Bethe Ansatz and thermodynamic limit of affine quantum group invariant extensions of the t-J modelAbstract. Several alternative dichotomous Item Response Theory (IRT) models have been introduced to account for guessing effect in multiple-choice assessment. The guessing effect in these models has been considered to be itemrelated. In the most classic case, pseudo-guessing in the three-parameter logistic IRT model is modeled to be the same for all the subjects but may vary across items. This is not realistic because subjects can guess worse or better than the pseudo-guessing. Derivation from the three-parameter logistic IRT model improves the situation by incorporating ability in guessing. However, it does not model non-monotone function. This paper proposes to study guessing from a subjectrelated aspect which is guessing test-taking behavior. Mixture Rasch model is employed to detect latent groups. A hybrid of mixture Rasch and 3-parameter logistic IRT model is proposed to model the behavior based guessing from the subjects' ways of responding the items. The subjects are assumed to simply choose a response at random. An information criterion is proposed to identify the behavior based guessing group. Results show that the proposed model selection criterion provides a promising method to identify the guessing group modeled by the hybrid model.

A psycho-technology approach to discouraging guessing in multiple-choice formatted item can be done through reducing the a priori guessing probability of an item. This study proposes a psychometrics framework of Item Response Theory (IRT) to model the effect of having various priori guessing probabilities across different items. A prior guessing parameter is proposed to serves as a moderator of the ability parameter in the two parameter logistic IRT. The results show that the proposed prior guessing parameter successfully moderates the ability parameters of the subjects with different degrees of guessing. However, the prior guessing parameter is insensitive when the performance pattern is mixed within the testlet but similar across testlet with different priori guessing probabilities

This paper considers three crucial issues in processing scaled down image, the representation of partial image, similarity measure and domain adaptation. Two Gaussian mixture model based algorithms are proposed to effectively preserve image details and avoids image degradation. Multiple partial images are clustered separately through Gaussian mixture model clustering with a scan and select procedure to enhance the inclusion of small image details. The local image features, represented by maximum likelihood estimates of the mixture components, are classified by using the modified Bayes factor (MBF) as a similarity measure. The detection of novel local features from MBF will suggest domain adaptation, which is changing the number of components of the Gaussian mixture model. The performance of the proposed algorithms are evaluated with simulated data and real images and it is shown to perform much better than existing Gaussian mixture model based algorithms in reproducing images with higher structural similarity index.

Owner satisfaction is one of the most important tools for evaluating and improving housing developer performance and government housing policies. The quality of government low-cost housing projects must be monitored, and data on owner satisfaction can assist. Owner satisfaction in low-cost housing, on the other hand, has been studied primarily in public lowcost flats. The purpose of this study was to investigate the factors that influence owner satisfaction in low-cost terrace housing. 806 questionnaires were distributed, and 403 completed questionnaires were collected from the study's target respondents. Five low-cost terrace housing areas in three regions of Sarawak were surveyed. Multiple regression analysis was used to investigate the factors that contribute to owner satisfaction. The findings show that in all three regions, homeownership, housing policies of developers, and house quality are the three key elements that have a substantial impact on owner satisfaction. In the Southern and Northern Regions, developer housing policies are a major determinant in owner satisfaction, whereas in the Central Region, homeownership is important. Only in the Central Region does the social environment component considerably influence owner satisfaction. Surprisingly, in the Northern Region, the cost of the home does not much affect how satisfied the owners are with their homes. This study was restricted to Sarawak means that it might not be applicable to other regions. To validate the results, additional research is needed in other geographic locations or with different home designs.