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.

Fireworks Optimization with Deep Learning-Based Arabic Handwritten Characters RecognitionModel

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.

Grain-size characteristics of linear dunes on the northern margin of Qarhan Salt Lake, northwestern China

In order to clarify the formation mechanism of linear dunes on the northern margin of Qarhan Salt Lake, northwestern China, we analyzed the grain-size and sorting parameters of the dune and interdune sands. The surface sands （0-30 ram） from the dune base to the crest of both flanks and interdune corridors were sampled along transects from upwind to downwind through the dune field. The results indicated that the grain-size distribution differed at different positions between and within the dunes. The frequency curve for dune sands mainly showed a bimodal distribution, while the interdune sediments showed a trimodal distribution. The grain size distribution of the linear dunes showed a finer crest pattern, i.e. the crests were composed of sands that were generally finer, better sorted than those of base sands. In addition, at the dune field scale, the dune crest sands were tending to become much finer but sorting became worse along the downwind transects. However, the grain-size parameters of sediments in the interdune corridors showed no clear pattern. The results demonstrated that the grain size and sorting parameters exhibited a systematic change not only at the individual scale but also at the dune field scale. Our results quantitatively estimate the limited role of cohesive sediments on the formation of linear dune under unidirectional wind regime. More attention should be paid to a long-term wind regime observation, internal sedimentary structures and their formation ages.

Grain-size Characteristics of Sediment in Daniugou Peatland in Changbai Mountains,Northeast China:Implications for Atmospheric Dust Deposition

The grain-size distribution characteristics and grain-size parameters of sediment in two vertical sections of Daniugou peatland in the Changbai Mountains were systematically investigated.A comparative analysis of the sediment granularity using a discriminative function with Hongyuan peat,red clay,loess-paleosol,fluvial deposit as well as lacustrine deposit was also conducted.It turns out that the vertical section of Daniugou peat ash is primarily constituted by clay and silt particles,and the content of sand is relatively small.Grain-size frequency curves generally show a single-peak modality while a bimodal pattern is detected in the upper layer.The grain-size component and peak pattern of grain-size frequency curves also illustrate that peat ash materials were transported to the peatland by long-range aeolian dust during the deposition process,while there existed short-distance dust influence in peat deposition of the upper layer.Comparisons of grain-size parameters and the discriminative Y-value of Daniugou peat ash with those of typical aeolian sediments show close similarities,suggesting the possibility that atmospheric dust transport processes were involved in the accumulation of peat again.Moreover,the variations of grain-size distribution suggest the local environmental deterioration which is just the driving force of local dust elevation.Grain-size analysis of peatland sediment is demonstrated to be one effective method to extract information about regional and global environmental evolution,and more attention should be paid to current local ecological environment and to seeking a balance between economic development and environmental protection in Northeast China.

Multiple grain-size fraction analysis of heavy minerals and the provenance identification of sediments from the abandoned Huanghe River,eastern China

The quantitative analysis of sediment sources in a sink is an important scientific topic and challenge in provenance research.The characteristics of heavy minerals,combined with the geochemical constituents of detrital grains,provide a reliable provenance-tracing approach.We developed a mineral identification method to analyze the multiple grain-size fraction of sediments,from which the elemental geochemistry of hornblende was used to compare the characteristics of sediments from the Huaihe River and Huanghe(Yellow)River in eastern China.Elements that were statistically identified as being able to discriminate sediment provenance were employed to perform a quantitative analysis of the sources of sediments of the abandoned Huanghe River.Results reveal that the Huaihe River is characterized by a high amphibole content of>60%and that the Huanghe and abandoned Huanghe rivers have greater abundances of limonite and carbonate minerals compared with those of the Huaihe River.The contents of trace elements and rare earth elements in hornblende show that the sediments of the abandoned Huanghe River are similar to those of the Huanghe River but different from those of the Huaihe River.Furthermore,chemical mass balance was used to calculate the relative contributions of different provenances of sediment from the abandoned Huanghe River,and nine trace elements of hornblende were identified as discriminators of provenance.Approximately 2%of the hornblende in the abandoned Huanghe River is derived from the Huaihe River and 98%from the Huanghe River.Considering the proportion of hornblende in the total sediment,it is inferred that the contribution of Huaihe River sediment to the abandoned Huanghe River is approximately 0.5%.This study shows that mineral analysis using multiple grain-size fractions(within the wide range of 1Φto 6Φ)with assessment in elemental geochemistry of hornblende can characterize the provenance of fluvial material in coastal zones.

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.

“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.

Grain-size Characteristics and Climate Variability in TMS5e Sequence of Tumen Section in Southern Tengger Desert,Northwestern China

The TMS5e sequence from the Tumen section, at the southern edge of Tengger Desert in the northwestern China, is synchronous with Marine Isotope Stage 5e （MIS5e）. It consists of 16 layers of aeolian dune sands, 11 layers of lacustrine loess-like facies, and 5 layers of lacustrine facies. The results of grain-size analysis shows that the pa- laeo-mobile dune sands, palaeo-fixed to semi-fixed dune sands and loess-like sandy loams are mainly composed of sands, ranging from 70% to 96%; their silt contents ranged from 4% to 20%, and their clay contents ranged from 1% to 5%; the climate under which the aeolian dune sands were deposited is similar to that under which modern mobile dune sands form, which is caused by the dominance of the cold, dry East Asian winter monsoon. In contrast, the lacustrine loess-like facies and lacustrine facies had a lower sand contents than those of the three aeolian dune sands, but have higher silt and clay contents, most of their sand content ranged from 30% to 60%, their silt contents ranged from 35% to 55%, and their clay contents ranged from 6% to 20%. The lacustrine loess-like facies and lacustrine facies formed under the influence of the warm, humid East Asian summer monsoon based on their similarity with modern sediments. The grain-size indicator Mz （mean grain diameter） and the SC/D value in the TMS5e sequence indicate climatic insta- bility at the southern edge of the Tengger Desert during MIS5e, with at least 14 fluctuations between a warm, humid climate and a cold, dry climate, divided into five stages： TMS5e5 （139 kyr to 129.3 kyr B.P.）, TMS5e4 （129.3 kyr to 124 kyr B.P.）, TMS5e3 （124 kyr to 119.5 kyr B.P.）, TMS5e2 （119.5 kyr to 116.5 kyr B.P.）, and TMS5el （116.5 kyr to 113.7 kyr B.P.）. These correspond roughly to MIS5e5, MIS5e4, MIS5e3, MIS5e2, and MIS5el, respectively, in the GRIP ice core data.

Grain-size distribution characteristics of red sandy sediments in Dongjiang River valley,southern Nanling Mountains,during the MIS2 stage

Layer LJ3 of Linjiang stratigraphic section in Dongjiang River valley in the south of the Nanling Mountains is a set of red sandy sediments.Measured by thermoluminescence(TL) dating,it was found to be formed in MIS2-9,500 ± 800 yr to 19,600 ± 1,800 yr B.P.After analy-sis of the grain sizes of the 16 samples(LJ3-100 to LJ3-85) in this layer,it was discovered that(1) The contents of each grain group in dif-ferent samples are similar.(2) The values of Md,Mz,,Sk,and Kg vary from LJ3-100 to LJ3-85 in a narrow range.(3) The segments of each sample in the accumulative curves extend parallel with similar slopes.All the three aspects reveal the Aeolian characteristics of Layer LJ3.Therefore,it is thought that Layer LJ3 consists of red sandy sediments formed in MIS2 in the south of Nanling Mountain,which reflects the arid climate at that time.

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.

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.

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.

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.

The grain-size characteristics of Quaternary deposits at Xingshan near Siping in Jilin province, China

This research paper analyses the grain-size characteristics of the Quaternary deposits at Xingshan near Siping, Jilin province in China by employing graphic measures to study the grain size distribution and its mode of transport and deposition. The Quaternary deposits at Xingshan lie unconformable on Cretaceous rocks made of siltstone, mudstone and sandstone. The average grain size is between 8.06 to 8.55Φ (0.002 6 ～0.003 7 mm). The Quaternary deposits at Xingshan mainly compose of very fine silt to clay. The compositions of the grade are clay 63% and silt 37%. The clay size components are weathered debris transported and deposited by flowing water from the SE highlands or hills to the low lying NW Xingshan plains whereas the silty components accumulated by aoelian process. The Quaternary deposits at Xingshan accumulated in the middle and late Pleistocene interglacial periods from (459.12～39.03) ka to (88.92～7.56) ka. The standard deviation ranged from 0.96 to 1.36Φ, indicating that the sediments are moderately to poorly sorted, Coefficient of skewness ranged from 0.16～0.31 with an average skewness of 0.218, (Positively skewed towards fine). Kurtosis values (0.84～1.05) from the grain size distribution and visual inspection of the frequency curves indicate platykurtic to mesokurtic curves and unimodal to bimodal grain-size distribution. The type of deposit formation is sand dune and the source is at a distal from its provenance.

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.