It is vital for a strapdown inertial navigation system (SINS) to be calibrated before normal use. In this paper, a new kind of norm-observed calibration method is proposed. Considering that the norm of the output of accelerometers and gyroscopes can be exactly the norm of local acceleration of gravity and Earth rotation angular velocity, respectively, optimization function about all-parameter calibration and the corresponding 24-position calibration path is established. Differential evolutionary algorithm (DE) is supposed to be the best option in parameter identification due to its strong search and fast convergence abilities. However, the high-dimensional individual vector from calibration error equations restrains the algorithm’s optimum speed and accuracy. To overcome this drawback, improved DE (IDE) optimization is specially designed: First, current “DE/rand/1” and “DE/current-to-best/1” mutation strategies are combined as one with complementary advantages and overall balance during the whole optimization process. Next, with the increase of the evolutionary generation, the mutation factor can adjust itself according to the convergence situation. Multiple identification tests prove that our IDE optimization has rapid convergence and high repeatability. Besides, certain motivation of external angular velocity is added to the gyroscope calibration, and a series of dynamic observation paths is formed, further improving the optimization accuracy. The final static navigation experiment shows that SINS with calibration parameters solved by IDE has better performance over other identification methods, which further explains that our novel method is more accurate and reliable in parameter identification.

Continuous mining of metal deposits leads the overlying strata to move, deform, and collapse, which is particularly obvious when open-pit mining and underground mining are adjacent. Once the mining depth of the adjacent open-pit lags severely behind the underground, the ultimate underground mining depth needs to be studied before the surface deformation extends to the open-pit mining area. The numerical simulation and the mechanical model are applied to research the ultimate underground mining depth of the southeast mining area in the Gongchangling Iron mine. In the numerical simulation, the effect of granular rock is considered and the granular rock in the collapse pit is simplified as the degraded rock mass. The ultimate underground mining depth can be obtained by the values of the indicators of surface movement and deformation. In the mechanical model, the modified mechanical model for the progressive hanging wall caving is established based on Hoke’s conclusion, which considers the lateral pressure of the granular rock. Using the limiting equilibrium analysis, the relationship of the ultimate underground mining depth and the range of surface caving can be derived. The results show that the ultimate underground mining depth obtained by the numerical simulation is greater than the theoretical calculation of the modified mechanical model. The reason for this difference may be related to the assumption of the granular rock in the numerical simulation, which increases the resistance of granular rock to the deformation of rock mass. Therefore, the ultimate underground mining depth obtained by the theoretical calculation is suggested. Meanwhile, the surface displacement monitoring is implemented to verify the reasonability of the ultimate underground mining depth. Monitoring results show that the indicators of surface deformation are below the critical value of dangerous movement when the underground is mined to the ultimate mining depth. The practice proves that the determination of the ultimate underground mining depth in this work can ensure the safety of the open-pit and underground synergetic mining.

The earth-to-air heat exchanger (EAHE) system, as a clean and efficient shallow geothermal energy application technology, has obvious effects in reducing the energy consumption of passive low-energy buildings. The traditional horizontal EAHE system is difficult to apply and popularize due to its large occupation, unfavorable shallow soil temperature, and difficulty in timely centralized discharge of condensed water. This paper proposes a new type of vertical earth-to-air heat exchanger (VEAHE) system. The VEAHE system has a number of advantages such as smaller occupation, efficient geothermal energy utilization, and centralized discharge of condensed water. In order to evaluate the influence of different parameters on the thermal performance of the VEAHE system, a mathematical model of the VEAHE system was developed. And, the data calculated by the model highly tallied with the experimental data. The results showed that laying thermal insulation layers at the outlet of risers will effectively restrain the interference of downcomers to risers. It is advisable to set thickness and length of the insulation layer at 30 mm and 3 m. Considering the compromise between thermal performance and construction costs of the VEAHE system, the length of the ducts at 30–50 m and the diameter at 150–250 mm are recommended. The air supply volume of a single shaft can reach 500–1200 m 3 /h as the air velocity reaches 3–7 m/s.

Big data technology has been developed rapidly in recent years. The performance improvement mechanism of targeted poverty alleviation is studied through the big data technology to further promote the comprehensive application of big data technology in poverty alleviation and development. Using the data mining knowledge to accurately identify the poor population under the framework of big data, compared with the traditional identification method, it is obviously more accurate and persuasive, which is also helpful to find out the real causes of poverty and assist the poor residents in the future. In the current targeted poverty alleviation work, the identification of poor households and the matching of assistance measures are mainly through the visiting of village cadres and the establishment of documents. Traditional methods are time-consuming, laborious, and difficult to manage. It always omits lots of useful family information. Therefore, new technologies need to be introduced to realize intelligent identification of poverty-stricken households and reduce labor costs. In this paper, we introduce a novel DBSCAN clustering algorithm via the edge computing-based deep neural network model for targeted poverty alleviation. First, we deploy an edge computing-based deep neural network model. Then, in this constructed model, we execute data mining for the poverty-stricken family. In this paper, the DBSCAN clustering algorithm is used to excavate the poverty features of the poor households and complete the intelligent identification of the poor households. In view of the current situation of high-dimensional and large-volume poverty alleviation data, the algorithm uses the relative density difference of grid to divide the data space into regions with different densities and adopts the DBSCAN algorithm to cluster the above result, which improves the accuracy of DBSCAN. This avoids the need for DBSCAN to traverse all data when searching for density connections. Finally, the proposed method is utilized for analyzing and mining the poverty alleviation data. The average accuracy is more than 96%. The average - measure, NMI, and PRE values exceed 90%. The results show that it provides decision support for precise matching and intelligent pairing of village cadres in poverty alleviation work.

This paper conducts an in-depth analysis and research on the optimization of the labor resource management information platform through the Internet of Things (IoT) technology; through the collection, classification, and data search functions of this application system, it meets the supply and demand of professional talents within a certain enterprise. At the same time, it also realizes the curriculum training application on improving the skills and literacy of the employees of a certain enterprise, and it can learn the enterprise curriculum training from the comments of the employees on the enterprise curriculum. The effect of the enterprise course training can be learned from the comments of the employees on the enterprise course, providing an important reference basis for the future revision of the enterprise course training content. The performance of the participants in the training also has objective data for reference, so that the situation will not be disconnected from reality, and the interaction between enterprise management and employees can achieve a balanced effect. The goal of this workforce resource management system is to create a systematic workforce resource management platform for professional talents and help enterprises achieve the goal of speeding up and increasing efficiency. The system interface provided by the third party is used for horizontal data expansion to realize the sharing of basic information or video data as well as system expansion to realize real-time monitoring and management of project works. The cloud platform realizes efficient management and scientific application of construction site projects by construction management departments, which better solves the current problem of lack of supervision at construction sites.

The power coverage of wireless communication is crucial for the quality of communication and cell network evaluation. In this letter, by taking the layout of Reconfigurable Intelligent Surface (RIS) into count, the power coverage area is proposed for a typical outdoor scenario, which has many rectangular buildings. In this approach, via designing the deploying angle, we introduce finding the optimal horizontal and elevation angles of RIS; we adjust RIS so as to get more power coverage. Since the computational complexity of the optimal solution is very high, a low-complexity method is proposed for solving the optimization problem. More specifically, the coverage is showed in the urban environment with RIS assisting. Presenting the numerical results, we can find the power coverage notably improved. It clearly indicates that our experiment is useful to solve the coverage problem for wireless communication.