Earticle

Noise at construction sites is a major cause of hearing loss and mental damage for construction workers. In order to ensure noise safety, a new technology is needed to classify construction noise that affects worker’s safety. This paper proposes a machine learning-based construction equipment noise classification technique. In this study, three feature domains including time, frequency, and MFCC(Mel-Frequency Cepstral Coefficient) features were extracted from the audio data, and four different construction equipment were classified using three classifiers. For validation, a series of laboratory experiments are conducted. From the test, two classifiers that are KNN(K-Nearest Neighbor) and SVM(Support Vector Machine) show a high classification accuracy compared to DTs(Decision Trees) classifier. In addition, among the three features domains, MFCC features are found to be the most effective one in classifying the four construction equipments. Moreover, in order to investigate the reason for the classification accuracy difference, overlapping feature data between different equipments are analyzed in the feature domains.

In carrying out a project related to the apartment house construction project, except for a certain project subject with sufficient capital, financing is one of the most important factors as the project is carried out with only a small amount of equity capital. In other words, initial investment costs such as licenses and permits are incurred by securing a business site for the construction project, and huge funds must be invested in order to proceed with construction. Therefore, in order to carry out a stable financing plan for a construction project, business operators are using project financing through financial institutions and other institutional financing. In this process, risk management is important for the project to proceed as planned, and types of project risks include implementation risk, construction risk, market risk, and financial risk. From this perspective, in this study, an efficient PF improvement plan for the apartment building construction project was suggested by conducting a theoretical study on PF for the apartment building construction project, conducting an interview with PF related experts, and conducting research and analysis through PF project case evaluation and questionnaire.

The purpose of this study is to propose a 40MPa concrete blending design model that applies the neural network theory to minimize the effort wasted in trial and error. A mixed design model was applied to each of the 180 data using fly ash, blast furnace slag, and rice husk powder. And in the neural network model, the optimized connection weight was obtained by repeatedly applying it to the back-propagation algorithm. The completed mixed design model was demonstrated by analyzing and comparing the predicted values in the mixing design model with those measured in the actual compressive strength test. The factors in the neural network theory affect the compressive strength as the input values and collect the mixed design data through references related to the compressive strength characteristics. To validate the model, a compressive strength test was conducted based on the prediction of the mix design factor, comparing the target compressive strength and the test value in the mix design. According to the results of the mix design verification experiment, the lowest error rate in 40MPa class strength cementless concrete composed of fly ash and rice husk powder was 4.7%, and in 40MPa class strength cementless concrete composed of fly ash, blast furnace slag, and rice husk powder, the lowest error rate was 4.3%. In addition, if the error rate decreases according to the test conditions and environment, a more accurate value could be obtained through the mixed design model.

This study is a basic study on the fixing device(Fastener) of the steel structure joint.Four types of T.S. Nut specimens were manufactured and tested. A total of 20 specimens were produced, 5 each. When manufacturing T.S. Nut, the existing long nut was used, and it was manufactured by precision machining so that the T.S. Nut head shear cross section could be cut. In order to reduce material deterioration due to heat that may occur during rotary cutting, cutting oil is used and low-speed machining is applied. The thickness parameter ranged from 0.5mm to 1.25mm. The clamping force(N) and the torque value(T) of the hexagonal high-strength bolt changes according to the shear sectional thickness(a) of the T.S Nut head. Clamping force(N), torque values(T) and torque coefficient(k) were analyzed to examine whether thickness variables affect the required tensile strength. As a result of the analysis, the clamping force(N) and the torque value(T) increased as a whole according to the shear sectional thickness(a) of the T.S. Nut head. In addition, in the case of T.S. Nut head shear thickness(a) 0.5mm to 1.0mm, the difference in torque coefficient(k) was similarly 103% to 105%, so it was found to be sufficiently stable.

The body temperature after walking in a cold environment may appear lower than when it is measured under stable indoor conditions. In order to improve the accuracy of detecting abnormal body temperature for COVID-19 pandemic situation, it is important to measure the accurate body temperature of subjects who enter the buildings. To do this, the body temperatures of 19 subjects were measured and analyzed immediately after walking for 15 minutes in a cold environment (7℃) and at rest in a climate chamber (20 ℃) for 15 minutes. As a result of measuring the subject's eardrum temperature with an eardrum thermometer, it was found that 36.3℃ (S.D. 0.50℃) immediately after walking in a cold environment, 36.8℃ (S.D. 0.42℃) after stabilization, and a difference of 0.5℃. As a result of measuring the subject's forehead temperature with non-contact infrared thermometers A, B, and C, immediately after walking in a cold environment, they were 36.3℃ (S.D. 0.27℃), 36.3℃ (S.D. 0.27℃), and 36.2℃ (S.D. 0.33℃), respectively, and after resting, 36.7℃, (S.D. 0.27℃), 36.6℃ (S.D. 0.20℃), 36.8℃ (S.D. 0.41℃), respectively, the difference was 0.4℃. As a result of measuring the subject's forehead skin temperature with a contact skin thermometer, it was found to be 31.0℃ (S.D. 1.57℃) immediately after walking in a cold environment, 33.2℃ (S.D. 1.43℃) after stabilization, and a difference of 2.2℃. The difference between the forehead contact skin temperature and the eardrum temperature was 5.3℃ immediately after walking in a cold environment and 3.6℃ after stabilization. In conclusion, it is thought that some correction is necessary when discriminating abnormal body temperature with a non-contact infrared thermometer in winter.

The purpose of this study is to understand the construction process of the Inner Port of Gunsan by period. For the purpose, this study analyses drawings, maps, photos and various documents related to the port construction. As a result, this study summarise the construction details of the Inner Port of Gunsan into 4 periods. Before 1906, Korean Empire built small piers and site construction was done around piers. During 1906∼1910, the Former Gunsan Customs and warehouses were built and small piers were added. Around 1910’s, Gunsan railway extended to the port and small piers constructed near the railway. The major facilities of Inner Port were built during 1926∼1933. The Floating Piers, consist of reinforced concrete pontoons, the shore protections and wharfs were constructed and Gunsan railway was expanded. Some parts of facilities still remained in the Inner Port. After mid of 1930’s, several plans for the extension of the Floating Piers were prepared, but the plan was not realized.

This study focused on the possibility of a integrated family center that focuses various welfare facilities in one place while communicating with local residents based on the region as a realistic alternative to systematically support various welfare needs of local residents in the community. The theoretical planning factors to be considered in the planning of a region-based Integrated Family Center are as follows. First, since the Integrated Family Center is a complex welfare facility with a comprehensive and complex concept, it is necessary to set the type and systematically combine the facilities accordingly. Second, the Integrated Family Center should play a role as an institution with expertise and universality by providing not only professional welfare services but also general public services, so it is necessary to have functionality and flexibility to meet these needs. Third, the Integrated Family Center should be planned with a design that is economical, environmentally conscious, and excludes disabilities. In addition, practical considerations that should be considered essential in actually conducting a region-based Integrated Family Center are as follows. First, the size of the facility based on accurate data such as statistics related to local residents and the program setting that predicts the needs of the local community and future changes should be preceded. Second, the basic functions of the building must be satisfied both inside and outside the building. Third, the plan of specialized facilities suitable for the conditions of the local community and the operation of practical programs based on demand should be properly carried out.