Urdu,a prominent subcontinental language,serves as a versatile means of communication.However,its handwritten expressions present challenges for optical character recognition(OCR).While various OCR techniques have bee...Urdu,a prominent subcontinental language,serves as a versatile means of communication.However,its handwritten expressions present challenges for optical character recognition(OCR).While various OCR techniques have been proposed,most of them focus on recognizing printed Urdu characters and digits.To the best of our knowledge,very little research has focused solely on Urdu pure handwriting recognition,and the results of such proposed methods are often inadequate.In this study,we introduce a novel approach to recognizing Urdu pure handwritten digits and characters using Convolutional Neural Networks(CNN).Our proposed method utilizes convolutional layers to extract important features from input images and classifies them using fully connected layers,enabling efficient and accurate detection of Urdu handwritten digits and characters.We implemented the proposed technique on a large publicly available dataset of Urdu handwritten digits and characters.The findings demonstrate that the CNN model achieves an accuracy of 98.30%and an F1 score of 88.6%,indicating its effectiveness in detecting and classifyingUrdu handwritten digits and characters.These results have far-reaching implications for various applications,including document analysis,text recognition,and language understanding,which have previously been unexplored in the context of Urdu handwriting data.This work lays a solid foundation for future research and development in Urdu language detection and processing,opening up new opportunities for advancement in this field.展开更多
The character of Lensky in Eugene Onegin is one of the most discussed figures in the novel.He is the friend of Eugene Onegin and represents a contradictory personality.In the novel,Lensky displays a complex set of cha...The character of Lensky in Eugene Onegin is one of the most discussed figures in the novel.He is the friend of Eugene Onegin and represents a contradictory personality.In the novel,Lensky displays a complex set of characteristics,appearing both elegant and noble on the outside,while concealing a deep inner loneliness and conflict.His attitude toward love and his dissatisfaction with society make him a dramatic and profound character in the story.By analyzing the character of Lensky,we can explore his role in the novel and his relationships with other characters.Lensky’s presence not only enriches the plot but also presents a figure filled with inner contradictions and emotional struggles.His friendship and rivalry with Eugene Onegin,as well as his admiration and helplessness in regard to Olga,showcase his complex inner world and reflections on life.Furthermore,the character of Lensky carries a certain symbolic significance.He can be seen as a metaphor for Russian society and culture at the time.His loneliness and inner conflict symbolize the limitations of Russian society and culture,while also reflecting Pushkin’s idealized pursuit of love and friendship,as well as his critical view of reality.In conclusion,through a deep analysis of Lensky’s character,we can better understand the portrayal of characters and the development of the plot in Eugene Onegin.It also provides readers with a perspective on Pushkin’s thoughts and observations on human nature,society,and culture.展开更多
The Tien's Mountain Stream Snake,Opisthotropis daovantieni Orlov, Darevsky, and Murphy, 1998, has been represented solely by its type series, with no additional specimens reported in the past two decades. As a res...The Tien's Mountain Stream Snake,Opisthotropis daovantieni Orlov, Darevsky, and Murphy, 1998, has been represented solely by its type series, with no additional specimens reported in the past two decades. As a result, limited data exist and O. daovantieni remains one of the least studied members of its genus. Based on a re-examination of the type series, analysis of newly collected topotypic specimens, and a review of museum collections, this study provides an updated and comprehensive morphological characterization of O. daovantieni including detailed descriptions of hemipenial morphology, revised diagnostic characters,phylogenetic positioning, and ecological insights.Based on morphological comparisons with congeners, we also define the informal Opisthotropis spenceri group to facilitate future taxonomic work. In addition, this study documents a previously unreported defensive behavior involving tail-poking,observed in the field and thus far unique within the genus Opisthotropis.展开更多
The English“T” is widely held as a well-behaved Kaplanian indexical that has a directly-referential content and a character which imples immunity to self misidentification.In this paper I present uses of“T”outside...The English“T” is widely held as a well-behaved Kaplanian indexical that has a directly-referential content and a character which imples immunity to self misidentification.In this paper I present uses of“T”outside attitudal contexts that are not directly referential yet exhibit immunity to self misidentification.They include uses of“I”for simulation and for counterfactual self portrait.I argue that they(i)challenge the non-shiftability and the rigidity arguments for the direct reference view,and(1)require a revision of the character of“T”to reflect the sensitivity of its content to the perspective from which the speaker identifies herself.展开更多
The increased accessibility of social networking services(SNSs)has facilitated communication and information sharing among users.However,it has also heightened concerns about digital safety,particularly for children a...The increased accessibility of social networking services(SNSs)has facilitated communication and information sharing among users.However,it has also heightened concerns about digital safety,particularly for children and adolescents who are increasingly exposed to online grooming crimes.Early and accurate identification of grooming conversations is crucial in preventing long-term harm to victims.However,research on grooming detection in South Korea remains limited,as existing models trained primarily on English text and fail to reflect the unique linguistic features of SNS conversations,leading to inaccurate classifications.To address these issues,this study proposes a novel framework that integrates optical character recognition(OCR)technology with KcELECTRA,a deep learning-based natural language processing(NLP)model that shows excellent performance in processing the colloquial Korean language.In the proposed framework,the KcELECTRA model is fine-tuned by an extensive dataset,including Korean social media conversations,Korean ethical verification data from AI-Hub,and Korean hate speech data from Hug-gingFace,to enable more accurate classification of text extracted from social media conversation images.Experimental results show that the proposed framework achieves an accuracy of 0.953,outperforming existing transformer-based models.Furthermore,OCR technology shows high accuracy in extracting text from images,demonstrating that the proposed framework is effective for online grooming detection.The proposed framework is expected to contribute to the more accurate detection of grooming text and the prevention of grooming-related crimes.展开更多
We construct the quantum fields presentation of the generalized universal character and the generalized B-type universal character,and by acting the quantum fields presentations to the constant 1,the generating functi...We construct the quantum fields presentation of the generalized universal character and the generalized B-type universal character,and by acting the quantum fields presentations to the constant 1,the generating functions are derived.Furthermore,we introduce two integrable systems known as the generalized UC(GUC)hierarchy and the generalized Btype UC(GBUC)hierarchy satisfied by the generalized universal character and the generalized B-type universal character,respectively.Based on infinite sequences of complex numbers,we further establish the multiparameter generalized universal character and the multiparameter generalized B-type universal character,which have been proved to be solutions of the GUC hierarchy and the GBUC hierarchy,respectively.展开更多
Against the backdrop of the deep integration of the global film and television industry,character design has long transcended the mere pursuit of aesthetics and has become a key symbolic system that carries cultural i...Against the backdrop of the deep integration of the global film and television industry,character design has long transcended the mere pursuit of aesthetics and has become a key symbolic system that carries cultural information,builds identity recognition,and drives narrative.This article,by integrating semiotic theory and cultural dimension analysis,deeply dissects the core functions and common predicaments(stereotypes,cultural misinterpretation)of formative symbols in cross-cultural communication and systematically proposed four core design strategies:“extraction and translation of cultural symbols,”“visual mapping of cultural dimensions,”“symbolic support of narrative functions,”and“cultural decoding presuppositions for target audiences.”This article holds that successful cross-cultural modeling design should be committed to creative transformation on the basis of respecting the authenticity of culture,constructing a visual symbol system that combines cultural depth and universal appeal,and ultimately serving global narratives and in-depth cultural dialogues.展开更多
As an important method of practical teaching,case-based teaching has become increasingly prominent in international Chinese language education.However,the development of case-based teaching for Chinese characters rema...As an important method of practical teaching,case-based teaching has become increasingly prominent in international Chinese language education.However,the development of case-based teaching for Chinese characters remains insufficient,with limited research outcomes,making it difficult to effectively support the teaching and research of Chinese character instruction.The establishment of a case library for international Chinese character teaching can provide a wealth of teaching cases,meeting the developmental needs of international Chinese language education in the new era.展开更多
Chinese Characteristics作为重要的域外文献,以他者视野译写了晚清时期中国社会面貌及中国人特征。本研究以无本译写为主体理据,首先通过版本流变考察明恩溥在译写语言上的特点,由此反观其译写意图及思想来源,并深入剖析其思维认知的改...Chinese Characteristics作为重要的域外文献,以他者视野译写了晚清时期中国社会面貌及中国人特征。本研究以无本译写为主体理据,首先通过版本流变考察明恩溥在译写语言上的特点,由此反观其译写意图及思想来源,并深入剖析其思维认知的改变;进而针对1894年修订版进行碎片式底本溯源。选取文本中的典型案例,分析其译写语言内部的中国人特质,以期挖掘明恩溥译写现象背后的社会文化因素。本研究对Chinese Characteristics的考释,不仅有助于了解西方人眼中的中国国民特质,还可以此为镜,揭示明恩溥他塑中国形象中的正与偏,为今后借力使力,塑造可信、可敬、可爱的中国形象提供借鉴和参考。展开更多
The SiO_(2)'-CaO/(CaO+K_(2)O)(S'CK)diagram is an empirically derived major element-based equivalent to the modal IUGS alkali feldspar-quartz-plagioclase classification scheme for granitoids.It employs the cont...The SiO_(2)'-CaO/(CaO+K_(2)O)(S'CK)diagram is an empirically derived major element-based equivalent to the modal IUGS alkali feldspar-quartz-plagioclase classification scheme for granitoids.It employs the content of SiO_(2)and CaO/(CaO+K_(2)O)ratio to approximate the IUGS classification diagram and a normative-based Q'-ANOR plot.Four trends have been superimposed onto the SiO_(2)'-CaO/(CaO+K_(2)O)diagram based on published datasets from the Peninsular Ranges(calcic:C),Tuolumne(calc-alkalic:CA),Sherman(alkali-calcic:AC),and Bjerkreim-Sokndal(alkalic:A)batholiths,which were employed to constrain the positions of the C-CA,CA-AC and AC-A suite boundaries on the SiO_(2)versus(Na_(2)O+K_(2)O-CaO)(or modified alkali-lime index,MALI)granitic classification diagram.A merit of the SiO_(2)'-CaO/(CaO+K_(2)O)plot is identifying rock types comprising a suite and their relative abundances.The distinguished projections of five typical granitoid assemblages,which are summarized by Bonin et al.(2020),demonstrate the ability of SiO_(2)'-CaO/(CaO+K_(2)O)diagram to decipher their petrogenesis.The SiO_(2)'-CaO/(CaO+K_(2)O)plots for the plutonic suites of'known'tectonic settings can reveal their evolution paths and the lithological statistics.Accordingly,it is suggested that the SiO_(2)'-CaO/(CaO+K_(2)O)plot can distinguish the tectonic environments of plutonic suits by comparing the plutonic suites or batholiths of'unknown'tectonic context to the published datasets from granitoid suites formed within'known'tectonic settings.The modified SiO_(2)'-CaO/(CaO+K_(2)O)diagram links the bulk chemical composition of granitoid suites to the likely source,magmatic evolution,and tectonic setting;thus,it may be a useful tectono-magmatic classification scheme for granitoid suites.展开更多
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.T...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.展开更多
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 und...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.展开更多
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 go...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.展开更多
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 detec...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.展开更多
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...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.展开更多
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 wa...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.展开更多
The main purpose of this paper is using the properties of the classical Gauss sum and the analytic methods to study the computational problem of one kind of hybrid power mean involving the character sum of polynomials...The main purpose of this paper is using the properties of the classical Gauss sum and the analytic methods to study the computational problem of one kind of hybrid power mean involving the character sum of polynomials and a sum analogous to Kloosterman sum mod p,an odd prime,and give two sharp asymptotic formulae for them.展开更多
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 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.展开更多
文摘Urdu,a prominent subcontinental language,serves as a versatile means of communication.However,its handwritten expressions present challenges for optical character recognition(OCR).While various OCR techniques have been proposed,most of them focus on recognizing printed Urdu characters and digits.To the best of our knowledge,very little research has focused solely on Urdu pure handwriting recognition,and the results of such proposed methods are often inadequate.In this study,we introduce a novel approach to recognizing Urdu pure handwritten digits and characters using Convolutional Neural Networks(CNN).Our proposed method utilizes convolutional layers to extract important features from input images and classifies them using fully connected layers,enabling efficient and accurate detection of Urdu handwritten digits and characters.We implemented the proposed technique on a large publicly available dataset of Urdu handwritten digits and characters.The findings demonstrate that the CNN model achieves an accuracy of 98.30%and an F1 score of 88.6%,indicating its effectiveness in detecting and classifyingUrdu handwritten digits and characters.These results have far-reaching implications for various applications,including document analysis,text recognition,and language understanding,which have previously been unexplored in the context of Urdu handwriting data.This work lays a solid foundation for future research and development in Urdu language detection and processing,opening up new opportunities for advancement in this field.
文摘The character of Lensky in Eugene Onegin is one of the most discussed figures in the novel.He is the friend of Eugene Onegin and represents a contradictory personality.In the novel,Lensky displays a complex set of characteristics,appearing both elegant and noble on the outside,while concealing a deep inner loneliness and conflict.His attitude toward love and his dissatisfaction with society make him a dramatic and profound character in the story.By analyzing the character of Lensky,we can explore his role in the novel and his relationships with other characters.Lensky’s presence not only enriches the plot but also presents a figure filled with inner contradictions and emotional struggles.His friendship and rivalry with Eugene Onegin,as well as his admiration and helplessness in regard to Olga,showcase his complex inner world and reflections on life.Furthermore,the character of Lensky carries a certain symbolic significance.He can be seen as a metaphor for Russian society and culture at the time.His loneliness and inner conflict symbolize the limitations of Russian society and culture,while also reflecting Pushkin’s idealized pursuit of love and friendship,as well as his critical view of reality.In conclusion,through a deep analysis of Lensky’s character,we can better understand the portrayal of characters and the development of the plot in Eugene Onegin.It also provides readers with a perspective on Pushkin’s thoughts and observations on human nature,society,and culture.
基金supported by the National Natural Science Foundation of China(32300370, 32200363)International Partnership Program of Chinese Academy of Sciences (071GJHZ2023041MI),Biological Resources Programme, Chinese Academy of Sciences (KFJ-BRP-017-65, KFJ-BRP017-086, CAS-TAX-24-051, CAS-TAX-24-052)+2 种基金China Postdoctoral Science Foundation (2023M743416)Natural Science Foundation of Sichuan Province (No. 2023NSFSC1155)partially supported by the Vietnam Academy of Science and Technology (CT0000.03/25-27) to NTT。
文摘The Tien's Mountain Stream Snake,Opisthotropis daovantieni Orlov, Darevsky, and Murphy, 1998, has been represented solely by its type series, with no additional specimens reported in the past two decades. As a result, limited data exist and O. daovantieni remains one of the least studied members of its genus. Based on a re-examination of the type series, analysis of newly collected topotypic specimens, and a review of museum collections, this study provides an updated and comprehensive morphological characterization of O. daovantieni including detailed descriptions of hemipenial morphology, revised diagnostic characters,phylogenetic positioning, and ecological insights.Based on morphological comparisons with congeners, we also define the informal Opisthotropis spenceri group to facilitate future taxonomic work. In addition, this study documents a previously unreported defensive behavior involving tail-poking,observed in the field and thus far unique within the genus Opisthotropis.
基金funded by the MOE Project of Key Research Institute of Humanities and Social Sciences at Universities(22JJD720021)。
文摘The English“T” is widely held as a well-behaved Kaplanian indexical that has a directly-referential content and a character which imples immunity to self misidentification.In this paper I present uses of“T”outside attitudal contexts that are not directly referential yet exhibit immunity to self misidentification.They include uses of“I”for simulation and for counterfactual self portrait.I argue that they(i)challenge the non-shiftability and the rigidity arguments for the direct reference view,and(1)require a revision of the character of“T”to reflect the sensitivity of its content to the perspective from which the speaker identifies herself.
基金supported by the IITP(Institute of Information&Communications Technology Planning&Evaluation)-ITRC(Information Technology Research Center)grant funded by the Korean government(Ministry of Science and ICT)(IITP-2025-RS-2024-00438056).
文摘The increased accessibility of social networking services(SNSs)has facilitated communication and information sharing among users.However,it has also heightened concerns about digital safety,particularly for children and adolescents who are increasingly exposed to online grooming crimes.Early and accurate identification of grooming conversations is crucial in preventing long-term harm to victims.However,research on grooming detection in South Korea remains limited,as existing models trained primarily on English text and fail to reflect the unique linguistic features of SNS conversations,leading to inaccurate classifications.To address these issues,this study proposes a novel framework that integrates optical character recognition(OCR)technology with KcELECTRA,a deep learning-based natural language processing(NLP)model that shows excellent performance in processing the colloquial Korean language.In the proposed framework,the KcELECTRA model is fine-tuned by an extensive dataset,including Korean social media conversations,Korean ethical verification data from AI-Hub,and Korean hate speech data from Hug-gingFace,to enable more accurate classification of text extracted from social media conversation images.Experimental results show that the proposed framework achieves an accuracy of 0.953,outperforming existing transformer-based models.Furthermore,OCR technology shows high accuracy in extracting text from images,demonstrating that the proposed framework is effective for online grooming detection.The proposed framework is expected to contribute to the more accurate detection of grooming text and the prevention of grooming-related crimes.
基金Project supported by the National Natural Science Foundation of China(Grant Nos.12461048 and 12061051)the Natural Science Foundation of Inner Mongolia Autonomous Region(Grant No.2023MS01003)+2 种基金the Program for Young Talents of Science and Technology in Universities of Inner Mongolia Autonomous Region(Grant No.NJYT23096)the financial support from the Program of China Scholarships Council(Grant No.202306810054)for one year study at the University of Leedsthe support of Professor Ke Wu and Professor Weizhong Zhao at Capital Normal University,China。
文摘We construct the quantum fields presentation of the generalized universal character and the generalized B-type universal character,and by acting the quantum fields presentations to the constant 1,the generating functions are derived.Furthermore,we introduce two integrable systems known as the generalized UC(GUC)hierarchy and the generalized Btype UC(GBUC)hierarchy satisfied by the generalized universal character and the generalized B-type universal character,respectively.Based on infinite sequences of complex numbers,we further establish the multiparameter generalized universal character and the multiparameter generalized B-type universal character,which have been proved to be solutions of the GUC hierarchy and the GBUC hierarchy,respectively.
文摘Against the backdrop of the deep integration of the global film and television industry,character design has long transcended the mere pursuit of aesthetics and has become a key symbolic system that carries cultural information,builds identity recognition,and drives narrative.This article,by integrating semiotic theory and cultural dimension analysis,deeply dissects the core functions and common predicaments(stereotypes,cultural misinterpretation)of formative symbols in cross-cultural communication and systematically proposed four core design strategies:“extraction and translation of cultural symbols,”“visual mapping of cultural dimensions,”“symbolic support of narrative functions,”and“cultural decoding presuppositions for target audiences.”This article holds that successful cross-cultural modeling design should be committed to creative transformation on the basis of respecting the authenticity of culture,constructing a visual symbol system that combines cultural depth and universal appeal,and ultimately serving global narratives and in-depth cultural dialogues.
基金the research result of the 2022 International Chinese Education Research Project“Construction and Research of International Chinese Character Teaching Case Library in Chinese Education”(22YH88D).
文摘As an important method of practical teaching,case-based teaching has become increasingly prominent in international Chinese language education.However,the development of case-based teaching for Chinese characters remains insufficient,with limited research outcomes,making it difficult to effectively support the teaching and research of Chinese character instruction.The establishment of a case library for international Chinese character teaching can provide a wealth of teaching cases,meeting the developmental needs of international Chinese language education in the new era.
文摘The SiO_(2)'-CaO/(CaO+K_(2)O)(S'CK)diagram is an empirically derived major element-based equivalent to the modal IUGS alkali feldspar-quartz-plagioclase classification scheme for granitoids.It employs the content of SiO_(2)and CaO/(CaO+K_(2)O)ratio to approximate the IUGS classification diagram and a normative-based Q'-ANOR plot.Four trends have been superimposed onto the SiO_(2)'-CaO/(CaO+K_(2)O)diagram based on published datasets from the Peninsular Ranges(calcic:C),Tuolumne(calc-alkalic:CA),Sherman(alkali-calcic:AC),and Bjerkreim-Sokndal(alkalic:A)batholiths,which were employed to constrain the positions of the C-CA,CA-AC and AC-A suite boundaries on the SiO_(2)versus(Na_(2)O+K_(2)O-CaO)(or modified alkali-lime index,MALI)granitic classification diagram.A merit of the SiO_(2)'-CaO/(CaO+K_(2)O)plot is identifying rock types comprising a suite and their relative abundances.The distinguished projections of five typical granitoid assemblages,which are summarized by Bonin et al.(2020),demonstrate the ability of SiO_(2)'-CaO/(CaO+K_(2)O)diagram to decipher their petrogenesis.The SiO_(2)'-CaO/(CaO+K_(2)O)plots for the plutonic suites of'known'tectonic settings can reveal their evolution paths and the lithological statistics.Accordingly,it is suggested that the SiO_(2)'-CaO/(CaO+K_(2)O)plot can distinguish the tectonic environments of plutonic suits by comparing the plutonic suites or batholiths of'unknown'tectonic context to the published datasets from granitoid suites formed within'known'tectonic settings.The modified SiO_(2)'-CaO/(CaO+K_(2)O)diagram links the bulk chemical composition of granitoid suites to the likely source,magmatic evolution,and tectonic setting;thus,it may be a useful tectono-magmatic classification scheme for granitoid suites.
文摘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.
文摘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.
基金The results and knowledge included herein have been obtained owing to support from the following institutional grant.Internal grant agency of the Faculty of Economics and Management,Czech University of Life Sciences Prague,Grant No.2023A0004-“Text Segmentation Methods of Historical Alphabets in OCR Development”.https://iga.pef.czu.cz/.Funds were granted to T.Novák,A.Hamplová,O.Svojše,and A.Veselýfrom the author team.
文摘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.
基金The work was supported by the National Natural Science Foundation of China(61972062,62306060)the Basic Research Project of Liaoning Province(2023JH2/101300191)+1 种基金the Liaoning Doctoral Research Start-Up Fund Project(2023-BS-078)the Dalian Academy of Social Sciences(2023dlsky028).
文摘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.
基金supported by the Inner Mongolia Natural Science Fund Project(2019MS06013)Ordos Science and Technology Plan Project(2022YY041)Hunan Enterprise Science and Technology Commissioner Program(2021GK5042).
文摘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.
基金Princess Nourah bint Abdulrahman University Researchers Supporting Project Number(PNURSP2022R263)Princess Nourah bint Abdulrahman University,Riyadh,Saudi Arabiathe Deanship of Scientific Research at Umm Al-Qura University for supporting this work by Grant Code:22UQU4340237DSR39.
文摘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.
基金Supported by NSFC(No.12126357)Natural Science Basic Research Plan in Shaanxi Province of China(No.2023-JC-QN-0058)。
文摘The main purpose of this paper is using the properties of the classical Gauss sum and the analytic methods to study the computational problem of one kind of hybrid power mean involving the character sum of polynomials and a sum analogous to Kloosterman sum mod p,an odd prime,and give two sharp asymptotic formulae for them.
基金Supported by the National Natural Science Foundation of China (62277014)the National Key Research and Development Program of China (2020YFC1523100)the Fundamental Research Funds for the Central Universities of China (PA2023GDSK0047)。
文摘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.
