Machine recognition of online handwritten Devanagari characters

In this paper, we describe a system for the automatic recognition of isolated handwritten Devanagari characters obtained by linearizing consonant conjuncts. Owing to the large number of characters and resulting demands on data acquisition, we use structural recognition techniques to reduce some characters to others. The residual characters are then classified using the subspace method. Finally the results of structural recognition and feature-based matching are mapped to give final output. The proposed system Ifs evaluated for the writer dependent scenario.

Resolving Ambiguities in Confused Online Tamil Characters with Post Processing Algorithms

This paper addresses the problem of resolving ambiguities in frequently confused online Tamil character pairs by employing script specific algorithms as a post classification step. Robust structural cues and temporal information of the preprocessed character are extensively utilized in the design of these algorithms. The methods are quite robust in automatically extracting the discriminative sub-strokes of confused characters for further analysis. Experimental validation on the IWFHR Database indicates error rates of less than 3 % for the confused characters. Thus, these post processing steps have a good potential to improve the performance of online Tamil handwritten character recognition.

Leader - Follower Relations In An Intercultural Chinese Context - Personal, Interpersonal and Behavioural Influences and Impact on Work Contribution

The successful interaction between leaders and their followers is central to the overall functioning of a company. The increasingly multinational nature of modern business and the resulting multicultural and increasingly heterogeneous workforce imposes specific challenges to the development of high-quality work relationships. The Western multinational companies that have started operations in China are facing these challenges. This study examines the quality of leader-follower relationships between Western expatriate leaders and their Chinese followers as well as between Chinese leaders and their Chinese followers in Western-owned subsidiaries in China. The focus is on the influence of personal, interpersonal and behavioural factors (personality, values, cultural knowledge, perceived and actual similarity, interactional justice, and follower performance) and the work-related implications of these relationships (job attitudes and organisational citizenship behaviour). One interesting finding of this study is that Chinese followers have higher perceptions of their Western than their Chinese leaders. The results also indicate that Chinese and Western leaders’ perceptions of their followers are not influenced favourably by the same follower characteristics. In a similar vein, Chinese followers value different traits in Western versus Chinese leaders. These results, as well as the numerous more specific findings of the study, have practical implications for international human resource management and areas such as selection, placement and training. Due to the different effect of personal and interpersonal factors across groups, it is difficult to achieve the “perfect match” between leader and follower characteristics that simultaneously contribute to high-quality relationships for Chinese and Western leaders as well as for followers. However, the results indicate that the ability of organisations to enhance the quality of leader-follower relations by selecting and matching people with suitable characteristics may provide an effective means for organisations to increase positive job attitudes and hence influence work-related outcomes.

Panel Cointegration of Chinese A and B Shares

This paper uses panel unit root and cointegration methods to test the stationarity of the premium on domestic investors’ A shares over foreign investors’ B shares and cointegration between the A and B share prices on the Chinese stock exchanges. We find that the A share price premium is nonstationary until 2001, when the A and B share markets were partially merged, and that the A and B share prices are cointegrated in the panel.Cointegration is more likely to be found for firms in the service sector and for firms that issued B shares recently.

CHITRA: Cognitive handprinted input-trained recursively analyzing system for recognition of alphanumeric characters

A novel system for recognition of handprinted alphanumeric characters has been developed and tested. The system can be employed for recognition of either the alphabet or the numeral by contextually switching on to the corresponding branch of the recognition algorithm. The two major components of the system are the multistage feature extractor and the decision logic tree-type catagorizer. The importance of ldquogoodrdquo features over sophistication in the classification procedures was recognized, and the feature extractor is designed to extract features based on a variety of topological, morphological and similar properties. An information feedback path is provided between the decision logic and the feature extractor units to facilitate an interleaved or recursive mode of operation. This ensures that only those features essential to the recognition of a particular sample are extracted each time. Test implementation has demonstrated the reliability of the system in recognizing a variety of handprinted alphanumeric characters with close to 100% accuracy.

Management of Routine in Two Chinese Kindergartens - An Ethnographic Study

Based on a one-month long ethnographic study conducted in two Chinese kindergartens, this study aims to understand the issue of discipline in the Chinese preschool setting through an examination of practices teachers use to manage everyday routines in the kindergarten. It also seeks to understand teachers’ values behind their choices of practices. Data of this study are comprised of three parts - notes of participant observation in eight classrooms with a focus on teacher-child interaction; interviews with nine teachers and directors of the two kindergartens; and written accounts of four teachers collected after the fieldwork in order to understand the particular practices of teachers’ praising and criticizing children. A grounded theory approach is applied to code and analyze data. Results of analysis are structured as followed. First the concept of routine is clarified based on teachers’ definition of it and observation notes on its main components, namely the timetable of everyday activities; general behavioral rules in the kindergarten; and detailed rules and procedures for various activities in the kindergarten. Then practices for managing routines are examined – how teachers organize children in activities, enforce routines, and restore routines when they are not followed well. After that, the matter of self-control is examined in relation with external control. Then teachers’ perception of their roles as the manager, director and executor of routines is presented in a discourse of control in which the values behind practices are found to be embedded. The next section of analysis examines the role of routine in relation with other activities in the kindergarten. Results indicate that routine which is supposed to be the foundation of other activities is in conflict with other activities. The last section of analysis provides some reflections on the rational of routine management in Chinese kindergartens in relation with the overall goals of Chinese preschool education. It also provides some reflections on the effect current mode of teacher-child interactions may have on children's self construction and their understanding of self in relation with the society. As a conclusion, this study suggests that the current mode of routine management in Chinese kindergartens relies heavily on teachers' control, leaving great room for better acknowledging children's agency.

Chinese immigrants to Finland: A qualitative study of housing, employment, access to health care and child care as sociological dimensions in their settlement process

The Master’s thesis is qualitative research based on interviews of 15 Chinese immigrants to Finland in order to provide a sociological perspective of the migration experience through the eyes of Chinese immigrants in the Finnish social welfare context. This research is mainly focused upon four crucial aspects of life in the settlement process: housing, employment, access to health care and child care. Inspired by Allardt’s theoretical framework ‘Having, Loving and Being’, social relationships and individual satisfaction are examined in the case of Chinese interviewees dealing with the four life aspects. Finland was not perceived as an attractive migration destination for most Chinese interviewees in the beginning. However, with longer residence in Finland, the Finnish social welfare system gradually became a crucial appealing factor in their permanent settlement in Finland. And meanwhile, social responsibility of attending their old parents in China, strong feelings of being isolated in Finland, and insufficient integration into the Finnish society were influential factors for their decision of returning to China. Social relationships with personal friends, migration brokers, schools, employers and family relatives had great influences in the four life aspects of Chinese immigrants in Finland. The social relationship with the Finnish social welfare sector is supportive to Chinese immigrants, but Chinese immigrants do not heavily rely on Finnish social protection. The housing conditions were greatly improved over time while the upward mobility in the Finnish labour market was not significant among Chinese immigrants. All Chinese immigrants were satisfied with their current housing by the time I interviewed them while most of them had subjective feelings of being alienated in the Finnish labour market, which seriously prevented them from integrating into the Finnish society. In general, Chinese immigrants were satisfied with the low cost of accessing the Finnish public health care services and affordable Finnish child day care services and financial subsidies for children from the Finnish social welfare sector. This research also suggests that employment is the central basis in well-being. Support from the Finnish social welfare sector can improve the satisfaction levels among immigrants, especially when it mitigates the effects of low-paid employment. As well, my empirical study of Chinese immigrants in Finland shows that Having (needs for materials), Loving (needs for social relations) and Being (needs for social integration) are all involved in the four concrete aspects (housing, employment, access to health care and child care).

Fusion of Complementary Online and Offline Strategies for Recognition of Handwritten Kannada Characters

This work describes an online handwritten character recognition system working in combination with an offline recognition system. The online input data is also converted into an offline image, and parallely recognized by both online and offline strategies. Features are proposed for offline recognition and a disambiguation step is employed in the offline system for the samples for which the confidence level of the classifier is low. The outputs are then combined probabilistically resulting in a classifier out-performing both individual systems. Experiments are performed for Kannada, a South Indian Language, over a database of 295 classes. The accuracy of the online recognizer improves by 11% when the combination with offline system is used.

Recognition of Kannada characters extracted from scene images

In this paper, we describe a method for feature extraction and classification of characters manually isolated from scene or natural images. Characters in a scene image may be affected by low resolution, uneven illumination or occlusion. We propose a novel method to perform binarization on gray scale images by minimizing energy functional. Discrete Cosine Transform and Angular Radial Transform are used to extract the features from characters after normalization for scale and translation. We have evaluated our method on the complete test set of Chars74k dataset for English and Kannada scripts consisting of handwritten and synthesized characters, as well as characters extracted from camera captured images. We utilize only synthesized and handwritten characters from this dataset as training set. Nearest neighbor classification is used in our experiments.

Dynamic multi-relational Chinese restaurant process for analyzing influences on users in social media

We study the problem of analyzing influence of various factors affecting individual messages posted in social media. The problem is challenging because of various types of influences propagating through the social media network that act simultaneously on any user. Additionally, the topic composition of the influencing factors and the susceptibility of users to these influences evolve over time. This problem has not been studied before, and off-the-shelf models are unsuitable for this purpose. To capture the complex interplay of these various factors, we propose a new non-parametric model called the Dynamic Multi-Relational Chinese Restaurant Process. This accounts for the user network for data generation and also allows the parameters to evolve over time. Designing inference algorithms for this model suited for large scale social-media data is another challenge. To this end, we propose a scalable and multi-threaded inference algorithm based on online Gibbs Sampling. Extensive evaluations on large-scale Twitter and Face book data show that the extracted topics when applied to authorship and commenting prediction outperform state-of-the-art baselines. More importantly, our model produces valuable insights on topic trends and user personality trends beyond the capability of existing approaches.

Phenotypic characters of rice landraces reveal independent lineages of short-grain aromatic indica rice

Rice landraces are lineages developed by farmers through artificial selection during the long-term domestication process. Despite huge potential for crop improvement, they are largely understudied in India. Here, we analyse a suite of phenotypic characters from large numbers of Indian landraces comprised of both aromatic and non-aromatic varieties. Our primary aim was to investigate the major determinants of diversity, the strength of segregation among aromatic and non-aromatic landraces as well as that within aromatic landraces. Using principal component analysis, we found that grain length, width and weight, panicle weight and leaf length have the most substantial contribution. Discriminant analysis can effectively distinguish the majority of aromatic from non-aromatic landraces. More interestingly, within aromatic landraces long-grain traditional Basmati and short-grain non-Basmati aromatics remain morphologically well differentiated. The present research emphasizes the general patterns of phenotypic diversity and finds out the most important characters. It also confirms the existence of very unique short-grain aromatic landraces, perhaps carrying signatures of independent origin of an additional aroma quantitative trait locus in the indica group, unlike introgression of specific alleles of the BADH2 gene from the japonica group as in Basmati. We presume that this parallel origin and evolution of aroma in short-grain indica landraces are linked to the long history of rice domestication that involved inheritance of several traits from Oryza nivara, in addition to O. rufipogon. We conclude with a note that the insights from the phenotypic analysis essentially comprise the first part, which will likely be validated with subsequent molecular analysis.

Improved recognition of aged Kannada documents by effective segmentation of merged characters

In optical character recognition of very old books, the recognition accuracy drops mainly due to the merging or breaking of characters. In this paper, we propose the first algorithm to segment merged Kannada characters by using a hypothesis to select the positions to be cut. This method searches for the best possible positions to segment, by taking into account the support vector machine classifier's recognition score and the validity of the aspect ratio (width to height ratio) of the segments between every pair of cut positions. The hypothesis to select the cut position is based on the fact that a concave surface exists above and below the touching portion. These concave surfaces are noted down by tracing the valleys in the top contour of the image and similarly doing it for the image rotated upside-down. The cut positions are then derived as closely matching valleys of the original and the rotated images. Our proposed segmentation algorithm works well for different font styles, shapes and sizes better than the existing vertical projection profile based segmentation. The proposed algorithm has been tested on 1125 different word images, each containing multiple merged characters, from an old Kannada book and 89.6% correct segmentation is achieved and the character recognition accuracy of merged words is 91.2%. A few points of merge are still missed due to the absence of a matched valley due to the specific shapes of the particular characters meeting at the merges.