A Method for Detecting and Recognizing Yi Character Based on Deep Learning

Aiming at the challenges associated with the absence of a labeled dataset for Yi characters and the complexity of Yi character detection and recognition,we present a deep learning-based approach for Yi character detection and recognition.In the detection stage,an improved Differentiable Binarization Network(DBNet)framework is introduced to detect Yi characters,in which the Omni-dimensional Dynamic Convolution(ODConv)is combined with the ResNet-18 feature extraction module to obtain multi-dimensional complementary features,thereby improving the accuracy of Yi character detection.Then,the feature pyramid network fusion module is used to further extract Yi character image features,improving target recognition at different scales.Further,the previously generated feature map is passed through a head network to produce two maps:a probability map and an adaptive threshold map of the same size as the original map.These maps are then subjected to a differentiable binarization process,resulting in an approximate binarization map.This map helps to identify the boundaries of the text boxes.Finally,the text detection box is generated after the post-processing stage.In the recognition stage,an improved lightweight MobileNetV3 framework is used to recognize the detect character regions,where the original Squeeze-and-Excitation(SE)block is replaced by the efficient Shuffle Attention(SA)that integrates spatial and channel attention,improving the accuracy of Yi characters recognition.Meanwhile,the use of depth separable convolution and reversible residual structure can reduce the number of parameters and computation of the model,so that the model can better understand the contextual information and improve the accuracy of text recognition.The experimental results illustrate that the proposed method achieves good results in detecting and recognizing Yi characters,with detection and recognition accuracy rates of 97.5%and 96.8%,respectively.And also,we have compared the detection and recognition algorithms proposed in this paper with other typical algorithms.In these comparisons,the proposed model achieves better detection and recognition results with a certain reliability.

Fireworks Optimization with Deep Learning-Based Arabic Handwritten Characters Recognition Model

Handwritten character recognition becomes one of the challenging research matters.More studies were presented for recognizing letters of various languages.The availability of Arabic handwritten characters databases was confined.Almost a quarter of a billion people worldwide write and speak Arabic.More historical books and files indicate a vital data set for many Arab nationswritten in Arabic.Recently,Arabic handwritten character recognition(AHCR)has grabbed the attention and has become a difficult topic for pattern recognition and computer vision(CV).Therefore,this study develops fireworks optimizationwith the deep learning-based AHCR(FWODL-AHCR)technique.Themajor intention of the FWODL-AHCR technique is to recognize the distinct handwritten characters in the Arabic language.It initially pre-processes the handwritten images to improve their quality of them.Then,the RetinaNet-based deep convolutional neural network is applied as a feature extractor to produce feature vectors.Next,the deep echo state network(DESN)model is utilized to classify handwritten characters.Finally,the FWO algorithm is exploited as a hyperparameter tuning strategy to boost recognition performance.Various simulations in series were performed to exhibit the enhanced performance of the FWODL-AHCR technique.The comparison study portrayed the supremacy of the FWODL-AHCR technique over other approaches,with 99.91%and 98.94%on Hijja and AHCD datasets,respectively.

A Novel 6G Scalable Blockchain Clustering-Based Computer Vision Character Detection for Mobile Images

6G is envisioned as the next generation of wireless communication technology,promising unprecedented data speeds,ultra-low Latency,and ubiquitous Connectivity.In tandem with these advancements,blockchain technology is leveraged to enhance computer vision applications’security,trustworthiness,and transparency.With the widespread use of mobile devices equipped with cameras,the ability to capture and recognize Chinese characters in natural scenes has become increasingly important.Blockchain can facilitate privacy-preserving mechanisms in applications where privacy is paramount,such as facial recognition or personal healthcare monitoring.Users can control their visual data and grant or revoke access as needed.Recognizing Chinese characters from images can provide convenience in various aspects of people’s lives.However,traditional Chinese character text recognition methods often need higher accuracy,leading to recognition failures or incorrect character identification.In contrast,computer vision technologies have significantly improved image recognition accuracy.This paper proposed a Secure end-to-end recognition system(SE2ERS)for Chinese characters in natural scenes based on convolutional neural networks(CNN)using 6G technology.The proposed SE2ERS model uses the Weighted Hyperbolic Curve Cryptograph(WHCC)of the secure data transmission in the 6G network with the blockchain model.The data transmission within the computer vision system,with a 6G gradient directional histogram(GDH),is employed for character estimation.With the deployment of WHCC and GDH in the constructed SE2ERS model,secure communication is achieved for the data transmission with the 6G network.The proposed SE2ERS compares the performance of traditional Chinese text recognition methods and data transmission environment with 6G communication.Experimental results demonstrate that SE2ERS achieves an average recognition accuracy of 88%for simple Chinese characters,compared to 81.2%with traditional methods.For complex Chinese characters,the average recognition accuracy improves to 84.4%with our system,compared to 72.8%with traditional methods.Additionally,deploying the WHCC model improves data security with the increased data encryption rate complexity of∼12&higher than the traditional techniques.

Petrology and Structural Characterization of Post-Neoproterozoic Dolerites from the Kimberlite Fields in the Kéniéba Region (Western Mali)

Post-Neoproterozoic dolerites from the Kéniéba region (Western Mali) are often associated with kimberlites. The rarity of kimberlite outcrops led to the study of doleritic rocks, spatially associated with them. The petrographic and lithogeochemical study showed that the dolerites of the Kéniéba kimberlitic fields are of tholeiitic nature and of the E-MORB (Enriched-Mid Ocean Ridge Basalt) type. This reflects an enrichment over time, compared to the Birimian dolerites of the volcano-sedimentary greenstone belt of Toumodi, in central C?te d’Ivoire. Furthermore, these dolerites are enriched in SiO2, TiO2, Zr and poor in Fe2O3, MgO. These dolerites would have formed in a late to post-orogenic intracontinental context during the breakup of Gondwana. Structurally, Kéniéba dolerites are often associated with kimberlite pipes, fractures and large deep structures identified using aeromagnetic images. Taking into account the fact that kimberlites do not outcrop in the Kéniéba region, the geochemical study coupled with the interpretation of aeromagnetic data proved to be very useful for the search for pipes.

Chip Surface Character Recognition Based on OpenCV

Chip surface character recognition is an important part of quality inspection in the field of microelectronics manufacturing.By recognizing the character information on the chip,automated production,quality control,and data collection and analysis can be achieved.This article studies a chip surface character recognition method based on the OpenCV vision library.Firstly,the obtained chip images are preprocessed.Secondly,the template matching method is used to locate the chip position.In addition,the surface characters on the chip are individually segmented,and each character image is extracted separately.Finally,a Support Vector Machine(SVM)is used to classify and recognize characters.The results show that this method can accurately recognize the surface characters of chips and meet the requirements of chip quality inspection.

Effects of Vermicompost on Agronomic Characters and Yield and Quality of Flue-cured Tobacco

The effects of vermicompost on the agronomic characters and yield and quality of flue-cured tobacco were investigated. The results showed that, the field growth periods of various treatments were 117-118 d, 1-2 days longer than that of the CK. The numbers of effective leaves of the treatments applied with vermicompost were 0.1-0.3 leaf more than the CK. The highest yield and the highest proportion of high-grade tobacco occurred in treatment 3 as 2 095.5 kg/m^2 and 49%, respectively, which were higher than those in the CK by 6.58 kg and 5.3%. In conclusion, the treatment with the application of vermicompost at 7 500-10 500 kg/hm^2 was the best.

Characterization of 124 Flue-cured Tobacco Germplasm Resources

[Objective] This study aimed to characterize 124 flue-cured tobacco germplasm resources, and to provide reference for making the best use of the existing flue-cured tobacco germplasm resources. [Method] A total of 124 flue-cured tobacco germplasm resources were studied via field experiment and statistic analysis to investigate characteristics of their growth period, morphologic characters, main agronomic traits, and economic characters. [Result] There were significant differences among the 124 flue-cured tobacco germplasm resources in growth period, morphologic characters, main agronomic traits, and economic characters. The coefficients of variation （CV） varied in a range of 7.9%-22.5%. Among them, CV of bud stage was higher, and that of corolla length was lower. Many germplasm resources were attacked seriously by black shank disease at the end of field experiment, including those with disease index higher than 90, like Kutsaga 110, TI706, Ky 151, KM10, Longshe, Chaoxian Kangchi, Kutsaga 51E, Yongding No.1, and those with disease index among 75-90 such as Liaoyan No. 8, Lingnong No.2, Shandong Duoye, 581, Cunjingyan, KRK26, and Special 400. The tobacco root knot nematode invasion was light in some germplasm or never happened in other germplasm resources. TMV happened sporadically. CV 87, Yunyan 99, Yunyan 85, K326, Yunyan 87, Zhubuo No.1, T64 and T66 produced higher yield, production value, proportion of good leaves and sold at a higher price. Finally, we screened out the germpalsm resources with good comprehensive economic values and high disease resistance such as CV 87, Yunyan 99, Yunyan 85, K326, Yunyan 87, Zhubuo No.1, T64, T66, Honghuadajinyan, G-28, Taiyan No. 8, 77089-12, Yunyan 97, K346, V2, K149, NC567, NC297, Yunyan 201, Yunyan 203, KRK22. [Conclusion] This study provides reference for making better use of tobacco germplasm resources, and breeding new varieties.

An Approach to Unsupervised Character Classification Based on Similarity Measure in Fuzzy Model

This paper presents a fuzzy logic approach to efficiently perform unsupervised character classification for improvement in robustness, correctness and speed of a character recognition system. The characters are first split into eight typographical categories. The classification scheme uses pattern matching to classify the characters in each category into a set of fuzzy prototypes based on a nonlinear weighted similarity function. The fuzzy unsupervised character classification, which is natural in the repre...

Identification of Quality Characteristics of Sun-cured Tobacco Leaves

[Objective] The aim was to explore tobacco varieties which satisfy tobacco formula and is suitable to be grown in ecotopes simultaneously. [Method] Interior and exterior qualities of tobacco were compared and identified based on agronomic and economic characters of tobacco in fields. [Result] Yunshai No.1 was better in both agronomic and economic characters. Specifically, the fragrance was dominated by empyreumatique and aroma; the highly-qualified variety is fragrant and sweet, with little irritation, which gives the tobacco smoke a light, mild flavor. As for Virgini- a934, economic characters were better, but agronomic characters were just ordinary. Similar to Yunshai No.l, dominated by empyreumatique and aroma, the variety was with distinctive resin and herbaceous fragrance. What＇s more, it tasted good with high quality and usability. Cunsanpi was ordinary in agronomic characters, and poor in economic characters, with coordinated quality and chemical composition. It is fra- grant and the smoke is clean. However, the quality was not so high and it tasted not so good. Tengruan No.2 was good in agronomic characters, but poor in eco- nomic characters, which gives delicate fragrance, but not clean enough. Waiweiba and Mijie Qinggeng neither taste well nor smell sweet, performing ordinary in agro- nomic and economic characters. Hence, the two varieties seem bad in quality and ranks poorly. [Conclusion] In terms of sensory quality, the varieties from high to low were Yunshai No.1, Virginia 934, Cunsanpi, Tengruan No.2, Waiweiba and Mijie Qinggeng.

Guilt Transformation and Redemption——A Character Analysis of Charlie in Fitzgerald's Babylon Revisited

Babylon Revisited is F.Scott Fitzgerald's most renowned and most considered work of short fiction.In the short story "Babylon Revisited,"F.Scott Fitzgerald generally centers on a theme of defining American character.The central figure in Babylon Revisited,Charlie Wales,serves as the lens through which readers observe the events of the story and the life that once thrived in Paris.The controversial questions are also explained in this paper.

Effects of Green Manure Mixed Cropping Patterns on Physical and Chemical Properties of Soil and Economic Characters of Flue-cured Tobacco

[Objective] The aim was to clear the suitable green manure cropping pat- terns in Xiangxi tobacco-planting areas. [Method] 8 treatments were set to study the effects of the monoculture and mixed cropping of common vetch （Vicia gigantea Bge.）, perennial ryegrass （Lofium） and rapeseed （Brassica campestris L.） on physi- cal and chemical properties of soil and economic characters of flue-cured tobacco. [Result] （1） Green manure turnover can reduce soil bulk density by 1.08%-8.62%, and the effect of green manure mixed cropping pattern was the best. （2） Green manure turnover also can increase the soil nutrient, soil organic matter, total nitro- gen （N）, total phosphorus （P）, total potassium （K）, alkali-hydrolyzale N, rapidly available P and rapidly available K by 1.44%-6.10%, 0.01-0.12 g/kg, 1.89%- 11.32%, 0.12%-3.56%, 1.06%-11.76%, 0.04%-18.93% and 0.98%-23.12%, respec- tively, and the effect of the monoculture of common vetch was the best.（3） The overall change of soil pH was not obvious.（4）Green manure turnover can increase the yield and output of flue-cured tobacco, and the effect of the monoculture of common vetch was the best. [Conclusion] The monoculture of common vetch can be generalized in the dry land of Xiangxi tobacco-planting areas.

Study on Biological Characters of Asparagus macowanii Baker.

Asparagus macowanfi Baker, is a climbing herbaceous foliage species in genus Asparagus of Liliaceae, This paper summarized its multiple uses, morphologi- cal characteristics, biological habit, reproduction methods, management after cultiva- tion, prevention and control of pests and disease, as well as harvest and grading, with the objective to provide references for the exploitation and utilization of As- paragus macowanii Baker.

STUDY FOR THE BIFURCATION TOPOLOGICAL STRUCTURE AND THE GLOBAL COMPLICATED CHARACTER OF A KIND OF NONLINEAR FINANCE SYSTEM(Ⅰ)

Based on the work discussed on the former study, this article first starts from the mathematical model of a kind of complicated financial system, and analyses all possible things that the model shows in the operation of our country's macro_financial system: balance, stable periodic, fractal, Hopf_bifurcation, the relationship between parameters and Hopf_bifurcation, and chaotic motion etc. By the changes of parameters of all economic meanings, the conditions on which the complicated behaviors occur in such a financial system, and the influence of the adjustment of the macro_economic policies and adjustment of some parameter on the whole financial system behavior have been analyzed. This study will deepen people's understanding of the lever function of all kinds of financial policies.

Studies on Oxygen Characteristics of YBa_2Cu_3O_(7-x) and Its Applications to Air Separation and Gas Purification

Oxygen diffusion and oxygen selective adsorption properties of rare earths material YBa_2Cu_3O_(7-x) (YBCO) were investigated by thermogravimetric, oxygen static adsorption and selectivity adsorption experiments. The results show that YBCO is a very good deoxidizing material. The oxygen desorption of YBCO begins remarkably at about 400 ℃, mass loss can arrive at 1.2% of its original quantity at 800 ℃. Oxygen can be completely absorbed back into the sample again when temperature descends to 400 ℃. The oxygen adsorption selectivity, reproducibility and oxygen adsorption under very low oxygen partial pressure make the material desirable for air separation and gas purification. High purity nitrogen gas was produced with the YBCO molecular sieves in the air separation and gas purification experiments. 0.017 m^3 of high purity nitrogen (>99.9999%) can be obtained with 1 kg YBCO molecular sieve in one cycle. As a deoxidant, an obvious advantage of YBCO is that no hydrogen is needed in its applications.

A new interpolation method based on satellite physical character in using IGS precise ephemeris

Due to the deficiency of sliding Lagrange polynomial interpolation, the author proposes a new interpolation method, which considers the physical character of satellite movement in coordinate transformation and reasonable selection of interpolation function. Precision of the two methods is compared by a numerical example. The result shows that the new method is superior to the sliding Lagrange polynomial interpolation in interpolation and extrapolation, especially in extrapolation that is over short time spans.

Denoising of Chinese calligraphy tablet images based on run-length statistics and structure characteristic of character strokes

In this paper, a novel approach is proposed for denoising of Chinese calligraphy tablet documents. The method includes two phases: First, a partial differential equations (PDE) based the total variation model and Otsu thresholding method are used to preprocess the calligraphy document image. Second, a new method based on run-length statistics and structure charac- teristics of Chinese characters is proposed to remove some random and ant-like noises. This includes the optimal threshold se- lection from histogram of run-length probability density, and improved Hough transform algorithm for line shape noise detection and removal. Examples are given in the paper to demonstrate the proposed method.

STUDY FOR THE BIFURCATION TOPOLOGICAL STRUCTURE AND THE GLOBAL COMPLICATED CHARACTER OF A KIND OF NONLINEAR FINANCE SYSTEM(Ⅱ)

Based on the work discussed on the former study, this article first starts from the mathematical model of a kind of complicated financial system, and analyses all possible things that the model shows in the operation of our country's macro_financial system: balance, stable periodic, fractal, Hopf_bifurcation, the relationship between parameters and Hopf_bifurcation, and chaotic motion etc. By the changes of parameters of all economic meanings, the conditions on which the complicated behaviors occur in such a financial system, and the influence of the adjustment of the macro_economic policies and adjustment of some parameter on the whole financial system behavior have been analyzed. This study will deepen people's understanding of the lever function of all kinds of financial policies.

Optimised CNN Architectures for Handwritten Arabic Character Recognition

Handwritten character recognition is considered challenging compared with machine-printed characters due to the different human writing styles.Arabic is morphologically rich,and its characters have a high similarity.The Arabic language includes 28 characters.Each character has up to four shapes according to its location in the word(at the beginning,middle,end,and isolated).This paper proposed 12 CNN architectures for recognizing handwritten Arabic characters.The proposed architectures were derived from the popular CNN architectures,such as VGG,ResNet,and Inception,to make them applicable to recognizing character-size images.The experimental results on three well-known datasets showed that the proposed architectures significantly enhanced the recognition rate compared to the baseline models.The experiments showed that data augmentation improved the models’accuracies on all tested datasets.The proposed model outperformed most of the existing approaches.The best achieved results were 93.05%,98.30%,and 96.88%on the HIJJA,AHCD,and AIA9K datasets.

Dynamic character analysis for the arc welding power source based on fuzzy logic

A lot of experimental methods have been brought forth to assess the dynamic character of the arc welding power source, but up to now, this issue has not been solved very well. In this paper, based on the fuzzy logic reasoning method, a dynamic character assessing model for the arc welding power source was established and used to analyze the dynamic character of the welding power source. Three different types of welding machine have been tested, and the characteristic information of the electrical signals such as re-striking arc voltage, low welding current and so on of the welding process were extracted accurately by using a self-developed welding dynamic arc wavelet analyzer. The experimental results indicate that this model can be used as a new assessing method for the dynamic character of the arc welding power source.

Lytic Characteristics and Identification of Two Alga-lysing Bacterial Strains

All previously reported bacterial species which are capable of lysing harmful algae have been isolated from coastal environments in which harmful algae blooms have occurred. Due to the low concentration of alga-lysing bacteria in an algal bloom, it is difficult to isolate the alga-lysing bacteria by existing methods. In this paper, two algae-lysing bacterial strains, P01 and P03, have been isolated from a biosystem immobilized on a sponge that was highly effective in removing algae and microcystins. Their lysing modes and effects on Microcystis aeruginosa have been studied. The results show that the degradation processes of these two strains for M. aeruginosa accorded with a first-order reaction model when the chlorophylla concentration was in the range from 0 to 1000 μgL-1. The degradation rate constants were 0.1067, 0.1274 and 0.2792 for P01 and0.0683, 0.0744 and 0.028 97 for P03, when the bacterial densities were 8.6 × 105, 8.6 × 106 and 8.6 × 107cells mL-1 respectively. Moreover, the two bacterial strains had favourable lytic effects not only on M. aeruginosa , but also on Chlorella and Scene-desmus. Their lytic effect on M. aeruginosa did not require physical cell to cell contact, but proceeded by the production of an extracellular product. The bacterial strains were identified as Bacillus species by PCR amplification of the 16S rRNA gene, BLAST analysis, and comparison with sequences in the GenBank nucleotide database.