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    Item type:Publication,
    Thai legal practitioners’ knowledge management: Communications skills, professionalism, and competency as the antecedents for success
    (2018-01-01)
    Teeranantawanich, Cherdsak
    ;
    Phimolsathien, Thepparat
    The purpose of this research was to examine the variables contributing to Thai legal practitioners’ knowledge management abilities. By means of simple random-sampling, the sample of 332 individuals was surveyed using the 72-item, 7-level, Likert type agreement scale questionnaire on the study’s four constructs. Confirmatory factor analysis was run prior to the structural equation model, with the analysis undertaken in LISREL 9.1. All causal factors in the model were shown to have a positive influence on knowledge management, with 92% variance of the factor affecting knowledge management (KM) (R2). Ranked in importance were communications skills (CSK), competency (COMP), and professionalism (PRO), with the total mean score of 0.96, 0.43, and 0.34, respectively.
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    Thai handwriting legal amounts recognition
    (2003-01-01)
    Chatwiriya, W.
    ;
    Klinkhachorn, P.
    ;
    Lass, N.
    A legal amount, or the word amount, is defined as the expression of a numerical value into words. It is used mostly in monetary documents. Thai legal amounts consist of a set of 17 words of 25 characters. This paper's objective is to develop a system to recognize Thai handwriting legal amounts. The strategies to improve the character recognition rates at the preprocessing and recognition process are discussed including the division of input characters into smaller subgroups: the body and high characters group, using multiple feature combinations and using the classifiers that give answers as a list of possible answers with scores. And at the post processes, we improved overall recognition rate using prior knowledge such as lexicon and syntax. We proposed the concept of partial lexicon matching mainly relying on the recognition results of the body group characters. The syntax verification algorithms are based on the sequences of word types, the joining between word types, and special rules for specific words. Irregular handwriting, i.e., touching and broken characters, are detected. Also holistic word recognition is employed to recognize these characters without explicit character segmentation.