Fracturing is an important segment in the sequences of exploring oil, which is also the indispensable means of increasing gas production. Resistivity difference is the premise of monitoring fracture azimuth. We can inject high ionization working liquid into fracturing layer, which lead to the changes of formation resistivity. But because the oil is deep, so the changes of surface potential gradient is small. At the same time, there are all kinds of natural and artificial noise on the earth. So our measuring instrument must have strong anti-interference ability and high accuracy. It can restrain noise by adopting the pseudo random signal as artificial field source and use correlation detection principle. So we can extract the surface potential gradient caused by artificial field source and improve the accuracy of judging fracture extension direction.
This study aims to construct a comprehensive feature system for identifying artificial intelligence–generated content (AIGC) in online Q&A communities, thus uncovering the key factors and mechanisms influencing the identification of AIGC. First, based on the theory of systemic functional linguistics (SFL) and information quality (IQ), this article extracts vocabulary, content, structure, and emotional features from the text, and identifies the AIGC through nine mainstream machine learning algorithms. Subsequently, three widely used resampling strategies are exploited to address the category imbalance problem. The grid search optimisation algorithm fine-tunes different combinations of parameters to improve the performance of the identification classifier. Finally, SHAP values are introduced to evaluate and elucidate the global feature importance and feature influence mechanism. A Chinese corpus from the Zhihu Q&A community is constructed to verify the validity of these methods. The experimental results show that the eXtreme Gradient Boosting (XGBoost) model optimised with hybrid sampling and grid search parameters exhibits excellent performance in identifying AI-generated text, which achieves an F 1 -score of 0.9935, an improvement of 0.11 percentage points over the original model. In addition, all four dimensions of features constructed in this article contribute to AI-generated text identification, and the results of feature interpretability analysis show the greatest impact of features that focus on content readability. The study facilitates the identification and labelling of AIGC in online Q&A communities, thereby enhancing transparency and accountability of information shared online.
Under the premise of protecting the privacy of teaching resources, resource sharing is an effective measure to improve the utilization rate of teaching resources. Therefore, this study proposes a sharing method of teaching resources for economics majors based on Federated learning. Firstly, collect teaching resources for economics majors and complete the integration of resources based on their classification results. Then, set the (Transaction Layer Protocol) TLP protocol as the resource sharing protocol, use the Federated learning algorithm to implement encryption processing for text/data, image/video resources, and complete the directional transmission of resources through the selected transmission channel, so as to achieve resource security sharing. The test results show that the average shared resource loss and error rate of this method are 0.27 GB and 1.37%, respectively, and the shared task execution time does not exceed 2 s, indicating that compared with traditional sharing methods, the sharing performance of this method is better.
Purpose The purpose of this paper is to build a mobile visual search service system for the protection of Dunhuang cultural heritage in the smart library. A novel mobile visual search model for Dunhuang murals is proposed to help users acquire rich knowledge and services conveniently. Design/methodology/approach First, local and global features of images are extracted, and the visual dictionary is generated by the k -means clustering. Second, the mobile visual search model based on the bag-of-words (BOW) and multiple semantic associations is constructed. Third, the mobile visual search service system of the smart library is designed in the cloud environment. Furthermore, Dunhuang mural images are collected to verify this model. Findings The findings reveal that the BOW_SIFT_HSV_MSA model has better search performance for Dunhuang mural images when the scale-invariant feature transform (SIFT) and the hue, saturation and value (HSV) are used to extract local and global features of the images. Compared with different methods, this model is the most effective way to search images with the semantic association in the topic, time and space dimensions. Research limitations/implications Dunhuang mural image set is a part of the vast resources stored in the smart library, and the fine-grained semantic labels could be applied to meet diverse search needs. Originality/value The mobile visual search service system is constructed to provide users with Dunhuang cultural services in the smart library. A novel mobile visual search model based on BOW and multiple semantic associations is proposed. This study can also provide references for the protection and utilization of other cultural heritages.
We propose an improved ant colony algorithm for avoiding obstacles in complex static environments that addresses the problems of a single evaluation factor and low path quality of the traditional ant colony algorithm in path planning. The improvements are: 1) a fuzzy planner is constructed according to the comprehensive evaluation method of fuzzy mathematics and the analytic hierarchy process to comprehensively evaluate and determine the impact of environmental factors, 2) the probability selection formula of the ant colony algorithm is optimized, 3) the pheromone update formula is optimized, and 4) the corner system mechanism is introduced as a post-processing method of path optimization to further smooth the path. Results from simulation experiments of the traditional ant colony algorithm were analysed and compared with those of the improved ant colony algorithm, showing that the latter has a stronger path planning ability and higher algorithm efficiency, resulting in a smoother path with a lower negative impact by environmental factors. Thus, the proposed algorithm is expected to provide a computational basis for effective multi-factor path planning in realistic environments, thereby saving human and material resources.
Classification by acoustic echoes analysis of buried sea mines is the main focus of this paper. Both simulation and actual experiment data show that when the active sonar transmits chirp signal, the energy of buried mines and reverberation echoes will concentrate on different fractional domain, which results the very different properties between the fractional Fourier spectrum of target echoes and that of reverberation. Features are extracted by means of the FRFT (Fractional Fourier Transform) spectrum, and then the Karhunen-Loeve (K-L) transform is used to compress the features before sending to classification. A SVM (Support Vector Machine) classifier is trained and tested on the feature sets of both target and reverberation samples. Experiment results of the FRFT method under different elevations indicated good recognition and classification rates.
To avoid the constraints of limited class hours and multiple teaching contents in the teaching process, this article designs an incremental update method for the data of the teaching resource database of economics majors. Firstly, use a combination of triggers and log tables to capture newly added teaching resource data. Then, the incremental data is sorted by clustering algorithm and loaded into the update log table of the In-memory database engine. Finally, data synchronization updates are completed through an event driven mechanism. The experimental results show that the incremental update efficiency obtained by this method is relatively higher, indicating that this method can better complete the incremental processing work. As the amount of data to be updated increases, this method consumes less time to complete the update, indicating a higher update efficiency.
'/%3e%3cuse xlink:href='%23a' transform='rotate(23.036 .093 25.536)'/%3e%3cuse xlink:href='%23a' transform='rotate(45.87 1.273 16.18)'/%3e%3cuse xlink:href='%23a' transform='rotate(69.945 .996 12.078)'/%3e%3cuse xlink:href='%23a' transform='rotate(20.66 -19.689 31.932)'/%3e%3c/svg%3e)