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.

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.

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.

Effect of Co on Solidification Characteristics and Microstructural Transformation of Non-equilibrium Solidified Cu-Ni Alloys

Non-equilibrium solidification structures of Cu55Ni45 and Cu55Ni43Co2 alloys were prepared by the molten glass purification cycle superheating method.The variation of the recalescence phenomenon with the degree of undercooling in the rapid solidification process was investigated using an infrared thermometer.The addition of the Co element affected the evolution of the recalescence phenomenon in Cu-Ni alloys.The images of the solid-liquid interface migration during the rapid solidification of supercooled melts were captured by using a high-speed camera.The solidification rate of Cu-Ni alloys,with the addition of Co elements,was explored.Finally,the grain refinement structure with low supercooling was characterised using electron backscatter diffraction(EBSD).The effect of Co on the microstructural evolution during nonequilibrium solidification of Cu-Ni alloys under conditions of small supercooling is investigated by comparing the microstructures of Cu55Ni45 and Cu55Ni43Co2 alloys.The experimental results show that the addition of a small amount of Co weakens the recalescence behaviour of the Cu55Ni45 alloy and significantly reduces the thermal strain in the rapid solidification phase.In the rapid solidification phase,the thermal strain is greatly reduced,and there is a significant increase in the characteristic undercooling degree.Furthermore,the addition of Co and the reduction of Cu not only result in a lower solidification rate of the alloy,but also contribute to the homogenisation of the grain size.

Audio2AB:Audio-driven collaborative generation of virtual character animation

Background Considerable research has been conducted in the areas of audio-driven virtual character gestures and facial animation with some degree of success.However,few methods exist for generating full-body animations,and the portability of virtual character gestures and facial animations has not received sufficient attention.Methods Therefore,we propose a deep-learning-based audio-to-animation-and-blendshape(Audio2AB)network that generates gesture animations and ARK it's 52 facial expression parameter blendshape weights based on audio,audio-corresponding text,emotion labels,and semantic relevance labels to generate parametric data for full-body animations.This parameterization method can be used to drive full-body animations of virtual characters and improve their portability.In the experiment,we first downsampled the gesture and facial data to achieve the same temporal resolution for the input,output,and facial data.The Audio2AB network then encoded the audio,audio-corresponding text,emotion labels,and semantic relevance labels,and then fused the text,emotion labels,and semantic relevance labels into the audio to obtain better audio features.Finally,we established links between the body,gestures,and facial decoders and generated the corresponding animation sequences through our proposed GAN-GF loss function.Results By using audio,audio-corresponding text,and emotional and semantic relevance labels as input,the trained Audio2AB network could generate gesture animation data containing blendshape weights.Therefore,different 3D virtual character animations could be created through parameterization.Conclusions The experimental results showed that the proposed method could generate significant gestures and facial animations.

Frontier Progress of Landscape Character Assessment in China

The role of Landscape Character Assessment(LCA)at the level of territorial landscape governance spans both natural and social sciences.By analyzing the development history,research distribution,methods and applications of cutting-edge cases of LCA in China,the following conclusions are drawn:①the LCA research in China originated earlier than that in Europe,but has not yet been systematically applied to the implementation of urban and rural planning at all levels;②the fundamental theory of LCA in China has been well constructed,with three main research directions:technologyled,assessment-led,and assessment combined with other theories;③the development of LCA in rural areas is more mature than in urban areas,but the progress of research is uneven across regions;④the current research presents significant“bottom-up”academic characteristics,and there is an urgent need for government decision-making authorities and academia to jointly promote a“top-down”standardized governance mechanism to comprehensively promote the modernization of territorial landscape governance.

Discussion of Online Teaching Strategies for Teaching Elementary Chinese Characters to Foreigners Based on Error Analyses

The expanding role of the Chinese language in international communications has become increasingly prominent as China’s comprehensive national power continues to grow,leading to a significant rise in the number of Chinese language learners.Since online teaching is not limited by time and space,its application is widespread.For beginners in the Chinese language,the Chinese characters are both a priority and a challenge.The“Chinese Character Classification,”also known as the“Six Writings,”is the earliest systematic theory of Chinese character structures,and teaching Chinese characters in categories based on the“Chinese Character Classification”is a method that fits the cognition of beginners.In order to teach Chinese characters in a targeted approach,based on the collection and analysis of the common errors of Chinese characters among beginners,(1)this paper proposes that(a)the intuitive method can be applied to teach pictographic characters,indicative characters,and associative compound characters in online teaching;(b)the inductive-deductive method of“basic characters to new characters”can be applied for the teaching of pictophonetic characters and associative compound characters;(c)the learning of character patterns should be approached in a whole-part-whole process,while importance should be attached to the suggestion of the frequency effect with a view to facilitating the online learning of Chinese characters for beginners.The aim of this paper is to provide some practical implications for the online teaching of Chinese characters to foreigners.

Research on the Path of Integrating Ideological and Political Courses into College Physical Education Courses Under the Background of Cultivating Moral Character and Cultivating People

The national education department clearly pointed out in the“Guidelines for the Construction of Ideological and Political Curriculum in Colleges and Universities”that colleges and universities need to take on the fundamental task of cultivating moral character and cultivating people in the process of education,and reasonably integrate ideological and political courses into the curriculum to promote the overall improvement of students’ideological and political quality.This article outlines the connotation of ideological and political courses in the context of cultivating moral character and cultivating people,analyzes and summarizes the significance of integrating ideological and political courses into college physical education courses,summarizes existing problems in the construction of ideological and political courses in college physical education,and explores the path of integrating ideological and political courses into college physical education courses under the background of cultivating moral character and cultivating people,with a view to providing guidelines for teachers.

Typos Correction in Overseas Chinese Learning Based on Chinese Character Semantic Knowledge Graph

In recent years, more and more foreigners begin to learn Chinese characters, but they often make typos when using Chinese. The fundamental reason is that they mainly learn Chinese characters from the glyph and pronunciation, but do not master the semantics of Chinese characters. If they can understand the meaning of Chinese characters and form knowledge groups of the characters with relevant meanings, it can effectively improve learning efficiency. We achieve this goal by building a Chinese character semantic knowledge graph (CCSKG). In the process of building the knowledge graph, the semantic computing capacity of HowNet was utilized, and 104,187 associated edges were finally established for 6752 Chinese characters. Thanks to the development of deep learning, OpenHowNet releases the core data of HowNet and provides useful APIs for calculating the similarity between two words based on sememes. Therefore our method combines the advantages of data-driven and knowledge-driven. The proposed method treats Chinese sentences as subgraphs of the CCSKG and uses graph algorithms to correct Chinese typos and achieve good results. The experimental results show that compared with keras-bert and pycorrector + ernie, our method reduces the false acceptance rate by 38.28% and improves the recall rate by 40.91% in the field of learning Chinese as a foreign language. The CCSKG can help to promote Chinese overseas communication and international education.

Review of Optical Character Recognition for Power System Image Based on Artificial Intelligence Algorithm

Optical Character Recognition(OCR)refers to a technology that uses image processing technology and character recognition algorithms to identify characters on an image.This paper is a deep study on the recognition effect of OCR based on Artificial Intelligence(AI)algorithms,in which the different AI algorithms for OCR analysis are classified and reviewed.Firstly,the mechanisms and characteristics of artificial neural network-based OCR are summarized.Secondly,this paper explores machine learning-based OCR,and draws the conclusion that the algorithms available for this form of OCR are still in their infancy,with low generalization and fixed recognition errors,albeit with better recognition effect and higher recognition accuracy.Finally,this paper explores several of the latest algorithms such as deep learning and pattern recognition algorithms.This paper concludes that OCR requires algorithms with higher recognition accuracy.

Analysis of Young Girls’Eagerness to Spend for Disney Virtual Characters Based on Marketing Mix Theory

A virtual character is a design of a fictitious creature with distinctive characteristics created by people,and Disney virtual characters are those Intellectual Property(IP)images that appeared in Disneyland and Disney movies.This investigation aimed to explore why many younger females are keen to spend money on Disney virtual characters.This paper adopted the Marketing Mix Theory strategy(product,price,placement,and promotion(4P)),and the SWOT analysis method has been utilized.This paper investigated the relationship between the 4Ps and consumers’purchasing intentions,and it turned out that unique design and effective promotion in this Disney case would promote consumers’purchase intention,while the higher price and less accessible placements affected their purchase intentions.Thus,the high price and limited places somewhat inhibit customers’desire to buy;due to the attractiveness of the product itself and the promotion on the internet,the target consumers are still willing to consume.

乡村体育赛事赋能乡村振兴的SWOT分析——以贵州“村超”“村BA”为例

本文运用文献综述法、专家访谈法等研究方法,以贵州“村超”“村BA”为例,论证乡村体育赛事赋能乡村振兴的必要性,分析乡村体育赛事赋能乡村振兴的优势、劣势、机遇和挑战,对乡村体育赛事赋能乡村振兴的因素进行系统分析,建立SWOT矩阵模型,提出乡村体育赛事赋能乡村振兴的制定增长型(S-O)、实施弥补型(W-O)、拟定拓展型(S-T)和采取防御型(W-T)发展策略,从而推动乡村经济高质量发展,以期全面实现乡村振兴战略目标。

乡村振兴战略下农村群众体育赛事的多维价值、制约因素与铺展路径——基于“村BA热”的思考

农村群众性体育赛事高度契合人民群众对美好生活追求的时代需要,是助力乡村振兴战略的重要抓手。采用文献资料法、逻辑分析法等研究方法,基于“价值探析—因素审视—路径铺展”的整体逻辑框架,旨在诠释乡村振兴战略背景下我国农村群众体育赛事的多重功能与作用,探明当前制约农村群众体育赛事进一步发展的潜在影响因素,并提出解决思路。研究认为:从实践成效来看,农村群众体育赛事具备产生经济效益、放大社会效益、提高社区凝聚力、促进社会发展以及改善农民生活等功能,为乡村产业兴旺、生态宜居、乡风文明、有效治理及生活富裕提供了助力支点。从理论与实践视角出发,发现乡村生活挖掘不充分、专业人才储备不充裕、乡村文化建设不到位、生态特色功能不明显、社会组织力量不聚合等是制约我国农村群众体育赛事进一步高质量发展的潜在制约因素。因此,提出坚持讲述乡村美好生活,深化赛事本质内涵;强化乡村人才效应,保障赛事运作质量;优化乡风文明环境,提升赛事开展活力;凸显乡村生态特色,扩大赛事承办优势;发挥乡村组织合力,增强赛事治理效能等铺展路径。

“村超”“村BA”助力贵州乡村体育产业高质量发展研究

基于乡村振兴的战略背景,厘清了“村超”“村BA”助力贵州乡村体育产业高质量发展的价值意蕴,剖析了“村超”“村BA”助力贵州乡村体育产业高质量发展的优势及现实困境,提出了“村超”“村BA”助力贵州乡村体育产业高质量发展的纾解路径,以期助推“十四五”时期贵州国民经济社会高质量发展.

“村BA”与乡村振兴文化建设的耦合发展研究——以贵州台盘村“村BA”为例

“村BA”是指在村里举行的以当地村民为运动主体的具有当地特色的篮球比赛。从运动员到奖品,“村BA”都与现代商业性体育文化形成鲜明相比。“村BA”虽以体育文化身份亮相乡村,却耦合乡村振兴过程中文化建设在物质、制度和精神三个层面发展需要,推动着乡村振兴过程中的文化建设。文章将从文化的物质、制度和精神三个层面解构“村BA”在乡村振兴过程中的耦合功能,多角度、多视点探讨乡村振兴过程中文化振兴的发展样式。

从“村BA”的火爆出圈探析群众体育高质量发展路径

促进群众体育高质量发展是推动我国体育事业持续健康发展的重要组成部分,也是实现体育大国向体育强国转变的关键一环。“村BA”作为一种群众体育活动,在丰富了农民文化生活的同时,也促进了农村体育事业的发展,推动了全民健身的普及和发展。文章结合火爆全网的“村BA”的发展情况,通过分析其火爆出圈的原因,以及我国群众体育发展现状存在的问题,对群众体育高质量发展的路径进行了探讨,旨在促进群众体育更好发展。

叶面喷施6-BA对盐胁迫下不同种源黑果枸杞幼苗生理指标和光合特性的影响

以青海黑果枸杞和甘肃黑果枸杞实生苗为试验材料,分析不同浓度6-苄氨基腺嘌呤(6-BA)对盐胁迫下不同种源黑果枸杞幼苗生理指标、抗氧化系统和光合参数的影响。结果表明:(1)施加低、中浓度6-BA降低了无盐条件下两种黑果枸杞叶片和根中Na^(+)和Cl^(-)质量分数、过氧化氢(H_(2)O_(2))质量摩尔浓度、电解质外渗率,提高了抗坏血酸过氧化酶(APX)、谷胱甘肽还原酶(GR)、硝酸还原酶(NR)和ATP硫酸化酶(ATPS)活性,以及还原型谷胱甘肽(GSH)、氧化型谷胱甘肽(GSSG)、氮(N)、硫(S)质量分数和光合氮利用效率;高浓度6-BA对无盐条件下两种黑果枸杞上述指标却有相反的作用。(2)与青海黑果枸杞相比,甘肃黑果枸杞在盐胁迫下叶片中积累了更多的Na^(+)和Cl^(-),并遭受更大的氧化胁迫,表现为叶片中更高的H_(2)O_(2)质量摩尔浓度和电解质渗出率以及更低的光合参数。(3)受到盐胁迫后,青海黑果枸杞体内抗坏血酸过氧化物酶(APX)和谷胱甘肽还原酶(GR)活性高于甘肃黑果枸杞,但甘肃黑果枸杞的超氧化物歧化酶(SOD)活性更高。(4)与甘肃黑果枸杞相比,青海黑果枸杞叶中的氮和硫通过提高同化酶—硝酸还原酶(NR)和ATP硫酸化酶(ATPS)活性而积累更多,从而使叶片中还原型谷胱甘肽(GSH)质量分数显著提高。(5)低、中浓度6-BA有利于提高青海黑果枸杞和甘肃黑果枸杞氮硫同化效率、GSH质量分数以及APX和GR的活性,导致在无盐条件下光合作用增强,缓解了盐胁迫下光合作用的下降,限制了叶片中Na^(+)和Cl^(-)的质量分数,提高了光合氮利用效率;然而高浓度6-BA的应用对黑果枸杞的生长具有反作用;6-BA对青海黑果枸杞盐胁迫下各生理指标变化的影响比甘肃黑果枸杞更明显。因此,6-BA的施用,使青海黑果枸杞的NR和ATPS活性提高,增强了抗氧化防御系统的功能,缓解了盐胁迫引起光合作用减弱的现象。

地方特性与新山乡巨变——关于“村BA”纪实叙事的文化解码

在人本主义地理学者看来,人类生活在充满意义内涵的世界中,地方是人们对世界的一种主观态度和情感体验,一个地方的动态性、开放性、独特性与地方历史和特定地域人们的实践活动分不开。作为乡村振兴之写照的文化热点事件,台盘“村BA”球赛的火爆出圈与地方独特的精神生活密切相关,姚瑶所著的《村BA:观察中国式现代化的一个窗口--台盘村乡村振兴故事》正是对这种地方特性及乡村巨变的诗性书写与文化解码。