组织中的规则行为：合法性、个体差异的认同-内化作用

This study employed the compliance, identification, and internalization model of attitude change to explore the mechanism of rule-following behaviors in organizations. The objectives of this study were to examine the effects of individual utilitarianism and formalism on rule compliance, deference and rule-breaking behaviors, and the relationships between legitimacy, organizational identification, and value internalization. I surveyed 262 employees from a high-tech corporation in Beijing. After Confirmative Factor Analysis, Regression Analysis, and Structural Equation Modeling, I summarized main conclusions as follow. First, rule legitimacy and organizational identification have different effects on different rule behaviors. Perceived rule legitimacy and organizational identification have direct positive effect on rule deference. But the effects of legitimacy on rule-compliance and rule-breaking are moderated by organizational identification and value internalization. Only under high identification or value congruence with organization, could legitimacy perception predict rule compliance and breaking. Second, individual formalism (IF) has positive effect on rule compliance. IF’s positive effect on rule deference only appear under high value congruence between individuals and organization. Third, organizational identification works as a “valve” in the relationship between individual viewpoints and rule-breaking. Organizational identification turns off the tendency of utilitarianism to break rules, and turns on the tendency of formalism to inhibit rule-breaking. Forth, attitudinal and behavioral facets of utilitarianism and formalism have different influences on rule-following behaviors. Only individuals who are both attitudinal and behavioral formalists show deference to rules, while formalism as behavioral tendency predicts less rule-breaking. Fifth, innovation behaviors coexist independently with compliance and deference to rules. But the division between innovation and rule-breaking is obscure. Organizational identification facilitate both rule following and innovation. Sixth, women comply with rules more than men do, while men break more rules than women do. More aged people develop deeper identification with their organizations, and higher deference to rules. Individuals with higher education are fewer formalists, and accordingly defer to rules less and break more.

Identification of nonlinear dynamic systems: Time-frequency filtering and skeleton curves

The nonlinear behavior varying with the instantaneous response was analyzed through the joint time-frequency analysis method for a class of S. D. O. F nonlinear system. A masking operator an definite regions is defined and two theorems are presented. Based on these, the nonlinear system is modeled with a special time-varying linear one, called the generalized skeleton linear system (GSLS). The frequency skeleton curve and the damping skeleton curve are defined to describe the main feature of the non-linearity as well. Moreover, an identification method is proposed through the skeleton curves and the time-frequency filtering technique.

An Amino Acid Substitution Matrix for Protein Conformation Identification

Amino acid substitution matrices play an essential role in protein sequence alignment, a fundamental task in bioinformatics. Most widely used matrices, such as PAM matrices derived from homologous sequences and BLOSUM matrices derived from aligned segments of PROSITE, did not integrate conformation information in their construction. There are a few structure-based matrices, which are derived from limited data of structure alignment. Using databases PDB_SELECT and DSSP, we create a database of sequence-conformation blocks which explicitly represent sequence-structure relationship. Members in a block are identical in conformation and are highly similar in sequence. From this block database, we derive a conformation-specific amino acid substitution matrix CBSM60. The matrix shows an improved performance in conformational segment search and homolog detection.

Identification of Nonlinear Systems Through Time-Frequency Filtering Technique

In the previous paper, a class of nonlinear system is mapped to a so-called skeleton linear model (SLM) based on the joint time-frequency analysis method. Behavior of the nonlinear system may be indicated quantitatively by the variance of the coefficients of SLM versus its response. Using this model we propose an identification method for nonlinear systems based on nonstationary vibration data in this paper. The key technique in the identification procedure is a time-frequency filtering method by which solution of the SLM is extracted from the response data of the corresponding nonlinear system. Two time-frequency filtering methods are discussed here. One is based on the quadratic time-frequency distribution and its inverse transform, the other is based on the quadratic time-frequency distribution and the wavelet transform. Both numerical examples and an experimental application are given to illustrate the validity of the technique.

Some advances in study of crack identification problems

In the present paper, the crack identification problems are investigated. This kind of problems belong to the scope of inverse problems and are usually ill-posed on their solutions. The paper includes two parts: (1) Based on the dynamic BIEM and the optimization method and using the measured dynamic information on outer boundary, the identification of crack in a finite domain is investigated and a method for choosing the high sensitive frequency region is proposed successfully to improve the precision. (2) Based on 3-D static BIEM and hypersingular integral equation theory, the penny crack identification in a finite body is reduced to an optimization problem. The investigation gives us some initial understanding on the 3-D inverse problems.