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.

Sedimentary Facies Characteristics of Chang 6 and Chang 7 Members of Yanchang Formation in Heshui Area, China

This paper takes Chang 6 and Chang 7 of Yanchang Formation in Heshui area of China as the research object. This study first divides the strata of Chang 6 and Chang 7. According to the review data, significant geological activities have caused a large settlement of the strata in this area. During the Chang 6 period, a lacustrine basin sedimentary system developed, reaching its peak in the Chang 7 period. The Chang 6 and Chang 7 members primarily feature deep-water gravity flow sedimentary systems, which can be categorized into three subfacies: outer fan, middle fan, and inner fan. These systems also exhibit turbidite fan sedimentary patterns, ranging from deep lake to semi-deep lake facies. By examining these sedimentary models, we can identify different types of turbidite deposits. Understanding the process of gravity flow deposition and the evolution of ancient lakes is crucial for guiding oil and gas exploration and conducting paleogeographic research.

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.

Sedimentary Processes and Depositional Characteristics of Coarse-grained Subaqueous Fans along Steep Slopes in a Lacustrine Rift Basin:A Case Study from the Dongying Depression,Bohai Bay Basin,China

Coarse-grained subaqueous fans are vital oil and gas exploration targets in the Bohai Bay basin,China.The insufficient understanding of their sedimentary processes,depositional patterns,and controlling factors restricts efficient exploration and development.Coarse-grained subaqueous fans in the Yong′an area,Dongying Depression,are investigated in this study.These fans include nearshore subaqueous fans,and sublacustrine fans,and their sedimentary processes,depositional patterns and distribution characteristics are mainly controlled by tectonic activity and paleogeomorphology.Nearshore subaqueous fans developed near the boundary fault during the early–middle deposition stage due to strong tectonic activity and large topographic subsidence.Early sublacustrine fans developed at the front of the nearshore subaqueous fans in the area where the topography changed from gentle to steep along the source direction.While the topography was gentle,sublacustrine fans did not develop.During the late weak tectonic activity stage,late sublacustrine fans developed with multiple stages superimposed.Frequent fault activity and related earthquakes steepened the basin margin,and the boundary fault slopes were 25.9°–34°.During the early–middle deposition stage,hyperpycnal flows triggered by outburst floods developed.During the late deposition stage,with weak tectonic activity,seasonal floods triggered hyperpycnal flows,and hybrid event beds developed distally.

CHARACTERISTICS OF FAN STALLING BASED ON CORRELATED DIMENSIONS

Different from the previous qualitative analysis of linear systems in time and frequency domains, the method for describing nonlinear systems quantitatively is proposed based on correlated dimensions. Nonlinear dynamics theory is used to analyze the pressure data of a contrarotating axial flow fan. The delay time is 18 and the embedded dimension varies from 1 to 25 through phase-space reconstruction. In addition, the correlated dimensions are calculated before and after stalling. The results show that the correlated dimensions drop from 1. 428 before stalling to 1. 198 after stalling, so they are sensitive to the stalling signal of the fan and can be used as a characteristic quantity for the judging of the fan stalling.

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.

Lithofacies Characters and Significance of the Submarine Fan of the Liufengguan Group in Qinling

Field investigation and laboratory research on flysch of the Liufengguan Group in Qinling indicate the following： （1） Sandstone of the Liufengguan Group is categorized as feldspathic lithic graywacke with a minor amount of lithic graywacke in the QFR triangular diagram. Grain size〈0.3 mm. Bedding plane structures such as groove casts and suspected flute casts can be found at the bottom of the sandstone. It is inferred that currents may have come from the southeast during deposition. Bedding structures such as ripple marks, graded bedding, parallel bedding, small-scale cross bedding, climbing bedding, suspected convolute bedding, microlamination and sliding structures have also been observed, which are of indicative significance. It is thought that the Liufengguan Group has the sedimentary characteristics of bedding, bedding plane structures and lithologicai assemblages of deep-sea low-density turbidity current deposits. The vertical succession of the Bouma sequence in the inner fan subfacies zone is generally incomplete： the assemblage of Ta and Tabc is commonly seen; the succession of the middle fan subfacies zone is relatively complete; and divisions Te and Tb are common in the outer fan subfacies zone. （2） The flysh of the Liufengguan Group is a sequence of deep-sea argillaceous-arenaceous submarine fan deposits, in which the authors recognize the inner, middle and outer fan subfacies and also nine types of lithofacies： normal graded sandstone （A1）, medium- to thick-bedded, fine-grained sandstone （A2）, medium- to thick-bedded and massive siltstone （A3）, thin-bedded, fine-grained sandstone and mudstone （B1）, irregular interbeds of thinbedded, fine-grained sandstone and siltstone （B2）, thin-bedded, fine-grained sandstone （C1）, very thin-bedded, fine-grained sandstone （D1）, olistostromes （El） anddeep-sea mudstone （F）. The inner fan consists of four microfacies： natural levee （A1）, water channel （A2, A3） and olistostrome （El）; in the middle fan there also occur four microfacies, i.e., branch channel （B1）, branch channel （B2）, interdistributary bay （D1） and olistostrome. The outer fan is made up of the branch channel （C1） and sheet sand （D1） microfacies, which alternate vertically with sediments of deep-sea plain subfacies （F）. There occur fining- and thinning-upward channel deposits in the outer-fan subfacies zone of the submarine fan of the Liufengguan Group observed in this study. The quartz content of the graywacke of the deposits is all higher than 40% and may reach as high as 60%. Therefore, on the basis of the aforementioned features, this flysh should be formed in a passive continental-margin tectonic environment.

Numerical Study on Aerodynamic Characteristics of Ducted Fan Aircraft

Based on investigations into the flow field of ducted fan aircrafts,structural parameters of duct are quantified.A three-dimensional model is established for numerical simulation,and adaptive Cartesian grid is used to mesh the model in order to improve calculation speed and solution accuracy.Three-dimensional Navier-Stokes equations are brought in to analyze different duct styles.Generalization of simulation results leads to several conclusions in duct aerodynamics to help design ducted fan aircrafts.

Characteristics of the turbidite fan in the Wenchang Formation of the Enping Sag, Pearl River Mouth Basin, China and its hydrocarbon significance

A turbidite fan in the Eocene upper Wenchang Formation in the Enping Sag, Pearl River Mouth Basin （PRMB） has been studied using seismic, logging and borehole data. The fan is characterized by parallel progradation on the dip seismic profile and is mound-shaped or lenticular-shaped on the strike seismic profile. The study of the core and logging data from well EP17-3-1, which is located in the front side of the turbidite fan, shows that this fan is a set of normal grading sand beds, interbedded within thick dark grey mudstones of semi-deep to deep lake deposits in the Wenchang Formation. The fan is interpreted as a sand/mud-rich turbidite fan that has an area of over 140 km2 and a maximum thickness of over 340 m. Combined with a study of the regional geological background and previous provenance analysis of the Eocene Wenchang Formation, the main potential provenances for the turbidite fan are considered to be the Panyu low-uplift and northern fault terrace zone. The Enping Sag is considered to be a half graben-like basin whose north side is faulted and whose south side is overlapped. Basement subsidence in the Eocene was mainly controlled by boundary faults which dip relatively steeply on the north side, causing the subsidence center of the Enping Sag in this stage to be close to the north boundary faults. Sustained faults developed in the Enping Sag during the Eocene caused an increase of the relative height difference between the north and the south uplift zone in the Enping Sag. Affected by the second episode of the Zhuqiong movement （39-36 Ma） in late Eocene, sediments which had accumulated on the Panyu low-uplift zone were triggered and moved toward the subsidence center of the Enping Sag and formed the turbidite fan. The second episode of the Zhuqiong movement is the most important triggering factor for the formation of the turbidite fan in the Wenchang Formation. Seismic attribute characterization shows that the low frequency energy is enhanced and high frequency energy is weakened when seismic waves propagate through the oil-bearing zone in this fan. Amplitude versus offset （AVO） anomalies are observed in the seismic data and abnormally high pressure is encountered. The turbidite fan in the Wenchang Formation has provided important information for sedimentary evolution in deep layers of the Enping Sag and pointed to a new direction for the hydrocarbon exploration in the study area.

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.