• Journal of Science and Technology Studies
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• v.9 no.2
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• pp.51-78
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• 2009

Usually, Technological failures have been recognized as a mundane and inevitable process of trial and error for finally achieving success, or pathological technologies clearly different from success. These approaches easily ignore that a failed technology also constructed complex technological networks with various actors for some times. Consequently, failed technologies failed not only technological realization, but also got a proper evaluation. This paper explore the emergence and decline of the city phone project (CT-2 technology), the very typical failure cases in the telecommunications industry at Korea. This story shows that the city phone project with low-price and low-technology could constructed a stable network at agreement the result from interaction between various actors, and then, changed because various actors gave technologies different meaning and desire. Finally, it suggests that collapse of its technological network was attributed to uncertain future and contingent, rather than technological limits.

• Steel and Composite Structures
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• v.52 no.2
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• pp.135-143
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• 2024

Once the foundation displacement of the transmission tower occurs, additional stress will be generated on the tower members, which will affect the seismic response of transmission tower-line systems (TTLSs). Furthermore, existing research has shown that the reciprocating slippage of joints needs to be considered in the seismic analysis. The hysteretic behavior of joints is obtained by model tests or numerical simulations, which leads to the low modeling efficiency of TTLSs. Therefore, this paper first utilized numerical simulation and model tests to construct a BP neural network for predicting the skeleton curve of joints, and then a numerical model for a TTLS considering the bolt slippage was established. Then, the seismic response of the TTLS under foundation displacement was studied, and the member stress changes and the failed member distribution of the tower were analyzed. The influence of foundation displacement on the seismic performance were discussed. The results showed that the trained BP neural network could accurately predict the hysteresis performance of joints. The slippage could offset part of the additional stress caused by foundation settlement and reduce the stress of some members when the TTLS with foundation settlement was under earthquakes. The failure members were mainly distributed at the diagonal members of the tower leg adjacent to the foundation settlement and that of the tower body. To accurately analyze the seismic performance of TTLSs, the influence of foundation displacement and the joint effect should be considered, and the BP neural network can be used to improve modeling efficiency.

• Particle and aerosol research
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• v.16 no.2
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• pp.31-47
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• 2020

Although interest in air quality has increased due to the frequent occurrence of high-concentration fine particulate matter recently, the official fine particulate matter measuring network has failed to provide spatial detailed air quality information. This is because current measurement equipment has a high cost of installation and maintenance, which limits the composition of the measuring network at high resolution. To compensate for the limitations of the current official measuring network, this study constructed a spatial high density measuring network using the fine particulate matter simple measuring device developed by Observer, W-Station. W-Station installed 48 units on Jeju Island and measured PM_2.5 for six months. The data collected in W-Station were corrected by applying the first regression equation for each section, and these measurements were compared and analyzed based on the official measurements installed in Jeju Island. As a result, the time series of PM_2.5 concentrations measured in W-Station showed concentration characteristics similar to those of the environmental pollution measuring network. In particular, the results of comparing the measurements of W-Station within a 2 km radius of the reference station and the reference station showed that the coefficient of determination (R²) was 0.79, 0.81, 0.67, respectively. In addition, for W-Station within a 1 km radius, the coefficient of determination was 0.85, 0.82, 0.68, respectively, showing slightly higher correlation. In addition, the local concentration deviation of some regions could be confirmed through 48 high density measuring networks. These results show that if a network of measurements is constructed with adequate spatial distribution using a number of simple meters with a certain degree of proven performance, the measurements are effective in monitoring local air quality and can be fully utilized to supplement or replace formal measurements.