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This research aims to develop the Korean handwriting recognition method with the help of Backpropagation Neural Network Learning Method, apply the method to the evaluation system, and improve the problems derived from the multiple choice type test. When the short written answers were scored, every syllable was divided into graphemes and strokes were extracted. Extracted strokes were presented according to the probability of their appearance, and then trained with six Type Recognition Neural Network. They were trained and recognized again with the specific neural network. After trained by PE92, the certified DB, and recognized by using the result of the subjective answers, the recognition ratio was 79.2%. This ratio is higher than the ratio in previous research.
Performance management has been emphasized as a critical factor to increase efficiency in both private and public sector. But methodological progress is somewhat slow especially in the field of performance indicators. This study shows drawbacks in performance indicators in the public sector and suggests improvement alternatives. For this purpose, this study examines several cases in government mintistries and agencies. These cases retain common features that most public organizations have. Most of all, performance management must be led by strategic allignment and priority-setting. Departmental or individual evaluation must not be over-emphasized. Performance indicators are to be as specific and simple as can be. Performance evaluation should work as an Incentive system and must be considered as fair by every individual in the organization.