Using the ‘Engagement’ Model of Problem Solving to Assist Students in Capstone Learning

The engagement model for problem solving was developed as a response to soft systems methodology being difficult to implement in certain circumstances. In the years since the original paper was published, the model has developed into an iterative problem solving approach for the assessment, creation and implementation of new ideas in difficult problem situations. This case study paper exemplifies the kind of work undertaken through the use of the model and provides a practical scenario for how one might apply it. The case study takes place in a higher education environment and relates to the development of a capstone course for management majors. The paper concludes with suggestions for future research.     

Liquidity dynamics around intraday price jumps in Chinese stock market

Using 4128 single jumps detected from high frequency data of 220 individual stocks in SZ300P index, this paper investigates the liquidity dynamics around price jumps in Chinese market. Some interesting empirical results are obtained and the corresponding explanations are given. The frequency of positive jumps is quite higher than that of negative jumps. The trading volumes and average trade sizes are all in a high level around positive jumps. The relatively low liquidities around negative jumps show that negative jumps may be generated and enlarged by poor liquidity provision. The price reversal after price jumps is significant, and price reversal lasts longer after positive jumps. Moreover, the size and direction of jumps are significantly correlated with the returns and trades in the post-jump trading time. These findings are believed to be associated with the high proportion of retail investors and their herding behavior for price trend chasing.     

The distributed representation for societal risk classification toward BBS posts

The risk classification of BBS posts is important to the evaluation of societal risk level within a period. Using the posts collected from Tianya forum as the data source, the authors adopted the societal risk indicators from socio psychology, and conduct document-level multiple societal risk classification of BBS posts. To effectively capture the semantics and word order of documents, a shallow neural network as Paragraph Vector is applied to realize the distributed vector representations of the posts in the vector space. Based on the document vectors, the authors apply one classification method KNN to identify the societal risk category of the posts. The experimental results reveal that paragraph vector in document-level societal risk classification achieves much faster training speed and at least 10% improvements of F-measures than Bag-of-Words. Furthermore, the performance of paragraph vector is also superior to edit distance and Lucene-based search method. The present work is the first attempt of combining document embedding method with socio psychology research results to public opinions area.     

Positive observer design for positive Markovian jump systems with partly known transition rates

The paper is concerned with positive observer design for positive Markovian jump systems with partly known transition rates. By applying a linear co-positive type Lyapunov-Krasovskii function, a sufficient condition is proposed to ensure the stochastic stability of the error positive system and the existence of the positive observer, which is computed in linear programming. Finally, an example is given to demonstrate the validity of the main results.     

The generalized Serre problem over <Emphasis Type="Italic">K</Emphasis>-Hermite rings

This paper investigates the completion and the zero prime factorization for matrices over a K-Hermite ring. The authors have generalized Kaplansky’s related results, solved similar Lin-Bose problem and generalized Serre problem over a K-Hermite ring.     

Maximum likelihood estimator of the parameter for a continuous one-parameter exponential family under the optimal ranked set sampling

This paper studies a maximum likelihood estimator (MLE) of the parameter for a continuous one-parameter exponential family under ranked set sampling (RSS). The authors first find the optimal RSS according to the character of the family, viz, arrange the RSS based on quasi complete and sufficient statistic of independent and identically distributed (iid) samples. Then under this RSS, some sufficient conditions for the existence and uniqueness of the MLE, which are easily used in practice, are obtained. Using these conditions, the existence and uniqueness of the MLEs of the parameters for some usual distributions in this family are proved. Numerical simulations for these distributions fully support the result from the above two step optimizations of the sampling and the estimation method.     

Advance selling in the presence of product diffusion effect

Product diffusion refers to the phenomenon that the later demand is dependent on the early sales. To investigate how a firm’s advance selling strategy is affected by the effect of product diffusion, we consider a monopolist seller who sells a fashionable product in a market that comprises of myopic and strategic consumers over two periods (i.e., the advance selling season and the regular selling season). For a linear product diffusion effect we find that, when the effect of product diffusion is positive, the seller may set an extremely high advance selling price to induce the strategic consumers to purchase in the regular selling season, which is counter-intuitive. Moreover, the optimal procurement quantity for the seller may increase in the negative effect of product diffusion and decrease in the amount of strategic consumers. When we extend our model to consider a concave quadratic product diffusion effect, however, the optimal procurement quantity is concave in the amount of strategic consumers. Numerical studies are further presented to discuss the managerial insights.     

Which is the use of systems theory in literature analysis?: The discovery of the place in La Mancha in Don Quixote

The use of systems theory to attempt to determine which ''place in La Mancha'' was the one whose name Cervantes could not quite recall in his universal novel, appears to be ordained to change certain attitudes towards science held in Cervantine literature. The reason: after four centuries of literary analysis, systemic methodology has proven able to identify the famous ''place'' with acceptable accuracy. Nonetheless, certain reasonable doubts persist around the suitability of a strictly scientific analysis of literature. In light of those doubts, the present article aims primarily to facilitate critique both of the systemic approach adopted and its outcome.