• Journal of Intelligence and Information Systems
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• v.29 no.1
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• pp.307-325
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• 2023

Due to the prolonged COVID-19 pandemic, the frequency of people who are tired of living indoors visiting nearby mountains and national parks to relieve depression and lethargy has exploded. There is a place where thousands of people who came out of nature stop walking and breathe and rest, that is the mineral spring. Even in mountains or national parks, there are about 600 mineral springs that can be found occasionally in neighboring parks or trails in the metropolitan area. However, due to irregular and manual water quality tests, people drink mineral water without knowing the test results in real time. Therefore, in this study, we intend to develop a model that can predict the quality of the spring water in real time by exploring the factors affecting the quality of the spring water and collecting data scattered in various places. After limiting the regions to Seoul and Gyeonggi-do due to the limitations of data collection, we obtained data on water quality tests from 2015 to 2020 for about 300 mineral springs in 18 cities where data management is well performed. A total of 10 factors were finally selected after two rounds of review among various factors that are considered to affect the suitability of the mineral spring water quality. Using AutoML, an automated machine learning technology that has recently been attracting attention, we derived the top 5 models based on prediction performance among about 20 machine learning methods. Among them, the catboost model has the highest performance with a prediction classification accuracy of 75.26%. In addition, as a result of examining the absolute influence of the variables used in the analysis through the SHAP method on the prediction, the most important factor was whether or not a water quality test was judged nonconforming in the previous water quality test. It was confirmed that the temperature on the day of the inspection and the altitude of the mineral spring had an influence on whether the water quality was unsuitable.

• Journal of Food Hygiene and Safety
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• v.25 no.3
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• pp.238-244
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• 2010

Currently, in vitro suspension tests using tubes are used as a authorized test method for sanitizers and disinfectants. However, the methods could not accurately assess the efficacy of sanitizers and disinfectant on the food-contacted surfaces in the field. This study evaluated the effectiveness of 5 kinds of representative sanitizers and disinfectants against E. coli and S. aureus to compare three quantitative surface testing methods that have been internationally standardized. As a result, the ASTM E2111-05 (ASTM(1)) test method obtained 5.18 $\pm$ 0.03 and 5.27 $\pm$ 0.04 log cfu/carrier reduction in dealing with E. coli and S. aureus, respectively, the ASTM E2197-02 (ASTM(2)) test method obtained 4.63 $\pm$ 0.04 and 3.97 $\pm$ 0.03 log cfu/carrier reduction and the CEN EN 13697 test method should 6.14 $\pm$ 0.05 and 5.31 $\pm$ 0.10 log cfu/carrier reduction in clean condition (CEN(1)) but 4.37 $\pm$ 0.02 and 4.06 $\pm$ 0.01 log cfu/carrier reduction in dirty condition (CEN(2)). Among them, CEN(1) showed the highest bactericidal effects, whereas ASTM(2) and CEN(2) revealed low performance (p < 0.05). In conclusion, the bactericidal effects of the ASTM(2) method and the CEN EN 13697 method adopting stainless steel were lower than the ASTM(1) method, which uses glass. The effectiveness assessment results among nationally accredited test methods were different each other. This implies that they could not fit for in the accurate evaluation of sanitization and disinfection on food-contact surfaces in practical food-processing fields. These results could be used as a basic data for establishment of an official surface test methods applicable in the field.

• Korean Journal of Air-Conditioning and Refrigeration Engineering
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• v.26 no.12
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• pp.605-619
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• 2014

This article reviews the papers published in the Korean Journal of Air-Conditioning and Refrigeration Engineering during 2013. It is intended to understand the status of current research in the areas of heating, cooling, ventilation, sanitation, and indoor environments of buildings and plant facilities. Conclusions are as follows. (1) The research works on the thermal and fluid engineering have been reviewed as groups of fluid machinery, pipes and relative parts including orifices, dampers and ducts, fuel cells and power plants, cooling and air-conditioning, heat and mass transfer, two phase flow, and the flow around buildings and structures. Research issues dealing with home appliances, flows around buildings, nuclear power plant, and manufacturing processes are newly added in thermal and fluid engineering research area. (2) Research works on heat transfer area have been reviewed in the categories of heat transfer characteristics, pool boiling and condensing heat transfer and industrial heat exchangers. Researches on heat transfer characteristics included the results for general analytical model for desiccant wheels, the effects of water absorption on the thermal conductivity of insulation materials, thermal properties of Octadecane/xGnP shape-stabilized phase change materials and $CO_2$ and $CO_2$-Hydrate mixture, effect of ground source heat pump system, the heat flux meter location for the performance test of a refrigerator vacuum insulation panel, a parallel flow evaporator for a heat pump dryer, the condensation risk assessment of vacuum multi-layer glass and triple glass, optimization of a forced convection type PCM refrigeration module, surface temperature sensor using fluorescent nanoporous thin film. In the area of pool boiling and condensing heat transfer, researches on ammonia inside horizontal smooth small tube, R1234yf on various enhanced surfaces, HFC32/HFC152a on a plain surface, spray cooling up to critical heat flux on a low-fin enhanced surface were actively carried out. In the area of industrial heat exchangers, researches on a fin tube type adsorber, the mass-transfer kinetics of a fin-tube-type adsorption bed, fin-and-tube heat exchangers having sine wave fins and oval tubes, louvered fin heat exchanger were performed. (3) In the field of refrigeration, studies are categorized into three groups namely refrigeration cycle, refrigerant and modeling and control. In the category of refrigeration cycle, studies were focused on the enhancement or optimization of experimental or commercial systems including a R410a VRF(Various Refrigerant Flow) heat pump, a R134a 2-stage screw heat pump and a R134a double-heat source automotive air-conditioner system. In the category of refrigerant, studies were carried out for the application of alternative refrigerants or refrigeration technologies including $CO_2$ water heaters, a R1234yf automotive air-conditioner, a R436b water cooler and a thermoelectric refrigerator. In the category of modeling and control, theoretical and experimental studies were carried out to predict the performance of various thermal and control systems including the long-term energy analysis of a geo-thermal heat pump system coupled to cast-in-place energy piles, the dynamic simulation of a water heater-coupled hybrid heat pump and the numerical simulation of an integral optimum regulating controller for a system heat pump. (4) In building mechanical system research fields, twenty one studies were conducted to achieve effective design of the mechanical systems, and also to maximize the energy efficiency of buildings. The topics of the studies included heating and cooling, HVAC system, ventilation, and renewable energies in the buildings. Proposed designs, performance tests using numerical methods and experiments provide useful information and key data which can improve the energy efficiency of the buildings. (5) The field of architectural environment is mostly focused on indoor environment and building energy. The main researches of indoor environment are related to infiltration, ventilation, leak flow and airtightness performance in residential building. The subjects of building energy are worked on energy saving, operation method and optimum operation of building energy systems. The remained studies are related to the special facility such as cleanroom, internet data center and biosafety laboratory. water supply and drain system, defining standard input variables of BIM (Building Information Modeling) for facility management system, estimating capability and providing operation guidelines of subway station as shelter for refuge and evaluation of pollutant emissions from furniture-like products.

• Korean Journal of Biological Psychiatry
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• v.3 no.2
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• pp.277-287
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• 1996

Objective : It has been proposed that cognition and related aspects of mental functioning are decreased in depression as well as in alcoholism. The objective of the study was to compare behavioral side effects of paroxetine and amitriptyline in depressed patients accompanied by alcoholism. The focused comparisons were drug effects concerning psychomotor performance, cognitive function, sleep and daytime sleepiness during the first 2 weeks of treatment. Methods : After an alcohol detoxification period(3 weeks) and a washout period(1 week), a total of 20 male inpatients with alcohol use disorder (DSM-IV), who also had a major depressive episode(DSM-IV), were treated double-blind with paroxetine 20mg/day(n=10) or amitriptyline 25mg/day(n=10) for 2 weeks. All patients were required to have a scare of at least 18 respectively on bath the Hamilton Rating Scale far Depression(HAM-D) and Beck Depression Inventory(BDI) at pre-drug baseline. Patients randomized to paroxetine received active medication in the morning and placebo in the evening whereas those randomized to amitriptyline received active medication in the evening and placebo in the morning. All patients performed the various tasks in a test battery at baseline and at days 3, 7 and 14. The test battery included : critical flicker fusion threshold for sensory information processing capacity : choice reaction time for gross psychomotor performance : tracking accuracy and latency of response to peripheral stimulus as a measure of line sensorimotor co-ordination and divided attention : digit symbol substitution as a measure of sustained attention and concentration. To rate perceived sleep and daytime sleepiness, 10cm line Visual analogue scales were employed at baseline and at days 3, 7 and 14. The subjective rating scales were adapted far this study from Leeds sleep Evaluation Questionnaire and Epworth Sleepiness Scale. In addition a comprehensive side effect assessment, using the UKU side effect rating scale, was carried out at baseline and at days 7 and 14. The efficacy of treatment was evaluated using HAM-D, BDI and clinical global impression far severity and improvement at days 7 and 14. Results : The pattern of results indicated thai paroxetine improved performance an mast of the lest variables and also improved sleep with no effect on daytime sleepiness aver the study period. In contrast, amitriptyline produced disruption of performance on same tests and improved sleep with increased daytime sleepiness in particular at day 3. On the UKU side effect rating scale, mare side effects were registered an amitriptyline. The therapeutic efficacy was observed in favor of paroxetine early in day 7. Conclusion : These results demonstrated thai paroxetine in much better than amitriptyline for the treatment of depressed patients accompained by alcoholism at least in terms of behavioral safety and tolerability, furthermore the results may assist in explaining the therapeutic outcome of paroxetine. For example, and earlier onset of antidepressant action of paroxetine may be caused by early improved cognitive function or by contributing to good compliance with treatment.

• Journal of Intelligence and Information Systems
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• v.17 no.4
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• pp.109-130
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• 2011

One of the major problems in the area of data mining is the size of the data, as most data set has huge volume these days. Streams of data are normally accumulated into data storages or databases. Transactions in internet, mobile devices and ubiquitous environment produce streams of data continuously. Some data set are just buried un-used inside huge data storage due to its huge size. Some data set is quickly lost as soon as it is created as it is not saved due to many reasons. How to use this large size data and to use data on stream efficiently are challenging questions in the study of data mining. Stream data is a data set that is accumulated to the data storage from a data source continuously. The size of this data set, in many cases, becomes increasingly large over time. To mine information from this massive data, it takes too many resources such as storage, money and time. These unique characteristics of the stream data make it difficult and expensive to store all the stream data sets accumulated over time. Otherwise, if one uses only recent or partial of data to mine information or pattern, there can be losses of valuable information, which can be useful. To avoid these problems, this study suggests a method efficiently accumulates information or patterns in the form of rule set over time. A rule set is mined from a data set in stream and this rule set is accumulated into a master rule set storage, which is also a model for real-time decision making. One of the main advantages of this method is that it takes much smaller storage space compared to the traditional method, which saves the whole data set. Another advantage of using this method is that the accumulated rule set is used as a prediction model. Prompt response to the request from users is possible anytime as the rule set is ready anytime to be used to make decisions. This makes real-time decision making possible, which is the greatest advantage of this method. Based on theories of ensemble approaches, combination of many different models can produce better prediction model in performance. The consolidated rule set actually covers all the data set while the traditional sampling approach only covers part of the whole data set. This study uses a stock market data that has a heterogeneous data set as the characteristic of data varies over time. The indexes in stock market data can fluctuate in different situations whenever there is an event influencing the stock market index. Therefore the variance of the values in each variable is large compared to that of the homogeneous data set. Prediction with heterogeneous data set is naturally much more difficult, compared to that of homogeneous data set as it is more difficult to predict in unpredictable situation. This study tests two general mining approaches and compare prediction performances of these two suggested methods with the method we suggest in this study. The first approach is inducing a rule set from the recent data set to predict new data set. The seocnd one is inducing a rule set from all the data which have been accumulated from the beginning every time one has to predict new data set. We found neither of these two is as good as the method of accumulated rule set in its performance. Furthermore, the study shows experiments with different prediction models. The first approach is building a prediction model only with more important rule sets and the second approach is the method using all the rule sets by assigning weights on the rules based on their performance. The second approach shows better performance compared to the first one. The experiments also show that the suggested method in this study can be an efficient approach for mining information and pattern with stream data. This method has a limitation of bounding its application to stock market data. More dynamic real-time steam data set is desirable for the application of this method. There is also another problem in this study. When the number of rules is increasing over time, it has to manage special rules such as redundant rules or conflicting rules efficiently.

• Safety and Health at Work
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• v.8 no.1
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• pp.36-41
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• 2017

Background: Police work is generally sedentary although there may be situations that require physical endurance and strength, such as foot chases and arresting suspects. Factors such as excessive body fat can impede an officer's physical ability to deal with such occurrences. Our objective was to examine associations between officers' body fat percentage (BF%) and performance on a standardized fitness protocol. Methods: Data were obtained from fitness screening among 1,826 male and 115 female officers in a large US police agency. The screening consisted of a 2.4-km run, push-ups, sit-ups, and sit-and-reach test. Sex-specific body fat percentages were estimated from skinfold thickness measured using calipers. Linear regression models were used to examine unadjusted and adjusted mean scores of fitness tests across BF% tertiles. Results: The prevalence of overall fitness was 4.3 times greater in male officers and 3.6 times greater in female officers having the lowest BF% tertile compared with the highest tertile (30.3% vs 7.1% and 46.0% vs 12.8%, respectively). BF% was linearly and positively associated with the time of 2.4-km run (p < 0.001), and linearly and inversely associated with the number of push-ups (p < 0.001), sit-ups (p < 0.001), and the distance of sit-and-reach (p < 0.001) in men. Similar associations were observed in women with the exception of sit-and-reach (p = 0.122). Associations were independent of age, race/ethnicity, rank, and duty station. Conclusion: Overall, BF% was inversely associated with fitness levels in male and female officers. Future longitudinal studies should be initiated to explore the potentially causal relationship between BF% and fitness in law enforcement officers.

• Clinical and Experimental Pediatrics
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• v.63 no.11
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• pp.438-446
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• 2020

Background: Most developmental screening tools in Korea are adopted from foreign tests. To ensure efficient screening of infants and children in Korea, a nationwide screening tool with high reliability and validity is needed. Purpose: This study aimed to independently develop, standardize, and validate the Korean Developmental Screening Test for Infants and Children (K-DST) for screening infants and children for neurodevelopmental disorders in Korea. Methods: The standardization and validation conducted in 2012-2014 of 3,284 subjects (4-71 months of age) resulted in the first edition of the K-DST. The restandardization and revalidation performed in 2015-2016 of 3.06 million attendees of the National Health Screening Program for Infants and Children resulted in the revised K-DST. We analyzed inter-item consistency and test-retest reliability for the reliability analysis. Regarding the validation of K-DST, we examined the construct validity, sensitivity and specificity, receiver operating characteristic curve analysis, and a criterion-related validity analysis. Results: We ultimately selected 8 questions in 6 developmental domains. For most age groups and each domain, internal consistency was 0.73-0.93 and test-retest reliability was 0.77-0.88. The revised K-DST had high discriminatory ability with a sensitivity of 0.833 and specificity of 0.979. The test supported construct validity by distinguishing between normal and neurodevelopmentally delayed groups. The language and cognition domain of the revised K-DST was highly correlated with the K-Bayley Scales of Infant Development-II's Mental Age Quotient (r=0.766, 0.739), while the gross and fine motor domains were highly correlated with Motor Age Quotient (r=0.695, 0.668), respectively. The Verbal Intelligence Quotient of Korean Wechsler Preschool and Primary Scales of Intelligence was highly correlated with the K-DST cognition and language domains (r=0.701, 0.770), as was the performance intelligence quotient with the fine motor domain (r=0.700). Conclusion: The K-DST is reliable and valid, suggesting its good potential as an effective screening tool for infants and children with neurodevelopmental disorders in Korea.

• Journal of Intelligence and Information Systems
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• v.20 no.4
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• pp.121-139
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• 2014

Predicting corporate failure has been an important topic in accounting and finance. The costs associated with bankruptcy are high, so the accuracy of bankruptcy prediction is greatly important for financial institutions. Lots of researchers have dealt with the topic associated with bankruptcy prediction in the past three decades. The current research attempts to use ensemble models for improving the performance of bankruptcy prediction. Ensemble classification is to combine individually trained classifiers in order to gain more accurate prediction than individual models. Ensemble techniques are shown to be very useful for improving the generalization ability of the classifier. Bagging is the most commonly used methods for constructing ensemble classifiers. In bagging, the different training data subsets are randomly drawn with replacement from the original training dataset. Base classifiers are trained on the different bootstrap samples. Instance selection is to select critical instances while deleting and removing irrelevant and harmful instances from the original set. Instance selection and bagging are quite well known in data mining. However, few studies have dealt with the integration of instance selection and bagging. This study proposes an improved bagging ensemble based on instance selection using genetic algorithms (GA) for improving the performance of SVM. GA is an efficient optimization procedure based on the theory of natural selection and evolution. GA uses the idea of survival of the fittest by progressively accepting better solutions to the problems. GA searches by maintaining a population of solutions from which better solutions are created rather than making incremental changes to a single solution to the problem. The initial solution population is generated randomly and evolves into the next generation by genetic operators such as selection, crossover and mutation. The solutions coded by strings are evaluated by the fitness function. The proposed model consists of two phases: GA based Instance Selection and Instance based Bagging. In the first phase, GA is used to select optimal instance subset that is used as input data of bagging model. In this study, the chromosome is encoded as a form of binary string for the instance subset. In this phase, the population size was set to 100 while maximum number of generations was set to 150. We set the crossover rate and mutation rate to 0.7 and 0.1 respectively. We used the prediction accuracy of model as the fitness function of GA. SVM model is trained on training data set using the selected instance subset. The prediction accuracy of SVM model over test data set is used as fitness value in order to avoid overfitting. In the second phase, we used the optimal instance subset selected in the first phase as input data of bagging model. We used SVM model as base classifier for bagging ensemble. The majority voting scheme was used as a combining method in this study. This study applies the proposed model to the bankruptcy prediction problem using a real data set from Korean companies. The research data used in this study contains 1832 externally non-audited firms which filed for bankruptcy (916 cases) and non-bankruptcy (916 cases). Financial ratios categorized as stability, profitability, growth, activity and cash flow were investigated through literature review and basic statistical methods and we selected 8 financial ratios as the final input variables. We separated the whole data into three subsets as training, test and validation data set. In this study, we compared the proposed model with several comparative models including the simple individual SVM model, the simple bagging model and the instance selection based SVM model. The McNemar tests were used to examine whether the proposed model significantly outperforms the other models. The experimental results show that the proposed model outperforms the other models.

• YAKHAK HOEJI
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• v.55 no.5
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• pp.411-418
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• 2011

The dissolution test method and an analytical procedure by HPLC were developed and validated for nafronyl oxalate capsules and tramadol hydrochloride capsules. These drugs were not yet characterized by the dissolution specifications in the Korean Pharmaceutical Codex. So, with each reference and test drugs, we did the preliminary and standard experiments based on the Korean Pharmacopeia Guideline of dissolution testing for solid oral dosage forms. The dissolution test for nafronyl oxalate capsules was carried out under sink conditions as follows: dissolution medium phosphate buffer pH 6.8, paddle rotation speed 100 rpm and vessel volume 900 ml. More than 80% of its label amount was released within 30 min in this method. Also the dissolution test for tramadol hydrochloride capsules was carried out under sink conditions as follows: dissolution medium water, paddle rotation speed 50 rpm and vessel volume 900 ml. More than 90% of its label amount was released within 15 min in this method. The dissolution samples were analyzed with a validated HPLC analytical procedure. The analytical methodology showed acceptable values in terms of specificity, linearity, precision and accuracy. The dissolution test methods described above were adequate for the purpose and may be proposed as a pharmacopeial standard to assess the performance of nafronyl oxalate capsules and tramadol hydrochloride capsules. Furthermore, the outcomes of this study were expected to help create an environment where safe and high quality drugs would be distributed on the domestic market making contributions to advancing public health.

• International Journal of Highway Engineering
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• v.19 no.6
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• pp.37-46
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• 2017

PURPOSES : A composite pavement utilizes both an asphalt surface and a concrete base. Typically, a concrete base layer provides structural capacity, while an asphalt surface layer provides smoothness and riding quality. This pavement type can be used in conjunction with rollercompacted concrete (RCC) pavement as a base layer due to its fast construction, economic efficiency, and structural performance. However, the service life and functionality of composite pavement may be reduced due to interfacial bond failure. Therefore, adequate interfacial bonding between the asphalt surface and the concrete base is essential to achieving monolithic behavior. The purpose of this study is to investigate the bond characteristics at the interface between asphalt (HMA; hot-mixed asphalt) and the RCC base. METHODS : This study was performed to determine the optimal type and application rate of tack coat material for RCC-base composite pavement. In addition, the core size effect, temperature condition, and bonding failure shape were analyzed to investigate the bonding characteristics at the interface between the RCC base and HMA surface. To evaluate the bond strength, a pull-off test was performed using different diameters of specimens such as 50 mm and 100 mm. Tack coat materials such as RSC-4 and BD-Coat were applied in amounts of 0.3, 0.5, 0.7, 0.9, and $1.1l/m^2$ to determine the optimal application rate. In order to evaluate the bond strength characteristics with temperature changes, a pull-off test was carried out at -15, 0, 20, and $40^{\circ}C$. In addition, the bond failure shapes were analyzed using an image analysis program after the pull-off tests were completed. RESULTS : The test results indicated that the optimal application rate of RSC-4 and BD-Coat were $0.8l/m^2$, $0.9l/m^2$, respectively. The core size effect was determined to be negligible because the bond strengths were similar in specimens with diameters of 50 mm and 100 mm. The bond strengths of RSC-4 and BD-Coat were found to decrease significantly when the temperature increased. As a result of the bonding failure shape in low-temperature conditions such as -15, 0, and $20^{\circ}C$, it was found that most of the debonding occurred at the interface between the tack coat and RCC surface. On the other hand, the interface between the HMA and tack coat was weaker than that between the tack coat and RCC at a high temperature of $40^{\circ}C$. CONCLUSIONS : This study suggested an optimal application rate of tack coat materials to apply to RCC-base composite pavement. The bond strengths at high temperatures were significantly lower than the required bond (tensile) strength of 0.4 MPa. It was known that the temperature was a critical factor affecting the bond strength at the interface of the RCC-base composite pavement.