Author’s reply

This note answers issues raised in Wang and Zhu (2009) [2] regarding the experimental results obtained in Ikhouane and Gomis-Bellmunt (2008) [1].     

NASA Langley’s approach to the Sandia’s structural dynamics challenge problem

The objective of this challenge is to develop a data-based probabilistic model of uncertainty to predict the acceleration response of subsystems (payloads) by themselves and while coupled to a primary (target) system. Although deterministic analyses of this type are routinely performed and representative of issues faced in real-world system design and integration, there are still several key technical challenges that must be addressed when analyzing the uncertainties of interconnected systems. For example, one key technical challenge is related to the fact that there is limited data on the target configurations. Also, while multiple data sets from experiments conducted at the subsystem level are provided, samples sizes are not sufficient to compute high confidence statistics. Moreover, in this challenge problem, additional constraints, in the form of ground rules, have been added. One such constraint is that mathematical models of the subsystem are limited to linear approximations of the nonlinear physics of the problem at hand. Also, participants are constrained to use these subsystem models and the multiple data sets to make predictions about the target system response under completely different forcing functions.Initially, our approach involved the screening of several different methods to arrive at the three presented herein. The first one is based on a transformation of the structural dynamic data in the modal domain to an orthogonal space where the mean and covariance of the data are matched. The other two approaches worked solutions in physical space where the uncertain parameter set is made of masses, stiffnessess, and damping coefficients; one matches the confidence intervals of low order moments of the statistics via optimization while the second one uses a Kernel density estimation approach. The paper will touch on the approaches, lessons learned, validation metrics and their comparison, data quantity restriction, and assumptions/limitations of each approach.     

Fuzzy rule-based analysis of firm’s technology transfer in Taiwan’s machinery industry

In the face of speedy revolution of high technology, the advanced technology becomes one of the key drivers to enhance productivity in a firm or even in a country. In order to compete in the global environment, the ability and effectiveness of acquiring new technology are essential for firms, especially for the traditional machinery industry. In Taiwan, the societal structure is built on the foundation of Small-Medium Enterprises (SMEs). Thus most new technologies need and depend on the technology transfer (TT) from international firms and research institutes. Due to the complicity of influential factors of TT, such as industrial feature (IF), organizational feature (OF), personnel feature (PF) and technological feature (TF), difficulties are encountered in evaluating the effectiveness of TT. This study develops a rule-based decision support mechanism using fuzzy set theory and the method of Analytic Hierarchy Process (AHP) to evaluate the effectiveness of TT. Also, a statistic analysis (Statistics Package for Social Science, SPSS) is adopted to confirm the results of fuzzy AHP analysis. This study finds that prior successful TT experience, workers’ positive attitude, proper authorization, and more codification exist in a novel technology are highly influential. Those factors are important in concern when a firm launching TT. Furthermore, firms’ age and personnel educational background are regardless.     

Experimental analysis of self-organizing team’s behaviors

This paper is focused on the study of self-organizing team’s behaviors which are dependent on the interaction rules and the decision factors of team members. The self-organizing team’s behavior means that team members work unconditionally with one of the three work attitudes (diligence, average, and shirking). A small-world network is suggested as the basic relationships of team members. Different from the traditional models, Reciprocators encourage their friends if they work diligently and punish them if they shirk work. It is supposed that team member’s decision of choosing work attitude depends on four decision factors, humanity, herd instinct, rationality, and follower tendency. Firstly, all of the four decision factors’ weights are supposed as 0.25. Multiple experiments were conducted to analyze the behavior of a team by a multi-agent experiment system. It is found that, in order to increase the fraction of diligent team members, different strategies should be used under different Reciprocators’ fractions. Increasing Reciprocators’ fraction is beneficial to the increase of diligent members; however, the increase rate will slow down after an inflexion (here it means the inflexion of Reciprocators’ fraction). After the previous experiments study, extended experiments were developed to work on the influence of the four factors’ different weights. A self-adaptive algorithm is suggested to achieve the four decision factors’ weights. The results of self-adaptive algorithm have different influences on the team’s behaviors under different fractions of Reciprocators. Finally, influences of members’ different relationships are studied by other experiments. It is also proved that the fraction of diligent members is not dependent on the structure of team members’ relationships. The results demonstrate that the self-organizing team’s behavior can be significantly influenced by its scenario while managing a self-organizing team.     

An oracle builder’s toolkit

We show how to use various notions of genericity as tools in oracle creation. In particular,

1. we give an abstract definition of genericity that encompasses a large collection of different generic notions;

2. we consider a new complexity class AWPP, which contains BQP (quantum polynomial time), and infer several strong collapses relative to -generics;

3. we show that under additional assumptions these collapses also occur relative to Cohen generics;

4. we show that relative to -generics, ULIN∩co-ULINDTIME(n^k) for any k, where ULIN is unambiguous linear time, despite the fact that UP(NP∩co-NP)P relative to these generics;

5. we show that there is an oracle relative to which NP/1∩co-NP/1(NP∩co-NP)/poly; and

6. we use a specialized notion of genericity to create an oracle relative to which

NP^BPPMA.

The Internet’s impact on sexuality: A critical review of 15 years of research

The body of empirical research on Internet sexuality has grown steadily since 1993. The following paper provides an overview of the current state of research in this field in its full thematic breadth, addressing six areas of online sexuality: Pornography, sex shops, sex work, sex education, sex contacts, and sexual subcultures. Key research results are presented concerning Internet sexuality’s forms of manifestation, participant groups, opportunities, and risks. This paper shows that sexually related online activities have become routine in recent years for large segments of the population in the Western world. Internet sexuality also takes somewhat different forms based on the age, gender, and sexual orientation of the individual. Academic studies to date have focused overwhelmingly on the possible negative effects of Internet sexuality. By contrast, little research has been conducted on potential benefits. Consequently, a surprising number of gaps are evident in the scholarship on Internet sexuality.     

Identrus system gets under way with Deutsche Bank’s pilot programme

Deutsche Bank, one of the world’s major financial institutions, has successfully piloted its first Identrus-based application – electronic bill presentment and payment – in Singapore.     

An adaptive neuro-fuzzy model for prediction of student’s academic performance

This paper introduces a systematic approach for the design of a fuzzy inference system based on a class of neural networks to assess the students’ academic performance. Fuzzy systems have reached a recognized success in several applications to solve diverse class of problems. Currently, there is an increasing trend to expand them with learning and adaptation capabilities through combinations with other techniques. Fuzzy systems-neural networks and fuzzy systems-genetic algorithms are the most successful applications of soft computing techniques with hybrid characteristics and learning capabilities. The developed method uses a fuzzy system augmented by neural networks to enhance some of its characteristics like flexibility, speed, and adaptability, which is called the adaptive neuro-fuzzy inference system (ANFIS). New trends in soft computing techniques, their applications, model development of fuzzy systems, integration, hybridization and adaptation are also introduced. The parameters set to facilitate the hybrid learning rules for the constitution of the Sugeno-type ANFIS architecture is then elaborated. The method can produce crisp numerical outcomes to predict the student’s academic performance (SAP). It also provides an alternative solution to deal with imprecise data. The results of the ANFIS model are as robust as those of the statistical methods, yet they encourage a more natural way to interpret the student’s outcomes.     

An N-player prisoner’s dilemma in a robotic ecosystem

The iterated prisoner’s dilemma (iPD) in its standard form is a very well-known popular basis for research on cooperation. Here, a significant generalization of the iPD is presented in the form of an N-player game, instead of only two players, with continuous degrees of cooperation, instead of binary cooperation or defection. This continuous N-player PD (CN-PD) is motivated and explained by an actual experimental set-up in the form of an artificial ecosystem including mobile robots. Furthermore, the novel strategy of the so-called Justified-Snobism (JS) is introduced, which tries to cooperate slightly more than the average of the group of players. Results from sets of experiments with N=20 are presented that indicate that JS is indeed a successful strategy in the CN-PD.     

Multi-objective genetic local search algorithm using Kohonen’s neural map

Genetic Algorithms (GAs) are population based global search methods that can escape from local optima traps and find the global optima regions. However, near the optimum set their intensification process is often inaccurate. This is because the search strategy of GAs is completely probabilistic. With a random search near the optimum sets, there is a small probability to improve current solution. Another drawback of the GAs is genetic drift. The GAs search process is a black box process and no one knows that which region is being searched by the algorithm and it is possible that GAs search only a small region in the feasible space. On the other hand, GAs usually do not use the existing information about the optimality regions in past iterations.In this paper, a new method called SOM-Based Multi-Objective GA (SBMOGA) is proposed to improve the genetic diversity. In SBMOGA, a grid of neurons use the concept of learning rule of Self-Organizing Map (SOM) supporting by Variable Neighborhood Search (VNS) learn from genetic algorithm improving both local and global search. SOM is a neural network which is capable of learning and can improve the efficiency of data processing algorithms. The VNS algorithm is developed to enhance the local search efficiency in the Evolutionary Algorithms (EAs). The SOM uses a multi-objective learning rule based-on Pareto dominance to train its neurons. The neurons gradually move toward better fitness areas in some trajectories in feasible space. The knowledge of optimum front in past generations is saved in form of trajectories. The final state of the neurons determines a set of new solutions that can be regarded as the probability density distribution function of the high fitness areas in the multi-objective space. The new set of solutions potentially can improve the GAs overall efficiency. In the last section of this paper, the applicability of the proposed algorithm is examined in developing optimal policies for a real world multi-objective multi-reservoir system which is a non-linear, non-convex, multi-objective optimization problem.     

A generalization of ACP using Belnap’s logic

ACP is combined with Belnap’s four-valued logic via conditional composition (if–then–else). We show that the operators of ACP can be seen as instances of more general, conditional operators. For example, both the choice operator + and δ (deadlock) can be seen as instances of conditional composition, and the axiom x + δ = x follows from this perspective. Parallel composition is generalized to the binary conditional merge _ψ where covers the choice between interleaving and synchronization, and ψ determines the order of execution. The instance _BB is ACP’s parallel composition, where B (both) is the truth value that models both true and false in Belnap’s logic. Other instances of this conditional merge are sequential composition, pure interleaving and synchronous merge. We investigate the expression of scheduling strategies in the conditions of the conditional merge.     

Suslin’s algorithms for reduction of unimodular rows

A well-known lemma of Suslin says that for a commutative ring $A$ if $(v_1\left(X\right),\dots ,v_n\left(X\right))\in {\left(A\left[X\right]\right)}^n$ is unimodular where $v_1$ is monic and $n\ge 3$, then there exist ${\gamma }_1,\dots ,{\gamma }_{\ell }\in E_{n-1}\left(A\left[X\right]\right)$ such that the ideal generated by $\mathrm{Res}(v_1,e_1.{\gamma }_1{}^t(v_2,\dots ,v_n)),\dots ,\mathrm{Res}(v_1,e_1.{\gamma }_{\ell }{}^t(v_2,\dots ,v_n))$ equals $A$. This lemma played a central role in the resolution of Serre’s Conjecture. In the case where $A$ contains a set $E$ of cardinality greater than $deg{v}_1+1$ such that $y-y^{\prime }$ is invertible for each $y\ne y^{\prime }$ in $E$, we prove that the ${\gamma }_i$ can simply correspond to the elementary operations $L_1\to L_1+y_i{\sum }_{j=2}^{n-1}{u}_{j+1}{L}_j$, $1\le i\le \ell =deg{v}_1+1$, where $u_1{v}_1+\cdots +u_n{v}_n=1$. These efficient elementary operations enable us to give new and simple algorithms for reducing unimodular rows with entries in $K[X_1,\dots ,X_k]$ to ${}^t(1,0,\dots ,0)$ using elementary operations in the case where $K$ is an infinite field. Another feature of this paper is that it shows that the concrete local–global principles can produce competitive complexity bounds.     

Nonlinear observer design using Lyapunov’s auxiliary theorem

The present work proposes a new approach to the nonlinear observer design problem. Based on the early ideas that influenced the development of the linear Luenberger observer theory, the proposed approach develops a nonlinear analogue. The formulation of the observer design problem is realized via a system of singular first-order linear PDEs, and a rather general set of necessary and sufficient conditions for solvability is derived by using Lyapunov’s auxiliary theorem. The solution to the above system of PDEs is locally analytic and this enables the development of a series solution method, that is easily programmable with the aid of a symbolic software package.