高职计算机应用技术专业'课证融合'教学改革探讨

在高校的开展教学过程之中,应当根据学生实际水平以及能力对学生进行必要的培养,在课程融合的教学模式之下,学生在完成自身职业能力的同时能够获得相关证书,这样就一定程度上提升学生学习积极性以及培训参与度,对于学生更好掌握岗位技能具有十分重要的作用,本文主要是关于高职计算机应用技术专业'课证融合'教学改革探讨.

多模态影像融合在颅底肿瘤的诊断、治疗中的应用价值

目的探讨多模态影像融合在颅底肿瘤的诊断、治疗中的应用价值。方法 9例颅底肿瘤术前均行DynaCTA检查及MRI薄层(2 mm)增强扫描检查,将多组影像数据输入工作站,采用"双容积重建"技术进行脑血管及MRI的影像融合,通过静态及动态融合影像观察肿瘤与脑结构、血管及颅骨的毗邻关系,并对肿瘤的诊断、手术治疗及预防血管并发症进行分析。结果 9例均获得满意的影像融合、具有很好的空间一致性,在一张影像上可以清晰显示病变及其周围脑结构、血管及颅骨解剖关系,提高精准性诊断,并应用于指导治疗策略、设计手术划及预防并发症。9例均恢复满意出院。结论多模态影像融合对提高颅底肿瘤的诊断精准性、提高肿瘤全切除率、降低病死率和残疾率效果肯定,对血管损伤并发症治疗疗效肯定。

Research on the Mechanism of Multi-Sensor Fusion Configuration Based on the Optimal Principle of the Vehicle

In order to address the issue of sensor configuration redundancy in intelligent driving,this paper constructs a multi-objective optimization model that considers cost,coverage ability,and perception performance.And then,combining a specific set of parameters,the NSGA-II algorithm is used to solve the multi-objective model established in this paper,and a Pareto front containing 24 typical configuration schemes is extracted after considering empirical constraints.Finally,using the decision preference method proposed in this paper that combines subjective and objective factors,decision scores are calculated and ranked for various configuration schemes from both cost and performance preferences.The research results indicate that the multi-objective optimization model established in this paper can screen and optimize various configuration schemes from the optimal principle of the vehicle,and the optimized configuration schemes can be quantitatively ranked to obtain the decision results for the vehicle under different preference tendencies.

State Estimation Method for GNSS/INS/Visual Multi-sensor Fusion Based on Factor Graph Optimization for Unmanned System

With the development of unmanned driving technology,intelligent robots and drones,high-precision localization,navigation and state estimation technologies have also made great progress.Traditional global navigation satellite system/inertial navigation system(GNSS/INS)integrated navigation systems can provide high-precision navigation information continuously.However,when this system is applied to indoor or GNSS-denied environments,such as outdoor substations with strong electromagnetic interference and complex dense spaces,it is often unable to obtain high-precision GNSS positioning data.The positioning and orientation errors will diverge and accumulate rapidly,which cannot meet the high-precision localization requirements in large-scale and long-distance navigation scenarios.This paper proposes a method of high-precision state estimation with fusion of GNSS/INS/Vision using a nonlinear optimizer factor graph optimization as the basis for multi-source optimization.Through the collected experimental data and simulation results,this system shows good performance in the indoor environment and the environment with partial GNSS signal loss.

Infrasound Event Classification Fusion Model Based on Multiscale SE-CNN and BiLSTM

The classification of infrasound events has considerable importance in improving the capability to identify the types of natural disasters.The traditional infrasound classification mainly relies on machine learning algorithms after artificial feature extraction.However,guaranteeing the effectiveness of the extracted features is difficult.The current trend focuses on using a convolution neural network to automatically extract features for classification.This method can be used to extract signal spatial features automatically through a convolution kernel;however,infrasound signals contain not only spatial information but also temporal information when used as a time series.These extracted temporal features are also crucial.If only a convolution neural network is used,then the time dependence of the infrasound sequence will be missed.Using long short-term memory networks can compensate for the missing time-series features but induces spatial feature information loss of the infrasound signal.A multiscale squeeze excitation–convolution neural network–bidirectional long short-term memory network infrasound event classification fusion model is proposed in this study to address these problems.This model automatically extracted temporal and spatial features,adaptively selected features,and also realized the fusion of the two types of features.Experimental results showed that the classification accuracy of the model was more than 98%,thus verifying the effectiveness and superiority of the proposed model.

秭归饮食文化与旅游业融合发展研究

围绕秭归饮食文化与旅游业的融合发展,对秭归特色饮食进行概述,分析当前秭归特色饮食文化与旅游业融合发展的成效和不足,进而提出一些有利于推动秭归饮食文化与旅游业融合发展的建议。

如何解决信息高速公路的“最后一公里”──浅谈三网融合技术

从智能化小区建设的网络报建过程中发现可能存在的重复建设等问题展开,对当今国内存在的几种流行的网络宽带接入方法的特点进行了分析和对比。在此基础上提出了解决信息高速路"最后一公里"的方法,提出三网融合的技术在解决此问题上明显的优势。

Fusion of ERT Images Based on Dempster-Shafer's Evidence Theory

In this paper, an electrical resistance tomography(ERT) imaging method is used as a classifier, and then the Dempster-Shafer's evidence theory with fuzzy clustering is integrated to improve the ERT image quality. The fuzzy clustering is applied to determining the key mass function, and dealing with the uncertain, incomplete and inconsistent measured imaging data in ERT. The proposed method was applied to images with the same investigated object under eight typical current drive patterns. Experiments were performed on a group of simulations using COMSOL Multiphysics tool and measurements with a piece of porcine lung and a pair of porcine kidneys as test materials. Compared with any single drive pattern, the proposed method can provide images with a spatial resolution of about 10% higher, while the time resolution was almost the same.

电网企业业财融合管理研究与实践

在电力体制改革的新环境下,电网企业运营重心、运营模式及盈利模式均发生了变化,企业组织管理功能也随之而调整.加强资产运营和输配电成本管理成为电网企业的日常管理重中之重,而业财融合管理便成为工作的核心任务.基于此,作者在多年的电网企业财务管理研究与实践工作基础上,密切结合电网企业业务,提出'两纵一横'业财融合主线框架即横向以生产综合计划与财务预算的融合、纵向以财务业务与运检业务、营销业务的高度融合,形成企业组织架构体系内的'纵横贯通'的业财融合管理体系,提出以制度建设、流程优化和标准建设并结合实际区分侧重点的业财融合管理实践和工作方法.

Driving fatigue fusion detection based on T-S fuzzy neural network evolved by subtractive clustering and particle swarm optimization

In order to improve the accuracy and reliability of the driving fatigue detection based on a single feature, a new detection algorithm based on multiple features is proposed. Two direct driver＇s facial features reflecting fatigue and one indirect vehicle behavior feature indicating fatigue are considered. Meanwhile, T-S fuzzy neural network（TSFNN）is adopted to recognize the driving fatigue of drivers. For the structure identification of the TSFNN, subtractive clustering（SC） is used to confirm the fuzzy rules and their correlative parameters. Moreover, the particle swarm optimization （PSO）algorithm is improved to train the TSFNN. Simulation results and experiments on vehicles show that the proposed algorithm can effectively improve the convergence speed and the recognition accuracy of the TSFNN, as well as enhance the correct rate of driving fatigue detection.

MOLECULAR CLONING AND FUNCTIONAL EXPRESSION OF α-BUNGAROTOXIN (V31) FROM CHINESE CONTINENTAL BANDED KRAIT

The cDNA encoding a variant of α bungarotoxin was cloned from the venom glands of Bungarus multicinctus by RT PCR.The deduced protein precursor contained a 21 amino acid signal peptide and a following 74 amino acid mature protein.The signal peptide is very similar to those of short chain neurotoxins,κ neurotoxins and cardiotoxins.The amino acid sequence of the mature protein is identical to α bungarotoxin (V31),a minor variant of α bungarotoxin identified by protein sequencing technique.Furthermore,the cDNA encoding the deletion precursor of α bungarotoxin was also cloned.By use of pMAL p2,the variant was overexpressed in E coli as a soluble fusion protein and purified by sepharose 6B amylose affinity chromatography,which was confirmed by western blotting with the antisera agai nst α bungarotoxin.The recombinant variant was achieved after digestion by factor X a.It displayed about 1/6 in vivo toxicity of natural α bungarotoxin.The successful cloning and functional expression of α bungarotoxin provided a basis for the future study of structure function of long neurotoxins.

Synergy Decision for Radar and IRST Data Fusion

A new synergy decision method for radar and infrared search and track (IRST) data fusion is proposed, to solve such problems as how to decrease opportunities for radar suffering from being locked on by adverse electronic support measures (ESM), how to retrieve range information of the target during radar off, and how to detect the maneuver of the target. Firstly, polynomials used to predict target motion states are constructed. Secondly, a set of discriminants for detecting target maneuver are established by comparing the predicted values with the observations from IRST. Thirdly, a set of decisions are presented. Lastly, simulation is performed on the given scenario to test the validity of the method.

Genetic Study on JS399-19 Resistance in Hyphal Fusion of Fusarium graminearum by Using Nitrate Nonutilizing Mutants as Genetic Markers

Twenty-two nitrate nonutilizing （nit） mutants were recovered from five wild-type isolates of Fusarium graminearum and fifty nit mutants were recovered from three JS399-19-resistant mutants of F. graminearum cultured on MMC medium. Some biological properties were compared between nit mutants and their parental isolates. The results showed that there were no significant differences in growth rate, cultural characters or pathogenicity between JS399-19-resistant nit mutants and their parental isolates. But the conidial production and the sexual reproduction ability changed to some extent. There was no cross resistance toward chlorate and JS399-19 in F. graminearum and the resistance could be stable through 20-time subcultures. Therefore, the nit could be used as a genetic marker for studying the genetics of JS399-19 resistance in E graminearum, which was used to study JS399-19 resistance transferability in hyphal fusion. Resistance in JS399-19 could not be transferred by hyphal fusion or could be transferred with low chance between two compatible isolates, which would delay the development of JS399-19 resistance in the field.

Intergeneric Somatic Hybrid Plants Between Citrus and Poncirus trifoliata and Evaluation of Their Root Rot Resistance

Protoplasts of Page tangelo (Citrus reticulata Blanco×C. paradisi Macf.) cell suspension culture were electrically fused with mesophyll protoplasts isolated from trifoliate orange (Poncirus trifoliata (L.) Raf.). More than 150 plantlets regenerated after 4-5 months of culture. The regenerated plants were trifoliate with well developed root systems. Root_tip chromosome counting of more than 20 randomly selected plants revealed that they were all tetraploids (2n=4x=36). RAPD analysis of 7 randomly selected plants verified their hybridity. Inoculation of citrus Phytophthora parasitica Dastar toxin on leaves of somatic hybrids and both parental genotypes showed that Page tangelo was moderately susceptible, and trifoliate orange was highly resistant while the somatic hybrids were resistant. The potential of this somatic hybrid as rootstock is also discussed.

Regeneration of Diploid Intergeneric Somatic Hybrid Plants Between Microcitrus and Citrus via Electrofusion

Leaf-derived protoplasts of Rough lemon (Citrus jambhiri Lush, 2n = 2x = 18) were electrofused with embryogenic suspension protoplasts of its relative, Microcitrus papuana Swingle (2n = 2x = 18), with an intention of creating novel germplasm. Six plants were regenerated following protoplasts fusion. Cytological examination demonstrated that they were diploids with 18 chromosomes (2n = 2x = 18). RAPD (random amplified polymorphic DNA) analyses with six arbitrary 10-mer primers showed that the regenerated plants had identical band patterns to those of Rough lemon for primers OPA-07, OPAN-07, OPE-05 and OPA-08, Whereas for the other two primers, OPA-04 and OPS-13, bands specific to M. papuana could be detected in the regenerated plants. Cytological and RAPD analysis revealed that the regenerated plants were diploid somatic hybrids between M. papuana and Rough lemon. The putative hybrids were morphologically similar to Rough lemon. This is the first report on production of diploid somatic hybrid plants between citrus with its related genus via symmetric fusion.

Fluvial reservoir characterization and identification:A case study from Laohekou Oilfield

Finding channel sandbodies is an important task in oil and gas exploration due to the importance of fluvial reservoirs. It is difficult to describe fluvial reservoirs in detail owing to their frequent changes and serious intersections, as well as limitations of S/N ratio and seismic data resolution. Based on the Laohekou 3D data in Shengli Oilfield, we analyze the general characteristics of fluvial reservoirs in this area, from which we find that they are characterized by strong amplitudes on seismic profiles, high continuity on time slices, and low frequency in the frequency domain. In addition, a cluster of strong string-bead- like reflections was found after color processing and detailed interpretation. To understand this observation, we conduct forward modeling to explain the mechanism. This provides a new way to identify ancient channels in similar areas. By using the multi-attribute fusion and RGB display techniques, channel incision is more obvious and the characteristics of the channel structures are manifested much better. Finally, we introduce and apply multi-wavelet detection technology to identify weaker fluvial reservoir signals.

Adaptive Modification of the Rolling Force Prediction

In rolling process, the rolling force is an important parameter. The precision of the predicted rolling force will directly affect the precision of the finished product. By using adaptive control theory and fusing the measured and predicted data, the precision of the predicted rolling force is gradually improved. This system has been used in plant for more than one year, and the result of the application shows that the system has steady and reliable performance, and high precision.

Design of a road vehicle detection system based on monocular vision

In order to decrease vehicle crashes, a new rear view vehicle detection system based on monocular vision is designed. First, a small and flexible hardware platform based on a DM642 digtal signal processor （DSP） micro-controller is built. Then, a two-step vehicle detection algorithm is proposed. In the first step, a fast vehicle edge and symmetry fusion algorithm is used and a low threshold is set so that all the possible vehicles have a nearly 100% detection rate （TP） and the non-vehicles have a high false detection rate （FP）, i. e., all the possible vehicles can be obtained. In the second step, a classifier using a probabilistic neural network （PNN） which is based on multiple scales and an orientation Gabor feature is trained to classify the possible vehicles and eliminate the false detected vehicles from the candidate vehicles generated in the first step. Experimental results demonstrate that the proposed system maintains a high detection rate and a low false detection rate under different road, weather and lighting conditions.

Ultrastructural Observation on the Intra-and Intercellular Microtrabecular Network of the Pollen Mother Cells in Onion ( Allium cepa )

Using DGD embedment_free electron microscopy, ultrastructural observation on the intra_ and intercellular microtrabecular network (MN) of the pollen mother cells (PMC) of the whole meiotic prophase Ⅰ in onion ( Allium cepa L.) was performed. Complex nuclear MN was observed in the nucleus of PMCs, spreading throughout the nuclear region. The nucleolus and chromosomes were connected with the MN filament network. The uniformity of nuclear MN changed with the development of the PMCs. A lamina_like structure surrounded the nucleus and joined the MN in nucleus and in cytoplasm, but it disassembled at the end of prophase Ⅰ. There was also a complex cytoplasmic MN in PMCs, without obvious variation during the prophase Ⅰ. Furthermore, MN in cytoplasmic connections (plasmodesmata and cytoplasmic channels) was noticed to link the frameworks in two neighboring PMCs into one entity. Cytomixis was observed at synizesis of prophase Ⅰ in this experiment, and MN in cytoplasm and in nucleus was noticed to distribute in these granules which migrated from one PMC into its neighboring cell. At this time the nucleus moved aside from center of the PMC, but the rest of the cell was still fulfilled with MN filaments. The relationships of nuclear MN with nucleolus and chromosomes, lamina with nucleus, as well as intra_ and intercellular MN with cytomixis are discussed in this paper.

Embryological Studies on Facultative Apomixis in Apluda mutica (Gramineae)

A cytological study on Apluda mutica L. revealed that this species was a facultative apomict with 60.74% of apomictic embryo sac formation. Its sexual reproduction exhibited the characteristics of polygonum_type embryo sac formation. After the 3 megaspores at the micropylar end had degenerated, leaving only the chalazal megaspore in the nucellus, a nucellar cell adjacent to the megaspore differentiated into an aposporous initial, which later developed into a panicum_type embryo sac. It was an aposporous 4_nucleate embryo sac without chromosome reduction and composed of an egg, a single synergid and a central cell with 2 polar nuclei. The chalazal megaspore degenerated before the onset of the division in the aposporous initial cell.