Wyniki wyszukiwania - BazTech

1

Research on the risk classification of cruise ship fires based on an attention-BP neural network

Xiong Zhenghua, Xiang Bo, Chen Ye, Chen Bin

Polish Maritime Research

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2022

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nr 3

61--68

EN

Due to the relatively closed environment, complex internal structure, and difficult evacuation of personnel, it is more difficult to prevent ship fires than land fires. In this paper, taking the large cruise ship as the research object, the physical model of a cruise cabin fire is established through PyroSim software, and the safety indexes such as smoke temperature, CO concentration, and visibility are numerically simulated. An Attention-BP neural network model is designed for realizing the intelligent identification of a cabin fire and dividing the risk level, which integrates the diagnosis results of multiple neural network models through the self-Attention mechanism and adaptively distributes the weight of each BP neural network model. The proposed model can provide decision-making reference for subsequent fire-fighting measures and personnel evacuation. Experimental results show that the proposed Attention-BP neural network model can effectively realize the early warning of the fire risk level. Compared with other machine learning algorithms, it has the highest stability and accuracy and reduces the uncertainty of early cabin fire warning.

2

Study on discrimination of different grades of rapeseed oil based on flavor fingerprint

Chen Tong, Liu Chunyou, Chen Bin, Huang Yongchun

Acta Chromatographica

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2021

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Vol. 33, no. 3

295--301

EN

In this work, Gas chromatograph-Mass Spectrometry (GC-MS) combined with solid phase micro-extraction technology was used to analyze the difference of volatile organic compounds (VOCs) in rapeseed oil of different grades, and the relationship between changes of VOCs and refining process were also investigated in order to construct a non-linear model, which could realize rapid and accurate discrimination of different grade rapeseed oils. 124 rapeseed oil samples with different grades were collected and analyzed by GC-MS technology and 55 VOCs were identified and selected as variables to characterize the internal quality information of rapeseed oils. Then, principal component analysis (PCA) method was used to extract useful features and reduce data dimensionality, and finally a discriminant model was built using linear discriminant analysis (LDA) algorithm. The correct recognition rate of sample set was close to 94.59%. The results showed that the proposed method is promising in discriminating different grades of vegetable oils. Besides, it provides a theoretical basis for studying the relationship between VOCs composition and vegetable oil quality.

3

Grain-size characteristics and net transport patterns of surficial sediments in the Zhejiang nearshore area, East China Sea

Liang Juan, Liu Jian, Xu Gang, Chen Bin

Oceanologia

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2020

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No. 62 (1)

12--22

EN

Spatial variations in grain-size parameters can reflect sediment transport patterns and depositional dynamic environments. Therefore, 616 surficial sediment samples taken from the Zhejiang nearshore area in the East China Sea were analyzed to better understand the net sediment transport pattern in this region. The study area is generally dominated by clayey silt and has relatively coarse mud sediment in the southeast. The sorting coefficient of surface sediment is higher than 1.4, and sediment is poorly sorted throughout the study area. The skewness has a strong correlation with the mean grain-size diameter. The net sediment transport pathways obtained by the grain-size trend analysis indicate several distinct characteristics of the surficial sediment transport. The sediment is transported southward under the action of the stronger southward Zhejiang-Fujian Coastal Current (ZMCC) in winter in the upper part of the nearshore area. Influenced by the obstruction of the Taiwan Warm Current (TWC) and the tidal current, surficial sediment transport vectors display two areas of grain-size trend convergence and indicate the net deposition environment has a high sedimentation rate. However, the transport is mainly toward the north under the control of the prevailing northward ZMCC and the strong TWC in the summer. The sedimentary rate is closely related to the processes of the sediment transport. On the one hand, sediment transportation affects the depositional rate in a different environment. On the other hand, the modern sedimentary rate can reflect indirectly the sediment source and sediment transportation.

4

Discrimination of Chinese yellow wine from different origins based on flavor fingerprint

Chen Tong, Qi Xingpu, Chen Mingjie, Lu Daoli, Chen Bin

Acta Chromatographica

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2020

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Vol. 32, no. 2

139--144

EN

In this study, discrimination of Chinese yellow wines from Shaoxing, Shandong, and Hubei in China has been carried out according to volatile flavor components. A total of 122 yellow wine samples were characterized by gas chromatography–ion mobility spectrometry (GC–IMS). A simple color mixing method was visually used to select characteristic peaks based on the RGB color model. Then, the volatile organic compounds corresponding to the selected characteristic peaks were identified via library searching, and the height values of those peaks were arranged for further chemometric pretreatment. Principal component analysis was employed to reveal significant differences and potential patterns between samples. Finally, quadratic discriminant analysis was applied to develop a classification model and achieved a correct classified rate of 95.35% for the prediction set. The results prove that the aroma composition combined with chemometric tools can be used as a fingerprinting technique to protect the product of origin and enable the authenticity of Chinese yellow wine.