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.

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.

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.

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.

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.

Sailfish Optimizer with Deep Transfer Learning-Enabled Arabic Handwriting Character Recognition

The recognition of the Arabic characters is a crucial task incomputer vision and Natural Language Processing fields. Some major complicationsin recognizing handwritten texts include distortion and patternvariabilities. So, the feature extraction process is a significant task in NLPmodels. If the features are automatically selected, it might result in theunavailability of adequate data for accurately forecasting the character classes.But, many features usually create difficulties due to high dimensionality issues.Against this background, the current study develops a Sailfish Optimizer withDeep Transfer Learning-Enabled Arabic Handwriting Character Recognition(SFODTL-AHCR) model. The projected SFODTL-AHCR model primarilyfocuses on identifying the handwritten Arabic characters in the inputimage. The proposed SFODTL-AHCR model pre-processes the input imageby following the Histogram Equalization approach to attain this objective.The Inception with ResNet-v2 model examines the pre-processed image toproduce the feature vectors. The Deep Wavelet Neural Network (DWNN)model is utilized to recognize the handwritten Arabic characters. At last,the SFO algorithm is utilized for fine-tuning the parameters involved in theDWNNmodel to attain better performance. The performance of the proposedSFODTL-AHCR model was validated using a series of images. Extensivecomparative analyses were conducted. The proposed method achieved a maximum accuracy of 99.73%. The outcomes inferred the supremacy of theproposed SFODTL-AHCR model over other approaches.

“Cartoon Characters Can Touch Your Soul and Set Trends”——Interview with Lina JU,Chief Designer of GENMEC

Recently,HUGY has become quite popular in the Chinese market.The character can been seen everywhere,from its emojis,memes,cartoon stories,and art toys,to T-shirts,candies,garments.HUGY is a cartoon of a cute puppy,who is always smiling widely and reaching out his arms,ready to hug you.We invited the character’s creator,Lina Ju for an interview.Lina Ju comes from South Korea but has been working in China for 10 years.She is the chief designer of GENMEC,a trendy brand belonging to Sums Model,a company based in the south of China.

Effects of Microelement Fertilizers on Main Economic Characters and Yield of Peanut

The main purpose of this study was to explore and master the optimal types and application methods of microelement fertilizers suitable for peanut cultivation in Linyi City.The results showed that the application of zinc,magnesium,sulfur,calcium and other microelement fertilizers to peanut plants had a certain yield-increasing effect,and zinc had the most significant yield-increasing effect.Compared with the control check(CK),the yield per unit area increased by 1431 kg/hm^(2),equivalent to an increase of 38.4%.Meanwhile,according to field investigation and observation,the treatment of increasing zinc fertilizer had a certain promotion effect on peanut emergence rate,seedling growth potential,and yield components.

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.

Comparative Study on Biological and Commercial Characteristics of Multiple Varieties of Broccoli(Brassica oleracea L.var.italica Plenck)and Vegetable Soybean(Glycine max(L.)Merr.)

[Objectives]This study was conducted to select vegetable soybean varieties(Glycine max(L.)Merr.)that are suitable for local cultivation and meet export requirements.[Methods]Through continuous years of comparative experiments on broccoli and vegetable soybean varieties,detailed biological characteristic and economic quality data of multiple varieties were obtained.[Results]Vegetable soybean variety Taiwan 75-3 had very prominent early-maturing trait,the highest quality(qualification rate),and higher yield than the control check(CK);and the early-maturing trait of vegetable soybean variety Kaohsiung 9 was also prominent,and its yield was higher than that of the CK.They could be promoted as the main vegetable soybean varieties for spring open field cultivation in this region.Among the tested broccoli varieties,Lake had a higher yield,and was relatively tolerant to cold.It had an early harvest period,and was planted as an early autumn variety in this region.Naihan Youxiu showed the highest yield,good quality,cold resistance,and strong adaptability,making it suitable for planting as a late autumn variety in this region.[Conclusions]This study provides technical guidance for the cultivation of local broccoli and vegetable soybean.

Associations between Mental Health Outcomes and Adverse Childhood Experiences and Character Strengths among University Students in Southern China

Adverse childhood experiences(ACEs)can negatively affect mental health,whereas character strengths seem to be positively correlated with mental health.Detailed information on the history of ACEs among university students in China and the extent which mental health is associated with ACEs and character strengths can contribute to the needed empirical evidence for relevant stakeholders.Objectives of this study are 1)to estimate the prevalence of ACEs among undergraduate students in Southern China;and 2)to assess the extent which mental health outcomes(positive growth,well-being,and depression)are associated with ACEs and character strengths among undergraduate students in Southern China.We conducted a self-administered survey amongfirst and second-year students at a university in Southern China and analyzed data using descriptive statistics and linear regression analyses.Among the 779 students who completed the questionnaire,283 were males,439 were females,and 57 did not indicate their gender.The prevalence of ACEs among the participants was 32.1%.History of ACEs was associated with lower positive growth score(Adjusted Beta=-0.20;95%CI=-0.37,-0.02;p=0.030)and lower well-being score(Adjusted Beta=-1.13;95%CI=-2.04,-0.23;p=0.014).Vitality domain of character strength was associated with all three mental health outcomes after adjusting for covariables(all p-values<0.001).Our studyfindings provide empirical evidence for stakeholders in university mental health.However,caveats regarding lack of temporality,selection bias,social desirability bias,and lack of generalizability should be considered in the interpretation of the studyfindings.

On the Mean Value of High-Powers of a Special Character Sum Modulo a Prime

In this paper,we use the elementary methods,the properties of Dirichlet character sums and the classical Gauss sums to study the estimation of the mean value of high-powers for a special character sum modulo a prime,and derive an exact computational formula.It can be conveniently programmed by the“Mathematica”software,by which we can get the exact results easily.

Arabic Optical Character Recognition:A Review

This study aims to review the latest contributions in Arabic Optical Character Recognition(OCR)during the last decade,which helps interested researchers know the existing techniques and extend or adapt them accordingly.The study describes the characteristics of the Arabic language,different types of OCR systems,different stages of the Arabic OCR system,the researcher’s contributions in each step,and the evaluationmetrics for OCR.The study reviews the existing datasets for the Arabic OCR and their characteristics.Additionally,this study implemented some preprocessing and segmentation stages of Arabic OCR.The study compares the performance of the existing methods in terms of recognition accuracy.In addition to researchers’OCRmethods,commercial and open-source systems are used in the comparison.The Arabic language is morphologically rich and written cursive with dots and diacritics above and under the characters.Most of the existing approaches in the literature were evaluated on isolated characters or isolated words under a controlled environment,and few approaches were tested on pagelevel scripts.Some comparative studies show that the accuracy of the existing Arabic OCR commercial systems is low,under 75%for printed text,and further improvement is needed.Moreover,most of the current approaches are offline OCR systems,and there is no remarkable contribution to online OCR systems.

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.

A Novel Siamese Network for Few/Zero-Shot Handwritten Character Recognition Tasks

Deep metric learning is one of the recommended methods for the challenge of supporting few/zero-shot learning by deep networks.It depends on building a Siamese architecture of two homogeneous Convolutional Neural Networks(CNNs)for learning a distance function that can map input data from the input space to the feature space.Instead of determining the class of each sample,the Siamese architecture deals with the existence of a few training samples by deciding if the samples share the same class identity or not.The traditional structure for the Siamese architecture was built by forming two CNNs from scratch with randomly initialized weights and trained by binary cross-entropy loss.Building two CNNs from scratch is a trial and error and time-consuming phase.In addition,training with binary crossentropy loss sometimes leads to poor margins.In this paper,a novel Siamese network is proposed and applied to few/zero-shot Handwritten Character Recognition(HCR)tasks.The novelties of the proposed network are in.1)Utilizing transfer learning and using the pre-trained AlexNet as a feature extractor in the Siamese architecture.Fine-tuning a pre-trained network is typically faster and easier than building from scratch.2)Training the Siamese architecture with contrastive loss instead of the binary cross-entropy.Contrastive loss helps the network to learn a nonlinear mapping function that enables it to map the extracted features in the vector space with an optimal way.The proposed network is evaluated on the challenging Chars74K datasets by conducting two experiments.One is for testing the proposed network in few-shot learning while the other is for testing it in zero-shot learning.The recognition accuracy of the proposed network reaches to 85.6%and 82%in few-and zero-shot learning respectively.In addition,a comparison between the performance of the proposed Siamese network and the traditional Siamese CNNs is conducted.The comparison results show that the proposed network achieves higher recognition results in less time.The proposed network reduces the training time from days to hours in both experiments.

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.

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.

A Comparative Analysis of the Origin and Formation Between Chinese Characters and English Alphabets

This research is based on the framework of social constructivism,utilizing the principle of Human Universals as a methodology to compare the similarities and differences between the ideation and formation methods of Chinese characters and English alphabets.Through comparative analysis of the ideation of English letters(pictogramme)and the origin of Chinese characters,known as the"Six Categories Theory,"we discover their alignment in terms of social,traditional,and cultural aspects.This suggests that different ethnic groups share common features in terms of life experience,learning cognitive development,and thinking habits.This study also finds that the origins of English letters and Chinese characters share similar linguistic features in their methods of constructing letters/characters,such as pictographic,ideographic,and semantic characteristics.Exploring these commonalities contributes to promoting learning and communication between Chinese and English characters.Additionally,by focusing on socio-cultural aspects,traditional customs,and cognitive learning,this study aims to break away from the traditional linguistic research approach that solely focuses on language differences.This provides a broader perspective and richer dimensions for Chinese and English language learning,facilitating the development of cross-linguistic and cross-cultural communication.

Characteristics and C-E Translation Methods of the Four-Character Frame in the Subtitles of the Documentary Daming Palace

This paper studies the four-character frame in the subtitle of the documentary Daming Palace, aiming to provide a reference for the translation of the documentary four-character case as well as better spread Chinese culture. By analyzing, researching and summarizing the subtitle of Daming Palace and reading a lot of literature, the author has found that in Daming Palace the four-character frame is characterized by the use of the absolute four-character frames and the recurrence of some four-character frames, and that C-E translation methods of the four-character frame are mainly literal translation, free translation, provincial translation and concise translation.