Character Structures Research Articles

Kreovanie, šírenie a recepcia komunikačných stereotypov v on-line médiách

V tomto příspěvku jsou analyzovány hlavní trendy ve vytváření a recepci specifických útvarů komunikační provozu v on-line médiích - komunikačních stereotypů jako ustálených znakových struktur. Interpretačním východiskem je teze, že fungování komunikačních stereotypů v on-line médiích je kulturně, sociálně a mentálně podmíněné a výsledkem tohoto fungování je konstruování sociokulturních izoglos ve společnosti, tedy rozšíření použití jistých komunikačních významů, jistého způsobu "čtení textu". Zvláštní pozornost je v textu věnována fungování mediálních presetů, komplexně zpracovávaných a šířených šablon a důsledkům, které použití presetů v on-line médiích vyvolává (i vzhledem k jejich využití v marketingovaej komunikaci): extenzifikaci on-line provozu a oslabování interpretačního vztahu uživatele k textu.

Nature of orbital and spin Rashba coupling in the surface bands ofSrTiO3andKTaO3

Tight-binding models for the recently observed surface electronic bands of ${\mathrm{SrTiO}}_{3}$ and ${\mathrm{KTaO}}_{3}$ are analyzed with a view to bringing out the relevance of momentum-space chiral angular momentum structures of both orbital and spin characters. The orbital and the accompanying spin angular momentum structures reveal complex linear and cubic dependencies in the momentum $\mathbf{k}$ (linear and cubic Rashba effects, respectively) in a band-specific manner. Analytical expressions for the cubic orbital and spin Rashba effects are derived by way of a unitary transformation technique we developed, and compared to numerical calculations. The cubic Rashba effect appears as in-plane modulations due to the ${C}_{4v}$ symmetry of the perovskite structure.

Effects of learning styles on learners’ collaborative patterns in a mobile-assisted, Chinese character-forming game based on a flexible grouping approach

This paper reports a novel, mobile-assisted, game-based learning design for Chinese character learning. In playing the ‘Chinese-PP’ game in a 1:1 (one-device-per-student) setting, each of the 31 target students in Primary 3 (9 years old) is assigned a Chinese character component. A student may make use of his/her own and peers’ character components to form a legitimate Chinese character, and invite the peers with matching components to join his/her group. The intention is to assist the students in developing general orthographic awareness (understanding the structures of Chinese characters) through social negotiation. In this paper, the students’ collaborative learning processes in three game sessions were analysed. The relationships between students with varied learning styles and their game behaviours and learning gains were unveiled as a result. Through the Chinese-PP learning activities that stimulated active peer coaching and social learning, we found that all the target students became active learning participants and achieved high learning gains in the last game session. Recommendations for the future development of such a novel learning approach will also be given.

Some psychic effects of neoliberalism: Narcissism, disavowal, perversion

Neoliberalisms promote the development of certain versions of subjectivity, certain character structures, defenses, transferences, and countertransferences. Foucauldian theories go only so far in being able to account for the way neoliberal versions of subjectivity are lived. The paper elaborates on the individual, group, and relational effects of social repudiations of vulnerability and dependency needs and describes the perverse effects of the widespread disavowal of the interdependence of privileged and marginalized populations.

Multi-scale Graph-matching Based Kernel for Character Recognition from Natural Scenes

Recognizing characters extracted from natural scene images is quite challenging due to the high degree of intraclass variation. In this paper, we propose a multi-scale graph-matching based kernel for scene character recognition. In order to capture the inherently distinctive structures of characters, each image is represented by several graphs associated with multi-scale image grids. The similarity between two images is thus defined as the optimum energy by matching two graphs (images), which finds the best match for each node in the graph while also preserving the spatial consistency across adjacent nodes. The computed similarity is suitable to construct a kernel for support vector machine (SVM). Multiple kernels acquired by matching graphs with multi-scale grids are combined so that the final kernel is more robust. Experimental results on challenging Chars74k and ICDAR03-CH datasets show that the proposed method performs better than the state of the art methods.

„Na ducha Lenina!” Historia sowieckich bohaterów komiksowych w popkulturze amerykańskiej

Napięcie między Związkiem Radzieckim a StanamiZjednoczonymi, definiujące światowy polityczny krajobrazdrugiej połowy dwudziestego wieku, miało swoje wyraźneprzełożenie na sposoby postrzegania i kreacji sowieckichbohaterów w ramach amerykańskiej kultury. Pierwszymi podstawowym celem naszego artykułu jest prześledzeniei opisanie funkcjonowania konkretnego motywu – figurRosjan, w szczególności zaś rosyjskich meta-ludzi w przestrzeniamerykańskiej kultury popularnej, przede wszystkimkomiksu głównonurtowego. Kwerenda ta ma w miarę możliwościwykazać podstawowy wymiar historyczny tj. okresywzrostu i spadku popularności, a nawet całkowitego zanikuposzukiwanej figury. Celem drugim jest analiza sposobówkonstrukcji komiksowych bohaterów związanychze Związkiem Radzieckim i postawienie ich w szerszymkontekście historyczno-kulturowym. Te zabiegi umożliwiąz kolei zasygnalizowanie zmieniającej się w czasie konstrukcji,na którą składają się wartości, stereotypy i popkulturoweklisze właściwe dla kultury amerykańskiej. Tym samymmamy nadzieję, że artykuł ten stanie się ważnym przyczynkiemdo dalszych badań nad omawianymi zagadnieniami.

Quantitative analysis of Chinese characters system based on a tree model

AbstractAs an ideographic system, Chinese writing is not based on the irreducible elements used in speaking (e.g., syllabic or alphabetic elements) as in phonetic systems. Consequently, there is a misperception that in Chinese writing, each character is treated as a separate symbol, which makes it seem very difficult to learn Chinese writing. In the modern study of Chinese ideography, the elements of Chinese writing are called components, which can play a quadruple role in composing characters. Based on this understanding of components, this paper uses the mathematical tree model to analyse the structure of Chinese characters and create a computational description of all of the character structures explained in

The effects of human finger and Chinese character on Chinese handwriting performance on mobile touch devices.

The aim of the present study is to investigate Chinese handwriting on mobile touch devices, considering the effects of three characteristics of the human finger (type, length, and width) and three characteristics of Chinese characters (direction of the first stroke, number of strokes, and structure). Due to the popularity of touch devices in recent years, finger input for Chinese characters has attracted more attention from both industry and academia. However, previous studies have no systematical consideration on the effects of human finger and Chinese characters on Chinese handwriting performance. An experiment was reported in this article to illustrate the effects of the human finger and Chinese characters on the Chinese handwriting performance (i.e., input time, accuracy, number of protruding strokes, mental workload, satisfaction, and physical fatigue). The experiment results indicated that all six factors have significant effects on Chinese handwriting performance, especially on the input time, accuracy, and number of protruding strokes. Finger type, finger length, finger width, direction of the first stroke, number of strokes, and character structures are significantly influencing Chinese handwriting performance. These factors should be taken into more consideration in future research and the practical design for Chinese handwriting systems.

Drawing on the variation theory to enhance students’ learning of Chinese characters

The variation theory of Ference Marton and his collaborators has widely been used as a framework for explaining what can possibly be learned in a particular classroom and what cannot. This paper reports on an experiment that put this theory to test in the context of students’ learning of the orthographic structures of Chinese characters. The experiment was carried out in the classrooms of two primary schools in Hong Kong. In each of the schools, two classes of students were taught differently, as informed by the theory, about the significance of the location of a component in the orthographic structure of a character in relation to whether the component provided a clue to the meaning of the character (called the part–part relations). The results of the experiment are consistent with the prediction of the theory that those students who were given the possibility to experience variation in the locations of components in the orthographic structures significantly outperformed those who were not. The results of the experiment demonstrate the power of the theory in guiding the design of teaching that affords students’ learning to happen.

An intelligent e‐learning software for learning to write correct Chinese characters on mobile devices

PurposeLearning Chinese is unquestionably very important and popular worldwide with the fast economic growth of China. To most foreigners and also local students, one of the major challenges in learning Chinese is to write Chinese characters in correct stroke sequences that are considered as significant in the Chinese culture. However, due to the potentially complicated structures of Chinese characters together with their stroke sequences, there are very few character recognition techniques that can effectively tackle the involved training task in an efficient and flexible manner. The purpose of this paper is to propose an intelligent and flexible e‐learning software based on learning objects to facilitate the learning of writing Chinese characters in correct stroke sequences.Design/methodology/approachThe paper adopts an incremental approach in designing the overall system architecture to emphasize on extendibility of the system. The basic features of the system including the evolution and pronunciation of each Chinese character can be embedded as a part of the learning object metadata to enhance students' understanding of Chinese characters. To demonstrate the feasibility of this proposal, a prototype of the proposed e‐learning software was built on smartphones such that students can learn anytime and anywhere.FindingsFrom the empirical evaluation of the e‐learning prototype for learning to write correct Chinese characters on mobile devices, it was found that foreign students can learn and practise the writing more effectively anytime and anywhere on their mobile devices after classes. Some initial positive feedback was collected. Furthermore, a more careful and thorough evaluation is planned to be conducted in relevant courses for foreign students in the upcoming Fall semester.Originality/valueThis proposal represents the first attempt to reduce the complexity while increasing the extendibility of the e‐learning software to learn Chinese through learning objects running on smartphones or mobile devices in general. More importantly, it opens up numerous opportunities for further investigations including possible integrations with other existing Chinese e‐learning systems.

Cognitive effects of English brush handwriting: the case of visual–spatial aptitude

Chinese calligraphic handwriting (CCH) involves a process of visual–spatial patterning of the characters as well as the motor control of the brush to follow specific character configurations through a projection of the cognitive images of the character. Past research has shown that this CCH act facilitates perceptual and cognitive abilities. One study showed a differentiating reaction time effect of brush writing in relation to symmetric and asymmetric Chinese character structures. Another study confirmed the effect of closure in character composition on visual–spatial ability of the practitioner through brush handwriting. Recognizing that different visual–spatial structuring of English alphabet could have different psychological impacts, this study examined whether brush writing of English letters could have similar effect on the practitioner's visual–spatial ability as that of Chinese brush handwriting. Because both the process of brush handwriting and the closed form of visual–spatial representation were common in the execution of Chinese and English scripts, the closed English letters would also advance the practitioners' general visual–spatial aptitude in terms of their enhanced cognitive capability to detect two- and three-dimensional cues. This expectation was confirmed to be in line with that found in the practice of Chinese brush handwriting with Chinese characters. This finding was accounted for by a common action grammar of handwriting between Chinese and English scripts. The implication is that the outcomes arising from brush handwriting using one script would be applicable to those of the other script. This view, therefore, suggests the plausible generality of handwriting theories and practical applications between the two writing systems.

The impact of the integrative perceptual approach on the teaching of Chinese characters in a Hong Kong kindergarten

This study investigated the effectiveness of the integrative perceptual approach (IPA) to enhancing Hong Kong kindergarten children’s Chinese character learning. The study applied the IPA to an experimental group of 29 lower form (K2) children. A group of 30 upper form children taught via traditional methods the year before, served as the control group. Quantitative data consisted of pre‐ and post‐test scores, analysed using dependent and independent t‐testing. It was found that the pupils in the experimental group had significantly improved their ability between pre‐ and post‐testing in three aspects of Chinese character mastery: shape, sound and meaning recognition. The progress made was significantly superior to that made by control group counterparts. Qualitative data gathered through teacher and parent interviews indicated that the pupils in the experimental group displayed increased awareness of the composition of several components and structures of Chinese characters.

Can isocyanogen azide exist?

Ever since the first attempt at its synthesis in 1912, cyanogen azide (NCN3) has continued to attract the attention of chemists in diverse fields such as photochemistry, organic chemistry, and energetic materials. However, to our great surprise, its isocyanide isomer, CNN3, has not been studied experimentally or theoretically. In this paper, for the first time, we report a theoretical spectroscopic and stability study of CNN3 employing the CCSD and CCSD(T) methods with the aug-cc-pVTZ basis set. In light of its potential multi-reference character, the isomers and transition state structures on the reaction pathway were re-optimized using the multi-configurational CASSCF method in conjunction with the cc-pVTZ basis set. It is shown that CNN3 should be intrinsically stable both with respect to isomerization and fragmentation. The structural and spectroscopic properties obtained in this study should provide useful information for the future laboratory identification of CNN3. For comparison, we also calculated the aug-cc-pVTZ-CCSD(T) and cc-pVTZ-CASSCF properties of NCN3.

Temporal dynamics of the modulation of character structure and phonetic radical in Chinese character processing—an ERP study

Chinese orthography, with semantic and phonetic radicals configured in different character structures, provides a unique opportunity to examine visual word processing. Previous ERP research showed that when participants silently named centrally presented characters, there was greater left hemisphere lateralization in N170 amplitude for sP characters (right-heavy, with a semantic radical on the left and a phonetic radical on the right) than Ps characters (the opposite configuration), suggesting that characters with different structures are processed differently in the brain. Here we utilize four additional character types, sS (right-heavy, no phonetic radical); Ss (the opposite configuration); Syp and Sys characters (symmetric structure, with and without phonetic radical respectively) to further examine how phonetic radical and character structure influence Chinese character processing. A significant interaction was found between character structure and hemisphere in P120 latency, suggesting that the modulation of character structure happens as early as 120 ms after the stimulus onset. Furthermore, the hemispheric asymmetry effects in N170 and P200 were found to be influenced by both phonetic radical and character structure, while N350 appeared to be modulated by phonetic radical only. These findings demonstrate that the modulation of character structure and phonetic radical have different time courses in Chinese character processing.

Handwritten Nushu Character Recognition Based on Hidden Markov Model

This paper proposes a statistical-structural character learning algorithm based on hidden Markov model for handwritten Nushu character recognition. The stroke relationships of a Nushu character reflect its structure, which can be statistically represented by the hidden markov model. Based on the prior knowledge of character structures, we design an adaptive statisticalstructural character learning algorithm that accounts for the most important stroke relationships, which aims to improve the recognition rate by adapting selecting correct character to the current handwritten character condition. We penalize the structurally mismatched stroke relationships using the prior clique potentials and derive the likelihood clique potentials from Gaussian mixture models. Theoretic analysis proves the convergence of the proposed algorithm. The experimental results show that the proposed method successfully detected and reflected the stroke relationships that seemed intuitively important. And the overall recognition rate is 93.7 percent, which confirms the effectiveness of the proposed methods.

Stereoscopic Effects in Character Structures Recognition: Application for Children with Developmental Dyslexia

Stereoscopic Effects in Character Structures Recognition: Application for Children with Developmental Dyslexia

Cascade Markov random fields for stroke extraction of Chinese characters

Extracting perceptually meaningful strokes plays an essential role in modeling structures of handwritten Chinese characters for accurate character recognition. This paper proposes a cascade Markov random field (MRF) model that combines both bottom-up (BU) and top-down (TD) processes for stroke extraction. In the low-level stroke segmentation process, we use a BU MRF model with smoothness prior to segment the character skeleton into directional substrokes based on self-organization of pixel-based directional features. In the high-level stroke extraction process, the segmented substrokes are sent to a TD MRF-based character model that, in turn, feeds back to guide the merging of corresponding substrokes to produce reliable candidate strokes for character recognition. The merit of the cascade MRF model is due to its ability to encode the local statistical dependencies of neighboring stroke components as well as prior knowledge of Chinese character structures. Encouraging stroke extraction and character recognition results confirm the effectiveness of our method, which integrates both BU/TD vision processing streams within the unified MRF framework.

Identifying Subscripts and Superscripts in Mathematical Documents

In mathematical OCR, it is necessary to analyze two-dimensional structures of the component characters and symbols in mathematical expressions printed in scientific documents. In this paper, we analyze the positional relationships between adjacent characters for the purpose of automatic discrimination between baseline characters, subscripts, and superscripts, which is one of the most important and delicate parts of structure analysis. It has been proven through a large-scale experiment that this discrimination can be carried out almost perfectly (~ 99.89%) by using the relative size and position of adjacent characters.

Type-2 Fuzzy Markov Random Fields and Their Application to Handwritten Chinese Character Recognition

In this paper, we integrate type-2 (T2) fuzzy sets with Markov random fields (MRFs) referred to as T2 FMRFs, which may handle both fuzziness and randomness in the structural pattern representation. On the one hand, the T2 membership function (MF) has a 3-D structure in which the primary MF describes randomness and the secondary MF evaluates the fuzziness of the primary MF. On the other hand, MRFs can represent patterns statistical-structurally in terms of neighborhood system and clique potentials and, thus, have been widely applied to image analysis and computer vision. In the proposed T2 FMRFs, we define the same neighborhood system as that in classical MRFs. To describe uncertain structural information in patterns, we derive the fuzzy likelihood clique potentials from T2 fuzzy Gaussian mixture models. The fuzzy prior clique potentials are penalties for the mismatched structures based on prior knowledge. Because Chinese characters have hierarchical structures, we use T2 FMRFs to model character structures in the handwritten Chinese character recognition system. The overall recognition rate is 99.07%, which confirms the effectiveness of the proposed method.

Markov Random Field-Based Statistical Character Structure Modeling for Handwritten Chinese Character Recognition

This paper proposes a statistical-structural character modeling method based on Markov random fields (MRFs) for handwritten Chinese character recognition (HCCR). The stroke relationships of a Chinese character reflect its structure, which can be statistically represented by the neighborhood system and clique potentials within the MRF framework. Based on the prior knowledge of character structures, we design the neighborhood system that accounts for the most important stroke relationships. We penalize the structurally mismatched stroke relationships with MRFs using the prior clique potentials, and derive the likelihood clique potentials from Gaussian mixture models, which encode the large variations of stroke relationships statistically. In the proposed HCCR system, we use the single-site likelihood clique potentials to extract many candidate strokes from character images, and use the pairsite clique potentials to determine the best structural match between the input candidate strokes and the MRF-based character models by relaxation labeling. The experiments on the KAIST character database demonstrate that MRFs can statistically model character structures, and work well in the HCCR system.