With the rapid increase of public opinion data, the technology of Weibo text sentiment analysis plays a more and more significant role in monitoring network public opinion. Due to the sparseness and high-dimensionality of text data and the complex semantics of natural language, sentiment analysis tasks face tremendous challenges. To solve the above problems, this paper proposes a new model based on BERT and deep learning for Weibo text sentiment analysis. Specifically, first using BERT to represent the text with dynamic word vectors and using the processed sentiment dictionary to enhance the sentiment features of the vectors; then adopting the BiLSTM to extract the contextual features of the text, the processed vector representation is weighted by the attention mechanism. After weighting, using the CNN to extract the important local sentiment features in the text, finally the processed sentiment feature representation is classified. A comparative experiment was conducted on the Weibo text dataset collected during the COVID-19 epidemic; the results showed that the performance of the proposed model was significantly improved compared with other similar models.
A hybrid meta-heuristic named variable neighborhood migrating birds optimization (VNMBO), which is a combination of variable neighborhood search (VNS) and migrating birds optimization (MBO). The main aim of this paper is to provide a new way for MBO to solve the flexible job shop scheduling problem (FJSP). A two-stage population initialization scheme was first adopted to improve the quality of the initial solutions. An individual leaping mechanism was introduced to the algorithm in order to avoid the premature convergence. To search the solution space effectively, three neighborhood structures were designed and a VNS was developed to enhance the local searching ability. Finally, to assess the performance of the proposed VNMBO, some published algorithms were compared by using two famous benchmark data sets. The comparison results show that the proposed VNMBO is effective for solving the FJSP with the objective of minimizing the makespan.
In this paper, a modified bat algorithm (MBA) is proposed for solving the multi-objective flexible job shop scheduling problem. Three different production performance indicators are considered which are the makespan, the total workload of machines and the critical machine workload. Firstly, to make the algorithm adaptive to the problem, the converting approaches are presented to implement the conversion between the continuous position vector and the discrete scheduling code. Secondly, an initialization scheme combining heuristics and random rule is introduced to ensure good quality and diversity of the initial population. Furthermore, five neighborhood structures are designed based on individual positions. Then, a local search algorithm is embedded into the BA to enhance the local searching ability. Finally, simulation results demonstrate the feasibility and effectiveness of our proposed algorithm.
ObjectiveTo explore the role of neuroendoscope assistance during surgical resection of the intracanalicular portion of vestibular schwannomas via the retrosigmoid approach and the subsequent early facial nerve outcomes.MethodsPatients of vestibular schwannoma with intracanalicular extensions undergoing retrosigmoid dissection at a single institution were retrospectively analyzed in this study. Several surgical techniques were applied to ensure maximal and safe removal of tumors. Tumors extending less than 10 mm into the internal acoustic canal (IAC) were classified as Grade A, while those extending over 10 mm into IAC were taken as Grade B. Neuroendoscope was applied at the end of microscopic phase to search for potential remnants for Grade B tumors. Absolute tumor extension was defined and measured. House and Brackmann (HB) scale was used to evaluate immediate CN VII outcomes.ResultsOf the 61 patients, there were 38 females and 23 males. A total of 18 (29.51%) cases were Koos Grade II, 12 (19.67%) cases Koos Grade III, and 31 (50.82%) cases Koos Grade IV. There were 38 cases (62.30%) of Grade A and 23 cases (37.70%) of Grade B. Gross total resection was achieved in 60 cases (98.36%). Four cases of intracanalicular remnants were detected and completely removed under endoscopic visualizations. There was a significantly higher proportion (17%, p = 0.02) of intracanalicular remnants in Grade B than Grade A. CN VII and VIII were anatomically preserved in all cases. A total of 55 cases (90.16%) retained good (HB Grades 1 and 2) facial nerve outcomes.ConclusionsIn Grade B vestibular schwannomas, after maximal microsurgical removal, endoscopic evaluation of the intracanalicular portion revealed residual tumors in 17% of the patients. Hence endoscopic evaluation of the potential intracanalicular remnants for tumor extending over 10 mm within IAC (Grade B) is recommended.
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