The surveillance and reports on accidents for the current traffic management are carried out by viewing and inspecting CCTV footage. This method is slow to detect incidents and requires a lot of manpower. Since nowadays communication technology and social media play a role in reporting such incidents this research has been conducted to investigate accidents of interest from text messages reported on social media in Thai. There is currently no research or platform that supports this type of work clearly. This research presented the development of a neuron network memory-learning model to solve the problem of incidence pattern classification and incidence severity identification from social media messages in Thai. Using deep learning models such as MLP CNN Bi-LSTM and LSTM+CNN the study was designed and divided into three experimental patterns. This included examining patterns to identify traffic incidents that may be reported as general news or traffic reporting; examining patterns to indicate the type of incidents such as traffic accidents disasters damaged roads or others other than those mentioned; and examining patterns to specify the severity levels of the incidents such as normal intermediate traffic lane blocking or immovable. The experiments demonstrated the capability of CNN+LSTM learning models with the best incidence detection result at 93.44 %. The CNN model gave the best result in identifying a pattern of incidence at 85.29 % and the LSTM model was best able to determine the severity levels of the incidence at 88.53 %.

The purpose of this research is to improve the physical and mechanicalqualities of natural rubber latex tiles. Water: surfactant: surfactant: 1: 2.75: 0.03: 0.30:0.03: 0.04 by weight and added with natural latex. In the ratio of Portland Cement Type 1: Natural Latex is 1: 0 1: 0.025 1: 0.05 1: 0.075 and 1: 0.10. Formed with compression presses at normal temperatures it was found that the optimum amount of natural latex For concrete reinforced concrete tiles the ratio is 1: 0.025. The tests in accordance with Thai Industrial Standard TIS 535-2556 are tested in 4 aspects. Dimensional stress test Water absorption test And waterproofness testing The value has passed the benchmark. And low thermal conductivity. Increasing the insulation of the roof as well. Can be used as a prototype product tile concrete roof natural latex. To produce commercially And there can be many local latex or rubber latex. To be more useful and valuable.

This research aims to test the properties of concrete block mixed with basalt fragment as aggregates in products. The mix ratios of Portland cement type1 : basalt fragment : water are 1 : 10 : 0.7 1 : 10.5 : 0.7 1 : 11 : 0.7 1 : 11.5 : 0.7 and 1 : 12 : 0.7 by weight. The concrete block samples were mixed and casted in 7 x 19 x 39 centimeter by the concrete block molding machine. The concrete block sample testing follows the TIS 58-2533 standard on non-load bearing concrete blocks. From the results the density compressive strength and thermal conductivity of concrete block mixed with basalt fragment are lower than the common concrete block. In addition the water absorption and volumetric change are higher than the common concrete block. The optimal ratio in this work is 1: 11: 0.7

Thermoelectric properties of cubic perovskite SrTiO3 have been investigated. The energy band structures are calculated using the total energy plane-wave pseudopotential method within the local density approximation (LDA) and generalized gradient approximation (GGA). The calculated energy band structures are then used in combination with Boltzmann transport equation to calculate the thermoelectric parameters of doped SrTiO3 especially seebeck coefficient electrical conductivity and electronic thermal conductivity.