Showing papers on "Character (mathematics) published in 2013"

VIA Character Strengths: Research and Practice (The First 10 Years)

Abstract: The VIA Classification is a widely used framework for helping individuals discover, explore, and use those qualities that are strongest in them – their character strengths. The VIA Inventory of Strengths is an accessible and widely used assessment instrument that measures 24 universally valued strengths. Research has found a number of important links between these character strengths and valued outcomes (e.g., life satisfaction, achievement). The practice of character strengths has not been studied as extensively; however, a number of practices, strength-based models, and applications are emerging with good potential.

Scene Text Recognition Using Part-Based Tree-Structured Character Detection

Abstract: Scene text recognition has inspired great interests from the computer vision community in recent years. In this paper, we propose a novel scene text recognition method using part-based tree-structured character detection. Different from conventional multi-scale sliding window character detection strategy, which does not make use of the character-specific structure information, we use part-based tree-structure to model each type of character so as to detect and recognize the characters at the same time. While for word recognition, we build a Conditional Random Field model on the potential character locations to incorporate the detection scores, spatial constraints and linguistic knowledge into one framework. The final word recognition result is obtained by minimizing the cost function defined on the random field. Experimental results on a range of challenging public datasets (ICDAR 2003, ICDAR 2011, SVT) demonstrate that the proposed method outperforms state-of-the-art methods significantly both for character detection and word recognition.

Developing Leadership Character in Business Programs

Abstract: Our objective is to encourage and enable leadership character development in business education. Building on a model of character strengths and their link to virtues, values, and ethical decision making, we describe an approach to develop leadership character at the individual, group, and organizational levels. We contrast this approach to existing practices that have focused on teaching functional content over character and address how business educators can enable leadership character development through their own behaviors, relationships, and structures. Most important, we provide concrete suggestions on how to integrate a focus on character development into existing business programs, both in terms of individual courses as well as the overall curriculum. We highlight that the development of leadership character must extend beyond student engagement in a course since “it takes a village” to develop character.

Device, system and method for processing character data

Abstract: A method is described. The method comprising the steps of receiving character data from the remote device following a selection of character data for application to a target; and determining, based on one or more characters in the character data, one or more components executable on the processor for supplying the character data thereto. A device is also described.

Sparse arrays of signatures for online character recognition

Abstract: In mathematics the signature of a path is a collection of iterated integrals, commonly used for solving dierential equations. We show that the path signature, used as a set of features for consumption by a convolutional neural network (CNN), improves the accuracy of online character recognition|that is the task of reading characters represented as a collection of paths. Using datasets of letters, numbers, Assamese and Chinese characters, we show that the rst, second, and even the third iterated integrals contain useful information for consumption by a CNN. On the CASIA-OLHWDB1.1 3755 Chinese character dataset, our approach gave a test error of 3.58%, compared with 5.61%[4] for a traditional CNN. A CNN trained on the CASIA-OLHWDB1.0-1.2 datasets won the ICDAR2013 Online Isolated Chinese Character recognition competition. Computationally, we have developed a sparse CNN implementation that make it practical to train CNNs with many layers of maxpooling. Extending the MNIST dataset by translations, our sparse CNN gets a test error of 0.31%.

Reducing Stigma and Out‐Group Distinctions Through Perspective‐Taking in Narratives

Abstract: We examine how viewers' narrative involvement is impacted by a character's membership in a highly stigmatized group. In particular, we explore how perspective-taking with a character, a dimension of the identification construct (J. Cohen, 2001), influences in-group/out-group perception. Participants viewed 1 of 2 edited versions of the film Sherrybaby, where the main character was manipulated to be relatively more stigmatized (recovering drug addict) or less stigmatized (single mother). As predicted, participants differed with respect to perspective-taking—the highly stigmatized character corresponded to less perspective-taking. Furthermore, the mediation and moderation results lend support to the argument that perspective-taking increases perceptions of in-group belonging and is of particular importance in determining whether a narrative influences in-group/out-group perspectives.

Character degrees of extensions of PSL2(q) and SL2(q)

Abstract: Denote by S the projective special linear group PSL2(q) over the field of q elements. We determine, for all values of q > 3, the degrees of the irreducible complex characters of every group H such that S 6 H 6 Aut(S). We also determine the character degrees of certain extensions of the special linear group SL2(q). Explicit knowledge of the character tables of SL2(q), GL2(q), PSL2(q), and PGL2(q) is used along with standard Clifford theory to obtain the degrees.

Order-independent text input

Abstract: A computing device is described that outputs, for display, a plurality of character input controls. A plurality of characters of a character set is associated with at least one character input control of the plurality of character input controls. The computing device receives an indication of a gesture to select the at least one character input control. The computing device determines, based at least in part on a characteristic of the gesture, at least one character included in the set of characters associated with the at least one character input control. The computing device determines, based at least in part on the at least one character, a candidate character string. In response to determining the candidate character string, the computing device outputs, for display, the candidate character string.

Pembentukan Karakter Melalui Pendidikan Agama Islam

Abstract: This writing is presenting about the role of Pendidikan Agama Islam (PAI) lesson toward students. Pendidikan Agama Islam (PAI) is one of the most importances pilar of character education. Character education will build well, if it is started from cultivating religious sense of students, therefore, PAI lesson become one of supporting lesson of character education. Through PAI teaching and learning, the students is taught belief of God as the basic of their religion, taught al quran and hadits as their way of life, taught fiqih as law signs in doing Islam teaching, taught Islam history as a good life example, and taught ethica as the way of human character.

Virtual keyboard input for international languages

Abstract: In one example, a computing device includes at least one processor configured to output for display, a graphical keyboard. The at least one processor may also be configured to model, in a first lattice, a plurality of candidate character strings that include symbols of a first alphabet. The first lattice may indicate spatial probabilities of the plurality of candidate character strings. The at least one processor may be configured to determine, using a second lattice that indicates probabilities of one or more words of a second language based at least in part on the spatial probabilities of the plurality of candidate character strings, a probability that the at least one of the plurality of candidate character strings corresponds to at least one word included in the second language. The at least one processor may be configured to output for display, the one or more symbols representing at least one word.

Learning to See the Patterns in Chinese Characters

Abstract: Chinese children's visual representation of characters was tracked with two tasks The Delayed Copy Character Task required children to reproduce different types of characters and noncharacters after each had been briefly presented The Detect Component Task required children to find different types of components embedded in sets of characters Experiment 1 showed that by late first grade some children are aware of the internal structure of Chinese characters and are beginning to encode characters in terms of units representing major character components Experiment 2 involved children from the second and fourth grade, as well as children early in the first grade, and more refined versions of the perceptual tasks The finding again was that major components of characters, and even subcomponents that do not represent semantic or phonological information, function as units of character perception The ability to see characters in terms of constituent units is acquired gradually over the early elementary sch

Recovering hidden Bloch character: Unfolding electrons, phonons, and slabs

Abstract: PBA was supported in part by US DOE Grant No DE-FG02-08ER46550 DAC thanks NSF for a summer REU scholarship administered by Stony Brook University (NSF Grant No PHYS-0851594) JMS was supported by Grants No FIS2009-12721 and No FIS2012-37549

Character data entry

Abstract: Methods and apparatuses for entry of character data are disclosed. In one example, a user action is received at a headset input user interface. The user action is correlated to a character data previously stored. The character data is transmitted to a host device, the character data configured to be automatically entered in one or more data fields.

Method and apparatus for word prediction selection

Abstract: Methods and apparatuses are provided for improving word prediction candidate selection in an electronic device. Input of one or more characters is received via a capacitive physical keyboard. A word prediction process generates a set of word prediction candidates, determines a unique character in each word prediction candidate, and displays the word prediction candidates along with visual indicia to indicate the unique character. A second input is then received comprising a tap input of a single character on the keyboard. The electronic device determines whether the second input corresponds to a unique character associated with any of the word prediction candidates, and if so, displays the selected word in an input field on the display.

Building Meaningful Parasocial Relationships Between Toddlers and Media Characters to Teach Early Mathematical Skills

Abstract: Very young children have difficulty transferring what they view onscreen to their offscreen worlds. This study examined whether familiarizing toddlers with a character would improve toddlers' performance on a subsequent seriation task. Toddlers were randomly assigned to one of three conditions: (1) a familiarized character condition where toddlers viewed character-based videos and engaged in character-based play over a 3-month period before viewing the seriation video demonstration; (2) an unfamiliarized character condition where the toddler only saw the seriation video demonstration; and (3) a no-exposure control group where the toddler did not see the seriation video demonstration or have any involvement with the character. All toddlers were tested on the same seriation task at age 21 months, with the familiarized character group beginning the study at age 18 months and the other groups participating only at age 21 months. Toddlers in the familiarized character condition, but not the unfamiliarized char...

Character input device, electronic apparatus, control method, control program and recording medium

Abstract: PROBLEM TO BE SOLVED: To dynamically change whether to present a conversion candidates for a correction character string in accordance with a user's selection.SOLUTION: A use frequency determination part 8 acquires an index value for determining an erroneous input, and determines whether to be an erroneous input on the basis of a magnitude relation of the acquired index value to a reference value. A Kana and Kanji conversion part 7 determines a conversion candidate for an input character string in the case of not being an erroneous input as a result of the determination, and conversion candidates for the input character string and a correction character string in the case of being the erroneous input. The use frequency determination part 8 increases or decreases the index value or the reference value on the basis of which is selected between conversion candidates for the input character string and conversion candidates for the correction character string.

Character input device and program

Abstract: PROBLEM TO BE SOLVED: To prompt quick recognition of a wrong input.SOLUTION: A touch panel 3 integrally includes a display section 3a for displaying a screen, and an input section 3b for receiving a touch input in a position on the screen displayed on the display section 3a. A CPU 11 displays a character input screen having a character display area on the display section 3a, assigns a software keyboard with a plurality of characters arranged to the touch panel 3, and displays a character of the software keyboard corresponding to a position of a touch input to the input section 3b, as a character to be input, in the character display area. The CPU 11 obtains an evaluation value of every character to be input on the basis of an input mode of the touch input to the input section 3b. The CPU 11 determines a character to be corrected from among characters to be input on the basis of the obtained evaluation value of every character to be input. The CPU 11 displays the determined character to be corrected identifiably on the display section 3a.

What Makes Characters’ Bad Behaviors Acceptable? The Effects of Character Motivation and Outcome on Perceptions, Character Liking, and Moral Disengagement

Abstract: Many characters in entertainment content behave in morally questionable ways at least some of the time. However, the negative effects of those behaviors on individuals’ judgments of the character may be diminished in some instances. This study examined the effects of character motivation and outcome in a written narrative on character perceptions and moral disengagement. The findings of a 2 (motivation: altruistic, selfish) × 2 (outcome: positive, negative) experiment (N = 123) revealed that both motivation and outcome affect perceptions of the character's positive and negative attributes, character liking, and moral disengagement. Specifically, altruistic motivations and positive outcomes led to more favorable perceptions of a character's attributes, greater character liking, and more justification of the character's actions. Furthermore, moral disengagement mediated the effects of motivation and outcome on perceptions of characters' positive and negative attributes, and in turn positive attributes media...

Young children's understanding of “more” and discrimination of number and surface area.

Abstract: The psychology supporting the use of quantifier words (e.g., "some," "most," "more") is of interest to both scientists studying quantity representation (e.g., number, area) and to scientists and linguists studying the syntax and semantics of these terms. Understanding quantifiers requires both a mastery of the linguistic representations and a connection with cognitive representations of quantity. Some words (e.g., "many") refer to only a single dimension, whereas others, like the comparative "more," refer to comparison by numeric ("more dots") or nonnumeric dimensions ("more goo"). In the present work, we ask 2 questions. First, when do children begin to understand the word "more" as used to compare nonnumeric substances and collections of discrete objects? Second, what is the underlying psychophysical character of the cognitive representations children utilize to verify such sentences? We find that children can understand and verify sentences including "more goo" and "more dots" at around 3.3 years-younger than some previous studies have suggested-and that children employ the Approximate Number System and an Approximate Area System in verification. These systems share a common underlying format (i.e., Gaussian representations with scalar variability). The similarity in the age of onset we find for understanding "more" in number and area contexts, along with the similar psychophysical character we demonstrate for these underlying cognitive representations, suggests that children may learn "more" as a domain-neutral comparative term.

Recovering hidden Bloch character: Unfolding Electrons, Phonons, and Slabs

Abstract: P.B.A. was supported in part by US DOE Grant No. DE-FG02-08ER46550. D.A.C. thanks NSF for a summer REU scholarship administered by Stony Brook University (NSF Grant No. PHYS-0851594). J.M.S. was supported by Grants No. FIS2009-12721 and No. FIS2012-37549

Character-to-Character Sentiment Analysis in Shakespeare's Plays

Abstract: We present an automatic method for analyzing sentiment dynamics between characters in plays. This literary format’s structured dialogue allows us to make assumptions about who is participating in a conversation. Once we have an idea of who a character is speaking to, the sentiment in his or her speech can be attributed accordingly, allowing us to generate lists of a character’s enemies and allies as well as pinpoint scenes critical to a character’s emotional development. Results of experiments on Shakespeare’s plays are presented along with discussion of how this work can be extended to unstructured texts (i.e. novels).

Character Recognition Using Neural Network

Abstract: In the present paper, we are use the neural network to recognize the character. In this paper it is developed 0ff-line strategies for the isolated handwritten English character (A TO Z) and (0 to 9) .This method improves the character recognition method. Preprocessing of the Character is used binarization, thresolding and segmentation method .The proposed method is based on the use of feed forward back propagation method to classify the characters. The ANN is trained using the Back Propagation algorithm. In the proposed system, English nue-merical letter is represented by binary numbers that are used as input then they are fed to an ANN. Neural network followed by the Back Propagation Algorithm which compromises Training. Index Terms—Neural network, back propagation method Segmentation, image processing toolbox ,matlab .

Interactive partner control in close interactions for real-time applications

Abstract: This article presents a new framework for synthesizing motion of a virtual character in response to the actions performed by a user-controlled character in real time. In particular, the proposed method can handle scenes in which the characters are closely interacting with each other such as those in partner dancing and fighting. In such interactions, coordinating the virtual characters with the human player automatically is extremely difficult because the system has to predict the intention of the player character. In addition, the style variations from different users affect the accuracy in recognizing the movements of the player character when determining the responses of the virtual character. To solve these problems, our framework makes use of the spatial relationship-based representation of the body parts called interaction mesh, which has been proven effective for motion adaptation. The method is computationally efficient, enabling real-time character control for interactive applications. We demonstrate its effectiveness and versatility in synthesizing a wide variety of motions with close interactions.