• Ecology and Resilient Infrastructure
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• v.8 no.4
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• pp.194-203
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• 2021

With the recent increase in maintenance works on water and sewer pipes as well as district heating supply pipes, pavement cutting work using pavement cutter is on the rise. The pavement cutting operation generates considerable dust (cutting sludge) as well as noise; therefore, it is necessary to apply eco-friendly technologies that have low noise and dust recovery capability. Thus far, various equipment for recovering dust have been developed; however, there is a limitation in that the environmental friendliness is not quantified. Therefore, in this study, we developed a low-noise, dust-recovery type pavement cutter that can fundamentally remove the causes of environmental hazards such as noise and dust and evaluated the eco-friendliness of the pavement cutting process performed by this cutter. To this end, an integrated water cooling-sludge recovery system composed of a vacuum device and a sludge suction unit was developed, and the developed system was applied to a pavement cutter. Subsequently, the developed equipment was applied to the test bed, and data related to its eco-friendliness were collected and evaluated. The results showed that the cutting sludge recovery rate of the developed equipment was greater than 83%, the noise level was approximately 82 - 83 dB, and the sound power level was 115 dB. The results of this study will be used as basic data to develop improved pavement cutters in the future with improved cutting sludge recovery performance and lower noise.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.22 no.4
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• pp.56-66
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• 2021

In this study, a waste heat recovery system was devised and the performances of components incorporated to recover the heat generated during the processing of aerobic liquid-composting in a livestock manure treatment facility were analyzed. In addition, the availability of recovered heat was confirmed. The heat generated by liquid fermentation in the livestock manure treatment facility was also checked. Experimental temperatures were set at 35, 40, and 45 ℃ based on considerations of the uniformity of aerobic liquid-composting fermentation tank temperature and its operating range (34.5 ~ 43.9 ℃). Recovered heat energies from the combined heat exchanger, which consisted of PE and STS pipes, were 53.5, 65.6, 74.4 MJ/h, The heat pump of capacity 5 RT was heated at 95.6, 96.1, 98.9 MJ/h and the heating COPs of the pump were 4.53, 4.62, and 4.65, respectively. The maximum hot water production capacity of the heat exchanger assuming a fermentation tank temperature of 45 ℃ confirmed an energy supply of 56 360 kcal/day. The heating capacity of the FCU linked to the heat storage tank was 20.8 MJ/h, and the energy utilization efficiency was 96.1%. When livestock manure was dried using the FCU, it was confirmed that the initial function rate was reduced by 50.5 to 45.8 % after drying.

• Clean Technology
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• v.24 no.4
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• pp.339-347
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• 2018

In order to cope with environmental problems and climate change caused by fossil fuels, renewable energy supply is increasing year by year. Currently, waste energy accounts for 60% of renewable energy production. However, waste has a lower calorific value than fossil fuels and contains various harmful substances, which causes serious problems when applied to power generation boilers. In particular, the chlorine in the waste fuel increases slagging and fouling of boiler heat exchangers, leading to a reduction in thermal efficiency and the main cause of high temperature corrosion, lowering facility operation rate and increasing operating cost. In this study, the high temperature corrosion experiments of superheater materials (ASME SA213/ASTM A213 T2, T12 and T22 alloy steel) by alkali chlorides were conducted, and their corrosion characteristics were analyzed by the weight loss method and SEM-EDS. Experiments show that the higher the temperature and chloride content, the more corrosion occurs, and KCl further corrodes the materials compared to NaCl under the same condition. In addition, the higher the chromium content of the material, the better the corrosion resistance to the alkali chlorides.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.4
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• pp.2060-2077
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• 2019

Recently, mobile healthcare services have attracted significant attention because of the emerging development and supply of diverse wearable devices. Smartwatches and health bands are the most common type of mobile-based wearable devices and their market size is increasing considerably. However, simple value comparisons based on accumulated data have revealed certain problems, such as the standardized nature of health management and the lack of personalized health management service models. The convergence of information technology (IT) and biotechnology (BT) has shifted the medical paradigm from continuous health management and disease prevention to the development of a system that can be used to provide ground-based medical services regardless of the user's location. Moreover, the IT-BT convergence has necessitated the development of lifestyle improvement models and services that utilize big data analysis and machine learning to provide mobile healthcare-based personal health management and disease prevention information. Users' health data, which are specific as they change over time, are collected by different means according to the users' lifestyle and surrounding circumstances. In this paper, we propose a prediction model of user physical activity that uses data characteristics-based long short-term memory (DC-LSTM) recurrent neural networks (RNNs). To provide personalized services, the characteristics and surrounding circumstances of data collectable from mobile host devices were considered in the selection of variables for the model. The data characteristics considered were ease of collection, which represents whether or not variables are collectable, and frequency of occurrence, which represents whether or not changes made to input values constitute significant variables in terms of activity. The variables selected for providing personalized services were activity, weather, temperature, mean daily temperature, humidity, UV, fine dust, asthma and lung disease probability index, skin disease probability index, cadence, travel distance, mean heart rate, and sleep hours. The selected variables were classified according to the data characteristics. To predict activity, an LSTM RNN was built that uses the classified variables as input data and learns the dynamic characteristics of time series data. LSTM RNNs resolve the vanishing gradient problem that occurs in existing RNNs. They are classified into three different types according to data characteristics and constructed through connections among the LSTMs. The constructed neural network learns training data and predicts user activity. To evaluate the proposed model, the root mean square error (RMSE) was used in the performance evaluation of the user physical activity prediction method for which an autoregressive integrated moving average (ARIMA) model, a convolutional neural network (CNN), and an RNN were used. The results show that the proposed DC-LSTM RNN method yields an excellent mean RMSE value of 0.616. The proposed method is used for predicting significant activity considering the surrounding circumstances and user status utilizing the existing standardized activity prediction services. It can also be used to predict user physical activity and provide personalized healthcare based on the data collectable from mobile host devices.

• The Journal of the Korea Contents Association
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• v.19 no.2
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• pp.516-524
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• 2019

The purpose of this study is to analyze the cases related to the multi-dimensional urban planning and its related systems that can contribute to the urban regeneration as the policies and projects for stereoscopic city increase. Through the case analysis, urban regeneration function and role of multi-dimensional urban planning are identified as connection of places, activation of local economy, expansion of infrastructure and supply of housing. In the institutional sector, private participation is hindered due to the ban on the establishment of the right to hold state property. In addition, it is difficult to utilize the three-dimensional urban space without land securing at a certain rate based on uniform installation standards of the two-dimensional land use plan, and the problem of insufficient interconnection between law and institution is derived. In conclusion, it should actively support and promote the promotion of the three-dimensional facility with the aim of diversifying the regional infrastructure structure and strengthening the urban function. In addition, development of stereoscopic and compound development should be promoted for old urban areas, and parking lots, underground shopping malls, parking lots, etc. should be installed using the subspaces of parks, schools, roads and traditional markets of old residential areas. Finally, cooperation between the central government, the municipalities and the private sector is necessary for the realization of these urban regeneration projects.

• Journal of Navigation and Port Research
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• v.42 no.6
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• pp.539-545
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• 2018

In recent years, research on shipping market forecasting with the employment of non-linear AI models has attracted significant interest. In previous studies, input variables were selected with reference to past papers or by relying on the intuitions of the researchers. This paper attempts to address this issue by applying the stepwise regression model and the random forest model to the Cape-size bulk carrier market. The Cape market was selected due to the simplicity of its supply and demand structure. The preliminary selection of the determinants resulted in 16 variables. In the next stage, 8 features from the stepwise regression model and 10 features from the random forest model were screened as important determinants. The chosen variables were used to test both models. Based on the analysis of the models, it was observed that the random forest model outperforms the stepwise regression model. This research is significant because it provides a scientific basis which can be used to find the determinants in shipping market forecasting, and utilize a machine-learning model in the process. The results of this research can be used to enhance the decisions of chartering desks by offering a guideline for market analysis.

• Korean Journal of Environmental Agriculture
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• v.37 no.3
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• pp.160-165
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• 2018

BACKGROUND: Mixed cropping of legume and grass was effective system in view point of providing organic matter and nitrogen or reducing the nitrogen starvation of following crop. The relation of the change of N and P constituents depending on the cropping types and those effects on the growth and nutrient uptake of the following crop were observed. METHODS AND RESULTS: Three cropping types, hairy vetch mono cropping, barley mono cropping, and mixed cropping of hairy vetch and barley were applied. Soil properties, growth characteristics, and nitrogen production of green manure crops were observed. In additions, the effect of cropping types on the growth pattern of corn as the following crop was observed. In the mixed cropping system, creeping type hairy vetch climbed to the erect type barely for light utilization resulting in improvement of light interception rate and higher LAI (Leaf Area Index) than in mono cropping. Mixed cropping showed higher biomass production and soil nitrogen availability among the cropping types, indicating relatively much more nutrient supply and higher yield production of following crop. CONCLUSION: Mixed cropping showed relatively higher LAI (dry matter) mainly because of intense competition for light utilization usually after flowering stage. Mixed cropping also showed relatively higher yield of corn, the following crop rather than other types, mainly due to the more biomass production potential and higher N and P production ability. Therefore, mixed cropping was adaptable method to reduce or replace chemical fertilizer application for environmentally-friendly agriculture.

• Journal of Food Hygiene and Safety
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• v.34 no.4
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• pp.374-379
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• 2019

This study developed predictive growth models of Salmonella enterica Serovar Typhimurium on lettuce washed with chlorine (100~300 ppm) and ultrasound (US, 37 kHz, 380 W) treatment and stored at different temperatures ($10{\sim}25^{\circ}C$) using a polynomial equation. The primary model of specific growth rate (SGR) and lag time (LT) showed a good fit ($R^2{\geq}0.92$) with a Gompertz equation. A secondary model was obtained using a quadratic polynomial equation. The appropriateness of the secondary SGR and LT model was verified by coefficient of determination ($R^2=0.98{\sim}0.99$ for internal validation, 0.97~0.98 for external validation), mean square error (MSE=-0.0071~0.0057 for internal validation, -0.0118~0.0176 for external validation), bias factor ($B_f=0.9918{\sim}1.0066$ for internal validation, 0.9865~1.0205 for external validation), and accuracy factor ($A_f=0.9935{\sim}1.0082$ for internal validation, 0.9799~1.0137 for external validation). The newly developed models for S. Typhimurium could be incorporated into a tertiary modeling program to predict the growth of S. Typhimurium as a function of combined chlorine and US during the storage. These new models may also be useful to predict potential S. Typhimurium growth on lettuce, which is important for food safety purposes during the overall supply chain of lettuce from farm to table. Finally, the models may offer reliable and useful information of growth kinetics for the quantification microbial risk assessment of S. Typhimurium on washed lettuce.

• Korean Journal of Heritage: History & Science
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• v.45 no.3
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• pp.100-113
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• 2012

In the midst of recent active excavation, lots of Silla(新羅) roof-end tiles are unearthed in Yeongnam area(嶺南地域). These are confirmed the same tile frame as the Silla tiles excavated in Gyeongju(慶州). It is represented by the Silla tiles excavated in Ingaksa Temple(麟角寺) excavation research. Roof-end tile with arabesque design(唐草文平瓦當) etc. including roof-end tile with lotus design(蓮花文圓瓦當) are judged to be the tile frame produced by the same frame of roof-end tile that was excavated in Gyeongju, Wolseong(月城) and Hwangyongsa Temple(皇龍寺址). There are three kinds of cases concerning the transportation of tile manufacture ; the roof-end tile manufactured in Gyeongju directly moved to each region, only tile frame moved to site to be manufactured there, and tile manufacturer moved to site to manufacture there. This article considers the case of the roof-end tile manufactured in Gyeongju that was directly moved to each region. In case of the Silla tiles excavated in region especially Ingaksa Temple, the aspects of tiles in accordance with different era show the repeated coexistence, expansion and maintenance. This situation is significant as a clue to understand the supply from Gyeongju not as temporary, but as continuous. On the other hand, if the Gyeongju tiles flowed directly into each region, and if the road was built of gravels and the means of transportation was cart, the damage from movement must never be prevented. On the contrary, transportation through waterway might be advantageous due to the reduction of labor and damage rate and the easiness of loading. Accordingly, it tells us why the ruins where roof-end tiles were excavated located near big and small rivers or streams. Of course there are some ruins located in a fixed distance, but the distance may be enough to endure the impact put on tiles from the overland movement. Therefore, in case of direct inflow form long distance, transportation must be finished by overland movement after waterway movement.

• Journal of IKEEE
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• v.23 no.1
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• pp.35-43
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• 2019

A capacitor self-calibration is proposed to improve the linearity of the capacitor digital-to-analog converter (CDAC) for an asynchronous successive approximation register (SAR) analog-to-digital converter (ADC) with 10-bit resolution. The proposed capacitor self-calibration is performed so that the value of each capacitor of the upper 5 bits of the 10-bit CDAC is equal to the sum of the values of the lower capacitors. According to the behavioral simulation results, the proposed capacitor self-calibration improves the performances of differential nonlinearity (DNL) and integral nonlinearity (INL) from -0.810/+0.194 LSBs and -0.832/+0.832 LSBs to -0.235/+0.178 LSBs and -0.227/+0.227 LSBs, respectively, when the maximum capacitor mismatch of the CDAC is 4%. The proposed 10-bit 20-MS/s asynchronous SAR ADC is implemented using a 110-nm CMOS process with supply of 1.2 V. The area and power consumption of the proposed asynchronous SAR ADC are $0.205mm^2$ and 1.25 mW, respectively. The proposed asynchronous SAR ADC with the capacitor calibration has a effective number of bits (ENOBs) of 9.194 bits at a sampling rate of 20 MS/s about a $2.4-V_{PP}$ differential analog input with a frequency of 96.13 kHz.