Tunable diode laser absorption spectroscopy technology (TDLAS) has been widely applied in gaseous component analysis based on gas molecular absorption spectroscopy. When dealing with molecular absorption signals, the desired signal is usually interfered by various noises from electronic components and optical paths. This paper introduces TDLAS-specific signal processing issues and summarizes effective algorithms so solve these.

Real-time identification of threats has been the focus of attention in the security field in recent years. Researchers have aimed to build a fast, efficient, and accurate model to address risks in threat event identification. This study proposes a fast, effective deep learning model-the squeeze and excitation WaveNet (SE-WaveNet). WaveNet is a 1-D convolutional neural network (CNN) model with a large receptive field. It is small, fast, and highly accurate. Thus, it has a great advantage in processing time series data. On this basis, the squeeze and excitation (SE) structure of the attention mechanism is introduced to adapt to matrix data with complete information. To ensure the integrity of information in the experimental verification, the distributed optical fiber vibration sensing (DVS) system is used to collect the data near the vibration point and form the time-space matrix as the input of the model. SE-WaveNet is compared with WaveNet and related models. Results show that the accuracy of SE-WaveNet based on WaveNet is increased by approximately 3.5%, the model size is reduced by 39%, and the speed is increased by 32%. Compared with the five other related models, the average performance is 3%-9% higher, and the final test accuracy rate can reach approximately 97.73%.

The investigation and evaluation data of reserved cultivated land resources are of great significance to the research and policy-making about cultivated land protection, it is necessary to establish stable and efficient information systems to manage and use the massive data. To this end, this article adopt a hybrid storage strategy, uses relational database, non-relational database and file database to establish the national investigation and evaluation database of reserved cultivated land resources. Automatic and parallel database building technology, spatial big data calculation technology and vector data dynamic rendering technology are researched on, which has solved the technical bottleneck of large-scale spatial data storage, management and visualization. On this basis, developed the database management system, it has been applied in the government administration of cultivated land resources in China and exerts positive results.