• Proceedings of the Korean Institute of Building Construction Conference
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• 2003.05a
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• pp.73.2-79
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• 2003

The purpose of this study is to provide the basic data on the optimum method for interfacial separation for an effective recycle of concrete waste by using the thermal properties of concrete. Therefore, this study is proceeded by dividing the interface of concrete into cement paste and fine aggregates or mortar and coarse aggregate, considering the aspect of recycled cement and aggregate as the recycling use of concrete waste. As results of the experiment, in case of recycle cement, the interfacial separation is easily appeared, but it is shown that the mixed amount of powder included in fine aggregate doesn't greatly decrease. But, in case of recycle coarse aggregate, the effect of interfacial separation by preliminary heating is predominant. Especially, the bonding rate of mortar is the lowest when it is heated 5 times for 120 minutes at $300^{\circ}C$. Hence, it is considered that it will be an excellent effect of quality control when the results of this study is applied to a manufacturing system of recycle coarse aggregate which is about to put into practical use.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.39 no.5
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• pp.1-10
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• 2002

Efficient processing of expensive queries that include joins and/or aggregate functions is crucial in data warehousing environment since there reside enormous volume of data. In this paper, we propose a new method for processing of queries that have both of joins and aggregate functions. The proposed method first performs grouping of the dimension table and then processes join by using the bitmap join index. This makes only the fact table accessed for processing aggregate functions, and thus resolves the serious performance degradation of the existing method. For showing the superiority of the proposed method, we suggest the cost models for the proposed and existing ones, and perform extensive simulations based on the TPC-H benchmark.

• KIEAE Journal
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• v.14 no.1
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• pp.131-138
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• 2014

The recent interests in securing alternative resource have increased due to environmental issues and exhaustion of natural resources. The government notices production of recycled aggregate using waste concrete as the substitute of the natural aggregate. However, It's important to reduce environmental burden being inevitably made in the process producing recycled aggregate. In this study, the scenarios of transportation distance were set in the transportation phase of production of recycled aggregate. In addition, The possibility of emissions and reduction of carbon dioxide were studied depending on the scenarios. For this study, data about a amount of waste concrete, transportation distance, kind of vehicle, the number of required vehicle, fuel efficiency of vehicle and etc were gathered from 15 companies of intermediate treatment and 60 constructions sites located in Daegu city and Kyungpook area. Based on those data, fuel consumptions and $CO_2$ emissions according to the transportation scheme of waste concrete were calculated. As a result of the study, the emission of carbon dioxide was possible to be reduced by 27.8~75.4% depending on the scenarios of transportation distance.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2009.05a
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• pp.473-476
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• 2009

Frame Aggregation is a promissing technology for improving MAC throughput in IEEE 802.11n. In IEEE 802.11n, two frame aggregation schemes, Aggregate MSDU (A-MSDU) and Aggregate MPDU (A-MPDU), are defined. In this paper, we analyze the performance the two-level frame aggregation scheme where A-MSDU and A-MPDU are combined. We develop the analytical model for the two-level frame aggregation scheme and present numerical results on the effect of bit error rate, aggregation size, and the number of nodes.

• Journal of KIISE:Databases
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• v.33 no.6
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• pp.563-577
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• 2006

A stream processor uses resource sharing method for efficient of limited resource in multiple continuous queries. The previous methods process aggregate queries to consist the level structure. So insert operation needs to reconstruct cost of the level structure. Also a search operation needs to search cost of aggregation information in each size of sliding windows. Therefore this paper uses linear structure for optimization of sliding window aggregations. The method comprises of making decision, generation and deletion of panes in sequence. The decision phase determines optimum pane size for holding accurate aggregate information. The generation phase stores aggregate information of data per pane from stream buffer. At the deletion phase, panes are deleted that are no longer used. The proposed method uses resources less than the method where level structures were used as data structures as it uses linear data format. The input cost of aggregate information is saved by calculating only pane size of data though numerous stream data is arrived, and the search cost of aggregate information is also saved by linear searching though those sliding window size is different each other. In experiment, the proposed method has low usage of memory and the speed of query processing is increased.

• Journal of the Korea Institute of Building Construction
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• v.17 no.6
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• pp.499-506
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• 2017

This study is to present empirical data about the needs for quality security of aggregate by randomly selecting aggregate from 4 major locations including A, B, C, D province in Korea, by investigating its quality status in terms of physical properties and particle distribution based on Korean industrial standards(KS). The test results indicated that wide variance in quality, and some of aggregate samples were far below the standard, still many of them are not satisfying KS standards. In addition, the current aggregate manufacturing process that does not include inspection of particle size distribution by sieving and fineness modulus, can induce a possibility of non-KS aggregate's distribution; this provide that the current status of aggregate quality security of Korea is seriously threatened. Thus, it is important to secure each aggregate's quality level under KS standards.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.38 no.3
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• pp.159-168
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• 2015

Aggregate Production Planning determines levels of production, human resources, inventory to maximize company's profits and fulfill customer's demands based on demand forecasts. Since performance of aggregate production planning heavily depends on accuracy of given forecasting demands, choosing an accurate forecasting method should be antecedent for achieving a good aggregate production planning. Generally, typical forecasting error metrics such as MSE (Mean Squared Error), MAD (Mean Absolute Deviation), MAPE (Mean Absolute Percentage Error), and CFE (Cumulated Forecast Error) are utilized to choose a proper forecasting method for an aggregate production planning. However, these metrics are designed only to measure a difference between real and forecast demands and they are not able to consider any results such as increasing cost or decreasing profit caused by forecasting error. Consequently, the traditional metrics fail to give enough explanation to select a good forecasting method in aggregate production planning. To overcome this limitation of typical metrics for forecasting method this study suggests a new metric, WACFE (Weighted Absolute and Cumulative Forecast Error), to evaluate forecasting methods. Basically, the WACFE is designed to consider not only forecasting errors but also costs which the errors might cause in for Aggregate Production Planning. The WACFE is a product sum of cumulative forecasting error and weight factors for backorder and inventory costs. We demonstrate the effectiveness of the proposed metric by conducting intensive experiments with demand data sets from M3-competition. Finally, we showed that the WACFE provides a higher correlation with the total cost than other metrics and, consequently, is a better performance in selection of forecasting methods for aggregate production planning.

• Proceedings of the Korean Institute of Building Construction Conference
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• 2005.05a
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• pp.119-124
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• 2005

It is necessary for prediction of recycled aggregate concrete(RAC) strength at the early stage that facilitate concrete form removal and scheduling for construction. However, to predict RAC strength is difficult because of being influenced by complicated many factors. Therefore, this research suggest optimized estimation method that can reflect many factors. One way is Case-Based Reasoning(CBR) that solved new problems by adapting solutions to similar problems solved in the past, which are solved in the case library. Other way is Artificial Neural Networks(ANN) that solved new problems by training using a set of data, which is representative of problem domain. This study is to propose comparing accuracy of the estimating the compressive strength of recycled aggregate concrete using Case-Based Reasoning(CBR) and Artificial Neural Networks(ANN).

• Proceedings of the Korea Concrete Institute Conference
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• 2001.11a
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• pp.647-650
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• 2001

The traffic noise from automobiles have been causing so serious problems in urban areas that the study and solutions to reduce noise and air pollution have been required. In general, Portland cement concrete(PCC) pavements have the advantage of durability and superior surface friction when compared to most dense-graded asphalt. However, data collected to date generally show PCC pavements to create more noise than asphaltic surfaces. Therefore, recent research has shown some new concrete pavement textures to be worth further examination. Exposed Aggregate Pavements have also been evaluated for noise impacts. This PCC surface is accomplished by brushing the surface of the plastic concrete to expose the aggregate, increasing the macro texture. In this study, in order to manufacture Aggregate Exposed Concrete for low noise pavements, we considered the effects of retarder agents according to dosage and curing conditions. So we tried to find out relationship between textures of surface and effects of retarder.

• Management Science and Financial Engineering
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• v.16 no.3
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• pp.49-70
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• 2010

Customer population management models can be classified into three categories: the first category includes the models that analyze the customer population at cohort level; the second one deals with the customer population at aggregate level; the third one has interest in the interactions among the customer populations in the competitive market. Our study proposes a model that can analyze the dynamics of customer population in consumer-durables market at aggregate level. The dynamics of customer population includes the retention curves from the purchase or at a specific duration time, the duration time expectancy at a specific duration time, and customer population growth or decline including net replacement rate, intrinsic rate of increase, and the generation time of customer population. For this study, we adopt mathematical ecology models, redefine them, and restructure interdisciplinary models to analyze the dynamics of customer population at aggregate level. We use the data of previous research on dynamic customer population management at cohort level to compare its results with those of ours and to demonstrate the useful analytical effects which the precious research cannot provide for marketers.