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.     

Building Organizational Identity: an Insider Action Research from a Founder’s Viewpoint

This paper features the implementation of an extensive insider action research, exhaustively following the framework of Coghlan and Brannick (2010, 2014). It consisted of two action research projects - the thesis action research and the core action research - which were done in a parallel manner, both following the iterative cycles of constructing, planning, taking, and evaluating action. The thesis action research was aimed at developing a theory on building organizational identity from the viewpoint of an organizational founder. On the other hand, the core action research was focused on promoting the specific identity of the Institute for Integrality, Inc. Quality and rigor were observed in the implementation of the action research cycles. In the fieldwork, there were three main cycles undertaken – understanding organizational identity, fine-tuning the practice of this identity, and designing the integration of this identity in organizational culture. Thereafter, significant learnings were derived from meta-learning in the form of content, process, and premise reflections. Finally, through the critical reflection of the project in the light of the experience and theory, A-Founder’s Integrative Theory of Organizational Identity Building was derived.     

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.     

Backstepping approach to the adaptive regulator design for a one-dimensional wave equation with general input harmonic disturbance

This paper considers the parameter estimation and stabilization of an unstable one-dimensional wave equation with matched general harmonic disturbance at the controlled end. The backstepping method for infinite-dimensional system is adopted in the design of the adaptive regulator. It is shown that the resulting closed-loop system is asymptotically stable. Meanwhile, the estimated parameter is shown to be convergent to the unknown parameter as time goes to infinity.     

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.     

Bell state preparation based on switching between quantum system models

For the preparation of any target Bell state under continuous quantum measurement, this paper proposes a method which achieves the control objective by switching between two different models or by switching between two control channels under one model. Proper control Hamiltonians are selected for the two system models, a switching strategy between the two models is designed, and the stability of the whole switching system is proved in theory. For a given target Bell state, the effectiveness of the proposed switching control strategy between different models is illustrated through simulation experiments.     

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.     

Fairness of extra-gain guilty in performance of supply chain and contract design

Considering a one-supplier and two-retailer supply chain setting in which the supplier makes contacts with retailers in sequence based on FCFS(first–come–first-service) principle, the authors investigate the marginal effect of extra-gain guilty fairness concerns of supply chain members on the contract design, supply chain's profit and profit distribution. When the supplier considers distributional fairness of loss aversion and extra-gain guilty, extra-gain guilty concern reduces the optimal wholesale and retail price, and improves supply chain performance. When the first or the second retailer considers distributional fairness and peer-induced fairness, extra-gain guilty concerns decrease the optimal wholesale and retail price but increase the profit of all supply chain members only when the level of loss aversion is large enough and the level of extra-gain guilty is less than 1/2. However, when the level of loss aversion is small and the level of extra-gain guilty is less than 1/2, extra-gain guilty has no influence on supply chain performance. The analysis reveals that the supply chain performance can be further improved by considering fairness of extra-gain guilty.     

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.     

Performance comparison of distributed state estimation algorithms for power systems

A newly proposed distributed dynamic state estimation algorithm based on the maximum a posteriori (MAP) technique is generalised and studied for power systems. The system model involves linear time-varying load dynamics and nonlinear measurements. The main contribution of this paper is to compare the performance and feasibility of this distributed algorithm with several existing distributed state estimation algorithms in the literature. Simulations are tested on the IEEE 39-bus and 118-bus systems under various operating conditions. The results show that this distributed algorithm performs better than distributed quasi-steady state estimation algorithms which do not use the load dynamic model. The results also show that the performance of this distributed method is very close to that by the centralized state estimation method. The merits of this algorithm over the centralized method lie in its low computational complexity and low communication load. Hence, the analysis supports the efficiency and benefits of the distributed algorithm in applications to large-scale power systems.