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.

Instance Segmentation of Characters Recognized in Palmyrene Aramaic Inscriptions

This study presents a single-class and multi-class instance segmentation approach applied to ancient Palmyrene inscriptions,employing two state-of-the-art deep learning algorithms,namely YOLOv8 and Roboflow 3.0.The goal is to contribute to the preservation and understanding of historical texts,showcasing the potential of modern deep learning methods in archaeological research.Our research culminates in several key findings and scientific contributions.We comprehensively compare the performance of YOLOv8 and Roboflow 3.0 in the context of Palmyrene character segmentation—this comparative analysis mainly focuses on the strengths and weaknesses of each algorithm in this context.We also created and annotated an extensive dataset of Palmyrene inscriptions,a crucial resource for further research in the field.The dataset serves for training and evaluating the segmentation models.We employ comparative evaluation metrics to quantitatively assess the segmentation results,ensuring the reliability and reproducibility of our findings and we present custom visualization tools for predicted segmentation masks.Our study advances the state of the art in semi-automatic reading of Palmyrene inscriptions and establishes a benchmark for future research.The availability of the Palmyrene dataset and the insights into algorithm performance contribute to the broader understanding of historical text analysis.

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.

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.

Progress in the evaluation tool of Character Strengths and its application in nursing staff

Character Strengths is a group of positive personality traits reflected through cognition,behavior,and emotion,which play a positive role in improving happiness,alleviating negative emotions,and maintaining physical and mental health.This article reviews the concept,content,methods,evaluation tools,and application progress of Character Strengths in nurses,so as to provide a reference for clinical managers and improve the quality of life,mental health,and professional satisfaction of n urses.

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.

A Review of Research on Handwritten Chinese Character Recognition with Multi-Feature Fusion

This paper analyzes the progress of handwritten Chinese character recognition technology,from two perspectives:traditional recognition methods and deep learning-based recognition methods.Firstly,the complexity of Chinese character recognition is pointed out,including its numerous categories,complex structure,and the problem of similar characters,especially the variability of handwritten Chinese characters.Subsequently,recognition methods based on feature optimization,model optimization,and fusion techniques are highlighted.The fusion studies between feature optimization and model improvement are further explored,and these studies further enhance the recognition effect through complementary advantages.Finally,the article summarizes the current challenges of Chinese character recognition technology,including accuracy improvement,model complexity,and real-time problems,and looks forward to future research directions.

Genetic and Correlation Analysis of Grain Characters in Three-line Hybrid Rice

Abst[Objective] This study was to understand the genetic dynamics of three-line hybrid rice, and explore the respective effect of sterile line and restoring line on grain characters of hybrid rica. [Method] Four three-line stedle lines and 27 restoring lines（cultivars） commonly culti- vated in Central China region were regarded as expadmental materials to conduct 4 x27NCII cross design, and the grain characters of three-line hybrid rico were analyzed at genetic and correlation levels. [ Result] Four characters of grain length, grain width, 1 000-grain weight and length- width ratio play the leading role in additive gene effect; these four characters were simultaneously influenced by male parent and female parent, but the effect from male parent was relatively larger. The grain length, grain width, 1 000-grain weight and length-width ratio all have high brood hedtabUities（ respectively 99.65%, 98.31%, 95.27% and 98.81% ）. Correlation analysis showed that grain length was positively correlated with 1 000-grain weight and length-width ratio at extremely significant level; 1 000-grain weight was positively correlated with grain length and length- width ratio at extremely significant level, and was insignificantly correlated with grain width; grain width was negatively correlated with grain length and length-width ratio at extremely significant level. Path analysis showed that the direct path coefficients of grain length, grain width and 1 0（30- grain weight to length-width ratio were 0.624 6, -0.555 9 and -0.015 8, respectively. [ Conclusion] This study systematically analyzed the effects of stedle line and restoring line on grain characters of hybrid rice, which provided theoretical basis for breeding high quality and yield hy- brid dce.

Study on the Change Character of Double Rice Cold Damage in Hunan and Hubei Province during the Past 50 Years

Based on the meteorological data of representative meteorological stations in Hunan and Hubei from 1961 to 2008 years,the change character of double rice cold damage under the background of climate change were analyzed adopting 30 years glide accumulation method.The analysis showed that the 30 years sliding cumulative days of mild low-temperature during spring sowing in Hunan and Hubei were decreased in the recent 50 years,as well as the 30 years sliding cumulative days of moderate low-temperature in central south Hubei,northern and western Hunan.However,there was an increase in southern Hunan,so was the 30 years sliding cumulative days of severe low-temperature.The 30 years sliding cumulative days of mild low-temperature in May reduced in Hunan and Hubei.Instead,that of moderate low-temperature in May in central south Hubei was on the rise,and it was opposite in northern and southern Hunan,but there was no obvious change in western Hunan.The 30 years sliding cumulative days of severe low-temperature showed a decreasing tendency in May in central south Hubei,northern and western Hunan,and southern Hunan showed a contrary tendency.The 30 years sliding cumulative days of mild cold dew wind in Hunan and Hubei were decreased,that of moderate cold dew wind in central south Hubei,northern and western Hunan had the same tendency,but there was a contrary tendency in southern Hunan.The 30 years sliding cumulative days of severe cold dew wind was decreased in central south Hubei and increased in western Hunan,without cold dew wind in northern and southern Hunan.

Main Agronomic Characters and Grain Quality of Rice Blast Resistance Gene Pi-d2 Transgenic Rice

[Objective] The aim of this study was to provide metabolic evidence for the analysis of the ecological and safety assessment of Pi-d2-transgenic rice.[Method] The main agronomic characters of Pi-d2-transgenic rice were observed in field experiment and the grain chemical characters and amino acid content were measured.[Results] Introduction of foreign gene Pi-d2 resulted in stably hereditable variation in agronomic characteristics in the descents.Most of the transgenic lines grew normally and orderly.Compared with the control（wild type plants）,about half of transgenic plants showed an increased or reduced plant height.There was no observable difference between transgenic plants and controls in tiller number,length of panicle,panicles per plant,seed-setting rate and 1 000-grain weight.Total amino acid content in transgenic rice was reduced,while the starch content,GC and GT were not altered in comparison with the control.[Conclusion] Introduction of foreign gene Pi-d2 has remarkable influence on plant height,while little on grain chemical characters.

Correlation Analysis of Characters of Indica Hybrid Rice with High Content of Amylose

[Objective] The aim was to research and analyze characters and related correlation of indica hybrid rice containing high amylose. [Method] In the research, major characters of 16 species of groups of {ndica hybrid rice and the correlation were explored in rice belts in Sichuan in 2011. [Result] The variation of chalkiness degree was the highest at 26.8%, followed by rate of head rice at 22.89%; varia- tions of head rice rate and chalkiness degree were lower at 0.72% and 2.61%. In addition, rate of unpolished rice was of significantly negative correlation with chalki- ness degree; rate of chalky rice was of extremely positive correlation with chalkiness degree and gel consistency; chalkiness degree was of significantly positive correla- tion with gel consistency; gel consistency was of significantly negative correlation with protein content; amylose content was of insignificant correlation with gel consis- tency （r=0.166 9） of the 16 hybrid groups. These indicated that gel consistency would be still high as the content of amylose grows （AC≥25%）. For example, when the content of anylose in Chuanxiang 29A/Luhui 37, Kangfeng AJ6684, and Lefeng A/SR536 exceeded 27%, the gel consistency was over 80 mm in the research. [Conclusion] The research provides references for improvement of amylose content in breeding hybrid rice.

Effects of Plastic Film Mulching on Physical Characters of Soil and Yield and Yield Components of Sweet Potato

Field experiments were carried out to study the effects of plastic film mulching on soil physical characters, including soil temperature, soil moisture content and soil bulk density, and yield and yield components of sweet potato. The results showed that plastic filming mulching increased soil temperature. Considering the soil temperature-increasing effect, the treatments ranked as black plastic film treatment 〉 white plastic film treatment 〉 control. However, with the deepening of soil layer, the warming effect of plastic film mulching was weakened. Black or white plastic film mulching was conducive to low T/R value, especially in the early growth stage of sweet potato. Plastic film mulching significantly improved the storage root yield of sweet potato. In terms of yield-improving effect, the treatments ranked as black plastic film treatment 〉 white plastic film treatment 〉 control. The storage root num- ber per plant showed a downward trend, but the weight of single storage root was increased.

Variation and Cluster Analysis on Leaf Characters from Different Provenance Sources of Polygonum multiflorum Thunb

[Objective] The aim was to study the variation of leaf characters from different provenance sources of Polygonum multiflorum Thunb,as well as to carry out cluster analysis on P.multiflorum from different provenance sources to provide basis for the classification,identification,breeding and improved variety selection of P.multiflorum.[Method] Leaf shape characters of 31 copies of germplasm resources in the major distribution region of the whole country were determined,and the genetic variation of P.multiflorum leaves from different producing areas was analyzed.[Result] The leaf characters of single plant of the same experimental provenance source of P.multiflorum were relatively stable,the variation was mainly found on the single leaf area,1/2 leaf width,leaf width and other indicators;the variation of each leaf character among different provenance sources was obvious,and the variation was mainly found on the single leaf weight,leaf area,1/2 leaf width,leaf length and other indicators.The correlation analysis of each leaf character in P.multiflorum suggested that the single leaf area and single leaf weight showed extremely significant positive correlation with leaf length,1/2 leaf width,leaf width,leaf thickness and leaf stem length,while the single leaf area and single leaf weight showed significant negative correlation with WWR（leaf width/1/2 leaf width）and LWR（leaf length/1/2 leaf length）,in addition,several macroscopic leaf characters such as leaf length,1/2 leaf width,leaf width,leaf stem length showed extremely positive correlation.The main component analysis result suggested that the contribution rate of accumulation variance of the front three main components was up to 97.4%,which could better reflect the comprehensive performance of leaf characters of different provenance sources of P.multiflorum.The cluster analysis showed that the experimental 31 copies of P.multiflorum provenance sources should be divided into three classes,the first class was distributed in the Middle,Western of Guizhou,northwestern of Guangxi and western areas with higher altitude;the second class was distributed in Hunan,Hubei,Sichuan,Guangdong and the most area of Guangxi;the third class was distributed in Anhui,Jiangsu and Henan and Shandong.[Conclusion] Cluster analysis of leaf characters indicated that the kinds of provenance sources which the geographical position was closer could be got together.The study had provided a certain basis for the classification of P.multiflorum.

Physicochemical Characters of rPoIFN-α and Its Antiviral Activity in vitro

[Objective]The research aimed to test and identify the physicochemical characters and antiviral activity in vitro of semi-finished product of the recombinant porcine rPoIFN-α. [Method]HEp-2/VSV system was used to test the antiviral activity of three batches of rPoIFN-α. Using recombinant human IFN-α as reference,the titer of interferon was measured. The semi-finished product of rPoIFN-α with the known titer were treated with 0.25% trypsin,HCl and mouse anti-porcine IFN-α monoclonal antibody. And the anti-viral activity of each batch of rPoIFN-α was detected. The physicochemical characters of rPoIFN-α were evaluated. The inhibition of induced cytopathic effect of rPoIFN-α on PPV （Porcine parvovirus） and PRV （Porcine pseudorabies） on swine kidney cell （PK-15） was determined. And the antiviral activity of rPoIFN-α in vitro was observed. [Result]The titers of semi-finished products of rPoIFN-α titrated by HEp-2/VSV system could reach 1.5×105 IU/ml,with the specific activity of 1.1×106 IU/mg. The residual rate of the tier of rPoIFN-α treated by 0.25% trypsin at 37 ℃ for 1 h was less than 1%. And that treated with HCl （pH of 2.0） for 72 h was up to 95%. And that treated at 56 ℃ for 30 min and that treated by mouse anti-porcine IFN-α monoclonal antibody at 37 ℃ for 1 h were higher than 47% and about 1% respectively. The antiviral test in vitro showed that 50 and 500 IU/ml rPoIFN-α could inhibit the induced cytopathic effect of PRV and PPV on PK-15 cell lines. [Conclusion]rPoIFN-α had the basic physicochemical characters of IFN-α. And it could inhibit the induced cytopathic effect of PRV and PPV on PK-15 cell lines,but there was dosage difference.

Vertical root distribution characters of Robinia pseudoacacia on the Loess Plateau in China

On the Loess Plateau, water is the main limiting factors for vegetation growth. Root distribution characters have special ecological meaning as it reflected the utilizations of trees to the environments. Even-aged stands ofRobinia pseudoacacia on slope lands facing south and north were selected as sampling plots for root distribution investigation. Investigatiing results showed that indicated that on all sites, root biomass decreased with depth, and the distribution depth of fine root was deeper than that of coarser root. The results of variance analysis indicated that there were great differences in root biomass among different diameter classes, and coarser root was the main sources of variance, and the root biomass, especially fine root (?<3mm) biomass on northern exposition sites was bigger than that on southern exposition sites. Analysis of the vertical root distribution parameters, root extinction coefficient, β indicated that the value of β on northern exposition was more than 0.982, while the value of β on southern exposition was less than 0.982, which indicated that the vertical root distribution depth ofRobinia pseudoacacia on southern exposition was deeper than that on southern exposition. And the distribution depth of fine roots (Φ<1mm) was deeper than that of thicker roots(Φ<3mm), which was in favor of the uptake of water and nutrients from deeper layers, helped the trees to adapt the arid environment, and promoted the growth of the upper parts of the tree. Keywords Root diameter classes - Variance analysis - Root extinction coefficient - Vertical distribution characters - Site conditions - Loess Plateau CLC number S792.27.01 Document code A Foundation Item: This research was supported by National Natural Science Foundation of China (30371150 and 40371075).Biography: LI Peng (1974-) male, post: Ph. D. in Northwest Scientific & Technological University of Agriculture and Forestry, Yangling 712100, Shaanxi Province, P. R. China. Tel: 029-82312651.Responsible editor: Chai Ruihal

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.