UWB-INS Fusion Positioning Based on a Two-Stage Optimization Algorithm

Ultra-wideband (UWB) is a carrier-less communication technology that transmits data using narrow pulses of non-sine waves on the nanosecond scale. The UWB positioning system uses the multi-lateral positioning algorithm to accurately locate the target, and the positioning accuracy is seriously affected by the non-line-of-sight (NLOS) error. The existing non-line-of-sight error compensation methods lack multidimensional consideration. To combine the advantages of various methods, a two-stage UWB-INS fusion localization algorithm is proposed. In the first stage, an NLOS signal filter is designed based on support vector machines (SVM). In the second stage, the results of UWB and Inertial Navigation System (INS) are fused based on Kalman filter algorithm. The two-stage fusion localization algorithm achieves a great improvement on positioning system, it can improve the localization accuracy by 79.8% in the NLOS environment and by 36% in the (line-of-sight) LOS environment

A Systematic Analysis on DNA Methylation and the Expression of Both mRNA and microRNA in Bladder Cancer

Background: DNA methylation aberration and microRNA (miRNA) deregulation have been observed in many types of cancers. A systematic study of methylome and transcriptome in bladder urothelial carcinoma has never been reported. Methodology/Principal Findings: The DNA methylation was profiled by modified methylation-specific digital karyotyping (MMSDK) and the expression of mRNAs and miRNAs was analyzed by digital gene expression (DGE) sequencing in tumors and matched normal adjacent tissues obtained from 9 bladder urothelial carcinoma patients. We found that a set of significantly enriched pathways disrupted in bladder urothelial carcinoma primarily related to "neurogenesis" and "cell differentiation" by integrated analysis of -omics data. Furthermore, we identified an intriguing collection of cancer-related genes that were deregulated at the levels of DNA methylation and mRNA expression, and we validated several of these genes (HIC1, SLIT2, RASAL1, and KRT17) by Bisulfite Sequencing PCR and Reverse Transcription qPCR in a panel of 33 bladder cancer samples. Conclusions/Significance: We characterized the profiles between methylome and transcriptome in bladder urothelial carcinoma, identified a set of significantly enriched key pathways, and screened four aberrantly methylated and expressed genes. Conclusively, our findings shed light on a new avenue for basic bladder cancer research

Analysis of Influencing Factors on Soil Thermal Conductivity Test in Ground Source Heat Pump

A three dimensional numerical model of ground source heat pump system was established. The effects of testing time, starting time, borehole radius, initial ground temperature and heat injection rate on identified thermal conductivity of the deep ground soil were analyzed based on the numerical model. The simulation results showed that thermal response test time should be more than 70 h; For cylinder-source model, with the increase of the size of the borehole, the identified thermal conductivity gradually decreased; The initial temperature of ground soil has no effect on the result of thermal conductivity identification, but the testing precision of the initial temperature has larger effects to identification results when the parameter estimation method is adopted; For pure thermal conductivity model, heat injection rate has no effect on thermal conductivity identification results

UWB-INS Fusion Positioning Based on a Two-Stage Optimization Algorithm

Ultra-wideband (UWB) is a carrier-less communication technology that transmits data using narrow pulses of non-sine waves on the nanosecond scale. The UWB positioning system uses the multi-lateral positioning algorithm to accurately locate the target, and the positioning accuracy is seriously affected by the non-line-of-sight (NLOS) error. The existing non-line-of-sight error compensation methods lack multidimensional consideration. To combine the advantages of various methods, a two-stage UWB-INS fusion localization algorithm is proposed. In the first stage, an NLOS signal filter is designed based on support vector machines (SVM). In the second stage, the results of UWB and Inertial Navigation System (INS) are fused based on Kalman filter algorithm. The two-stage fusion localization algorithm achieves a great improvement on positioning system, it can improve the localization accuracy by 79.8% in the NLOS environment and by 36% in the (line-of-sight) LOS environment

Sequence-to-Sequence Prescription Recommendation Model Based on Chinese Medicine Keywords

Taking the traditional Chinese medicine prescription recommendation task as an entry point, a keyword-aware model for traditional Chinese medicine based on a sequence-to-sequence framework is proposed. This is done to address the problems of existing prescription recommendation models that ignore domain knowledge information, such as herb compatibility, which can lead to poor recommendation effects and deviation of recommended prescriptions from the reality. A keyword-aware network is added to the symptom sequence information mining part to expand the multi-branch structure of the model, and prescription monarch medicine serves as the keyword embedding vector to mine the prescription dispensing information to enhance the model's ability to represent the deep knowledge features and improve the recommendation quality. A cross-propagation mechanism is proposed to reduce the feature dimensions that are over-attended in the attention accumulation process, ensuring that the accumulation result can focus on the unattended region, and reducing the probability of recommended prescription repetition. A hybrid soft loss function is also proposed to further improve the results by increasing the gap between different distributions and penalizing repeated attention to the same location behavior. The model is tested on two public clinical traditional Chinese medicine prescription datasets. The experimental results show that, compared with other deep learning models such as TPGen and Herb-Know, the model can effectively enhance the quality of recommended prescriptions and improve the repetition problem in the model generation process. It also improves the quality of recommended prescriptions compared with the best baseline model in terms of Precision, Recall, and F1 value by 8, 5, and 6 percentage points, respectively. In addition, the results of ablation experiments demonstrate the effectiveness of the modules

Recommendation Method of Chinese Herbal Medicine Based on TCMTF

[Purposes] Taking the task of Chinese herbal medicine recommendation as the starting point, a Chinese herbal medicine recommendation model based on an improved Transformer is proposed to address the problems of existing Chinese herbal medicine recommendation models ignoring traditional Chinese medicine related theoretical knowledge, resulting in poor effectiveness and deviation from actual recommended prescriptions. [Methods] Convolutional neural networks were added to the symptom sequence information mining module, the multi branch structure of the model was expanded, and the trained symptom text vector was used as the embedding vector to mine relevant information to improve the deep level feature combination ability and recommendation quality of the model. A multi feature fusion attention mechanism was proposed to reduce the feature dimensions that are overly focused during the attention accumulation process, so that the accumulation results can focus on areas that are not being paid attention to and reduce the probability of recommending Chinese herbal medicine duplicates. An entropy smoothing loss was also proposed to further improve recom mendation results by reducing the impact of strict order on the results. The model was tested on a public clinical Chinese medicine prescription dataset and a private dataset of a collaborating hospital. [Results] The experimental results show that compared with other Chinese herbal recommendation models such as Herb Know and TCM Translator, the proposed model can effectively improve the quality of recommended Chinese herbal medicine and improve the problem of repetition in the process. Compared with the best benchmark model, the proposed model improved the precision, recall, and F1 by 7%-9%, 5%-6%, and 7%-8%, respectively. In addition, the ablation experiment also demonstrates the effectiveness between various modules

INS/CNS integrated filtering technique based on celestial calibration

Abstract This paper analyzes the filtering mode and working characteristics of INS/CNS system according to application features of celestial equipment. In view of combination mode of gyro drift calibrated by CNS, this paper establishes corresponding filtering model according to different measurement information selected by INS/CNS system. The error of inertia component is compensated by virtue of star vector estimate value so as to guarantee the long-term precision of inertial navigation. Simulation analysis verifies that this method may improve adaptability of INS/CNS system to environment, and effectively guarantee the navigation precision in long-time operation of the system.</jats:p

Research Summary on Light Field Display Technology Based on Projection

Abstract In recent years, three-dimensional display technology has developed rapidly, among which light field display technology is a type of technology with broad application prospects that can realize naked-eye stereo display. With the enhancement of digital image processing capabilities and the development of projection technology, projection-based light field display technology has also made great progress. This article analyzes the principle and development of light field display technology based on high-speed projection and projection arrays, briefly introduces the relevant experimental results of the research team at home and abroad, and finally discusses the application prospects of different technical directions.</jats:p

Comprehensive Analysis of HMCN1 Somatic Mutation in Clear Cell Renal Cell Carcinoma

Background: Renal cell carcinoma (RCC) is a common malignancy of the genitourinary system and clear cell renal cell carcinoma (ccRCC) is the most representative subtype. The morbidity and mortality of ccRCC have gradually risen during recent years; however, the pathogenesis and potential biomarkers remain unclear. The purpose of our study was to find out prognostic genes correlated with somatic mutation and the underlying mechanisms of HMCN1 mutation in ccRCC. Methods: Somatic mutation data of two ccRCC cohorts were acquired from TCGA and cBioPortal. Genes frequently mutated in both datasets were extracted, from which tumor mutation burden and survival analysis revealed three prognostic genes. Further comprehensive analysis of HMCN1 mutation was carried out to identify differentially expressed genes and apply functional annotations. The correlation of HMCN1 mutation and tumor immunity was also evaluated. Results: HMCN1, SYNE1, and BAP1 mutations were associated with both tumor mutation burden and clinical prognosis in ccRCC. Gene enrichment analysis suggested the effects of HMCN1 mutation on biological processes and pathways linked to energy metabolism. HMCN1 mutation was also correlated with anti-tumor immunity. There were several limitations in the sample size and cohort availability of the present computational study. Conclusions: The present results inferred that HMCN1 mutation might have an important clinical significance for ccRCC patients by regulating metabolism and the immune microenvironment