Systemic Development of Leadership: Action Research in an Indian Manufacturing Organization

This insider action research study differentiates between developing leaders and leadership, evolves a systemic leadership model, and intervenes on the human, social and processes dimensions for developing leadership. This is a real-time study and responds to the organizational reality of fast pace of change and its systemic nature. Consequently, the research too is fast to guide actions and influence positive changes in the organization. As the action research addresses a systemic reality, research and contributions are in multiple aspects, with new techniques having huge implications for theory building as well as improving practice. The study provides a structural solution to perceived lack of commitment in senior colleagues—a syndrome I acronym as HILE (High Intentions and Lukewarm Execution)–by re-designing organizational processes and making time available for its effective utilization in developing leadership. A new technique of triggering major changes in organizations termed “concept sublimation” distils concept from the statements of major stakeholder and sublimates it from lower to higher unit of analysis and to higher levels of positivity. Statistical simplification of a competency framework by applying concepts from Euclidian geometry and making it effective is yet a unique contribution of this action research study. The study adapts the competing values framework in developing a method of assessing cultural congruence of a candidate with the culture of the organization. The uniqueness of the study lies in bridging the gap in the literature by actually and systemically developing leadership in an organization and providing pragmatic insights on developing leadership while also creating knowledge for theory building.     

Operationalising “Double-Loop” Learning in Service Organisations: A Systems Approach for Creating Knowledge

Learning organisation literature has widely discussed the connections between “double-loop” learning and its significance to organisational performance, but paying little attention to tools and systems that can operationalise “double-loop” learning in organisations. This paper investigates the impact of applying a systems approach for service operations design, expressed as the Vanguard Method (Seddon, Freedom from command and control: a better way to make the work work, 2003), in order to activate “double-loop” learning in service organisations. Two case studies were conducted in the banking mortgage operations and adults’ social care services in the UK, using the dimensions of the learning organisation questionnaire (DLOQ), semi-structured interviews, observations, and documents. The findings of the cross-case analysis support the link of applying the Vanguard Method with operationalising “double-loop” learning through three main factors, namely systematic-operations improvement, organisational capacity development, and outside-in mode of work; that are all embedded into the seven dimensions of the DLOQ. The value of this paper is the introduction of a service operations design tool that can activate “double-loop” learning performance in the fast changing knowledge era. It also provides an impetus for service organisations to creatively influence employees’ competencies to effectively improve internal systems.     

An Analysis of an SIRS Epidemic Model with General Direct Immunization in Networks北大核心CSCD

We consider an SIRS epidemic model with a general direct immunization rate on networks. By constructing suitable Lyapunov functions, we find that the dynamical behvaior of the model is completely determined by the epidemic threshold λc. When λ≤λc, the disease-free equilibrium is globally asymptotically stable; when λ>λc, the endemic equilibrium is globally asymptotically stable. In addition, we propose a uniform direct immunization and a targeted direct immunization. The results show that under the same average immunization rate s there exists a critical immunization-lost rate δc so that the epidemic threshold of the targeted direct immunization is smaller (larger) than that of the uniform direct immunization if δ<δc(δ>δc). © 2017, The Journal of Agency of Complex Systems and Complexity Science. All right reserved.     

Parallel Optimization of the Crystal-KMC on Tianhe-2

The Kinetic Monte Carlo(KMC) is one of the commonly used methods for simulating radiation damage of materials. Our team develops a parallel KMC software named Crystal-KMC, which supports the Embedded Atom Method(EAM) potential energy and utilizes the Message Passing Interface(MPI) technology to simulate the vacancy transition of the Copper(Cu) element under neutron radiation. To make better use of the computing power of modern supercomputers, we develop the parallel efficiency optimization model for the Crystal-KMC on Tianhe-2, to achieve a larger simulation of the damage process of materials under irradiation environment. Firstly, we analyze the performance bottleneck of the Crystal-KMC software and use the MIC offload statement to implement the operation of key modules of the software on the MIC coprocessor. We use Open MP to develop parallel optimization for the Crystal-KMC, combined with existing MPI inter-process communication optimization, finally achieving hybrid parallel optimization. The experimental results show that in the single-node CPU and MIC collaborative parallel mode, the speedup of the calculation hotspot reaches 30.1, and the speedup of the overall software reaches 7.43.     

COMPARISON OF TWO METHODS OF OPERATING THEATRE PLANNING： APPLICATION IN BELGIAN HOSPITAL

Operating Theatre is the centre of the hospital management＇s efforts. It constitutes the most expensive sector with more than 10% of the intended operating budget of the hospital. To reduce the costs while maintaining a good quality of care, one of the solutions is to improve the existent planning and scheduling methods by improving the services and surgical specialty coordination or finding the best estimation of surgical case durations. The other solution is to construct an effective surgical case plan and schedule. The operating theatre planning and scheduling is the two important steps, which aim to make a surgical case programming with an objective of obtaining a realizable and efficient surgical case schedule. This paper focuses on the first step, the operating theatre planning problem. Two planning methods are introduced and compared. Real data of a Belgian university hospital ＂Tivoli＂ are used for the experiments.     

An improved branch-and-bound algorithm to minimize the weighted flowtime on identical parallel machines with family setup times

This article investigates identical parallel machines scheduling with family setup times. The objective function being the weighted sum of completion times, the problem is known to be strongly NP-hard. We propose a constructive heuristic algorithm and three complementary lower bounds. Two of these bounds proceed by elimination of setup times or by distributing each of them to jobs of the corresponding family, while the third one is based on a lagrangian relaxation. The bounds and the heuristic are incorporated into a branch-and-bound algorithm. Experimental results obtained outperform those of the methods presented in previous works, in term of size of solved problems.     

Comparison between several satellite constellation schemes for MEO-TDRSS of China

The satellite constellation classes, which are suitable for the medium earth orbit tracking and data relay satellite system （MEO-TDRSS） of China, are investigated. On the basis of the functionality and the traffic distribution characteristic of MEO-TDRSS, the coverage performance and inter-satellite link properties of four different constellation schemes are compared by simulations. Simulation results indicate that the rosette and common-track constellations, whose satellites are distributed on the celestial sphere more uniformly, are appropriate for the implementation of MEO-TDRSS of China.     

Multiple targets vector miss distance measurement accuracy based on 2-D assignment algorithms

An extension of 2-D assignment approach is proposed for measurement-to-target association for improving multiple targets vector miss distance measurement accuracy. When the multiple targets move so closely, the measurements can not be fully resolved due to finite resolution. The proposed method adopts an auction algorithm to compute the feasible measurement-to-target assignment with unresolved measurements for solving this 2-D assignment problem. Computer simulation results demonstrate the effectiveness and feasibility of this method.     

Interval Time Series Analysis with an Application to the Sterling-Dollar Exchange Rate

Traditional econometrics has long employed ＂points＂ to measure time series data. In real life situations, however, it suffers the loss of volatility information, since many variables are bounded by intervals in a given period. To address this issue, this paper provides a new methodology for interval time series analysis. The concept of ＂interval stochastic process＂ is formally defined as a counterpart of ＂stochastic process＂ in point-based econometrics. The authors introduce the concepts of interval stationarity, interval statistics （including interval mean, interval variance, etc.） and propose an interval linear model to investigate the dynamic relationships between interval processes. A new interval-based optimization approach for estimation is proposed, and corresponding evaluation criteria are derived. To demonstrate that the new interval method provides valid results, an empirical example on the sterling-dollar exchange rate is presented.     

Designing a Hybrid Intelligent Mining System for Credit Risk Evaluation

In this study, a novel hybrid intelligent mining system integrating rough sets theory and support vector machines is developed to extract efficiently association rules from original information table for credit risk evaluation and analysis. In the proposed hybrid intelligent system, support vector machines are used as a tool to extract typical features and filter its noise, which are different from the previous studies where rough sets were only used as a preprocessor for support vector machines. Such an approach could reduce the information table and generate the final knowledge from the reduced information table by rough sets. Therefore, the proposed hybrid intelligent system overcomes the difficulty of extracting rules from a trained support vector machine classifier and possesses the robustness which is lacking for rough-set-based approaches. In addition, the effectiveness of the proposed hybrid intelligent system is illustrated with two real-world credit datasets.