separate surveys and analyzed using a structural equation technique. Results are summarized as follows. First, consumers' autonomy value(AV) positively affects locus of control(LC) and corporate image(CI). Second, consumers' environmental value(EV) positively influences perceived consumer effectiveness(PCE), which in turn has a negative effect on perceived barriers(PB). Perceived barriers finally affect product image(PI) negatively. Third, both corporate image and product image have causal relationships with brand loyalty. Our results suggest that carbon labeling policy contributes not only to the reduction of greenhouse gases but also to the increase of consumers' attitude and brand loyalty toward carbon labeling products. This research also provides governments with directions for efficient environmental policy and firms with guidance on effective marketing strategies about carbon labeling.

• The KIPS Transactions:PartD
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• v.9D no.4
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• pp.587-602
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• 2002

Replicated database system was emerged to resolve the problem of reduction of the availability and the reliability due to the communication failures and site errors generated at centralized database system. But if update transactions are many occurred, the update is equally executed for all replicated data. Therefore, there are many problems the same thing a message overhead generated by synchronization and the reduce of concurrency happened because of delaying the transaction. In this paper, I propose a new concurrency control algorithm for enhancing the degree of parallelism of the transaction in fully replicated database designed to improve the availability and the reliability. To improve the system performance in the replicated database should be performed the last operations in the submitted site of transactions and be independently executed update-only transactions composed of write-only transactions in all sites. I propose concurrency control method to maintain the consistency of the replicated database and reflect the result of update-only transactions in all sites. The superiority of the proposed method has been tested from the respondence and withdrawal rate. The results confirm the superiority of the proposed technique over classical correlation based method.

• The Korean Journal of Quaternary Research
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• v.18 no.1 s.22
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• pp.1-20
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• 2004

A geoscientific research was performed on 12 samples of comb-pattern potteries which were excavated at Daecheonri neolithic site, Korea. The texture and compositions of 12 potteries and surrounding metrix of soil and rocks were compared with the help of petrographic microscope, XRD and REE data. As to the manufacturing techniques thick potteries are caused by the amount and number of coarse grains which are assumed to be added shards when their distributional pattern are considered. DC1, DC3, DC 7 and DC11 samples have clearly oriented textures, and the orientation of vesicles in DC3 and DC11 samples arranged in the same direction with those on the pottery surface. This indicates the use potter's wheel technique in manufacturing potteries. Burning temperature is assumed over $800^{/circ}C$, particularly under reduction environment. As to the source, raw materials of pottery matrix are derived from the bottom of excavation site, or in an extracted outcrop of the northwestern foothill from site, while the shard materials are very similar with those extracted from sandy loams near sites. Finally any use pattern of pottery may control the pottery thickness, shard addition, and matrix selection.

• The Korean Journal of Pesticide Science
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• v.9 no.4
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• pp.292-302
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• 2005

Condition of Ion-Trap gas chromatography-mass spectrometry (GC-MS) for rapid screening of 206-pesticides residues in agricultural foodstuffs was optimized. As applying a wide-bore column (10 m${\times}$0.53 mm, DF 0.25 um) connected with a fused silica restrictor (0.6 m${\times}$0.1 mm), a significant retention time reduction was obtained. Additionally, the shape of peaks was sharper and higher than classical GC's and GC-MS's, which allowed lower detection limits. To easily manage many spectral data, both of Electron Ionization(EI) and Chemical Ionization(CI) techniques were adopted in screening procedure. At the following steps, MS-MS technique were used to confirm screened analytes in complicated matrices.

• Journal of the Korean Institute of Intelligent Systems
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• v.22 no.6
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• pp.722-728
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• 2012

Urban sewer systems has a limitation of capacity of rainwater storage and problem of occurrence of untreated sewage, so adopting a storage facility for sewer flooding prevention and urban non-point pollution reduction has a big attention. The Korea Ministry of Environment has recently introduced a new concept of "multi-functional storage facility", which is crucial not only in preventive stormwater management but also in dealing with combined sewer overflow and sanitary sewer discharge, and also has been promoting its adoption. However, reserving a space for a single large-scale storage facility might be difficult especially in urban areas. Thus, decentralized construction of small- and midium-sized storage facilities and its operation have been introduced as an alternative way. In this paper, we propose a model predictive control scheme for an optimized operation of distributed storage facilities and sewer networks. To this aim, we first describe the mathematical model of each component of networks system which enables us to analyze its detailed dynamic behavior. Second, overflow locations and volumes will be predicted based on the developed network model with data on the external inflow occurred at specific locations of the network. MPC scheme based on the introduced particle swarm optimization technique then produces the optimized the gate setting for sewer network flow control, which minimizes sewer flooding and maximizes the potential storage capacity. Finally, the operational efficacy of the proposed control scheme is demonstrated by simulation study with virtual rainstorm event.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2009.05a
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• pp.253-256
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• 2009

This paper describes a core generator (FFT_Core_Gen) which generates Verilog HDL models of 8 different FFT/IFFT cores with $N=64{\times}2^k$($0{\leq}k{\leq}7$ for OFDM-based communication systems. The generated FFT/IFFT cores are based on in-place single memory architecture, and use a hybrid structure of radix-4 and radix-2 DIF algorithm to accommodate various FFT lengths. To achieve both memory reduction and the improved SQNR, a conditional scaling technique is adopted, which conditionally scales the intermediate results of each computational stage, and the internal data and twiddle factor has 14 bits. The generated FFT/IFFT cores have the SQNR of 58-dB for N=8,192 and 63-dB for N=64. The cores synthesized with a $0.35-{\mu}m$ CMOS standard cell library can operate with 75-MHz@3.3-V, and a 8,192-point FFT can be computed in $762.7-{\mu}s$, thus the cores satisfy the specifications of wireless LAN, DMB, and DVB systems.

• Journal of Intelligence and Information Systems
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• v.16 no.4
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• pp.99-112
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• 2010

Ensemble learning is a method for improving the performance of classification and prediction algorithms. It is a method for finding a highly accurateclassifier on the training set by constructing and combining an ensemble of weak classifiers, each of which needs only to be moderately accurate on the training set. Ensemble learning has received considerable attention from machine learning and artificial intelligence fields because of its remarkable performance improvement and flexible integration with the traditional learning algorithms such as decision tree (DT), neural networks (NN), and SVM, etc. In those researches, all of DT ensemble studies have demonstrated impressive improvements in the generalization behavior of DT, while NN and SVM ensemble studies have not shown remarkable performance as shown in DT ensembles. Recently, several works have reported that the performance of ensemble can be degraded where multiple classifiers of an ensemble are highly correlated with, and thereby result in multicollinearity problem, which leads to performance degradation of the ensemble. They have also proposed the differentiated learning strategies to cope with performance degradation problem. Hansen and Salamon (1990) insisted that it is necessary and sufficient for the performance enhancement of an ensemble that the ensemble should contain diverse classifiers. Breiman (1996) explored that ensemble learning can increase the performance of unstable learning algorithms, but does not show remarkable performance improvement on stable learning algorithms. Unstable learning algorithms such as decision tree learners are sensitive to the change of the training data, and thus small changes in the training data can yield large changes in the generated classifiers. Therefore, ensemble with unstable learning algorithms can guarantee some diversity among the classifiers. To the contrary, stable learning algorithms such as NN and SVM generate similar classifiers in spite of small changes of the training data, and thus the correlation among the resulting classifiers is very high. This high correlation results in multicollinearity problem, which leads to performance degradation of the ensemble. Kim,s work (2009) showedthe performance comparison in bankruptcy prediction on Korea firms using tradition prediction algorithms such as NN, DT, and SVM. It reports that stable learning algorithms such as NN and SVM have higher predictability than the unstable DT. Meanwhile, with respect to their ensemble learning, DT ensemble shows the more improved performance than NN and SVM ensemble. Further analysis with variance inflation factor (VIF) analysis empirically proves that performance degradation of ensemble is due to multicollinearity problem. It also proposes that optimization of ensemble is needed to cope with such a problem. This paper proposes a hybrid system for coverage optimization of NN ensemble (CO-NN) in order to improve the performance of NN ensemble. Coverage optimization is a technique of choosing a sub-ensemble from an original ensemble to guarantee the diversity of classifiers in coverage optimization process. CO-NN uses GA which has been widely used for various optimization problems to deal with the coverage optimization problem. The GA chromosomes for the coverage optimization are encoded into binary strings, each bit of which indicates individual classifier. The fitness function is defined as maximization of error reduction and a constraint of variance inflation factor (VIF), which is one of the generally used methods to measure multicollinearity, is added to insure the diversity of classifiers by removing high correlation among the classifiers. We use Microsoft Excel and the GAs software package called Evolver. Experiments on company failure prediction have shown that CO-NN is effectively applied in the stable performance enhancement of NNensembles through the choice of classifiers by considering the correlations of the ensemble. The classifiers which have the potential multicollinearity problem are removed by the coverage optimization process of CO-NN and thereby CO-NN has shown higher performance than a single NN classifier and NN ensemble at 1% significance level, and DT ensemble at 5% significance level. However, there remain further research issues. First, decision optimization process to find optimal combination function should be considered in further research. Secondly, various learning strategies to deal with data noise should be introduced in more advanced further researches in the future.

• Korean Journal of Remote Sensing
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• v.39 no.5_1
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• pp.481-493
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• 2023

In high-density urban areas, the urban heat island effect increases urban temperatures, leading to negative impacts such as worsened air pollution, increased cooling energy consumption, and increased greenhouse gas emissions. In urban environments where it is difficult to secure additional green spaces, rooftop greening is an efficient greenhouse gas reduction strategy. In this study, we not only analyzed the current status of the urban heat island effect but also utilized high-resolution satellite data and spatial information to estimate the available rooftop greening area within the study area. We evaluated the mitigation effect of the urban heat island phenomenon and carbon sequestration capacity through temperature predictions resulting from rooftop greening. To achieve this, we utilized WorldView-2 satellite data to classify land cover in the urban heat island areas of Busan city. We developed a prediction model for temperature changes before and after rooftop greening using machine learning techniques. To assess the degree of urban heat island mitigation due to changes in rooftop greening areas, we constructed a temperature change prediction model with temperature as the dependent variable using the random forest technique. In this process, we built a multiple regression model to derive high-resolution land surface temperatures for training data using Google Earth Engine, combining Landsat-8 and Sentinel-2 satellite data. Additionally, we evaluated carbon sequestration based on rooftop greening areas using a carbon absorption capacity per plant. The results of this study suggest that the developed satellite-based urban heat island assessment and temperature change prediction technology using Random Forest models can be applied to urban heat island-vulnerable areas with potential for expansion.

• Journal of Korean Society of Transportation
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• v.17 no.1
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• pp.29-39
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• 1999

An earlier study of the effect of rain found that the capacity of freeway systems was reduced, but did not address the effects of rain on the nature of traffic flows. Indeed, the substantial variation due to the intensity of adverse weather conditions is entirely rational so that its effects must be considered in freeway facility design. However, all of the data in Highway Capacity Manual(HCM) have come from ideal conditions. The primary objective of this study is to investigate the effect of rain on urban freeway traffic flows in Seoul. To do so, the relations between three key traffic variables(flow rates, speed, occupancy), their threshold values between congested and uncontested traffic flow regimes, and speed distribution were investigated. The traffic data from Olympic Expressway in Seoul were obtained from Imagine Detection System (Autoscope) with 30 seconds and 1 minute time periods. The slope of the regression line relating flow to occupancy in the uncongested regime decreases when it is raining. In essence, this result indicates that the average service flow rate (it may be interpreted as a capacity of freeway) is reduced as weather conditions deteriorate. The reduction is in the range between 10 and 20%, which agrees with the range proposed by 1994 US HCM. It is noteworthy that the service flow rates of inner lanes are relatively higher than those of other lanes. The average speed is also reduced in rainy day, but the flow-speed relationship and the threshold values of speed and occupancy (these are called critical speed and critical occupancy) are not very sensitive to the weather conditions.

• Radiation Oncology Journal
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• v.22 no.3
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• pp.225-233
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• 2004

Purpose: The Ideal breast irradiation method should provide an optimal dose distribution In the treated breast volume and a minimum scatter dose to the nearby normal tissue. Physical wedges have been used to Improve the dose distribution In the treated breast, but unfortunately Introduce an Increased scatter dose outside the treatment yield, pavllculariy to the contralateral breast. The typical physical wedge (FW) was compared with 4he virtual wedge (VW) to do)ermine the difference In the dose distribution affecting on the treated breast and the contralateral breast, lung, heart and surrounding perlpheral soft tissue. Methods and Materials: The data collected consisted of a measurement taken with solid water, a Humanoid Alderson Rando phantom and patients. The radiation doses at the ipsllateral breast and skin, contralateral breast and skin, surrounding peripheral soft tissue, and Ipsllateral lung and heart were compared using the physical wedge and virtual wedge and the radiation dose distribution and DVH of the treated breast were compared. The beam-on time of each treatment technique was also compared Furthermore, the doses at treated breast skin, contralateral breast skin and skin 1.5 cm away from 4he field margin were also measured using TLD in 7 patients of tangential breast Irradiation and compared the results with phantom measurements. Results: The virtual wedge showed a decreased peripheral dose than those of a typical physical wedge at 15$^{\circ}$, 30$^{\circ}$, 45$^{\circ}$, and 60$^{\circ}$. According to the TLD measurements with 15$^{\circ}$ and 30$^{\circ}$ virtual wedge, the Irradiation dose decreased by 1.35$\%$ and 2.55$\%$ In the contralateral breast and by 0.87$\%$ and 1.9$\%$ In the skin of the contralateral breast respectively. Furthermore, the Irradiation dose decreased by 2.7$\%$ and 6.0$\%$ in the Ipsllateral lung and by 0.96$\%$ and 2.5$\%$ in the heart. The VW fields had lower peripheral doses than those of the PW fields by 1.8$\%$ and 2.33$\%$. However the skin dose Increased by 2.4$\%$ and 4.58$\%$ In the Ipsliateral breast. VW fields, In general, use less monitor units than PW fields and shoriened beam-on time about half of PW. The DVH analysis showed that each delivery technique results In comparable dose distribution in treated breast. Conclusion: A modest dose reduction to the surrounding normal tissue and uniform target homogeneity were observed using the VW technique compare to the PW beam in tangential breast Irradiation The VW field is dosmetrically superlor to the PW beam and can be an efficient method for minimizing acute, late radiation morbidity and reduce 4he linear accelerator loading bV decreasing the radiation delivery time.