Quantitative Analysis of Multi-Recovery-Based Intrusion Tolerance Model

Quantitative analysis has always been a difficult problem in security analysis of intrusion tolerance systems. An intrusion tolerance model based on multiple recovery mechanisms is introduced in this paper and how to quantify the security attributes of the model is proposed. A state transition model with recovery states more accurately describes the dynamic behavior of the system. Considering that recovery mechanisms have a great impact on the security performance of the system, we set up the cost models corresponding to different recovery mechanisms. We propose a feasible security measure based on mean cost to security failure in order to evaluate the system cost during the recovery phase. The experimental results confirmed the feasibility of the proposed methods.     

The Life-Cycle Model with Optimal Retiring Age and Simulation

In this paper, a life-cycle model with retirement is set up to study how an individual chooses the optimal retiring age on account of wage growth rate, longevity and healthy state. It is proved that there exists optimal retiring age under given conditions. The numerical simulations are given to show how wage growth rate, longevity and healthy state affect retiring age.     

Variable Selection via Generalized SELO-Penalized Cox Regression Models

The seamless-L_0(SELO) penalty is a smooth function that very closely resembles the L_0 penalty, which has been demonstrated theoretically and practically to be effective in nonconvex penalization for variable selection. In this paper, the authors first generalize the SELO penalty to a class of penalties retaining good features of SELO, and then develop variable selection and parameter estimation in Cox models using the proposed generalized SELO(GSELO) penalized log partial likelihood(PPL) approach. The authors show that the GSELO-PPL procedure possesses the oracle property with a diverging number of predictors under certain mild, interpretable regularity conditions. The entire path of GSELO-PPL estimates can be efficiently computed through a smoothing quasi-Newton(SQN) with continuation algorithm. The authors propose a consistent modified BIC(MBIC) tuning parameter selector for GSELO-PPL, and show that under some regularity conditions, the GSELOPPL-MBIC procedure consistently identifies the true model. Simulation studies and real data analysis are conducted to evaluate the finite sample performance of the proposed method.     

Community Work Research through Co-Operative Inquiry in Timor-Leste,Australia and Peru: Insights into Process

Co-operative inquiry is an under-explored method in community-based research. Its democratic approach involves a group of “co-researchers” collaboratively inquiring into a mutually-agreed research topic through systematic cycles of reflection and action. This article shares the process, outcomes, and methodological reflections of three co-operative inquiries that were conducted as part of an international study regarding love in community work. Groups of up to 10 community workers in rural villages in Timor-Leste, Australia, and Peru engaged in co-operative inquiry to collaboratively develop new knowledge to inform practice. The article analyses data regarding co-inquirer experiences of the methodology, and identifies the strengths and challenges of the co-operative inquiry method to support the collective generation of new knowledge. The article concludes that co-operative inquiry involves shared power, participation, action, and contextual reflexivity, and is a useful method for community workers to collaboratively develop innovative approaches to community work practice through cycles of reflection and action.     

The Convergence of Least-Squares Progressive Iterative Approximation for Singular Least-Squares Fitting System

Data fitting is an extensively employed modeling tool in geometric design. With the advent of the big data era, the data sets to be fitted are made larger and larger, leading to more and more leastsquares fitting systems with singular coefficient matrices. LSPIA (least-squares progressive iterative approximation) is an efficient iterative method for the least-squares fitting. However, the convergence of LSPIA for the singular least-squares fitting systems remains as an open problem. In this paper, the authors showed that LSPIA for the singular least-squares fitting systems is convergent. Moreover, in a special case, LSPIA converges to the Moore-Penrose (M-P) pseudo-inverse solution to the leastsquares fitting result of the data set. This property makes LSPIA, an iterative method with clear geometric meanings, robust in geometric modeling applications. In addition, the authors discussed some implementation detail of LSPIA, and presented an example to validate the convergence of LSPIA for the singular least-squares fitting systems.     

Prediction of end-use energy consumption in a region of Northwest China

End-use energy consumption can reflect the industrial development of a country and the living standards of its residents. The study of end-use energy consumption can provide a solid basis for industrial restructuring, energy saving, and emission reduction. In this paper, we analyzed the end-use energy consumption of a region in Northwestern China, and applied the Markov prediction method to forecast the future demand of different types of end-use energy. This provides a reference for the energy structure optimization in the Northwestern China.     

Free Information Flow Benefits Truth Seeking

How can we approach the truth in a society? It may depend on various factors. In this paper, using a well-established truth seeking model, the authors show that the persistent free information flow will bring us to the truth. Here the free information flow is modeled as the environmental random noise that could alter one's cognition. Without the random noise, the model predicts that the truth can only be captured by the truth seekers who own actively perceptive ability of the truth and their believers, while the other individuals may stick to falsehood. But under the influence of the random noise, the authors strictly prove that even there is only one truth seeker in the group, all individuals will finally approach the truth.     

Input-to-State Stability of Switched Nonlinear Delay Systems Based on a Novel Lyapunov-Krasovskii Functional Method

In this paper, the input-to-state stability (ISS) analysis is addressed for switched nonlinear delay systems. By introducing a novel Lyapunov-Krasovskii functional with indefinite derivative and the merging switching signal techniques, some new criteria are established for switched nonlinear delay systems under asynchronous switching, which extends the existing results to the nonlinear systems with switching rules and delays. The ISS problem is also considered under synchronous switching for switched nonlinear systems by employing the similar techniques. Finally, a nonlinear delay model is provided to show the effectiveness of the proposed results.     

Systemic Thinking and Practice Toward Facilitating Inclusive Education: Reflections on a Case of Co-Generated Knowledge and Action in South Africa

This article offers our reflections around a case of facilitating systemic thinking and practice in which the first author of the article (Tlale) interacted with research participants/participant researchers with the intention of strengthening systemic thought and action toward fostering inclusive education in the setting (a rural school in the Eastern Cape in South Africa). We reflect upon the process and also how our engagement was perceived by participants, as expressed in feedback received from them. We point to how Tlale introduced the idea of systemic thinking (to teachers, school management team, school governing body, and a district officer for the district) as tied to the possibility of acting to generate transformation toward a more inclusive educational context for the benefit of the learners at the school in question, thus acting as a systemic mediator on their behalf.