Using generative models for handwritten digit recognition

We describe a method of recognizing handwritten digits by fitting generative models that are built from deformable B-splines with Gaussian ``ink generators'' spaced along the length of the spline. The splines are adjusted using a novel elastic matching procedure based on the Expectation Maximization (EM) algorithm that maximizes the likelihood of the model generating the data. This approach has many advantages. (1) After identifying the model most likely to have generated the data, the system not only produces a classification of the digit but also a rich description of the instantiation parameters which can yield information such as the writing style. (2) During the process of explaining the image, generative models can perform recognition driven segmentation. (3) The method involves a relatively small number of parameters and hence training is relatively easy and fast. (4) Unlike many other recognition schemes it does not rely on some form of pre-normalization of input images, but can handle arbitrary scalings, translations and a limited degree of image rotation. We have demonstrated our method of fitting models to images does not get trapped in poor local minima. The main disadvantage of the method is it requires much more computation than more standard OCR techniques.

Drying processess in the United Kingdom:assessment of industrial energy utilisation and efficiency of drying systems and the modelling of drying characters using neural networks (BL)

Drying is an important unit operation in process industry. Results have suggested that the energy used for drying has increased from 12% in 1978 to 18% of the total energy used in 1990. A literature survey of previous studies regarding overall drying energy consumption has demonstrated that there is little continuity of methods and energy trends could not be established. In the ceramics, timber and paper industrial sectors specific energy consumption and energy trends have been investigated by auditing drying equipment. Ceramic products examined have included tableware, tiles, sanitaryware, electrical ceramics, plasterboard, refractories, bricks and abrasives. Data from industry has shown that drying energy has not varied significantly in the ceramics sector over the last decade, representing about 31% of the total energy consumed. Information from the timber industry has established that radical changes have occurred over the last 20 years, both in terms of equipment and energy utilisation. The energy efficiency of hardwood drying has improved by 15% since the 1970s, although no significant savings have been realised for softwood. A survey estimating the energy efficiency and operating characteristics of 192 paper dryer sections has been conducted. Drying energy was found to increase to nearly 60% of the total energy used in the early 1980s, but has fallen over the last decade, representing 23% of the total in 1993. These results have demonstrated that effective energy saving measures, such as improved pressing and heat recovery, have been successfully implemented since the 1970s. Artificial neural networks have successfully been applied to model process characteristics of microwave and convective drying of paper coated gypsum cove. Parameters modelled have included product moisture loss, core gypsum temperature and quality factors relating to paper burning and bubbling defects. Evaluation of thermal and dielectric properties have highlighted gypsum's heat sensitive characteristics in convective and electromagnetic regimes. Modelling experimental data has shown that the networks were capable of simulating drying process characteristics to a high degree of accuracy. Product weight and temperature were predicted to within 0.5% and 5C of the target data respectively. Furthermore, it was demonstrated that the underlying properties of the data could be predicted through a high level of input noise.

Progressive structural analysis for dynamic recognition of on-line handwritten mathematical expressions

Structural analysis in handwritten mathematical expressions focuses on interpreting the recognized symbols using geometrical information such as relative sizes and positions of the symbols. Most existing approaches rely on hand-crafted grammar rules to identify semantic relationships among the recognized mathematical symbols. They could easily fail when writing errors occurred. Moreover, they assume the availability of the whole mathematical expression before being able to analyze the semantic information of the expression. To tackle these problems, we propose a progressive structural analysis (PSA) approach for dynamic recognition of handwritten mathematical expressions. The proposed PSA approach is able to provide analysis result immediately after each written input symbol. This has an advantage that users are able to detect any recognition errors immediately and correct only the mis-recognized symbols rather than the whole expression. Experiments conducted on 57 most commonly used mathematical expressions have shown that the PSA approach is able to achieve very good performance results.

Offline Handwriting Recognition Using Genetic Algorithm

In this paper, a new method for offline handwriting recognition is presented. A robust algorithm for handwriting segmentation has been described here with the help of which individual characters can be segmented from a word selected from a paragraph of handwritten text image which is given as input to the module. Then each of the segmented characters are converted into column vectors of 625 values that are later fed into the advanced neural network setup that has been designed in the form of text files. The networks has been designed with quadruple layered neural network with 625 input and 26 output neurons each corresponding to a character from a-z, the outputs of all the four networks is fed into the genetic algorithm which has been developed using the concepts of correlation, with the help of this the overall network is optimized with the help of genetic algorithm thus providing us with recognized outputs with great efficiency of 71%.

Az európai vállalkozó karaktere (The characters of the European entrepreneur and the European manager)

Miben különböznek motivációjukat, értékeit, habitusukat tekintve a vállalkozók, illetve a menedzserek a társadalom többi tagjától és egymástól? Egy 29 európai országra kiterjedő reprezentatív lakossági kérdőíves felmérés (European Social Survey) alapján keresik a szerzők a választ e kérdésre. A Schwartz-értéktesztet használják, amelynek segítségével meghatározhatók az általános célok, elvek, amelyek követését egy személy fontosnak tartja az életében. Így felrajzolható a személy karaktere. Hozzájárulásuk az irodalomhoz kettős. Bár készültek európai szinten elemzések a vállalkozók által vallott sajátos értékekről, a Schwartz-teszt átfogóbb, árnyaltabb és megbízhatóbb elemzést tesz lehetővé. Továbbá, az említett elemzések csak az önfoglalkoztatókat vizsgálták, amely kategória magában foglalja ugyan a vállalkozókat, ám tágabb annál. Az alkalmazott menedzserekről pedig tudomásuk szerint egyáltalán nem készült hasonló elemzés. / === / What distinguishes entrepreneurs and managers from the rest of society and from each other in terms of motivation and values? The authors attempt to answer these questions by analysing data from the European Social Survey covering the populations of 29 countries. They use the Schwartz value-test to identify the general goals and principles people choose to follow in their lives. The test enables them to paint the typical personal characters of entrepreneurs and managers. Their contribution to the literature is threefold. First, although the values held by European entrepreneurs have been investigated before, the Schwartz test provides for a more comprehensive and nuanced analysis. Second, prior statistical analyses have focussed on self-employed, which is a much broader category than entrepreneurs. Third, the distinguishing values of employed managers have not been analysed so far in a similar way.

I want out of the labels : how Chuck Palahniuk's characters challenge the dominant discourse

The purpose of this study was to explore postmodern identity in the work of Chuck Palahniuk. The characters within Palahniuk's text Invisible Monsters realize the manner in which identity is a construct, and their response is to oppose and redefine it. In my research, I looked at how postmodern identity is defined by some of the leading critical thinkers in the field, and then I applied their thought to Palahniuk's characters. I showed how these characters come to understand the process by which society defines them, and with that realization, they oppose its totalizing definitions. The characters deconstruct the natural attitudes society has towards identity, and they reveal that it is in some way possible to create a unique identity that is not easily definable by the ruling discourse. I concluded that his attention to identity highlights Palahniuk's concern for the place, identity, and influence of his generation.

Students' views on the learning of kanji : A study the views and experiences of students at the Swedish universities concerning the teaching and learning of Chinese characters as used in Japanese

Kanji, the Chinese characters adopted to write the Japanese language, is often mentioned as one of the most difficult aspects of mastering said language. This is especially said about people from outside the Sinosphere i.e. PRC, Taiwan, North and South Korea, Japan and Vietnam. In the following thesis 12 students studying the Japanese language at Swedish universities were interviewed about their experiences when it comes to learning and being taught about kanji. A chapter summarizing some of the research that is relevant to this thesis is also included. Topics touched upon in this and the result chapter include the desire for more structured approach to kanji learning based on breaking down the characters into elemental components, spaced repetition (SRS), mnemonics.

Great characters of the New Testament /

"Reprinted June 1925"--T.p. verso.

Dynamically balanced and plausible trajectory planning for human-like characters

International audience

Variation, correlation and heritability of interest characters for selection of African eggplant

The eggplant ( Solanum aethiopicum ) is the species of the Solanum genus, whose geographical distribution is broadest. It is grown throughout tropical Africa, and includes three groups of cultivars commonly called African or indigenous eggplant. Kumba group or “bitter eggplant” is an important Solanaceous vegetable crop in Burkina Faso. The objective of this study was to determine genetic variability, strength of association and level of heritability among agronomic interest traits. Phenotypic and genotypic variations and heritability of 14 traits were estimated in 61 accessions at Institut de Développement Rural (IDR), Gampela in Burkina Faso. High phenotypic and genotypic coefficients of variation were observed for fruit diameter, number of seeds per fruit, fruit weight, leaf blade length and width, and height at flowering. In addition, genetic and phenotypic variances were high for the number of seed, fruit weight, plant height at flowering and days to 50% flowering. High heritability estimates were recorded for all traits. Fruit weight showed a positive association with fruit diameter and thickness. The fifty percent flowering cycle registered positive correlations with plant height and fruit diameter. Fruit number showed a negative association with fruit weight and diameter, and 50% flowering cyle.